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TAT-Pathway-Dependent Lipoproteins as a Niche-BasedAdaptation in Prokaryotes
Hamsanathan Shruthi • Mohan Madan Babu •
Krishnan Sankaran
Received: 1 October 2009 / Accepted: 3 March 2010
� Springer Science+Business Media, LLC 2010
Abstract Bacterial lipoproteins, characterized by the
N-terminal N-acyl S-diacylglyceryl Cysteine, are key
membrane proteins in bacterial homeostasis. It is generally
thought that during the modification lipoprotein precursors
are translocated via the Sec-machinery in an unfolded state.
The recent discovery of twin-arginine translocation (TAT)
machinery, meant for exporting folded-proteins, and the
presence of TAT-type signal sequences in co-factor-con-
taining (hence already folded) lipoproteins, prompted us to
investigate its role and significance in lipoprotein biosyn-
thesis. We systematically analyzed 696 prokaryotic gen-
omes using an algorithm based on DOLOP and TatP rules
to predict TAT-pathway-dependent lipoprotein substrates.
Occurrence of the deduced TAT-pathway-dependent lipo-
protein substrates in relation to genome size, presence or
absence of TAT machinery, and extent of its usage for
lipoprotein export and habitat types revealed that unlike the
host-obligates, the free-living prokaryotes in complex
hostile environments (e.g., soil) depend more on TAT-
exported lipoproteins. Functional classification of the pre-
dicted TAT-dependent lipoproteins revealed enrichment in
hydrolases and oxido-reductases, which are fast-folding
and co-factor-containing proteins. The role of the TAT
pathway in the export of folded-lipoproteins and in
niche-specific adaptation for survival has important impli-
cations not only in lipoprotein biosynthesis, but also for
protein and metabolic engineering applications.
Keywords TAT-box � Lipobox � Co-factor containing
lipoproteins � DOLOP � TatP � Habitat � Oxido-reductases �Hydrolases � Binding proteins
Introduction
Bacteria need to transport proteins across their membrane
for constant interaction with their extracellular milieu. The
general secretory pathway, referred to as Sec-pathway, has
been known to transport the majority of proteins across the
cytoplasmic membrane. Proteins exported through this
pathway possess a characteristic N-terminal extension that
is cleaved off after the translocation by the transmembrane
signal peptidases (Spases I&II) on the periplasmic side of
the membrane (Pugsley 1993). Signal peptidase II is spe-
cific to prolipoproteins, whose signal sequence contains the
lipobox, [LVI][ASTVI][GAS]C at its C-terminus. In the
lipoprotein biosynthesis, the invariant Cys gets lipid
modified and only then is the signal peptide cleaved off and
the partially modified N-terminal Cys is fatty acylated. The
acyl moieties anchor the lipoproteins to either the inner or
outer membrane (Sankaran and Wu 1994).
The Sec apparatus has been demonstrated to transport
proteins in the unfolded state (Liu et al. 1989). Such a
system is not suited to transport fully folded proteins, but a
machinery for exporting such proteins is available via the
Twin Arginine Translocase pathway (TAT) (Lee et al.
2006). This pathway exports fully folded proteins con-
taining a signal sequence with a characteristic semi-con-
sensus sequence (TAT-box), S/T-R-R-F-L-K, at the
Electronic supplementary material The online version of thisarticle (doi:10.1007/s00239-010-9334-2) contains supplementarymaterial, which is available to authorized users.
H. Shruthi � K. Sankaran (&)
Centre for Biotechnology, Anna University,
Chennai 600 025, Tamil Nadu, India
e-mail: [email protected]; [email protected]
M. Madan Babu
MRC-Laboratory of Molecular Biology, Hills Road,
Cambridge CB2 0QH, UK
123
J Mol Evol
DOI 10.1007/s00239-010-9334-2
boundary of the n-region and the h-region; the twin argi-
nines are almost invariant and a signature for identifying
TAT substrates (Dilks et al. 2003). TAT as an export
system has been studied extensively using the prototypical
signal sequence of E. coli trimethylamine oxido-reductase
(TorA) (Lee et al. 2006). Other TAT-signal sequences,
DmsA, SufI FdnG, FdoG, HyaA, from E. coli (DeLisa et al.
2003), PhoD from Bacillus subtilis (Jongbloed et al. 2002)
and PhoA, PhoC from Streptomyces coelicolor (Apel et al.
2007) have also been used. Heterologous proteins such as
the green fluorescent protein, human tissue plasminogen
activator, and murine scFv and Fab antibody fragments
were found to require the TAT pathway for the export of
functional protein to the periplasm (Lee et al. 2006;
Ribnicky et al. 2007).
Although experiments, as well as bioinformatic analy-
ses, highlight the importance of the TAT machinery in the
translocation of folded proteins, its role in prolipoprotein
translocation (Hutchings et al. 2009) has not been ade-
quately probed. Presence of a lipobox sequence along with
the TAT motif in the protein sequences of Streptomyces
coelicolor, Legionella pneumophila, and Haloferax volca-
nii, suggests the existence of TAT-dependent lipoproteins
(De Buck et al. 2004; Dilks et al. 2005; Gimenaz et al.
