Open Access

Draft genome sequence of ‘Treponema phagedenis’ strain V1, isolated from bovine digital dermatitis

  • Mamoona Mushtaq1,
  • Shahid Manzoor1, 4,
  • Märit Pringle2,
  • Anna Rosander3 and
  • Erik Bongcam-Rudloff1Email author
Standards in Genomic Sciences201510:67

https://doi.org/10.1186/s40793-015-0059-0

Received: 24 May 2014

Accepted: 17 August 2015

Published: 21 September 2015

Abstract

‘Treponema phagedenis’ is considered to be a key agent in the pathogenesis of bovine digital dermatitis, an infectious foot condition of economic and animal welfare importance. We hereby report the draft sequence of ‘T. phagedenis’ strain V1. The draft genome assembly consists of 51 scaffolds comprising 3,129,551 bp and a GC-content of 39.9 %. Putative pathogenicity related factors have been identified in the genome that can be used in future studies to gain insight into the pathogenic mechanisms of ‘T. phagedenis’.

Keywords

‘T. phagedenis’ Genome assembly Digital dermatitis Västra Götaland Sweden

Introduction

Digital dermatitis is a painful infection of the foot and is the leading cause of lameness in dairy cattle. Secondary effects of lameness are decreased milk production and weight loss leading to economic losses and animal welfare problems [1]. The disease is characterized by a diffuse or circumscribed superficial dermatitis of the skin at the coronary margin of the hoof. Erosive lesions are formed at the superficial layer of epidermis accompanied by pain, swelling and foul odor. Bacteria from different genera have been identified from these lesions, among them spirochetes of the genus Treponema are most prevalent [24]. Members of this genus constitute both commensal and pathogenic spirochetes. Treponema pallidum , which causes syphilis, is a well-known example of a pathogenic treponeme. A Treponema phylotype recently suggested being the same species as is the human commensal Treponema phagedenis [5] which is considered to be a key agent in the pathogenesis of digital dermatitis [69]. T. phagedenis is thought to be important for lesion development because it is found at the interface with healthy tissue [10] and has been detected in infected cattle from Europe [11], North America [12], and Asia [13]. To identify the putative pathogenicity related factors of ‘ T. phagedenis ', we performed sequencing of the ‘ T. phagedenis ’ strain V1 chromosome [14].

Organism information

Classification and features

' Treponema phagedenis ' strain V1 (Fig. 1) was isolated from a Swedish dairy cow [14]. Strains 4A and YG3903R were isolated from digital dermatitis lesion in cattle from USA and Japan respectively [12, 13]. According to 16S rRNA sequence comparison using NCBI blast [15] T. phagedenis V1 (DQ470655) shares 100 % identity with T. phagedenis strains 4A (AF546875) and YG3903R (FJ004921) and 98 %-99 % identity with human strains CIP 62.29 (EF645248) and K5 (M57739). Among other treponemes, T. phagedenis V1 is most closely related to Treponema putidum (AJ543428) and Treponema denticola (AF139203) sharing 93 % 16S rRNA identity with them. Figure 2 shows the phylogenetic relationship of T. phagedenis V1 with the other Treponema species in a 16S rRNA based tree.
Fig. 1

A scanning electron microscope picture of Treponema phagedenis V1 cells. Photo: Leif Ljung

Fig. 2

16S rRNA phylogenetic tree; Phylogenetic tree of 16S rRNA sequences highlighting the position of ‘Treponema phagedenis’ strain V1 relative to other ‘Treponema phagedenis’ strains and to the other species within the genus. Brachyspira hyodysenteriae and Brachyspira innocens are used as out-group. The evolutionary history was inferred from 1212 aligned characters [42, 43]. The tree is drawn to scale, with branch lengths measured in the number of substitutions per site. Numbers above branches are support values from 1000 bootstrap replicates. 0.04 on the scale bar represents 4 substitutions in 100 bp. Evolutionary analyses were conducted using maximum Likelihood method in MEGA6 [44]

