Fungal laccase research in the 21st century: a critical holistic view on soil ecological studies

Von der Fakultät für Biowissenschaften, Pharmazie und Psychologie der Universität Leipzig

genehmigte

D I S S E R T A T I O N

zur Erlangung des akademischen Grades

Doctor rerum naturalium (Dr. rer. nat.)

vorgelegt von

Diplom-Biologin Susanne Theuerl geboren am 17.08.1978 in Schwedt/Oder

Dekan: Prof. Dr. Matthias Müller Gutachter: 1. Prof. Dr. François Buscot (Leipzig/Halle)

2. Prof. Dr. Gerhard Rambold (Bayreuth) Tag der öffentlichen Verteidigung: 17.08.2010

„Das schönste Glück des denkenden Menschen ist, das Erforschliche erforscht zu haben und das Unerforschliche ruhig zu verehren.“

J.W. von Goethe – Naturwissenschaftliche Schriften

Table of content

Table of content I

List of Tables V

List of Figures VI

Bibliographic description X

Introduction - Fungal laccase research in the 21st century: a critical holistic view

on soil ecology 1-12

1. The consideration of soil microbes 1

2. The history and consideration of fungi 1

3. The fungal-mediated decomposition of recalictrant substances 2

4. Fungal laccases and molecular soil ecology 4

5. Conception and objectives of the thesis 6

References 9-12

Chapter I: Laccases: toward disentangling their diversity and functions in

relation to soil organic matter cycling 13-39

Abstract 14

1. Introduction 15

2. The ecological importance of decomposition in soil 16

3. Lignin as key recalcitrant polmer in soils 18

4. Enzymatic characteristics of laccases and biodegradation of

recalcitrant compunds 18

5. Role of laccases in decomposition of recalcitrant plant compounds 20

6. Suitability of the laccase genes for ecological studies and first

inverstigations on soil fungi 21

7. Spatial distribution and transcription profiles of soil fungal laccase genes 22

8. Temporal distribution and expression profiles of soil fungal laccase genes 23

9. Involvement of non-fungal microorganisms in the laccase activity in soils 24

I

10. Influence of the environment on the soil laccase activity and on related

microorganisms 25

11. Conclusions and perspectives 26

Acknowledgments 28

References 29-39

Chapter II: Response of recalcitrant soil substances to reduced N deposition

in a spruce forest soil: integrating laccase encoding genes and lignin

decomposition 40-65

Abstract 41

1. Introduction 42

2. Materials and methods 44-48

2.1. Experimental site and sampling 44

2.2. Analysis of basic soil paprameters 45

2.3. Lignin analysis 46

2.4. Measurement of fungal phenol oxidase activity 46

2.5. DNA isolation from soil samples, PCR amplification, cloning

and sequencing 47

2.6. Sequence and data analysis 47

3. Results 48-54

3.1. Soil chemical properties 48

3.2. Lignin and phenolic compound 50

3.3. Fungal phenol oxidase activity 51

3.4. Diversity and distribution of the laccase gene sequences 52

3.5. Treatment effect on the laccase gene diversity 54

4. Discussion 54-58

Acknowledgments 58

References 59-65

II

Chapter III: Towards a universally adaptable method for quantitative

extraction of high-purity nucleic acids from soil 66-83

Abstract 67

1. Introduction 68

2. Materials and methods 68-72

2.1. Experimental site and sampling 68

2.2. Nucleic acid extraction 69

2.2.1. Preliminary studies 69

2.2.2. Determination of the required Al2(SO4)3 quantity 70

2.2.3. Extraction protocol 70

2.2.4. Separation of DNA and RNA 72

2.3. Additional extraction protocols tested 72

2.4. Quality and quantity of nucleic acid extracts 72

3. Results 73-75

4. Discussion 76-80

4.1. Extraction of nucleic acids from soil 76

4.2. Nucleic acid extraction protocol 77

4.3. Reliability of data 78

4.4. Layout for quantitative studies 79

Acknowledgements 80

References 81-83

Chapter IV: The phylogenetic resolving potential of laccase encoding gene

fragments frequently employed in soil molecular ecological studies 84-113

Abstract 84

1. Introduction 85

2. Data collection 89-95

2.1. Definition of the laccase encoding gene dataset 89

2.2. Definition of the laccase protein dataset 91

III

IV

2.3. Estimation of evolutionary models and sequence phylogeny 91

3. What can the commonly applied laccase encoding gene fragment tell us? 95

4. Is there a lack of phylogenetic resolution? 99

5. Conclusions 103

Acknowledgements 104

References 105-113

Summary: Recent fungal laccase research and future challenges 114-118

Zusammenfassung 119-123

Cooperations 124

Acknowledgement 125

Curriculum vitae 126

List of publications 127

Conference proceedings 128

Statutory declaration 129

Eidesstattliche Erklärung 130

Appendix

List of Tables

Table 3.1: Basic physicochemical soil parameters from the Dystric Cambisol at Solling,

central Germany for the plots D1, D2 and D0 within a soil profile. Results are

given as arithmetic means and standard errors. 49

Table 3.2: Diversity of the detected basidiomyceteous laccase OTU types of the analyzed

plots (D1, D2 and D0) and horizons (Oe, Oa, A and Bw) of the Dystric

Cambisol from both sampling dates. For each plot and horizon the number of

detected laccase gene types from four subplots were pooled together. The

diversity was analyzed by the richness (S), the Shannon index (H) and the

eveness (E). 53

Table 4.1: Absorbance ratios and nucleic acid concentration of extracts from the two soil

horizons and the two litter layers, applying increasing Al2(SO4)3

concentrations. 74

Table 5.1: Summary of available studies on molecular ecological laccase research

including the research objectives, applied methods, phylogenetic analyses and

results. 86-87

Table 5.2: Analysed fungal fruiting bodies used in this study, their order, trophic state,

main characteristicts of the sequences and the corresponding accession

numbers. 90

Table 5.3: Fungal taxa (and/or strains) examined in the study, their trophic state and their

corresponding full length laccase protein sequences with database accession

numbers. 92-93

Table 5.4: Results of simple heuristic maximum-parsimony analyses of the four datasets

presented in this study. 95

V

List of Figures

Figure 1.1: Spruce branch with cones (A), the structure of cellusose fibres ambedded in

matrix of hemicellulos and lignin (B) and the chemical structure of the spruce

lignin molecule from Kögel-Knabner, 2002 (C). 2

Figure 1.2: Three-dimensional protein structure of the laccase from Trametes versicolor

(left) and the biocatalytic reaction of laccase (modified from Baldrian, 2006

and Wong, 2008). 3

Figure 1.3: Experimental site of the 'Solling roof project' established in 1989 in Norway

spruce plantation. It consists of four plots (A); three of them (D1, D2, D3) are

covered with a translucent roof (B, C). D0 is the unroofed 'Ambient plot'

exposed to natural conditions to assess a roof effect. D1) is the 'Clean Rain

plot' where pre-industrial conditions are simulated. D2 is the 'Control plot'

exposed to natural atmospheric deposition. D3 is the 'Drought/Rewetting plot'

simulating strong drought event with subsequent intensive rewetting. 7

Figure 2.1: Degradation of organic material, the underlying mechanisms including the

chemical changes during the turnover with special emphasis of the

decompostion of recalcitrant plant compounds as the bottleneck in relation to

the involved organisms and the influence on the balance between soils as sink

or source of carbon dioxide. 17

Figure 2.2: Decomposition of organic matter as a process based link between ecosystem

biodiversity and ecosystem functionality emphasising the importance of the

laccase approach. Suitability of commonly used molecular biological and

enzymological techniques for tracing the microbial diversity (genetic

potential and functionality) and the activity in natural environments. 26

Figure 3.1: Total phenolic compounds (A) and VSC lignin (B) (V = vanillyl, S = syringyl

and C = cinnamyl phenols) from the first sampling date (April 2006) of the

three analyzed plots (D1, D2 and D0) and the five soil horizons (Oi, Oe, Oa,

A and Bw) of the Dystric Cambisol from Solling (Lower Saxony, Germany).

The values represent the arithmetic means (bars) and standard errors (error

bars) of four field replications. Columns marked with the same lower-case

letter are not significant different. 50

VI

Figure 3.2: Changes of acid-to-aldehyde ratio of vanillyl units [(ac/al)V] (squares and

dotted lines) with soil depth of the Dystric Cambisol from the first sampling

date (April 2006) of the three plots D1 (black), D2 (dark grey) and D0 (grey).

The values represent the arithmetic means and standard errors of four field

replications. 51

Figure 3.3: Relation between syringyl-to-vanillyl (S/V) and cinnamyl-to-vanillyl (C/V)

ratios in the Dystric Cambisol from the first sampling date (April 2006) of the

three analyzed plots D1 (black), D2 (dark grey) and D0 (grey). The values of

the two calculated parameters represent the arithmetic means and standard

errors of four field replications. 51

Figure 3.4: Phenol oxidase activities from April 2006 (A) and October 2006 (B) of the

three analyzed plots (D1, D2 and D0) and the four soil horizons (Oe, Oa, A

and Bw) of the Dystric Cambisol. The values represent as arithmetic means

(bars) and standard errors (error bars) of four field replications, which are the

mean of three laboratory replications. Columns marked with the same lower-

case letter are not significant different. 52

Figure 3.5: Relative frequency distribution of the detected basidiomycetous laccase

OTUs of the analyzed plots (D1, D2 and D0) and horizons (Oe, Oa, A and

Bw) of the Dystric Cambisol from April 2006 (A) and October 2006 (B).

Each colour symbolizes one detected laccase type. 53

Figure 3.6: Principle component analysis (PCA) showing effects of the detected laccase

OTU diversity of the tree analyzed plots D1 (black), D2 (dark grey) and D0

(grey) of the Dystric Cambisol from the first (A) and second (B) sampling

date. 54

Figure 4.1: A260/230 ratio of nucleic acid extracts obtained using different extraction

methods. 75

Figure 4.2: Absorbance spectra of nucleic acid extracts obtained applying different

protocols, exemplified for samples of the litter layer Oh. The here presented

protocol (Al-method) was comparatively analyzed to purification of a crude

extract using PVPP (both scaled on left y-axis), the Fast DNA Spin Kit for

Soil (Q-Biogene), and the protocols of Griffiths et al. (2000) and Hurt et al.

(2001), the values for which refer to the right y axis. The absorbance spectra

of pure humic acids (Roth) in water (1 mg/ml, scaled on the right y-axis) and

VII

pure nucleic acids (0.1 mg/ml; DNA:RNA 2:1, scaled on the left y-axis) are

given for comparison. 75

Figure 4.3: Workflow fort the extraction of nucleic acids from soil. For detail see

text. 78

Figure 5.1: General arrangement of the laccase encoding gene structure including the

four conserved copper binding regions (cbr I - IV) and the approximated

length of the coding characters of the related fragments. For three of the four

copper binding regions different published primer combinations are given

considering the amino acid motifs they are deduced from, the corresponding

consensus degenerated nucleotide sequences and the resulting forward (FOR)

and reverse (REV) primer sequences. 88

Figure 5.2: Bayesian tree calculated from the coding region of the laccase encoding gene

fragment (A) and the corresponsing amino acid sequences (B) obtained from

soil samples as well as fungal fruiting bodies (Table 4.2) using the GTR

model for nucleotide sequenes or the WAG model for the amino acid

sequences. Nulcotide sequences are given with their Genbank accession

number, the corresponding protein ID (in brackets), a short name (Table 4.2)

and a putative gene name. Protein sequences are given with their Genbank

protein ID, the corresponding nucleotide accession number (in brackets), a

short name (Table 4.2) as well as a putative protein name. Discussed cases

were emphasized by boxes and labelled monophyletic clades of at least two

sequences with a clade symbol “/”. Branch support derived from Bayesian

posterior probabilities (PP) and bootstrap values (bsv) obtained from 1,000

pseudoreplicates of maximum-parsimony (MP) analyses. Non-supported

(n.s.) means monophyletic topology with less that 0.90 PP and less that 85%

MP-bsv. 96-97

Figure 5.3: Bayesian tree calculated from full length laccase protein sequences (A) and

the corresponding short length fragment (B) obtained from Genbank (NCBI)

using the WAG model for the amino acid sequences. Protein sequences are

given with their Genbank protein accession number, a short name (Table 4.3)

as well as the according protein name (if available). Discussed cases were

emphasized by boxes and labelled monophyletic clades of at least two

sequences with a clade symbol “/”. Branch support derived from Bayesian

VIII

IX

posterior probabilities (PP) and bootstrap values (bsv) obtained from 1,000

pseudoreplicates of maximum-parsimony (MP) analyses. Non-supported

(n.s.) means monophyletic topology with less that 0.90 PP and less that 85%

MP-bsv. 100-102

Figure S.1: Conceptual framework for the prospective microbial, particularly fungal

laccase research encompassing traditionally laboratory-based (orange) and

ecological (green) studies (modified from Fitter, 2005 and Ungerer et al.,

2008). In respect to the recent technical advances (e.g. whole genome

sequencing, genome-wide expression profiling or high-throughput

screening) the future challenge is to verify laccase genes encoding true

extracellular efficient exoenzymes and to understand their involvement in

the degradation of recalcitrant plant compound at different levels of

biological organisation using multidisciplinary approaches. The black

arrows indicate interactions and effects within and among different levels of

the organisation hierarchy. 118

Bibliographic description – Dissertation of Susanne Theuerl

Fungal laccase research in the 21st century: a critical holistic view

on soil ecological studies

Faculty of Life Science, Pharmacy and Psychology of the University of Leipzig

130 pages, 241 references, 7 tables, 18 figures

The here presented cumulative dissertation provides a critical, holistic view of the fungal

laccase research in the 21st century by invesitgating an environmental study considering the

response of lignin-decomposing fungi to reduced nitrogen (N) deposition and by critically

evaluating of the results.

Chapter I synthesize the results of previous and current studies considering ecological theories

that are responsible for the laccase-containing fungal community composition and their activity

according to the coexistence of species via niche separation, the nutritional pathways of fungi,

the microbial succession during litter decomposition or the degradation process as a function of

interactions among microorganisms.

Chapter II presents the mentioned environmental study and showed that the composition of

laccase encoding genes respond sensitive to various environmental factors in the organic soil

layer, although they is mainly affected by spatio-temporal substrate availability. In contrast, the

enzyme activities and the lignin decomposition process itself behave more conservative. Due

to the slow turnover rates of the spruce needles, at this point it is unratable whether the

reduction of N deposition leads to an accelerated or decelerated decay of soil organic

compounds in respect to the capacity of soils to act as sink for or source of carbon dioxide.

The Chapter III and IV are in the line of two previously reported methodological limitations:

(1) the extraction of nucleic acid at satisfactory purity and/or quantity from soil samples using

Al2(SO4)3 to remove humic substances prior to cell lysis (Chapter III) and (2) Considering that

the multigene character and related functional diversification of laccases complicates a

correlation between the presence of laccase genes and/or transcripts to effective enzyme

activities, comparative phylogenetic analyses of nucleotide and protein sequences to ascertain

that the commonly targeted laccase encoding gene fragment contains insufficient phylogenetic

information for reliably separating distinct clades in regard to a respective function of the

corresponding enzyme (Chapter IV).

X

Introduction

Introduction – Fungal laccase research in the 21st century: a critical

holistic view on soil ecology

1. The consideration of soil microorganisms

In autumn deciduous forests of temperate regions are characterized by coloured leaves

drifting down to the soil surface. This marks the starting point for many soil biotic

processes. Plant litter provides the primary nutrient and energy source for heterotrophic

microbes (bacteria and fungi) making nutrients available for the uptake by mycorrhizal

fungi and plant roots or immobilizing nutrients into microbial biomass or recalcitrant soil

organic matter (van der Heijden et al., 2008). Hence, soil microbes play an essential role in

ecosystems as they drive major biogeochemical processes and contribute the maintenance

of plant productivity and species richness (van der Heijden et al., 2008).

2. The history and consideration of fungi

Historically, the conquest of land by autotrophic plants revealed new habitats for

heterotrophic microorganisms coupled with the development of new survival strategies for

both plants and microbes. Colonization of terrestrial ecosystems by plants has probably

coincided with the occurrence of associated fungi (Brundrett, 2002). The plant-fungus-

association termed mycorrhiza by Frank (1885) is based on a mutual exchange whereby

the plant provides photoassimilates (fixed carbon) to the fungus and in turn receives soil-

derived nutrients. It is hypothized that the mycorrhiza has evolved from an initial

endophytic association with undifferentiated rhizomes to a balanced symbiosis in which

both the plant (photobiont) and the fungus (mycobiont) are optimally adjusted to each

other and to the soil habitat (Brundrett, 2002). Parallel with the belowground structural

formations, the aboveground plant organs (stems, branches and leaves) evolved new

structural compound for enabling vertical growth and for protecting against desiccation

and solar radiation (Hedges & Oades, 1997). This in turn provided new challenges for

decomposing microbes, especially for fungi as they developed new pathways to penetrate

into plant tissues and to degrade recalcitrant plant compounds. Deductively, fungi have

gained a pivotal role in ecosystem functioning as they capture two important niches in

terrestrial systems: the one of mycorrhizal formation and the one of decomposition of

recalcitrant plant compounds (see review from de Boer et al., 2005). Consequently,

1

Introduction

heterotrophic microbes (fungi and bacteria) have undergone niche differentiation related to

gradual changes in the chemical composition of plant residues and the relative proportions

of easily accessible and recalcitrant compounds during decomposition associated with a

succession of microbial communities.

3. The fungal-mediated decomposition of recalcitrant substances

Lignin, as the second most abundant biopolymer on earth (Kögel-Knabner, 2002), was

present in the oldest known plants and it is assumed that the structural rigidity that is

provided by the complex molecule structure (Figure 1.1) was a prerequisite for the

colonization of terrestrial environments (Ewank et al., 1996). Lignin is found in the plant

cell walls, where it is intimately interspersed with hemicellulose, forming a matrix that

surrounds the cellulose fibres (Kirk & Farrell, 1987). Biochemically, lignin consists of

phenylpropan units (mainly vanillyl (V), syringyl (S) and cinnamyl (C) alcohols) (Adler,

1977; Kögel-Knabner, 2002) varying between woody and non-woody tissues of

gymnosperms and angiosperms as well as non-vascular plant tissues (Hedges & Mann,

1979).

A

B

CA

B

C

Figure 1.1: Spruce branch with cones (A), the structure of cellulose fibres ambedded in matrix of hemicellulose and lignin (B) and the chemical structure of the spruce lignin molecule from Kögel-Knabner, 2002 (C).

The evolution of pathways for the degradation of recalcitrant substances such as lignin is

largely restricted to Asco- and in particular Basidiomycota, the two main phyla of

2

Introduction

Eumycota (real fungi) as they secrete extracellular enzymes mediating the gradual

oxidative break down of complex cross-linked molecules (Kirk & Farrell, 1987). In

particular, fungi play a crucial role in the initial stage of the lignin degradation (Kirk &

Farrell, 1987; Kjøller & Struwe, 2002) as they produce efficient acting enzymes such as

lignin peroxidase (LiP; EC 1.11.1.14), mangan peroxidase (MnP; EC 1.11.1.13), versatile

peroxidase (VP; EC 1.11.1.16) and especially laccase (EC 1.10.3.2). These individual

enzymes are components of an enzyme system (ligninolytic enzymes) that collectively

decomposes specific polymers such as lignin. Subsequently, multiple enzyme systems

(e.g., proteases, xylanases, cellulases, lignolytic enzymes) degrade synergistically the

matrix of polymers that constitute plant cell walls (Sinsabaugh et al., 2002). Due to the

compact structure of the plant cell wall and the necessity for the ligninolytic enzymes to be

in direct contact with its substrates, the existence of redox mediators is essential as they

can be oxidized by the enzymes and are able to migrate far away from the fungal mycelium

into the lignocellulose complex that is inaccessible to the enzymes themselves (Baldrian,

2006; Loenowicz et al., 2001; Martínez, 2002).

Of all ligninolytic exoenzymes, laccases are one of the most investigated enzymes related

to decomposition of recalcitrant plant compounds. Laccases (benzenediol:oxygen

oxidoreductase) senso stricto belong to the family of multicopper oxidases (MCO) using

the redox ability of four copper (Cu) ions to catalyze the oxidation of aromatic substrates

coupled with the reduction of molecular oxygen to water (Solomon et al., 1996; Thurston,

1994; Wong, 2008). The catalytic cycle of laccases is shown in Figure 1.2.

Cu2+ → Cu+

OH

R

OH

R

O

R

O

R

T1

T3

T2

T3

O2

2 H2O4 x

4 x

4e-4H+

4H+

4e-

phenolicsubstrate

phenoxyradical

laccase

Cu2+ → Cu+

OH

R

OH

R

O

R

O

R

T1

T3

T2

T3

O2

2 H2O4 x

4 x

4e-4H+

4H+

4e-

phenolicsubstrate

phenoxyradical

laccase

Cu2+ → Cu+

OH

R

OH

R

O

R

O

R

T1

T3

T2

T3

O2

2 H2O4 x

4 x

4e-4H+

4H+

4e-

phenolicsubstrate

phenoxyradical

laccase

Cu2+ → Cu+

OH

R

OH

R

O

R

O

R

T1

T3

T2

T3

O2

2 H2O4 x

4 x

4e-4H+

4H+

4e-

phenolicsubstrate

phenoxyradical

laccase

Figure 1.2: Three-dimensional protein structure of the laccase from Trametes versicolor (left) and the biocatalytic reaction of laccase (modified from Baldrian, 2006 and Wong, 2008).

3

Introduction

The Cu ion binding sites are of three different types (Solomon et al. 1996). In the native

enzyme all four Cu ions are in the 2+ oxidation state. The first step of biocatalytic reaction

is the oxidation of the substrate and the one-electron transfer to the Cu ion at the T1 site,

which is the primary electron acceptor. The native enzyme is successively fully reduced by

four single electron transfers of four substrates, whereby the electrons extracted from the

reducing substrate are transferred to the T2/T3 trinuclear site, where the reduction of

molecular oxygen to water occurs (see recent review from Giardina et al., 2010). Laccases

catalyze the substraction of one electron from the hydroxy group of the phenolic

compound resulting in the formation of phenoxy radicals which undergo further reactions

like polymerisation via radical coupling, aromatic ring cleavage, or breaking C-C bonds

(Wong, 2008).

4. Fungal laccases and molecular soil ecology

The fact that microbes mediate key steps of element cycles through their production of

particular enzymes encoded by functional genes enables to expand investigations of

biogeochemical processes to the enzymatic properties, the corresponding biochemical

pathways and the community of involved organisms (Leckie, 2005; Zak et al., 2006). In

this line, fungal laccases attracted the attention of ecologists studying the carbon cycling,

particularly the degradation of recalcitrant plant compounds (Baldrian, 2006).

Structural analyses of laccase protein sequences have shown that one cysteine and ten

histidine residues are involved in the binding of the four Cu ions which are spread over

four relative conserved amino acid regions within the enzyme sequence (Thurston, 1994;

Valderrama et al., 2003; Wong, 2008). While the copper binding regions (cbr) II and IV

are in line with earlier reported copper signature sequences of MCOs, cbr I and III are

distinctive to the laccases (Giardina et al., 2010). Deduced from the conserved amino acids

motifs different degenerated primer pairs were published during the last years particularly

for cbr I and II to detect the diversity and distribution of laccase gene containing microbes

(fungi and bacteria) in environmental samples (D´Souza et al., 1996; Luis et al., 2004;

Kellner et al., 2008). Genomic studies targeting functional genes can elucidate both the

genetic potential for enzyme production in soil microbial communities and the factors that

regulate the transcription of those genes which improve the accuracy of determining

microbial communities and their metabolic status in the environment (Liecke, 2005;

Nannipieri et al., 2003).

4

Introduction

Molecular ecological studies in a beech-oak forest soil have shown that the abundance and

distribution of saprotrophic and mycorrhizal basidiomycetes containing laccase genes

concomitant with the related laccase (phenol oxidase) activity is reflected by a pronounced

vertical stratification within the soil profile according to a decline in the suitability of

available organic energy sources (Luis et al., 2005). Additionally, in conjunction with the

high small scale physicochemical and biological heterogeneity of soils (e.g., see Nannipieri

et al., 2003; Šnajdr et al., 2008), the spatial (horizontal) distribution of fungal laccase

encoding genes demonstrated high dissimilarities between adjacent soil cores (e.g., 67 %

variety at 30 cm soil core distance; Luis et al., 2005). Besides these spatial diversifications,

temporal changes in the presence and expression of fungal laccase genes are greatly

affected by seasonal variations mirrored by a degradative microbial succession (early litter

colonization by ascomycetes followed by saprotrophic and mycorrhizal fungi) accordant

with the resource availability and the fungal nutritional pathways (Kellner et al., 2009).

Several studies realized in the last years in biogeochemical and microbial soil ecology

regarding the decomposition process of plant residues addressed the question whether

terrestrial ecosystems, especially forest soils act as an overall sink of or source for carbon

dioxide (CO2). In this case, comparative studies of different litter types revealed that the

amount and the biochemical composition of the available plant material deeply affect the

degradation process which determines variations in the enzyme activities (Sinsabaugh et

al., 2002) and differences in the abundance of basidiomycetous laccase encoding genes

(Blackwood et al., 2007) with higher values for putative slow-degradable litter types (e.g.,

oak) characterized by higher lignin and nitrogen (N) contents.

It should be noted that since the 19th century, elevated CO2 and N emission resulting from

human activities (industrialisation, fossil fuel combustion, deforestation, urbanization and

agriculture) increased the atmospheric CO2 concentration and N deposition drastically. It

can be assumed that this in turn disturbs biogeochemical cycling in a variety of ways by,

for example, affecting the productivity of terrestrial ecosystems, the turnover of soil

organic matter (SOM) by microbial, especially fungal communities due to changes in the

carbon-to-nitrogen ratio (C/N ratio) of the plant material or the rate of nutrient delivery to

soils as historically N-limited temperate forest ecosystems began to saturate when N input

exceeded the abiotic and biotic demand (Galloway et al., 2004; Keeler et al., 2009; Zak et

al., 2000). Consequently such environmental changes probably influence the function of

forest soils as sink for or source of CO2 (Sinsabaugh et al., 2005; Vitousek et al., 1997;

Weis et al., 2006; Zak et al., 2000). In this case previous studies reported that in organic

5

Introduction

soil horizons (Oi, Oe, Oa) effects of increased N deposition on the laccase encoding gene

abundance presumably depend on the ecosystem type and hence the level of substrate

recalcitrance (Blackwood et al., 2007). Moreover, in conjunction with enhanced or

repressed enzyme activities there is evidence that ecosystems with relatively labile litter

(e.g., dogwood, maple, basswood) respond to increased N deposition with accelerated

decay, while ecosystems with more recalcitrant litter (e.g., beech, oak) show decelerated

decay of soil substances (e.g., Carreiro et al., 2000; Knorr et al., 2005; Hofmockel et al.,

2007; Hassett et al., 2008).

Irrespective of the done analyses, a central discrepancy posed by almost all far-reaching

soil ecological studies is a clear relation of the measured phenol oxidase activity to the

presence (and expression) of laccase encoding genes. While consistent patterns between

enzyme activity and gene community structures were found within the soil profile

reflecting the proceeding biodegradation and the spatial separation of ecological guilds

(saprotrophs vs. mycorrhizas), shifts (mainly seasonal) in the community composition are

not systematically mirrored by changes in the phenol oxidase activity (Blackwood et al.,

2007; Hofmockel et al., 2007; Kellner et al., 2009). Such inconsistency may have several

causes, whereby, for example, the functional redundancy concept can be consulted

proposing that in the species-rich ecosystems such as soils various species or groups of

species (e.g., fungi and bacteria) can perform a given function (Kellner et al., 2008; Wohl

et al., 2004). A further important fact is substantiated in the multigene character of fungal

laccases represented by paralogous genes within the fungal genome (e.g., see Kilaru et al.,

2006; Courty et al., 2008) that reflects functional divergence (e.g., lignin decay, fruiting

body formation, pigmentation, pathogenesis or competitive interactions). In this context, it

is currently impossible to attribute laccase encoding genes (especially the commonly

applied gene fragment between the cbr I and II) to an effective extracellular decay activity,

although there are indications that the evolutionary relationship assessed by full length

laccase proteins sequences does not follow fungal systematics or ecological guilds, but

rather the respective functions of the isoenzymes (Hoegger et al., 2006).

5. Conception and objectives of this thesis

The presented thesis was performed in consideration of the above mentioned

circumstances. The work was financially supported by the German Research Foundation

(DFG - Deutsche Forschunsgemeinschaft, PAK 12, BU 941/9-1). The project aimed at

6

Introduction

outlining the contribution of soil microbes (bacteria and fungi) in the degradation cascade

of plant-derived compounds under changing environmental conditions, in particular under

manipulated nitrogen (N) deposition.

A long-term field experiment was conducted in a Norway spruce forest at Solling, Central

Germany (51° 31´N, 09° 34´E). The experimental site consists of four plots (each 300 m2);

three of them are covered with a roof construction (Figure 1.3; Bredemeier et al., 1995).

Since 1991 the entire throughfall water is permanently collected, filtered to remove the

organic debris and immediately resprinkled onto the plots either without deionization (D2 -

'Control plot': 34 ± 1 kg N ha-1 yr-1) or after partly deionization (D1 - 'Clean Rain plot':

11.5 kg N ha-1 yr-1). The 'Ambient plot' (D0) is exposed to recent throughfall conditions

with a mean N deposition of 33 ± 2 kg N ha-1 yr-1 (Corre & Lamersdorf, 2004).

Photo: H. Kellner 2006A from Bredemeier et al. 1995

SW

B

D2

D0 D3

D1

SW C Photo: H. Kellner 2006A from Bredemeier et al. 1995

SW

B from Bredemeier et al. 1995

SWSW

B

D2

D0 D3

D1

SW

D2

D0 D3

D1

SWSW C Figure 1.3: Experimental site of the 'Solling roof project' established in 1989 in Norway spruce plantation. It consists of four plots (A); three of them (D1, D2, D3) are covered with a translucent roof (B, C). D0 is the unroofed 'Ambient plot' exposed to natural conditions to assess a roof effect. D1 (C) is the 'Clean Rain plot' where pre-industrial conditions are simulated. D2 is the 'Control plot' exposed to natural atmospheric deposition. D3 is the 'Drought/Rewetting plot' simulating strong drought event with subsequent intensive rewetting.

The mentioned experimental circumstances were used to investigate an environmental

study concerning possible effects of reduced N deposition integrating basidiomycetous

laccase encoding genes and the corresponding phenol oxidase activity in relation with

lignin decomposition.

Defining the general framework of this study required an exhaustive evaluation of the

degradation process of recalcitrant plant residues attributed to the involved laccase-

producing soil microbes and laccase activity under different environmental conditions. On

that account Chapter I (“Laccases: toward disentangling their diversity and functions in

relation to soil organic matter cycling“) summarized and discussed previous classical

ecological, biogeochemical, enzymatic and molecular-biological studies.

7

Introduction

Based on valuable results derived from Chapter I we performed the abovementioned

environmental study (Chapter II - “Response of recalcitrant soil substances to reduced N

deposition in a spruce forest soil: integrating laccase encoding genes and lignin

decomposition”) assuming that the lignin decomposition, the related enzyme activity and

the diversity structure of basidiomycetous laccase encoding genes will be mainly affected

by ecological factors, e.g. the availability of substrates and energy sources along the soil

profile or possibly by the experimental design e.g. the roof constructions (changes in the

light or temperature regimes). We further questioned whether 14.5-years reduction of N

deposition affects the decomposition process of spruce-derived lignin compounds. In the

case that the overall process is affected, it can be expected that this response is also

reflected in the phenol oxidase activity as well as the diversity of laccase encoding genes.

Chapter III (“Towards a universally adaptable method for quantitative extraction of high-

purity nucleic acids from soil”) and IV (“The phylogenetic resolving potential of laccase

encoding gene fragments frequently employed in soil molecular ecological studies”) are in

the line of two previously reported methodological limitations: (1) In the course of the joint

research project we collaborated on a nucleic acid extraction method that provide nucleic

acids at satisfactory purity and/or quantity from soil samples, a basal problem in molecular

ecological studies (Chapter III). (2) In respect to the multigene character and related

functional diversification of laccases that complicates a clear correlation between the

presence of laccase genes and/or transcripts to effective enzyme activities, comparative

phylogenetic analyses of nucleotide and protein sequences were performed to ascertain the

phylogenetic information content of the commonly targeted laccase encoding gene

fragment between the cbr I and II for reliably separating distinct clades in regard to a

respective function of the corresponding enzyme (Chapter IV).