2007). Employing TAT mutants of S. coelicolor, putative
TAT lipoprotein substrates, peptidylprolyl cis–trans isom-
erase, a putative sugar-binding protein, an iron–sulfur
binding protein and a putative secretory protein were
shown to be TAT-dependent (Widdick et al. 2006). Site-
directed mutagenesis of TAT signals of the iron-binding
protein, DsbA-like thioredoxin domain protein, and malt-
ose binding protein in H. volcanii, resulted in their accu-
mulation in the cytoplasm. Further, it was shown that the
lipoprotein signal peptidase inhibitor, Globomycin, inhib-
ited the maturation of these putative TAT substrates
(Gimenaz et al. 2007). Curiously, it was observed that the
TAT substrate, [NiFeSe] hydrogenase (HysAB) of Des-
ulfovibrio vulgaris Hildenborough has the TAT-box in the
signal sequence of the small subunit and the Lipobox in the
N-terminal region of the large subunit. Mass-spectrometric
data supporting lipid modification of this protein were
reported recently (Valente et al. 2007).
The prediction tools for identifying either putative TAT
substrates or bacterial prolipoproteins are well established.
Among these, the available TAT prediction tools are
trained only to recognize the TAT motif and an uncharged
stretch of at least 13 amino acids downstream, as in Tat-
FIND or TAT motif with Spase-I cleavage region as in
TatP (Bendtsen et al. 2005; Dilks et al. 2003). Bacterial
lipoprotein prediction tools do not distinguish between Sec
or TAT signals (Babu et al. 2006). These tools are obvi-
ously not suitable to predict potential TAT-dependent
lipoproteins. Hence a new program was written combining
the bacterial lipoprotein prediction tool that was published
recently (available in the bacterial lipoprotein web site,
DOLOP; Babu et al. 2006) and the TAT substrate predic-
tion (TatP) tool described by Bendtsen et al. (2005). Using
this new program, we have analyzed a large number of
prolipoprotein sequences from over 600 prokaryotic gen-
omes for the presence of TAT signals to obtain insight into
their occurrence and the purpose for their presence.
Methods
The completed genome sequences were obtained from the
ftp site of NCBI (ftp.ncbi.nih.gov). TAT-dependent lipo-
protein sequences were extracted using an in-house PERL
script, ‘‘TAT LIPO.’’ The program was developed by
combining DOLOP lipoprotein identification with TatP
server algorithm (Bendtsen et al. 2005; Babu et al. 2006)
.The script was trained to search for
• Presence of [LVI][ASTVI][GAS]C within the first 50
amino acids of the sequence starting with methionine.
• The sequence should contain a positively charged
residue within the first seven amino acids.
• The sequence should have an uncharged amino acid
stretch with a minimum of seven amino acids.
The sequences satisfying these conditions were taken as
lipoproteins. Among the predicted lipoproteins, the con-
sensus pattern, RR.[FGAVML][LITMVF], which is char-
acteristic of TAT dependency, was identified to predict
TAT-dependent lipoproteins (Bendtsen et al. 2005).
TAT-dependent lipoproteins were identified from 696
prokaryotic genomes and categorized based on their func-
tion. Information about the lifestyle for these organisms
was obtained from the NCBI microbial genomes website
(http://www.ncbi.nlm.nih.gov/genomes/lproks.cgi). The func-
tional classification was carried out by grouping the pre-
dicted TAT-dependent lipoproteins and providing a keyword
search for enzymes, transporters/binding proteins, and
hypothetical proteins.
The essential TAT components required for functional
TAT machinery are TatA/E and TatC. The presence or
absence of these components in 696 genomes was analyzed
by PSI-BLAST and its iterations (Dilks et al. 2003).
Functional Assignment to Hypothetical
TAT-Dependent Lipoproteins
FASTA sequences of 647 hypothetical proteins among the
predicted TAT-lipoproteins were extracted from protein
database of NCBI (http://www.ncbi.nlm.nih.gov/sites/entrez?
db=protein&cmd=search&term=) by providing the corre-
sponding accession ID. The SCOP domains to the FASTA
J Mol Evol
123
sequences were assigned using the SUPERFAMILY Hidden
Markov Models that is made available through the sequence
search facility in the SUPERFAMILY database (www.
supfam.org) (Wilson et al. 2009). The query sequences that
had significant e-value scores (\10-3) were retrieved (Gough
et al. 2001) and were further classified based on their func-
tions as described above.
Results
The New Algorithm Identifies TAT-Dependent
Lipoproteins Reliably and Reveals the Absence
of Correlation with Genome Size and Total Number
of Lipoproteins
Since there are not many experimentally verified TAT-
dependent lipoproteins, the accuracy and reliability of the
algorithm were tested on the basis of the occurrence of
essential components of the TAT pathway, TatA/E, and
TatC, as done by Dilks et al. (2003) for TatFIND. Among
the 696 bacterial and archaeal genomes analyzed, (i) 391
genomes had detectable orthologs of the TAT components
and several predicted TAT-dependent lipoproteins, (ii) 34
genomes contained no detectable orthologs of the TAT
components, but each genome did contain one or two
predicted TAT-dependent lipoproteins, 60% of which were
hypothetical proteins, (iii) 127 genomes had only the TAT
components without any predicted TAT-dependent lipo-
proteins, and (iv) 144 genomes were negative for both (See
Supplementary Table 1). It was earlier reported with a
limited dataset of prokaryotic genomes that those bacteria
lacking TatC, an essential TAT component, had small
genomes of the size 1–2 Mb (Wu et al. 2000), indicating
possible correlation between use of TAT and genome size.
