The complete genome of Zunongwangia profunda SM-A87 reveals its adaptation to the deep-sea environment and ecological role in sedimentary organic nitrogen degradation.
ABSTRACT Zunongwangia profunda SM-A87, which was isolated from deep-sea sediment, is an aerobic, gram-negative bacterium that represents a new genus of Flavobacteriaceae. This is the first sequenced genome of a deep-sea bacterium from the phylum Bacteroidetes.
The Z. profunda SM-A87 genome has a single 5 128 187-bp circular chromosome with no extrachromosomal elements and harbors 4 653 predicted protein-coding genes. SM-A87 produces a large amount of capsular polysaccharides and possesses two polysaccharide biosynthesis gene clusters. It has a total of 130 peptidases, 61 of which have signal peptides. In addition to extracellular peptidases, SM-A87 also has various extracellular enzymes for carbohydrate, lipid and DNA degradation. These extracellular enzymes suggest that the bacterium is able to hydrolyze organic materials in the sediment, especially carbohydrates and proteinaceous organic nitrogen. There are two clustered regularly interspaced short palindromic repeats in the genome, but their spacers do not match any sequences in the public sequence databases. SM-A87 is a moderate halophile. Our protein isoelectric point analysis indicates that extracellular proteins have lower predicted isoelectric points than intracellular proteins. SM-A87 accumulates organic osmolytes in the cell, so its extracelluar proteins are more halophilic than its intracellular proteins.
Here, we present the first complete genome of a deep-sea sedimentary bacterium from the phylum Bacteroidetes. The genome analysis shows that SM-A87 has some common features of deep-sea bacteria, as well as an important capacity to hydrolyze sedimentary organic nitrogen.
- [show abstract] [hide abstract]
ABSTRACT: Rates of transformation, recycling and burial of nitrogen and their temporal and spatial variability were investigated in deep-sea sediments of the Porcupine Abyssal Plain (PAP), NE Atlantic during eight cruises from 1996 to 2000. Benthic fluxes of ammonium (NH4) and nitrate (NO3) were measured in situ using a benthic lander. Fluxes of dissolved organic nitrogen (DON) and denitrification rates were calculated from pore water profiles of DON and NO3, respectively. Burial of nitrogen was calculated from down core profiles of nitrogen in the solid phase together with 14C-based sediment accumulation rates and dry bulk density. Average NH4 and NO3-effluxes were 7.4 ± 19 μmol m−2 d−1 (n = 7) and 52 ± 30 μmol m−2 d−1 (n = 14), respectively, during the period 1996–2000. During the same period, the DON-flux was 11 ± 5.6 μmol m−2 d−1 (n = 5) and the denitrification rate was 5.1 ± 3.0 μmol m−2 d−1 (n = 22). Temporal and spatial variations were only found in the benthic NO3 fluxes. The average burial rate was 4.6 ± 0.9 μmol m−2 d−1. On average over the sampling period, the recycling efficiency of the PON input to the sediment was ∼94% and the burial efficiency hence ∼6%. The DON flux constituted ∼14% of the nitrogen recycled, and it was of similar magnitude as the sum of burial and denitrification. By assuming the PAP is representative of all deep-sea areas, rates of denitrification, burial and DON efflux were extrapolated to the total area of the deep-sea floor (>2000 m) and integrated values of denitrification and burial of 8 ± 5 and 7 ± 1 Tg N year−1, respectively, were obtained. This value of total deep-sea sediment denitrification corresponds to 3–12% of the global ocean benthic denitrification. Burial in deep-sea sediments makes up at least 25% of the global ocean nitrogen burial. The integrated DON flux from the deep-sea floor is comparable in magnitude to a reported global riverine input of DON suggesting that deep-sea sediments constitute an important source of DON to the world ocean.Progress In Oceanography. 01/2004;
- [show abstract] [hide abstract]
ABSTRACT: Life on Earth most likely originated as microorganisms in the sea. Over the past approximately 3.5 billion years, microorganisms have shaped and defined Earth's biosphere and have created conditions that have allowed the evolution of macroorganisms and complex biological communities, including human societies. Recent advances in technology have highlighted the vast and previously unknown genetic information that is contained in extant marine microorganisms, from new protein families to novel metabolic processes. Now there is a unique opportunity, using recent advances in molecular ecology, metagenomics, remote sensing of microorganisms and ecological modelling, to achieve a comprehensive understanding of marine microorganisms and their susceptibility to environmental variability and climate change. Contemporary microbial oceanography is truly a sea of opportunity and excitement.Nature Reviews Microbiology 11/2007; 5(10):759-69. · 22.49 Impact Factor
- [show abstract] [hide abstract]
ABSTRACT: Chemical analyses of the pore waters from hundreds of deep ocean sediment cores have over decades provided evidence for ongoing processes that require biological catalysis by prokaryotes. This sub-seafloor activity of microorganisms may influence the surface Earth by changing the chemistry of the ocean and by triggering the emission of methane, with consequences for the marine carbon cycle and even the global climate. Despite the fact that only about 1% of the total marine primary production of organic carbon is available for deep-sea microorganisms, sub-seafloor sediments harbour over half of all prokaryotic cells on Earth. This estimation has been calculated from numerous microscopic cell counts in sediment cores of the Ocean Drilling Program. Because these counts cannot differentiate between dead and alive cells, the population size of living microorganisms is unknown. Here, using ribosomal RNA as a target for the technique known as catalysed reporter deposition-fluorescence in situ hybridization (CARD-FISH), we provide direct quantification of live cells as defined by the presence of ribosomes. We show that a large fraction of the sub-seafloor prokaryotes is alive, even in very old (16 million yr) and deep (> 400 m) sediments. All detectable living cells belong to the Bacteria and have turnover times of 0.25-22 yr, comparable to surface sediments.Nature 03/2005; 433(7028):861-4. · 38.60 Impact Factor
Qin et al. BMC Genomics 2010, 11:247
The complete genome of Zunongwangia profunda
SM-A87 reveals its adaptation to the deep-sea
environment and ecological role in sedimentary
organic nitrogen degradation
© 2010 Qin et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons At-
tribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any
medium, provided the original work is properly cited.
Qi-Long Qin†1, Xi-Ying Zhang†1, Xu-Min Wang2, Gui-Ming Liu2, Xiu-Lan Chen1, Bin-Bin Xie1, Hong-Yue Dang3, Bai-
Cheng Zhou1, Jun Yu2 and Yu-Zhong Zhang*1
Background: Zunongwangia profunda SM-A87, which was isolated from deep-sea sediment, is an aerobic, gram-
negative bacterium that represents a new genus of Flavobacteriaceae. This is the first sequenced genome of a deep-sea
bacterium from the phylum Bacteroidetes.
Results: The Z. profunda SM-A87 genome has a single 5 128 187-bp circular chromosome with no extrachromosomal
elements and harbors 4 653 predicted protein-coding genes. SM-A87 produces a large amount of capsular
polysaccharides and possesses two polysaccharide biosynthesis gene clusters. It has a total of 130 peptidases, 61 of
which have signal peptides. In addition to extracellular peptidases, SM-A87 also has various extracellular enzymes for
carbohydrate, lipid and DNA degradation. These extracellular enzymes suggest that the bacterium is able to hydrolyze
organic materials in the sediment, especially carbohydrates and proteinaceous organic nitrogen. There are two
clustered regularly interspaced short palindromic repeats in the genome, but their spacers do not match any
sequences in the public sequence databases. SM-A87 is a moderate halophile. Our protein isoelectric point analysis
indicates that extracellular proteins have lower predicted isoelectric points than intracellular proteins. SM-A87
accumulates organic osmolytes in the cell, so its extracelluar proteins are more halophilic than its intracellular proteins.