Treponema phagedenis ’ is a helically, right-handed coiled bacterium with bent ends that are motile [16]. The typical size of ‘ T. phagedenis ’ ranges in length from 0.8 to 15 μm and 0.3 to 0.4 μm in width, with 7 to 9 flagella attached on each end [5, 12]. These bacteria are mostly host-associated, anaerobic and have fastidious growth requirements. Treponema phagedenis strain V1 was isolated from a clinical sample from a digital dermatitis lesion. [14]. The sample was taken from an acute lesion in a herd with continuous problems with digital dermatitis. According to the API ZYM profile, T. phagedenis strain V1 shows a positive reaction for alkaline phosphatase, C4 esterase, C8 esterase lipase, acid phosphatase, naptholphosphohydrolase, β-galactosidase, and N-acetyl-β-glucosaminidase. The antimicrobial susceptibility test performed on T. phagedenis strain V1 shows that it is susceptible to tiamulin, valnemulin, tylosin, aivlosin and doxycycline [14]. Also, three immunogenic proteins, TmpA, Ttm, and PrrA, have been detected in T. phagedenis . The presence of antibodies against these proteins has been identified in high titer in sera from cattle with digital dermatitis through indirect enzyme-linked immunosorbent assay [17]. General features of T. phagedenis V1 are stated in Table 1.
Table 1

Classification and general features of ‘Treponema phagdenis’ strain V1 [33]

MIGS ID

Property

Term

Evidence codea

 

Classification

Domain Bacteria

TAS [34]

  

Phylum Spirochaetes

TAS [35]

  

Class ‘Spirochaetia’

TAS [36]

  

Order Spirochaetales

TAS [3739]

  

Family Spirochaetaceae

TAS [40]

  

Genus Treponema

TAS [6, 14]

  

Species ‘Treponema phagdenis’

TAS [5, 14]

  

Strain: V1

 
 

Gram stain

negative

TAS [41]

 

Cell shape

Helical

TAS [41]

 

Motility

Motile

TAS [14, 17]

 

Sporulation

Non-sporulating

NAS

 

Temperature range

30-42 °C

NAS [41]

 

Optimum temperature

37 °C

NAS [41]

 

pH range; Optimum

6–8.5; 7

TAS [5]

 

Carbon source

D-glucose

IDA

MIGS-6

Habitat

Digital dermatitis lesion in cattle

TAS [14]

MIGS-6.3

Salinity

Not reported

 

MIGS-22

Oxygen requirement

Anaerobic

NAS

MIGS-15

Biotic relationship

Host-associated

NAS

MIGS-14

Pathogenicity

Potential pathogen in cattle

TAS [14]

MIGS-4

Geographic location

Västra Götaland county, Sweden

TAS [14]

MIGS-5

Sample collection

2005

TAS [14]

MIGS-4.1

Latitude

Not reported

 

MIGS-4.2

Longitude

Not reported

 

MIGS-4.4

Altitude

Not reported

 

IDA Inferred from Direct Assay, 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 the Gene Ontology project [33]

aEvidence codes

Genome sequencing information

Genome project history

Treponema phagedenis strain V1 was selected for sequencing in 2009 at the Swedish University of Agricultural Sciences (SLU), Uppsala, Sweden. The genome was assembled and annotated by the SLU-Global Bioinformatics Centre at SLU. The genome project is deposited in the Genomes OnLine Database [18] with GOLD id Gi0072982 and the draft genome assembly is deposited in the European Nucleotide Archive database with accession number (CDNC01000001-CDNC01000051) under the study accession number: PRJEB5300. The aim of the sequencing was to identify genes that are linked to pathogenicity and virulence in related bacteria, to strengthen the hypothesis that bacteria of the genus Treponema causes digital dermatitis in cattle. Almost nothing is known about virulence factors of treponemes involved in digital dermatitis. Table 2 contains the summary of the project information.
Table 2

Project information

MIGS ID

Property

Term

MIGS 31

Finishing quality

Draft

MIGS-28

Libraries used

454 Single end reads, Illumina paired end reads

MIGS 29

Sequencing platforms

454, Illumina hiseq

MIGS 31.2

Fold coverage

25×, 100×

MIGS 30

Assemblers

Newbler

MIGS 32

Gene calling method

Prodigal

 

Locus Tag

TPHV1

 

GeneBank ID

CDNC00000000

 

GenBank Date of Release

18-01-2015

 

GOLD ID

Gp0092386

 

BIOPROJECT

PRJEB5300

MIGS 13

Source Material Identifier

Not reported

 