As can be seen in Fig. 1a, the genome sizes of 696 pro-
karyotes fell into two groups: 368 of the genomes below
(small genomes) and 328 of the genomes above 3.5 Mb
(big genomes) (Fig. 1a). The organisms were further cat-
egorized as TAT-users and TAT-deficient, respectively,
based on the presence and absence of the essential com-
ponents of TAT machinery. The TAT users were again
classified into ‘‘minimal TAT user’’ and ‘‘extensive TAT
user’’ on the basis of whether the proportion of TAT-
dependent lipoproteins out of the total lipoproteins pre-
dicted was below or above 10%, respectively (see inset B
in Fig. 1). The bar diagram in Fig. 1 clearly shows that
among the TAT users, the majority of prokaryotes (398),
including those containing big genomes, are minimal users
of TAT. The rest (120) are extensive users, which also
includes prokaryotes with small genomes. As a specific
case, in eubacteria (with nearly equal numbers of small and
big genomes), the members with small genomes are
minimal TAT users and those with big genomes contain
both minimal and extensive users, irrespective of the size.
Hence there was no apparent correlation between the
number of TAT-dependent lipoproteins and the genome
size.
Though it is expected that the presence of the TAT
machinery would normally indicate the presence of TAT-
dependent lipoproteins, there were examples of TAT-con-
taining prokaryotes lacking TAT-dependent lipoproteins.
The majority of the archaeal genomes are small (46 out of
51) with either a few or no TAT-dependent lipoproteins.
Many (21 out of 51) lack detectable components of the
TAT machinery indicating that TAT is less significant for
lipoprotein targeting in archaea, which consists of organ-
isms living under extreme conditions. It was also found that
there was no apparent correlation between the number of
TAT substrates, which includes both lipoproteins and
nonlipoproteins (Dilks et al. 2003), and the number of
TAT-dependent lipoproteins. The largest prokaryote by
genome size, Sorangium cellulosum has 335 lipoproteins,
but only 24 (7%) of them were predicted to be exported via
the TAT pathway. In contrast, the relatively smaller pro-
karyote, Natronomonas pharaonis DSM 2160 was pre-
dicted to translocate 49 out of 67 (*73%) of its
lipoproteins via the TAT pathway.
Another parameter that defines prokaryotic genomes is
the base composition. As can be seen in the inset C in
Fig. 1, the extent of TAT usage for lipoproteins remains
uniformly low-to-moderate in organisms with 30–60% of
G ? C content. There is, however, a steep increase in TAT
usage among prokaryotes with very high G ? C content
(65–70%). Among Gram-positives, Firmicutes with low
G ? C content showed either no TAT components at all
(67% of 80 organisms) or only modest numbers of TAT-
dependent lipoproteins (32% of 80 organisms). Contras-
tingly 44 actinobacterial species (85% of 52 organisms)
with exceptionally high G ? C content (60–74%) were
predicted to be extensive TAT users.
Phylogenetic Analysis Suggests that TAT Utilization
for Lipoproteins Could Have Been Driven
by Adaptation to Complex Habitats
Generally, the TAT dependency appeared to be related to
the genera rather than the phyla. The archaeal phylum
Euryarchaeota consists of halophiles, methanogens, and
thermophiles. Among the 34 genera of Euryarchaeota for
which genome data was available, halophiles (five organ-
isms) showed 56–73% of their total lipoproteins to be TAT-
dependent; the highest was predicted for Natronomonas
pharaonis DSM 2160. Among methanogens, 17 out of 21
lacked TAT components; the rest of the methogens as well
as thermophiles (eight organisms) were predicted to utilize
J Mol Evol
123
TAT either poorly or moderately for lipoprotein biosyn-
thesis. Among the eubacteria, Firmicutes, the second largest
phylum consisting mainly of common pathogens like
Staphylococccus, Strepococccus, Clostridium, and Myco-
plasma, contain moderate-to-high numbers (30–100) of
lipoproteins, but uses TAT minimally between 0 and 3% of
total lipoproteins. However in this phylum, an exception to
this trend and a striking niche-based preference for TAT-
dependent lipoproteins was seen in the free-living bacteria,
Desulfitobacterium hafniense Y51 (21% of total lipopro-
teins) and Symbiobacterium thermophilum (17% of total
lipoproteins). In Actinobacteria, except two of the 54 gen-
era, the TAT-dependent lipoproteins, which are mostly
substrate-binding proteins, account for 15–25% of the total
lipoproteins. For example, Streptomyces ceolicolor, a soil-
dwelling bacterium and a prolific protein secretor, was
predicted to have significant numbers of TAT-dependent
lipoproteins (28% of total lipoproteins) including the proven
A
0
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15
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25
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10 20 30 40 50
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AT
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No.
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opro
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00 1 2 3 4 5 6 7 8 9 11 12 13 140
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Genome size
No.
