Literature DB >> 21304749

Complete genome sequence of Sulfurimonas autotrophica type strain (OK10).

Johannes Sikorski, Christine Munk, Alla Lapidus, Olivier Duplex Ngatchou Djao, Susan Lucas, Tijana Glavina Del Rio, Matt Nolan, Hope Tice, Cliff Han, Jan-Fang Cheng, Roxanne Tapia, Lynne Goodwin, Sam Pitluck, Konstantinos Liolios, Natalia Ivanova, Konstantinos Mavromatis, Natalia Mikhailova, Amrita Pati, David Sims, Linda Meincke, Thomas Brettin, John C Detter, Amy Chen, Krishna Palaniappan, Miriam Land, Loren Hauser, Yun-Juan Chang, Cynthia D Jeffries, Manfred Rohde, Elke Lang, Stefan Spring, Markus Göker, Tanja Woyke, James Bristow, Jonathan A Eisen, Victor Markowitz, Philip Hugenholtz, Nikos C Kyrpides, Hans-Peter Klenk.   

Abstract

Sulfurimonas autotrophica Inagaki et al. 2003 is the type species of the genus Sulfurimonas. This genus is of interest because of its significant contribution to the global sulfur cycle as it oxidizes sulfur compounds to sulfate and by its apparent habitation of deep-sea hydrothermal and marine sulfidic environments as potential ecological niche. Here we describe the features of this organism, together with the complete genome sequence and annotation. This is the second complete genome sequence of the genus Sulfurimonas and the 15(th) genome in the family Helicobacteraceae. The 2,153,198 bp long genome with its 2,165 protein-coding and 55 RNA genes is part of the Genomic Encyclopedia of Bacteria and Archaea project.

Entities:  

Keywords:  Epsilonproteobacteria; GEBA; Gram-negative; Helicobacteriaceae; deep-sea hydrothermal vents; facultatively anaerobic; mesophilic; spermidine; sulfur metabolism

Year:  2010        PMID: 21304749      PMCID: PMC3035374          DOI: 10.4056/sigs.1173118

Source DB:  PubMed          Journal:  Stand Genomic Sci        ISSN: 1944-3277


Introduction

Strain OK10T (= DSM 16294 = ATCC BAA-671 = JCM 11897) is the type strain of Sulfurimonas autotrophica [1], which is the type species of its genus Sulfurimonas [1,2]. Together with S. paralvinellae and S. denitrificans, the latter of which was formerly classified as Thiomicrospira denitrificans [3]. There are currently three validly named species in the genus Sulfurimonas [4,5]. The autotrophic and mixotrophic sulfur-oxidizing bacteria such as the members of the genus Sulfurimonas are believed to contribute significantly to the global sulfur cycle [6]. The genus name derives from the Latin word ‘sulphur’, and the Greek word ‘monas’, meaning a unit, in order to indicate a “sulfur-oxidizing rod” [1]. The species epithet derives from the Greek word ‘auto’, meaning self, and from the Greek adjective ‘trophicos’ meaning nursing, tending or feeding, in order to indicate its autotrophy [1]. S. autotrophica strain OK10T, like S. paralvinellae strain GO25T (= DSM 17229), was isolated from the surface of a deep-sea hydrothermal sediment on the Hatoma Knoll in the Mid-Okinawa Trough hydrothermal field [1,2]. Thus, the members of the genus Sulfurimonas appear to be free living, whereas the other members of the family Helicobacteraceae, the genera Helicobacter and Wolinella, appear to be strictly associated with the human stomach and the bovine rumen, respectively. Here we present a summary classification and a set of features for S. autotrophica OK10T, together with the description of the complete genomic sequencing and annotation.

Classification and features

There exist currently no experimental reports that indicate further cultivated strains of this species. The type strains of S. denitrificans and S. paralvinellae share 93.5% and 96.3% 16S rRNA gene sequence similarity with strain OK10T. Further analysis also revealed that strain OK10T shares high similarity (99.1%) with the uncultured clone sequence PVB-12 (U15104) obtained from a microbial mat near the deep-sea hydrothermal vent in the Loihi Seamont, Hawaii [7]. This further corroborates the distribution of S. autotrophica in hydrothermal vents. The 16S rRNA gene sequence similarities of strain OK10T to metagenomic libraries (env_nt) were 87% or less, indicating the absence of further members of the species in the environments screened so far (status August 2010). Figure 1 shows the phylogenetic neighborhood of S. autotrophica OK10T in a 16S rRNA based tree. The sequences of the four 16S rRNA gene copies in the genome differ from each other by up to four nucleotides, and differ by up to three nucleotides from the previously published sequence (AB088431).
Figure 1

