Open Access

Complete genome sequence of Paludibacter propionicigenes type strain (WB4T)

  • Sabine Gronow
  • , Christine Munk,
  • , Alla Lapidus
  • , Matt Nolan
  • , Susan Lucas
  • , Nancy Hammon
  • , Shweta Deshpande
  • , Jan-Fang Cheng
  • , Roxane Tapia,
  • , Cliff Han,
  • , Lynne Goodwin,
  • , Sam Pitluck
  • , Konstantinos Liolios
  • , Natalia Ivanova
  • , Konstantinos Mavromatis
  • , Natalia Mikhailova
  • , Amrita Pati
  • , Amy Chen
  • , Krishna Palaniappan
  • , Miriam Land,
  • , Loren Hauser,
  • , Yun-Juan Chang,
  • , Cynthia D. Jeffries,
  • , Evelyne Brambilla
  • , Manfred Rohde
  • , Markus Göker
  • , John C. Detter,
  • , Tanja Woyke
  • , James Bristow
  • , Jonathan A. Eisen,
  • , Victor Markowitz
  • , Philip Hugenholtz,
  • , Nikos C. Kyrpides
  • and Hans-Peter Klenk
Corresponding author

DOI: 10.4056/sigs.1503846

Received: 20 February 2011

Published: 04 March 2011

Abstract

Paludibacter propionicigenes Ueki et al. 2006 is the type species of the genus Paludibacter, which belongs to the family Porphyromonadaceae. The species is of interest because of the position it occupies in the tree of life where it can be found in close proximity to members of the genus Dysgonomonas. This is the first completed genome sequence of a member of the genus Paludibacter and the third sequence from the family Porphyromonadaceae. The 3,685,504 bp long genome with its 3,054 protein-coding and 64 RNA genes consists of one circular chromosome and is a part of the Genomic Encyclopedia of Bacteria and Archaea project.

Keywords:

strictly anaerobicnonmotileGram-negativeanoxic rice-field soilmesophilicchemoorganotrophicPorphyromonadaceaeGEBA

Introduction

Strain WB4T (= DSM 17365 = CCUG 53888 = JCM 13257) is the type strain of P. propionicigenes, which is the type species of the genus Paludibacter [1,2]. Currently, there is only one species placed in the genus Paludibacter [1]. The generic name derives from the Latin noun palusudis meaning swamp or marsh and the Neo-Latin word bacter meaning a rod, referring to a rod living in swamps [2]. The species epithet is derived from the Neo-Latin word acidum propionicum meaning propionic acid and the Greek verb gennao meaning to produce, referring to the metabolic property of the species [2]. P. propionicigenes strain WB4T was isolated together with a number of other strains from rice plant residues in an anoxic rice-field soil in Yamagata, Japan, and described for the first time by Akasaka et al. in 2003 [3]. In 2006 the species was formally described by Ueki et al. and the genus Paludibacter was introduced [2]. No further isolates have been obtained for P. propionicigenes, however, cultivation-independent 16S rRNA-dependent molecular investigations showed the presence of P. propionicigenes in the rumen of sheep [4]. Here we present a summary classification and a set of features for P. propionicigenes WB4T, together with the description of the complete genomic sequencing and annotation.

Classification and features

A representative genomic 16S rRNA sequence of strain WB4T was compared using NCBI BLAST under default values (e.g., considering only the best 250 hits) with the most recent release of the Greengenes database [5] and the relative frequencies, of taxa and keywords (reduced to their stems [6]) were determined, weighted by BLAST scores. The most frequently occurring genus was Dysgonomonas (100%) (8 hits in total). Among all other species, the one yielding the highest score was Dysgonomonas capnocytophagoides, which corresponded to an identity of 91.9% and a HSP coverage of 83.6%. The highest-scoring environmental sequence was AY212569 ('water 10 m downstream manure clone 118ds10'), which showed an identity of 99.6% and a HSP coverage of 100.1%. The five most frequent keywords within the labels of environmental samples which yielded hits were 'digest' (11.7%), 'anaerob' (6.2%), 'sludge' (6.1%), 'wastewater' (6.0%) and 'mesophile' (5.9%) (241 hits in total). The single most frequent keyword within the labels of environmental samples which yielded hits of a higher score than the highest scoring species was 'downstream/manure/water' (33.3%) (1 hit in total).