Finally, the summary presents a concluding view of the thesis and future challenges with

special emphasis on the detection of clearly verifiable extracellular laccases of ecological

important fungal taxa. The current fungal genome programmes (e.g., Fungal Genome

Initiative (FGI) - MIT and Harvard, Cambridge, MA, USA or DOE Joint Genome Institute

(JGI), Walnut Creek, CA, USA) and the continuous development of analytical tools

provide perspectives that certainly will precise our understanding of the degradation

process of recalcitrant plant compounds in conjunction with the diversity structure and

activity patterns of involved microorganisms, particularly soil fungi.

8

Introduction

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147: 201–22.

Chapter I: The holistic view of the laccase research

Chapter I: Laccases: toward disentangling their diversity and

functions in relation to soil organic matter cycling

Susanne Theuerl1,* and François Buscot1

1UFZ - Helmholtz Centre of Environmental Research, Department of Soil Ecology,

Theodor-Lieser-Strasse 4, 06120 Halle (Saale), Germany

*Corresponding author: Tel: +49 (0)345 558-5224, fax: +49 (0)345 558-5449

E-mail address: susanne.theuerl@googlemail.com

Biology and Fertility of Soils

Accepted

Date of acceptance: 05.01.2010

13

Chapter I: The holistic view of the laccase research

Abstract

Degradation of the recalcitrant polyphenolic plant residue lignin is a bottleneck of element

turnover in terrestrial ecosystems. Consequently, there is a great interest to understand

underlying mechanisms and dynamics, considering the possible ecological roles of soils as

sinks or sources of carbon dioxide.

The present review provides a critical, holistic view of the ecological importance of the

degradation of recalcitrant residues attributed to laccase-producing soil microbes and

laccase activity under different environmental conditions. We synthesize and discuss the

results of previous classical ecological, enzymatic and molecular-ecological studies to

point out discrepancies between gene detection, enzyme activity, and substrate

degradability. We single out major hindrances to current research and outline a progression

towards a better understanding of laccase activity by fungi in soil ecosystems.

14

Chapter I: The holistic view of the laccase research

1. Introduction

A central concern of soil ecology is to link the biotic diversity to biogeochemical processes

governing ecosystem functioning (Zak et al., 2003; Setälä & McLean, 2004;

Hättenschwiler et al., 2005). The decomposition of plant-derived organic compounds

represents a process of truly global importance (Paul & Clark, 1996; Sinsabaugh et al.,

2002a, 2008; Zak et al., 2006). The cycling of elements contained within the organic

material by heterotrophic soil microbes is an essential part of nutrient turnover and energy

transfer within terrestrial ecosystems (Prescott, 2005). This also directly relates to the

carbon dioxide (CO2) exchange between the soil and atmosphere and the built up of the

soil humic fractions (Swift et al., 1979). Initial biogeochemical investigations focused on

particular steps such as the wood-degradation by white-rot fungi, studying the involved

enzymes mainly on cultivable microorganisms (Zak et al., 2006). Biochemical,

physiological and especially molecular biological techniques now enable to assess and

compare in situ the diversity, composition, functioning, ecology and responses to

disturbance of soil microbial consortia within and among complex ecosystems such as

forests (Kirk et al., 2004; Leckie, 2005; Zak et al., 2006).

Recalcitrant plant compounds such as aromatic polymers represent a bottleneck for litter

decomposition (Berg & McClaugherty, 2003). Among the recalcitrant natural polymers,

lignin is the second most abundant component of plant litter (Kögel-Knabner, 2002; Wong,

2008). A large diversity of extracellular enzymes are involved in the degradation of such

plant residues, of which ligninolytic exoenzymes, namely lignin and mangan peroxidases

as well as laccases, are to date predominantly investigated (Allison et al., 2007). Due to

their comparable high redox potential ligninolytic peroxidases can directly attack aromatic

(preferentially phenolic) structures of the lignin molecule, whereby manganese peroxidases

are considered to be the most common lignin-modifying enzyme produced by almost all

wood-colonizing and litter-degrading basidiomycetes (Martinez et al., 2005: Steffen et al.,

2007; Valáŝková et al., 2007). In contrast, laccases have a lower redox potential and

therefore reduced direct ligninolytic efficiency, but their potential can be increased by

mediators and they are produced by a wide range of soil microorganisms, especially fungi

(Hatakka, 2001; Leonowicz et al., 2001; Baldrian, 2006).

Of all ligninolytic exoenzymes, laccases are the most suitable for far-reaching soil

molecular ecological studies. Besides their frequent occurrence in soil microorganisms, the

laccase encoding gene sequence enables designing primers compatible with a broad group

15

Chapter I: The holistic view of the laccase research

of taxa (see below). Therefore, laccase encoding genes were used as molecular markers in

a number of recent studies aimed at relating the structural and functional diversity of

especially soil fungi with potential to litter degradation and soil organic matter (SOM)

cycling under the influence of ecological or environmental variables. This article reviews

such studies to pinpoint encountered difficulties and to outline some perspectives. The

general line of the article is that the diversity pattern of fungal laccase genes and transcripts

in soil is highly variable in space and time and difficult to relate to exoenzyme activities

and plant litter decomposition. Further developments in molecular biological tools toward

more exhaustiveness and resolution will only partially help overcoming the difficulties.

The appropriate strategy especially in attempts of scaling up and bridging microbial

processes to the landscape and regional level is rather to cautiously select the right

microbial indicators even if they only represent a part of the total community.

2. The ecological importance of decomposition in soil

Integrating both processes of mineralization and soil organic matter formation, Satchell

(1974) defines “decomposition” as the breakdown of gross plant cell structures into

constitute elements and the mechanical disintegration to the humus stage. Accordingly,

decomposition is a complex suite of biotic and abiotic processes and constitutes the

principal pathway for the return of nutrients to soil (Berg, 2000; Berg & McClaugherty,

2003; Prescott, 2005). This is of crucial importance for plant productivity (Couteaux et al.,

1995) as the amount of essential nutrients entering an ecosystem each year is generally

limited (Gartner & Cardon, 2004). Degradation of plant material is influenced by a variety

of factors including the prevailing physicochemical soil condition (e.g., soil texture, pH or

redox potential), climate (temperature, precipitation, and moisture), amount and

biochemical nature of the entering litter as well as the composition, interactions and

production of exoenzymes of the soil inhabiting biocoenosis (Melillo et al., 1982;

McGlaugherty et al., 1985; Nannipieri et al., 2003; Gartner & Cardon, 2004).

Plant biomass is complex and generally considered to consist of a mixture of labile (e.g.

sugars, starch, hemicellulose, and cellulose) and recalcitrant (e.g. lignin, suberin, and cutin)

compounds (Aneja et al., 2006). Upon death, plant material provides the primary energy

source for heterotrophic microbes and the primary substrate for SOM formation. The

chemical composition of plant material and the relative proportions of labile and

recalcitrant compounds change during decomposition (see Figure 2.1), which is associated

16

Chapter I: The holistic view of the laccase research

with a succession of microbial communities: r-strategists (synonymous terms:

opportunistic, zymogenic or copiotrophic microbes) dominating the early stages and are

later replaced by K-strategists (synonymous terms: persisting, autochthonous or

oligotrophic microbes) (Rosenbrock et al., 1995; Fontaine et al., 2003; Langer et al., 2004;

Osono, 2007; Blagodatskaya & Kuzyakov, 2008; Kubartová et al., 2008). During the early

phase easily accessible metabolites (e.g. sugar, starch, proteins, lipids, and cellulose) are

decomposed and the growth of ligninolytic microbes is restricted (Fontaine et al., 2003; Di

Nardo et al., 2004). As a result, the proportion of recalcitrant compounds such as lignin

increases in the remaining material, which tends to limit the decomposition rate (Paul &

Clark, 1996; Aneja et al., 2006). This scheme is most commonly observed in the field

although it has been proven that some fungi attack lignin faster than the rest of litter

(Valasková et al., 2007). After this first microbial decomposition stage and a mechanical

fragmentation of the plant material by the soil macro- and mesofauna (resulting in an

increased contact surface), a second group of soil microorganisms in terms of autochtonous

soil fungi and bacteria with a wide range of physiological properties have the potential to

attack recalcitrant residues (Paul & Clark, 1996; Hättenschwiler et al., 2005).

Figure 2.1: Degradation of organic material, the underlying mechanisms including the chemical changes during the turnover with special emphasis of the decompostion of recalcitrant plant compounds as the bottleneck in relation to the involved organisms and the influence on the balance between soils as sink or source of carbon dioxide.

17

Chapter I: The holistic view of the laccase research

3. Lignin as key recalcitrant polymer in soils

Lignin (from the Latin term lignum = wood) is a main source of aromatic polymers in

nature (Kögel-Knabner, 2002; Wong, 2008). It polymerizes in the cell walls of vascular

plants, ferns and club mosses, where it is intimately interspersed with hemicellulose,

thereby forming a matrix that surrounds cellulose microfibrils (Kirk & Farrell, 1987).

Biochemically, lignin is a high molecular mass, three-dimensional macromolecule

synthesized from phenyl propane units (mainly vanillyl, syringyl and cinnamyl alcohols)

mainly linked by arylglycerol-β-aryl-ether bonds (Adler, 1977; Kögel-Knabner, 2002). The

proportion between the three phenylpropanoid units varies between woody and non-woody

(leaves and needles) tissues of gymnosperms and angiosperms as well as non-vascular

plant tissues (Hedges & Mann, 1979).

Lignin mineralization involves two sequential processes: (a) the primary attack and

breakdown of aromatic polymers to oligo- or monomers and (b) the complete degradation

of these products to CO2, H2O and minerals (Talbot et al., 2008). Due to its complex cross-

linked structure, lignin is highly refractory and resistant to chemical and biological

degradation (Martinez et al., 2005). After the primary attack it undergoes a gradual

oxidative degradation or re-polymerizes in humic compounds (Kirk & Farrell, 1987;

Grandy & Neff, 2008). Among the soil fungi, especially basidiomycetes are involved in

lignin decomposition (Kirk & Farrell, 1987; Kjøller & Struwe, 2002) as they possess the

ability to enzymatically degrade or modify lignin (Martinez et al., 2005). While brown-rot

and soft-rot fungi often considered to only modify the lignin polymer (with some exception

for brown-rot fungi; see review from Baldrian & Valáŝková, 2008), ligninolytic fungi are

able to completely decompose lignin to CO2 (Kirk & Farrell, 1987; Kögel-Knabner, 2002)

because they are efficient producers of ligninolytic enzymes, especially of laccases.

4. Enzymatic characteristics of laccases and biodegradation of recalcitrant

compounds

The fungal genome contains genes encoding several classes of extracellular enzymes that

oxidatively cleave the phenylpropane units by breaking the ether crosslinks. Thereby,

methoxylic groups are demethylated into phenols, aldehydes are oxidized into acids, and

aromatic rings within the lignin structure are cleaved (Kirk & Farrell, 1987; Martínez et al.,

2005). The major enzymes involved in lignin degradation/modification are lignin

18

Chapter I: The holistic view of the laccase research

peroxidase (LiP; EC 1.11.1.14), manganese peroxidase (MnP; EC 1.11.1.13), versatile

peroxidase (VP; EC 1.11.1.16) and laccase (EC 1.10.3.2). The catalytic properties of the

ligninolytic peroxidases are characterized by the hydrogen peroxide (H2O2) activation of

the native enzyme and the related oxidation of high redox-potential aromatic compounds.

LiP degrades non-phenolic (up to 90% of the polymer), whereas MnP generates Mn3+,

which acts on a variety of phenolic or non-phenolic lignin units. The third type of

lignolytic peroxidases, VP, combines the catalytic properties of LiP and MnP. It is able to

oxidize Mn2+ to Mn3+ as well as phenolic and non-phenolic compounds (Martínez et al.,

2005; Wong, 2008).

Besides the three ligninolytic peroxidases, laccases are the most investigated enzymes

involved in decomposition of recalcitrant plant compounds. Laccases were firstly found in

the Japanese lacquer tree Rhus vernicifera (Yoshida, 1883), shortly later in fungi (Bertrand,

1896) and in the meantime they were detected in the majority of organisms (plants, fungi,

bacteria and insects), in which they fulfil various functions (Hoegger et al., 2006).

Numerous authors reported fungi to represent the most important group of laccase-

producing organisms and emphasised their capability to modify plant-derived lignin (as

reviewed by Leonowicz et al., 2001 and Baldrian, 2006). Beside this impact on

delignification, fungal laccases are involved in various processes including competitive

interactions (Iakovlev & Stenlid, 2000), pathogenesis (Nosanchuk & Casadevall, 2003),

fruiting body formation (Kües & Liu, 2000; Wösten & Wessel, 2006), pigment formation

during asexual development (Tsai et al., 1999), and degradation of other SOM compounds

as well as formation of the humic fraction (Burke & Cairney, 2002; Luis et al., 2004).

Biochemically, laccases (benzenediol:oxygen oxidoreductase) sensu stricto belong to

oxidoreductases acting on diphenols and related substances (according to NC-IUBMB;

Nomenclature Committee of the International Union of Biochemistry and Molecular

Biology). Due to their catalytic properties which are related to four copper (Cu) atoms

bound to active sites (Solomon et al., 1996), laccases belong to the family of multi-copper

oxidases. They catalyze the reduction of molecular oxygen (O2) to water (H2O) concurrent

to the oxidation of a substrate (e.g. mono-, di- and polyphenols, aminophenols,

methoxyphenols or aromatic amins) resulting in the formation of phenoxy radicals which

undergo further reactions like polymerisation via radical coupling, aromatic ring cleavage,

or breaking C-C bonds (Thurston, 1994; Wong, 2008). Considering that laccases have low

redox potential compared to the ligninolytic peroxidases, they act on the initial

19

Chapter I: The holistic view of the laccase research

oxidation/cleavage of phenolic lignin units that often comprise less than 10 % of the total

polymer (Martinez et al., 2005).

To be efficient, the laccase enzyme must be in direct contact with their substrate molecules,

which can be hampered by the compact structure of plant cell walls in the case of lignin

and also by the enzyme size. However, a large number of low molecular weight

compounds exists that can be oxidized by laccases to stable radicals which in turn act as

redox mediators for substrate oxidation. These mediators can be derived from oxidized

lignin units (external) or directly from fungal metabolism (internal) and are able to migrate

far away from the fungal mycelium into the tight lignocellulose complex that is

inaccessible to the laccase itself (Leonowicz et al., 2001; Baldrian, 2006).

5. Role of laccases in decomposition of recalcitrant plant compounds

Initial research on laccase functioning was performed in the frame of investigations on

white-rot fungi and their wood decaying capabilities, demonstrating the involvement of

laccases sensu stricto (as reviewed by Leonowicz et al., 2001). Over the last years, the

focus shifted to studies on the occurrence and functions of laccases in different

compartments of the soil ecosystem e.g. plant litter, forest floors and mineral soils. Several

studies focused on the degradation of individual or mixed plant litter using the litter-bag

method, which led to better understand the mechanisms and factors influencing plant litter

decay (as reviewed by Gartner & Cardon, 2004). Generally, increased phenol oxidase

(laccase) activity was observed during later stages of decomposition characterized by an

enrichment of recalcitrant compounds in the SOM and an increased fungal biomass

(Fioretto et al., 2000; Sinsabaugh et al., 2002b; Di Nardo et al., 2004). However,

comparisons of the decomposability of coniferous and deciduous litter types did not only

reveal a negative relationship between lignin content and decomposition rate, but also the

influence of the nitrogen (N) concentration in the plant material (Berg & Meentemeyer,

2002). For example, needles of Scots pine (Pinus sylvestris) and leaves of trembling aspen

(Populus tremuloides) or flowering dogwood (Cornus florida) characterized by low lignin

and N contents constitute fast-degradable litter types with higher mass loss rates and

required lower enzyme activity, especially phenol oxidase activity for decomposition than

needles of silver fir (Abies alba) and leaves of common beech (Fagus sylvatica), red maple

(Acer rubrum) or red oak (Quercus borealis), which have higher lignin and N contents

(Carreiro et al., 2000; Berg & Meentemeyer, 2002; Sinsabaugh et al., 2002a).

20

Chapter I: The holistic view of the laccase research

Similar observations were made in studies on forest floors (organic layers) and in mineral

soils of different forest types where significantly higher phenol oxidase activity was

detemined for an oak forest (Quercus velutina, Quercus rubra) as compared to a maple-

basswood forest (Acer saccharum, Tilia americana) (Gallo et al., 2004; Sinsabaugh et al.,

2005). This suggests that the type of the organic substances influences the soil microbial

enzyme activity to degrade lignin and phenolic compounds, which in turn affects the

carbon (C) storage, SOM formation and release of nutrients from litter.

Irrespective of the litter type, several studies showed significantly higher phenol oxidase

activity in soil organic layers (forest floor) with high contents of recalcitrant plant

compounds than in mineral soil (Gallo et al., 2004; Luis et al., 2005b; Sinsabaugh et al.,

2005; Finzi et al., 2006; Šnajdr et al., 2008). Depth gradients in enzyme activity are related

to changes in biomass, abundance, composition and distribution of the microbial (fungal)

community (Fierer et al., 2003; O´Brien et al., 2005; Lindahl et al., 2007; Šnajdr et al.,

2008). From an ecological point of view this underlines the importance to link ecosystem

processes to the biotic, especially microbial diversity and their enzyme activity (Leckie,

2005; Nannipieri et al., 2003; Zak et al., 2006).

6. Suitability of the laccase genes for ecological studies and first

investigations on soil fungi

Due to their role in modifying plant-derived recalcitrant substances in soils (Baldrian,

2006), laccases that are mainly produced by fungi increasingly gained importance to

molecular ecological studies on soil carbon cycling (Luis et al., 2004, 2005b). To date

numerous gene and protein sequences of basidio- and ascomycetes have been characterized

(e.g. Valderrama et al., 2003; Hoegger et al., 2006; Kellner et al., 2007a), showing that

fungal laccase encoding genes frequently occur as multiple copies within the genome. For

example, the saprotrophic fungus Coprinus cinereus contains a total of 17 (Kilaru et al.,

2006) and the ectomycorrhizal fungus Laccaria bicolor 11 laccase genes (Courtry et al.,

2008).

The well conserved copper-binding amino acid sequence (one cysteine and ten histidin

residues) and their distribution within the protein sequence, enabled the design of

degenerated oligonucleotide primers to study laccase containing fungi in environmental

samples by polymerase chain reaction (PCR) (D´Souza et al., 1996; Luis et al., 2004,

2005a).

21

Chapter I: The holistic view of the laccase research

With such an approach Luis et al. (2004) determined the diversity and spatial distribution

of saprotrophic and mycorrhizal basidiomycetes within the soil profile of a mixed oak-

beech forest. In general, they found laccase producing fungi to preferentially colonize the

upper soil layers with high amounts of SOM (Luis et al., 2005b). Luis et al. (2004) also

found saprotrophic fungi to be less widespread than mycorrhizal ones within deeper soil

horizons. In a pine forest, Lindahl et al. (2007) confirmed that in accordance with their

nutritional pathways saprotrophic fungi were confined to the fresh and partially

decomposed surface litter, while mycorrhizal ones dominated in the well-degraded litter

and humus layers. The more widespread vertical occurrence of mycorrhizal fungi relies on

their ability to use photoassimilates from their host plants but also to acquire energy and

nutrients from the SOM saprotrophically by producing extracellular enzymes, thus

contributing to different parts of the soil carbon cycle, especially the influence of

mycorrhizal fungi in both input and loss of soil carbon from the environment (Cullings et

al., 2008; Cullings & Courty, 2009; Talbot et al., 2008). Despite some doubts on the

saprotrophic capacity of mycorrhizal fungi (Baldrian, 2009), it is assumed that they play a

significant role in mobilizing nitrogen compounds from organic matter, especially in

deeper parts of the soil profile (Lindahl et al., 2007).

7. Spatial distribution and transcription profiles of soil fungal laccase genes

Generally the diversity (richness, evenness and composition) of fungal laccase genes

changes significantly with soil depth. Evenness (relative contribution of an individual gene

sequence to the total number of detected genes) was found to display the best correlation

with SOM quantity (content) and quality (chemical composition) along soil profiles. As the

variations also parallel the laccase activity (Luis et al., 2005b), it is tempting to interpret

shifts in the vertical gene distribution as functional indications of the relative availability of

organic energy sources. However, the systematic validity of this interpretation is

challenged by studies on spatial distribution of fungal laccase genes, which stress the

complexity of soil ecosystems. Studying laccase encoding genes of basidiomycetes along a

three-directional transect in an oak-beech forest stand showed a high dissimilarity (67 %)

between soil cores collected at a distance of only 30 cm but also that soil cores can be

considered as independent samples regarding their gene population up to a core distance of

several meters (Luis et al., 2005b). This multi-scale heterogeneity in the gene distribution

reflects conjunction of the fractal growth pattern of fungal mycelium and the high small

22

Chapter I: The holistic view of the laccase research

scale heterogeneity of both physicochemical properties and biological soil characteristics

(e.g. microbial community composition) (Nannipieri et al., 2003; Gartner & Cardon, 2004;

Šnajdr et al., 2008).

Working at the gene level is not the most adequate to analyse spatial variations as gene

presence at a given time does not provide a related activity (Leckie, 2005). To circumvent

this bias, Luis et al. (2005a) studied variations of effectively expressed laccase genes by

semi-quantitative RT-PCR on mRNA extracts from different samples of the Oh horizon of

a forest soil. Compared to the laccase gene level, the authors found a lower diversity of

laccase transcripts (Luis et al., 2004) of which a high proportion was related to mycorrhizal

fungi. Additionally, a markedly high diversity of transcripts was found in samples with tree

rootlets indicating rhizospheric soil compartments (Luis et al., 2005a).

8. Temporal distribution and expression profiles of soil fungal laccase genes

Seasonal variations in climate (e.g., temperature and moisture) and resource availability

(litter input regime) are expected to affect microbial communities and their enzymatic

activity in temperate forest soils (Leckie, 2005). Over a time period of one year Kellner et

al. (2009) analyzed bimonthly the presence and expression of fungal laccase genes and the

phenol oxidase (laccase) activity in the organic soil layer (including the litter layer) of a

beech forest stand. They found distinct variations in the gene and transcript diversity

profiles and a great impact of the seasonal input of fresh litter (early colonization by

ascomycetes followed by saprotrophic and mycorrhizal fungi), which is consistent with

studies on microbial succession during plant litter degradation (Fontaine et al., 2003;

Koide et al., 2005; Aneja et al., 2006; Osono, 2007; Kubartová et al., 2008).

Despite high temporal variations in the diversity of laccase genes and transcripts, Kellner

et al. (2009) found a constant phenol oxidase (laccase) activity over the whole sampling

campaign. Such a discrepancy was also reported by others (Blackwood et al., 2007;

Hofmockel et al., 2007) and may have several causes. As mentioned the fungal genome

often comprises multiple copies of laccase genes and the number of which varies among

species (e.g. Kilaru et al., 2006; Kellner et al., 2007a; Courty et al., 2008), so that shifts in

fungal communities are not mirrored by proportional changes in the diversity of laccase

gene sequence types. In addition, some laccase genes do not encode oxidative exoenzymes

involved in litter decomposition, but may relate to other functions such as organismic

interactions and development processes as comprehensively reviewed by Burke & Cairney

23

Chapter I: The holistic view of the laccase research

(2002) and Hoegger et al. (2006). For example, differences in the biochemical properties

(redox potential) of laccase isoenzymes from Trametes sp. strain C30 (Klonowska et al.,

2002, 2005) or in the enzymatic characteristics (pI values and pH optimum) of laccase

isoenzymes from Trametes villosa (Yaver & Golightly 1996; Yaver et al., 1996) suggests

variabilities in the physiological roles or catalytic activities under different environmental

conditions. Furthermore, there are indications for various roles of laccase isoenzymes

during the lilecycle of a fungal organism (e.g., Pycnoporus cinnabarinus and Trametes sp.

I-62 (CECT 20197)) due to the induction or repression of laccase genes at different growth

levels (Mansur et al., 1998; Temp et al., 1999). Close laccase sequence similarities from

fungi occupying different ecological niches (litter decomposer: Agaricus bisporus,

Coprinopsis cinerea; wood decomposer: Pleurotus ostreatus, Pleurotus sajor-cuja; plant

pathogen: Rhizoctonia solani) may be based on shared function (e.g. developmental

processes) independend from the ecological relevance (Hoegger et al., 2006). Burns (1982)

as well as Nannipieri et al. (1990) further noted that enzyme analyses in environmental

samples may rather reflect the potential than the real in situ activities. Finally, the total

phenol oxidase (laccase) activity detected in a field may in part be due to soil inhabiting

microbial groups other than fungi.

9. Involvement of non-fungal microorganisms in the laccase activity in soils

Laccases or laccase-like multi-copper oxidases (LMCOs) were also reported in prokaryotes

(Claus, 2003). They have the potential to oxidize the naturally occurring laccase substrate

2,6-dimethoxyphenol (Solano et al., 2001; Kellner et al., 2008). Kellner et al. (2008)

investigated the diversity and distribution of bacterial LMCO encoding genes in two

different ecosystems (forest and grassland). In the forest ecosystem the bacterial LMCO

gene diversity was much higher than the one for basidiomycetes of the same plot by Luis et

al. (2005b). The effective involvement of prokaryotic LMCOs in SOM cycling is further

substantiated by the detection of high phenol oxidase activities in the grassland soils,

where no fungal laccase encoding genes were found (Kellner et al., 2008). These results

illustrate that metabolic processes in soils can be carried out by several microbial groups

indicating a complementary role of the occurring microbes. Only comprehensive

investigation of the entire soil inhabiting microbial community may potentially explain the

ecosystem functionality (Leckie, 2005; Zak et al., 2006).

24

Chapter I: The holistic view of the laccase research

10. Influence of the environment on the soil laccase activity and on related

microorganisms

In the past century industrialisation, fossil fuel combustion, deforestation, urbanization and

agriculture contributed to increase atmospheric CO2 concentration and N deposition, which

in turn enhanced the productivity of terrestrial ecosystems, the SOM turnover and the rate

of nutrient delivery to soils (Zak et al., 2000; Keeler et al., 2009). These environmental

changes may influence the function of forest soils as sink or source of CO2 (Vitousek et al.,

1997; Zak et al., 2000; Sinsabaugh et al., 2005; Weis et al., 2006).

In the last decade, the effect of N amendment in forests on decomposition of recalcitrant

plant compounds, microbial communities and enzyme activities was analysed (e.g.

Carreiro et al., 2000; Knorr et al., 2005; Hofmockel et al., 2007; Hassett et al., 2008).

Variable responses were found depending on physicochemical soil conditions, nutrient

supply, microbial community composition and content of recalcitrant materials in litter and

soil. In general, ecosystems with relatively fast-decomposable litter (dogwood, maple,

basswood) responded to increased N deposition with accelerated decay and increased

enzyme activities compared to ecosystems with more recalcitrant litter (beech, oak).

However, a recent study showed the response of enzyme activity to N addition to differ

more between distant sites with similar vegetation and litter chemistry than between

adjacent sites with different plant covers, indicating a prominent influence of the soil

ecological context (Keeler et al., 2009). The study also found a lack of general correlation

between litter decomposition and enzyme activity. These findings indicate that soil

conditions and/or soil inhabiting communities appear to differ sufficiently to cause

opposite responses to N addition in terms of enzyme activity (Keeler et al., 2009). In this

case, efforts to link the composition of microbial communities containing specific enzyme-

producing genes (e.g. laccases) and their enzymatic activities (e.g. phenol oxidase activity)

have thus far yielded only weak correlations. In organic soil horizons (Oi, Oe, Oa) the

ecosystem type and hence the level of substrate recalcitrance (Blackwood et al., 2007),

increased N deposition (Hofmockel et al., 2007) or the interaction between the ecosystem

stand and manipulated N deposition (Hassett et al., 2008) can significantly affect the

laccase encoding gene abundance. It also was shown that laccase encoding gene abundance

and its interaction with the ecosystem type significantly influence actual phenol oxidase

activity (Blackwood et al., 2007) that in turn can be affected by an ecosystem by N

deposition interaction (Hoffmockel et al., 2007). The phenol oxidase activity decreased

25

Chapter I: The holistic view of the laccase research

with increasing N deposition to a greater extent in ecosystems with higher litter lignin

content (oak) (Hofmockel et al., 2007). The response of microbe-mediated soil processes

to N amendment seemingly results in inconsistent patterns. This might be explainable by

interactions between litter chemistry and microbial guilds (Moorhead & Sinsabaugh, 2006)

due to the ability of species to exploit different resource niches (Hanson et al., 2008;

Allison et al., 2009). The underlying mechanisms are still insufficiently understood, nor

they are fully resolved. Further investigations in the context of system responses to

changing N regimes are essential to bridge the distinction between the abundance of

organisms with ligninolytic (laccase) genes, the related enzyme activity and the

decomposition process itself.

11. Conclusions and perspectives

Investigations on the biodiversity of heterotrophic microbial communities mediating

nutrient cycling allow establishing a process based link to the functionality of terrestrial

ecosystems (see Figure 2.2).

Figure 2.2: Decomposition of organic matter as a process based link between ecosystem biodiversity and ecosystem functionality emphasising the importance of the laccase approach. Suitability of commonly used molecular biological and enzymological techniques for tracing the microbial diversity (genetic potential and functionality) and the activity in natural environments.

26

Chapter I: The holistic view of the laccase research

Identifying soil microbes using functional marker genes such as laccases at best provides

indirect functional indication but does not allow conclusions on actual active functions in

the ecosystem. Several studies described the diversity, distribution and composition of soil

microbial communities harbouring laccase or LMCO genes (e.g. Luis et al., 2005a, b;

Kellner et al., 2008) and correlated them to ecological functions (e.g. saprotrophic vs.

mycorrhizal) and to hierarchical effects of environmental factors (e.g. Hofmockel et al.,

2007; Hassett et al., 2008, Kellner et al., 2009). General methodological limitations,

including nucleic acid extraction in satisfactory quality and quantity as well as PCR

efficiency fluctuations were comprehensively discussed in several publications (e.g.

Anderson & Cairney, 2004; Kirk et al., 2004; Leckie, 2005; Bakken & Frosegard, 2006,

Hasset et al., 2008; Persǒh et al., 2008). Though, in regards to laccase, two major

stumbling blocks may have hampered recent investigations: Firstly, it is difficult to design

efficient primers for defined taxonomic groups, especially for eukaryotic protein-encoding

sequences containing introns (Luis et al., 2004, 2005a; Hassett et al., 2008). This means

that likely not all laccases will be detected. Additionally, the lack of complete ORF

sequences of fungal laccases further complicates the design of primers able to detect

sequences clearly assignable to extracellular, ligninolytic enzymes. Amplifying a sequence

too short ultimately could lead to wrong conclusions, perhaps compounded by limitations

of phylogenetic inference based on a dataset of unreliable character homology. Regarding

that laccases or LMCOs are involved in a number of intra- and extracellular functions

(Hoegger et al., 2006), we may not be sure whether all sequences detected really encode

extracellular, ligninolytic enzymes.

The challenge at this point is to enlarge the proportion of detected, verifiably true

extracellular laccases by several means, in order to trace and quantify the activities of

especially fungi in terrestrial ecosystems. Therefore, in future two points have to be

considered: (1) Upcoming complete genome sequences of fungi (e.g. Fungal Genome

Initiative (FGI) of the Broad Institute of MIT and Harvard, Cambridge, MA or DOE Joint

Genome Institute (JGI), Walnut Creek, CA) hopefully will serve as a basis to screen

ecological relevant fungi for all potential laccases (e.g. see Courty et al., 2008). (2) There

is an urgent need to link the genetic potential for producing extracellular enzymes and to

study their expression under (i) laboratory and (ii) natural conditions. Such investigations

hopefully will lead to the design of additional primers that will gather a larger slice of

laccases from litter and soil microbial consortia. Additionally there is also a need to verify

the exoenzymes itself, under laboratory and environmental conditions where fungi are

27

Chapter I: The holistic view of the laccase research

actually confronted to lignin model substrates or litter cocktails (Wilmes & Bond, 2004;

Nannipieri, 2006). As such, a very comprehensive, iterative process is needed here. Of

course, this would also improve our understanding of other fungal enzymes that might also

be found to be present in such culture experiments. In the end, we may find that in the

studies so far, we may have gathered already valuable information on the laccase activities

under natural conditions, yet considering the rapid improvement of “omics” methods, there

is hope we can soon not only alleviate some doubts, and vastly expand our knowledge. In

regards to laccase genes directly in metagenomic libraries (e.g. see Daniel, 2005;

Schmeisser et al., 2007), it is still absolutely necessary to improve our ability to correctly

address them as extracellular, active ligninolytic laccase. The more we are able to work in

these cases, the better we can ultimately pull out the truly relevant genes and estimate their

responses to environmental conditions, e.g. by using specifically designed microarrays

(Gao et al., 2007; Yergeau et al., 2007) which should be the ultimate stepping stone

towards high-throughput, across-landscape analyses relevant for understanding element

cycling.