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enom
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Smal
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enom
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xten
sive
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T u
ser
No.
of
prok
aryo
tes
TA
T D
efic
ient
Aci
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cter
ia
Act
inob
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Bact
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dete
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orob
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Chla
myd
iae/
Ver
ruco
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robi
a
Chlo
rofle
xi
Cyan
obac
teria
Dei
noco
ccus
-The
rmus
Del
tapr
oteo
bact
eria
Epsil
onpr
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bact
eria
Firm
icut
es
Fuso
bact
eria
Gam
map
rote
obac
teria
Oth
er B
acte
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Plan
ctom
ycet
es
Spiro
chae
tes
Ther
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ogae
Cren
arch
aeot
a Eu
ryar
chae
ota
Nan
oarc
haeo
ta
Oth
er A
rcha
ea
Big
Gen
ome
Smal
lG
enom
eB
igG
enom
eSm
all
Gen
ome
Min
imal
TA
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ser
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T U
ser
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Gen
ome
80
0
20
40
No. of TAT-dependentlipoproteins
MinimalTAT users
ExtensiveTAT users
Fig. 1 Eubacteria and archaea generally use TAT minimally: The
bar graph shows the distribution of 696 prokaryotes (bacteria and
archaea) arranged according to the phyla (horizontal axis), with
respect to the frequency (vertical axis on the left) genome size
categorization (vertical axis on the right), presence or absence of TAT
machinery and degree of usage (vertical axis on the right). The
categorization of genomes as small or big was decided on the basis of
the inflection point at 3.5 Mb seen in the genome size distribution
shown as inset A. The extensive and minimal users of TAT were
determined based on plotting the relative abundance of TAT-
dependent lipoproteins among total lipoproteins in an organism, as
shown in inset B. Those bacteria exceeding 10% were taken as
extensive users. Inset C shows the number of TAT-dependent
lipoproteins as a function of G ? C content of the genome
J Mol Evol
123
TAT substrates, peptidylprolyl cis–trans isomerase, a
putative sugar-binding protein, an iron–sulfur binding pro-
tein and a putative secretory protein (Widdick et al. 2006).
In Proteobacteria, the phylum with the maximum
number of genome sequences reported, 23,840 lipoproteins
have been predicted in 343 genomes but only 1,201 TAT-
dependent lipoproteins (ranging from 0 to 24% of the
lipoproteins, as the case may be) could be predicted. Chl-
amydiae and most of the Spirochetes even lacked detect-
able TAT components. We were, therefore, interested in
investigating the significance of TAT usage for lipopro-
teins across evolution and its influence in adaptation. From
the recent phylogenic tree obtained by comparing 31 uni-
versal protein families (Ciccarelli et al. 2006), we selected
the highly diversified Proteobacteria and matched the TAT
usage (%TAT-dependent lipoproteins among the total
lipoproteins). According to the phylogenetic analysis,
Delta, Epsilon, and a common ancestor for Alpha, Beta,
and Gamma subdivisions of Proteobacteria emerged from
Firmicutes, which are poor TAT users. However, even
among such phylogenetically related groups there was
significant difference in the usage of TAT for lipopro-
teins. For instance, the predominantly soil-dwelling Delta
proteobacteria are moderate users of TAT, whereas the
predominantly pathogenic Epsilon proteobacteria are poor
TAT users. In the Alpha, Beta, and Gamma proteobac-
terial group, Alpha and Beta proteobacteria contain free-
living and pathogenic bacteria in roughly equal numbers,
but Gamma proteobacteria are predominantly pathogenic.
Only the free-living organisms are moderate users of
TAT, whereas the pathogenic organisms use TAT mini-
mally (see Fig. 2). This trend indicates association of
TAT usage to an organism’s lifestyle rather than the
phylum it belongs to.
Functional Classification of Predicted TAT-Dependent
Lipoproteins
Many TAT substrates and the few lipoproteins identified so
far as TAT-dependent are either substrate-binding proteins
or cofactor-containing enzymes (Gimenaz et al. 2007;
Valente et al. 2007). To verify the possibility that TAT-
dependent lipoproteins could be a lifestyle adaptation of
prokaryotes in meeting the challenges posed by their sur-
roundings, the functional compatibility of such predicted
lipoproteins was investigated. Such functions should
obviously include digestive and detoxifying enzymes,
nutrient or metabolite transporting proteins, and compo-
nents of stress sensors and tolerance. One of the advantages
of lipid modification of a protein is its membrane locali-
zation providing access to the external milieu (Navarre and
Schneewind, 1999). As can be seen in the Pie-chart in
Fig. 3, 2307 TAT-dependent lipoproteins were predicted
from 518 genomes containing TatC and TatA/E. Among
these, 503 (22%) were enzymes, 562 (24%) were trans-
porters/binding proteins, and the remaining 54% were
either hypothetical proteins (647) or proteins with other or
unknown functions (595).
The distribution of these functional lipoproteins among
the minimal and extensive users according to genome size
is shown in Fig. 4. Enzymes, but not transporters/binding
proteins, are predominant among the minimal users,
whereas both are evenly distributed among the extensive
users. This interesting distribution has relevance to the
metabolic requirements according to their habitat. The
minimal use of the TAT pathway among the smaller gen-
omes is expected, as the host-obligates readily obtain their
nutrients from their respective hosts and therefore lipid
modification of the metabolizing enzymes would aid their
assimilation. On the other hand, extensive users of TAT
among small genomes are mostly extremophiles requiring
both transport/binding proteins and enzymes for nutrient
uptake and assimilation.