Conclusion: Here, we present the first complete genome of a deep-sea sedimentary bacterium from the phylum
Bacteroidetes. The genome analysis shows that SM-A87 has some common features of deep-sea bacteria, as well as an
important capacity to hydrolyze sedimentary organic nitrogen.
The average depth of the oceans is about 3 800 m, and
almost 60% of the earth's surface is deep-sea floor (water
depth greater than 2 000 m) . Although most of the
deep-sea floor environment is characterized by darkness,
high hydrostatic pressure and low temperatures, more
than half of the world's prokaryotes live in sub-seafloor
sediments [2-4], which play a major role in marine bio-
geochemical cycling . Every year, massive amounts of
particulate organic matter (POM) are transported to the
deep layers of the ocean floor, forming a large pool of car-
bon and nitrogen . However, how this organic material
is degraded, as well as the types of bacteria involved and
the enzymes used, are still unclear, especially for the deg-
radation of sedimentary organic nitrogen (SON) . To
date, numerous efforts have been made to clarify the
mechanism of SON degradation, including investigations
of the diversity of bacteria and proteases involved in SON
degradation [8,9]. Researchers have also characterized
some extracellular proteases from sedimentary bacteria
and elucidated their ecological role in SON degradation
[10-13]. However, the role of deep-sea bacteria in SON
degradation and cycling has never been analyzed at a
genomic level. Genome analyses of deep-sea het-
* Correspondence: firstname.lastname@example.org
1 State Key Lab of Microbial Technology, Marine Biotechnology Research
Center, Shandong University, Jinan 250100, PR China
† Contributed equally
Full list of author information is available at the end of the article
Qin et al. BMC Genomics 2010, 11:247
Page 2 of 10
erotrophic bacteria would provide a better understanding
of the deep-sea nitrogen cycle, and reveal to what extent
bacteria affect the deep-sea environment .
Bacteroidetes (formerly Cytophaga-Flavobacterium-
Bacteroides (CFB)) are a widespread and diverse group of
bacteria that can be found throughout the sea, from sur-
face water to deep-sea sediment. Studies of both culti-
vated and uncultivated marine Bacteroidetes have shown
that Bacteroidetes are able to efficiently consume biopoly-
mers such as protein and chitin [15,16], which make up a
significant fraction of the high-molecular-weight dis-
solved organic matter (HMW DOM) pool in the ocean
. Biopolymer degradation is considered to be the rate-
limiting step in DOM mineralization by marine microor-
ganisms, and Bacteroidetes are hypothesized to play a key
role in this process in the oceans . Genome sequence
data have been extremely helpful in the development of
detailed hypotheses on the role of specific Bacteroidetes
members in marine biogeochemical cycling. An analysis
of the genome of Bacteroidetes 'Gramella forsetii'
KT0803, a bacterioplankton isolated from North Sea sur-
face waters during a phytoplankton bloom, indicated that
it is efficient at degrading biopolymers, especially pro-
teins [18,19]. Metagenomic studies have also reported the
distribution and functional
Cytophaga-like hydrolases in the Sargasso Sea and west-
ern Arctic Ocean and described hydrolase-containing
genome fragments of Antarctic marine Bacteroidetes
[20,21]. However, while Bacteroidetes have been fre-
quently encountered in the analysis of sedimentary bacte-
rial diversity, no complete genome analysis of a deep-sea
sedimentary Bacteroidetes has yet been published [15,16].
This type of analysis could be used to address how the
organisms' genetic inventories reflect both their SON
remineralization capabilities and their adaptation to the
Wangia profunda SM-A87 (hereafter called SM-A87),
isolated at a depth of 1 245 m from deep-sea sediment in
the southern Okinawa Trough with in situ temperature of
4.7°C, is a newly described species of Bacteroidetes and
represents a new genus of Flavobacteriaceae . It was
renamed Zunongwangia profunda in the International
Journal of Systematic and Evolutionary Microbiology
(IJSEM) Validation List no. 116. In this study, we report
its complete genome sequence, which represents the first
genome of a deep-sea bacterium of the phylum Bacteroi-
detes. In addition, we performed a genomic comparison
with two bacteria of the family of Flavobacteriaceae from
surface seawater, and two bacteria from a cold deep-sea
environment. Our genomic analysis of strain SM-A87
indicates that it is capable of degrading biopolymer
sources and sheds light on its adaptation to the deep-sea
analysis of specific
Results and discussion
General genome features
General features of the Z. profunda SM-A87 genome are
summarized in Table 1. The genome has a single 5.1-Mbp
circular chromosome with no extrachromosomal ele-
ments. The G+C content of the genome is 36.2%, which is
slightly higher than the experimentally determined 35.8%
. The genome harbors 4 653 predicted open reading
frames (ORFs), of which 69.4% are annotated with known
or predicted functions. About 50% of SM-A87 ORFs have
the highest similarity to those in the published genome of
G. forsetii KT0803. SM-A87 has 47 tRNA genes and three
Figure 1 shows the proportions of proteins belonging to
clusters of orthologous groups (COGs) in SM-A87 and
several other bacterial groups. The deep-sea bacteria
(SM-A87, Photobacterium profundum SS9 and She-
wanella piezotolerans WP3) have an average of 2.35%
more proteins belonging to COG K (transcription), and
2.11% more proteins belonging to COG T (signal trans-
duction mechanisms) than the shallow-water bacteria
(Flavobacterium psychrophilum and Gramella forsetii
KT0803). These differences are statistically significant (p
SM-A87 has a full set of genes for glycolysis, the pentose
phosphate pathway and the tricarboxylic/citric acid cycle.
The strain has five predicted lactate dehydrogenases, two
L- and three D-, and also contains predicted ethanol-pro-
ducing enzymes including aldehyde dehydrogenase
(ZPR_1384, ZPR_3649) and alcohol dehydrogenase
(ZPR_4362). These enzymes may help the bacterium to
survive in the low-oxygen environment of the deep sea.
SM-A87 contains predicted cytochrome bd ubiquinol
oxidase subunits I (ZPR_1985) and II (ZPR_1985). This
oxidase is related to adaptation to microaerobic condi-
tions in the deep sea . According to the Kyoto Ency-
clopedia of Genes and Genomes (KEGG) pathway map of
Table 1: General features of the Z. profunda SM-A87
Size (bp) 5 128 187
G + C content36.2%
Number of predicted ORFs4 653
Average ORF length (bp) 960
Hypothetical proteins %13.5%
Qin et al. BMC Genomics 2010, 11:247
Page 3 of 10
SM-A87, fructose and mannose can be converted to fruc-
tose-6p, and galactose can be converted to glucose-1p;
both fructose-6p and glucose-1p are then degraded
through glycolysis. SM-A87 harbors a predicted keto-
deoxy-phosphogluconate aldolase (ZPR_2957), which is
the key enzyme of the Entner-Doudoroff metabolic path-
way. This strain also contains the enzymes that utilize
most amino acids. All these features confer a metabolic
versatility to SM-A87 that allows it to utilize sparse and
sporadic nutrients in the deep-sea environment.