Figure 1 shows the phylogenetic neighborhood of P. propionicigenes WB4T in a 16S rRNA based tree. The three identical 16S rRNA sequences in the genome differ by one nucleotide from the previously published 16S rRNA sequence (AB078842).

Figure 1

Phylogenetic tree highlighting the position of P. propionicigenes relative to the other type strains within the family Porphyromonadaceae. The tree was inferred from 1,400 aligned characters [7,8] of the 16S rRNA gene sequence under the maximum likelihood criterion [9] and rooted in accordance with the current taxonomy. The branches are scaled in terms of the expected number of substitutions per site. Numbers above branches are support values from 300 bootstrap replicates [10] if larger than 60%. Lineages with type strain genome sequencing projects registered in GOLD [11] are shown in blue, published genomes in bold [12,13].

The cells of P. propionicigenes are generally rod-shaped (0.5-0.6 μm × 1.3-1.7 µm) with ends that are round or slightly tapered [2]. Elongated cells can also be seen, either as single cells or in short chains (Figure 2). P. propionicigenes is a Gram-negative and non spore-forming bacterium (Table 1). The organism is described to be nonmotile; only eight genes associated with motility were identified in the genome. The organism is strictly anaerobic and chemoorganotrophic [2,3]. The temperature range for growth is between 15°C and 35°C, with an optimum at 30°C [2]. The organism does not grow at 37°C [2]. The pH range for growth is 5.0-7.6 with an optimum at pH 6.6 [2]. NaCl concentrations from 0-0.5% (w/v) are tolerated. P. propionicigenes is able to utilize arabinose, glucose, fructose, xylose, cellobiose, galactose, mannose, maltose, melibiose, glycogen and soluble starch as growth substrates [2]. The organism does not utilize ribose, lactose, sucrose, melezitose, raffinose, sorbose, rhamnose, trehalose, cellulose, xylan, salicin, dulcitol, inositol, mannitol, sorbitol, ethanol, glycerol, fumarate, malate, lactate, succinate or pyruvate [2]. Glucose is fermented to propionate and acetate in a molar ratio of 2:1 as major products and succinate as a minor product [2]. The organism does not reduce nitrate, it does not hydrolyze gelatin or urea and does not produce indole or hydrogen sulfide [2]. P. propionicigenes does not grow in the presence of bile salts. Catalase and oxidase are not present in the organism [2].

Figure 2

Scanning electron micrograph of P. propionicigenes WB4T

Table 1

Classification and general features of P. propionicigenes WB4T according to the MIGS recommendations [14].

MIGS ID

    Property

    Term

    Evidence code

    Current classification

    Domain Bacteria

    TAS [15]

    Phylum Bacteroidetes

    TAS [16]

    Class Bacteroidia

    TAS [16,17]

    Order Bacteroidales

    TAS [16]

    Family Porphyromonadaceae

    TAS [16]

    Genus Paludibacter

    TAS [2]

    Species Paludibacter propionicigenes

    TAS [2]

    Type strain WB4

    TAS [2]

    Gram stain

    negative

    TAS [3]

    Cell shape

    rod-shaped

    TAS [3]

    Motility

    non-motile

    TAS [2]

    Sporulation

    none

    TAS [3]

    Temperature range

    15°C to 35°C

    TAS [3]

    Optimum temperature

    30°C

    TAS [2]

    Salinity

    normal

    NAS

MIGS-22

    Oxygen requirement

    strictly anaerobic

    TAS [3]

    Carbon source

    carbohydrates

    TAS [3]