Predicted TAT-Dependent Lipoproteins as Transporters
and Binding Proteins
According to the analysis, components of ABC transporters,
RND efflux pump, TRAP transporters, and electron transfer
proteins were predicted as TAT-dependent lipoproteins in
0
50
100
150
200
250
300
350
Aqu
atic
hab
itat
Soil
Hab
itat
Path
ogen
sSy
mbi
onts
Extre
mop
hile
sFe
rmen
tativ
e or
gani
sm
Oth
ers
No.
of
Gen
omes
Without TAT-dependent Lipoproteins
With TAT-dependent Lipoproteins
Fig. 2 Prokaryotes surviving in complex habitats predominantly use
the TAT pathway for lipoprotein export: The bar graph shows the
distribution of bacterial genomes with predicted TAT-dependent
lipoproteins (filled bar) and without predicted TAT-dependent
lipoproteins (gray filled bar) surviving in complex habitats or host-
associated environments. Free-living bacteria surviving in complex
environments such as soil and aquatic habitats prefer TAT, with the
usage increasing with the complexity of the habitat. Pathogens and
other host-obligates use TAT lesser than free-living bacteria as they
depend on a host for survival. The data on lifestyle and habitat for the
microbial genomes was obtained from http://www.ncbi.nlm.nih.gov/
genomes/lproks.cgi
J Mol Evol
123
the extensive users of small and big genomes (Fig. 5). Out of
the 562 transporters/binding proteins, 194 are components
of ABC transporters, which constitute as high as 53% of the
total predicted TAT-dependent lipoproteins in small gen-
omes (predominantly from Haloarchaea) and 33% in big
genomes (mostly in soil bacteria of Actinobacteria). Among
the transporters/binding proteins of minimal users of big
genomes, the outer-membrane protein component of the
RND efflux pump (used in multidrug resistance mechanism)
is more common, especially in Gram-negative pathogens
like Burkholderia, Pseudomonas, Escherichia, Shigella, and
Xanthomonas. OprA of Burkholderia and OprM of Pseu-
domonas, which were predicted to be TAT-dependent
lipoproteins in this analysis, had been demonstrated to be
lipoproteins (Nakajima et al. 2000; Moore et al. 1999).
Substrate-/solute-binding proteins constitute 36% of the
total TAT-dependent transporter/binding lipoproteins. Such
lipoproteins include extracellular solute-binding proteins
Enzymes, 503, 22%
Superfamily unassigned hypothetical proteins, 228, 10%
Transporters and Binding proteins, 562, 24%
Superfamily assigned hypothetical proteins, 419, 18%
Other proteins, 595, 26%
Fig. 3 Transporters/binding proteins and enzymes predominate the
known functions of predicted TAT-dependent lipoproteins in pro-
karyotes: Pie-chart showing the functional distribution of 2,307
predicted TAT-dependent lipoproteins from bacterial and archaeal
genomes that contain a TAT machinery. The predicted TAT-
dependent lipoproteins are transporters/binding proteins, enzymes,
hypothetical proteins with superfamily-assignments and proteins of
unknown functions
50
50
100
150
200
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250
50
100
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Pero
xida
ses/S
OD
DM
SO R
educ
tase
s
Fum
arat
e Red
ucta
ses
Thio
redo
xins
Mol
ybdo
prot
eins
Oth
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xido
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ctas
es
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idas
es/P
rote
ases
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rase
s/Dea
cety
lase
s/Li
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s
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amas
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ses/D
ipho
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tase
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s
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ansf
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es
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rans
porte
rsRN
D-E
fflu
x
TRA
P-Tr
ansp
orte
rs
Elec
tron
trans
port
prot
eins
Iron-
ente
roba
ctin
s
Subs
trate
/Sol
ute-
Bin
ding
pro
tein
s
Oth
ers B
indi
ng an
d
trans
port
prot
eins
Hyp
othe
tical
/Unk
now
n
lipop
rote
ins
Lyas
esLi
gase
s
No.
of
TA
T-d
epen
dent
lipo
prot
eins
Smal
lG
enom
esB
ig G
enom
es
Oth
er T
AT-
depe
nden
t
Lipo
prot
eins
Oxido-reductases Hydrolases
Enzymes Transporters/Bindingproteins
0
Smal
lG
enom
esB
ig G
enom
es
Min
imal
TA
T u
ser
Ext
ensi
ve T
AT
use
r
Fig. 4 TAT-dependent
lipoprotein enzymes, rather than
transporters/binding proteins are
predominant among minimal
users (largely host-obligates),
the latter are preferred by
extensive users surviving in
complex habitats: The bargraph shows the functional
distribution of predicted TAT-
dependent lipoproteins
organized as functional class of
proteins (horizontal axis) in
relation to the frequency of
occurrence (vertical axis on the
left), the genome size and extent
of TAT usage (as defined in
Fig. 1, vertical axis on the right)
J Mol Evol
123
generally involved in chemoreception and transport of
nutrients and they fall in to either family-1 (specific to
oligosaccharides, a-glycerol phosphate, and iron) or family-
5 (specific to peptides and nickel, Tam and Saier 1993) of
binding proteins. Among the extensive TAT users of big
genomes, 72% of these proteins are contributed by soil
bacteria of Actinobacteria and 20% by sludge-dwellers of
Chloroflexi. Even among the smaller genomes, 60% of the
predicted TAT-dependent extracellular binding lipoproteins
belong to soil dwellers of Actinobacteria and 14% to
aquatic Cyanobacteria.
Predicted TAT-Dependent Lipoproteins as Enzymes
The next abundant functional class of predicted TAT-
dependent lipoproteins is enzymes. These are predomi-
nately hydrolases and oxido-reductases (typical TAT sub-
strates) (Fig. 6). Among small genomes 32 of the 180
predicted TAT-dependent lipoproteins were enzymes in
minimal TAT users, whereas only 43 of the 400 predicted
TAT-dependent lipoproteins were enzymes in extensive
TAT users. Among big genomes, there were 205 enzymes
among 800 TAT-dependent lipoproteins in the minimal
TAT user category and 223 enzymes out of 1000 TAT-
dependent lipoproteins predicted in the extensive TAT user
category. Hydrolases (128) predominate compared to
oxido-reductases (46) among the minimal users of big
genomes; both are almost equal in numbers among the
extensive users of big genomes (102 and 95, respectively)
as well as among the minimal users of small genomes (10
and 11, respectively).