Project relevance

Potential pathogen

Growth conditions and genomic DNA preparation

' Treponema phagedenis ' V1 was grown in flasks containing 10 ml FABGS (LAB071 fastidious anaerobe broth, LabM, with 2.0 g D-glucose per liter and 25 % fetal calf serum, S 0115, Biochrom AG), and incubated in anaerobic jars at 37 °C, 90 rpm. Genomic DNA was prepared with the DNeasy Blood & Tissue Kit (QIAGEN) following the protocol for Gram-negative bacteria [17]. The DNA concentration measured by Picodrop Microliter UV/Vis Spectrophotometer was 566 ng μl−1.

Genome sequencing and assembly

The genomic sequence was obtained using a combination of Roche 454 GS FLX sequencing platform at the Royal Institute of Technlogy in Stockholm and Illumina HiSeq 2000 at the Uppsala sequencing platform. For Illumina sequencing three different libraries were used with the insert size of 160 bp, 305 bp and 505 bp. A total of 306,592 reads with the average read length of 300 bp were obtained from 454 sequencing and 60,174,091, 61,097,083, and 71,967,626 reads from the 160, 305 and 505 bp insert size libraries, respectively, from the Illumina sequencing. Subsets of reads from all three libraries were generated using a custom perl script to lower the coverage before performing assembly. Four different assemblies were produced, these include (i) hybrid assembly of 454 reads and Illumina reads from 160 bp insert size library (ii) hybrid assembly of 454 reads and Illumina reads from 305 bp insert size library (iii) hybrid assembly of 454 reads and Illumina reads from 505 bp insert size library (iv) 454 reads assembly. The resulting assemblies varied in size from 2.9 to 3.1 Mbp with the average GC content of 39 %. Assembly was performed with the GS de novo assembler version 2.5.3 (Roche) using reads from each Illumina paired end library and the 454 sequencing. Resulting assemblies were compared using the MAUVE genome alignment tool [19]. The hybrid assembly produced from 454 reads and Illumina reads from 305 bp insert size library was selected for further analysis. Selection was based on N50 statistics, number of contigs and the length of the largest contig. Assembly statistics of all assemblies are provided in supporting Additional file 1: Table S1. Scaffolding of the selected assembly was performed using SSPACE [20] and possible removal of gaps present in scaffolds was done using Gapfiller [21] and. Homopolymer errors were corrected manually using Consed [22].

Genome annotation

The structural and functional annotation was accomplished via the Magnifying Genome (MaGe) Annotation Platform [23]. Prediction of tRNA and rRNA genes was performed using tRNAscan-SE version 1.23 [24] and RNAmmer version 1.2 [25], respectively. Putative functions of the encoding genes were assigned automatically by MAGE′s inbuilt BlastP searches against the UniProt and Trembl, TIGR-Fam, Pfam, PRIAM, COG and InterPro databases. Putative phage prediction was performed using PHAST (PHAge Search Tool) webserver [26]. Proteins with signal peptides were predicted using SignalP v 4.1 [27] and TMHMM Server, v.2.0 [28] was used to predict transmembrane helices in the protein sequences.

Genome properties

The draft genome assembly comprised 60 contigs in 51 scaffolds with a total size of 3,129,551 bp (Fig. 3) that corresponds well to the size of two previously sequenced ‘ T. phagedenis strains, 4A isolated from bovine digital dermatitis and F0421 isolated from human urogenitalia, with the assembly sizes of 3,027,773 and 2,830,421 respectively. The G + C content of the assembly was 39.9 %. In total 3,222 genes were predicted, of which 3,157 were protein coding genes. Table 3 contains the general genomic features. The classification of the protein coding genes in different COG categories is shown in Table 4.
Fig. 3

Circular representation of genome; Circular map (from the outside to the center): (1) GC percent deviation (GC window - mean GC) in a 1000-bp window. (2) Predicted CDSs transcribed in the clockwise direction. (3) Predicted CDSs transcribed in the counterclockwise direction. (4) GC skew (G + C/G-C) in a 1000-bp window. (5) rRNA (blue), tRNA (green), miscRNA (orange), Transposable elements (pink) and pseudogenes (grey)

Table 3

Genome statistics

Attribute

Value

% of Total

Genome size (bp)