Acknowledgments

This work was financially supported by the German Research Foundation (DFG, PAK 12,

BU 941/9-1). We thank Christine Linck and Dr. Dirk Krüger for their help with editing the

manuscript.

28

Chapter I: The holistic view of the laccase research

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Chapter II: The field study

Chapter II: Response of recalcitrant soil substances to reduced N

deposition in a spruce forest soil: integrating laccase encoding genes

and lignin decomposition

Susanne Theuerl1#*, Nicole Dörr2,#, Georg Guggenberger2,, Uwe Langer4, Klaus

Kaiser3, Norbert Lamersdorf5, and François Buscot1

1 UFZ - Helmholtz Centre of Environmental Research, Department of Soil Ecology,

Theodor-Lieser-Strasse 4, 06120 Halle (Saale), Germany 2Institute of Soil Science, Leibniz University Hannover, Herrenhäuser Str. 2, 30419

Hannover, Germany

3Soil Sciences, Martin Luther University Halle-Wittenberg, Weidenplan 14, 06108 Halle

(Saale), Germany 4Landesamt für Umweltschutz Sachsen-Anhalt, Fachgebietsleiter Bodenschutz / Altlasten,

Reideburger Straße 47, 06116 Halle (Saale), Germany 5Soil Science of Temperate and Boreal Ecosystems, Büsgen-Institute, Georg August

University of Göttingen, Büsgenweg 2, 37077 Göttingen, Germany

#ST and ND contributed equally to this work.

*Corresponding author: Tel: +49 (0)345 558-5224, fax: +49 (0)345 558-5449

E-mail address: susanne.theuerl@googlemail.com

FEMS Microbiology Ecology

Accepted

Date of acceptance: 13.03.2010

40

Chapter II: The field study

Abstract

A long-term field experiment conducted in a Norway spruce forest at Solling, Central

Germany, was used to verify and compare the response of lignin-decomposing fungal

communities in soils receiving current and pre-industrial atmospheric N input for 14.5

years. Therefore, we investigated the decomposition of lignin compounds in relation to

phenol oxidase activity and the diversity of basidiomycetes containing laccase genes in

organic and mineral horizons.

Lignin-derived CuO oxidation products and enzyme activity decreased with soil depth

while the degree of oxidative transformation of lignin increased. These patterns did not

change with reduced atmospheric N input, likely reflecting a lasting saturation in available

N. The laccase gene diversity decreased with soil depth in spring. In autumn, this pattern

was only found at the control plot, receiving current N input. Principal component analysis

confirmed the depth profile and distinguished a response of the fungal community to

reduced N deposition for most organic layers in spring and a roof effect for the Oe layer in

autumn. These responses of the fungal community did not translate into changes in enzyme

activity and lignin content and decomposition, suggesting that transformation processes in

soils are well buffered despite the rapid response of the microbial community to

environmental factors.

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Chapter II: The field study

1. Introduction

A central concern in soil ecology is to link the biodiversity to biogeochemical processes

governing ecosystem functionality (Zak et al., 2003; Setälä & McLean 2004;

Hättenschwiler et al., 2005). The cycling of elements contained within the organic material

by heterotrophic microorganisms is of truly global importance for nutrient turnover and

energy transfer within terrestrial ecosystems (Paul & Clark, 1996; Sinsabaugh et al., 2002;

Zak et al., 2006). A bottleneck of element turnover is the degradation of recalcitrant plant

residues such as lignin (Berg & McClaugherty, 2003), the second most abundant

compound of plant biomass (Kögel-Knabner, 2002). Biochemically, lignin is a high

molecular mass, three-dimensional macromolecule and consists of phenylpropane units

(mainly vanillyl, syringyl and cinnamyl alcohols) in variable proportions specific to plant

groups (see Adler, 1977; Hedges & Mann, 1979; Kögel, 1986; Kögel-Knabner, 2002). Due

to its complex cross-linked structure and thus its high resistance against chemical and

biological decomposition (Hofrichter & Steinbüchel, 2001; Martinez et al., 2005), a large

diversity of extracellular enzymes are involved in the degradation, of which ligninolytic

exoenzymes, namely lignin and manganese peroxidases as well as laccases, are to date

predominantly investigated (Allison et al., 2007).

Among the diversity of soil microbes, especially basidiomycetous fungi are involved in

lignin decomposition (Kirk & Farrell, 1987; Kjøller & Struwe, 2002; Baldrian, 2006) as

their genomes contain genes encoding several classes of ligninolytic exoenzymes (Kirk &

Farrell, 1987). Of all ligninolytic exoenzymes, laccases are one of the best characterized

lignin-modifying exoenzyme groups (Hatakka, 2001). Laccases (EC 1.10.3.2;

benzenediol:oxygen oxidoreductase) sensu stricto catalyze the reduction of molecular

oxygen (O2) to water (H2O) concurrent to the one-electron oxidation of organic and

inorganic substrates (Thurston, 1994).

In regards to their role in modifying plant-derived recalcitrant substances and their frequent

occurrence in soil microbes, especially fungi, laccases increasingly gained scientific

importance for far-reaching soil ecological studies. Consequently, several studies aimed to

describe the diversity, distribution and composition of soil fungal communities harbouring

laccase encoding genes and correlated them for example to ecological functions (Luis et

al., 2004, 2005a; Kellner et al., 2009) or to changing environmental conditions (e.g.,

Hofmockel et al., 2007; Hassett et al., 2008).

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Chapter II: The field study

Along the soil profile of temperate forests, the laccase encoding gene diversity appeared to

correlate with the quantity (content) and quality (chemical composition) of soil organic

matter (SOM) and also to parallel with the laccase enzyme activity (Luis et al., 2005a). In

this case, the fungal community composition is in accordance to the commonly attributed

nutritional pathways of basidiomycetous fungi: saprotrophic fungi were confined to the

fresh, partially decomposed and energy-rich surface litter, while mycorrhizal taxa

dominated in the well-degraded humus layers and mineral soil horizons (Luis et al., 2004;

Lindahl et al., 2007) as they have the ability to use photoassimilates from their host plants

but also to acquire energy and nutrients from the SOM saprotrophically by producing

extracellular enzymes (e.g. see Talbot et al., 2008). Additionally, some studies described

seasonal variations in the fungal laccase gene and transcript diversity, but constant laccase

enzyme activity (Blackwood et al., 2007; Hofmockel et al., 2007; Kellner et al., 2009)

indicating that the enzyme activity is in part be due to other soil microbes than fungi, e.g.

bacteria (Kellner et al., 2008).

In the past century industrialization, fossil fuel combustions, agriculture, urbanization and

deforestation have increased the atmospheric nitrogen deposition into forest ecosystems,

which in turn influenced the productivity of terrestrial ecosystems, the SOM turnover and

the rate of nutrient delivery of soils (Zak et al., 2000; Weis et al., 2006; Keeler et al.,

2009). Concerning the effects of N input on the decomposition of recalcitrant plant

compounds, microbial communities and enzyme activities (e.g. Carreiro et al., 2000; Knorr

et al., 2005; Hofmockel et al., 2007; Hassett et al., 2008) a wide range of responses were

observed due to physico-chemical soil conditions, nutrient supply, microbial community

composition and to the amount and biochemical composition of the plant litter. In general,

these results suggest that ecosystems with relatively labile litter (e.g., dogwood, maple,

basswood) respond to increased N deposition with accelerated SOM decay due to

enhanced enzyme activities. Ecosystems with more recalcitrant litter (e.g., beech, oak)

show retarded decay of SOM in conjunction with repressed enzyme activities (e.g. see

Knorr et al., 2005).

In contrast to previous studies, the present work takes advantage of a long-term field

experiment where the N deposition was not increased, but rather reduced at one

experimental plot by collecting precipitation water on transparent plexi-glas roofs built

under the canopy and redistributing it after manipulating the element contents (Bredemeier

et al., 1998). Following the approach of Zak et al. (2006), our study combined chemical

43

Chapter II: The field study

and biological analyses to link decomposition patterns of lignin, activities of phenol

oxidases, and the diversity of laccase-containing basidiomycetes under current and reduced

atmospheric N deposition. We hypothesized that the lignin decomposition, the related

enzyme activity and the diversity structure of basidiomycetous laccase encoding genes will

be mainly affected by (a) ecological factors, e.g. the availability of substrates and energy

sources along the soil profile and (b) changing environmental conditions, especially

reduced atmospheric N deposition. Supplementary, due to the roof construction over two

of the analyzed plots (e.g. changes in the light or temperature regimes) we (c) assumed a

roof effect especially on the soil inhabiting microbial community.

2. Materials and methods

2.1. Experimental site and sampling

Soils were sampled at a experimental site near Göttingen (Lower Saxony, central

Germany), located on a mountain plateau of the Solling, at an elevation of about 500 m

above sea level (51° 31´N, 9° 34´E) (Bredemeier et al., 1998). The experimental site is

covered with a today (2010) 77-years old Norway spruce plantation. The climate is

temperate suboceanic, with moderate changes in temperature (MAT = 6.4°C) and a mean

annual precipitation of 1090 mm homogenously distributed over the year. The soils were

strongly acidic Dystric Cambisols (FAO, 1998), with the pH (CaCl2) ranging from 2.6 in

the Oa horizons to 4.1 in the Bw horizons. The mineral horizons were poor in

exchangeable alkali and earth alkali cations (Mg, Na, K, Ca) but high in exchangeable

acidity (Table 3.1).

In the present study we analyzed three experimental plots (D1, D2 and D0), each with an

area of 300 m2 (Bredemeier et al., 1995). The soil of each plot is separated from the

surrounding area by a vertical 1 m deep plastic foil (Xu et al., 1998). The plots D1 and D2

are covered with highly translucent polycarbonate roofs underneath the canopy, installed

approximately 3.5 m above the ground; D0 is an unroofed plot (Raubuch et al., 1999). D1

is a “Clean Rain” plot where pre-industrial atmospheric deposition is simulated since

September 1991 by permanent collection of the entire throughfall water, followed by

removal of contained organic debris, partly de-ionization and immediately resprinkled onto

the plot. The clean rain throughfall water contains 11.5 kg N ha-1 yr-1, which corresponds

44

Chapter II: The field study

to a 65% reduction compared to the actual total atmospheric N deposition (Corre &

Lamersdorf, 2004). On the ”Control” plot D2 with an atmospheric N deposition of 34 ± 1

kg N ha-1 yr-1, throughfall water is also collected but distributed onto the plot without

manipulation, except for removal of organic debris (Corre & Lamersdorf, 2004). D0 is the

“Ambient” plot exposed to natural conditions without roof and throughfall manipulation

(N input: 33 ± 2 kg N ha-1 yr-1) for assessing eventual roof effects (Bredemeier et al., 1998,

Corre & Lamersdorf, 2004).

In April 2006 and October 2006, three to five soil cores (8 cm in diameter) were taken

from four subplots on each plot. The cores were divided into three litter horizons (Oi, Oe,

Oa) and two mineral soil horizons (A, Bw). For each subplot, the sample replicates were

combined into a composite probe, mixed, and split in subsamples. Subsamples for basic

soil characterization and lignin analysis were air dried while subsamples for enzymatic and

molecular biological analyses were transported in liquid nitrogen and stored at –80°C.

2.2. Analysis of basic soil parameters

Air dried soil samples were used for analyzing basic chemical soil parameters. The soil

samples from the mineral horizons (A, Bw) were sieved to <2 mm. Soil pH was

determined potentiometrically in 0.01 M CaCl2 at a soil-to-solution ratio of 1:10 for the

organic soil samples (Oi, Oe, Oa) and of 1:2.5 for the mineral soil samples. Exchangeable

Mg, Na, K, and Ca were extracted into 1 M NH4Cl and analyzed by ICP-OES (JY-70plus;

Jobin-Yvon, Longjumeau, France); the exchangeable acidity was determined by

potentiometric titration. The amount of poorly crystalline Fe and Al hydrous oxides was

estimated by extraction with 0.2 M ammonium oxalate at pH 3 (Schwertmann, 1964);

extracted Fe and Al were determined by ICP-OES. Total C and N were determined on

ground samples with an elemental analyzer (Vario MAX, Elementar GmbH, Hanau,

Germany). All samples were free of carbonate, thus, C was entirely organic. Inorganic N

(NH4+ and NO3

-/NO2-) was determined on samples stored at –18°C by SPINMAS (Sample

Preparation unit for Inorganic Nitrogen coupled to a Mass Spectrometer) according to

Stange et al. (2007) after extraction with 1 M KCl (soil-to-solution ratio 1:10 for organic

horizons and 1:5 for mineral soils). The content of organic N was calculated by difference

between total and inorganic N.

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Chapter II: The field study

2.3. Lignin analysis

Soil samples were air dried (mineral soil samples were additionally sieved at 2 mm) and

ground. Lignin and its state of oxidative decomposition were analyzed by CuO oxidation

according to Hedges & Ertel (1982). The lignin-derived products released by CuO

oxidation are vanillyl (V), syringyl (S) and cinnamyl phenols (C). While vanillyl and

syringyl units comprise aldehydes, ketones and acids, cinnamyl units only occur as acids.

The sum of the three units (VSC) was used to estimate the lignin content of the analyzed

soil samples (Kögel, 1986) and normalized to the sample’s C content. In addition, the total

phenolic compounds (TPC) included other phenolic compounds released by alkaline CuO

oxidation like benzoic acids, benzaldehyde and acetophenone in addition to VSC.

The degree of oxidative degradation of the spruce lignin was estimated by the acid-to-

aldehyde ratio of vanillyl units [(ac/al)V]. Increasing oxidative degradation results in an

increasing [(ac/al)V] ratio. For further lignin characterization, syringyl-to-vanillyl (S/V)

and cinnamyl-to-vanillyl (C/V) ratios were calculated. While gymnosperm lignin contains

mainly vanillyl units, angiosperms contain about an equal proportion of syringyl and

vanillyl units. Furthermore, cinnamyl units are characteristic for non-woody lignin (Ertel &

Hedges, 1984). So, the S/V and C/V ratios were used for differentiation between

gymnosperm and angiosperms and woody and non-woody lignin, respectively. Treatment

differences between mean values of the functional parameters were evaluated by a one-

way analysis of variance (ANOVA), followed by the test of Least Significant Differences

(0.05) (SigmaStat 2.0, SPSS Inc., Chicago). Since the analysis of the CuO oxidation

products represent the stage of lignin decomposition in soil after several years (Oe horizon)

to several hundred years (mineral soil horizons), changes in lignin parameters from April

2006 to October 2006 are smaller than the analytical error of the method. Therefore, lignin

analysis was performed on the April 2006 samples only, because we postulate that the

quantity and quality of lignin and of its decomposition products in the Oe to Bw horizon

did not change markedly over such a short period (Koopmans et al., 1998).

2.4. Measurement of the fungal phenol oxidase activity

The activity of the fungal phenol oxidase, able to oxidize ABTS (2,2-azino-bis(3-

ethylbenzothiazoline-6-sulfonate)) (Sigma-Aldrich, Munich, Germany) as substrate (Mayer

46

Chapter II: The field study

& Staples, 2002, Floch et al., 2007), was determined for all soil samples as described in

Luis et al. (2005b). Results are presented as arithmetic means ± standard deviations (SD)

of four field replications (i.e., subplots), with three analytical replicates. Treatment

differences between means of parameters were evaluated by a one-way analysis of

variance (ANOVA), followed by the test of Least Significant Differences (0.05)

(SigmaStat 2.0, SPSS Inc., Chicago).

2.5. DNA isolation from soil samples, PCR amplification, cloning and sequencing

Genomic DNA was isolated either from 0.3 g (organic Oe and Oa horizons) or 0.5 g

(mineral A and Bw horizons) of soil using the FastDNA® SPIN Kit for soil (Q-BIOgene,

Heidelberg, Germany), using the protocol of Luis et al. (2004). Genomic DNA extracts

were used as templates in PCR amplification to characterize the diversity of basidiomycete

laccase genes from soil samples. Laccase gene fragments between the copper binding

regions cbrI and cbrII were amplified with the basidiomycete-specific primer pair Cu1F

(5´- CAY TGG CAY GGN TTY TTY CA -3´) and Cu2R (5´- G RCT GTG GTA CCA

GAA NGT NCC -3´) following the procedure proposed by Luis et al. (2004, 2005b). After

amplification, 7 µl of each product and 2 µl of a DNA ladder (GeneRuler® DNA Ladder

mix, Fermentas, St. Leon-Rot, Germany) were loaded onto a 2% agarose gel and

electrophoresed in TEA-buffer for 45 min at 80 V cm-1. The agarose gel was stained with

ethidium bromide. The DNA bands were visualized and photographed under UV light.

PCR products were cloned using the TOPO TA cloning® Kit for sequencing (Invitrogen,

Karlsruhe, Germany). Depending on the occurrence of introns in the amplified fragments,

the expected amplicon length ranges between 142 and 350 bp (Luis et al., 2004). Bacterial

clones containing inserts of expected sizes were selected for sequencing. Of each soil

sample, 30 to 40 clones were sequenced.

2.6. Sequence and data analysis

The detected nucleotide sequences were compared with the database of the National Centre

for Biotechnology Information (NCBI, GenBank) using the BLAST search algorithm

(Altschul et al., 1997). This comparison allowed for confirmation of clones to be related to

laccase sequences, and selection of reference sequences for phylogenetic analysis.

47

Chapter II: The field study

The ARB software (Ludwig et al., 2004) was used to align the gained sequences and those

available in GenBank for establishing a specific database for the present study. Different

laccase operational taxonomic units (OTUs) and their richness were determined from a

neighbour-joining (NJ) tree. All detected genes showing the same DNA sequence were set

as identical OTU.

Based on the sequence data, a quantitative matrix compiling the number of laccase OTUs

in each soil sample was built. The number of OTUs from the four subplots was pooled for

each plot and each soil horizon. Three variables of interest were calculated from the

quantitative matrix: the richness (S, total number of different laccase OTUs), the diversity,

as determined by the Shannon index (H), and the evenness (E). This matrix was used to

evaluate also the relative frequency distribution of the detected laccase OTUs. Treatment

differences between the three plots and the analyzed horizons were evaluated by one-way

analysis of variance (ANOVA). The quantitative matrix was used to perform a Jackknife

analysis for further statistical analysis, utilizing the program PC Ord for Microsoft

Windows version 4.37 (McCune et al., 1999). This program generated a saturation curve,

which was used to estimate the potential maximum number of different laccase OTUs in

the samples. Additional principal component analysis (PCA; Rosswall & Kvillner, 1978)

were performed with the software package SPSS 10.0 (SPSS Inc., Chicago, USA), as

described by McSpadden et al. (1997). PCA computes a compact and optimal description

of the data set. The data set was condensed into two principal components (PC 1 and PC

2). PC1 is the combination of variables that explains the greatest amount of variation and

PC2, which is independent of the first principal component, is the combination of variables

explaining the next largest amount of variation.

All new sequences found in this study were submitted to GenBank and are available under

accession numbers EU882599-EU882725.

3. Results

3.1. Soil chemical properties

The soil chemical parameters were common for Dystric Cambisols under forest vegetation,

showing typical gradients with depth (Table 3.1). The organic horizons (Oi, Oe, Oa) were

characterized by large organic C and organic N contents; the respective contents if the

48

Chapter II: The field study

49

plot

D1

D2

D0

horiz

onO

iO

eO

aA

BwO

iO

eO

aA

Bw

Oi

Oe

Oa

AB

wla

y th

ickn

ess [

cm]

n.d.

1-3

1-2

7-10

10-1

2n.

d.1-

31-

27-

1010

-12

n.d.

1-3

1-2

7-10

10-1

2

pH (C

aCl 2)

3,67

3,10

2,76

3,18

4,03

3,51

2,94

2,63

2,91

3,77

3,46

2,91

2,69

3,17

4,11

± 0.

1±

0.0

± 0.

0±

0.1

± 0.

1±

0.1

± 0.

1±

0.0

± 0.

0±

0.0

± 0.

0±

0.0

Exch

ange

able

Aci

dity

[cm

olc k

g-1]

n.d.

n.d.

n.d.

8,22

3,47

n.d.

n.d.

n.d.

7,44

3,63

n.d.

n.d.

n.d.

7,66

2,92

± 0.

2±

0.3

± 0.

1±

0.2

± 0.

2±

0.1

Exch

ange

able

Cat

ions

[cm

olc k

g-1]

n.d.

n.d.

n.d.

0,77

0,31

n.d.

n.d.

n.d.

0,52

0,24

n.d.

n.d.

n.d.

0,48

0,19

(Mg,

Na,

K, C

a)

± 0.

0±

0.0

± 0.

0±

0.0

± 0.

0±

0.0

Cor

g. [g

C k

g-1 D

M]

470,

343

6,0

327,

239

,715

,947

2,6

434,

835

0,1

45,5

17,0

474,

841

7,7

357,

137

,913

,8

± 11

.6±

11.9

± 2.

8±

1.7

± 11

.4±

31.9

± 3.

7±

1.2

± 27

.2±

38.4

± 1.

1±

0.5

Nor

g [g

N k

g-1 D

M]

10,1

15,8

13,5

2,0

0,9

12,5

16,6

13,8

2,1

0,9

11,6

16,0

13,8

1,9

0,8

± 1.

5±

1.1

± 0.

3±

0.1

± 0.

5±

2.5

± 0.

4±

0.1

± 1.

7±

2.5

± 0.

1±

0.1

Nm

in [m

g N

kg-1

DM

]34

3,1

225,

513

4,7

9,8

4,7

468,

122

3,2

94,3

7,3

4,2

164,

031

3,6

189,

37,

74,

3

± 29

.8±

27.3

± 1.

6±

0.1

± 27

.0±

17.1

± 0.

3±

0.3

± 43

.1±

60.9

± 0.

5±

0.3

C:N

ratio

45,4

27,8

24,3

20,0

17,6

36,5

26,2

25,5

21,9

19,0

40,3

26,1

25,6

20,3

16,8

± 2.

1±

0.6

± 0.

6±

1.2

± 0.

7±

0.7

± 0.

7±

0.3

± 0.

8±

0.7

± 0.

4±

0.6

Feo [

‰]

n.d.

n.d.

n.d.

6,14

4,64

n.d.

n.d.

n.d.

5,45

4,48

n.d.

n.d.

n.d.

6,08

4,53

± 0.

1±

0.2

± 0.

1±

0.2

± 0.

1±

0.2

Al o

[ ‰]

n.d.

n.d.

n.d.

1,81

3,69

n.d.

n.d.

n.d.

1,33

2,84

n.d.

n.d.

n.d.

1,59

3,28

± 0.

1±

0.2

± 0.

1±

0.2

± 0.

1±

0.1

wat

er c

onte

nt [%

]49

,468

,766

,534

,426

,547

,468

,265

,030

,925

,943

,665

,766

,328

,625

,1±

1.2

± 0.

7±

1.3

± 0.

6±

0.9

± 1.

4±

0.9

± 0.

2±

1.3

± 2.

4±

0.1

± 0.

1

Tab

le 3

.1: B

asic

phy

sico

chem

ical

soil

para

met

ers f

rom

the

Dys

tric

Cam

biso

lat S

ollin

g, c

entra

l Ger

man

y fo

r the

plo

ts D

1, D

2 an

d D

0 w

ithin

a so

il pr

ofile

. Res

ults

are

giv

en a

s arit

hmet

ic m

eans

and

stan

dard

err

ors.

n.d.

: not

det

erm

ined

; Cor

g: or

gani

c ca

rbon

; Nor

g: or

gani

c ni

troge

n; N

min: i

norg

anic

nitr

ogen

; Fe o

and

Al o:

iron

and

alum

iniu

m e

xtra

cted

in o

xala

te.

plot

D1

D2

D0

horiz

onO

iO

eO

aA

BwO

iO

eO

aA

Bw

Oi

Oe

Oa

AB

wla

y th

ickn

ess [

cm]

n.d.

1-3

1-2

7-10

10-1

2n.

d.1-

31-

27-

1010

-12

n.d.

1-3

1-2

7-10

10-1

2

pH (C

aCl 2)

3,67

3,10

2,76

3,18

4,03

3,51

2,94

2,63

2,91

3,77

3,46

2,91

2,69

3,17

4,11

± 0.

1±

0.0

± 0.

0±

0.1

± 0.

1±

0.1

± 0.

1±

0.0

± 0.

0±

0.0

± 0.

0±

0.0

Exch

ange

able

Aci

dity

[cm

olc k

g-1]

n.d.

n.d.

n.d.

8,22

3,47

n.d.

n.d.

n.d.

7,44

3,63

n.d.

n.d.

n.d.

7,66

2,92

± 0.

2±

0.3

± 0.

1±

0.2

± 0.

2±

0.1

Exch

ange

able

Cat

ions

[cm

olc k

g-1]

n.d.

n.d.

n.d.

0,77

0,31

n.d.

n.d.

n.d.

0,52

0,24

n.d.

n.d.

n.d.

0,48

0,19

(Mg,

Na,

K, C

a)

± 0.

0±

0.0

± 0.

0±

0.0

± 0.

0±

0.0

Cor

g. [g

C k

g-1 D

M]

470,

343

6,0

327,

239

,715

,947

2,6

434,

835

0,1

45,5

17,0

474,

841

7,7

357,

137

,913

,8

± 11

.6±

11.9

± 2.

8±

1.7

± 11

.4±

31.9

± 3.

7±

1.2

± 27

.2±

38.4

± 1.

1±

0.5

Nor

g [g

N k

g-1 D

M]

10,1

15,8

13,5

2,0

0,9

12,5

16,6

13,8

2,1

0,9

11,6

16,0

13,8

1,9

0,8

± 1.

5±

1.1

± 0.

3±

0.1

± 0.

5±

2.5

± 0.

4±

0.1

± 1.

7±

2.5

± 0.

1±

0.1

Nm

in [m

g N

kg-1

DM

]34

3,1

225,

513

4,7

9,8

4,7

468,

122

3,2

94,3

7,3

4,2

164,

031

3,6

189,

37,

74,

3

± 29

.8±

27.3

± 1.

6±

0.1

± 27

.0±

17.1

± 0.

3±

0.3

± 43

.1±

60.9

± 0.

5±

0.3

C:N

ratio

45,4

27,8

24,3

20,0

17,6

36,5

26,2

25,5

21,9

19,0

40,3

26,1

25,6

20,3

16,8

± 2.

1±

0.6

± 0.

6±

1.2

± 0.

7±

0.7

± 0.

7±

0.3

± 0.

8±

0.7

± 0.

4±

0.6

Feo [

‰]

n.d.

n.d.

n.d.

6,14

4,64

n.d.

n.d.

n.d.

5,45

4,48

n.d.

n.d.

n.d.

6,08

4,53

± 0.

1±

0.2

± 0.

1±

0.2

± 0.

1±

0.2

Al o

[ ‰]

n.d.

n.d.

n.d.

1,81

3,69

n.d.

n.d.

n.d.

1,33

2,84

n.d.

n.d.

n.d.

1,59

3,28

± 0.

1±

0.2

± 0.

1±

0.2

± 0.

1±

0.1

wat

er c

onte

nt [%

]49

,468

,766

,534

,426

,547

,468

,265

,030

,925

,943

,665

,766

,328

,625

,1±

1.2

± 0.

7±

1.3

± 0.

6±

0.9

± 1.

4±

0.9

± 0.

2±

1.3

± 2.

4±

0.1

± 0.

1

Tab

le 3

.1: B

asic

phy

sico

chem

ical

soil

para

met

ers f

rom

the

Dys

tric

Cam

biso

lat S

ollin

g, c

entra

l Ger

man

y fo

r the

plo

ts D

1, D

2 an

d D

0 w

ithin

a so

il pr

ofile

. Res

ults

are

giv

en a

s arit

hmet

ic m

eans

and

stan

dard

err

ors.

n.d.

: not

det

erm

ined

; Cor

g: or

gani

c ca

rbon

; Nor

g: or

gani

c ni

troge

n; N

min: i

norg

anic

nitr

ogen

; Fe o

and

Al o:

iron

and

alum

iniu

m e

xtra

cted

in o

xala

te.

Chapter II: The field study

mineral horizons (A and Bw) far smaller. The C/N ratio decreased continuously from the

top organic to the lower mineral horizon (p ≤ 0.001). Inorganic N was dominated by NH4+

(data not shown) and declined with soil depth. In the mineral soil, exchangeable acidity

and cations (Mg, Na, K, Ca) and oxalate-extractable Fe decreased from the A to the Bw

horizon, while oxalate-extractable Al increased. The highest pH was measured in the Bw

and the lowest in the Oa horizon at all plots.Most chemical variables of the Dystric

Cambisol were not affected by released N deposition. Solely organic N in the litter layer

(Oi) showed an effect of reduced N deposition, resulting in a wider C/N ratio in plot D1

(Table 3.1).

3.2. Lignin and phenolic compounds

The amounts of total and lignin-derived phenolic compounds displayed similar variations

along the soil profile. Largest C-normalized concentrations were found in the organic

horizons (Oi, Oe, Oa), followed by a strong decrease in the A horizon and a second

maximum in the Bw horizon (Figure 3.1).

0

20

40

60

80

100

120

140

160

Oi Oe Oa A Bw Oi Oe Oa A Bw Oi Oe Oa A Bw

D1 D2 D0

Tota

l phe

nolic

com

poun

ds [m

g g-1

OC

]

A

c

LSD (0.05) = 7.2c

a

b

d

e

f f

LSD (0.05) = 8.9 LSD (0.05) = 14.2

g

h

j j

0

20

40

60

80

100

120

Oi Oe Oa A Bw Oi Oe Oa A Bw Oi Oe Oa A Bw

D1 D2 D0

VSC

-lign

in [m

g g-1

OC

]

B

m

LSD (0.05) = 7.2

m

kl

no

qp

LSD (0.05) = 3.3 LSD (0.05) = 4.1

rs

ut

0

20

40

60

80

100

120

140

160

Oi Oe Oa A Bw Oi Oe Oa A Bw Oi Oe Oa A Bw

D1 D2 D0

Tota

l phe

nolic

com

poun

ds [m

g g-1

OC

]

A

c

LSD (0.05) = 7.2c

a

b

d

e

f f

LSD (0.05) = 8.9 LSD (0.05) = 14.2

g

h

j j

0

20

40

60

80

100

120

140

160

Oi Oe Oa A Bw Oi Oe Oa A Bw Oi Oe Oa A Bw

D1 D2 D0

Tota

l phe

nolic

com

poun

ds [m

g g-1

OC

]

A

c

LSD (0.05) = 7.2c

a

b

d

e

f f

LSD (0.05) = 8.9 LSD (0.05) = 14.2

g

h

j j

0

20

40

60

80

100

120

Oi Oe Oa A Bw Oi Oe Oa A Bw Oi Oe Oa A Bw

D1 D2 D0

VSC

-lign

in [m

g g-1

OC

]

B

m

LSD (0.05) = 7.2

m

kl

no

qp

LSD (0.05) = 3.3 LSD (0.05) = 4.1

rs

ut

0

20

40

60

80

100

120

Oi Oe Oa A Bw Oi Oe Oa A Bw Oi Oe Oa A Bw

D1 D2 D0

VSC

-lign

in [m

g g-1

OC

]

B

m

LSD (0.05) = 7.2

m

kl

no

qp

LSD (0.05) = 3.3 LSD (0.05) = 4.1

rs

ut

Figure 3.1: Total phenolic compounds (A) and VSC lignin (B) (V = vanillyl, S = syringyl and C = cinnamyl phenols) from the first sampling date (April 2006) of the three analyzed plots (D1, D2 and D0) and the five soil horizons (Oi, Oe, Oa, A and Bw) of the Dystric Cambisol from Solling (Lower Saxony, Germany). The values represent the arithmetic means (bars) and standard errors (error bars) of four field replications. Columns marked with the same lower-case letter are not significant different.

Lignin-derived vanillyl (V), syringyl (S) and cinnamyl phenols (C) in the litter represented

up to 65.8 ± 0.2% of the total phenolic compounds, with a V/S/C ratio of about 79/8/13.