SM-A87 has all the genes required for fatty acid oxida-
tion. However, 3R-hydroxymyristoyl ACP dehydrase, a
component of the fatty acid biosynthesis pathway, was
not found by genome annotation. This absence may be
due to the low similarity of this gene to those in the data-
bases or to convergent evolution from other functionally
similar enzymes with divergent sequences. Phosphati-
dylethanolamine is the only phospholipid that has been
experimentally identified in Zunongwangia profunda
. The genome analysis suggests that phosphatidyleth-
anolamine is derived from phosphatidylserine, which is
synthesized from glycerate.
SM-A87 has all of the components of the oxidative
phosphorylation pathway but does not contain any rho-
dopsin or retinal genes, consistent with the dark deep-sea
environment in which the strain thrives.
Most nutrients arrive in the deep sea in an annual pulse,
and the bacteria in the deep sea can sense this food pulse
and respond accordingly . A widespread sensing sys-
tem used by bacteria is the two-component signal trans-
duction system, which consists of a signal sensor
histidine kinase and a response regulator [25,26]. SM-
A87 harbors 47 predicted sensor histidine kinases, the
most of any of the compared strains (Table 2), which indi-
cates its strong ability to sense environment signals. SM-
A87 has nine predicted two-component operons, each of
which is composed of a histidine kinase and a response
regulator that may form a one-to-one phosphotransfer
pair. SM-A87 has three rRNA operons, suggesting that it
can respond to nutrient enrichment rapidly and grow
quickly . SM-A87 can form colonies of 1-3 mm in
diameter on a rich medium after 48 h of cultivation at
Figure 1 COG category percentage of Z. profunda SM-A87 and other compared bacteria.
Qin et al. BMC Genomics 2010, 11:247
Page 4 of 10
SM-A87 contains 22 genes encoding RagB/SusD family
proteins in its genome, while the other compared
genomes have fewer or none (Table 2). RagB is a protein
involved in signaling and SusD is an outer membrane
protein involved in nutrient binding [28,29]. Nineteen of
the RagB/SusD family protein genes are each adjacent to
a TonB-dependent receptor gene, forming 19 predicted
operons. Of the 19 predicted operons, 12 are adjacent to
predicted glycosyl hydrolases or peptidases [see Addi-
tional file 1]. Specifically for the genes from ZPR_1020 to
ZPR_1033, there are two glycosidase genes, two esterase
genes, one xylanase gene and seven glycosyl hydrolase
genes next to the operon, implying that SM-A87 can
sense and respond to sugar sources. The genome also
contains 27 putative outer membrane protein genes,
which are probably involved in nutrient binding. All these
features imply that SM-A87 has the ability to sense extra-
cellular nutrients such as sugars and proteins.
Many deep-sea bacteria produce exopolysaccharides that
help them survive in the extreme deep-sea environment
. Reports suggest that these polysaccharides help the
bacteria concentrate organic matter, absorb metal ions,
and form biofilms in the marine environment [31,32].
Different glycosyltransferases can contribute to the bio-
synthesis of disaccharides, oligosaccharides, and polysac-
charides . Our experimental results show that strain
SM-A87 can produce large quantities of capsular polysac-
charide (data not shown). The genome analysis shows
that SM-A87 contains 46 predicted glycosyl transferases,
of which 13 belong to family two and 10 belong to family
one. SM-A87 contains two glycosyl transferases
(ZPR_0565 and ZPR_1126) that are similar to WbaP from
Salmonella enterica. WbaP is responsible for the initia-
tion of polysaccharide synthesis, transferring the first
sugar to undecaprenyl phosphate (Und-P) . Similar to
WbaP, ZPR_1126 has 462 amino acid residues and five
predicted transmembrane regions. The topological orga-
nization of the transmembrane regions of these two
enzymes is similar: there are four transmembrane regions
at the N-terminus and one transmembrane domain with
sugar-phosphate transferase activity at the C-terminus.
ZPR_0565 consists of 339 amino acid residues and has
only one transmembrane domain. A multiple sequence
alignment [see Additional file 2] shows that ZPR_0565
corresponds to the C-terminus of WbaP and other initial
glycosyltransferases; in addition, they all contain the
highly conserved amino acid motifs KFRSM, DELPQ, and
PGITG . This implies that ZPR_0565 contains only
Table 2: Comparison of the numbers of selected proteins between SM-A87 and other four marine bacteria.
SM-A87 P. profundum
Histidine kinase47 2046 3713
130 (60)74 (18) 129 (50) 94 (47)59 (42)
Other glycosidase 5046 212
Esterase4620 32 227
40 155 642840
400 33 40 22
1In parentheses is the number of proteins with signal peptides.
Qin et al. BMC Genomics 2010, 11:247
Page 5 of 10
the glycosyltransferase catalytic domain. Genes encoding
other glycosyltransferases and polysaccharide export pro-
teins are found close to ZPR_0565 and ZPR_1126;
together, these genes form two gene clusters for polysac-
charide synthesis and export [see Additional file 3].
ZPR_1123, which is upstream of ZPR_1126, is predicted
to encode an O-antigen polymerase, implying that poly-
saccharides are synthesized through the Wzy-dependent
pathway in SM-A87 . SM-A87 harbors two predicted
capsular polysaccharide biosynthesis proteins that are
probably involved in the synthesis of capsular polysaccha-
rides. The production of capsular polysaccharide is
advantageous for SM-A87 to thrive in the marine envi-
Signal peptide analysis suggests that SM-A87 can secrete
a large number of hydrolysis enzymes, and it has more
exported peptidases than the other compared strains
(Table 2), reflecting its unusual ability to degrade organic
nitrogen. SM-A87 contains 130 predicted peptidases, 61
of which have signal peptides. The peptidases with signal
peptides have more aspartic acids and a higher ratio of
acidic residues to basic residues. Additionally, they have a
lower predicted isoelectric point (pI) than the peptidases
without signal peptides (Table 3), a difference that is sta-
tistically significant (p < 0.05). Thus, the extracellular
peptidases are more halophilic than the intracellular pep-
tidases, as high numbers of acidic residues and low pIs
are key features of halophilic proteins . The halophi-
licity of the extracellular peptidases helps them function
in saline environments and decompose extracellular
organic nitrogen matter in the marine salty condition.
Fifty-two of the SM-A87 peptidases with signal pep-
tides can be assigned to different families in the MEROPS
peptidase database . As shown in Figure 2, the pepti-
dases mainly belong to families of metallopeptidases and
serine peptidases, consistent with our previous study that
the extracellular peptidases of marine sedimentary bacte-
ria are mainly serine proteases and metalloproteases .
Compared to G. forsetii KT0803, deep-sea bacteria SM-
A87 and S. piezotolerans WP3 have more peptidases in
families S09 and S41, but fewer in family M14 (Figure 2).