    Energy source

    chemoorganotroph

    TAS [3]

MIGS-6

    Habitat

    soil

    TAS [3]

MIGS-15

    Biotic relationship

    free-living

    NAS

MIGS-14

    Pathogenicity

    none

    NAS

    Biosafety level

    1

    TAS [18]

    Isolation

    rice plant residue in anoxic rice-field soil

    TAS [3]

MIGS-4

    Geographic location

    Yamagata, Japan

    TAS [3]

MIGS-5

    Sample collection time

    1994

    TAS [3]

MIGS-4.1

    Latitude

    38.25

    NAS

MIGS-4.2

    Longitude

    140.34

    NAS

MIGS-4.3

    Depth

    not reported

MIGS-4.4

    Altitude

    not reported

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 [19]. If the evidence code is IDA, then the property was directly observed by one of the authors or an expert mentioned in the acknowledgements.

Chemotaxonomy

Little chemotaxonomic data are available for strain WB4T. Only the fatty acid composition has been elucidated. The major fatty acids found were anteiso-C15:0 (30.8%), C15:0 (19.0%) and 3-hydroxy anteiso-C17:0 (17.9%) [2]. Also, iso-C17:0 3-OH (6.2%) and C16:0 (4.9%) were detected in intermediate amounts whereas iso-C15:0 3-OH, iso-C16:0 3-OH, C15:0 3-OH, C16:03-OH, iso-C15:0, C14:0, C16:0, and C18:0 were present in minor amounts (1% to 5% of the total fatty acids). Unsaturated fatty acids were not detected [2].

Genome sequencing and annotation

Genome project history

This organism was selected for sequencing on the basis of its phylogenetic position [20], and is part of the Genomic Encyclopedia of Bacteria and Archaea project [21]. The genome project is deposited in the Genomes OnLine Database [11] 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

     Three genomic libraries: one 454 pyrosequence standard library, one 454 PE library (9 kb insert size),     one Illumina library

MIGS-29

     Sequencing platforms

     Illumina GAii, 454 GS FLX Titanium

MIGS-31.2

     Sequencing coverage

     337.6 × Illumina; 28.1 × pyrosequence

MIGS-30

     Assemblers

     Newbler version 2 2.3-PreRelease-10-21-2009-gcc-4.1.2-threads,     Velvet, phrap

MIGS-32

     Gene calling method

     Prodigal 1.4, GenePRIMP

     INSDC ID

     CP002345

     Genbank Date of Release

     December 2, 2010

     GOLD ID

     Gc01549

     NCBI project ID

     694427

     Database: IMG-GEBA

     2503538024

MIGS-13

     Source material identifier

     DSM 17365

     Project relevance

     Tree of Life, GEBA

Growth conditions and DNA isolation

P. propionicigenes WB4T, DSM 17365, was grown anaerobically in DSMZ medium 104 [22] at 30°C. DNA was isolated from 0.5-1 g of cell paste using a MasterPure Gram-positive DNA purification kit (Epicentre MGP04100) following the standard protocol as recommended by the manufacturer, with modification st/DL for cell lysis as described in Wu et al. [21].