The degree of lignin degradation as reflected by the acid-to-aldehyde ratio of vanillyl

phenols [(ac/al)v)] increased from the Oi (0.42 ± 0.01) to the A horizon (0.90 ± 0.05),

50

Chapter II: The field study

followed by a small decrease in the Bw horizon (0.81 ± 0.02) (Figure 3.2). The ratio of

syringyl-to-vanillyl phenols (S/V) (0.10 ± 0.01 – 0.93 ± 0.02) and of cinnamyl-to-vanillyl

phenols (C/V) (0.15 ± 0.01 – 0.56 ± 0.02) both increased with depth without differences

between the three plots (Figure 3.3). No change in the depth distribution of total and

lignin-derived phenolic compounds was found upon different N deposition (Figure 3.1 and

3.3). Likewise, reduced N input did not affect the degree of side-chain oxidation (Figure

3.2). Also manipulation by roof covering did not modify lignin variables.

(ac/al)V

0,2 0,4 0,6 0,8 1,0 1,2

Soil

horiz

on

Bw

A

Oa

Oe

Oi

0.2 0.4 0.6 0.8 1.0 1.2

(ac/al)V

0,2 0,4 0,6 0,8 1,0 1,2

Soil

horiz

on

Bw

A

Oa

Oe

Oi

0.2 0.4 0.6 0.8 1.0 1.2

Figure 3.2: Changes of acid-to-aldehyde ratio of vanillyl units [(ac/al)V] (squares and dotted lines) with soil depth of the Dystric Cambisolfrom the first sampling date (April 2006) of the three plots D1 (black), D2 (dark grey) and D0 (grey). The values represent the arithmetic means and standard errors of four field replications.

C/V ratio

0,0 0,2 0,4 0,6 0,8 1,0

S/V

ratio

0,0

0,2

0,4

0,6

0,8

1,0

Oi, Oe

Oa

A

Bw

0.0 0.2 0.4 0.6 0.8 1.00.0

0.2

0.4

0.6

0.8

1.0

C/V ratio

0,0 0,2 0,4 0,6 0,8 1,0

S/V

ratio

0,0

0,2

0,4

0,6

0,8

1,0

Oi, Oe

Oa

A

Bw

C/V ratio

0,0 0,2 0,4 0,6 0,8 1,0

S/V

ratio

0,0

0,2

0,4

0,6

0,8

1,0

Oi, Oe

Oa

A

Bw

0.0 0.2 0.4 0.6 0.8 1.00.0

0.2

0.4

0.6

0.8

1.0

Figure 3.3: Relation between syringyl-to-vanillyl (S/V) and cinnamyl-to-vanillyl (C/V) ratios in the Dystric Cambisol from the first sampling date (April 2006) of the three analyzed plots D1 (black), D2 (dark grey) and D0 (grey). The values of the two calculated parameters represent the arithmetic means and standard errors of four field replications.

(ac/al)V

0,2 0,4 0,6 0,8 1,0 1,2

Soil

horiz

on

Bw

A

Oa

Oe

Oi

0.2 0.4 0.6 0.8 1.0 1.2

(ac/al)V

0,2 0,4 0,6 0,8 1,0 1,2

Soil

horiz

on

Bw

A

Oa

Oe

Oi

0.2 0.4 0.6 0.8 1.0 1.2

Figure 3.2: Changes of acid-to-aldehyde ratio of vanillyl units [(ac/al)V] (squares and dotted lines) with soil depth of the Dystric Cambisolfrom the first sampling date (April 2006) of the three plots D1 (black), D2 (dark grey) and D0 (grey). The values represent the arithmetic means and standard errors of four field replications.

C/V ratio

0,0 0,2 0,4 0,6 0,8 1,0

S/V

ratio

0,0

0,2

0,4

0,6

0,8

1,0

Oi, Oe

Oa

A

Bw

0.0 0.2 0.4 0.6 0.8 1.00.0

0.2

0.4

0.6

0.8

1.0

C/V ratio

0,0 0,2 0,4 0,6 0,8 1,0

S/V

ratio

0,0

0,2

0,4

0,6

0,8

1,0

Oi, Oe

Oa

A

Bw

C/V ratio

0,0 0,2 0,4 0,6 0,8 1,0

S/V

ratio

0,0

0,2

0,4

0,6

0,8

1,0

Oi, Oe

Oa

A

Bw

0.0 0.2 0.4 0.6 0.8 1.00.0

0.2

0.4

0.6

0.8

1.0

Figure 3.3: Relation between syringyl-to-vanillyl (S/V) and cinnamyl-to-vanillyl (C/V) ratios in the Dystric Cambisol from the first sampling date (April 2006) of the three analyzed plots D1 (black), D2 (dark grey) and D0 (grey). The values of the two calculated parameters represent the arithmetic means and standard errors of four field replications.

3.3. Fungal phenol oxidase activity

The ABTS (2,2-azino-bis(3-ethylbenzothiazoline-6-sulfonate)) oxidizing activity in the

three plots D1, D2 and D0 showed a similar pattern for both sampling dates, i.e., a

decrease in enzyme activity from the Oe to the A horizon followed by a slight increase in

the Bw horizon (Figure 3.4). The median values for the phenol oxidase activity ranged

from 2.5 to 20.5 × 10-2 U g-1 dry matter for the April sampling and from 3.8 to 17.6 × 10-2

U g-1 dry matter for the October sampling (Figure 3.4). For both sampling dates, ANOVA

revealed differences between horizons, with patterns varying for each sampling time

(Figure 3.4). In contrast, no difference was found in the phenol oxidase activity of the

51

Chapter II: The field study

entire soil profile between the three plots, although the least significant distances were

markedly smaller at plot D1 in spring and at plot D0 in autumn.

0

5

10

15

20

25

30

Oe Oa A Bw Oe Oa A Bw Oe Oa A Bw

D1 D2 D0

Lign

olyt

ic e

nzym

e ac

tivity

[x10-2

U g

-1 D

M]

k

kk

i

m

mm

l

p

no

n

op

B

LSD (0.05) = 6.1 LSD (0.05) = 6.1 LSD (0.05) = 4.4

Lign

olyt

ic e

nzym

eac

tivty

[x10

-2U

g-1

DM

]

0

5

10

15

20

25

30

Oe Oa A Bw Oe Oa A Bw Oe Oa A Bw

D1 D2 D0

Lign

olyt

ic e

nzym

e ac

tivity

[x10-2

U g

-1 D

M]

e

h

f ffg

A

LSD (0.05) = 6.6

Lign

olyt

ic e

nzym

eac

tivty

[x10

-2U

g-1

DM

]

c

b

a

bc

e

d

d

LSD (0.05) = 4.6 LSD (0.05) = 7.9

0

5

10

15

20

25

30

Oe Oa A Bw Oe Oa A Bw Oe Oa A Bw

D1 D2 D0

Lign

olyt

ic e

nzym

e ac

tivity

[x10-2

U g

-1 D

M]

k

kk

i

m

mm

l

p

no

n

op

B

LSD (0.05) = 6.1 LSD (0.05) = 6.1 LSD (0.05) = 4.4

Lign

olyt

ic e

nzym

eac

tivty

[x10

-2U

g-1

DM

]

0

5

10

15

20

25

30

Oe Oa A Bw Oe Oa A Bw Oe Oa A Bw

D1 D2 D0

Lign

olyt

ic e

nzym

e ac

tivity

[x10-2

U g

-1 D

M]

k

kk

i

m

mm

l

p

no

n

op

B

LSD (0.05) = 6.1 LSD (0.05) = 6.1 LSD (0.05) = 4.4

Lign

olyt

ic e

nzym

eac

tivty

[x10

-2U

g-1

DM

]

0

5

10

15

20

25

30

Oe Oa A Bw Oe Oa A Bw Oe Oa A Bw

D1 D2 D0

Lign

olyt

ic e

nzym

e ac

tivity

[x10-2

U g

-1 D

M]

e

h

f ffg

A

LSD (0.05) = 6.6

Lign

olyt

ic e

nzym

eac

tivty

[x10

-2U

g-1

DM

]

c

b

a

bc

e

d

d

LSD (0.05) = 4.6 LSD (0.05) = 7.9

0

5

10

15

20

25

30

Oe Oa A Bw Oe Oa A Bw Oe Oa A Bw

D1 D2 D0

Lign

olyt

ic e

nzym

e ac

tivity

[x10-2

U g

-1 D

M]

e

h

f ffg

A

LSD (0.05) = 6.6

Lign

olyt

ic e

nzym

eac

tivty

[x10

-2U

g-1

DM

]

c

b

a

bc

e

d

d

LSD (0.05) = 4.6 LSD (0.05) = 7.9

Figure 3.4: Phenol oxidase activities from April 2006 (A) and October 2006 (B) of the three analyzed plots (D1, D2 and D0) and the four soil horizons (Oe, Oa, A and Bw) of the Dystric Cambisol. The values represent as arithmetic means (bars) and standard errors (error bars) of four field replications, which are the mean of three laboratory replications. Columns marked with the same lower-case letter are not significant different.

3.4. Diversity and distribution of the laccase gene sequences

In soil samples collected in April, 92 different laccase OTUs were found, which

corresponded to 70% of the maximum potentially detectable OTUs as evaluated by the

Jackknife analysis (data not shown). The diversity of OTUs decreased from the Oe to the A

horizon and slightly increased again in the Bw horizon. The largest richness (S) of OTUs

was found in Oe horizons, with values of 38 at plot D1, 39 at plot D2, and 31 at plot D0

(Figure 3.5A, Table 3.2); the results were confirmed by the Shannon diversity (H) index. In

addition, dominant OTUs were found for each horizon, with a tendency of dominancy

increase with depth (Figure 3.5A). The evenness (E) values also reflected this pattern

(Table 3.2) and a one-way ANOVA analysis confirmed the respective soil horizons of each

plot to differ significantly at p ≤0.05. The E values ranged from 0.85 and 0.87 in the Oe

horizon of the three plots, which indicates a relatively homogeneous laccase OTU

distribution in that horizon. Comparison of E values by one-way ANOVA for each horizon

showed no significant differences between plots D1, D2, and D0 (p ≥0.2) in April.

In soil samples of October, a total of 76 different laccase OTUs was found, of which 41

had already been detected in spring. As evaluated by the Jackknife analysis (date not

shown) this diversity correspond to 70% of the maximum potentially expectable laccase

OTUs. Interestingly, the highest diversity found of OTUs was markedly lower in autumn

52

Chapter II: The field study

(S value 27) than in spring (S values 39), and the OTU diversity was more homogeneous

along the profiles at the three plots (Table 3.2 and Figure 3.5B). The stronger homogeneity

in autumn samples holds true also for the diversity itself (S and H values) as well as for the

distribution of the most dominant OTUs as reflected by the E values (Table 3.2 and Figure

3.5B); one-way ANOVA revealed no significant differences in S, H, and E values between

the three plots and their respective horizons (p ≥0.1), except for the Oe horizon of plot D0

(p ≤0.05).

Table 3.2: Diversity of the detected basidiomycetous laccase OTU types of the analyzed plots (D1, D2 and D0) and horizons (Oe, Oa, A and Bw) of the Dystric Cambisol from both sampling dates. For each plot and horizon the number of detected laccase gene types from four subplots were pooled together. The diversity was analyzed by the richness (S), the Shannon index (H) and the eveness (E).

plot horizon layer thick- April 2006 October 2006ness [cm] S H E S H E

D1 Oe 1-3 38 3.17 0.87 21 1.91 0.63Oa 1-2 19 2.25 0.76 22 2.10 0.68A 7-10 16 1.99 0.72 23 1.87 0.60

Bw 10-12 18 2.23 0.77 23 2.15 0.68

D2 Oe 1-3 39 3.13 0.86 18 1.61 0.56Oa 1-2 14 2.29 0.87 26 2.25 0.69A 7-10 12 1.64 0.66 18 2.13 0.74

Bw 10-12 15 1.79 0.66 23 2.19 0.70

D0 Oe 1-3 31 2.93 0.85 27 2.66 0.81Oa 1-2 16 2.18 0.78 19 2.00 0.68A 7-10 16 1.84 0.66 20 2.29 0.76

Bw 10-12 9 1.44 0.65 25 2.39 0.74

0%

20%

40%

60%

80%

100%

D1 D2 D0 D1 D2 D0 D1 D2 D0 D1 D2 D0

Oe Oa A Bw

Rel

ativ

e fr

eque

ncy

dist

ribut

ion

Rela

tive

freq

uenc

ydi

strib

utio

n

A

0%

20%

40%

60%

80%

100%

D1 D2 D0 D1 D2 D0 D1 D2 D0 D1 D2 D0

Oe Oa A Bv

Rel

ativ

e fr

eque

ncy

dist

ribut

ion

Rela

tive

freq

uenc

ydi

strib

utio

n

B

0%

20%

40%

60%

80%

100%

D1 D2 D0 D1 D2 D0 D1 D2 D0 D1 D2 D0

Oe Oa A Bw

Rel

ativ

e fr

eque

ncy

dist

ribut

ion

Rela

tive

freq

uenc

ydi

strib

utio

n

A

0%

20%

40%

60%

80%

100%

D1 D2 D0 D1 D2 D0 D1 D2 D0 D1 D2 D0

Oe Oa A Bw

Rel

ativ

e fr

eque

ncy

dist

ribut

ion

Rela

tive

freq

uenc

ydi

strib

utio

n

A

0%

20%

40%

60%

80%

100%

D1 D2 D0 D1 D2 D0 D1 D2 D0 D1 D2 D0

Oe Oa A Bv

Rel

ativ

e fr

eque

ncy

dist

ribut

ion

Rela

tive

freq

uenc

ydi

strib

utio

n

B

0%

20%

40%

60%

80%

100%

D1 D2 D0 D1 D2 D0 D1 D2 D0 D1 D2 D0

Oe Oa A Bv

Rel

ativ

e fr

eque

ncy

dist

ribut

ion

Rela

tive

freq

uenc

ydi

strib

utio

n

B

Figure 3.5: Relative frequency distribution of the detected basidiomycetous laccase OTUs of the analyzed plots (D1, D2 and D0) and horizons (Oe, Oa, A and Bw) of the Dystric Cambisol from April 2006 (A) and October 2006 (B). Each colour symbolizes one detected laccase type.

53

Chapter II: The field study

3.5. Treatment effect on the laccase gene diversity

Treatment effects on the assemblage of laccase OTUs at the three plots and in individual

horizons were analyzed by principal component analysis (PCA) for both sampling dates.

The two principle components accounted 88.16 % of the variance for the samples collected

in April 2006. Factor loadings >|0.8| separated clearly organic layer from mineral soil

horizons. No treatment effect was found for the two mineral horizons (A and Bw) as the

OTU communities at the plots D1, D2 and D0 grouped into one cluster (Figure 3.6A). In

contrast, the OTU communities in the Oe horizon of plot D0 and D2 could be separated

from the community of plot D1 with reduced atmospheric N input. The laccase OTU

communities in the Oa horizon displayed a similar pattern although the separation from the

D1 community was less pronounced (Figure 3.6A). For the samples taken in October, the

principal components accounted for 90.2% of the variance (Figure 3.6B). While the

laccase OTU community of the Oe horizons at the control plot D0 clustered separately

from the two roofed plots D1 and D2, the communities of all other horizons showed a

horizontal stratification.

0

0,2

0,4

0,6

0,8

1

0 0,2 0,4 0,6 0,8 1

PC 1 [49,3%]

PC 2

[38,

86%

]

A

OeOa

A, Bw

0

0,2

0,4

0,6

0,8

1

0 0,2 0,4 0,6 0,8 1

PC 1 [55,28%]

PC 2

[34,

89%

]

BD1-OeD2-OeD0-Oe

D1-OaD2-OaD0-Oa

D1-AD2-AD0-A

D1-BwD2-BwD0-Bw

Oe

Oa, A, Bw

0

0,2

0,4

0,6

0,8

1

0 0,2 0,4 0,6 0,8 1

PC 1 [49,3%]

PC 2

[38,

86%

]

A

OeOa

A, Bw

0

0,2

0,4

0,6

0,8

1

0 0,2 0,4 0,6 0,8 1

PC 1 [55,28%]

PC 2

[34,

89%

]

BD1-OeD2-OeD0-Oe

D1-OaD2-OaD0-Oa

D1-AD2-AD0-A

D1-BwD2-BwD0-Bw

D1-OeD2-OeD0-Oe

D1-OaD2-OaD0-Oa

D1-AD2-AD0-A

D1-BwD2-BwD0-Bw

Oe

Oa, A, Bw

Figure 3.6: Principle component analysis (PCA) showing effects of the detected laccase OTU diversity of the tree analyzed plots D1 (black), D2 (dark grey) and D0 (grey) of the Dystric Cambisol from the first (A) and second (B) sampling date.

4. Discussion

In general it is assumed that increased atmospheric N deposition may influence the

function of forest soils as sink for or source of CO2 (Zak et al., 2000; Sinsabaugh et al.,

54

Chapter II: The field study

2005; Weis et al., 2006; Keeler et al., 2009). While studies on the ecosystem responses to

increased N deposition demonstrated inconsistent results (e.g., Knorr et al., 2005), efforts

on the ecosystem response to reduced atmospheric N deposition are scarce. In our study we

found that solely the organic N and the resulting C/N ratio of the litter (Oi) were affected

by the reduced N deposition (Table 3.1) indicating a lasting saturation in bio-available N in

the organic (Oe, Oa) and mineral (A, Bw) soil horizons (Bredemeier et al., 1995; Feng et

al., 2008) and that the available organic material in the analyzed soil horizons were

negligible diluted by N-depleted material due to the long life span and turnover times of

spruce needles (Dörr et al., 2010). These results and the related suggestions hamper the

verification of our second main hypotheses that the reduction of N deposition since 14.5

years may significantly affect the lignin decomposition, the related phenol oxidase activity

and the diversity structure of basidiomycetous laccase encoding genes. Therefore we

expect that ecological factors like the substrate availability along a soil depth gradient will

be of greater impact than factors assumed from experimental manipulations (e.g., reduced

N deposition or roof construction).

According to the commonly attributed ecological circumstances the results of our study

showed a vertical gradient for the April sampling. The decrease of lignin-derived CuO

oxidations products (e.g. VSC) from the organic horizons (Oe, Oa) to the upper mineral

horizon (A) reflects proceeding biodegradation of plant-derived compounds that is in

agreement with an increase of the lignin decomposition state (symbolized by (ac/al)v;

Figure 3.2) and the decreasing C/N ratio (Table 3.1) (Kögel, 1986; Hedges et al., 1988).

These finding were confirmed by our measured enzyme values showing a higher phenol

oxidase activity in soil organic layers with higher contents of recalcitrant plant compounds

than in the mineral soil (Figure 3.4A) which was previously reported in other studies

(Gallo et al., 2004; Luis et al., 2005a; Sinsabaugh et al., 2005; Finzi et al., 2006; Šnajdr et

al., 2008). Furthermore, this depth gradients in enzyme activity were relatable to the

diversity of basidiomycetous laccase encoding genes (determined as laccases OTUs; Table

3.2; Figure 3.5A) that is in accordance with prior described vertical changes in the

biomass, abundance, composition and distribution of the microbial, especially fungal

communities (O´Brien et al., 2005; Lindahl et al., 2007; Šnajdr et al., 2008). Additionally,

we found slight variations from the A to the Bw horizons for almost all measured

parameters in spring. At the biochemical level we firstly assumed that increasing VSC and

decreasing (ac/al)V are indicative for the leaching of soluble organic material from the

organic (Oe, Oa) and upper mineral horizons (A) into the deeper mineral horizon (Bw)

55

Chapter II: The field study

(Figure 3.1; Figure 3.2; Guggenberger & Zech, 1994) and secondly that the residual lignin

in the Bw horizon seems still mainly derived from a pervious angiosperm (beech)

vegetation, symbolized by increasing S/V and C/V ratios (Figure 3.3; Hedges & Mann,

1979; Ertel & Hedges, 1984). These changes in the availability of carbon compounds in

turn led to variances in the phenol oxidase activity (Figure 3.4A) and the laccase OTU

diversity (Table 3.2; Figure 3.5A) pinpointing the relative availability of organic energy

sources as one important factor for driving the ecosystem processes/functionality. These

inferences were recently confirmed by studies demonstrating that the fungal community

structure and the related enzyme activity shift in response to different available

carbon/nutrient sources due to the ability of species to exploit different resource niches

(Hanson et al., 2008; Allison et al., 2009). Despite the prominent role of the chemical

composition of the available litter material, the heterogeneity of physicochemical and

biological factors (Nannipieri et al., 2003; Leckie, 2005; Kellner et al., 2008; Šnajdr et al.,

2008; Artz et al., 2009; Kellner et al., 2009) offer several other possibilities for affecting

and controlling the fungal community structure and therefore the relative potential pool of

phenol oxidases.

In this study, we observed at the level of basidiomycetous laccase OTU community

structure a response to the reduced N deposition for the spring samples. The PCA pinpoint

that the laccase OTU community structure in the organic Oe and Oa horizons at plot D1

clustered separately from the communities in the corresponding horizons at plot D2 and D0

(Figure 3.6A). This response at the community level was neither translatable into effects

on the phenol oxidase activity nor on the lignin content and decomposition. Such

distinctions between the abundance of organisms with ligninolytic laccase genes, the

related enzyme activity and the decomposition process itself are in accordance with

previous reported findings by Hofmockel et al. (2007), Hassett et al. (2008) and Keeler et

al. (2009).

Interestingly and in contrast to the results from our spring samples, we found an almost

constant diversity level of the basidiomycetous laccase OTUs along the soil profiles in the

autumn samples, with exception of the unroofed plot D0 (Table 3.2; Figure 3.5B). Both the

Shannon index and the evenness were slightly higher for the Oe horizon of the plot D0

compared to that of D1 and D2 (Table 3.2). The PCA further filtered out these differences

in the laccase OTU community structure of the Oe horizon by separate clustering of the

plots (Figure 3.6B). The roofs covering the plots D1 and D2 caused changes in the

56

Chapter II: The field study

temperature regime (Lamersdorf & Borken, 2004) which might have triggered a

differential succession in the fungal communities compared to the unroofed plot. Although

we found changes in the laccase OTU community structure between the two sampling

dates possibly due to seasonal variations of the microbial succession during plant litter

degradation (e.g., Osono, 2007), the total phenol oxidase activity was nearly similarly as

previously reported (Blackwood et al., 2007; Kellner et al., 2009).

The findings in the present study indicate that the laccase containing fungal communities

respond sensitive to various environmental factors (e.g., reduced N deposition or changing

temperature regime by the roof construction), although they are mainly affected by spatio-

temporal ecological factors like substrate availability. However, enzyme activities and in

particular patterns of substrate decomposition, in this case of lignin, obversely behave

more conservative. Though, in regards to laccases, such discrepancy can be explained by

several factors. First, the fungal genome often comprises multiple copies of laccase

encoding genes and the number of which varies among species (e.g., the saprotrophic

fungus Coprinus cinereus contains a total of 17, Kilaru et al., 2006 and the

ectomycorrhizal fungus Laccaria bicolor 11 laccase genes, Courty et al., 2008), so that

variances in fungal community composition are not mirrored by proportional changes in

the diversity of laccase encoding gene sequence types. Second, a correlation between the

laccase encoding gene abundance and their related phenol oxidase activity can only occur

when genes were expressed and translated in an efficient acting protein that is only the

case for a minor portion of the detected laccase encoding genes in the community (Luis et

al., 2005a; Kellner et al., 2009). Third, some laccase encoding genes are not clearly

assignable to extracellular, ligninolytic enzymes involved in litter decomposition, but may

relate to other functions such as organismal interactions and development processes as

comprehensively reviewed by Burke & Cairney (2002) and Hoegger et al. (2006). Finally,

the total phenol oxidase (laccase) activity detected in a field may be in part the result of

soil inhabiting microbial groups other than fungi (e.g., bacteria, Kellner et al., 2008)

indicating a complementary role of the occurring microbes to sustain metabolic processes

in soils.

Concluding, studies on the ecosystem response to changing environmental conditions may

have gathered already valuable information on the fungal laccase activities under natural

conditions, though they produce inconsistent results and remain poorly understood. The

challenge at this point is to strengthen investigations on the detection of clearly verifiable

57

Chapter II: The field study

extracellular laccases (e.g., by screening of ecological relevant fungi for all potential

laccases and linking their genetic potential to produce laccase exoenzymes under

laboratory and natural conditions) in order to trace and quantify the activity of especially

fungi in terrestrial ecosystems. The more it is possible to work in this case, the better we

can pull out the relevant genes and estimate their responses to environmental conditions,

e.g. by using specific designed mircoarrays that beneficial effect on high-troughput, across-

landscape analyses relevant for understanding element cycling.

Acknowledgments

This work was financially supported by the German Research Foundation (DFG, PAK 12,

BU 941/9-1 and GU 406/14-1). We thank Dirk Böttger (University of Göttingen) for his

help during the soil sampling and our project partners from the Universities of Hohenheim

and Bayreuth (Germany) for the good cooperation. We are grateful to Florian Stange for

the SPINMAS measurements. Several anonymous reviewers made valuable critical

comments helping to improve the manuscript.

58

Chapter II: The field study

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Chapter III: Extraction of nucleic acids from soil

Chapter III: Towards a universally adaptable method for quantitative

extraction of high-purity nucleic acids from soil

Derek Peršoha,*, Susanne Theuerlb, François Buscotb, Gerhard Rambolda

a Lehrstuhl für Pflanzensystematik, Universität Bayreuth, Universitätsstraße 30 NW I, D-

95440 Bayreuth, Germany

b UFZ-Helmholtz Centre for Environmental Research, Department of Soil Ecology,

Theodor-Lieser-Straße 4, D-06120 Halle (Saale), Germany

*Corresponding author. Tel.: +49 921 55 2456; fax: +49 921 55 2567. E-mail address: derek.persoh@uni-bayreuth.de (D. Peršoh).

Journal of Microbiological Methods

Accepted

Date of acceptance: 22.04.2008

66

Chapter III: Extraction of nucleic acids from soil

Abstract

A universally adaptable protocol for quantitative extraction of high-purity nucleic acids

from soil is presented. A major problem regarding the extraction of nucleic acids from soil

is the presence of humic substances, which interfere with the extraction process itself and

in subsequent analytical manipulations. By the approach described here, the humic

compounds are precipitated prior to cell lysis with Al2(SO4)3, and thus eliminated prior to

the nucleic acid extraction. The protocol allows for removing of a considerable content and

range of humic acids and should therefore be applicable for a wide spectrum of soil types.

Accordingly, reproducible results in analyses of different soil types are made possible,

inclusively for quantitative comparisons.

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Chapter III: Extraction of nucleic acids from soil

1. Introduction

In the course of a joint research project focusing on the diversity of fungal and bacterial

organisms in relation to processes involved in the nutrient cycling in a spruce forest soil,

the basal problem of a quantitative extraction of nucleic acids was encountered. Recently

published and re-evaluated protocols (see LaMontagne et al., 2002; Lakay et al., 2007;

Weiss et al., 2007) did not provide nucleic acids at satisfactory purity or quantity from our

soil samples.

A major problem with the extraction of nucleic acids (DNA and RNA) from environmental

samples (i.e. soil, compost, and sediments) is the presence of humic substances. Because of

their chemically similar properties to nucleic acids, humic compounds are not removed

during standard extraction procedures (Holben, 1994; Zhou et al., 1996; Moreira, 1998;

Bruns & Buckley, 2002). Since coextracted humic substances interfere in most

manipulations applied for DNA and RNA analyses (e.g., Tsai & Olson 1991; Tebbe &

Vahjen, 1993; von Wintzingerode et al., 1997; Rochelle, 2001; Fortin et al., 2004), i.e.

enzymatic reactions (PCR, transcription, restriction) and hybridizations to reference

nucleic acids, their removal is essential. Different soil types are characterized by a different

composition and content of humic substances, which makes necessary to optimize specific

protocols for each given soil (Weiss et al., 2007), a time-consuming and difficult task.

Moreover, results gained by protocols specifically adapted to individual soils are not

necessarily comparable, as different extraction protocols have been shown to produce

different results (LaMontagne et al., 2002; Carrigg et al., 2007).

Our aim was to develop a time and cost efficient protocol for the simultaneous extraction

of high-purity DNA and RNA from soils. In anticipation of comparative studies of

different environmental samples, the optimized protocol had to be universally applicable.

2. Materials and methods

2.1. Experimental site and sampling

The sampling site is located in Solling, a mountainous plateau with an elevation of about

500 m above sea level near Uslar (Lower Saxony, Germany), in the experimental area (51

31′N, 9° 34′E) of the ‘Solling roof project’ (Bredemeier et al., 1998). The field-scale roof

experiment was established in 1989 in a 57-year-old Norway spruce plantation, growing on

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Chapter III: Extraction of nucleic acids from soil

strongly acidic Dystric Cambisol (FAO classification) with a moderate podzolized A

horizon.

Sampled soil cores were divided into two litter layers (Of and Oh) and two mineral soil

horizons (Ah and Bv). The samples were transferred to sterile 15 ml reaction tubes in the

field and immediately stored in liquid nitrogen for transport. In the laboratory, the samples

were subdivided in 0.5 g portions and stored in 2ml screwcap tubes at −80 °C until further

processing.

2.2. Nucleic acid extraction

2.2.1. Preliminary studies

Comprehensive preliminary tests (more than 300 nucleic acid extractions) were conducted,

the results of which are not presented here in detail. Briefly, all nucleic acid extractions

were performed using bead beating (FaastPrep™ Instrument, Bio 101), a step consistently

reported this as being the most effective method in comparative studies (Kuske et al., 1998;

Yeates et al., 1998; Lakay et al., 2007). The efficiency of extraction reagents that

previously lead to satisfactorily results (Kramer & Singleton, 1992; Griffiths et al., 2000;

Hurt et al., 2001) was analyzed by adding the reagents to 0.5 g of soil, followed by bead

beating, purification of the extract with phenol:chloroform:isoamylalcohol (25:24:1) and

chloroform:isoamylalcohol (24:1), and subsequent isopropanol precipitation. The

resuspended brown precipitates were not further purified, but the extracted nucleic acids

were analyzed by visible comparison of EtBr-stained bands after agarose gel

electrophoresis. Subsequently, established methods for removing humic substances

(Mendum et al., 1998; Fortin et al., 2004; Dong et al., 2006) were pre- or appended to the

“crude” extraction step. The efficiency of these methods was evaluated according to the

absorbance ratio A260/230 of the extracted nucleic acid solution.

The preliminary protocol was refined for providing optimal results with the best suited

purification method, which was based on flocculation of humic substances with Al2(SO4)3,

prior to the nucleic acid extraction.

A test series was conducted to estimate the amount of humic substances which may be

precipitated with a given concentration of Al2(SO4)3. Different volumes of 0,2 M Al2(SO4)3

solution were added to solutions of 1 mg pure humic acid (Roth) in 1 ml of water,

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Chapter III: Extraction of nucleic acids from soil

thoroughly mixed, and centrifuged at 11,000 g for 1 min. A clear supernatant indicated

complete precipitation of the humic acids.

2.2.2. Determination of the required Al2(SO4)3 quantity

To quickly estimate the Al2(SO4)3 concentration required to precipitate the humic

substances, we used the following procedure. Five subsamples of a soil sample were

treated as described in steps 1 to 4 of the protocol below, with volumes of 0.2 M Al2(SO4)3

solution ranging from 50 to 250 μl for samples of the mineral soil horizons and from 200

to 600 μl for samples of the organic litter layers. 800 mg of glass beads (0.5 mm in

diameter) were added, and the mixwas shaken in the bead beating instrument at 5.5 m/s for

1 min. The pH was adjusted to 8 or above by stepwise addition of 4 M NaOH. The samples

were mixed again at speed 5.5 m/s for 15 s in the bead beating instrument and the

minimum Al2(SO4)3 concentration needed to produce a clear supernatant after

centrifugation (11,000 g for 1 min at room temperature) was noted.

Subsequently, three series (3 to 5 subsamples each) of nucleic acid extractions were

conducted for each sampled litter layer and soil horizon. Al2(SO4)3 concentrations covering

the range of about 75 % to 125 % (mineral horizons) and 70 % to 90 % (litter layers) of the

determined concentration for the respective sample were added to the subsamples of each

series. [For organic samples with higher humic substance content a relatively lower

Al2(SO4)3 concentration proved to be adequate, probably because in these samples more

organic material is enclosed in intact cell and tissue residues, which does not compete

against the free humic substances in the substrate as long as beating has not been applied.]