3,129,551

100.0

DNA coding (bp)

2,623,392

83.8

DNA G + C (bp)

1,249,392

39.9

DNA scaffolds

51

100.0

Total genes

3,222

100.0

Protein coding genes

3,157

98

RNA genes

51

1.6

Pseudo genes

9

0.3

Genes in internal clusters

  

Genes with function prediction

1,547

48

Genes assigned to COGs

2,051

63.7

Genes with Pfam domains

1,788

55.5

Genes with signal peptides

187

5.8

Genes with transmembrane helices

791

24.5

CRISPR repeats

  
Table 4

Number of genes associated with general COG functional categories

Code

Value

%age

Description

J

152

4.8

Translation, ribosomal structure and biogenesis

A

0

0.0

RNA processing and modification

K

132

4.2

Transcription

L

263

8.3

Replication, recombination and repair

B

0

0.0

Chromatin structure and dynamics

D

33

1.0

Cell cycle control, Cell division, chromosome partitioning

V

74

2.3

Defense mechanisms

T

139

4.4

Signal transduction mechanisms

M

123

3.9

Cell wall/membrane biogenesis

N

102

3.2

Cell motility

U

41

1.3

Intracellular trafficking and secretion

O

85

2.3

Posttranslational modification, protein turnover, chaperones

C

114

3.6

Energy production and conversion

G

223

7.0

Carbohydrate transport and metabolism

E

156

4.9

Amino acid transport and metabolism

F

57

1.8

Nucleotide transport and metabolism

H

57

1.8

Coenzyme transport and metabolism

I

41

1.3

Lipid transport and metabolism

P

119

3.7

Inorganic ion transport and metabolism

Q

15

0.5

Secondary metabolites biosynthesis, transport and catabolism

R

313

9.8

General function prediction only

S

170

5.4

Function unknown

-

1115

35.2

Not in COGs

The total is based on the total number of protein coding genes in the genome

Insights from the genome sequence

Potential pathogenicity related factors

Putative pathogenicity related proteins that are present in the genomes of T. pallidum [29] and T. denticola [30] were predicted in ‘ T. phagedenis strain V1. Protein sequences from T. pallidum strain Nichols (accession number NC_000919) and T. denticola strain ATCC 35405 (accession number NC_002967) were used to perform blast searches against the predicted proteins of ' T. phagedenis ' V1. These contained genes that encode for putative adhesins, antigens and a major sheath protein (Additional file 2: Table S2). Also, 22 CDS encoding chemotaxis and motility proteins, 17 CDS encoding transposases, 2 CDS encoding hemolysins and 3 putative prophages were predicted in the ' T. phagedenis ' genome annotation.

Lipoproteins are considered to be of special attention in spirochetes because of their abundance in different spirochetal genera including Treponema [31]. Several of them localize to the bacterial surface and are considered as important vaccine targets. Lipoprotein prediction was thus performed separately using the SpLip server [32] that predicted 155 probable lipoproteins. The predicted lipoproteins were then Blasted against the proteins in all bacteria. Two lipoproteins with homology to known virulence related or antigenic proteins in other treponemes were expressed in Escherichia coli and are being used in ongoing studies.

Conclusions

The genome sequence of ‘ T. phagedenis strain V1 provides useful information on potential virulence related and antigenic proteins, which may help to establish the role of treponemes in digital dermatits in cattle. They may also be used in development of diagnostic tools and prevention strategies for the disease. Comparative studies with genome sequences of treponemes in general and ‘ T. phagedenis isolates from digital dermatitis lesions in particular, can be performed. The V1 genome sequence may also prove useful for classification purposes.