The variety of extracellular peptidases suggests that SM-
A87 has the capacity to decompose diverse peptides and
proteins from its surroundings. For instance, SM-A87 has
six exported family M01 peptidases, which are amino-
peptidases. It has been reported that when marine bacte-
ria grow on HMW dissolved organic nitrogen (DON) as
the sole nitrogen source, aminopeptidase activity is
greatly enhanced . Aminopeptidase activity in the
deep-sea sediment is higher than that in the surface sea-
water; however, this is not the case for other hydrolysis
enzymes . The large number of aminopeptidases
secreted by SM-A87 may contribute to the high amino-
peptidase activity in the deep-sea sediment, and suggests
that SM-A87 may be able to respond to HMW DON and
decompose it. SM-A87 secretes seven S09 peptidases,
which are prolyl oligopeptidases that cannot degrade
peptides of more than 30 residues in length . There-
fore, the S09 peptidases specifically hydrolyze oligopep-
tides. Notably, there are six exported peptidases that
contain a PDZ domain, which is known to be involved in
peptide binding . The large number of PDZ domain-
containing peptidases secreted by SM-A87 suggests a
strategy for binding and degrading proteins, similar to the
PKD domains of exported proteins in G. forsetii KT0803
. In the deep-sea sedimentary nitrogen cycle, the pro-
cess by which particulate organic nitrogen is converted to
NH4+ is known to be dominated by bacteria but is poorly
characterized [1,14]. The secreted peptidases of SM-A87
may play an important role in this process.
Among the compared strains, SM-A87 has the largest
proportion of proteins belonging to carbohydrate trans-
port and metabolism COGs (Figure 1). Accordingly, it has
many genes encoding enzymes that degrade oligo- and
polysaccharides (Table 2) [Additional file 4]. SM-A87 has
Table 3: Properties of peptidases with and without signal peptides.
With signal peptidesWithout signal peptides
G+C content (%) 37.536.8
Asp (percentage) 6.66.0
Lys (percentage)8.0 8.1
Arg (percentage)3.6 3.5
6.0 ± 1.76.7 ± 2.0
1pI, predicted isoelectric point. The data are averages with standard deviation.
Qin et al. BMC Genomics 2010, 11:247
Page 6 of 10
50 annotated glycosidases, 17 of which have signal pep-
tides, suggesting that SM-A87 can hydrolyze extracellular
carbohydrates. It does not contain any predicted cellu-
lases, agreeing with the experimental result that it can not
hydrolyze cellulose. Although SM-A87 has a gene for
exported chitinase (ZPR_1703), experiments suggest that
it does not degrade chitin. SM-A87 harbors six xylanase
genes and three xylosidase genes, of which three xyla-
nases and two xylosidases have signal peptides, indicating
that the strain should have the ability to degrade xylan.
The genome also has four genes encoding exported beta-
galactosidases; correspondingly, beta-galactosidase activ-
ity has been detected in this strain .
SM-A87 contains 11 predicted glucosidases, of which
seven have signal peptides. Glucosidase production can
be induced by dissolved polymeric glucose . The large
number of glucosidases in SM-A87 indicates that it is able
to decompose the easily used polymeric sugar in the envi-
ronment. The carbohydrate-hydrolyzing enzymes men-
tioned above imply that SM-A87 is able to use a variety of
carbohydrates in the environment as carbon and energy
SM-A87 harbors seven genes encoding extracellular
lipases, including one phospholipase A1 (ZPR_0295) and
two GDSL family lipases. The strain contains 20 genes
encoding esterases with signal peptides, of which five are
carboxyl esterases and six are phosphoesterases. These
enzymes may allow SM-A87 to degrade various phospho-
lipids and carboxyl esters in the environment as carbon
and phosphorus sources.
DNA is abundant in the deep-sea sediment, and most
of it is extracellular. More than half of the total extracellu-
lar DNA can be rapidly degraded by enzymes . DNA
can be utilized by bacteria as a source of carbon, nitrogen,
and phosphorous, contributing to phosphate recycling
. SM-A87 harbors two predicted extracellular endo-
nucleases (ZPR_0199, ZPR_1186), implying that it can
obtain nutrient elements by degrading extracellular
It has been reported that sedimentary carbohydrate is
hydrolyzed more easily when it is treated with four
enzymes, α-amylase, β-glucosidase, protease and lipase,
than when it is treated with only one enzyme . SM-
A87 contains these four kinds of extracellular enzymes,
implying that the strain can hydrolyze sedimentary car-
bohydrates easily. The variety of exported peptidases and
other hydrolysis enzymes in the SM-A87 genome would
allow the bacterium to degrade sedimentary biopoly-
meric materials into small molecules that can be
absorbed by the cell. A previous genome analysis revealed
that G. forsetii KT0803 from surface seawater is good at
degrading polymeric organic materials . Our analysis
of the SM-A87 genome indicates that this deep-sea sedi-
ment Bacteroidetes species also has the unusual ability to
decompose polymeric organic materials, which could
contribute considerably to deep-sea sedimentary biogeo-
Nitrogen and sulfur metabolism
According to the KEGG pathway map, nitrite reductase
can catalyze the conversion of nitrite to ammonia .
Two nitrite reductases (ZPR_3631, ZPR_4195) could be
responsible for the conversion of nitrite to ammonia in
SM-A87. One formate/nitrite transporter (ZPR_2292)
and three putative nitrate/nitrite DNA-binding response
regulators in the genome indicate that SM-A87 can
absorb nitrite from the environment. All of the above evi-
dence suggests that the strain can use inorganic nitrogen.
The SM-A87 genome encodes one sulfate transporter
(ZPR_0777) and two sodium:sulfate
(ZPR_0364, ZPR_4168) that can transport sulfate ions
into the cell. It also has corresponding enzymes to utilize
sulfate. There are three adjacent ORFs that encode adeny-
lylsulfate kinase (ZPR_0539) and two subunits of sulfate
adenylyltransferase (ZPR_0540, ZPR_0541), which con-
vert sulfate to adenylyl sulfate (APS) and subsequently to
3'-phosphoadenylyl sulfate (PAPS). Phosphoadenosine
phosphosulfate reductase (ZPR_3632) can convert PAPS
into sulfite, and then hydrogen sulfide (H2S) could be
produced from sulfite by the sulfite reductases
(ZPR_0424, ZPR_4048). However, our previous experi-
ments showed that SM-A87 does not secrete H2S (22).
Thus, H2S is probably used to produce acetate via
cysteine synthase (ZPR_2076), which converts 3-O-
acetyl-L-serine (from serine) and H2S to acetate.
Substrate transport systems
Since SM-A87 has many extracellular hydrolytic
enzymes, there must be related systems to transport the
nutrient products into the cell. The ATP-binding cassette
Figure 2 The MEROPS category of the extracellular peptidases
from Z. profunda SM-A87, G. forsetii KT0803 and S. piezotolerans
Qin et al. BMC Genomics 2010, 11:247
Page 7 of 10
(ABC) transporters, which are widespread among bacte-
ria, can couple ATP hydrolysis to the transport of a vari-
ety of substrates into and out of the cell . An
examination of SM-A87 genome identified many genes
encoding possible ABC transporters (Table 2), which is
consistent with the report that there is an enrichment of
ABC transporter genes in the genomes of deep-sea
microorganisms . SM-A87 has three predicted amino
acid permeases and three amino acid transporters, which
make it possible for the strain to absorb amino acids and
oligopeptides. According to the KEGG pathway map, the
strain may be able to transport molybdate, iron com-
plexes, lipopolysaccharides and lipoproteins. In addition,
the presence of genes encoding xylose permease
(ZPR_0446), fucose permease (ZPR_4359) and glucose/
galactose transporter (ZPR_0518) may correspond to the
carbohydrate transport ability of SM-A87.
