Engineering Biology IITD2012

7/31/2019 Engineering Biology IITD2012

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Engineering Biology throughMolecular Microbial Ecology

Russell Davenport


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Global challengesUN Millenium Development Goals 2.6 billion without improved sanitation

WHO/Unicef, 2010


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Global challenges

Rockstrm et al., 2009 Nature

Anthropocene

Ecologicalfootprint has beenexceeded

Affect air, land andwater

21st Century of theenvironment or

biology

Living beyond our planetary boundaries


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Double burden and emerging hazards

Lvovsky, 2001

World Bank, 2003

Traditional hazards: water-borne diseases from inadequate water supply & sanitation

Modern hazards: exposure to agro-industrial chemicals

Dual jeopardy risks to health


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Emerging hazards chemical exposure

Personal care and domestic

hygiene products, pesticides,

pharmaceuticals and plastics

Mitigation:

Manufacturing source chemical regulation (e.g. REACH)

Engineered intervention of emissions wastewater regulation

(e.g. Integrated Pollution Prevention & Control; IPPC and

Water Framework Directive; WFD)


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Environmental engineering

Provide appropriate water and

wastewater treatment

governance and technologies

Protection of human health and

the environment through theregulation of chemicals

World Bank, 1992


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Empiricism and opportunism

1910

1891

1914

..practices do not represent the zenithof scientific treatment, nor are theythe product of a logical

and rational and design process.

Feachem et al., 1983


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- 4 M tonnes total CO2 (0.5% total UK) emissions- 1.5% of UK electricity

Economic and Environmental Costs

Organic carbon, N, P

Waste sludge

(WAS)

Return Activated Sludge

(RAS)

CO2 emissions

CO2 emissions

Treated

effluent

to sludge

treatmentO2


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Empirical wastewater treatment

Sometimes result in failure

Unpredictable and inexplicable Situation bound

Proximity to failure unknown

Adequate theories and models

Aggregate behaviour

Poorly calibrated

Over design Over aeration


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Why theory? How difficult can it be?

Stars in the our galaxy : Stars in the universe :

Measures of complexity

Bacteria in a STW : Bacteria in the world :

1030

1021

1018

1011


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Causey Arch, Built 1725

Severan Bridge, Turkey ~200 AD

The limits of empiricism

Roman design: unchanged since 179 BC
http://id-archserve.ucsb.edu/arthistory/152k/large_pictures/lgA57.1.htm


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A new era

New molecular based tools based on

evolutionary principles

Novel (ecological) theories


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Evolutionary tree of life

Woeses tree (1977) based on rRNA gene sequence

comparisons

Tree dominated by microbial forms


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Revolution in microbial ecology


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The basic molecular tool box

Clone, screen &sequence

DNA extraction

Amplification

Community analysis

RNA sequence determination

Fingerprint gel

Sample

Fix cells

Fluorescence in situHybridisation (FISH)

Probe/primer design

Abundance Diversity

Quantitative real-time PCR


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Measure diversity and abundance

Microbial ecology

Understanding the problems

0

10

20

30

40

50

60

70

Time

BacterialNumbers

Identification and quantification is central inachieving population dynamics

- Empirical monitoring (reactive management)

- (Ecological) theory (predictive management)


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Challenges facing biological treatment

Nitrification Foaming

Phosphorus removal

Bulking Denitrification

Removal of micropollutants including Endocrine

Disrupting Compounds (EDC)

Nutrient removal Solids separation

BOD removal

N- Fixation


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Nitrification

3 step process involving 2 distinct groups of bacteria

Ammonia oxidation (autotrophic AOB)

NH3 + O2 + 2H+ + 2e- NH2OH + H2O

Nitrite oxidation(nitrite-oxidizing bacteria)

NH2OH + H2O NO2- + 5H+ + 4e-

NO2- + H2O NO3

- + 2H+ + 2e-

Rate limiting step

NH4

NO2

-

NO3-

N2

N- Fixation


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Quantitative analysis of AOB

AOB occur in microcolonies

in activated sludge flocs

Can contain thousands of

individual cells


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R2= 0.8704

012345678

0 2 4 6 8 10Microcolony radius (microns)

Cell No.4/3

3

R2 = 0.87

n = 80

Quantitative analysis of AOB


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On the basis of this theoretical model the proportion of AOB

to total biomass can be predicted from ammonia removal

Values from cultured AOB are used to provide yield and

growth rate

Xv

Ammoniaxbnit

Ynitx

Xv

Xnit

**1

XAOB

YAOB

bAOB

* x

Integrating microbial data and processmodels

I i i bi l d d


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Good fit between theoreticalpredictions and measurement

Betaproteobacterial AOB

responsible for observed

nitrification

Deviations from theoretical

predictions suggest

Novel AOB Failing nitrification

Model not universal

XAOB/Xv predicted (%)

X

AOB

/Xvmeasu

red(%)

Regression

95% CI

8

4

0

0 1 2 3 4 5 6 7

y = 0.94x 1.42

Integrating microbial data and processmodels

Coskunuret al.,AEM, 2005


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Data useful for resource management?

Can high biomass

plants be made to work

harder?