Among the hydrolases, irrespective of genome size,
peptidases and esterases are the major types seen in mini-
mal and extensive users; lytic transglycosylases and
phosphatases are also major types in minimal users.
Hydrolases are commonly seen in pathogenic or symbiotic
bacteria. For instance, b-lactamases of Mycobacteria
and Burkholderia, that confer penicillin-resistance, were
predicted to be TAT-dependent lipoproteins; the one from
M. smegmatis has been experimentally verified to be TAT-
dependent (McDonough et al. 2005). Peptidases, phos-
phodiesterases, and alkaline phosphatases were the pre-
dominant types of hydrolases predicted as TAT-dependent
lipoproteins among marine bacteria and other free-living
bacteria. It is also interesting to note that bulk of the oxido-
reductases predicted as TAT-dependent lipoproteins among
the minimal users of big genomes belonged to one partic-
ular subclass, the DMSO reductases (26/177). The majority
of these were molybdenum containing DMSO reductases
of Shewenella sps.
Hypothetical Proteins belong to Mostly Substrate-
Binding Proteins and Enzymes such as Hydrolases
and Oxido-Reductases
Out of 647 hypothetical proteins, 419 could be assigned to
SCOP domains using the superfamily database (Wilson
et al. 2009). The significant entries indicated that like the
known TAT-dependent lipoproteins, the predicted func-
tional domains also belonged to the categories of enzymes,
substrate-binding proteins and transport proteins (Fig. 7).
Among enzymes, a fairly even distribution of hydrolases
(38%) and oxido-reductases (35%) were seen, followed by
transferases (14%), isomerases and lyases (4%). Periplas-
mic-binding protein-like I and II superfamilies (44%)
predominated the functional class of binding proteins and
transporters. Cytochromes and electron transport proteins
(14%), components of the RND efflux pump (7%) and
metal-binding proteins, predominantly copper- and iron-
binding proteins were also predicted. It is intriguing that
domains of outer-membrane lipoprotein localization fac-
tors were exclusively assigned to hypothetical TAT-
dependent lipoproteins of Gram-positive Bacillus species.
Even the hypothetical TAT-dependent lipoproteins turned
out to be oxidoreductases, hydrolases and binding proteins
by SCOP domain assignment.
ABC-Transporters, 194, 35%
RND-Efflux, 58, 10%TRAP-Transporters, 24, 4%
Electron transfer proteins, 49, 9%
Iron-enterobactins, 9, 2%
Substrate/Solute- Binding proteins, 206, 36%
Other Binding and transport proteins, 22, 4%
Fig. 5 Substrate/solute-binding proteins and components of ABC
transporters form majority of transporters and binding proteins among
the predicted TAT-dependent lipoproteins: The pie-chart shows
functional distribution of predicted TAT-dependent lipoproteins as
transporters/binding proteins. In addition to ABC transporters, the
outer-membrane component of the RND efflux system, electron
transport proteins, iron-enterobactins and components of TRAP
transporters are also predicted as TAT-dependent lipoproteins
J Mol Evol
123
Oxido Reductases, 177, 35%
Hydrolases, 255, 50%
Transferases, 18, 4%
Lyases, 9, 2%Ligases, 35, 7%
Isomerases, 9, 2%
Peroxidases/SOD, 13, 7%DMSO Reductases,
26, 15%Fumarate Reductases,
14, 8%Thioredoxins, 10, 6%
Molybdopterins, 24, 14%
Other Oxidoreductases, 90, 50%
Peptidases/Proteases, 57, 23%
Esterases/Deacetylases/Lipases, 53, 21%
Beta-lactamases, 28, 11%Phosphatases/Diphosphatases/Phosphohydrolases, 34, 13%
Lytic transglycosylases, 39, 15%
Other hydrolases, 44, 17%
A
B
Fig. 6 Majority of the
predicted TAT-dependent
lipoproteins as enzymes are
hydrolases and oxido-
reductases: Pie-chart shows
distribution of enzyme classes
among predicted TAT-
lipoproteins. Other enzyme
class, transferases, isomerases,
ligases, and lyases are also
predicted as TAT-dependent
lipoproteins. The majority is
further grouped into sub-
classes; inset A shows
subclasses of oxido-reductases
and inset B shows subclasses of
hydrolases as predicted TAT-
lipoproteins
Enzymes, 201, 49%
Transporters and binding proteins, 98, 23%
Hypothetical proteins, 10, 2%
Proteins with other functions, 110, 26%
Periplasmic binding protein, 42, 44%Cytochromes and Electron
transport proteins, 14, 14%
Other binding proteins, 13, 13%
RND efflux, 7, 7%
Lipoprotein localization factors, 5, 5%
Cupredoxins, 5, 5%
ABC transporter, 5, 5%
Ferritin - like and HIPIP 4, 4%
Other metal - binding proteins, 3, 3%
Hydrolases, 76, 38%
Oxidoreductases, 69, 35%
Transferases, 28, 14%
Isomerases, 8, 4%Lyases, 7, 4%
Ligases, 9, 5%A
B
Fig. 7 Hypothetical TAT-
dependent lipoproteins with
superfamily-assignments are
enzymes, substrate-binding
proteins, and transport proteins:
Hydrolases and oxido-
reductases contribute to the
majority of enzymes class.