Genome sequencing and assembly

The genome was sequenced using a combination of Illumina and 454 sequencing platforms. All general aspects of library construction and sequencing can be found at the JGI website [23]. Pyrosequencing reads were assembled using the Newbler assembler version 2.3-PreRelease-10-21-2009-gcc-4.1.2-threads (Roche). The initial Newbler assembly consisting of 26 contigs in one scaffold which was converted into a phrap assembly by [24] making fake reads from the consensus, to collect the read pairs in the 454 paired end library. Illumina GAii sequencing data (967 Mb) was assembled with Velvet [25] and the consensus sequences were shredded into 1.5 kb overlapped fake reads and assembled together with the 454 data. The 454 draft assembly was based on 93.4 Mb 454 draft data and all of the 454 paired end data. Newbler parameters are -consed -a 50 -l 350 -g -m -ml 20. The Phred/Phrap/Consed software package was used for sequence assembly and quality assessment in the subsequent finishing process. After the shotgun stage, reads were assembled with parallel phrap (High Performance Software, LLC). Possible mis-assemblies were corrected with gapResolution [23], Dupfinisher, or sequencing cloned bridging PCR fragments with subcloning or transposon bombing (Epicentre Biotechnologies, Madison, WI) [26]. Gaps between contigs were closed by editing in Consed, by PCR and by Bubble PCR primer walks (J.-F.Chang, unpublished). A total of 124 additional reactions and one shatter library were necessary to close the gaps and to raise the quality of the finished sequence. Illumina reads were also used to correct potential base errors and increase consensus quality using a software Polisher developed at JGI [27]. The error rate of the completed genome sequence is less than 1 in 100,000. Together, the combination of the Illumina and 454 sequencing platforms provided 365.7 × coverage of the genome. The final assembly contained 333,397 pyrosequence and 34,564,373 Illumina reads.

Genome annotation

Genes were identified using Prodigal [28] as part of the Oak Ridge National Laboratory genome annotation pipeline, followed by a round of manual curation using the JGI GenePRIMP pipeline [29]. The predicted CDSs were translated and used to search the National Center for Biotechnology Information (NCBI) nonredundant database, UniProt, TIGR-Fam, 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 [30].

Genome properties

The genome consists of a 3,685,504 bp long chromosome with a GC content of 38.9% (Table 3 and Figure 3). Of the 3,118 genes predicted, 3,054 were protein-coding genes, and 64 RNAs; 34 pseudogenes were also identified. The majority of the protein-coding genes (65.8%) 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)

   3,685,504

    100.00%

DNA coding region (bp)

   3,225,817

    87.53%

DNA G+C content (bp)

   1,432,064

    38.86%

Number of replicons

   1

Extrachromosomal elements

   0

Total genes

   3,118

    100.00%

RNA genes

   64

    2.05%

rRNA operons

   3

Protein-coding genes

   3,054

    97.95%

Pseudo genes

   34

    1.09%

Genes with function prediction

   2,051

    65.78%

Genes in paralog clusters

   325

    10.42%

Genes assigned to COGs

   2,005

    64.30%

Genes assigned Pfam domains

   2,205

    70.72%

Genes with signal peptides

   843

    27.04%

Genes with transmembrane helices

   784

    25.14%

CRISPR repeats

   2

Figure 3

Graphical circular map of the chromosome. 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