Phylogenetic tree highlighting the position of S. autotrophica OK10T relative to the type strains of the other species within the genus and the type strains of the other genera within the order Campylobacterales. The tree was inferred from 1,327 aligned characters [8,9] of the 16S rRNA gene sequence under the maximum likelihood criterion [10] and rooted in accordance with current taxonomy [11]. The branches are scaled in terms of the expected number of substitutions per site. Numbers above branches are support values from 350 bootstrap replicates [12] if larger than 60%. Lineages with type strain genome sequencing projects registered in GOLD [13] are shown in blue, published genomes in bold [14,15], such as the recently published GEBA genomes from Sulfurospirillum deleyianum [16] and Arcobacter nitrofigilis [17].

Phylogenetic tree highlighting the position of S. autotrophica OK10T relative to the type strains of the other species within the genus and the type strains of the other genera within the order Campylobacterales. The tree was inferred from 1,327 aligned characters [8,9] of the 16S rRNA gene sequence under the maximum likelihood criterion [10] and rooted in accordance with current taxonomy [11]. The branches are scaled in terms of the expected number of substitutions per site. Numbers above branches are support values from 350 bootstrap replicates [12] if larger than 60%. Lineages with type strain genome sequencing projects registered in GOLD [13] are shown in blue, published genomes in bold [14,15], such as the recently published GEBA genomes from Sulfurospirillum deleyianum [16] and Arcobacter nitrofigilis [17]. The cells of strain OK10T are Gram-negative, occasionally slightly curved rods of 1.5–2.5 × 0.5-1.0 µm (Figure 2 and Table 1) [1]. On solid medium, the cells form white colonies [1]. Under optimal conditions, the generation time of S. autotrophica strain OK10T is approximately 1.4 h [1,2]. The reductive tricarboxylic acid (rTCA) cycle for autotrophic CO2 fixation is present in strain OK10T, as shown by PCR amplification of the respective genes [28]. Moreover, the activities of several rTCA key enzymes (ACL, ATP dependent citrate lyase; POR, pyruvate:acceptor oxidoreductase; OGOR, 2-oxoglutarase:accecptor oxidoreductase; ICDH, isocytrate dehydrogenase) have been determined, also in comparison to S. paralvinellae and S. denitrificans [28]. There were no enzyme activities for the phosphoenolpyruvate and ribulose 1,5-bisphosphate (Calvin-Benson) pathways detected in strain OK10T [28], though the latter is apparently active in S. thermophila [28]. Also, soluble hydrogenase activity was not found in strain OK10T [28]. With respect to sulfur oxidation, enzyme activity for SOR (sulfite oxidoreductase) but not for APSR (adenosine 5′-phosphate sulfate reductase) and TSO (thiosulfate-oxidizing enzymes) were detected [28]. A detailed comparison of these enzyme activities to S. paralvinellae and S. denitrificans is given in Takai et al. [28]. Elemental sulfur, thiosulfate or sulfide is utilized as the sole electron donor for chemolithoautotrophic growth with O2 as electron acceptor. Thereby thiosulfate is oxidized to sulfate [1]. Organic substrates and H2 are not utilized as electron donors and only oxygen is utilized as an electron acceptor [28]. Strain OK10T requires 4% sea salt for growth [1] and is not able to reduce nitrate [2].
Figure 2

Scanning electron micrograph of S. autotrophica OK10T

Table 1

Classification and general features of S. autotrophica OK10T according to the MIGS recommendations [18]