Declarations

Acknowledgements

The PhD program of the Higher Education Commission of Pakistan supported MM. The authors would further like to acknowledge support of Uppsala Genome Center, UPPMAX and KTH Genome Center at the Royal Institute of Technology, and BILS for providing assistance in massive parallel sequencing and computational infrastructure. The contribution of MM and EB-R was supported by COST action SeqAhead, www.seqahead.eu. This work was also supported by the ALLBIO, EU FP7, grant number 289452, www.allbioinformatics.eu. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Authors’ Affiliations

(1)
Department of Animal Breeding and Genetics Science, Swedish University of Agricultural Science, SLU-Global Bioinformatics Centre
(2)
Department of Animal Health and Antimicrobial Strategies, National Veterinary Institute
(3)
Department of Biomedical Sciences and Veterinary Public Health, Swedish University of Agricultural Sciences
(4)
Department of Information Technology, University of the Punjab

References

  1. Bruijnis MR, Hogeveen H, Stassen EN. Assessing economic consequences of foot disorders in dairy cattle using a dynamic stochastic simulation model. J Dairy Sci. 2010;93:2419–32.View ArticlePubMedGoogle Scholar
  2. Rasmussen M, Capion N, Klitgaard K, Rogdo T, Fjeldaas T, Boye M, et al. Bovine digital dermatitis: possible pathogenic consortium consisting of Dichelobacter nodosus and multiple Treponema species. Vet Microbiol. 2012;160(1–2):151–61.View ArticlePubMedGoogle Scholar
  3. Klitgaard K, Nielsen MW, Ingerslev HC, Boye M, Jensen TK. Discovery of bovine digital dermatitis- associated Treponema spp. in the dairy herd environment by a targeted deep- sequencing approach. Appl Environ Microbiol. 2014;80(14):4427–32.PubMed CentralView ArticlePubMedGoogle Scholar
  4. Klitgaard K, Breto AF, Boye M, Jensen TK. Targeting the treponemal microbiome of digital dermatitis infections by high-resolution phylogenetic analyses and comparison with fluorescent in situ hybridization. J Clin Microbiol. 2013;51(7):2212–9.PubMed CentralView ArticlePubMedGoogle Scholar
  5. Wilson-Welder JH, Elliott MK, Zuerner RL, Bayles DO, Alt DP, Stanton TP. Biochemical and molecular characterization of Treponema phagedenis-like spirochetes isolated from a bovine digital dermatitis lesion. BMC Microbiol. 2013;13:280.PubMed CentralView ArticlePubMedGoogle Scholar
  6. Choi BK, Nattermann H, Grund S, Haider W, Göbel UB. Spirochetes from digital dermatitis lesions in cattle are closely related to treponemes associated with human periodontitis. Int J Syst Bacteriol. 1997;47:175–81.View ArticlePubMedGoogle Scholar
  7. Evans NJ, Brown JM, Demirkan I, Singh P, Getty B, Timofte D, et al. Association of unique, isolated treponemes with bovine digital dermatitis lesions. J Clin Microbiol. 2009;47:689–96.PubMed CentralView ArticlePubMedGoogle Scholar
  8. Nordhoff M, Moter A, Schrank K, Wieler LH. High prevalence of treponemes in bovine digital dermatitis: a molecular epidemiology. Vet Microbiol. 2008;131:293–300.View ArticlePubMedGoogle Scholar
  9. Yano T, Moe KK, Yamazaki K, Ooka T, Hayashi T, Misawa N. Identification of candidate pathogens of papillomatous digital dermatitis in dairy cattle from quantitative 16S rRNA clonal analysis. Vet Microbiol. 2010;143:352–62.View ArticlePubMedGoogle Scholar
  10. Moter A, Leist G, Rudolph R, Schrank K, Choi BK, Wagner M, et al. Fluorescence in situ hybridization shows spatial distribution of as yet uncultured treponemes in biopsies from digital dermatitis lesions. Microbiology. 1998;144(Pt 9):2459–67.View ArticlePubMedGoogle Scholar