    149

   6.8

   Translation, ribosomal structure and biogenesis

A

    0

   0

   RNA processing and modification

K

    136

   6.2

   Transcription

L

    101

   4.6

   Replication, recombination and repair

B

    0

   0

   Chromatin structure and dynamics

D

    22

   1.0

   Cell cycle control, cell division, chromosome partitioning

Y

    0

   0

   Nuclear structure

V

    48

   2.2

   Defense mechanisms

T

    99

   4.5

   Signal transduction mechanisms

M

    232

   10.6

   Cell wall/membrane/envelope biogenesis

N

    8

   0.4

   Cell motility

Z

    0

   0

   Cytoskeleton

W

    0

   0

   Extracellular structures

U

    40

   1.8

   Intracellular trafficking, secretion, and vesicular transport

O

    80

   3.7

   Posttranslational modification, protein turnover, chaperones

C

    108

   5.0

   Energy production and conversion

G

    172

   7.9

   Carbohydrate transport and metabolism

E

    166

   7.6

   Amino acid transport and metabolism

F

    61

   2.8

   Nucleotide transport and metabolism

H

    128

   5.9

   Coenzyme transport and metabolism

I

    67

   3.1

   Lipid transport and metabolism

P

    131

   6.0

   Inorganic ion transport and metabolism

Q

    24

   1.1

   Secondary metabolites biosynthesis, transport and catabolism

R

    256

   11.7

   General function prediction only

S

    153

   7.0

   Function unknown

-

    1,113

   35.7

   Not in COGs

Declarations

Acknowledgements

We would like to gratefully acknowledge the help of Sabine Welnitz (DSMZ) for growing P. propionicigenes cultures. This work was performed under the auspices of the US Department of Energy Office of Science, Biological and Environmental Research Program, and by the University of California, Lawrence Berkeley National Laboratory under contract No. DE-AC02-05CH11231, Lawrence Livermore National Laboratory under Contract No. DE-AC52-07NA27344, and Los Alamos National Laboratory under contract No. DE-AC02-06NA25396, UT-Battelle and Oak Ridge National Laboratory under contract DE-AC05-00OR22725, as well as German Research Foundation (DFG) INST 599/1-2.