MIGS ID   Property    Term  Evidence code
   Current classification    Domain Bacteria  TAS [19]
    Phylum Proteobacteria  TAS [20]
    Class Epsilonproteobacteria  TAS [21,22]
    Order Campylobacterales  TAS [23,24]
    Family Helicobacteraceae  TAS [24,25]
    Genus Sulfurimonas  TAS [1,2]
    Species Sulfurimonas autotrophica  TAS [1]
    Type strain OK10  TAS [1]
   Gram stain    negative  TAS [1]
   Cell shape    short rods, occasionally slightly curved rods  TAS [1]
   Motility    by monotrichous, polar flagellum  TAS [1]
   Sporulation    non-sporulating  TAS [1]
   Temperature range    10°C - 40°C  TAS [1]
   Optimum temperature    23°C - 26°C  TAS [1]
   Salinity    4% NaCl  TAS [1]
MIGS-22   Oxygen requirement    aerobic  TAS [1]
   Carbon source    CO2  TAS [1]
   Energy source    chemolithoautotrophic, S0, Na2S2O3    and Na2S x 9H2O  TAS [1]
MIGS-6   Habitat    hydrothermal deep-sea sediments  TAS [1]
MIGS-15   Biotic relationship    free living  NAS
MIGS-14   Pathogenicity    not reported  NAS
   Biosafety level    1  TAS [26]
   Isolation    Mid-Okinawa Trough hydrothermal sediments  TAS [1,7]
MIGS-4   Geographic location    Japan, Hatoma Knoll  TAS [1,7]
MIGS-5   Sample collection time    2003 or before  TAS [1]
MIGS-4.1 MIGS-4.2   Latitude   Longitude    27.27    127.17  TAS [1]
MIGS-4.3   Depth    sediment surface  TAS [1]
MIGS-4.4   Altitude    not reported  NAS

Evidence codes - IDA: Inferred from Direct Assay (first time in publication); TAS: Traceable Author Statement (i.e., a direct report exists in the literature); NAS: Non-traceable Author Statement (i.e., not directly observed for the living, isolated sample, but based on a generally accepted property for the species, or anecdotal evidence). These evidence codes are from of the Gene Ontology project [27]. If the evidence code is IDA, then it was directly observed by one of the authors or an expert mentioned in the acknowledgements.

Scanning electron micrograph of S. autotrophica OK10T Evidence codes - IDA: Inferred from Direct Assay (first time in publication); TAS: Traceable Author Statement (i.e., a direct report exists in the literature); NAS: Non-traceable Author Statement (i.e., not directly observed for the living, isolated sample, but based on a generally accepted property for the species, or anecdotal evidence). These evidence codes are from of the Gene Ontology project [27]. If the evidence code is IDA, then it was directly observed by one of the authors or an expert mentioned in the acknowledgements.

Chemotaxonomy

The major cellular fatty acids found in strain OK10T are C14:0 (8.4%), C16:1 (45.2%), C16:0 (37.1%) and C18:1 (9.4%) [1]. Further fatty acids were not reported [1]. The only polyamine identified in S. autotrophica is spermidine [29]. Spermidine was also found in another representative of the order Campylobacterales, Sulfuricurvum kujiense. For comparison, Hydrogenimonas thermophila, the type species and genus of the family Hydrogenimonaceae in the order Campylobacterales, contains both spermidine and spermine as the major polyamines [29]. The cellular fatty acid composition of S. autotrophica was compared with that of other autotrophic Epsilonproteobacteria from deep-sea hydrothermal vents: Nautilia profundicola AmHT, Lebetimonas acidiphila Pd55T, Hydrogenimonas thermophila EP1-55-1%T, and Nitratiruptor tergarcus MI55-1T [30]. It was found that S. autotrophica strain OK10T has much higher levels of the fatty acid C16:1cis (45.2%) than do other Epsilonproteobacteria from hydrothermal vents express (3.6%-28.8%) [2,30]. On another hand, the percentage of C18:1 was the lowest in S. autotrophica: (9.4%), while other Epsilonproteobacteria contained 20.0%-73.3% [30]. C14:0 (8.4%) was also more abundant in strain OK10T than in other strains [30].

Genome sequencing and annotation

Genome project history

This organism was selected for sequencing on the basis of its phylogenetic position [31], and is part of the enomic ncyclopedia of acteria and rchaea project [32]. The genome project is deposited in the Genome OnLine Database [13] and the complete genome sequence is deposited in GenBank. Sequencing, finishing and annotation were performed by the DOE Joint Genome Institute (JGI). A summary of the project information is shown in Table 2.
Table 2

Genome sequencing project information

MIGS ID    Property   Term
MIGS-31    Finishing quality   Finished
MIGS-28    Libraries used   Four genomic libraries: Sanger 8 kb pMCL200 library,   454 pyrosequence standard library,   454 pyrosequence paired end (PE) library,   Illumina standard library
MIGS-29    Sequencing platforms   ABI3730, 454 GS FLX Titanium, Illumina GAii
MIGS-31.2    Sequencing coverage   3.7 × Sanger; 121.7 × pyrosequence, 30.0 × Illumina
MIGS-30    Assemblers   Newbler version 2.0.00.20-PostRelease-11-05-2008-gcc-3.4.6, phrap
MIGS-32    Gene calling method   Prodigal 1.4, GenePRIMP
    INSDC ID   CP002205
    Genbank Date of Release   September 15, 2010
    GOLD ID   Gc01373
    NCBI project ID   31347
    Database: IMG-GEBA   2502082114
MIGS-13    Source material identifier   DSM 16294
    Project relevance   Tree of Life, GEBA