  11. Evans NJ, Brown JM, Demirkan I, Murray RD, Vink WD, Blowey RW, et al. Three unique groups of spirochetes isolated from digital dermatitis lesions in UK cattle. Vet Microbiol. 2008;130(1–2):141–50.View ArticlePubMedGoogle Scholar
  12. Trott DJ, Moeller MR, Zuerner RL, Goff JP, Waters WR, Alt DP, et al. Characterization of Treponema phagedenis-like spirochetes isolated from papillomatous digital dermatitis lesions in dairy cattle. J Clin Microbiol. 2003;41(6):2522–9.PubMed CentralView ArticlePubMedGoogle Scholar
  13. Yano T, Yamagami R, Misumi K, Kubota C, Moe KK, Hayashi T, et al. Genetic heterogeneity among strains of Treponema phagedenis-like spirochetes isolated from dairy cattle with papillomatous digital dermatitis in Japan. J Clin Microbiol. 2009;47:727–33.PubMed CentralView ArticlePubMedGoogle Scholar
  14. Pringle M, Bergsten C, Fernström LL, Höök H, Johansson KE. Isolation and characterization of Treponema phagedenis-like spirochetes from digital dermatitis lesions in Swedish dairy cattle. Acta Vet Scand. 2008;50:40.PubMed CentralView ArticlePubMedGoogle Scholar
  15. Altschul SF, Madden TL, Schäffer AA, Zhang J, Zhang Z, Miller W, et al. Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res. 1997;25:3389–402.PubMed CentralView ArticlePubMedGoogle Scholar
  16. Charon NW, Goldstein SF, Curci K, Limberger RJ. The Bent-End Morphology of Treponema phagedenis is Associated with Short, Left-Handed, Periplasmic Flagella. J Bacteriol. 1991;173(15):4820.PubMed CentralPubMedGoogle Scholar
  17. Rosander A, Guss B, Frykberg L, Björkman C, Näslund K, Pringle M. Identification of immunogenic proteins in Treponema phagedenis-like strain V1 from digital dermatitis lesions by phage display. Vet Microbiol. 2011;153(3–4):315–22.View ArticlePubMedGoogle Scholar
  18. Liolios K, Mavromatis K, Tavernarakis N, Kyrpides NC. The Genomes On Line Database (GOLD) in 2007: status of genomic and metagenomic projects and their associated metadata. Nucleic Acids Res. 2008;36:D475–9.PubMed CentralView ArticlePubMedGoogle Scholar
  19. Darling AE, Mau B, Perna NT, ProgressiveMauve. Multiple genome alignment with gene gain, loss and rearrangement. PLoS One. 2010;5, e11147.PubMed CentralView ArticlePubMedGoogle Scholar
  20. Boetzer M, Henkel CV, Jansen HJ, Butler D, Pirovano W. Scaffolding pre-assembled contigs using SSPACE. Bioinformatics. 2011;27(4):578–9.View ArticlePubMedGoogle Scholar
  21. Boetzer M, Pirovano W. Toward almost closed genomes with GapFiller. Genome Biol. 2012;13:56–64.View ArticleGoogle Scholar
  22. Gordon D. Viewing and editing assembled sequences using Consed. Curr Protoc Bioinformatics. 2003;11:11–2.Google Scholar
  23. Vallenet D, Engelen S, Mornico D, Cruveiller S, Fleury L, Lajus A, et al. MicroScope: a platform for microbial genome annotation and comparative genomics. Database (Oxford). 2009;2009:bap021.View ArticleGoogle Scholar
  24. Lowe TM, Eddy SR. tRNAscan-SE: a program for improved detection of transfer RNA genes in genomic sequence. Nucleic Acids Res. 1997;25:955–64.PubMed CentralView ArticlePubMedGoogle Scholar
  25. Lagesen K, Hallin P, Rødland EA, Staerfeldt HH, Rognes T, Ussery DW. RNAmmer: consistent and rapid annotation of ribosomal RNA genes. Nucleic Acids Res. 2007;35:3100–8.PubMed CentralView ArticlePubMedGoogle Scholar
  26. Zhou Y, Liang Y, Lynch K, Dennis JJ, Wishart DS. PHAST: a fast phage search tool”. Nucl Acids Res. 2011;39 suppl 2:W347–52.PubMed CentralView ArticlePubMedGoogle Scholar
  27. Petersen TN, Brunak S, von Heijne G, Nielsen H. SignalP 4.0: discriminating signal peptides from transmembrane regions. Nat Methods. 2011;8:785–6.View ArticlePubMedGoogle Scholar