The TonB-dependent transport system can take up
large substrate molecules, such as siderophores and vita-
mins, into the cell from the environment . The
genome analysis showed that 40 TonB-dependent recep-
tor genes and 5 TonB protein genes are present in SM-
A87. Consistent with previous reports, there are fewer
TonB proteins than TonB receptors . The predicted
TonB-dependent siderophore receptors (ZPR_0148,
ZPR_2532) are likely to be involved in the enrichment
and transport of iron into the cell.
SM-A87 is predicted to carry many transposases, sup-
porting the idea that transposases are abundant in the
deep-sea environment [5,48]. Two predicted putative
transposons were identified in the SM-A87 genome. One
is composed of ZPR_3981, ZPR_3982 and ZPR_3983, of
which ZPR_3981 and ZPR_3983 belong to the IS66 fam-
ily of transposases. Surprisingly, ZPR_3982 is predicted
to be an RNA-directed DNA polymerase (reverse tran-
scriptase), implying that the DNA segment of ZPR_3982
may have come from an RNA virus. The second transpo-
son is composed of ZPR_1509, ZPR_1511 and ZPR_1512,
of which ZPR_1509 is an IS3 family transposase and
ZPR_1512 is a IS116/IS110/IS902 family transposase.
ZPR_1511 encodes a glyoxalase family protein with the
highest amino acid similarity (63%) to a glyoxalase from
Clustered regularly interspaced short palindromic repeat
(CRISPR) elements are common in bacteria and archaea.
A CRISPR is characterized by direct repeats (DR) that are
separated by similarly sized non-repetitive spacers. There
are also CRISPR-associated (CAS) genes and a leader
sequence before the repeat area. CRISPR elements can be
described as follows: CAS genes-leader-DR1-spacer1-
DR2-spacer2 ...DRn-1-spacern-1-DRn, where n is the num-
ber of repeats [51,52]. A single CRISPR locus has been
detected in many bacterial genomes . However, there
are two predicted CRISPR loci in the SM-A87 genome.
The first locus is 5 594 bp in length (bp 1 642 261 to bp 1
647 855). In the first locus, the DR sequence is 37 bp in
length with 76 spacers. Six CAS genes of the cas1, cas2,
cas3 and cas5 families were detected upstream of the first
locus. The second locus is 2 114 bp in length (bp 4 768
893 to bp 4 771 007), with a 47-bp DR sequence and 26
spacers. There are only two CAS genes upstream of the
second locus, one belonging to the cas1 family and one to
the cas2 family. The two CAS systems are classified as
different types according to the family and arrangement
of the CAS genes.
CRISPR is thought to function as an anti-phage defense
system via an RNA-silencing-like mechanism, and the
spacers are often found to share high sequence similari-
ties with phage sequences . However, our BLAST
searches resulted in no hits in the public databases, prob-
ably because only a small fraction of phage sequences are
deposited in the databases. In the ocean, the quantity of
phages is about 5-10 times more than that of bacteria
. SM-A87's CRISPRs may help defend against infec-
tion by unknown phages in the deep sea.
Adaptation to salt and cold
Halophiles have two different ways to maintain their cel-
lular osmotic balance in salty environments: by accumu-
lating organic compatible solutes or by maintaining a
high concentration of ions such as potassium in the cell
[54,55]. SM-A87 is a moderate halophile and can tolerate
0-12% NaCl . To analyze the mechanism of SM-A87's
adaptation to the marine salty environment, we predicted
and compared the pIs of intracellular and extracellular
proteins from SM-A87, G. forsetii KT0803, hyperhalo-
philic bacterium Salinibacter ruber, nonhalophilic bacte-
rium Escherichia coli and Bacteroidetes soil bacterium
Cytophaga hutchinsonii (Table 4). Halophilic proteins
contain more acidic residues and have lower pIs than
nonhalophilic proteins . E. coli is not halophilic, and
there is no statistically significant difference between the
pIs of its intracellular and extracellular proteins. S. ruber
is a hyperhalophilic bacterium that has a high intracellu-
lar potassium concentration to maintain its cellular
osmotic balance ; thus, the ion concentrations inside
and outside of the cell are both high. The pIs of both the
intracellular and extracellular proteins of S. ruber are
much lower than those of E. coli and C. hutchinsonii
(Table 4), suggesting that the S. ruber proteins are all
halophilic. For the marine bacteria SM-A87 and G.
forsetii KT0803, the intracellular protein pIs are higher
than those of the extracellular proteins, with a statistically
significant difference (p < 0.01 for all proteins, p < 0.05 for
Qin et al. BMC Genomics 2010, 11:247
Page 8 of 10
peptidases). This indicates that the intracellular proteins
of SM-A87 have poor salt-tolerance, and it is therefore
impossible for SM-A87 to maintain high ion concentra-
tions in the cell for osmotic balance. Instead, SM-A87 has
a glycine betaine transporter (ZPR_3842). Glycine
betaine is a well-known osmoregulator, implying that
SM-A87 may use organic compatible solutes rather than
ions to maintain its cellular osmotic balance. Thus, the
intracellular proteins of SM-A87 are not halophilic and
have higher pIs. In contrast, the extracellular proteins of
SM-A87 must face the moderately high ion concentration
(~3%) of the sea, so these proteins are halophilic and have
low pIs. This is also the case for G. forsetii KT0803, which
also contains glycine betaine transporter. The salt-toler-
ance of the extracellular proteins of SM-A87 and their
lower pIs are indicative of their adaptation to the salty
Unsaturated fatty acids can increase the fluidity of the
membrane, which is a common strategy used by bacteria
to adapt to a cold environment. The membranes of deep-
sea bacteria contain a high proportion of monounsatu-
rated fatty acids, which are very important for maintain-
ing bacterial membrane fluidity . SM-A87 has five
fatty acid desaturase genes, which may contribute to high
membrane fluidity, and thus cold adaptation. In addition
to the chaperones GroEL and DnaJ, SM-A87 has four
cold shock protein genes and one heat shock protein
gene, which may help the strain survive in the cold deep-
sea environment. SM-A87 also has genes encoding the
pyruvate dehydrogenase complex and trehalose phos-
phate synthase (ZPR_2459), which are both associated
with cold adaptation .
This work presents the first complete deep-sea bacterial
genome of a member of the phylum Bacteroidetes. SM-
A87 has some features that are common in deep-sea bac-
teria, such as numerous transposases and ABC-type
transporters. Our genome survey also reveals its meta-
bolic versatility and extensive hydrolytic capabilities.