Can such data permit

more intelligent balance

between process

performance and

process cost?456789

0.01 0.1 1 10 100

logAOBcells/ml

Cell-specific ammonia

oxidation rate fmol/cell/h

Coskunuret al.,AEM, 2005


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Cell Specific Ammonia Oxidation Rate (fmol/cell/hr)

LogAOBcells/m

l

10.01.00.1

1.0E+09

1.0E+08

1.0E+07

Stability

Failing

Irregular

Stable

23

22

21

20

1918

17

16

15

14

13

12

11

10

98

7

6

54

3

2

1

Quantifying AOB in relation to failure

Pickering et al., submitted Environ. Sci. Tchnol. (under review)Pickering, 2008

P A i i


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Dissolved

oxygen

(mg l-1)

Ammoniacal

nitrogen

(mg l-1)

1. Influent

2. Anoxic zone

3. Mechanical aeration

4. Mechanical aeration5. Diffuse aeration

6. Diffuse aeration

7. Diffuse aeration

8. Secondary effluent

9. Return Activated Sludge

Sutton-in-Ashfield

TotonNitrosomonas europaeaNCIMB 11850T

1. Influent

2. Anoxic zone



5. Diffuse aeration

6. Diffuse aeration7. Diffuse aeration



Sutton-in-Ashfield

Toton

Nitrosomonas europaeaNCIMB 11850T

Wanlip

DNA

Wanlip

RNA

Presence versus Activity

Milneret al., 2008, Water Research

P A i i


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1. Influent

2. Anoxic zone


4. Mechanical aeration5. Diffuse aeration

6. Diffuse aeration

7. Diffuse aeration



Sutton-in-Ashfield

TotonNitrosomonas europaeaNCIMB 11850T

1. Influent

2. Anoxic zone



5. Diffuse aeration

6. Diffuse aeration7. Diffuse aeration



Sutton-in-Ashfield

Toton

Nitrosomonas europaeaNCIMB 11850T

Wanlip

DNA

Wanlip

RNA

Presence versus Activity

AOB

abundance

( 107 ml-1)

Ammoniacal

nitrogen

(mg l-1)

Nitrosomonas europaea-like organism

Milneret al., 2008 Water Research


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Are AOB mixotrophic?

Y= (MtMt0)/ (St St0)

Observed yield

Assumptions: All ammonia is consumed by AOB with little used for maintenance,no heterotrophic assimilation

26 mg mg-1ammonia removed

0.03 - 0.34 mg mg-1ammonia removed

C k h bi k h d ?


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Can we make the biomass work harder?

Bellucci et al., 2011 Appl. Environ. Microbiol.

43373125191371

100

80

60

40

20

0

Time (days)

ConcentrationasN(mg/

L)

RH4

43373125191371

100

80

60

40

20

0

Time (days)

ConcentrationasN(mg/

L)

RH3

43373125191371

100

80

60

40

20

0

Time (days)

Concentrationa

sN(mg/L)

RL2

43373125191371

100

80

60

40

20

0

Time (days)

Concentrationa

sN(mg/L)

RL1

0.25 mg l-1 0.5 mg l-1

3.4 mg l-1 3.0 mg l-1

NH3

NO2-

NO3-

RHsRLs

2.5

2.0

1.5

1.0

0.5

0.0

Treatments

Yield(VSSaob/NH4+

-Nremoved)

M di i i d d


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All biological communities are characterised by a species abundance

distribution

Area under the curve is the total number of taxa, ST i.e. total (alpha)diversity or species richness

00 5 10 15 20 25

Log2 Bacterial abundance (arbitrary units)

Numberofspecies(S)

ST

Intermediate abundance

Rare

speciesCommon

species

Most diversity is undetected

M di i i d d


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0

5001000

1500

2000

2500

30003500

4000

4500

5000

0 5 10 15 20 25

log2 species abundance (arbitrary units)

Numberofspeciespresentata

givenabundance

Even cloning and sequencing efforts will only sample the

far right hand end of the species curve

Most diversity is undetected

N i i


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Next generation sequencing Generates orders of magnitude greater sequencing depth (i.e. number

of sequences) than conventional Sanger-sequencing of clones Clone-sequencing: 100 clones reads is a big library takes

approx. 2 days from PCR

Parallel sequencing: up to 1,000,000 reads takes hours to days

0

5001000150020002500

30003500400045005000

0 5 10 15 20 25

log2 species abundance (arbitrary units)

Numberofspec

iespresentat

agivenab

undance

N t ti i


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An explosion of data

Key tools and theories stillbeing developed

Genbank growth nowexceeding Moores law

Economist 2009

Next generation sequencing

N t ti i


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Next generation sequencing ABI SOLiD (~50 100 bp)

Illumina Solexa and Hi-Seq genome analyser(~75 150 bp)

Roche 454 pyrosequencing (~400 1000 bp)

Ion Torrent (~100 200 bp)

Pyrosequencing


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Pyrosequencing

PCR using fusion primers (so-called tags)

Generates PCR amplicons with A and B adaptor tags

One fragment binds to one bead Emulsified in oil to give microreactors with reagents

for PCR (emPCR)

Multiple copies made of single fragment

Pyrosequencing


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Initially each bead has a single DNA molecule attached

Pyrosequencing

Pyrosequencing


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Sequencing by synthesis as nucleotides are flowed across plate in turn

Incorporated bases emit light with intensity proportional to homopolymer

length n

Pyrosequencing

Pyrosequencing


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Flowgrams are translated into sequences (by rounding to integers)

Can cause noise which can be removed (Quince et al., 2009, Nature Methods)

Pyrosequencing


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Beware of sequencing error!

Quince et al., Nat.Meths 2009, BMC Bioinf. 2011


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Species diversity in activated sludge

30,000 sequencesfrom UK AS plants Sequencing noise

removed

1000s of species in ASplants!

Just to sequence 90%

of diversity in 0.25 mlrequires 2-8 MILLION

sequences 0

1000

2000

3000

4000

5000

6000

7000

8000

Lognormal InverseGaussian

Derby Wanlip

NumberofSpe

cies

Davenport et al., unpublished


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Thanks!

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Engineering Biology IITD2012