2.2.3. Extraction protocol

1) Weight 0.5 g of the sample in a 2 ml screw cap reaction tube;

2) Add 100 μl of 1 M Tris–HCl buffer (pH 5.5);

3) Add V1 μl of sterile distilled Water (dH2O*) // V1=900 μl-V2;

4) Add V2 μl of 0.2 M Al2(SO4)3 // V2 depends on humic substance content of the sample (see below);

5) Shake in bead beating instrument (BBI) at 4.0 m/s for 15 s;

6) Add 1/3*V2 μl of 4 M NaOH;

7) Add V3 μl of 0.1 M Tris–HCl [pH 8] // V3=1300 μl-(4/3�V2)-V1;

8) Shake in BBI at 4.0 m/s for 15 s;

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Chapter III: Extraction of nucleic acids from soil

9) Adjust pH to 8 // stepwise add 10 μl of 4 M NaOH and shake in BBI at 4.0 m/s for 10 s until pH is 8 or

above;

10) Centrifuge 2 min at 3500 g and room temperature;

11) Carefully discard supernatant with a pipette and note the volume (V4);

12) Add V5 μl of 0.1 M Tris–HCl [pH 8] // V5=V4-650 μl;

13) Add 0.5 g of 0.5 mm, 0.3 g of 0.1 mm glass beads and one 4 mm glass bead;

14) Add 325 μl of extraction buffer (0.4 M LiCl, 100 mM Tris–HCl, 120 mM EDTA, pH 8);

15) Add 325 μl of 10% SDS (pH 8);

16) Shake in BBI at 4.0 m/s for 30 s;

17) Incubate on ice for 1 min to avoid overheating;

18) Shake in BBI at 5.5 m/s for 30 s;

19) Incubate on ice for 5 min;

20) Shake in BBI at 5.5 m/s for 30 s;

21) Centrifuge 1 min at 11,000 g and 4 °C;

22) Transfer 750 μl of the supernatant into a 1.5 ml reaction tube;

23) Add 750 μl of phenol:chloroform:isoamylalcohol (25:24:1);

24) Incubate 5 min on ice and shake well every minute;

25) Centrifuge 15 min at 16,000 g and 4 °C;

26a) Transfer the supernatant into a new 1.5 ml reaction tube;

27a) Add 1 volume, equal to the transferred supernatant, of chloroform:isoamylalcohol (24:1);

28a) Centrifuge 15 min at 16,000 g and 4 °C;

29a) Repeat steps 26 to 28 once;

30a) Transfer the supernatant to a new 1.5 ml reaction tube;

31a) Add 0.1 volume of 5 M NaCl and 0.7 volumes of isopropanol;

32a) Incubate over night at room temperate;

33a) Centrifuge 60 min at 18,000 g and room temperate;

34a) Remove the isopropanol completely using a pipette;

35a) Re-suspend pellet in 50 μl diethyl pyrocarbonate (DEPC) treated sterile dH2O.

a In case extraction of RNA is desired, all used vessels must be free of RNAse and solutions must be prepared

with DEPC treated water.

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Chapter III: Extraction of nucleic acids from soil

2.2.4. Separation of DNA and RNA

The extracted nucleic acid solutions are subdivided into two equal aliquots and treated with

DNAse I and RNAse A (both Invitrogen), respectively, as recommended by the

manufacturer. Subsequently, the respective nucleic acid fractions are precipitated as

described in steps 31 to 34 of the protocol above, and re-suspended in 25 μl of DEPC

treated dH2O.

2.3. Additional extraction protocols tested

To evaluate the efficiency of the newly developed protocol, corresponding subsamples

were processed with the Fast DNA Spin Kit for Soil (Q-Biogene) aswell as according to

the protocols of Griffiths et al. (2000) and Hurt et al. (2001). Additionally, parallel

subsamples were washed applying the respective steps of the protocol of Fortin et al. (2004)

before crude nucleic acid extraction (steps 1 and 12 to 35 of the protocol above, with

V5=650 μl), whereas the three washing steps were repeated once to thrice. The crude

extract of further subsamples was purified by filtration through polyvinylpolypyrrolidone

(PVPP) spin columns as described by Mendum et al. (1998).

2.4. Quality and quantity of nucleic acid extracts

The quality of the DNA extractions was controlled via spectrophotometry (NanoDrop,

Peqlab). Contamination by co-extracted humic substances was assessed via the absorbance

ratio A260/230. This ratio exceeds 2.0 for pure DNA.While ratios of 1.7 indicate nearly pure

DNA extractions from environmental samples (Bruns & Buckley, 2002), we decided to use

1.5 as a threshold for reasonable quantification of nucleic acids using spectrophotometry,

considering the results of Bachoon et al. (2001). Likewise, the A260/280 ratio, indicating

contamination by proteins, is about 2.0 for pure DNA and should exceed 1.7 for nearly

pure nucleic acid extractions from environmental samples. Finally, the A260/270 ratio (about

1.2 for pure DNA) was measured to detect significant phenol contamination (A260/270 < 1.1),

which would result in an overestimation of the nucleic acid concentration (Stulnig &

Amberger 1994). Of nucleic acid extractions fitting the three criteria, concentrations were

calculated assuming an absorbance of 1.0 (10 mm path) at 260 nm, which corresponds to a

concentration of 46.7 ng/μl. The factor was deduced from the results, which indicated a

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Chapter III: Extraction of nucleic acids from soil

ratio of about 2:1 for DNA:RNA in most samples and factors of 50 and 40 for pure DNA

and RNA, respectively.

3. Results

The relevant results of the preliminary tests are briefly summarized as follows. The bead

beating instrument was used to thoroughly mix the samples in step 5 of the protocol,

because vortexing alone proved not to be sufficient. However, two vortexing steps (45 s,

max. speed) with an intermediate centrifugation step (1 min at 3500 g) provided similar

results. Agarose gel electrophoresis revealed that, while the tested extraction buffers

yielded similar amounts of DNA, RNA recovery was best using Tris-HCl buffer with LiCl,

SDS and EDTA (Kramer & Singleton, 1992). EtOH and isopropanol were similarly

efficient for the precipitation of nucleic acids (steps 31 and 32), both at room temperature

over night and at -20 °C for 2 h. However, the volume of the precipitate obtained with

isopropanol at room temperature was less than 10% compared to the others, indicating a

low amount of co-precipitated salts.

A test series revealed that 1.5 μmol of Al2(SO4)3 suffice to efficiently precipitate 1mg of

pure humic acid. The experiment also revealed that 15 min of mixing 1 mg humic acids

added to 1 ml of water on a vortexing device at maximum speed was insufficient to

dissolve the humic acids, while these were completely dissolved in 15 s using the bead

beating instrument.

According to the protocol for rough estimation of the required Al2(SO4)3 concentration,

100 μmol of Al2(SO4)3 were needed to precipitate all humic substances from the Of and Oh

litter layers, 40 μmol for samples from the Ah, and 30 μmol for the Bv horizon. The

nucleic acid extractions revealed that addition of 80, 90, 40, and 40 μmol Al2(SO4)3 was

necessary to obtain extracts with an A260/230 above 1.5 from the Of, Oh, Ah and Bv,

respectively (Table 4.1). Addition of excessive Al2(SO4)3 resulted in similar qualitative

parameters, while the total amount of extracted nucleic acids decreased.

The concentration of nucleic acids was highest in the uppermost organic litter layer (Of)

and decreased with soil depth, with the highest difference between the upper litter layers

and the lower soil horizons. The DNA:RNA ratio within the extracts increased from 1.69

in Oh over 1.86 in Ah to 3.10 in Bv, while a median ratio of 2.12 was found for the Of

litter layer.

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Chapter III: Extraction of nucleic acids from soil

Table 4.1: Absorbance ratios and nucleic acid concentration of extracts from the two soil horizons and the two litter layers, applying increasing Al2(SO4)3 concentrations.

Layer / horizon

Al2(SO4)3 added in [µM]

A260/230 A260/280 A260/270 Nucleic acid yield [µg] per gram soil

Wet weight

Dry weighta

Of 70 0.87 1.50 1.09 7b 21b

80 1.66 1.82 1.18 28 83 90 1.71 1.84 1.19 25 71 100 1.93 1.90 1.22 20 58 Oh 80 1.24 1.64 1.12 4b 12b

90 1.70 1.79 1.18 18 54 100 1.71 1.79 1.17 14 42 110 1.73 1.82 1.16 10 29 Ah 35 1.15 1.63 1.11 10b 14b

40 1.69 1.83 1.17 13 18 45 1.68 1.84 1.16 13 18 50 1.68 1.81 1.14 9 13 Bv 30 1.06 1.59 1.10 8b 10b

35 1.35 1.74 1.14 8b 11b

40 1.72 1.84 1.15 9 12 45 1.71 1.83 1.18 5 7

a Water content analyzed of parallel samples by Kandeler et al. (submitted for publication). b value estimated by assuming the straight line trough the absorbance values at 310 nm and 340 nm as baseline.

None of the additionally tested methods resulted in a nucleic acid extract with A260/230 ratio

above 1.5 (Figure 4.1). The extracts obtained according to the protocol of Hurt et al. (2001)

and by the Fast DNA Spin Kit for Soil (Q-Biogene) showed a maximum absorbance at

about 230 nm (Figure 4.2). The protocol by Griffiths et al. (2000) resulted in an extract, the

absorbance spectrum of which roughly matches that of pure humic acids in water. The

effect of soil washing (Fortin et al., 2004) was negligible. Even after the washing steps had

been conducted thrice, the nucleic extracts were of nearly black color and a

spectrophotometric measurement was only possible for extracts from the Bv horizon that

contains the lowest concentration of humic substances. The respective data are therefore

not shown. Purification of the crude extract with PVPP resulted in an absorbance spectrum

consistently decreasing from 220 to 350 nm. However, all measurable extracts showed a

minor bulge around 260 nm. While this was a bit more distinct for extracts from the lower

horizons that contain fewer humic substances, the deviation from the trend line never

exceeded 25 % of the absorbance of the corresponding extract obtained with the here

optimized method.

74

Chapter III: Extraction of nucleic acids from soil

0

1

2

Of Oh Ah Bv

Litter layer or soil horizon

A26

0/23

0ra

tio

Al-Method Fast DNA Spin Kit for Soil (Q-Biogene)

Hurt et al. 2001 Griffiths et al. 2000

PVPP-Purification of crude extract

0

1

2

Of Oh Ah Bv

Litter layer or soil horizon

A26

0/23

0ra

tio

Al-Method Fast DNA Spin Kit for Soil (Q-Biogene)

Hurt et al. 2001 Griffiths et al. 2000

PVPP-Purification of crude extract

Figure 4.1: A260/230 ratio of nucleic acid extracts obtained using different extraction methods.

0

1

2

3

4

220 240 260 280 300 320 340

Wavelength [nm]

Abs

orba

nce

[10

mm

pat

h], f

ulls

ymbo

ls

0

5

10

15

20

Abs

orba

nce

[10

mm

pat

h], o

pen

sym

bols

Al-Method

PVPP-Purification of crude extractGriffiths et al. 2000Hurt et al. 2001Fast DNA Spin Kit for Soil (Q-Biogene)

Pure nucleic acids

Pure humic acid

0

1

2

3

4

220 240 260 280 300 320 340

Wavelength [nm]

Abs

orba

nce

[10

mm

pat

h], f

ulls

ymbo

ls

0

5

10

15

20

Abs

orba

nce

[10

mm

pat

h], o

pen

sym

bols

Al-Method

PVPP-Purification of crude extractGriffiths et al. 2000Hurt et al. 2001Fast DNA Spin Kit for Soil (Q-Biogene)

Pure nucleic acids

Pure humic acid

Figure 4.2: Absorbance spectra of nucleic acid extracts obtained applying different protocols, exemplified for samples of the litter layer Oh. The here presented protocol (Al-method) was comparatively analyzed to purification of a crude extract using PVPP (both scaled on left y-axis), the Fast DNA Spin Kit for Soil (Q-Biogene), and the protocols of Griffiths et al. (2000) and Hurt et al. (2001), the values for which refer to the right y axis. The absorbance spectra of pure humic acids (Roth) in water (1 mg/ml, scaled on the right y-axis) and pure nucleic acids (0.1 mg/ml; DNA:RNA 2:1, scaled on the left y-axis) are given for comparision.

75

Chapter III: Extraction of nucleic acids from soil

4. Discussion

4.1. Extraction of nucleic acids from soil

The majority of the hitherto published protocols for the extraction of nucleic acids from

soil consist of two steps. First, nucleic acids are extracted (“crude extract”) and

subsequently co-extracted humic substances are removed from the crude extract (Jackson

et al., 1997; Miller et al., 1999; Bruns & Buckley 2002; LaMontagne et al., 2002; Luis et

al., 2004; Luis et al., 2005; Arbeli & Fuentes 2007; Bernard et al., 2007; Lakay et al., 2007;

Weiss et al., 2007). However, humic substances (i.e. humic acids) interact with all kinds of

molecules (Stevenson, 1976), including nucleic acids, to which they may covalently bind.

Accordingly, the loss of nucleic acids during the purification step is, with above 50 %,

immense (Howeler et al., 2003; Carrigg et al., 2007). For this reason, it appears unlikely

that the recovered fraction sufficiently represents the nucleic acid spectrum within the

original soil sample. Interactions of the humic substances with reagents applied during

nucleic acid extraction may additionally account for inconsistencies in analyses of

microbial community with different extraction techniques (LaMontagne et al., 2002;

Carrigg et al., 2007). Against this background, reliable comparative analyses of soils with

different humic substance composition appear virtually impossible. These problems may

only be overcome by removal of humic substances prior to cell lysis (Fortin et al., 2004;

Dong et al., 2006).

While washing the soil samples (Fortin et al., 2004) proved deficient with our samples, it

may be feasible for samples with lower humic substance content, or when repeated several

times. In the latter case, however, the procedure is very time-consuming and the stability of

the nucleic acids (mainly the RNA) may not be guaranteed. The aim of the soil washing

procedure, i.e. the removal of heavy metals and other contaminants of polluted

environments, is also reached by the quantitative elimination of humic substances, because

these contaminants are readily bound by humic substances, wherefore they are not

removed from the nucleic acid extracts by standard isolation protocols (Fortin et al., 2004).

While the original protocol using Al2(SO4)3 for flocculation of humic substances (Dong et

al., 2006) had minor weaknesses, the basic principle proved very efficient. The here

presented protocol, which is based on this principle, resulted in nucleic acids extracts of

high purity. None of the extracts resulting from other tested protocols matched the criteria

for pure nucleic acids. Especially A260/230 ratios below 1.5 revealed huge amounts of co-

extracted humic substances (Figure 4.1). Due to the impurity of these extracts, there are no

76

Chapter III: Extraction of nucleic acids from soil

reliable data to directly compare the quantity of nucleic acids extracted using these and our

protocols. Nevertheless, the absorbance spectra of the impure extracts showed only a minor

elevation of the absorbance at 260 nm deviating from the expected absorbance spectrum of

the humic substances (Figure 4.2). This deviation was always clearly below the absorbance

measured for the extracts obtained with the here presented protocol. Hence, its application

recovered the highest concentration of nucleic acids.

4.2. Nucleic acid extraction protocol

A schematic overview on the presented extraction protocol is given in Figure 4.3, while its

crucial steps are discussed in detail in the following. A variable amount of Al2(SO4)3 may

be added to the soil sample, which allows the application of the protocol for a variety of

soil types with humic acid contents even higher than 200 mg per gram wet soil. At step 5

of the protocol, the humic substances are flocculated by the Al3+ ions under acid conditions,

as discussed in detail by Dong et al. (2006). Vortexing alone was insufficient for a

quantitative flocculation of the humic substances, because the outer layers of humic

substances probably hamper detain the Al3+ ions to reach the inner layers. The observation

thatmixingwith the bead beating instrument ismuchmore effective in dissolving pure humic

acids than using a vortexing device additionally indicates that the bead beating instrument

should be used at step 5. At steps 6 to 9, the pH value is adjusted to 8 or above, to

precipitate excessive Al3+ as Al(OH)3. The finding that nucleic acid recovery decreases

with increasing Al2(SO4)3 concentrations (Table 4.1) indicates that the precipitation of Al3+

ions is either not complete, or, that formed Al(OH)4+ ions may precipitate nucleic acids as

well. To minimize the loss of nucleic acids and concurrently expand the range of Al2(SO4)3

concentrations suitable for maximum nucleic acid recovery, the excessive solution is

removed at step 11 of the protocol. Furthermore, a beating step at low speed (step 16) was

included to release humic substances inaccessible for the Al3+ ions until then, while

themajority of cells present in the substrate remain intact at this step. Because of the

chemically similar nature of humic and nucleic acids, any substance in solution capable of

precipitating nucleic acids should precipitate with the released humic acids. The

composition of the beads (step 13) may be adapted to particular needs, without affecting

comparability of the results. Steps 14 to 30 roughly follow standard nucleic acid extraction

protocols (Zhou et al., 1996; Jackson et al., 1997; Miller et al., 1999; Griffiths et al., 2000;

Hurt et al., 2001; Bruns & Buckley, 2002), using a previously published extraction buffer

77

Chapter III: Extraction of nucleic acids from soil

(Kramer & Singleton, 1992), which provedmost effective for simultaneous DNA and RNA

recovery in the preliminary tests. Protein bound humic substances, which may cause a

brown to black coloration of the supernatant at step 22, are removed from the extracts at

steps 23 to 25. Nucleic acids are precipitated (step 31) with isopropanol at room

temperature for minimal co-precipitation of salt.

Soil sample

Precipitation of nucleic acids with isopropanol

Disruption of microbial cells

Precipitation of excessive Al3+ by pH adjustment

Precipitation of humic substances with Al3+

Precipitation of proteins with phenol

Dissolution of pure nucleic acids

Soil sample

Precipitation of nucleic acids with isopropanol

Disruption of microbial cells

Precipitation of excessive Al3+ by pH adjustment

Precipitation of humic substances with Al3+

Precipitation of proteins with phenol

Dissolution of pure nucleic acids

Figure 4.3: Workflow fort he extraction of nucleic acids from soil. For detail see text.

4.3. Reliability of data

The nucleic acid extractions according to each tested protocol have been conducted at least

thrice for each horizon and layer and the results reveal unambiguous trends. Due to the

heterogeneous structure of soil, the replicate number is insufficient to calculate reasonable

statistical support for the data. However, because the purpose of this article was to make a

powerful protocol available for soil scientists and not to discuss the findings in a biological

context, we consider statistical analyses as being dispensable at this stage. Therefore,

representative data are presented throughout this article. Nevertheless, a layout for

reproducible quantitative studies is proposed below.

78

Chapter III: Extraction of nucleic acids from soil

4.4. Layout for quantitative studies

By removal of humic substances prior to the nucleic acid isolation, the presented protocol

enables quantitative studies on nucleic acid diversity (e.g., microarray analyses) and

composition (e.g., DNA–RNA proportion) for the first time. The fact, that the amount of

extracted nucleic acids increases until sufficient Al2(SO4)3 is added, confirms that nucleic

acids bind to the thereby removed humic substances and indicates that a maximum of

nucleic acids may be extracted with this protocol. However, since soils are of

heterogeneous structure, a constant amount of sample net weight does not warrant constant

humic and nucleic acids contents. Especially, irregularities in the colonization density of

microorganisms due to the accumulation of organic or inorganic material (e.g., decaying

roots, mineral grains) and corresponding variations in the amount of organic soil

compounds might lead to inconsistent results. Therefore, for obtaining reliable results,

sample series with different Al2(SO4)3 concentrations have to be processed in parallel.

Furthermore, parallels of these sample series have to be analyzed. During nucleic acid

extraction, the most errorprone step is certainly the quantitative removal of isopropanol

from the precipitate. The risk of inadvertent removal of nucleic acid fractions increases

with decreasing size of the precipitate. Accordingly, this risk is minimized by a maximum

amount of nucleic acids in the extract, which may be accomplished by pooling of parallel

samples.

For further analyses in the course of our ongoing project, we designed the following

sampling strategy. Six series of three samples (18 samples in total) are processed for each

soil sample. The three samples of each series are treated with different Al2(SO4)3

concentrations, spanning the desired range. Subsequent to nucleic acid extraction, all

samples with humic substance (A260/230 < 1.65), phenol (A260/270 < 1.15), or protein

(A260/280 < 1.75) contamination are discarded. From the remaining samples, the one with

the highest nucleic acid content is selected from each series. From the six remaining

samples those representing median nucleic acids contents are selected and pooled, while

those with clearly deviating contents are discarded. If necessary (i.e. parallel analyses of

DNA and RNA) the obtained sample may be subsequently subdivided into parallel

subsamples for further processing.

Concluding, the here presented protocol allows for efficient extraction of highly pure

nucleic acids from soil. Because humic substances are precipitated in a flexible step prior

79

Chapter III: Extraction of nucleic acids from soil

to cell lysis, it may be used for various types of soil and related substrates, making

comparative results and quantitative analyses possible.

Acknowledgements

We thank Dirk Böttger (Göttingen) for invaluable help during the soil sampling. The

excellent cooperation with our project partners (working groups of Ellen Kandeler,

Hohenheim and Georg Guggenberger, Halle) accounted for an efficient sample drawing.

Thomas Brune (Hohenheim) also readily shared his data on water content of the soil

samples with us. Andrea Kirpal (Bayreuth) is thanked for assistance with the laboratory

work. The project (RA 731/9-1 and BU 941/9-1) was funded by the Deutsche

Forschungsgemeinschaft (DFG) in a joined application (PAK 12).

80

Chapter III: Extraction of nucleic acids from soil

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Bachoon, D.S., Otero, E., Hodson, R.E., 2001. Effects of humic substances on fluorometric

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Bernard, L., Mougel, C., Maron, P.-A., Nowak, V., Leveque, J., Henault, C., et al., 2007.

Dynamics and identification of soil microbial populations actively assimilating carbon

from 13C-labelled wheat residue as estimated by DNA- and RNA-SIP techniques.

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Carrigg, C., Rice, O., Kavanagh, S., Collins, G., O'Flaherty, V., 2007. DNA extraction

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Dong, D.X., Yan, A., Liu, H.M., Zhang, X.H., Xu, Y.Q., 2006. Removal of humic

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Fortin, N., Beaumier, D., Lee, K., Greer, C.W., 2004. Soil washing improves the recovery

of total community DNA from polluted and high organic content sediments. J.

Microbiol. Methods 56, 181–191.

Griffiths, R.I., Whiteley, A.S., O'Donnell, A.G., Bailey, M.J., 2000. Rapid method for

coextraction of DNA and RNA from natural environments for analysis of ribosomal

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Holben, W.E., 1994. Isolation and purification of bacterial DNA from soil. In: Weaver,

R.W. (Ed.), Methods of Soil Analysis. Part 2. Microbiological and Biochemical

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and purification from compost. J. Microbiol. Methods 54, 37–45.

Hurt, R.A., Qiu, X.Y., Wu, L.Y., Roh, Y., Palumbo, A.V., Tiedje, J.M., et al., 2001.

Simultaneous recovery of RNA and DNA from soils and sediments. Appl. Environ.

Microbiol. 67, 4495–4503.

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Chapter IV: The Sequence Study

Chapter IV: The phylogenetic resolving potential of laccase encoding

gene fragments frequently employed in soil molecular ecological

studies

Abstract

Laccases are of great interest for soil microbiologists as they are crucial enzymatic tools of

resident microbes involved in the degradation of recalcitrant plant-derived substances. The

enzyme activity depends on the redox potential of four copper atoms bond at particular,

relatively conserved amino acid motifs. This enabled the design of degenerated fungal- and

bacteria-specific primers for amplifying laccase encoding gene fragments between the

copper binding regions I and II. The PCR approach has yielded a number of ecological

studies coupling spatio-temporal variations of laccase-containing microbial communities

with organic matter processing in the heterogeneous and dynamic soil system.

Unfortunately, the multigene character and related functional diversification of laccases

complicates a tight correlation between the presence of laccase gene and/or transcript

fragments and effective enzyme activities.

The present review used comparative phylogenetic analyses of nucleotide and protein

sequences to ascertain that the commonly targeted laccase encoding gene fragment

contains insufficient phylogenetic information for reliably separating distinct clades with

regard to a respective function of the corresponding enzyme. The review concludes that

fungal functional ecology will certainly benefit from the ongoing whole genome

sequencing efforts due to the possibility of designing new primer combinations targeting

longer gene fragments of well-characterized, ecological important fungi.

84

Chapter IV: The Sequence Study

1. Introduction

The application of molecular biological methods in soil ecology leads to comprehensive

insights into the diversity, composition, and functioning of soil microbial consortia within

complex ecosystems (Kirk et al., 2004; Leckie, 2005; Zak et al., 2006). Molecular

ecological studies target either barcoding markers (e.g., regions of the ribosomal RNA

encoding gene) to assess the diversity across wide taxonomic swaths (Anderson & Cairney,

2004; Kirk et al., 2004; Leckie, 2005) or functional markers (e.g., genes encoding specific,

ecologically important enzymes) to reveal parts of an entire community with the related

functional potential, which can also be correlated to specific biogeochemical processes

(Philippot, 2005; Zak et al., 2006).

Due to their role in modifying plant-derived recalcitrant substances (e.g., lignin), one often

investigated functional markers are laccase or laccase-like multicopper oxidase (LMCO)

encoding genes that are widespread in bacteria (Kellner et al., 2008) and especially in

basidiomycetous fungi (Baldrian, 2006; Theuerl & Buscot, 2010). The amino acid

sequence consists of four well-conserved copper binding regions (cbr) that are

characterized by the occurrence of one cysteine and ten histidin residues (Thurston, 1994;

Valderrama et al., 2003; Wong, 2008). Deduced from the conserved amino acids motifs

around cbr I, II and III, different degenerated primer pairs were published during the last

years (Figure 5.1) to amplify laccase encoding genes of wood decaying fungi (D´Souza et

al., 1996), basidiomycetous (Luis et al., 2004) or ascomycetous fungi (Lyons et al., 2003,

Kellner et al., 2007) or bacterial LMCO genes (Kellner et al., 2008).

Comprehensive soil ecological studies showed that the diversity of fungal communities

harbouring laccase encoding genes can be correlated with ecological variables such as

quality and quantity of soil organic matter, nutritional pathways of fungi (e.g., saprotrophic

vs. mycorrhizal) or environmental conditions (Table 5.1; see review by Theuerl & Buscot,

2010). Almost all of these studies were based on the molecular biological processing of

environmental samples to obtain nucleotide sequences from unknown species of the entire

community by amplifying the laccase encoding gene fragment between the cbr I and II

(Table 5.1, Figure 5.1; D´Souza et al., 1996; Luis et al., 2004; Kellner et al., 2008). Quite

often, quite often phylogenetic analyses were conducted subsequently to find homologous

genes from fungal fruiting bodies to possibly relate sequences found in soil samples to

reference specimens.

85

Chapter IV: The Sequence Study

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sidi

omyc

etou

s lac

case

enc

odin

g ge

nes i

n so

ilsR

NA

; RT-

PCR

and

sem

i-qua

ntita

tive

PCR

; pr

imer

pai

r: C

u1F/

Cu2

RN

J with

K2P

- tre

e w

ith lo

w b

oots

trap

supp

ort;

MP

heur

istic

sle

ss th

an 3

0% o

f the

lacc

ase

enco

ding

gen

es w

ere

expr

esse

d; d

iffer

ent e

xpre

ssio

n of

lacc

ase

gene

s in

the

rhiz

osph

ere

and

bulk

soil

Ger

man

y, E

urop

e; d

ecid

uous

fore

st (b

eech

-oak

); so

il ho

rizon

s:

Oa

Luis

et a

l. 2

005b

dive

rsity

and

spat

ial d

istri

butio

n of

bas

idio

myc

etou

s lac

case

en

codi

ng g

enes

in so

ilsD

NA

; PC

R a

ppra

och

on fu

ngal

frui

ting

bodi

es

and

soil

sam

ples

; prim

er p

air:

Cu1

F/C

u2R

NJ w

ith K

2P -

tree

not s

how

n; M

P he

uris

tics

gene

dis

trubu

tion

alon

g th

e so

il pr

ofile

was

in a

ccor

danc

e w

ith th

e nu

tritio

nal p

athw

ay o

f fun

gi; h

igh

gene

he

tero

gene

ity b

etw

een

adja

cent

soil

core

sG

erm

any,

Eur

ope;

dec

iduo

us fo

rest

(bee

ch-o

ak);

soil

horiz

ons:

O

a, A

h, B

w

Kel

lner

et a

l. 2

007

dete

ctio

n an

d ex

pres

sion

pro

files

of l

acca

se-li

ke m

ultic

oppe

r ox

idas

e (L

MC

O) e

ncod

ing

gene

s in

Mor

chel

lace

aeD

NA

and

RN

A; P

CR

app

aoch

es o

n fu

ngal

cu

lture

s; p

rimer

pai

rs C

u1A

F/C

u2R

or C

u3R

NJ w

ith K

2P -

tree

with

low

boo

tstra

p su

ppor

t; M

P he

uris

tics

mul

tigen

e fa

mily

; ver

ifica

tion

of g

enes

enc

odin

g en

zym

es

invo

lved

in li

tter d

ecay

by

indu

ctio

n of

gen

e ex

pres

sion

us

ing

phen

olic

com

poun

ds

Bla

ckw

ood

et a

l. 2

007

effe

ct o

f enh

ance

d ni

troge

n (N

) dep

ositi

on o

n th

e di

vers

ity o

f la

ccas

e en

codi

ng g

ene

in d

iffer

ent f

ores

t typ

esD

NA

; QPC

R a

nd L

H-P

CR

; prim

er p

air:

Cu1

F/C

u2R

ML

and

NJ -

tree

with

low

boo

tstra

p su

ppor

t; tre

e no

t sho

wn

no N

eff

ect;

ecos

yste

m ty

pe a

nd h

ence

the

leve

l of s

ubst

rate

re

calc

itran

ce si

gnifi

cant

ly a

ffec

t the

lacc

ase

enco

ding

gen

e ab

unda

nce

Mic

higa

n, U

SA; d

ecid

uous

fore

st (B

OW

O, S

MR

O, S

MB

W);

fore

st fl

oor (

orga

nic

soil

laye

rs)

Hof

moc

kel e

t al.

200

7ef

fect

s of e

nhan

ced

N d

epos

ition

on

the

abun

danc

e of

lacc

ase

enco

ding

gen

es in

diff

eren

t har

dwoo

d fo

rest

sD

NA

; QPC

R a

nd L

H-P

CR

; prim

er p

air:

Cu1

F/C

u2R

not d

one

ecos

yste

m b

y N

dep

ostio

n in

tera

ctio

n af

fect

the

phen

ol

oxid

ase

activ

ity, b

ut n

ot th

e la

ccas

e ge

ne a

bund

ance

; gen

e di

vers

ity a

ffec

ted

by le

af li

tter l

igni

n co

nten

tM

ichi

gan,

USA

; dec

iduo

us fo

rest

(BO

WO

, SM

RO

, SM

BW

); fo

rest

floo

r and

surf

ace

soil

Tab

le 5

.1: A

vaila

ble

stud

ies o

n m

olec

ular

eco

logi

cal l

acca

sere

sear

ch in

clud

ing

the

rese

arch

obj

ectiv

es, a

pplie

d m

etho

ds, p

hylo

gene

tican

alys

es a

nd re

sults

.