Additionally, based on the contents of its genome, SM-
A87 can sense nutrient pulses, synthesize exopolysaccha-
rides to absorb nutrients, export a variety of enzymes to
degrade materials, transport substrates into the cell effi-
ciently and utilize resources via versatile metabolic path-
ways. With these features, SM-A87 can thrive in the
Strain SM-A87, originally isolated from deep-sea sedi-
ment in the southern Okinawa Trough, was cultured as
previously described . The cells were harvested by
centrifugation at 12 000 g at 10°C for 30 min. Genomic
DNA was prepared by using a genomic DNA extraction
kit (BioTeke, China) according to the manufacturer's
The genome sequence of strain SM-A87 was deter-
mined using a combined strategy of Sanger sequencing
and 454 pyrosequencing. About 100 megabases of data
were obtained from one 454 (GS-FLX) sequencing run.
The sequences were assembled into 144 large contigs that
were oriented by Sanger sequencing reads from paired
ends of plasmid and fosmid libraries with insert sizes
varying from 3 kb and 5 kb to 40 kb. The gaps were closed
by primer walking and PCR segment sequencing. The
phred-phrap-consed package was used for the assembly
and finishing , and the finished genome was validated
further by 10-kb long PCR.
The tRNA genes were predicted by tRNAscan-SE .
The rRNA genes were identified by BLAST search
against Rfam . The open reading frames (ORFs) were
found by using GLIMMER 3.0 . The predicted ORFs
were annotated by similarity searches against databases
of nonredundant protein sequences from NCBI, SWIS-
SPROT, Pfam , COG , KEGG and InterPro .
The annotation of ORFs was manually curated with
Artemis . Transmembrane regions of the predicted
proteins were predicted with TMHMM 2.0 http://
www.cbs.dtu.dk/services/TMHMM/. Signal peptide pre-
diction was done with SignalP 3.0 . Clustered regu-
larly interspaced short palindromic repeats (CRISPR)
were found with CRISPR-finder http://crispr.u-psud.fr/
Server/CRISPRfinder.php. The sequence alignment was
done with Clustal X .
Table 4: Predicted isoelectric points of the proteins of SM-A87 and compared strains1.
SM-A87G. forsetii KT0803 E. coliC. hutchinsonii S. rubber
All proteins 6.29 ± 2.087.28 ± 2.215.73 ± 1.907.07 ± 2.20 7.22 ± 2.177.20 ± 2.117.45 ± 1.50 6.47 ± 1.426.58 ± 2.52 5.79 ± 2.15
Peptidases5.96 ± 1.656.65 ± 2.025.29 ± 1.435.93 ± 1.66 7.54 ± 2.387.33 ± 2.137.65 ± 1.95 7.35 ± 1.935.76 ± 1.905.91 ± 2.17
1 The data are averages with standard deviation.
Qin et al. BMC Genomics 2010, 11:247
Page 9 of 10
The compared genome sequences were obtained from
the NCBI database FTP site: ftp://ftp.ncbi.nih.gov/
genomes/Bacteria/. Amino acid composition and protein
isoelectric points were predicted by the EMBOSS Pep-
stats program. The compared protein numbers were
counted by searching the genome annotation file using
the protein name with no further refinement of the anno-
tation. COG functional categories were assigned by using
a blastp program to search the COG database with all
SM-A87 proteins, and the final results were compiled
using custom-made Perl scripts.
The complete genome sequence of strain SM-A87 was
deposited in GenBank under the accession no. CP001650.
XZ coordinated the study. YZ, BZ and JY designed the project; HD provied the
strain; QQ prepared the DNA; XW and GL carried out the sequencing and
assembly; QQ and XZ finished the genome; QQ, GL, BX and XZ analyzed the
data; QQ wrote the paper; YZ and XC critically reviewed the paper. All authors
approved the final manuscript.
We thank Haibo Sun for his help in sequence assembly. The work was sup-
ported by National Natural Science Foundation of China (30770040, 40706001),
Hi-Tech Research and Development program of China (2007AA091903,
2007AA021306), and COMRA Program (DYXM-115-02-2-6).
1State Key Lab of Microbial Technology, Marine Biotechnology Research
Center, Shandong University, Jinan 250100, PR China, 2CAS Key Laboratory of
Genome Sciences and Information, Beijing Institute of Genomics, Chinese
Academy of Sciences, Beijing, 100029, PR China and 3Centre for
Bioengineering and Biotechnology, China University of Petroleum (East China),
Qingdao 266555, PR China
1.Brunnegarda J, Grandel S, Stahl H, Tengberg A, Hall POJ: Nitrogen cycling
in deep-sea sediments of the Porcupine Abyssal Plain, NE Atlantic.
Progress in Oceanography 2004, 63:159-181.
2.Karl DM: Microbial oceanography: paradigms, processes and promise.
Nat Rev Microbiol 2007, 5:759-69.
3. Schippers A, Neretin LN, Kallmeyer J, Ferdelman TG, Cragg BA, Parkes RJ,
Jorgensen BB: Prokaryotic cells of the deep sub-seafloor biosphere
identified as living bacteria. Nature 2005, 433:861-4.
4.Whitman WB, Coleman DC, Wiebe WJ: Prokaryotes: The unseen
majority. Proc Natl Acad Sci USA 1998, 95:6578-6583.
5.Worden AZ, Cuvelier ML, Bartlett DH: In-depth analyses of marine
microbial community genomics. Trends Microbiol 2006, 14(8):331-6.
Delong EF, Karl DM: Genomic perspective in microbial oceanography.
Nature 2005, 437:336-42.
Jorgensen BB, Boetius A: Feast and famine-microbial life in the deep-sea
bed. Nat Rev Microbiol 2007, 5:770-81.
Olivera NL, Sequeiros C, Nievas ML: Diversity and enzyme properties of
protease-producing bacteria isolated from sub-Antarctic sediments of
Isla de Los Estados, Argentina. Extremophiles 2007, 11:517-526.
Zhou MY, Chen XL, Zhao HL, Dang HY, Luan WX, Zhang XY, He HL, Zhou
BC, Zhang YZ: Diversity of both the cultivable protease-producing
bacteria and their extracellular proteases in the sediments of the South
China Sea. Microb Ecol 2009, 58:582-590.
10. Chen XL, Xie BB, Bian F, Zhao GY, Zhao HL, He HL, Zhou BC, Zhang YZ:
Ecological function of myroilysin, a novel bacterial M12
metalloprotease with elastinolytic activity and a synergistic role in
collagen hydrolysis, in biodegradation of deep-sea high-molecular-
weight organic nitrogen. Appl Environ Microbiol 2009, 75:1838-1844.
11. Chen XL, Zhang YZ, Gao PJ, Luan XW: Two different proteases produced
by a deep-sea psychrotrophic bacterial strain Pseudoalteromonas sp.
SM9913. Marine Biology 2003, 143:989-993.
12. Zeng R, Zhang R, Zhao J, Lin N: Cold-active serine alkaline protease from
the psychrophilic bacterium Pseudomonas strain DY-A: enzyme
purification and characterization. Extremophiles 2003, 7:335-337.
13. Zhao GY, Chen XL, Zhao HL, Xie BB, Zhou BC, Zhang YZ: Hydrolysis of
insoluble collagen by deseasin MCP-01 from deep-sea
Pseudoalteromonas sp. SM9913: Collagenolytic characters, collagen-
binding ability of C-terminal PKD domain and Implication for its novel
role in deep-sea sedimentary particulate organic nitrogen
degradation. J Biol Chem 2008, 283:36100-36107.