This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

References

  1. Garrity G. NamesforLife. BrowserTool takes expertise out of the database and puts it right in the browser. Microbiol Today. 2010; 7:1
  2. Ueki A, Akasaka H, Suzuki D and Ueki K. Paludibacter propionicigenes gen. nov., sp. nov., a novel strictly anaerobic, Gram-negative, propionate-producing bacterium isolated from plant residue in irrigated rice-field soil in Japan. Int J Syst Evol Microbiol. 2006; 56:39-44 View ArticlePubMed
  3. Akasaka H, Izawa T, Ueki K and Ueki A. Phylogeny of numerically abundant culturable anaerobic bacteria associated with degradation of rice plant residue in Japanese paddy field soil. FEMS Microbiol Ecol. 2003; 43:149-161 View ArticlePubMed
  4. Pei CX, Liu Q, Dong CS, Li H, Jiang JB and Gao WJ. Diversity and abundance of the bacterial 16S rRNA gene sequences in forestomach of alpacas (Lama pacos) and sheep (Ovis aries). Anaerobe. 2010; 16:426-432 View ArticlePubMed
  5. DeSantis TZ, Hugenholtz P, Larsen N, Rojas M, Brodie EL, Keller K, Huber T, Dalevi D, Hu P and Andersen GL. Greengenes, a Chimera-Checked 16S rRNA Gene Database and Workbench Compatible with ARB. Appl Environ Microbiol. 2006; 72:5069-5072 View ArticlePubMed
  6. Porter MF. An algorithm for suffix stripping. Program: electronic library and information systems. 1980; 14:130-137
  7. Lee C, Grasso C and Sharlow MF. Multiple sequence alignment using partial order graphs. Bioinformatics. 2002; 18:452-464 View ArticlePubMed
  8. Castresana J. Selection of conserved blocks from multiple alignments for their use in phylogenetic analysis. Mol Biol Evol. 2000; 17:540-552PubMed
  9. Stamatakis A, Hoover P and Rougemont J. A rapid bootstrap algorithm for the RAxML web-servers. Syst Biol. 2008; 57:758-771 View ArticlePubMed
  10. Pattengale ND, Alipour M, Bininda-Emonds ORP, Moret BME and Stamatakis A. How Many Bootstrap Replicates Are Necessary? Lect Notes Comput Sci. 2009; 5541:184-200 View Article
  11. Liolios K, Chen IM, Mavromatis K, Tavernarakis N, Hugenholtz P, Markowitz VM and Kyrpides NC. The Genomes OnLine Database (GOLD) in 2009: status of genomic and metagenomic projects and their associated metadata. Nucleic Acids Res. 2010; 38:D346-D354 View ArticlePubMed
  12. Xu J, Mahowald MA, Ley RE, Lozupone CA, Hamady M, Martens EC, Henrissat B, Coutinho PM, Minx P and Latreille P. Evolution of symbiotic bacteria in the distal human intestine. PLoS Biol. 2007; 5:e156 View ArticlePubMed
  13. Naito M, Hirakawa H, Yamashita A, Ohara N, Shoji M, Yukitake H, Nakayama K, Toh H, Yoshimura F and Kuhara S. Determination of the genome sequence of Porphyromonas gingivalis strain ATCC 33277 and genomic comparison with strain W83 revealed extensive genome rearrangements in P. gingivalis. DNA Res. 2008; 15:215-225 View ArticlePubMed
  14. Field D, Garrity G, Gray T, Morrison N, Selengut J, Sterk P, Tatusova T, Thomson N, Allen MJ and Angiuoli SV. The minimum information about a genome sequence (MIGS) specification. Nat Biotechnol. 2008; 26:541-547 View ArticlePubMed
  15. Woese CR, Kandler O and Wheelis ML. Towards a natural system of organisms: proposal for the domains Archaea, Bacteria, and Eucarya. Proc Natl Acad Sci USA. 1990; 87:4576-4579 View ArticlePubMed
  16. Garrity GM, Holt JG. Taxonomic Outline of the Archaea and Bacteria In: Garrity GM, Boone DR, Castenholz RW (eds), Bergey's Manual of Systematic Bacteriology, Second Edition, Volume 1, Springer, New York, 2001, p. 155-166.
  17. Ludwig W, Euzeby J, Whitman WG. Draft taxonomic outline of the Bacteroidetes, Planctomycetes, Chlamydiae, Spirochaetes, Fibrobacteres, Fusobacteria, Acidobacteria, Verrucomicrobia, Dictyoglomi, and Gemmatimonadetes Taxonomic Outline 2008.Web Site
  18. . Classification of bacteria and archaea in risk groups. TRBA. 2005; 466:84
  19. Ashburner M, Ball CA, Blake JA, Botstein D, Butler H, Cherry JM, Davis AP, Dolinski K, Dwight SS and Eppig JT. Gene Ontology: tool for the unification of biology. Nat Genet. 2000; 25:25-29 View ArticlePubMed
  20. Klenk HP and Goeker M. En route to a genome-based classification of Archaea and Bacteria? Syst Appl Microbiol. 2010; 33:175-182 View ArticlePubMed
  21. Wu D, Hugenholtz P, Mavromatis K, Pukall R, Dalin E, Ivanova NN, Kunin V, Goodwin L, Wu M and Tindall BJ. A phylogeny-driven genomic encyclopaedia of Bacteria and Archaea. Nature. 2009; 462:1056-1060 View ArticlePubMed
  22. List of growth media used at DSMZ: Web Site
  23. . Web Site
  24. Phrap and Phred for Windows. MacOS, Linux, and Unix. Web Site
  25. Zerbino DR and Birney E. Velvet: algorithms for de novo short read assembly using de Bruijn graphs. Genome Res. 2008; 18:821-829 View ArticlePubMed
  26. Han C, Chain P. 2006. Finishing repeat regions automatically with Dupfinisher. in Proceeding of the 2006 international conference on bioinformatics & computational biology. Edited by Hamid R. Arabnia & Homayoun Valafar, CSREA Press. June 26- 29, 2006: 141-146.30.
  27. Lapidus A, LaButti K, Foster B, Lowry S, Trong S, Goltsman E. POLISHER: An effective tool for using ultra short reads in microbial genome assembly and finishing. AGBT, Marco Island, FL, 2008.
  28. Hyatt D, Chen GL, LoCascio PF, Land ML, Larimer FW and Hauser LJ. Prodigal: prokaryotic gene recognition and translation initiation site identification. BMC Bioinformatics. 2010; 11:119 View ArticlePubMed
  29. Pati A, Ivanova NN, Mikhailova N, Ovchinnikova G, Hooper SD, Lykidis A and Kyrpides NC. GenePRIMP: a gene prediction improvement pipeline for prokaryotic genomes. Nat Methods. 2010; 7:455-457 View ArticlePubMed
  30. Markowitz VM, Ivanova NN, Chen IMA, Chu K and Kyrpides NC. IMG ER: a system for microbial genome annotation expert review and curation. Bioinformatics. 2009; 25:2271-2278 View ArticlePubMed