BO

WO

= b

lack

oak

-whi

teoa

k, S

MR

O =

suga

rmap

le-r

ed o

ak, S

MBW

= su

garm

aple

-bas

swoo

d, R

T-PC

R =

Rev

erse

Tra

nsci

ptas

ePC

R, Q

PCR

= q

uant

itativ

e PC

R, L

H-P

CR

= le

ngth

hete

roge

neity

PCR

, NJ w

ithK

2P =

nei

ghbo

urjo

inin

g, M

P =

max

imum

pars

imon

y, M

L =

max

imum

likel

ihoo

d, K

2P K

imur

a-2-

para

met

er

mod

el, J

TT =

Jone

s-Ta

ylor

-Tho

rnto

n m

odel

Ref

eren

ceO

bjec

tM

etho

dsPh

ylog

enet

ic a

naly

ses

Res

ults

D´S

ouza

et a

l. 1

996

prim

er d

esig

n an

d ap

plic

atio

n (d

educ

ed fr

om th

e co

nser

ved

copp

er b

indi

ng re

gion

s (cb

r) I

and

II of

lacc

ase

prot

ein

sequ

ence

s) fo

r woo

d de

cayi

ng fu

ngi

DN

A; P

CR

app

raoc

h on

myc

elia

l cul

ture

s;

prim

er p

air:

lccF

/lccR

not d

one

succ

esfu

l am

plifi

catio

n of

the

lacc

ase

gene

frag

men

t be

twee

n cb

r I a

nd II

from

woo

d de

cayi

ng fu

ngi

Lyon

s et a

l. 2

003

desi

gn o

f a fu

ngal

-spe

cific

prim

er p

air t

o de

tect

the

lacc

ase

dive

rsity

am

ong

asco

myc

etou

s fun

gi in

a sa

lt m

arsh

DN

A, P

CR

app

raoc

h; p

rimer

pai

r: LA

C2F

OR

/LA

C3R

EVN

J with

K2P

- tre

e w

ith lo

w b

oots

trap

supp

ort

succ

esfu

l am

plifi

catio

n of

the

lacc

ase

gene

frag

men

t be

twee

n cb

r II a

nd II

I fro

m fu

ngal

cul

ture

s and

as

com

ycet

ous f

ungi

from

dec

ayin

g bl

ades

Geo

rgia

, USA

; sal

t mar

sh

Luis

et a

l. 2

004

desi

gn o

f a b

asid

iom

ycet

e-sp

ecifi

c pr

imer

pai

r to

asse

ss th

e di

vers

ity o

f fun

gal l

acca

se e

ncod

ing

gene

s dire

ctly

in so

ilsD

NA

; PC

R, c

loni

ng a

nd se

quen

cing

; prim

er p

air:

Cu1

F/C

u2R

NJ w

ith K

2P -

tree

with

low

boo

tstra

p su

ppor

t; M

P he

uris

tics

succ

esfu

l am

plifi

catio

n of

bas

idio

myc

ete-

spec

ific

lacc

ase

enco

ding

gen

e fo

m e

nviro

nmen

tal s

ampl

es; d

ecre

ase

of

dive

rsity

with

incr

easi

ng so

il de

pth

Ger

man

y, E

urop

e; d

ecid

uous

fore

st (b

eech

-oak

); so

il ho

rizon

s:

Oa,

Ah,

Bw

Luis

et a

l. 2

005a

met

hod

deve

lopm

ent f

or a

naly

sing

the

expr

essi

on o

f ba

sidi

omyc

etou

s lac

case

enc

odin

g ge

nes i

n so

ilsR

NA

; RT-

PCR

and

sem

i-qua

ntita

tive

PCR

; pr

imer

pai

r: C

u1F/

Cu2

RN

J with

K2P

- tre

e w

ith lo

w b

oots

trap

supp

ort;

MP

heur

istic

sle

ss th

an 3

0% o

f the

lacc

ase

enco

ding

gen

es w

ere

expr

esse

d; d

iffer

ent e

xpre

ssio

n of

lacc

ase

gene

s in

the

rhiz

osph

ere

and

bulk

soil

Ger

man

y, E

urop

e; d

ecid

uous

fore

st (b

eech

-oak

); so

il ho

rizon

s:

Oa

Luis

et a

l. 2

005b

dive

rsity

and

spat

ial d

istri

butio

n of

bas

idio

myc

etou

s lac

case

en

codi

ng g

enes

in so

ilsD

NA

; PC

R a

ppra

och

on fu

ngal

frui

ting

bodi

es

and

soil

sam

ples

; prim

er p

air:

Cu1

F/C

u2R

NJ w

ith K

2P -

tree

not s

how

n; M

P he

uris

tics

gene

dis

trubu

tion

alon

g th

e so

il pr

ofile

was

in a

ccor

danc

e w

ith th

e nu

tritio

nal p

athw

ay o

f fun

gi; h

igh

gene

he

tero

gene

ity b

etw

een

adja

cent

soil

core

sG

erm

any,

Eur

ope;

dec

iduo

us fo

rest

(bee

ch-o

ak);

soil

horiz

ons:

O

a, A

h, B

w

Kel

lner

et a

l. 2

007

dete

ctio

n an

d ex

pres

sion

pro

files

of l

acca

se-li

ke m

ultic

oppe

r ox

idas

e (L

MC

O) e

ncod

ing

gene

s in

Mor

chel

lace

aeD

NA

and

RN

A; P

CR

app

aoch

es o

n fu

ngal

cu

lture

s; p

rimer

pai

rs C

u1A

F/C

u2R

or C

u3R

NJ w

ith K

2P -

tree

with

low

boo

tstra

p su

ppor

t; M

P he

uris

tics

mul

tigen

e fa

mily

; ver

ifica

tion

of g

enes

enc

odin

g en

zym

es

invo

lved

in li

tter d

ecay

by

indu

ctio

n of

gen

e ex

pres

sion

us

ing

phen

olic

com

poun

ds

Bla

ckw

ood

et a

l. 2

007

effe

ct o

f enh

ance

d ni

troge

n (N

) dep

ositi

on o

n th

e di

vers

ity o

f la

ccas

e en

codi

ng g

ene

in d

iffer

ent f

ores

t typ

esD

NA

; QPC

R a

nd L

H-P

CR

; prim

er p

air:

Cu1

F/C

u2R

ML

and

NJ -

tree

with

low

boo

tstra

p su

ppor

t; tre

e no

t sho

wn

no N

eff

ect;

ecos

yste

m ty

pe a

nd h

ence

the

leve

l of s

ubst

rate

re

calc

itran

ce si

gnifi

cant

ly a

ffec

t the

lacc

ase

enco

ding

gen

e ab

unda

nce

Mic

higa

n, U

SA; d

ecid

uous

fore

st (B

OW

O, S

MR

O, S

MB

W);

fore

st fl

oor (

orga

nic

soil

laye

rs)

Hof

moc

kel e

t al.

200

7ef

fect

s of e

nhan

ced

N d

epos

ition

on

the

abun

danc

e of

lacc

ase

enco

ding

gen

es in

diff

eren

t har

dwoo

d fo

rest

sD

NA

; QPC

R a

nd L

H-P

CR

; prim

er p

air:

Cu1

F/C

u2R

not d

one

ecos

yste

m b

y N

dep

ostio

n in

tera

ctio

n af

fect

the

phen

ol

oxid

ase

activ

ity, b

ut n

ot th

e la

ccas

e ge

ne a

bund

ance

; gen

e di

vers

ity a

ffec

ted

by le

af li

tter l

igni

n co

nten

tM

ichi

gan,

USA

; dec

iduo

us fo

rest

(BO

WO

, SM

RO

, SM

BW

); fo

rest

floo

r and

surf

ace

soil

Tab

le 5

.1: A

vaila

ble

stud

ies o

n m

olec

ular

eco

logi

cal l

acca

sere

sear

ch in

clud

ing

the

rese

arch

obj

ectiv

es, a

pplie

d m

etho

ds, p

hylo

gene

tican

alys

es a

nd re

sults

.

BO

WO

= b

lack

oak

-whi

teoa

k, S

MR

O =

suga

rmap

le-r

ed o

ak, S

MBW

= su

garm

aple

-bas

swoo

d, R

T-PC

R =

Rev

erse

Tra

nsci

ptas

ePC

R, Q

PCR

= q

uant

itativ

e PC

R, L

H-P

CR

= le

ngth

hete

roge

neity

PCR

, NJ w

ithK

2P =

nei

ghbo

urjo

inin

g, M

P =

max

imum

pars

imon

y, M

L =

max

imum

likel

ihoo

d, K

2P K

imur

a-2-

para

met

er

mod

el, J

TT =

Jone

s-Ta

ylor

-Tho

rnto

n m

odel

Chapter IV: The Sequence Study

Ref

eren

ceO

bjec

tM

etho

dsPh

ylog

enet

ic a

naly

ses

Res

ults

Has

sett

et a

l. 2

008

pote

ntia

l of N

inpu

t to

redu

ce th

e ab

unda

nce

and

alte

r the

co

mpo

sitio

n of

bas

idio

myc

etes

in h

arw

ood

fore

sts

DN

A; Q

PCR

and

LH

-PC

R; p

rimer

pai

r: C

u1F/

Cu2

Rno

t don

eno

con

sist

ent e

ffec

t of N

dep

ostio

n; d

iffer

ence

s bet

wee

n fo

rest

floo

r and

min

eral

soil

due

to d

istri

butio

n of

sa

prot

roph

ic a

nd m

ycor

rhiz

al fu

ngi

Mic

higa

n, U

SA; d

ecid

uous

fore

st (s

ugar

map

le);

fore

st

floor

(org

anic

soil

laye

rs) a

nd m

iner

al so

il

Laub

er e

t al.

200

8ef

fect

of s

hort-

term

N fe

rtiliz

atio

n on

lacc

ase

gene

di

vers

ity a

nd c

ompa

rison

with

pre

viou

s stu

dies

DN

A; P

CR

, clo

ning

, seq

uenc

ing

and

QPC

R;

prim

er p

air:

Cu1

F/C

u2R

N

J; a

naly

ses o

f the

phy

loge

netic

dis

tanc

e be

twee

n th

e sa

mpl

es u

nsin

g U

niFr

acno

N e

ffec

t on

lacc

ace

gene

div

ersi

ty; l

acca

se g

ene

com

mun

ities

: nea

rly si

min

lar i

n m

iner

al so

ils,

phyl

ogen

etic

ally

diff

eren

t bet

wee

n lit

ter t

ypes

Mic

higa

n, U

SA; d

ecid

uous

fore

st (B

OW

O);

litte

r and

m

iner

al so

il

Kel

lner

et a

l. 2

008

dive

rsity

and

dis

tribu

tion

of b

acte

rial l

acca

se-li

ke m

ulti-

copp

er o

xida

se (L

MC

O) g

enes

in tw

o di

ffere

nt e

cosy

stem

sD

NA

; PC

R, c

loni

ng a

nd se

quen

cing

; prim

er p

air:

Cu1

AF/

Cu2

RN

J with

K2P

- tre

e w

ith lo

w b

oots

trap

supp

ort

mul

tigen

e fa

mily

in b

acte

ria; e

vide

nce

for e

ffec

tive

invo

lvem

ent o

f pro

cary

otic

LM

CO

s in

SOM

cyc

ling

Ger

man

y, E

urop

e; d

ecid

uous

fore

st (b

eech

-oak

) and

gr

assl

and;

org

anic

soil

laye

rs a

nd m

iner

al h

oriz

ons

Artz

et a

l. 2

009

effe

ct o

f fire

eve

nts o

n SO

M tu

rnov

er in

rela

tion

to p

heno

l ox

idas

e ac

tivity

and

the

dive

rsity

of l

acca

se e

ncod

ing

gene

sD

NA

; PC

R, c

loni

ng a

nd se

quen

cing

; prim

er p

air:

lccF

/lccR

NJ w

ith JT

T - t

ree

with

low

boo

tstra

p su

ppor

tfir

e le

ads t

o a

decl

ine

in p

heno

l oxi

dase

act

ivity

, but

an

incr

ease

in la

ccas

e ge

ne d

iver

sity

due

to a

n in

crea

sed

need

to

acc

ess t

he th

erm

ally

alte

red

SOM

Que

ensl

and,

Aus

tralia

; dec

iduo

us fo

rest

(euc

alyp

tus)

; top

so

il la

yers

and

subs

urfa

ce

Kel

lner

et a

l. 2

009

tem

pora

l cha

nges

in d

iver

sity

and

exp

ress

ion

patte

rns o

f fu

ngal

lacc

ase

enco

ding

gen

esD

NA

and

RN

A; P

CR

app

aoch

es; p

rimer

pai

rs

Cu1

F/C

u2R

or C

u1A

F/C

u2R

NJ w

ith K

2P -

tree

with

low

boo

tstra

p su

ppor

t; de

term

ing

the

phyl

ogen

etic

di

stan

ce u

sing

Uni

Frac

dist

inct

var

iatio

ns in

the

gene

and

tran

scrip

t div

ersi

ty

prof

iles a

nd a

gre

at im

pact

of t

he se

ason

al in

put o

f fre

sh

litte

r G

erm

any,

Eur

ope;

dec

iduo

us fo

rest

(bee

ch-o

ak);

orga

nic

soil

horiz

ons

Theu

erl e

t al.

201

0ef

fect

of r

educ

ed N

dep

ositi

on o

n fu

ngal

lacc

ase

enco

ding

ge

ne d

iver

sity

and

lign

in d

ecom

post

ions

DN

A, P

CR

, clo

ning

and

sequ

enci

ng; p

rimer

pai

r: C

u1F/

Cu2

Rno

t don

eev

iden

ce th

at tr

ansf

orm

atio

n pr

oces

ses i

n so

ils a

re w

ell

buff

ered

des

pite

the

mic

robi

al c

omm

unity

resp

onse

rapi

d to

en

viro

nmen

tal f

acto

rsG

erm

any,

Eur

ops;

con

ifero

us fo

rest

(spr

uce)

; soi

l hor

izon

s:

Oe,

Oa,

Ah

and

Bw

Chr

ist e

t al.

201

0fu

ngal

com

mun

ity c

ompo

sitio

n in

bul

k so

il an

d st

ones

of

di

ffer

ent f

ores

t- an

d so

il ty

pes

DN

A, P

CR

app

raoc

h; p

rimer

pai

rs: I

TS1F

/ITS4

an

d C

u1F/

Cu2

Rno

t don

edi

ffer

ence

s bet

wee

n ec

osys

tem

type

s and

bul

k so

il an

d st

ones

; coh

eren

ce a

nd c

ompl

emen

tarit

y us

ing

stru

ctur

al a

nd

func

tiona

l mar

ker g

enes

Ger

man

y, E

urop

e; d

ecid

uous

and

con

ifero

us fo

rest

(bee

ch,

spru

ce);

soil

horiz

on: B

Tab

le 5

.1: c

ontin

ued.

BO

WO

= b

lack

oak

-whi

teoa

k, S

MR

O =

suga

rmap

le-r

ed o

ak, S

MBW

= su

garm

aple

-bas

swoo

d, R

T-PC

R =

Rev

erse

Tra

nsci

ptas

ePC

R, Q

PCR

= q

uant

itativ

e PC

R, L

H-P

CR

= le

ngth

hete

roge

neity

PCR

, NJ w

ithK

2P =

nei

ghbo

urjo

inin

g, M

P =

max

imum

pars

imon

y, M

L =

max

imum

likel

ihoo

d, K

2P K

imur

a-2-

para

met

er

mod

el, J

TT =

Jone

s-Ta

ylor

-Tho

rnto

n m

odel

Ref

eren

ceO

bjec

tM

etho

dsPh

ylog

enet

ic a

naly

ses

Res

ults

Has

sett

et a

l. 2

008

pote

ntia

l of N

inpu

t to

redu

ce th

e ab

unda

nce

and

alte

r the

co

mpo

sitio

n of

bas

idio

myc

etes

in h

arw

ood

fore

sts

DN

A; Q

PCR

and

LH

-PC

R; p

rimer

pai

r: C

u1F/

Cu2

Rno

t don

eno

con

sist

ent e

ffec

t of N

dep

ostio

n; d

iffer

ence

s bet

wee

n fo

rest

floo

r and

min

eral

soil

due

to d

istri

butio

n of

sa

prot

roph

ic a

nd m

ycor

rhiz

al fu

ngi

Mic

higa

n, U

SA; d

ecid

uous

fore

st (s

ugar

map

le);

fore

st

floor

(org

anic

soil

laye

rs) a

nd m

iner

al so

il

Laub

er e

t al.

200

8ef

fect

of s

hort-

term

N fe

rtiliz

atio

n on

lacc

ase

gene

di

vers

ity a

nd c

ompa

rison

with

pre

viou

s stu

dies

DN

A; P

CR

, clo

ning

, seq

uenc

ing

and

QPC

R;

prim

er p

air:

Cu1

F/C

u2R

N

J; a

naly

ses o

f the

phy

loge

netic

dis

tanc

e be

twee

n th

e sa

mpl

es u

nsin

g U

niFr

acno

N e

ffec

t on

lacc

ace

gene

div

ersi

ty; l

acca

se g

ene

com

mun

ities

: nea

rly si

min

lar i

n m

iner

al so

ils,

phyl

ogen

etic

ally

diff

eren

t bet

wee

n lit

ter t

ypes

Mic

higa

n, U

SA; d

ecid

uous

fore

st (B

OW

O);

litte

r and

m

iner

al so

il

Kel

lner

et a

l. 2

008

dive

rsity

and

dis

tribu

tion

of b

acte

rial l

acca

se-li

ke m

ulti-

copp

er o

xida

se (L

MC

O) g

enes

in tw

o di

ffere

nt e

cosy

stem

sD

NA

; PC

R, c

loni

ng a

nd se

quen

cing

; prim

er p

air:

Cu1

AF/

Cu2

RN

J with

K2P

- tre

e w

ith lo

w b

oots

trap

supp

ort

mul

tigen

e fa

mily

in b

acte

ria; e

vide

nce

for e

ffec

tive

invo

lvem

ent o

f pro

cary

otic

LM

CO

s in

SOM

cyc

ling

Ger

man

y, E

urop

e; d

ecid

uous

fore

st (b

eech

-oak

) and

gr

assl

and;

org

anic

soil

laye

rs a

nd m

iner

al h

oriz

ons

Artz

et a

l. 2

009

effe

ct o

f fire

eve

nts o

n SO

M tu

rnov

er in

rela

tion

to p

heno

l ox

idas

e ac

tivity

and

the

dive

rsity

of l

acca

se e

ncod

ing

gene

sD

NA

; PC

R, c

loni

ng a

nd se

quen

cing

; prim

er p

air:

lccF

/lccR

NJ w

ith JT

T - t

ree

with

low

boo

tstra

p su

ppor

tfir

e le

ads t

o a

decl

ine

in p

heno

l oxi

dase

act

ivity

, but

an

incr

ease

in la

ccas

e ge

ne d

iver

sity

due

to a

n in

crea

sed

need

to

acc

ess t

he th

erm

ally

alte

red

SOM

Que

ensl

and,

Aus

tralia

; dec

iduo

us fo

rest

(euc

alyp

tus)

; top

so

il la

yers

and

subs

urfa

ce

Kel

lner

et a

l. 2

009

tem

pora

l cha

nges

in d

iver

sity

and

exp

ress

ion

patte

rns o

f fu

ngal

lacc

ase

enco

ding

gen

esD

NA

and

RN

A; P

CR

app

aoch

es; p

rimer

pai

rs

Cu1

F/C

u2R

or C

u1A

F/C

u2R

NJ w

ith K

2P -

tree

with

low

boo

tstra

p su

ppor

t; de

term

ing

the

phyl

ogen

etic

di

stan

ce u

sing

Uni

Frac

dist

inct

var

iatio

ns in

the

gene

and

tran

scrip

t div

ersi

ty

prof

iles a

nd a

gre

at im

pact

of t

he se

ason

al in

put o

f fre

sh

litte

r G

erm

any,

Eur

ope;

dec

iduo

us fo

rest

(bee

ch-o

ak);

orga

nic

soil

horiz

ons

Theu

erl e

t al.

201

0ef

fect

of r

educ

ed N

dep

ositi

on o

n fu

ngal

lacc

ase

enco

ding

ge

ne d

iver

sity

and

lign

in d

ecom

post

ions

DN

A, P

CR

, clo

ning

and

sequ

enci

ng; p

rimer

pai

r: C

u1F/

Cu2

Rno

t don

eev

iden

ce th

at tr

ansf

orm

atio

n pr

oces

ses i

n so

ils a

re w

ell

buff

ered

des

pite

the

mic

robi

al c

omm

unity

resp

onse

rapi

d to

en

viro

nmen

tal f

acto

rsG

erm

any,

Eur

ops;

con

ifero

us fo

rest

(spr

uce)

; soi

l hor

izon

s:

Oe,

Oa,

Ah

and

Bw

Chr

ist e

t al.

201

0fu

ngal

com

mun

ity c

ompo

sitio

n in

bul

k so

il an

d st

ones

of

di

ffer

ent f

ores

t- an

d so

il ty

pes

DN

A, P

CR

app

raoc

h; p

rimer

pai

rs: I

TS1F

/ITS4

an

d C

u1F/

Cu2

Rno

t don

edi

ffer

ence

s bet

wee

n ec

osys

tem

type

s and

bul

k so

il an

d st

ones

; coh

eren

ce a

nd c

ompl

emen

tarit

y us

ing

stru

ctur

al a

nd

func

tiona

l mar

ker g

enes

Ger

man

y, E

urop

e; d

ecid

uous

and

con

ifero

us fo

rest

(bee

ch,

spru

ce);

soil

horiz

on: B

Tab

le 5

.1: c

ontin

ued.

BO

WO

= b

lack

oak

-whi

teoa

k, S

MR

O =

suga

rmap

le-r

ed o

ak, S

MBW

= su

garm

aple

-bas

swoo

d, R

T-PC

R =

Rev

erse

Tra

nsci

ptas

ePC

R, Q

PCR

= q

uant

itativ

e PC

R, L

H-P

CR

= le

ngth

hete

roge

neity

PCR

, NJ w

ithK

2P =

nei

ghbo

urjo

inin

g, M

P =

max

imum

pars

imon

y, M

L =

max

imum

likel

ihoo

d, K

2P K

imur

a-2-

para

met

er

mod

el, J

TT =

Jone

s-Ta

ylor

-Tho

rnto

n m

odel

87

Chapter IV: The Sequence Study

copper binding region I (5´→ 3´) copper binding region II (5´→ 3´) copper binding region III (5´→ 3´)

amino acid sequence; * = variable positions amino acid sequence; * = variable positions amino acid sequence; * = variable positions

T S* V* H W H G F* F* Q G T* F* W Y H S* H I P* H P F* H L H G H

consensus sequence deduced from the amino acid sequence consensus sequence deduced from the amino acid sequence consensus sequence deduced from the amino acid sequence

ACN ASN RTN CAY TGG CAY GNN HTN YTN CAR GGN AMN HDY TGG TAY CAY RSN CAY ATH VHN CAY CCN NWN CAY YTN CAY GGN CAY

deduced primer sequence deduced primer sequence deduced primer sequence

(1) For CAY TGG CAY GGN TTY TTY CA Rev RTG RCT RTG RTA CCA RAA NGT(2) For CAY TGG CAY GGN TTY TTY CA Rev G RCT GTG GTA CCA GAA NGT NCC(3) For GGI ACI WII TGG TA- CAY WSI CA Rev CC RTG IWK RTG IAW IGG RTG IGG(4) For ACM WCB GTY CAY TGG CAY GG Rev G RCT GTG GTA CCA GAA NGT NCC(5) For ACM WCB GTY CAY TGG CAY GG Rev G RCT GTG GTA CCA GAA NGT NCC Rev TG ICC RTG IAR RTG IAN IGG RTG

R=A/G, Y=C/T, M=A/C, K=G/T, W=A/T, S=C/G, B=C/G/T, D=A/G/T, H=A/C/T, V=A/C/G, N=A/C/G/T, I = inosine

(1) D`Souza et al. 1996) primer pair: lcc1/lcc2 (3) Lyons et al. 2003 primer pair: LAC2FOR/LAC3REV (5) Kellner et al. 2007 primer pair: CU1AF/Cu2R/Cu3R(2) Luis et al. 2004 primer pair: Cu1F/Cu2R (4) Kellner et al. 2008 primer pair: CU1AF/Cu2R

cbr I cbr II cbr III cbr IV

150 bp 1000 - 1400 bp 200 bp

copper binding region I (5´→ 3´) copper binding region II (5´→ 3´) copper binding region III (5´→ 3´)

amino acid sequence; * = variable positions amino acid sequence; * = variable positions amino acid sequence; * = variable positions

T S* V* H W H G F* F* Q G T* F* W Y H S* H I P* H P F* H L H G H

consensus sequence deduced from the amino acid sequence consensus sequence deduced from the amino acid sequence consensus sequence deduced from the amino acid sequence

ACN ASN RTN CAY TGG CAY GNN HTN YTN CAR GGN AMN HDY TGG TAY CAY RSN CAY ATH VHN CAY CCN NWN CAY YTN CAY GGN CAY

deduced primer sequence deduced primer sequence deduced primer sequence

(1) For CAY TGG CAY GGN TTY TTY CA Rev RTG RCT RTG RTA CCA RAA NGT(2) For CAY TGG CAY GGN TTY TTY CA Rev G RCT GTG GTA CCA GAA NGT NCC(3) For GGI ACI WII TGG TA- CAY WSI CA Rev CC RTG IWK RTG IAW IGG RTG IGG(4) For ACM WCB GTY CAY TGG CAY GG Rev G RCT GTG GTA CCA GAA NGT NCC(5) For ACM WCB GTY CAY TGG CAY GG Rev G RCT GTG GTA CCA GAA NGT NCC Rev TG ICC RTG IAR RTG IAN IGG RTG

R=A/G, Y=C/T, M=A/C, K=G/T, W=A/T, S=C/G, B=C/G/T, D=A/G/T, H=A/C/T, V=A/C/G, N=A/C/G/T, I = inosine

(1) D`Souza et al. 1996) primer pair: lcc1/lcc2 (3) Lyons et al. 2003 primer pair: LAC2FOR/LAC3REV (5) Kellner et al. 2007 primer pair: CU1AF/Cu2R/Cu3R(2) Luis et al. 2004 primer pair: Cu1F/Cu2R (4) Kellner et al. 2008 primer pair: CU1AF/Cu2R

cbr I cbr II cbr III cbr IV

150 bp 1000 - 1400 bp 200 bp

cbr I cbr II cbr III cbr IV

150 bp 1000 - 1400 bp 200 bp

Figure 5.1: General arrangement of the laccase encoding gene structure including the four conserved copper binding regions (cbr I - IV) and the approximated length of the coding characters of the related fragments. For three of the four copper binding regions different published primer combinations are given considering the amino acid motifs they are deduced from, the corresponding consensus degenerated nucleotide sequences and the resulting forward (FOR) and reverse (REV) primer sequences.

A priori assumption of homology of nucleotide characters is the basis of molecular

phylogenetics (Koonin, 2005). There are two main types of homology - those ascribed to a

single gene of a direct, last common ancestor (orthology) and those resulting from a

lineage-specific duplication after separation of species (paralogy). In the latter case, gene

duplication events often result in the emergence of a multigene family within an organism

(Walsh & Stephan, 2001). Gene families differ in their size and location on genomes.

Many families consist of just a few very similar genes, while others involve a large number

of both closely related and more distant genes (Walsh & Stephan 2001).

Fungal laccase encoding genes belong to such a multigene family represented by

paralogous genes within one fungal genome (Kilaru et al., 2006; Courty et al., 2008). As

one of the first, Perry et al. (1993) described the presence of two laccase genes in the

genome of Agaricus bisporus. Several authors reported the existence of multiple laccase

gene copies within fungal genomes. For example, three district laccase genes were

characterized from Trametes sp. AH28-2 (Xiao et al., 2006), four from Thanatephorus

cucumeris (Rhizoctonia solani) (Wahleithner et al., 1996) and Pleurotus sajor-caju (Sodon

& Dobson, 2001), five from Trametes villosa (Yaver & Golightly, 1996; Yaver et al.,

1996), seven from Pleurotus ostreatus (Pezzella et al., 2009), 11 were identified in the

ectomycorrhizal fungus Laccaria bicolor (Courty et al., 2008) and the saprotrophic fungus

88

Chapter IV: The Sequence Study

Coprinopsis cinerea possesses a total of 17 different laccase encoding genes (Kilaru et al.,

2006). The members of a gene family show varying degrees of sequence similarities that

often reflect functional divergence (Walsh & Stephan, 2001). Beside the above mentioned

association with delignification, fungal laccases are involved in fruiting body formation

(Kües & Liu, 2000; Wösten & Wessel, 2006), pigment formation during asexual

development (Tsai et al., 1999), pathogenesis (Nosanchuk & Casadevall, 2003),

competitive interactions (Iakovlev & Stenlid, 2000) and soil organic matter cycling (Luis

et al., 2005b).

Phylogenetic analyses indicated that the cladistic arrangement of full length laccase protein

sequences does not follow fungal taxonomy, but rather reflect the function of the

respective isoenzyme (Hoegger et al., 2006). In the case of the commonly targeted short

length laccase encoding gene fragments it is possible to associate detected sequences from

environmental samples to sequences of known fungi, but phylogenetic analyses especially

with regards to a possible functional assignment are hampered by an unstable tree topology

(Luis et al., 2004; Blackwood et al., 2007; Kellner et al., 2009).

This review questions the suitability of the laccase encoding small gene fragments used in

many current studies for phylogenetic analyses. We evaluated the phylogenetic resolution

of these laccase gene fragment sequences (Table 5.2) for separating laccase encoding

genes of individual fungal taxa as compared phylogenetic relationships inferred from to

full length laccase protein sequences (Table 5.3) using best-fit models of phylogeny.

2. Data collection

2.1. Definition of the laccase encoding gene dataset

A total of 128 different basidiomycetous laccase encoding gene sequences (sequence

subset 1; SS1) were used for the present study (Table 5.2). Ninety sequences were obtained

from GenBank (National Centre for Biotechnology Information, NCBI) and assigned to 25

fungal species (Theuerl et al., unpublished data). Additionally, 30 sequences of the main

dataset derived from unknown fungi detected in soil samples of a spruce forest soil

(Theuerl et al., 2010), and eight sequences of Pinus taeda (Sato et al., 2001) were further

selected from GenBank. All sequences cover the laccase encoding gene fragment between

the copper binding regions (cbr) I and II. To establish a specific nucleotide database, the

ARB software package (Ludwig et al., 2004) was used for the sequence alignment. Based

89

Chapter IV: The Sequence Study

on the protein coding character of the analyzed genes, it was necessary to adjust the

alignment manually with BioEdit v. 7.0.9.1 (Hall, 1999), including cleavage of all non-

coding introns from the sequences. The resulting dataset consisted of 128 sequences

covering 142 unambiguously alignable nucleotide positions. For additional analyses the

nucleotide dataset SS1 was translated in the selected reading frame to the corresponding

protein sequence subset SS2 using BioEdit with resulted in 47 aligned amino acid

positions.

Table 5.2: Analysed fungal fruiting bodies used in this study, their order, trophic state, main characteristicts of the sequences and the corresponding accession numbers. ShortName Fungal species Order Trophic state Sequence

length [bp] No. of

sequencesNo. of introns intron position GenBank Acc. No.

CPI Chalciporus piperatus Boletales EM 142 4 EU882538 - EU882541XBA Xerocomus badius Boletales EM 142 5 EU882542 - EU882546PIN Paxillus involutus Boletales EM 142 3 EU882560 - EU882562

HAU Hygrophoropsis aurantiaca Boletales EM 139 1 EU882512142 2 EU882570, EU882571

INO Inocybe sp. Agricales EM 139 2 EU882513142 4 EU882572 - EU882575

ROC Russula ochroleuca Russulales EM 139 1 EU882516142 1 EU882554187 1 1 116-166 EU882576198 1 1 121-177 EU882590

MPE Micromphale perforans Agricales S 142 3 EU882547 - EU882549194 1 1 48-99 EU882579

LCO Lyophyllum connatum Agricales S 142 4 EU882550 - EU882553MSA Mycena sanguinolenta Agricales S 139 2 EU882509, EU882510

191 1 1 45-93 EU882578194 2 1 109-160 EU882582, EU882593

GSA Gymnopilus sapineus Agricales S 139 1 EU882511142 3 EU882563 - EU882565

CVI Calocera viscosa Dacrymycetales S 139 2 EU882514, EU882517142 5 EU882555 - EU882559195 1 1 118-170 EU882585199 1 1 121-177 EU882595

BED Boletus edulis GLM 60900 Boletales EM 142 3 EU882521 - EU882523APO Amanita porphyria GLM 45104 Agricales EM 142 3 EU882518 - EU882520HOL Hygrophorus olivaceoalbus GLM 44692 Agricales EM 142 4 EU882566 - EU882569

194 1 48-99 EU882584CCI Cortinarius cinnamomeus GLM 52057 Agricales EM 142 1 EU882528CVI Cortinarius variicolor GLM 61246 Agricales EM 142 3 EU882535 - EU882537HME Hebeloma mesophaeum GLM 62056 Agricales EM 142 1 EU882534RIN Russula integra GLM 52091 Russulales EM 190 1 1 120-168 EU882577

198 1 1 121-176 EU882589199 2 1 121-177 EU882592, EU882593

LLI Lactarius lignyotus GLM 44942 Russulales EM 197 1 1 121-175 EU882587197 1 1 118-175 EU882586

LDE Lactarius deterrimus GLM 46139 Russulales EM 194 2 1 121-172 EU882580, EU882581198 1 1 121-176 EU882588

RMA Rhodocollybia maculata GLM 45290 Agricales S 267 1 2 45-109, 113-172 EU882596338 2 3 25-111, 132-184, 188-243 EU882597, EU882598

CCA Cystoderma carcharias GLM 44986 Agricales S 142 3 EU882524 - EU882526 199 1 1 121-177 EU882591

CDI Clitocybe ditopa GLM 52151 Agricales S 142 1 EU882527AES Agaricus essettei GLM 42150 Agricales S 142 1 EU882529ASI Agaricus silvaticus GLM 45325 Agricales S 142 4 EU882530 - EU882533

UF unknown fungi soil sequences 139 2 EU882599, EU882611, EU882615

142 15 EU882621, EU882630, EU882631, EU882636, EU882641, EU882644, EU882652, EU882653, EU882655, EU882656, EU882657, EU882658, EU882659, EU882662, EU882663

187 2 1 119-166 EU882672, EU882673190 1 1 119-169 EU882676191 1 1 45-93 EU882678194 1 1 48-99 EU882720194 2 1 109-160 EU882721, EU882722195 1 1 118-170 EU882680198 1 1 121-176 EU882692199 2 1 121-177 EU882699, EU882701201 1 1 121-179 EU882701

Pta Pinus taeda Coniferales 142 8 AF132119-AF132126

90

Chapter IV: The Sequence Study

2.2. Definition of the laccase protein dataset

Overall 147 different full length laccase protein sequences (sequence subset 3; SS3) from

44 different fungal and one plant taxa (Table 5.3) were used in the presented study. The

database of NCBI was searched for full length laccase protein sequences from

Basidiomycota. Sequences were selected by the presence of the four conserved copper

binding regions (cbr) typical for laccases (Thurston, 1994; Valderrama et al., 2003; Wong,

2008). In accordance with Hoegger et al. (2006), for phylogenetic analysis only complete

sequences were kept, i.e. protein sequences had to be alignable over considerable amino

acid sequence stretches. From the available laccase protein sequences from Trametes

gallica (Dong et al., unpublished), only one sequence (AAW65489) was integrated in this

phylogenetic study because the remaining four sequences (AAW65485-AAW65488) were

lacking representative sequence regions. Furthermore, only one representative of identical

sequences (100% amino acid identity) from one and the same species was kept. Due to the

lack of available information, it was impossible to distinguish between allelic and non-

allelic sequences. Therefore we used all sequences with identities smaller than 100% for

our analysis. For phylogenetic analysis an alignment was created with the ClustalW tool in

MEGA v. 4.1 (http://www.megasoftware.net/ index.html; Kumar et al., 2008) using default

settings for multiple sequence alignments. The obtained alignment was adjusted manually

with BioEdit and consisted of 147 sequences covering 640 alignable aminos acid positions.