14. Zehr JP, Ward BB: Nitrogen cycling in the ocean: new perspectives on
processes and paradigms. Appl Environ Microbiol 2002, 68:1015-24.
15. Cottrell MT, Kirchman DL: Natural assemblages of marine
proteobacteria and members of the Cytophaga-Flavobacter cluster
consuming low- and high-molecular-weight dissolved organic matter.
Appl Environ Microbiol 2000, 66(4):1692-7.
16. Kirchman DL: The ecology of cytophaga-flavobacteria in aquatic
environments. FEMS Microbiology Ecology 2002, 39:91-100.
17. Benner R: Molecular indicators of the bioavailability of dissolved
organic matter. In Aquatic Ecosystems: Interactivity of Dissolved Organic
Matter Edited by: Findlay SEG, Sinsabaugh RL. San Diego, CA, Academic
18. Eilers H, Pernthaler J, Peplies J, Glockner FO, Gerdts G, Amann R: Isolation
of novel pelagic bacteria from the German bight and their seasonal
contributions to surface picoplankton. Appl Environ Microbiol 2001,
19. Bauer M, Kube M, Teeling H, Richter M, Lombardot T, Allers E, Wurdemann
CA, Quast C, Kuhl H, Knaust F, Woebken D, Bischof K, Mussmann M,
Choudhuri JV, Meyer F, Reinhardt R, Amann RI, Glockner FO: Whole
genome analysis of the marine Bacteroidetes 'Gramellaforsetii' reveals
adaptations to degradation of polymeric organic matter. Environ
Microbiol 2006, 8(12):2201-13.
20. Cottrell MT, Yu L, Kirchman DL: Sequence and expressionanalyses of
Cytophaga -like hydrolases in a Western arctic metagenomic library
and the Sargasso Sea. Appl Environ Microbiol 2005, 71:8506-13.
21. Grzymski JJ, Carter BJ, DeLong EF, Feldman RA, Ghadiri A, Murray AE:
Comparative genomics of DNA fragments from six Antarctic marine
planktonic bacteria. Appl Environ Microbiol 2006, 72:1532-41.
22. Qin QL, Zhao DL, Wang J, Chen XL, Dang HY, Li TG, Zhang YZ, Gao PJ:
Wangia profunda gen. nov., sp. nov., a novel marine bacterium of the
family Flavobacteriaceae isolated from southern Okinawa Trough
deep-sea sediment. FEMS Microbiol Lett 2007, 271:53-8.
23. Ivars-Martinez E, Martin-Cuadrado AB, D'Auria G, Mira A, Ferriera S,
Johnson J, Friedman R, Rodriguez-Valera F: Comparative genomics of
two ecotypes of the marine planktonic copiotroph Alteromonas
macleodii suggests alternative lifestyles associated with different kinds
of particulate organic matter. ISME J 2008, 2:1194-1212.
24. Witte U, Wenzhofer F, Sommer S, Boetius A, Heinz P, Aberle N, Sand M,
Cremer A, Abraham WR, Jorgensen BB, Pfannkuche O: In situ
experimental evidence of the fate of a phytodetritus pulse at the
abyssal sea floor. Nature 2003, 424:763-6.
Additional file 1 Operons of TonB-dependent receptor and SusD/
RagB family protein. Predicted operons of TonB-dependent receptor and
SusD/RagB family protein as well as adjacent proteins in Z. profunda SM-
Additional file 2 Sequence alignment of ZPR_0565 and ZPR_1126
with other initial glycosyltransferases. CpsE (CAC18355), EpsE
(AAC44012), EpsT (EF362569), ExoY (Q02731), GumD (AAA86372), RfbP
(P26406), WbaP (AAD21565), WchA (AAK20699). The boxed sequences are
conserved amino acid motif of initial glycosyltransferase.
Additional file 3 Polysaccharide biosynthesis clusters. Two predicted
polysaccharide biosynthesis clusters in Z. profunda SM-A87 genome.
Additional file 4 Summary of the carbohydrate-degrading enzymes
from Z. profunda SM-A87. 1 Y, with signal peptide. 2 aa, amino acids.
Received: 26 September 2009 Accepted: 17 April 2010
Published: 17 April 2010
This article is available from: http://www.biomedcentral.com/1471-2164/11/247 © 2010 Qin et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
BMC Genomics 2010, 11:247
Qin et al. BMC Genomics 2010, 11:247
Page 10 of 10
25. Fabret C, Feher VA, Hoch JA: Two-Component Signal Transduction in
Bacillus subtilis: How One Organism Sees Its World. J Bacteriol 1999,
26. Szurmant H, White RA, Hoch JA: Sensor complexes regulating two-
component signal transduction. Curr Opin Struct Biol 2007, 17:706-715.
27. Klappenbach JA, Dunbar JM, Schmidt TM: rRNA operon copy number
reflects ecological strategies of bacteria. Appl Environ Microbiol 2000,
28. Schurmann A, Brauers A, Massmann S, Becker W, Joost HG: Cloning of a
novel family of mammalian GTP-binding proteins (RagA, RagBs,
RagB1) with remote similarity to the Ras-related GTPases. J Biol Chem
29. Cho KH, Salyers AA: Biochemical analysis of interactions between outer
membrane proteins that contribute to starch utilization by Bacteroides
thetaiotaomicron. J Bacteriol 2001, 183:7224-7230.
30. Nichols CA, Guezennec J, Bowman JP: Bacterial exopolysaccharides from
extreme marine environments with special consideration of the
southern ocean, sea ice, and deep-sea hydrothermal vents: a review.
Mar Biotechnol 2005, 7:253-71.
31. Hou S, Saw JH, Lee KS, Freitas TA, Belisle C, Kawarabayasi Y, Donachie SP,
Pikina A, Galperin MY, Koonin EV, Makarova KS, Omelchenko MV, Sorokin
A, Wolf YI, Li QX, Keum YS, Campbell S, Denery J, Aizawa S, Shibata S,
Malahoff A, Alam M: Genome sequence of the deep-sea gamma-
proteobacterium Idiomarina loihiensis reveals amino acid fermentation
as a source of carbon and energy. Proc Natl Acad Sci USA 2004,
32. Qin GK, Zhu L, Chen XL, Wang PG, Zhang YZ: Structural characterization
and ecological roles of a novel exopolysaccharide from the deep-sea
psychrotolerant bacterium Pseudoalteromonas sp. SM9913.
Microbiology 2007, 153:1566-1572.
33. Cantarel BL, Coutinho PM, Rancurel C, Bernard T, Lombard V, Henrissat B:
The Carbohydrate-Active EnZymes database (CAZy): an expert
resource for Glycogenomics. Nucleic Acids Res 2009, 37:233-8.
34. Saldías MS, Patel K, Marolda CL, Bittner M, Contreras I, Valvano MA:
Distinct functional domains of the Salmonella enterica WbaP
transferase that is involved in the initiation reaction for synthesis of the
O antigen subunit. Microbiology 2008, 154:440-453.
35. Steiner K, Novotny R, Patel K, Vinogradov E, Whitfield C, Valvano MA,
Messner P, Schaffer C: Functional characterization of the initiation
enzyme of S-layer glycoprotein glycan biosynthesis in Geobacillus
stearothermophilus NRS 2004/3a. J Bacteriol 2007, 189:2590-8.