Growth conditions and DNA isolation

S. autotrophica strain OK10T, DSM 16294, was grown in DSMZ medium 1011 (MJ medium) [33] at 24°C. DNA was isolated from 0.5-1 g of cell paste using MasterPure Gram Positive DNA Purification Kit (Epicenter MGP04100) following the standard protocol as recommended by the manufacturer, with modification st/LALM for cell lysis as described in Wu et al. [32].

Genome sequencing and assembly

The genome was sequenced using a combination of Sanger, 454 and Illumina sequencing platforms. All general aspects of library construction and sequencing can be found at the JGI website (http://www.jgi.doe.gov/). Illumina sequencing data was assembled with VELVET [34], and the consensus sequences were shredded into 1.5 kb overlapped fake reads and used for the assembly with 454 and Sanger data. Contigs resulting from a 454 Newbler (2.0.00.20-PostRelease-11-05-2008-gcc-3.4.6) assembly were shredded into 2 kb fake reads, which were assembled with Sanger data. The Phred/Phrap/Consed software package (www.phrap.com) was used for sequence assembly and quality assessment. After the shotgun stage, reads were assembled with parallel phrap (High Performance Software, LLC). Possible mis-assemblies were corrected with Dupfinisher or transposon bombing of bridging clones (Epicentre Biotechnologies, Madison, WI). Gaps between contigs were closed by editing in Consed, custom primer walk or PCR amplification (Roche Applied Science, Indianapolis, IN) [35]. A total of 790 additional custom primer reactions were necessary to close gaps and to raise the quality of the finished sequence. Illumina reads were also used to improve the final consensus quality using an in-house developed tool - the Polisher [36]. Together, the combination of the Illumina and 454 sequencing platforms provided 155.4 × coverage of the genome. The error rate of the completed genome sequence is less than 1 in 100,000.

Genome annotation

Genes were identified using Prodigal [37] as part of the Oak Ridge National Laboratory genome annotation pipeline, followed by a round of manual curation using the JGI GenePRIMP pipeline [38]. The predicted CDSs were translated and used to search the National Center for Biotechnology Information (NCBI) nonredundant database, UniProt, TIGRFam, Pfam, PRIAM, KEGG, COG, and InterPro databases. Additional gene prediction analysis and functional annotation was performed within the Integrated Microbial Genomes - Expert Review (IMG-ER) platform [39].

Genome properties

The genome consists of a 2,153,198 bp long chromosome with a 35.2% GC content (Table 3 and Figure 3). Of the 2,220 genes predicted, 2,165 were protein-coding genes, and 55 RNAs; seven pseudogenes were also identified. The majority of the protein-coding genes (69.1%) were assigned with a putative function while the remaining ones were annotated as hypothetical proteins. The distribution of genes into COGs functional categories is presented in Table 4.
Table 3

Genome Statistics

Attribute   Value  % of Total
Genome size (bp)   2,153,198  100.00%
DNA coding region (bp)   2,043,048  94.88%
DNA G+C content (bp)   758,696  35.24%
Number of replicons   1
Extrachromosomal elements   0
Total genes   2,220  100.00%
RNA genes   55  2.48%
rRNA operons   4
Protein-coding genes   2,165  97.52%
Pseudo genes   7  032%
Genes with function prediction   1,534  69.10%
Genes in paralog clusters   141  6.35%
Genes assigned to COGs   1,590  71.62%
Genes assigned Pfam domains   1,656  74.59%
Genes with signal peptides   429  19.32%
Genes with transmembrane helices   563  25.36%
CRISPR repeats   0
Figure 3

Graphical circular map of the genome. From outside to the center: Genes on forward strand (color by COG categories), Genes on reverse strand (color by COG categories), RNA genes (tRNAs green, rRNAs red, other RNAs black), GC content, GC skew.