Periplasmic-binding protein-
like I and II superfamilies
predominate the functional class
of binding proteins and
transporters. Cytochromes and
electron transport proteins,
RND efflux pump component
and copper- and iron-binding
proteins are also predicted
among this functional class
J Mol Evol
123
Discussion
Knowledge about bacterial lipid modification has been
gradually advancing with the identification of several
bacterial lipoproteins and from the recent studies of lipo-
protein biosynthesis and targeting (Sankaran and Wu 1994;
Selvan and Sankaran 2008; Hutchings et al. 2009). In fact,
this understanding has led to the design of strategies for
converting nonlipoproteins to lipoproteins that could have
potential biotechnological applications such as ELISA,
biosensors, vaccines, targeted-drug delivery and also in
display-libraries (Kamalakkannan et al. 2004). The
recently identified translocation system (TAT pathway),
except for indirect experimental evidence (Valente et al.
2007), remains inadequately explored for its role in the
export of bacterial prolipoproteins. As a first step, the
prevalence and significance of TAT-dependent lipoproteins
in 696 prokaryotic genomes were investigated using the
new prediction tool ‘‘TATLIPO.’’ This was developed
based on the currently accepted prediction tools, TatP and
DOLOP for TAT substrates and bacterial lipoproteins,
respectively. In the absence of an experimentally verified
dataset, its predictability, as judged by the correlation of
predicted TAT-dependent lipoproteins to the presence of
TAT machinery in prokaryotes was 95% [(696 - 34)/696].
However, the prediction of TAT-dependent lipoproteins in
34 prokaryotes lacking TAT machinery and no predicted
TAT-dependent lipoproteins in 127 prokaryotes possessing
TAT machinery indicated an overall accuracy of prediction
of 77%. It is noteworthy that in cases where TAT com-
ponents, TatC and TatA/E are missing, on the average only
one or two TAT-dependent lipoproteins were identified, of
which 60% were hypothetical. In cases where the TAT-
dependent lipoproteins were not predicted even though
TAT components were present, the TAT usage was found
to be limited, averaging only five TAT substrates per
organism compared to the overall average of 27 per
organism, as deduced using TatP for 696 prokaryotic
genomes.
According to Bolhuis (2002), the proteins of halophiles
tend to fold rapidly and are thereby rendered Sec-incom-
patible; the higher TAT usage of halophiles among the
extremophiles of Euryarchaeota could be an attempt to
escape protein aggregation and precipitation at high intra-
cellular salt concentrations (4–5 M of K?). Similarly such
selection pressures could have driven lipoproteins to
become TAT-dependent. In another instance, Firmicutes
contain mostly pathogens and minimal users of TAT.
However, there are two exceptions that signify the role of
TAT-dependent lipid modification in environmental adap-
tation. Desulfitobacterium hafniense Y51, a dehalorespiring
firmicute thrives in the complex milieu, tetrachloroethene-
contaminated soil, by virtue of the presence of a large
number of specialized electron donors and acceptors
(Nonaka et al. 2006), many of which are TAT-dependent
lipoproteins. The Firmicute, Symbiobacterium thermophi-
lum, a marine thermophile with a high G ? C content, is an
extensive TAT user (Sugihara et al. 2008).
For lipoproteins in general a direct correlation between
the number and the genome size, had been reported (Babu
et al. 2006). However, no correlation could be observed
between the number of TAT-dependent lipoproteins and
the genome size, the number of lipoproteins or the number
of TAT substrates. This is similar to the case of proteins
involved in the secretion and transport of inorganic ions
and such an adaptation in response to environmental sig-
nals was found not to correlate with the genome size
(Konstantinidis and Tiedje 2004). However, the increase in
TAT usage for lipoproteins in prokaryotes with high
G ? C content is interesting and points to habitat-based
adaptation, as these are normally free-living in complex
habitats like soil. According to Bentley and Parkhill
(2004), free-living prokaryotes possess larger genomes and
are equipped to survive in a complex and variable envi-
ronment whereas, pathogenic bacteria in general have
smaller genomes, as they can readily acquire nutrition from
their stable niche. This correlation is reflected in our phy-
logenetic analysis of the largest phylum, Proteobacteria, in
which, irrespective of the phylogeny, pathogenic bacteria
appears as poor users of TAT, while the free-living and soil
bacteria are moderate-to-extensive users. To scavenge
nutrients from such competitive and variable habitats,
prokaryotes depend largely on high-affinity substrate-
binding proteins of transporters, as seen in the ABC
transport machinery (Albers et al. 2004). For instance,
Actinobacteria, which comprises essentially of soil-dwell-
ing bacteria, has been predicted to be an extensive TAT
user for lipoprotein biosynthesis, especially for substrate-
binding lipoproteins. Such high-affinity binding at the
surface of the organism is essential for an efficient response
to the amount and quality of available nutrients in a
complex and altering milieu and to even physico-chemical
conditions (Roszak and Colwell 1987).