  28. Krogh A, Larsson B, von Heijne G, Sonnhammer EL. Predicting transmembrane protein topology with a hidden Markov model: Application to Complete Genomes. J Mol Biol. 2001;305:567–80.View ArticlePubMedGoogle Scholar
  29. Fraser CM, Norris SJ, Weinstock GM, White O, Sutton GG, Dodson R, et al. Complete genome sequence of Treponema pallidum, the syphilis spirochete. Science. 1998;281(5375):375–88.View ArticlePubMedGoogle Scholar
  30. Seshadri R, Myers GS, Tettelin H, Eisen JA, Heidelberg JF, Dodson RJ, et al. Comparison of the genome of the oral pathogen Treponema denticola with other spirochete genomes. Proc Natl Acad Sci U S A. 2004;101(15):5646–51.PubMed CentralView ArticlePubMedGoogle Scholar
  31. Haake DA. Spirochaetal lipoproteins and pathogenesis. Microbiology. 2000;146:1491–504.PubMed CentralView ArticlePubMedGoogle Scholar
  32. Setubal JC, Reis M, Matsunaga J, Haake DA. Lipoprotein computational prediction in spirochaetal genomes. Microbiology. 2006;152:113–21.PubMed CentralView ArticlePubMedGoogle Scholar
  33. Field D, Garrity G, Gray T. The minimum information about a genome sequence (MIGS) specification. Nat Biotechnol. 2008;26:541–7.PubMed CentralView ArticlePubMedGoogle Scholar
  34. Woese CR, Kandler O, Wheelis ML. Towards a natural system of organisms: proposal for the domains Archaea, Bacteria, and Eucarya. Proc Natl Acad Sci U S A. 1990;87:4576–9 [PubMed].PubMed CentralView ArticlePubMedGoogle Scholar
  35. Garrity GM, Lilburn TG, Cole JR, Harrison SH, Euzeby J, Tindall BJ. Introduction to the taxonomic outline of bacteria and archaea (TOBA) Release 7.7. Taxon Outl Bact Archaea. 2007;7:1–5.Google Scholar
  36. Ludwig W, Euzeby J, Whitman WG. Draft taxonomic outline of the Bacteroidetes, Planctomycetes, Chlamydiae, Spirochaetes, Fibrobacteres, Fusobacteria, Acidobacteria, Verrucomicrobia, Dictyoglomi, and Gemmatimonadetes. http://www.bergeys.org/outlines/Bergeys_Vol_4_Outline.pdf. Taxonomic Outline 2008.
  37. Paster BJ, Dewhirst FE, Weisburg WG, Tordoff LA, Fraser GJ, Hespell RB, et al. Phylogenetic analysis of the spirochetes. J Bacteriol. 1991;173:6101–9.PubMed CentralPubMedGoogle Scholar
  38. Buchanan RE. Studies in the nomenclature and classification of the bacteria. J Bacteriol. 1918;3:541–5.PubMed CentralPubMedGoogle Scholar
  39. Paster BJ, Dewhirst FE. Phylogenetic foundation of spirochetes. J Mol Microbiol Biotechnol. 2000;2:341–4.PubMedGoogle Scholar
  40. Abt B, Han C, Lu M, Lapidus A, Nolan M, Lucas S, et al. Complete genome sequence of the termite hindgut bacterium Spirochaeta coccoides type strain (SPN1T), reclassification in the genus Sphaerochaeta as Sphaerochaeta coccoides comb. nov. and emendations of the family Spirochaetaceae and the genus Sphaerochaeta. Stand Genomic Sci. 2012;6:194–209.PubMed CentralView ArticlePubMedGoogle Scholar
  41. Norris SJ, Paster BJ, Smibert RM. Genus IV. Treponema. In: Krieg NR, Staley JT, Brown DR, Hedlund BP, Paster BJ, Ward NL, Ludwig W, Whitman WB, editors. Bergey's Manual of Systematic Bacteriology. Volume 4, vol. 4. 2nd ed. New York: Springer; 2011. p. 501–31.Google Scholar
  42. Larkin MA, Blackshields G, Brown NP, Chenna R, McGettigan PA, McWilliam H, et al. Clustal W and Clustal X version 2.0. Bioinformatics. 2007;23:2947–8.View ArticlePubMedGoogle Scholar
  43. Castresana J. Selection of conserved blocks from multiple alignments for their use in phylogenetic analysis. Mol Biol Evol. 2000;17:540–52.View ArticlePubMedGoogle Scholar
  44. Tamura K, Stecher G, Peterson D, Filipski A, Kumar S, MEGA6. Molecular evolutionary genetics analysis version 6.0. Mol Biol and Evol. 2013;30:2725–9.View ArticleGoogle Scholar

Copyright

© Mushtaq et al. 2015