36. Valvano MA: Export of O-specific lipopolysaccharide. Front Biosci 2003,
37. Bolhuis A, Kwan D, Thomas JR: Halophilic adaptations of proteins. In
Protein adaptation in extremophiles Edited by: Siddiqui KS, Thomas T. New
York, Nova Science Publishers, Inc; 2008:71-104.
38. Rawlings ND, Morton FR, Kok CY, Kong J, Barrett AJ: MEROPS: the
peptidase database. Nucleic Acids Res 2008, 36:320-325.
39. Berg GM, Repeta DJ, LaRoche J: The role of the picoeukaryote
Aureococcus anophagefferens in cycling of marine high-molecular
weight dissolved organic nitrogen. Limnol Oceanogr 2003,
40. Boetius A: Microbial hydrolytic enzyme activities in deep-sea
sediments. Helgoland Marine Research 1995, 49:177-187.
41. Polgar L: The prolyl oligopeptidase family. Cell Mol Life Sci 2002,
42. Beebe KD, Shin J, Peng J, Chaudhury C, Khera J, Pei D: Substrate
Recognition through a PDZ Domain in Tail-Specific Protease.
Biochemistry 2000, 39:3149-55.
43. Rath J, Herndl GJ: Characteristics and diversity of beta-d-glucosidase
(EC 126.96.36.199) activity in marine snow. Appl Environ Microbiol 1994,
44. Dell'Anno A, Danovaro R: Extracellular DNA plays a key role in deep-sea
ecosystem functioning. Science 2005, 309:2179.
45. Dell'Anno A, Fabiano M, Mei ML, Danovaro R: Enzymatically hydrolysed
protein and carbohydrate pools in deep-sea sediments: estimates of
the potentially bioavailable fraction and methodological
considerations. Mar Ecol Progr Ser 2000, 196:15-23.
46. Kanehisa M, Goto S, Kawashima S, Okuno Y, Hattori M: The KEGG resource
for deciphering the genome. Nucleic Acids Res 2004, 32:277-80.
47. Davidson AL, Chen J: ATP-binding cassette transporters in bacteria.
Annu Rev Biochem 2004, 73:241-68.
48. DeLong EF, Preston CM, Mincer T, Rich V, Hallam SJ, Frigaard NU, Martinez
A, Sullivan MB, Edwards R, Brito BR, Chisholm SW, Karl DM: Community
genomics among stratified microbial assemblages in the ocean's
interior. Science 2006, 311:496-503.
49. Giovannoni S, Stingl U: The importance of culturing bacterioplankton in
the 'omics' age. Nat Rev Microbiol 2007, 5:820-6.
50. Kadner RJ, Heller KJ: Mutual inhibition of cobalamin and siderophore
uptake systems suggests their competition for TonB function. J
Bacteriol 1995, 177:4829-4835.
51. McShan WM, Ferretti JJ, Karasawa T, Suvorov AN, Lin S, Qin B, Jia H, Kenton
S, Najar F, Wu H, Scott J, Roe BA, Savic DJ: Genome sequence of a
nephritogenic and highly transformable M49 strain of Streptococcus
pyogenes. J Bacteriol 2008, 190:7773-85.
52. Sorek R, Kunin V, Hugenholtz P: CRISPR -- a widespread system that
provides acquired resistance against phages in bacteria and archaea.
Nat Rev Microbiol 2008, 6:181-6.
53. Wommack KE, Colwell RR: Virioplankton: viruses in aquatic ecosystems.
Microbiol Mol Biol Rev 2000, 64:69-114.
54. Burg MB, Ferraris JD: Intracellular organic osmolytes: function and
regulation. J Biol Chem 2008, 283:7309-7313.
55. Mongodin EF, Nelson KE, Daugherty S, DeBoy RT, Wister J, Khouri H,
Weidman J, Walsh DA, Papke RT, Perez GS, Sharma AK, Nesbo CL, MacLeod
D, Bapteste E, Doolittle WF, Charlebois RL, Legault B, Rodriguez-Valera F:
The genome of Salinibacter ruber: Convergence and gene exchange
among hyperhalophilic bacteria and archaea. Proc Natl Acad Sci USA
56. Simonato F, Campanaro S, Lauro FM, Vezzi A, D'Angelo M, Vitulo N, Valle G,
Bartlett DH: Piezophilic adaptation: a genomic point of view. J
Biotechnol 2006, 126:11-25.
57. Rodrigues DF, Tiedje JM: Coping with our cold planet. Appl Environ
Microbiol 2008, 74:1677-86.
58. Gordon D, Abajian C, Green P: Consed: a graphical tool for sequence
finishing. Genome Res 1998, 8:195-202.
59. Lowe TM, Eddy SR: tRNAscan-SE: a program for improved detection of
transfer RNA genes in genomic sequence. Nucleic Acids Res 1997,
60. Griffiths-Jones S, Bateman A, Marshall M, Khanna A, Eddy SR: Rfam: an
RNA family database. Nucleic Acids Res 2003, 31:439-441.
61. Delcher AL, Harmon D, Kasif S, White O, Salzberg SL: Improved microbial
gene identification with GLIMMER. Nucleic Acids Res 1999,
62. Bateman A, Birney E, Cerruti L, Durbin R, Etwiller L, Eddy SR, Griffiths-Jones
S, Howe KL, Marshall M, Sonnhammer E: The Pfam Protein Families
Database. Nucleic Acids Res 2002, 30:276-280.
63. Tatusova RL, Natale DA, Garkavtsev IV, Tatusova TA, Shankavaram UT, Rao
BS, Kiryutin B, Galperin MY, Fedorova ND, Koonin EV: The COG database:
new developments in phylogenetic classification of proteins from
complete genomes. Nucleic Acids Res 2001, 9:222-28.
64. Apweiler R, Attwood TK, Bairoch A, Bateman A, Birney E, Biswas M, Bucher
P, Cerutti L, Corpet F, Croning MDR, Durbin R, Falquet L, Fleischmann W,
Gouzy J, Hermjakob H, Hulo N, Jonassen I, Kahn D, Kanapin A,
Karavidopoulou Y, Lopez R, Marx B, Mulder NJ, Oinn TM, Pagni M, Servant
F, Sigrist CJA, Zdobnov EM: The InterPro database, an integrated
documentation resource for protein families, domains and functional
sites. Nucleic Acids Res 2001, 29:37-40.
65. Rutherford K, Parkhill J, Crook J, Horsnell T, Rice P, Rajandream MA, Barrell
B: Artemis: sequence visualization and annotation. Bioinformatics 2000,
66. Bendtsen JD, Nielsen H, Heijne GV, Brunak S: Improved prediction of
signal peptides: SignalP 3.0. J Mol Biol 2004, 340:783-95.
67. Jeanmougina F, Thompson JD, Gouy M, Higgins DG, Gibson TJ: Multiple
sequence alignment with Clustal X. Trends in Biochemical Sciences 1998,
Cite this article as: Qin et al., The complete genome of Zunongwangia pro-
funda SM-A87 reveals its adaptation to the deep-sea environment and eco-
logical role in sedimentary organic nitrogen degradation BMC Genomics