Based on this alignment, only conserved regions throughout which the assignment of

positional homology was possible were used for phylogeny reconstruction; all other

regions were excluded. For a subsequent approach we selected the sequence fragment

between cbr I (HWH…) and cbr II (…HSH) of the full length protein amino acid

sequences (SS4) (55 alignable amino acid characters) because most studies focused on this

sequence fragment.

2.3. Estimation of evolutionary models and sequence phylogeny

In the context of molecular phylogeny, ‘best-fit’ models of nucleotide or amino acid

substitution were selected for all sequence datasets with the programs ModelTest v. 3.7

(http://darwin.uvigo.es/software/modeltest.html; Posada & Crandall, 1998) or ProtTest v.

2.1 (http://darwin.uvigo.es/software/prottest.html; Abascal et al., 2005) using the Akaike

Information Criterion (AIC; Akaike, 1974) implemented in these programs and starting

with a BIONJ generated tree (Gascuel, 1997).

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Table 5.3: Fungal taxa (and/or strains) examined in the study, their trophic state (S = saprtophic fungi, WR = white root fungi) and their corresponding full length laccase protein sequences with database accession numbers. ShortName Species Order Trophic Accession-No. Protein Reference

state Protein sequence

Abi Agaricus bisporus Agaricales S Q12541 LAC1 Perry et al. 1993Q12542 LAC2 Perry et al. 1993

Abb Agaricus bisporus var. bisporus Agaricales ACE73659 putative laccase 3 Billette et al. unpublished

Cci Coprinopsis cinerea Agaricales S DAA04506 - DAA04522 laccase 1 - 17 Kilaru et al. (2006)(strain okayama7#130)

Cco Coprinellus congregatus Agaricales S CAB69046 acidic laccase Kim et al. (2001)CAD62686 acidic laccase precursor Han et al. unpublished

Vvo Volvariella volvacea Agaricales S AAO72981 laccase 1 Chen et al. (2004)AAR03581 - AAR03585 laccase 2 - 6 Chen et al. unpublished

Cbu Cyathus bulleri Agaricales WR ABW75771 laccase Salony et al. (2008)

Fve Flammulina velutipes Agaricales WR AAR82931 laccase Zhang et al. (2004)BAE80732 laccase 2 Watanabe et al. unpublished

Led Lentinula edodes Agaricales WR BAB83131 laccase 1 Sakamoto et al. (2008)BAC06819 laccase Sato et al. unpublishedBAB84355 laccase Sato et al. unpublishedBAB83132 laccase 2 Sato et al. unpublishedBAB83133 laccase 2' Sato et al. unpublished

Led-NRRL Lentinula edodes NRRL 22663 Agaricales AAT99286 LAC1AVT Marabottini et al. unpublishedAAT99287 LAC1BVT Marabottini et al. unpublishedAAT99288 LAC1CVT Marabottini et al. unpublishedAAT99289 LAC1DVT Marabottini et al. unpublishedAAT99290 LAC2VT Marabottini et al. unpublishedAAT99291 LAC3VT Marabottini et al. unpublished

Led-L54 Lentinula edodes L54 Agaricales AAF13037 laccase Zhao et al. (1999)AAF13038 laccase Zhao et al. (1999)

Pna Pholiota nameko Agaricales WR ABR24264 laccase Zhou and Ding unpublished

Ple Pleurotus eryngii Agaricales WR AAV85769 laccase precursor Rodriguez et al. (2008)ABB30169 laccase precursor Rodriguez et al. unpublished

Plo Pleurotus ostreatus Agaricales WR Q12729 LAC1_PLEOS Giardina et al. (1995)Q12739 LAC2_PLEOS Giardina et al. (1996)AAR21094 laccase Zhang and Ma et al. unpublishedCAC69853 laccase Palmieri et al. (2003)CAR48258 phenol oxidase Pezzella et al. (2009)CAR48257 phenol oxidase Pezzella et al. (2009)

Plp Pleurotus pulmonarius Agaricales WR AAX40733 laccase 2 Yau and Chiu unpublishedAAX40732 laccase 6 Yau and Chiu unpublished

Psc Pleurotus sajor-caju Agaricales WR CAD45377 - CAD45381 laccase 1 - 5 Tang et al. unpublished

Pls Pleurotus sapidus Agaricales WR CAH05069 laccase precursor Zorn et al. unpublished

Psp-Flo Pleurotus sp. 'Florida' Agaricales WR CAA06291 laccase Giardina et al. (1999)CAA80305 laccase Giardina et al. (1995)

Sco Schizophyllum commune Agaricales WR BAA31217 Hatamoto et al . unpublished

Tcu Thanatephorus cucumeris Cantharellales S P56193 LAC1_THACU Wahleithner et al. (1996)Q02075 LAC2_THACU Wahleithner et al. (1996)Q02079 LAC3_THACU Wahleithner et al. (1996)Q02081 LAC4_THACU Wahleithner et al. (1996)

Csu Ceriporiopsis subvermispora Polyporales WR AAC97074 laccase precursor Karahanian et al. (1998)

Cun Cerrena unicolor FCL139 Polyporales WR ACL93462 Lac1 Janusz et al. unpublished

Gfo Ganoderma fornicatum Polyporales WR ABK59827 laccase Tai unpublishedABK59826 laccase Tai unpublished

Glu Ganoderma lucidum Polyporales WR AAR82934 laccase Zhang and Ma unpublishedAAG17009 laccase Joo et al. (2008)ABK59822 laccase Tai unpublishedABK59823 laccase Tai unpublished

Gts Ganoderma tsugae Polyporales WR ABK59825 laccase Tai unpublishedABK59824 laccase Tai unpublished

Lti Lentinus tigrinus Polyporales WR AAX07469 laccase Schmatchenko et al. unpublished

Pru Panus rudis Polyporales WR AAW28932 laccase A Hong et al. unpublishedAAR13230 laccase Zhang et al. (2006)

Pra Phlebia radiata Polyporales WR CAA36379 laccase Saloheimo et al. (1991)CAI56705 Lac2 Makela et al. (2006)

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Chapter IV: The Sequence Study

Table 5.3: continued.

ShortName Species Order Trophic Accession-No. Protein Referencestate Protein sequence

Ppb Polyporus brumalis Polyporales WR ABN13591 LAC1 Ryu et al. unpublishedABN13592 LAC2 Ryu et al. unpublished

Ppc Polyporus ciliatus Polyporales WR AAG09229 LCC3-1 Schnee et al. unpublishedAAG09230 LCC3-2 Schnee et al. unpublishedAAG09231 LCC3-3 Schnee et al. unpublished

Pci Pycnoporus cinnabarinus Polyporales WR AAG13724 laccase Otterbein et al. unpublishedAAC39469 laccase Eggert et al. (1996), (1998)AAD49218 laccase Temp et al. (1999)

Pco Pycnoporus coccineus Polyporales WR BAB69775 laccase Hoshida et al. (2001)

Psa Pycnoporus sanguineus Polyporales WR AAR20864 laccase Zhao et al. unpublished

Rmi Rigidoporus microporus (Fomes Polyporales WR AAO38869 laccase Liu et al. (2003)CAE81289 laccase Rizzi et al. unpublishedAAQ82021 laccase Liu and Qian unpublished

Tga Trametes gallica Polyporales WR AAF70119 laccase Yague et al unpublished(Coriolopsis gallica) ABD93940 laccase Huang et al. unpublished

AAW65489 laccase Dong et al. unpublished

Thi Trametes hirsuta Polyporales WR Q02497 LAC1 Kojima et al. 1990ACC43989 laccase Cherkashin et al. unpublishedAAL89554 laccase Koroleva et al. unpublished

Tpu Trametes pubescens Polyporales WR AAM18408 laccase 1A Galhaup et al. 2002AAM18407 laccase 2 Galhaup et al. 2002

Tsp-420 Trametes sp. 420 Polyporales WR AAW28936 laccase A Tong et al. (2007)AAW28937 laccase B Tong et al. (2007)AAW28938 laccase C Tong et al. (2007)AAW28939 laccase D Hong et al. (2007)ABB21020 laccase E Tong et al. (2007)

Tsp-AH28-2 Trametes sp. AH28-2 Polyporales WR AAW28933 laccase A Xiao et al. (2006)AAW31597 laccase B Xiao et al. (2006)AAW28934 laccase C Xiao et al. (2006)AAW28935 laccase D Tong et al. (2007)

Tsp-C30 Trametes sp. C30 Polyporales WR AAM10738 LAC1 Klonowska et al. (2005)AAM66349 LAC2 Klonowska et al. (2002)AAR00925 LAC3 Klonowska et al. (2005)

Tsp-I62 Trametes sp. I-62 Polyporales WR AAQ12270 laccase Gonzalez et al. 2003(CECT 20197) AAQ12269 laccase Mansur et al. 1997; Gonzalez et al. 2003

AAB63443 phenoloxidase Mansur et al. 1997AAQ12267 laccase Gonzalez et al. 2003

Ttr Trametes trogii Polyporales WR CAC13040 laccase Colao et al. (2003)(Funalia trogii)

Tve Trametes versicolor Polyporales WR Q12718 LAC2 Ong et al. 1997Q12719 LAC4 Joensson et al. 1995Q12717 LAC5 Ong et al. 1997BAA23284 laccase Mikuni et al. 1997AAC49828 laccase I Ong et al. 1997AAL00887 laccase 1 O'Callaghan et al. 2002AAL07440 laccase B precursor Jolivalt et al. 2005AAW29420 laccase 1 Necochea et al. 2005CAA77015 laccase Jonsson et al. unpublishedAAL93622 laccase III Schuren et al. unpublishedBAA22153 laccase Iimura and Mikuni unpublishedCAD90888 unnamed Patent: EP 1300469-A 09-APR-2003

Tvi Trametes villosa Polyporales WR Q99044 LAC1 Yaver et al. 1996Q99046 LAC2 Yaver et al. 1996Q99049 LAC3 Yaver and Golightly 1996Q99055 LAC4 Yaver and Golightly 1996Q99056 LAC5 Yaver and Golightly 1996

PM1 basidiomycete PM1 (CECT 2971) CAA78144 laccase Coll et al. (1993)

Pta Pinus taeda Coniferales Plant AAK37823-AAK37830 Sato et al. 2001

To infer evolutionary relationships among the sequences we used MrBayes v. 3.1.2

(http://mrbayes.csit.fsu.edu/; Ronquist & Huelsenbeck, 2003). Bayesian estimation of

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phylogeny considers a maximum-likelihood function based on the Bayesian theorem

coupled with a Metropolis Coupled Markov Chain Monte Carlo algorithm to approximate

the posterior probabilities of tree topologies (Huelsenbeck & Ronquist, 2001). While for

the Bayesian analysis of SS1 the GTR (General Time Reversible) model of nucleotide

substitution (Tavare, 1986) was used, the Bayesian analyses of SS2-SS4 were carried out

with the WAG model of amino acid substitution (Whelan & Goldman, 2001), considering

an estimated proportion of invariable site (+I) and a gamma distribution of four categories

(+G) for all analyses. Additionally, for the SS3 dataset the observed amino acid frequency

(+F) was determined as an important parameter. All Bayesian analyses were run with four

independent chains, with every 200th tree sampled over three million generations,

discarding all trees before the burnin of 150,000 generations. To ensure that all runs

converged on the log-likelihood stationary level, we conducted three simultaneous,

independent analyses. Phylogenetic support for the sequence data was derived from

Bayesian posterior probabilities (PP) and bootstrap values (bsv) obtained from 1,000

pseudoreplicates of maximum-parsimony (MP) analyses conducted with MEGA, whereby

PP ≥ 0.90 (threshold) and MP-bsv ≥ 85% were deemed significant. For the MP

phylogenetic tree estimation we used the default setting from MEGA (close-neighbor-

interchange (CNI) with search level one and random addition trees with ten replications).

Additionally we calculated the parsimony informative and variable sites of the utilized

sequence datasets. For visualization of the phylogenetic tree the program TreeDyn

(http://www.treedyn.org/; Chevenet et al., 2006) was used. In the tree figures, we have

highlighted groupings discussed in the text by boxes and labelled monophyletic clades of

at least two sequences with a clade symbol “/”. To investigate causes of the lack of

cladistic resolution, we performed single heuristic maximum-parsimony analyses in

PAUP* v. 4beta10 (Swofford, 2003). The maximum number of saved optimal tree

solutions was not restricted, swapping was done in the tree bisection- reconnection (TBR)

mode, and we calculated the parsimony tree length (TL), homoplasy, consistency and

retention indices (HI, CI, and RI, respectively). Exhaustive searches of tree space with

more than 12 sequences are not feasible using PAUP* and are refused by this program.

The single MP analysis for SS4 had to be stopped after 20 hours, when already 75,800

trees had been retained and almost all had still to be swapped, indicating exponential rise

of saved trees. All results are summarized in Table 5.4. While with no replications and no

exhaustive tree space evaluation we cannot be sure that we found the actual most

parsimonious tree in these runs, we apparently hit large tree islands in all four cases.

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Table 5.4: Results of simple heuristic maximum-parsimony analyses on the four datasets presented in this study.

sequence subset SS1 sequence subset SS2 sequence subset SS3 sequence subset SS4nucleotide codon aa full length protein short lenght protein

alignment sites 142 47 640 55parsimony informative sites 105 34 468 34variable uninformative sites 8 6 67 4parsimony tree lenght (TL) 1784 475 8067 465min possible TL 263 193 3052 182max possible TL 4983 1609 19378 1320found 1 tree island of 7512 3792 8062 >75800computing duration on same computer

00:16:24.9 01:52:06.4 02:56:05.6 20:00:00.0 (stopped)

homoplasy index (HI) 0.853 0.594 0.622 0.609consistency index (CI) 0.147 0.406 0.378 0.391retention index (RI) 0.678 0.801 0.693 0.751

3. What can the commonly used laccase encoding gene fragment tell us?

The multicopy, paralogous character of laccase encoding genes: Most fungal fruiting

bodies considered in this study reveal the presence of more than one partial/putative

laccase encoding gene (plac) (Table 5.2). For example, the fungus Calocera viscosa (CVI)

comprises nine different paralogous laccase encoding gene sequences which clearly cluster

separately from each other with exception of the genes plac 8 (EU882558) and plac 9

(EU882556) which show a nucleotide sequence identity of 93% (Figure 5.2, left tree). For

ten other fungal taxa laccase encoding genes were found which show a sequence identity

over 90% (e.g., APO plac 1 and 2, CCA plac 2 and 4, CVA plac 1 and 2, MSA plac1 and 2,

RIN plac 2 and 3, RMA plac 2 and 3, XBA plac 3 and 4, ASI plac 2, 3 and 4, and HOL

plac 1, 2 and 3). All other sequences obtained from the fungi are clearly different from

each other. The observed high sequence identity of two or three genes obtained from the

same fungus could indicate that these genes originated from a recent duplication (Walsh &

Stephan, 2001). Such gene duplication events were also reported by Kilaru et al. (2006)

and Courty et al. (2008) and they are thought to be an important mechanism of creating

evolutionary novelties (new genes or new genetic systems) (Walsh & Stephan, 2001)

according to the birth-and-death-model for the evolution of multigene families (Nei &

Rooney, 2005). This model assume that new genes are created by gene duplication and

some of these genes are maintained in the genome because of the new gene function

aquired (keeping the original function while allowing the duplicate copy to be removed

from such constraints and potentially to be used as raw material for new novelties) whereas

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Chapter IV: The Sequence Study

other genes are inactivated or deleted from the genome (Walsh & Stephan, 2001; Nei &

Rooney, 2005). The occurence of pseudogenes, large gene internal deletions and

alternation of splice junctions leading to frame shifts, deletion of essential amino acids

and/or protein truncations, indicating that some of the duplicated laccase genes might be

eliminated from the genome over time (Kilaru et al., 2006; Courty et al., 2008). For the

sequences analysed in this study it is not possible to identify potential pseudogenes

because all utilized nucleotide sequences are derived from genomic DNA and were not

transcriptionally and/or translationally verified due to the major efforts of fungal

cultivation and their biochemical characterization. Besides the assumed gene duplications

events, the occurrence of multiple paralogous copies of laccase encoding genes varying in

the degree of sequence similarity often reflects functional divergence (Walsh & Stephan,

2001). The constructed phylogenetic tree (Figure 5.2, left tree) shows that the sequence

arrangment does not reflect taxonomy or ecological guilds (saprotrophic vs. mycorrhizal)

of the fungi they are derived from. The phylogenetic tree of the nucleotide sequences

possibly depicts functional relationships of laccases due to the separate distribution of

paralogous laccase genes of the same fungus.

Assessing the diversity of laccase containing fungi in environmental samples: Recently,

most soil ecological studies focused on the molecular biological processing of soil samples

to obtain nucleotide sequences (e.g., laccase encoding gene sequences) of unknown fungal

species of the entire community and subsequently sought homologs in fungal fruiting

bodies to possibly relate sequences found in soil samples to references specimens (Table

5.1; Luis et al., 2005b; Kellner et al., 2009).

Figure 5.2: Bayesian tree calculated from the coding region of the laccase encoding gene fragment

(A) and the corresponsing amino acid sequences (B) obtained from soil samples as well as fungal

fruiting bodies (Table 5.2) using the GTR model for nucleotide sequenes or the WAG model for

the amino acid sequences. Nulcotide sequences are given with their Genbank accession number,

the corresponding protein ID (in brackets), a short name (Table 5.2) and a putative gene name.

Protein sequences are given with their Genbank protein ID, the corresponding nucleotide accession

number (in brackets), a short name (Table 5.2) as well as a putative protein name. Discussed cases

were emphasized by boxes and labelled monophyletic clades of at least two sequences with a clade

symbol “/”. Branch support derived from Bayesian posterior probabilities (PP) and bootstrap values

(bsv) obtained from 1,000 pseudoreplicates of maximum-parsimony (MP) analyses. Non-supported

(n.s.) means monophyletic topology with less that 0.90 PP and less that 85% MP-bsv.

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Chapter IV: The Sequence Study

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Figure 5.2: Bayesian tree calculated from the coding region of the laccase encoding gene fragment (A) and the corresponsing amino acid sequences (B).

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Chapter IV: The Sequence Study

Theuerl et al. (2010) detected a total of 127 different laccase encoding gene sequences

(defined as operational taxonomic units, OTUs) in soil samples of a spruce forest stand.

Less than one forth (30 of 127 soil sequences used in this study) could be related to fungal

fruiting body references (Figure 5.2, left tree). The boxes for clades /2a-nt, /2b-nt, and /2c-

nt contain sequences from soil samples (e.g., EU882720, EU882699 and EU882599) that

correspond to at least two different fungal taxa with different ecological roles (litter

decomposers: Mycena sanguinolenta, Cystoderma carcharias and Micromphale perforans,

wood decomposers: Gymnopilus sapineus and Calocera viscosa, ectomycorrhizal fungi:

Inocybe sp. and Hygrophoropsis aurantiaca). This is even more pronounced at the level of

the corresponding protein sequences (Figure 5.2, right tree, /2a-aa, /2b-aa, and /2c-aa). A

comparison of both trees (nucleotide vs. amino acid) reveals that (i) the tree topologies and

phylogenetic supports are partly incongruent (Figure 5.2, boxes 1a-g: 1f-aa is not a clade

anymore, clades /1a-aa, /1c-aa, /1d-aa, /1e-aa and /1g-aa are not supported) and (ii) both

the nucleotide tree (Figure 5.2, left tree) and the corresponding amino acid tree (Figure 5.2,

right tree) showed massive polytomies in the “deeper” branches. The phylogenetic

information content from the nucleotide to the amino acid characters decreases, mainly due

to the effects of the degenerated universal code (Simmons et al., 2002, 2004). Irrespective

of the causes of lacking phylogenetic resolution, the identity of sequences from different

fungal taxa severely hampers the assignment of detected laccase encoding gene sequences

with the fungal taxonomy and thus with ecological functions respresented by the fungi

(e.g., saprotrophic vs. mycorrhizal). Based on the multicopy, homologous character of

laccase encoding genes and hence their multifunctional potential, the sequence similarity

from fungi occupying different ecological niches might be due to convergent evolutionary

events represented by orthologous genes that fulfill the same functions in different fungi.

The restricted amount of phylogenetic information: The commonly applied molecular

ecological laccase approach is restricted on the detection of the laccase encoding gene

fragment between the cbr I and II. The sequence length of this fragment differs depending

on the occurrence of introns, whereby the coding region usually covers around 150

nucleotide characters (Figure 5.1). In contrast, as roughly calculated the whole laccase

encoding gene consists of up to 4,000 nucleotide characters whereof about 1,500 ± 200

nucleotides code for the protein (e.g., see sequences from Coprinopsis cinerea, Kilaru et

al., 2006). Evidently, with extending the length of available nucleotide sequences and

hence with an increase in the differences among sequences, the amount of phylogenetically

informative characters will increase. At this point the sequence fragments we are getting

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from environmental samples only offer a small fraction (ca. 10%) of possible phylogenetic

informative positions infering a lack of phylogenetic resolution.

4. Is there a lack of phylogenetic resolution?

To verify the assumed phylogenetic lack of information we performed an analysis using

147 full length laccase protein sequences (SS3) derived from NCBI that consists of 640

alignable amino acid characters with 73% parsimony-informative sites and compared this

with the corresponding short length protein sequence data set (SS4) covering 55 alignable

charaters (Table 5.4, Figure 5.3). The comparison reveals that only the phylogenetic

arrangment of SS3 (Figure 5.3, left tree) is potentially in accordance with an assumed

function of the respective enzymes which is in agreement with Hoegger et al. (2006).

Additionally, at the level of the full length protein dataset, there is a high resolution of

different fungal taxa and/or different laccase proteins from one fungal taxon (Figure 5.3;

left tree). Both the observed phylogenetic separation based on potentially functional

characteristics as well as the high resolution of different laccase proteins almost completely

disappears towards the short length protein dataset (Figure 5.3, right tree). For better

illustration of this point, we select some examples that are covered below.

Sequences from one fungal taxon cluster separately in SS3: In the upper part of the full

length laccase protein tree (Figure 5.3; left tree) sequences from one fungal taxon can be

found that are clearly separated from each other (e.g., laccase A-D from Trametes sp.

AH28-2 or LAC1 and LAC2 from Trametes villosa; boxes 1a-fl and 1b-fl). Laboratory

studies of these isoenzymes showed differences in the expression and enzymatic properties

suggesting variabilities in the catalytic activity under different physiological or

environmental conditions (Yaver & Golightly, 1996; Yaver et al., 1996). This indicates

that these isoenzymes fulfill different functions. Furthermore, the induction of laccase

genes by metal ions and phenolic compounds have been suggested to result from the

presence of specific regulatory sites such as metal-responsive elements (MRE) and/or

xenobiotic response elements (XRE) in the promoter regions of the genes which indicates

different strategies of substrate detoxification (Xiao et al., 2006).

Sequences from different fungal taxa cluster together in SS3: Laccase sequences from

basidiomyctes PM1 (CAA78144, Coll et al., 1993), Trametes sp. C30 (LAC1, AAM10738,

Dedeyan et al., 2000) and Trametes trogii (CAC13040, Colao et al., 2003) (Figure 5.3, left

tree, /1c-fl) are an example that is supportive of the functional clustering of the laccase

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protein sequences due to the high sequence similarity as well as comparable biochemical

characteristics of the enzymes (constitutive laccase activity, pH optima at 4.5, low redox

potential). Additionally, in the lower part of the tree there is a cluster containing possibly

orthologous laccases from two litter decomposing fungi (Agaricus bisporis and

Coprinopsis cinerea), two wood decomposing fungi (Pleurotus ostreatus and Pleurotus

sajor-caju) and the plant pathogen Thanatephorus cucumaris (Figure 5.3, left tree,

unsupported /1d-fl). The close relationship of these sequences indicates the occurrence of

orthologous genes encoding poteins that fulfill the same function (Hoegger et al., 2006).

Clade dissolution in SS4: The phylogenetic resolution reflecting functional characteristics

of the respective full length laccase proteins almost completely disappeared at the level of

the short length protein dataset (Figure 5.3, right tree). The distinct seperation of different

laccase proteins from one fungal taxon (Figure 5.3, left tree, boxes 1a-sl and 1b-sl) or of

laccase proteins from different fungal taxa (Figure 5.3, left tree, clade /1c-sl) does not exist

within the pylogenetic tree of the short length protein dataset, but is rather replaced by a

polytomic tree topology (Figure 5.3, right tree, boxes 1a-sl, 1b-sl and 1c-sl). The

aforementioned cluster containing laccases from fungi with different ecological roles

(Figure 5.3, left tree, unsupported clade /1d-fl) splits into two separate clusters when only

the sequence fragment between the cbr I and II was phylogenetically analysed (Figure 5.3,

right tree, unsupported clade /1d-sl and /partial 1d-sl). Furthermore, laccase protein

sequences from different fungi cluster distinctly different from each other at the full length

protein sequence level (Figure 5.3, left tree, clades /1e-fl contains laccase sequences from

Volvariella volvacea and Coprinopsis cinerea) and appeared phylogenetically closer at the

short length protein sequence level (Figure 5.3, right tree, box 1e-sl).

Figure 5.3: Bayesian tree calculated from full length laccase protein sequences (A) and the corresponding short length fragment (B) obtained from Genbank (NCBI) using the WAG model for the amino acid sequences. Protein sequences are given with their Genbank protein accession number, a short name (Table 5.3) as well as the according protein name (if available). Discussed cases were emphasized by boxes and labelled monophyletic clades of at least two sequences with a clade symbol “/”. Branch support derived from Bayesian posterior probabilities (PP) and bootstrap values (bsv) obtained from 1,000 pseudoreplicates of maximum-parsimony (MP) analyses. Non-supported (n.s.) means monophyletic topology with less that 0.90 PP and less that 85% MP-bsv.

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5. Conclusions Comparison of a full length laccase protein (SS3) and a derived short length laccase

protein dataset (SS4), showed that there is evidently a lack of phylogenetic resolution

power towards the short length protein dataset. We calculated a loss of ca. 92% of the

parsimony-informative sites from the full length towards the short length protein dataset.

Therefore, it is evident that the currently amplified laccase encoding gene fragments do not

contain sufficient information for phylogenetic inference. The Bayesian topologies (figures

5.2 and 5.3), especially when based on SS2 and SS4, show a high degree of polytomy

(non-resolved comb architecture). Both contain the least total amount of sites in the

alignment. The heuristic parsimony search, however, revealed trees with lower homoplasy

indices (HI) for SS1 and SS3 (Table 5.4). Actually, the phylogenetic tree based on SS1

indicated a huge homoplasy of characters. We conclude that in the short protein sequences,

the relatively little amount of phylogenetic data contains information that leads to equally

parsimonious trees that in consensus topologically cancel each other out, so a bad

phylogenetic resolvedness becomes even worse. This relates to similar behaviour in the

Bayesian environment (expressed in short and unsupported branching) and in the MP

bootstrap analysis. In MP probably most bootstrap pseudoreplicates will hit even worse

conflicts, given that each pseudoreplicate is a reweighted smaller subset of the already

conflict-rich data. Due to the results of this study, it is inadvisable to keep on conducting

phylogenetic analyses to relate detected short laccase encoding gene fragments of

unknown organisms from environmental samples to reference sequences of known species

that were characterized by the short sequence fragment only. It would be helpful to assign

the fragment to available well-characterized full length laccase gene sequences. But

unfortunately many available full length sequences originate from white-rot wood

decaying fungi which are unlikely to be important in soils where litter decomposers and

mycorrhizal fungi should dominate.

While this review discloses the phylogenetic inadequacy of the small laccase encoding

gene fragment currently used for many soil ecological studies (see Table 5.1), it still does

not invalidate the hitherto published studies which demonstrate the ecological force to

characterize the spatial and temporal variations of laccase- or LMCO-containing fungal

and bacterial communities in the heterogeneous soil environment. Certainly, there is a

great diversity of laccase and LMCO genes out there, some of which are directly linked to

the actual process of biopolymer breakdown. The future challenge will be to clearly verify

laccase genes encoding true extracellular efficient enzymes (responsible for the phenol

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Chapter IV: The Sequence Study

oxidase activity) that can be used for creating new primers targeting longer gene fragments

of specific fungal taxa. We are confident that the ongoing efforts of whole genome

sequencing projects and the related gene annotations benefit the development of such new

molecular biological tool. Given the enormous ecological importance of fungal

decomposers, particularly in forest ecosystems, with respect to the cycling of elements,

future studies require multidisciplinary approaches combining organismic studies with

molecular “omic” analyses and finally with experimental studies that will certainly

improve our knowledge of the biological or more precise enzymatic mechanisms of the

decomposition process.

Acknowledgements

This work was financially supported by the German Research Foundation (DFG -

Deutsche Forschungsgemeinschaft, PAK 12, BU 941/9-1 and Grant BU 941/11-1, BU

941/17-1). We are indebted to Peter Otto (University of Leipzig) for his helpful

characterization of the collected fungal species and to the State Museum of Natural History

Görlitz (Germany) for the supplying specimen fungal taxa from the herbarium. We are

grateful to Bettina Schlitt for her help with the laboratory work. We thank Derek Peršoh

for their help with editing the manuscript.

104

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Summary

Summary: Recent fungal laccase research and future challenges

The here presented cumulative dissertation provides a critical, holistic view of the fungal

laccase research in the 21st century. This work primarily investigated an environmental

study considering possible effect of reduced nitrogen deposition on the diversity structure

of fungal laccase encoding genes and their related enzymes as they are involved in the

degradation of recalcitrant plant-derived compounds, an ecologically important process. In

this case, the objectives of this thesis were (1) to exhaustively summarize and discuss

previous and current classical ecological, enzymatic and molecular-biological studies to

define the general framework for the environmental study, (2) to carry out and evaluate the

study itself and (3) to expose ecological and especially methodological hindrances of the

resent research to deductively point up future challenges.