Table 4

Number of genes associated with the general COG functional categories

Code   value    %age    Description
J   143    8.1    Translation, ribosomal structure and biogenesis
A   0    0.0    RNA processing and modification
K   70    4.0    Transcription
L   82    4.6    Replication, recombination and repair
B   0    0.0    Chromatin structure and dynamics
D   22    1.2    Cell cycle control, cell division, chromosome partitioning
Y   0    0.0    Nuclear structure
V   30    1.7    Defense mechanisms
T   158    8.9    Signal transduction mechanisms
M   126    7.1    Cell wall/membrane/envelope biogenesis
N   77    4.3    Cell motility
Z   0    0.0    Cytoskeleton
W   0    0.0    Extracellular structures
U   69    3.9    Intracellular trafficking and secretion
O   89    5.0    Posttranslational modification, protein turnover, chaperones
C   141    8.0    Energy production and conversion
G   62    3.5    Carbohydrate transport and metabolism
E   121    6.8    Amino acid transport and metabolism
F   49    2.8    Nucleotide transport and metabolism
H   107    6.0    Coenzyme transport and metabolism
I   36    2.0    Lipid transport and metabolism
P   103    5.8    Inorganic ion transport and metabolism
Q   12    0.7    Secondary metabolites biosynthesis, transport and catabolism
R   158    8.9    General function prediction only
S   119    6.7    Function unknown
-   630    28.4    Not in COGs
Graphical circular map of the genome. From outside to the center: Genes on forward strand (color by COG categories), Genes on reverse strand (color by COG categories), RNA genes (tRNAs green, rRNAs red, other RNAs black), GC content, GC skew.
  28 in total

1.  Selection of conserved blocks from multiple alignments for their use in phylogenetic analysis.

Authors:  J Castresana
Journal:  Mol Biol Evol       Date:  2000-04       Impact factor: 16.240

2.  GenePRIMP: a gene prediction improvement pipeline for prokaryotic genomes.

Authors:  Amrita Pati; Natalia N Ivanova; Natalia Mikhailova; Galina Ovchinnikova; Sean D Hooper; Athanasios Lykidis; Nikos C Kyrpides
Journal:  Nat Methods       Date:  2010-05-02       Impact factor: 28.547

3.  Enzymatic and genetic characterization of carbon and energy metabolisms by deep-sea hydrothermal chemolithoautotrophic isolates of Epsilonproteobacteria.

Authors:  Ken Takai; Barbara J Campbell; S Craig Cary; Masae Suzuki; Hanako Oida; Takuro Nunoura; Hisako Hirayama; Satoshi Nakagawa; Yohey Suzuki; Fumio Inagaki; Koki Horikoshi
Journal:  Appl Environ Microbiol       Date:  2005-11       Impact factor: 4.792

4.  List of new names and new combinations previously effectively, but not validly, published.

Authors: 
Journal:  Int J Syst Evol Microbiol       Date:  2006-01       Impact factor: 2.747

5.  Velvet: algorithms for de novo short read assembly using de Bruijn graphs.

Authors:  Daniel R Zerbino; Ewan Birney
Journal:  Genome Res       Date:  2008-03-18       Impact factor: 9.043

6.  List of Bacterial Names with Standing in Nomenclature: a folder available on the Internet.

Authors:  J P Euzéby
Journal:  Int J Syst Bacteriol       Date:  1997-04

7.  The complete genome sequence of Helicobacter pylori strain G27.

Authors:  David A Baltrus; Manuel R Amieva; Antonello Covacci; Todd M Lowe; D Scott Merrell; Karen M Ottemann; Markus Stein; Nina R Salama; Karen Guillemin
Journal:  J Bacteriol       Date:  2008-10-24       Impact factor: 3.490

8.  Sulfurimonas autotrophica gen. nov., sp. nov., a novel sulfur-oxidizing epsilon-proteobacterium isolated from hydrothermal sediments in the Mid-Okinawa Trough.

Authors:  Fumio Inagaki; Ken Takai; Hideki Kobayashi; Kenneth H Nealson; Koki Horikoshi
Journal:  Int J Syst Evol Microbiol       Date:  2003-11       Impact factor: 2.747

9.  Complete genome sequence and analysis of Wolinella succinogenes.

Authors:  Claudia Baar; Mark Eppinger; Guenter Raddatz; Jörg Simon; Christa Lanz; Oliver Klimmek; Ramkumar Nandakumar; Roland Gross; Andrea Rosinus; Heike Keller; Pratik Jagtap; Burkhard Linke; Folker Meyer; Hermann Lederer; Stephan C Schuster
Journal:  Proc Natl Acad Sci U S A       Date:  2003-09-19       Impact factor: 11.205

10.  Nautilia profundicola sp. nov., a thermophilic, sulfur-reducing epsilonproteobacterium from deep-sea hydrothermal vents.