Electron transfer is an essential bioenergy metabolism
intimately coupled to nutrient utilization. Therefore, their
coupling should be efficient to maximize the chances of
surviving in challenging conditions. Halocyanin, a copper-
containing lipoprotein is involved in the transfer of elec-
trons in high-salt habitats. The halocyanin isolated from
Natronomonas pharaonis contains characteristic N-acetyl
S-diphytanyl Cys as the N-terminal amino acid similar to
that of eubacteria (Mattar et al. 1994). Interestingly,
our analysis has also predicted that these halocyanins are
TAT-dependent lipoproteins, suggesting the role of TAT-
dependent lipoproteins for survival in high-ionic environ-
ments. Similarly, in Shewanella, significant numbers of
J Mol Evol
123
ferredoxins that mediate transfer of electrons in several
metabolic reactions are predicted to be TAT-dependent
lipoproteins. Being anaerobic inhabitants of sediments or
deep sea environments, this genus employs ferredoxins for
respiration while utilizing a variety of terminal electron
acceptors such as nitrate, nitrite, thiosulfate, sulfite etc.,
abundant in such habitats (Heidelberg et al. 2002).
The lifestyle adaptation of prokaryotes is exemplified by
the presence of lipid-modified digestive enzymes tethered
to the surface for effective accumulation of nutrients (Na-
varre and Schneewind 1999). The presence of hydrolases
among extensive users of TAT signifies the digestive and
nutrition acquisition capabilities. Peptidases, phosphodies-
terases, and alkaline phosphatases, predicted in marine and
free-living bacteria are essential to metabolize organic
matter in ever-changing mineral rich habitats. For instance,
the inorganic phosphate content in marine habitats is low
(3 nM) and therefore alkaline phosphatases are required to
liberate phosphate from organic phosphates (Hassan and
Pratt 1977). Oxidoreductases are the other major class of
enzymes predicted as TAT-dependent lipoproteins and are
involved in detoxification and downstream metabolism of
nutrients. The DMSO reductases of Shewanella sp. are
essential for extracellular respiration of DMSO, which is
abundant in aquatic environments due to its release by
algae and other microplanktons. The enzyme has been
found localized to the cell surface of Shewenella to enable
efficient capture of DMSO from the complex habitat
(Gralnick et al. 2006). It is noteworthy that our analysis had
predicted this proven lipoprotein as TAT-dependent and
thus pointing to niche-based adaptation. The requirement
of such lipoproteins, especially at the cell surface to
metabolize substrates, reveals the significance of TAT-
dependent lipid modification in environmental adaptation.
In a similar lifestyle adaptation (Cases et al. 2003), the
larger number of transcriptional regulators identified in
free-living bacteria rather than in intracellular pathogens
and endosymbionts, was attributed to rapid adaptation to
environmental conditions.
Taken together, the predicted functional profile of TAT-
dependent lipoproteins closely matches the expected
functional attributes necessary for the adaptation of a
prokaryote to its surroundings, particularly providing an
advantage to survive under challenging conditions.
Implications of the Present Finding in Lipoprotein
Biosynthesis and Applications
Bacterial lipoprotein biosynthesis has been exploited by
our group and a few others to engineer proteins and express
them as lipoproteins for a variety of applications such as
enhanced antigenicity, outer surface display, and liposomal
integration. For instance, the use of bacterial lipid
modification as a novel protein engineering method was
successfully demonstrated by Kamalakkannan et al. (2004)
and it has opened-up promising applications. However,
these strategies if based on the erroneous premise that all
lipoprotein biosynthesis and translocation depend on the
Sec-machinery, would be incompatible with prefolded
proteins. Therefore, the new protein engineering design for
such fast-folding or prefolded proteins would have to
involve fusion of TAT-dependent lipid modification signals
in the signal peptide. Similarly the major aims of metabolic
engineering include providing or enhancing the viability of
an organism in harsh environments or to utilize specific
compounds for useful metabolic conversions. Such appli-
cations would most probably require fast folding substrate-
binding proteins or cofactor-requiring enzymes on the
surface of a bacterium. TAT-dependent lipoprotein modi-
fication could provide a convenient strategy to engineer
such target proteins for such applications, as in the adap-
tation that appears to be working in nature. Already,
uptake-hydrogenases, hydrogenase-1 and hydrogenase-2
(known TAT substrates) have been targeted for enhanced
production of hydrogen in E. coli (Maeda et al. 2007). The
database created from the current analysis can be useful to
select such targets.
Conclusion
Prompted by the presence of TAT-signal sequence in
bacterial lipoproteins, an extensive and up-to-date com-
putational analysis of possible role of TAT in lipoprotein
export across the membrane was undertaken. It revealed
that many of these are substrate-binding proteins, trans-
porters, enzymes that could be a useful adaptation for
viability and survival in a niche. These predicted TAT-
dependent lipoproteins are mostly present in free-living
prokaryotes in complex environments or niche, a striking
example being Haloarchea; host-obligates hardly use TAT
for lipoprotein transport. Though there is no correlation
with the genome size or phylogeny a rough correlation is
seen with respect to G ? C content. There is a tendency to
use TAT extensively with increasing G ? C content. Our
findings also have implications for potential protein engi-
neering applications. This comprehensive study reveals the
significance of the TAT pathway in lipoprotein biosyn-
thesis and its understanding is essential in developing
versatile protein and metabolic engineering tools.
Acknowledgments We thank A. Tamil Selvan for the algorithm
and script. We are grateful to Prof. Edward J. Behrman, Ohio State
University, USA for his critical inputs to improve the readability of
the manuscript and Prof. Venkat Gopalan, Ohio State University,
USA for his valuable help. UGC-DRS and DBT-Center of Excellence
programmes are acknowledged for financial support and fellowship to
J Mol Evol
123
HS. MMB acknowledges the Medical Research Council, UK, Darwin
College Cambridge and Schlumberger Ltd. for support.
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