Generally, one central challenge in soil microbial ecology is to link the fungal diversity to

the degradation process of recalcitrant plant-derived compounds, a process of truly global

importance. Among the recalcitrant natural polymers, lignin is the second most abundant

component of plant litter and its degradation is mainly restricted to basidiomycetes and

their potential to produce ligninolytic enzymes such as laccases. Biochemically, fungal

laccases use the redox potential of four copper ions and catalyze the substrate oxidation

concurrent to the reduction of molecular oxygen (O2) to water (H2O) resulting in the

formation of radicals which undergo further reactions like (de-) polymerisation (e.g., lignin

degradation of wood and litter as well as the formation of soil organic matter). Structural

analyses of the amino acid sequences have shown that four copper binding regions (cbr)

and their general distribution within the protein sequence are strongly conserved enabling

the design of degenerated primer pairs particularly for the gene fragment between the cbr I

and II to detect the diversity and distribution of laccase-containing microbes (fungi and

bacteria) within environmental samples. Bases on these circumstances, Chapter I

synthesized results from previous and current ecological studies demonstrating that the

physicochemical and biotic heterogeneity of soil systems offer a broad range of

possibilities for affecting and controlling the laccase-containing fungal community

structure and therefore the relative potential pool of phenol oxidases that in turn impact the

decomposition process. Combined molecular-biological, enzymatic and biogeochemical

analyses have shown that the abundance and distribution of laccase-containing fungi are

114

Summary

deeply affected by the availability of organic energy sources. In that account, it was shown

that functional guilds (saprotrophic and mycorrhizal fungi) occupy different ecological

niches due to their nutritional pathways resulting in spatial and temporal variabilities. In

addition, despite the ecological importance of fungi, there is evidence that bacteria contain

laccase-like multicopper oxidases (LMCOs) and that they are probably involved in nutrient

cycling in forest ecosystems. This suggests that the decay of recalcitrant plant compounds

is a function of interactions among microorganisms, whereby the complementary roles of

fungi and bacteria warrant the maintenance of ecosystem functionality, for example, by

constant enzyme activities. These results demonstrate the ecological force of functional

ecological studies, whereby it has to be considered that only up to 50 % of the soil-derived

fungal laccase and/or bacterial LMCO sequences can be assigned to basic functional guilds.

This reflects the high proportion of unknown soil microbes, an important future challenge

in microbial ecology because the function in and the response to their environment is still

not (or only restricted) verifiable.

Despite the current inaccuracies there is an urgent need to expand scientific investigations

to enlarge the knowledge of effects of environmental variables on the diversity and

functioning of soil fungi. In respect to the human-induced elevated carbon dioxide (CO2)

and nitrogen (N) emission since the 19th century, it can be expected that, for example,

increasing N deposition in terrestrial ecosystems may have strong effects on the soil

microbial, especially fungal communities due to changes in the carbon-to-nitrogen ratio

(C/N ratio) of the plant material. Therefore the environmental study presented in Chapter

II was established in a Norway spruce forest at Solling (Central Germany) to evaluate the

response of lignin-decomposing fungal communities in soils receiving current (34 kg N ha-

1 yr-1) and pre-industrial (11.5 kg N ha-1 yr-1) atmospheric N input for 14.5 years. The study

principally outlined that the composition of laccase encoding genes and hence possibly the

fungal community assembly respond sensitive to various environmental factors (e.g.,

reduced N deposition in spring or changing light and temperature regime by the roof

construction in autumn), although they are mainly affected by spatio-temporal ecological

factors such as substrate availability. It further expressly underline that the enzyme

activities and the lignin decomposition process itself obversely behave more conservative.

Noteworthy, 11 years (2006) after first treatment effects at the plant level solely the pure

spruce litter (Oi litter layer) contained less organic N resulting in higher C/N ratio

indicating that the available organic material in the organic (Oe, Oa) and mineral (A, Bw)

soil horizons were negligible diluted by N-depleted material. Conclusively this study

115

Summary

showed that the analysed spruce forest ecosystem is characterized by a long life span and

slow turnover rates of the spruce needles. At this point it is unratable whether the reduction

of N deposition leads to an accelerated or decelerated decay, although there are first

indications that the basidiomycetous laccase-containing fungal community is partly

affected by reduced N deposition. Despite there are some studies which showed that, for

example, the soil organic carbon (SOC) pool of European forest ecosystems will increase

until about 2050 (indicative for a retarded decay of organic material), much more time and

further investigations are needed to determine the effects of changing N deposition in

conjunctions with a possible function of soils as sink or source of CO2.

In our study we encountered the same difficulties that were previously reported by several

studies: (a) the extraction of nucleic acids in satisfactory purity and/or quantity and (b) the

correlation of spatial and temporal shifts in the laccase gene community structure to the

measured enzyme activity and lignin degradation progress. In the former case, Chapter III

provides a universally adaptable protocol for simultaneous extraction of high-purity DNA

and RNA from soil. In contrast to previous methods and in respect to the future challenges,

the described approach used Al2(SO4)3 to precipitated interfering humic compounds prior

to cell lysis, and thus prior to the nucleic acid extraction that makes quantitative studies on

nucleic acid diversity (e.g., microarray analyses) and composition (e.g., DNA-RNA

proportion) possible. Additionally, for evaluation of the second hindrance, Chapter IV

deals with the validity of the commonly targeted laccase encoding gene fragment in regard

to a respective function of the corresponding enzyme. The observed discrepancy is mainly

due to the multigene character of fungal laccases represented by paralogous genes within

one fungal genome (e.g., 11 laccase encoding genes in Laccaria bicolor and 17 in

Coprinopsis cinerea) that seemingly respresent functional diversification of laccases (e.g.,

lignin decay, pigmentation, fruiting body formation, pathogenesis or competitive

interactions). Despite comprehensive phylogenetic analyses of available full length laccase

protein sequences demonstrated that the evolutionary relationship reflecting some

functional indications for different laccase proteins, at this point it is still impossible to

clearly verify genes that encode true extracellular efficient laccase proteins responsible for

the measured enzyme activities. This phenomenon become more evident as the laccase

encoding gene frequently employed in molecular ecology is mainly restricted to the

fragment between the copper binding region (cbr) I and II resulting in a high loss of

phylogenetic informative sites towards the short sequence fragment. Unfortunately it is

also not possible to relate the detected short length gene fragment to known full length

116

Summary

sequences because many of the available full length sequences derived from white-rot

wood-decaying fungi and sequences from soil inhabiting saprotrophic, litter decomposer or

mycorrhizal fungi that are in an ecologically relevant framework in soil systems are

lacking. One future challenge will be to close this gap and to strengenth the focus of fungal

laccase research on soil ecologically relevant fungal species.

Irrespectively of the done analyses and despite much progress, there are currently still

more questions than answers. The present thesis about fungal laccase encoding genes and

their potential for soil ecological studies pave the way for a next research generation. An

exhaustive understanding of the ecological force of laccase-containing microbes especially

fungi and the biological or more precise the enzymatic mechanisms behind the fungal-

mediated decomposition process within terrestrial ecosystems will necessarily require

multidisciplinary approaches encompassing various experimental expertises (Figure S.1).

In respect to the current fungal genome programs (e.g., Fungal Genome Initiative (FGI) -

MIT and Harvard, Cambridge, MA, USA or DOE Joint Genome Institute (JGI), Walnut

Creek, CA, USA) that keep on providing complete sequences of numerous diverse fungal

organisms (e.g., see GOLD Genome OnLine database, http://www.genomesonline.org/),

there is an ongoing possibility to ascertain the genetic wealth of individual organisms. For

example, resent genome projects reveal the occurrence of laccase encoding genes in the

white-rot fungi Pleurotus ostreatus and Schizophyllum commune, the brown-rot fungus

Postia placenta, the litter-decomposing fungi Agaricus bisporus and Coprinopsis cinerea

or the ectomycorrhizal fungus Laccaria bicolor, whereby the role of laccases in respect to

their involvement in decomposition of recalcitrant plant-derived compounds is currently

unratable.

One future challenge at this point is to identify laccase genes encoding true extracellular

efficient enzymes and to verify their significance in respect to the cycling of elements

using artificial, laboratory-based and semi-natural, e.g. microcosm-based analyses. A

second challenge aims at investigations on individual organisms to understand the genetic

mechanisms in regard to their natural environment by, for example, microarray-based

transcriptional profiling that can further expose synergistic interactions within the

ligninolytic enzyme system. Last but not least, to understand how genes interact at higher

levels of biological organisation (e.g., population (groups of interacting individuals) and

community (sets of interacting populations) profiles and the interactions with the abiotic

117

Summary

118

environment), metagenomic analyses in combination with functional analyses (functional

gene-based community microarrays and proteomic analyses) reveal the extent how species

interact as consortia providing complementary functions within an ecosystem.

I am confident that such approaches will change and hopefully improve our knowledge of

the role(s) of microbial, especially fungal laccases.

INDIVIDUUM(genome)

population

community

ecosystem

laboratory studies

expressional gene regulation

biochemical protein characterization

whole genome sequencing

decode the genetic potential

screen for possibly all laccase genes

(semi-) environmental studies

microcosm experiments

transcriptional profiling

functional microarray

„omic“ analyses

physiologytranscriptome

proteome

M U

L T I D I S C I P L I N

A R Y A P P R O

A C H E S

organismal response

geneexpression

physiologicaltraints

genetic wealth

ecosystemconditions

community and population profile

E C O L O G Y

G E N E T I C S

INDIVIDUUM(genome)

population

community

ecosystem

laboratory studies

expressional gene regulation

biochemical protein characterization

whole genome sequencing

decode the genetic potential

screen for possibly all laccase genes

(semi-) environmental studies

microcosm experiments

transcriptional profiling

functional microarray

„omic“ analyses

physiologytranscriptome

proteome

M U

L T I D I S C I P L I N

A R Y A P P R O

A C H E S

organismal response

geneexpression

physiologicaltraints

genetic wealth

ecosystemconditions

community and population profile

E C O L O G Y

G E N E T I C S

Figure S.1: Conceptual framework for the prospective microbial, particularly fungal laccase research encompassing traditionally laboratory-based (orange) and ecological (blue) studies (modified from Fitter, 2005, J Ecol 93: 231-243 and Ungerer et al., 2008, Heredity 100: 178-183). In respect to the recent technical advances (e.g. whole genome sequencing, genome-wide expression profiling or high-throughput screening) the future challenge is to verify laccase genes encoding true extracellular efficient exoenzymes and to understand their involvement in the degradation of recalcitrant plant compound at different levels of biological organisation using multidisciplinary approaches. The black arrows indicate interactions and effects within and among different levels of the organisation hierarchy.

May the force be with the next research generation!

Zusammenfassung

Zusammenfassung

Die hier vorliegende kumulative Dissertation beschäftigt sich mit einer ganzheitlichen und

kritischen Abhandlung der mykologischen Laccase-Forschung des 21. Jahrhundert. Diese

Arbeit befasst sich in erster Linie mit einer Umweltstudie unter Berücksichtigung

möglicher Auswirkungen eines reduzierten Stickstoff-Eintrags auf die Diversität pilzlicher

Laccase-kodierenden Gene, deren Genprodukte am Abbau von recalcitrantem Pflanzen-

material beteiligt sind und somit eine wichtige ökologische Funktion erfüllen. In diesem

Zusammenhang galt es (1) vorangegangene und aktuelle ökologische, biogeochemische

und molekular-biologische Studien eingehend und umfassend zu analysieren um die

grundlegenden Rahmenbedingungen für diese Studie festzulegen, (2) diese Studie

durchzuführen und ihre Ergebnis genau zu evaluieren und (3) mögliche ökologische und

vor allem methodische Schwierigkeiten aufzudecken, die in Zukunft unter Berück-

sichtigung eines multidisziplinären Forschungsansatzes behoben werden könnten.

Kapitel I befasst sich mit der mikrobiellen Umsetzung von recalcitrantem, organischem

Material. Lignin, das zweithäufigstes Biopolymer der Natur, zählt aufgrund seiner sehr

komplexen Molekülstruktur zu den schwer abbaubaren (recalcitranten) Pflanzenbestand-

teilen, dessen Zersetzung vorwiegend durch Pilze, insbesondere Basidiomyzeten mittels

ligninolytischer Enzyme (z. B. Laccasen) realisiert wird. Biochemisch betrachtet, nutzen

pilzliche Laccasen das Redoxpotential von vier Kupfer-Ionen und katalysieren eine

Substratoxidation, die direkt an die Reduktion von Sauerstoff (O2) zu Wasser (H2O)

gebunden ist. Bei dieser Reaktion werden Elektronen von den Substraten erst auf das

Enzym, später auf den Sauerstoff übertragen, wobei Radikale entstehen, die im Weiteren

zu (De-) Polymerisationsreaktionen (z. B. Abbau von Lignin im Holz und in der Streu oder

Bildung von Humusfraktionen) führen. Strukturelle Analysen der Proteinsequenz haben

ergeben, dass vier Kupferbindestellen durch relativ konservierte Aminosäure-Motive

gekennzeichnet sind. Dies ermöglichte die Entwicklung degenerierter Primerpaare für die

spezifische Amplifizierung laccase-kodierender Gene, mit deren Hilfe die Diversität und

Verteilung Laccase-tragender Mikroorganismen (Pilze und Bakterien) in Umweltproben

erfassen werden konnte bzw. kann. Molekular-biologische, enzymatische und biogeo-

chemische Analysen haben gezeigt, dass die physikochemische und biotische Hetero-

genität des Bodens ein breites Spektrum an Faktoren bietet, die die Struktur und Funktion

119

Zusammenfassung

von pilzlichen Lebensgemeinschaften beeinflussen und kontrollieren können. Gemäß der

Verfügbarkeit und Qualität von Nährstoffen in der organischen Bodensubstanz (OBS)

sowie dem Vorhandensein ökologischer Nischen, ergaben Untersuchungen vertikale und

temporale Stratifizierungen (sowohl auf genetischer als auch auf expressioneller Ebene),

die sich mit den Ernährungsweisen von saprotrophen und ektomykorrhizalen Pilzen bzw.

der degradativen Sukzession erklären lassen. Neben der ökologischen Bedeutung der Pilze,

mehren sich Hinweise, dass Bakterien durch die Produktion laccase-ähnliche Multikupfer-

Oxidasen (engl. laccase-like multicopper oxidases; LMCO) an der Umsetzung von

organischem Material in Wald-Ökosystemen beteiligt sind. Das unterstützt die Annahme,

dass die Umsetzung von organischem Material eine Funktion der Interaktion von

Mikroorganismen ist, die in ihrer Gesamtheit zur Aufrechterhaltung der Ökosystem-

funktion (z. B. die Gewährleistung einer konstanten Enzymaktivität durch komplementäre

Funktionsverteilung zwischen Pilzen und Bakterien) beitragen. Diese Ergebnisse

veranschaulichen die erhebliche Aussagekraft funktioneller, molekular-ökologischer

Forschungsarbeiten, wobei berücksichtig werden muss, dass nur ca. 50 % der in den

Umweltproben erfassten Laccase-Gensequenzen, spezifischen funktionellen Gilden

zugeordnet werden können. An dieser Stelle verdeutlicht sich eine zukünftige Heraus-

forderung im Bereich der mikrobiellen Ökologie - die enorme Vielfalt unbekannter

Bodenorganismen, deren Interaktionen mit ihrer biotischen und abiotischen Umwelt

derzeit nicht (bzw. nur eingeschränkt) verifizierbar sind.

Trotz der vorhandenen Unstimmigkeiten heben die aufgezeigten Forschungsergebnisse

hervor, dass es notwendig ist, die derzeit durchgeführten Studien auszubauen und weiter-

zuentwickeln, um den Prozess der Zersetzung in seiner Gesamtheit sowie dessen Dynamik

vor allem in Hinblick auf variable Umweltbedingungen besser verstehen zu können. Unter

Berücksichtigung der vom Menschen induzierten Erhöhung der Kohlenstoffdioxid (CO2)

und Stickstoff (N) Emissionen seit beginn der Industrialisierung im 19. Jahrhundert, kann

davon ausgegangen werden, dass derartige Veränderung gravierende Auswirkungen auf

die Ökosystemfunktionen haben, vor allem im Hinblick auf die Frage, ob Böden als Senke

(Akkumulation) von oder Quelle (Freisetzung) für CO2 fungieren. Aus diesem Grund

wurde die in Kapitel II angeführte Forschungsstudie in einem Fichtenwald des Solling

(Mitteldeutschland) etabliert. Ziel war es die Reaktion lignin-abbauender Pilze sowie den

Lignin-Abbauprozess an sich zu verifizieren, nachdem über 14,5 Jahre der N-Eintrag

reduziert wurde. In erster Linie belegt diese Studie, dass die Laccase-Gendiversität und

demzufolge auch die Zusammensetzung der Pilz-Gemeinschaft in den obersten Boden-

120

Zusammenfassung

horizonten sehr sensitive auf variable Umweltbedingungen (z. B. Effekt bedingt durch den

reduzierten N-Eintrag im Frühjahr bzw. Effekt aufgrund der Dachkonstruktion basierend

auf veränderte Licht- und Temperaturveränderungen im Herbst) reagiert, wobei der

Haupteinflussfaktor die räumliche und zeitliche Verfügbarkeit von Nährstoffen ist. Zudem

wurde gezeigt, dass die Enzymaktivitäten sowie der Abbauprozess sehr konservativ

reagieren. 1995 wurde erstmalig nachgewiesen, dass die Reduzierung des N-Eintrags zu

einer Verminderung in der N-Konzentration und demzufolge zu einer Erhöhung des C/N-

Verhältnisses der Fichtennadel führt, was bemerkenswerter Weise 11 Jahre später (2006)

erneut bestätigt wurde. Diese Ergebnisse weisen darauf hin, dass darunter liegende

organische und mineralische Bodenhorizonte vernachlässigbar durchmischt sind mit N-

reduzierter Nadelstreu. Diese Studie verdeutlicht, dass das untersuchte Fichtenwald-

Ökosystem durch langsame Umsatzraten der Fichtennadelstreu gekennzeichnet ist. Zum

jetzigen Zeitpunkt kann nicht abgeschätzt werden, ob die Reduzierung des N-Eintrags zu

einem verstärkten oder verlangsamten Abbau der OBS führt. Es gibt zwar Studien, die

postulieren, dass das Reservoir der OBS in europäischen Wald-Ökosystem bis 2050

ansteigen wird (Hinweis auf einen verlangsamten Abbau), jedoch werden mehr Zeit und

weitere Forschungsarbeiten benötigt, um langfristige Auswirkungen von Umwelt-

veränderungen kalkulieren zu können.

Im Rahmen der vorliegenden Dissertation wurden methodische Schwierigkeiten vorge-

funden, die in früheren Studien bereits erwähnt wurden: (1) die Extraktion von

Nukleinsäuren in zufriedenstellender Qualität und Quantität und (2) Unstetigkeiten

bezüglich der Korrelation räumlicher und zeitlicher Variationen der Laccase-Gendiversität

sowie deren Expression mit dem im Bodensystem gemessenen Enzymaktivität. Zur

Bewältigung der ersten Schwierigkeit bietet Kapitel III ein universell adaptierbares

Protokoll zur simultanen Extraktion von DNA und RNA aus Bodenproben. Im Gegensatz

zu anderen Methoden und in Hinblick auf zukünftige molekular-ökologische Heraus-

forderungen, basiert der beschriebene Ansatz darauf störende Huminstoffe unter

Verwendung von Al2(SO4)3 bereits vor der Zelllyse und demzufolge vor der eigentlichen

Nukleinsäure-Extraktion zu entfernen, wodurch sowohl die Reinheit als auch die Ausbeute

an Nukleinsäuren deutlich erhöht wird. Für die Bewertung des zweiten Problems,

beschäftigt sich Kapitel IV mit der Aussagekraft des gegenwärtig amplifizierten Laccase-

kodierenden Genfragments und einer möglichen funktionellen Zuordnung der zugehörigen

Proteine. Die erwähnte Unstetigkeit ist vorwiegend darauf zurück zuführen, dass Laccase-

Gene zu einer sog. Multigen-Familie gehören, die durch das Vorkommen paraloger Gene

121

Zusammenfassung

innerhalb eines Genoms definiert sind (z. B. 11 Laccase-Gene bei Laccaria bicolor oder 17

Laccase-Gene bei Coprinopsis cinerea) und für diverse Funktionen verantwortlich sind

(u. a. Ligninabbau, Pigmentierung, Konkurrenz-Interaktionen, Pathogenese, Fruchtkörper-

bildung,). Obwohl eingehende phylogenetische Studien verfügbarer Proteinsequenzen

gezeigt haben, dass die evolutionäre Beziehung Hinweise auf mögliche Funktionen der

Laccasen gibt, ist es derzeit nicht möglich Laccase-Gene zu verifizieren, die eindeutig für

extrazellulär wirksame Enzyme kodieren. Die vergleichende phylogenetische Studie in

Kapitel IV offenbart, dass dieses Problem noch deutlicher wird, wenn man berücksichtig,

dass der momentan für molekular-ökologische Studien verwendete Laccase-Genmarker

sich auf ein Genfragmentbereich zwischen der Kupferbindestelle (engl. copper binding

region) I und II beschränkt, womit ein enormer Verlust (ca. 92 %) an phylogenetischer

Information verbunden ist. In diesem Zusammenhang und unter Berücksichtigung einer

möglichen Funktionszuordnung wäre es hilfreich, die in den Umweltstudien erfassten

kurzen Genfragmente mit vollständigen Gensequenzen bekannter Pilz-Arten abzugleichen.

Dies wird jedoch dadurch erschwerte, dass die meisten vollständigen Laccase-

Gensequenzen von holzzersetzenden Weißfäulepilzen stammen und Sequenzen von

saprotrophen Streuzersetzern oder ektomykorrhizalen Pilzen fehlen. Eine zukünftige

Herausforderung wird es sein, diese Lücke zu schließen und den Fokus der Laccase-

Forschung auf bodenökologisch relevante saprotrophe sowie ektomykorrhizale Pilze zu

richten.

Die hier vorliegende Dissertation zeigt, dass es im Bereich der mykologischen Laccase-

Forschung derzeit mehr offene Fragen als Antworten gibt. Ein umfassendes Verständnis

der ökologischen Bedeutung der an der Umsetzung von recalcitrantem organischem

Material beteiligten Mikroorganismen erfordert zukünftig einen interdisziplinären

Forschungsansatz, der diverse experimentelle Fachkompetenzen umfasst. Die derzeit

weltweit stattfindenden Programme zur Genomsequenzierung u. a. diverser Pilzarten,

bieten die Möglichkeit zur Entschlüsselung und Evaluierung des gesamten genetischen

Potentials bzw. einzelner Gene oder Gengruppen eines Individuums. Rezente Genom-

Programme offenbarten beispielsweise das Vorkommen diverser Laccase-kodieren der

Gene u. a. in den Weißfäulepilzen Pleurotus ostreatus und Schizophyllum commune, dem

Braunfäulepilz Postia placenta, den Streuzersetzern Agaricus bisporus und Coprinopsis

cinerea sowie dem Ektomykorrhizapilz Laccaria bicolor, wobei die Funktion der

122

Zusammenfassung

123

zugehörigen Laccase-Proteine vor allem in Hinblick auf ihre Beteiligung am Abbau von

recalcitrantem Pflanzenmaterial derzeit nicht bekannt sind.

Basierend auf den Ausführungen dieser Arbeit ergeben sich für die Zukunft der Laccase-

Forschung drei wesentliche Punkte: (1) Identifizierung von Laccase-Genen, die für

extrazellulär wirksame Enzyme kodieren sowie die Verifizierung ihrer Bedeutung beim

Abbau von recalcitrantem organischem Material unter Verwendung labor-basierte bzw.

semi-natürliche mikrokosmus-basierte Analysen. (2) Untersuchungen an Einzelorganismen

bezüglich der Regulation der Laccase-Gen-Expression unter künstlichen sowie umwelt-

relevanten (ökologischen) Bedingungen und biochemische Charakterisierung der Proteine

(möglicherweise auch unter Berücksichtung der synergistischen Wirkung anderer

wichtiger enzym-kodierender Gene des ligninolytischen Systems) unter Anwendung

biochip-basierte Analysen (engl. microarray-based transcriptional profiling). (3) Unter-

suchungen auf Ebene der Populationen und Lebensgemeinschaften sowie deren

Interaktionen im und mit dem Ökosystem (ausschließlich unter Berücksichtigung der

Laccase-Gene, die für extrazellulär wirksame Enzyme codieren) unter Verwendung von

Metagenom-Analysen in Kombination mit funktionellen Analysen (z. B. funktioneller

DNA-Biochips bzw. Proteom-Analysen).

Möge die Macht mit der nachfolgenden Wissenschaftsgeneration sein!

Cooperations

The present work was conducted at the Helmholtz-Centre for Environmental Research in

Halle (Saale), Department of Soil Ecology in the group of Prof. Dr. F. Buscot.

The following cooperations were important for the completion of this work:

Chapter I based on a publication in close cooperation with Prof. Dr. F. Buscot (UFZ Halle

(Saale), Department of Soil Ecology).

Chapter II based on a publication which was written in close cooperation with the

workgroup of Prof. Dr. Georg Guggenberger (Martin-Luther-University Halle (Saale);

present address: University of Hannover) and Prof. Dr. Norbert Lamersdorf (University of

Göttingen). The basic soil chemical and lignin analyses were carried out and evaluated by

Nicole Dörr. Statistical analyses were performed in cooperation with Dr. Uwe Langer

(UFZ Halle (Saale), Department of Soil Ecology; present address: Landesamt für

Umweltschutz Sachsen-Anhalt, Halle (Saale)). The laboratory work was conducted in

excellent cooperation with the technical assistants Sabine Jarzombski and Bettina Schlitt.

Chapter III based on a publication which was written in close cooperation with Derek

Peršoh (University of Bayreuth; present adress: University of Munich).

Chapter IV was carried out in close cooperation with Prof. Dr. F. Buscot, Dr. Dirk Krüger

and Dr. Tesfaye Wubet (UFZ Halle (Saale), Department of Soil Ecology), whereby the

phylogenetic analyses were done after helpful introduction by Dr. Dirk Krüger.

For the consideration of the cooperations please take further note of the form “Verfication

of the (co-) author parts” of the respective publication as well as the acknowledgements of

each chapter.

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125

Acknowledgement

First I would like to thank Prof. Dr. François Buscot for providing the topic, the support

and helpful advices.

My sincere thanks are given to my colleagues and truly friends Bettina Schlitt, Tina

Schäfer and Stephan König who accompanied me in both smooth and heavy times.

Additionally, I am also thankful to the members of the so called “Hallenser subset”. Guys,

we really have had good times.

I am further thankful to Ingo Bergmann, Nicole Grabowski, Steffi Haubold, Daniala

Schulte and Beate Fiszkal for their longstanding friendship and encouragements.

I am especailly thankful to Sabine Jarzombski and Bettina Schlitt for their assistance in the

laboratory work.

Moreover I would like to thank all of my project colleagues, especially Nicole Dörr and

Derek Peršoh for the excellent cooperation.

Many thanks are given to former and previous members of the Soil Ecology Group for the

good working atmosphere and helpful discussions.

Last but not least I deeply appreciate to my parents, especially to my mom for giving me

the possibility to study biology and to take opportunities when I had them.

Curriculum vitae

Personal data

Name: Susanne Theuerl

Date of birth: 17.08.1978 in Schwedt/Oder, Germany

Current address: Burgstrasse 51A in 06114 Halle (Saale), Germany

Email address: susanne.theuerl@googlemail.com

Education

since 2006 PhD student in the group of Prof. Dr. F. Buscot at the Department of

Soil Ecology, Helmholtz-Centre for Environmental Research (UFZ)

PhD thesis: “Fungal laccase research in the 21st century: a critical

holistic view on soil ecological studies”; supervisor: Prof. Dr. F. Buscot

2005 Diploma in Biology (Microbial Ecology, Genetic, Physical Geography)

Diploma thesis: “Untersuchung der bakteriellen Lebensgemeinschaft in

Sedimenten des Windwatts vor der Insel Hiddensee mit molekularen

Methoden“; supervisor: Prof. Dr. C. Gliesche

2003 Work experiences in marine, microbial ecology at the Leibnitz-Institut

für Meereswissenschaften, IfM-Geomar in Kiel, Germany

1998 - 2005 Diploma student in Biology at the Ernst-Moritz-Arndt-Universität

Greifswald

1998 Abitur at the gramma school “Albert Einstein” in Angermünde

Teaching experiences

Students practical courses: “Soil ecology – Introduction to molecular ecology” and “Symbioses

and mycorrhizal associations”

126

List of publications

Theuerl S, Dörr, N, Guggenberger G, Langer U, Kaiser K, Lamersdorf N & Buscot F

(2010) Response of recalcitrant soil substances to reduced N deposition in a spruce

forest soil: integrating fungal laccase encoding genes and lignin decompostion. FEMS

Microbiology Ecology (accepted). Doi: 10.1111/j.1574-6941.2010.00877.x.

Theuerl S & Buscot F (2010) Laccases: toward disentangling their diversity and functions

in relation to soil organic matter cycling. Bioliology and Fertility of Soils 46: 215-225.

Peršoh D, Theuerl S, Buscot F & Rambold G (2008) Towards a universally adaptable

method for quantitative extraction of high-purity nucleic acids from soil. Journal of

Microbiological Methods 75: 19–24.

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Conference proceedings

Lecture: Buscot F, Theuerl S, Luis P and Kellner H - "Struggling with scales in tracing

diversity, distribution and expression patterns of fungal and bacterial laccase genes in

soils" – EUROSOIL, Wien, 25.-29.08.2008

Lecture: Christ S, Theuerl S, Wubet T, Buscot F - “Application of phylogenetic and

functional marker genes to characterize fungal community composition in different forest

soils” - EURECO-GFOE, Bayreuth, 14.-18.09.2008

Poster: Theuerl S, Dörr N, Langer U, Kaiser K, Guggenberger G, Buscot F - “Tracing the

diversity and sitribution of fungal genes encoding laccases in a spruce forest soil" -

EURECO-GFOE, Leipzig, 15.-19.09.2008

Poster: Dörr N, Theuerl S, Kaiser K, Buscot F, Guggenberger G – “Grad des Lignin-

Abbaus in einem Fichtenwaldbestand in Anhängigkeit von der N-Deposition“ -

Jahrestagung der Deutschen Bodenkundlichen Gesellschaft, Dresden, 02.-09.2007

Statutory declaration

I, Susanne Theuerl, hereby affirm that I take note and accept the doctorate regulations of

the Faculty of Life Science, Pharmacy and Psychology of the University of Leipzig from

the 20th January 2010.

I further affirm that the presented thesis was prepared autonomously without inadmissible

help. All aids used in this thesis as well as scientific ideas which are quoted from or based

on other sources were cited at the respective point.

All people who helped me to prepare the conception, to select and analyse the materials of

this thesis as well as to improve the manuscript are namely cited in the acknowledgements.

With exception of the namely mentioned people no other persons were involved in the

intellectual work. No PhD consultant service was employed. Third parties did not get

money´s worth for benefits that were in conjunction with the content of this dissertation.

I declare that this dissertation has been neither presented nationally nor internationally in

its entirety or in parts to any institution for the purpose of dissertation or other official or

scientific examination and/or publishing.

Previously unsuccessful dissertations had not taken place.

The original document of the verification of the co-author parts are deposited in the office

of the dean.

Halle (Saale), May 2010

Susanne Theuerl

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Eidesstattliche Erklärung

Hiermit erkläre ich, Susanne Theuerl, eidesstattlich, dass mir die Promotionsordnung der

Fakultät für Biowissenschaften, Pharmazie und Psychologie der Universität Leipzig vom

20. Januar 2010 bekannt ist und von mir anerkannt wird.

Zudem versichere ich, dass die vorliegende Promotionsarbeit von mir selbstständig und

ohne unzulässige Hilfsmittel angefertigt worden ist. Sämtliche von mir verwendete

Hilfsmittel sowie die aus fremden Quellen direkt oder indirekt übernommen

wissenschaftlichen Gedanken sind als solche in der vorliegenden Arbeit gekennzeichnet.

Alle Personen, von denen ich bei der Auswahl und Auswertung des Materials sowie bei

der Herstellung des Manuskripts Unterstützungsleistungen erhalten habe, sind an

entsprechender Stelle namentlich in der(n) Danksagung(en) („Acknowledgements“)

genannt. Außer den genannten waren keine weiteren Personen an der geistigen Herstellung

der vorliegenden Arbeit beteiligt. Die Hilfe eines Promotionsberaters wurde nicht in

Anspruch genommen. Dritte haben von mir für Arbeiten, die im Zusammenhang mit dem

Inhalt der vorliegenden Dissertation stehen, weder unmittelbar noch mittelbar geldwerte

Leistungen erhalten.

Ich versichere, dass die vorgelegte Dissertation weder im Inland noch im Ausland in

gleicher oder ähnlicher Form einer anderen Prüfungsbehörde zum Zwecke der Promotion

oder anderer staatlicher oder wissenschaftlicher Prüfungsverfahren vorgelegt und/oder

veröffentlicht wurde.

Frühere erfolglose Promotionsversuche haben nicht stattgefunden.

Die Nachweise über die Anteile der (Co-)Autorenschaften der in dieser Dissertation

verwendeten Publikationen sind im Origonal im Dekanat der Universität Leipzig hinterlegt.

Halle (Saale), May 2010

Susanne Theuerl