Authors:  Julie L Smith; Barbara J Campbell; Thomas E Hanson; Chuanlun L Zhang; S Craig Cary
Journal:  Int J Syst Evol Microbiol       Date:  2008-07       Impact factor: 2.747

View more
  19 in total

1.  Niche partitioning of diverse sulfur-oxidizing bacteria at hydrothermal vents.

Authors:  Dimitri V Meier; Petra Pjevac; Wolfgang Bach; Stephane Hourdez; Peter R Girguis; Charles Vidoudez; Rudolf Amann; Anke Meyerdierks
Journal:  ISME J       Date:  2017-04-04       Impact factor: 10.302

2.  A proposed genus boundary for the prokaryotes based on genomic insights.

Authors:  Qi-Long Qin; Bin-Bin Xie; Xi-Ying Zhang; Xiu-Lan Chen; Bai-Cheng Zhou; Jizhong Zhou; Aharon Oren; Yu-Zhong Zhang
Journal:  J Bacteriol       Date:  2014-04-04       Impact factor: 3.490

3.  Strain-level genomic variation in natural populations of Lebetimonas from an erupting deep-sea volcano.

Authors:  Julie L Meyer; Julie A Huber
Journal:  ISME J       Date:  2013-11-21       Impact factor: 10.302

4.  Deep-sea hydrothermal vent Epsilonproteobacteria encode a conserved and widespread nitrate reduction pathway (Nap).

Authors:  Costantino Vetriani; James W Voordeckers; Melitza Crespo-Medina; Charles E O'Brien; Donato Giovannelli; Richard A Lutz
Journal:  ISME J       Date:  2014-01-16       Impact factor: 10.302

5.  Sulfide Consumption in Sulfurimonas denitrificans and Heterologous Expression of Its Three Sulfide-Quinone Reductase Homologs.

Authors:  Yuchen Han; Mirjam Perner
Journal:  J Bacteriol       Date:  2016-03-31       Impact factor: 3.490

6.  Complete genome sequence of the sulfur compounds oxidizing chemolithoautotroph Sulfuricurvum kujiense type strain (YK-1(T)).

Authors:  Cliff Han; Oleg Kotsyurbenko; Olga Chertkov; Brittany Held; Alla Lapidus; Matt Nolan; Susan Lucas; Nancy Hammon; Shweta Deshpande; Jan-Fang Cheng; Roxanne Tapia; Lynne A Goodwin; Sam Pitluck; Konstantinos Liolios; Ioanna Pagani; Natalia Ivanova; Konstantinos Mavromatis; Natalia Mikhailova; Amrita Pati; Amy Chen; Krishna Palaniappan; Miriam Land; Loren Hauser; Yun-Juan Chang; Cynthia D Jeffries; Evelyne-Marie Brambilla; Manfred Rohde; Stefan Spring; Johannes Sikorski; Markus Göker; Tanja Woyke; James Bristow; Jonathan A Eisen; Victor Markowitz; Philip Hugenholtz; Nikos C Kyrpides; Hans-Peter Klenk; John C Detter
Journal:  Stand Genomic Sci       Date:  2012-03-05

7.  Microbiological characterization of post-eruption "snowblower" vents at Axial Seamount, Juan de Fuca Ridge.

Authors:  Julie L Meyer; Nancy H Akerman; Giora Proskurowski; Julie A Huber
Journal:  Front Microbiol       Date:  2013-06-17       Impact factor: 5.640

8.  Phylogenetic diversity and functional gene patterns of sulfur-oxidizing subseafloor Epsilonproteobacteria in diffuse hydrothermal vent fluids.

Authors:  Nancy H Akerman; David A Butterfield; Julie A Huber
Journal:  Front Microbiol       Date:  2013-07-08       Impact factor: 5.640

9.  Metatranscriptomics reveal differences in in situ energy and nitrogen metabolism among hydrothermal vent snail symbionts.

Authors:  J G Sanders; R A Beinart; F J Stewart; E F Delong; P R Girguis
Journal:  ISME J       Date:  2013-04-25       Impact factor: 10.302

Review 10.  The globally widespread genus Sulfurimonas: versatile energy metabolisms and adaptations to redox clines.

Authors:  Yuchen Han; Mirjam Perner
Journal:  Front Microbiol       Date:  2015-09-16       Impact factor: 5.640

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.