Open Access

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

  • Birte Abt
  • , Cliff Han,
  • , Carmen Scheuner
  • , Megan Lu,
  • , 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
  • , Marcel Huntemann
  • , Amrita Pati
  • , Amy Chen
  • , Krishna Palaniappan
  • , Miriam Land,
  • , Loren Hauser,
  • , Evelyne-Marie Brambilla
  • , Manfred Rohde
  • , Stefan Spring
  • , Sabine Gronow
  • , Markus Göker
  • , Tanja Woyke
  • , James Bristow
  • , Jonathan A. Eisen,
  • , Victor Markowitz
  • , Philip Hugenholtz,
  • , Nikos C. Kyrpides
  • , Hans-Peter Klenk
  • and John C. Detter,
Corresponding author

DOI: 10.4056/sigs.2796069

Received: 04 May 2012

Published: 25 May 2012

Abstract

Spirochaeta coccoides Dröge et al. 2006 is a member of the genus Spirochaeta Ehrenberg 1835, one of the oldest named genera within the Bacteria. S. coccoides is an obligately anaerobic, Gram-negative, non-motile, spherical bacterium that was isolated from the hindgut contents of the termite Neotermes castaneus. The species is of interest because it may play an important role in the digestion of breakdown products from cellulose and hemicellulose in the termite gut. Here we provide a taxonomic re-evaluation for strain SPN1T, and based on physiological and genomic characteristics, we propose its reclassification as a novel species in the genus Sphaerochaeta, a recently published sister group of the Spirochaeta. The 2,227,296 bp long genome of strain SPN1T with its 1,866 protein-coding and 58 RNA genes is a part of the Genomic Encyclopedia of Bacteria and Archaea project.

Keywords:

obligately anaerobicnon-motiletermite hindgutGram-negativedi- and oligosaccharide-degradingmesophilicchemoorganotrophicSpirochaetaceaeSphaerochaetaGEBA

Introduction

Strain SPN1T (= DSM 17374 = ATCC BAA-1237) is the type strain of Spirochaeta coccoides and was isolated from the hindgut contents of the lower dry-wood termite Neotermes castaneus [1,2]. The genus Spirochaeta currently consists of 19 validly named species [3]. The genus name was derived from the Latinized Greek words speira, 'a coil' and chaitê, 'hair', yielding the Neo-Latin 'Spirochaeta', the coiled hair [3]. The species epithet was derived from the neo-Greek words coccos, 'a berry' and eidos, meaning 'shape', yielding the Neo-Latin word coccoides, meaning berry-shaped [1]. Based on the nucleotide sequence of the 16S rRNA gene strain SPN1T was assigned to the genus Spirochaeta, although its coccoid, non-motile cells differ from the morphology of all known validly named spirochetes [1]. Recently, Ritalahti et al. proposed that Spirochaeta sp. Buddy and Spirochaeta sp. Grapes belonged to the novel genus Sphaerochaeta based on their unique morphology and the 16S rRNA sequence similarity to their closest relatives. The two spherical isolates Spirochaeta sp. Buddy and Spirochaeta sp. Grapes were named Sphaerochaeta globosa and Sphaerochaeta pleomorpha, respectively [4]. On the basis of its morphological, physiological and genomic characteristics, S. coccoides is more closely related to Sphaerochaeta than to the remaining Spirochaeta species, and we therefore propose the placement of S. coccoides SPN1T into the genus Sphaerochaeta. Here we thus present a summary classification and a set of features for S. coccoides SPN1T, a description of the complete genome sequencing and annotation, and a proposal to reclassify S. coccoides as a member of the genus Sphaerochaeta as Sphaerochaeta coccoides comb. nov.

Classification and features

A representative genomic 16S rRNA sequence of strain SPN1T was compared using NCBI BLAST [5,6] under default settings (e.g., considering only the high-scoring segment pairs (HSPs) from the best 250 hits) with the most recent release of the Greengenes database [7] and the relative frequencies of taxa and keywords (reduced to their stem [8]) were determined, weighted by BLAST scores. The most frequently occurring genera were Spirochaeta (57.6%), Sphaerochaeta (39.7%) and Cytophaga (2.7%) (22 hits in total). Regarding the six hits to sequences from other members of the genus, the average identity within HSPs was 90.2%, whereas the average coverage by HSPs was 30.9%. Among all other species, the one yielding the highest score was Spirochaeta bajacaliforniensis (AJ698859), which corresponded to an identity of 90.3% and an HSP coverage of 32.6%. (Note that the Greengenes database uses the INSDC (= EMBL/NCBI/DDBJ) annotation, which is not an authoritative source for nomenclature or classification.) The highest-scoring environmental sequence was AY570600 ('biodegraded Canadian oil reservoir clone PL-16B9'), which showed an identity of 91.0% and an HSP coverage of 85.9%. The most frequently occurring keywords within the labels of all environmental samples which yielded hits were 'microbi' (6.5%), 'mat' (4.5%), 'hypersalin' (3.1%), 'termit' (2.8%) and 'hindgut' (2.6%) (228 hits in total). Environmental samples which yielded hits of a higher score than the highest scoring species were not found. The keywords are partially in agreement with the known environmental preferences of S. coccoides SPN1T, but the results also indicate that the species itself is rarely found in environmental probes.

Figure 1 shows the phylogenetic neighborhood of S. coccoides in a 16S rRNA based tree. The sequences of the three 16S rRNA gene copies in the genome differ from each other by up to two nucleotides, and differ by up to two nucleotides from the previously published 16S rRNA sequence (AJ698092).

Figure 1

Phylogenetic tree highlighting the position of S. coccoides relative to the other type strains within the family Spirochaetaceae. The tree was inferred from 1,360 aligned characters [9,10] of the 16S rRNA gene sequence under the maximum likelihood criterion [11]. Rooting was done initially using the midpoint method [12] and then checked for its agreement with the current classification (Table 1). The branches are scaled in terms of the expected number of substitutions per site. Numbers adjacent to the branches are support values from 500 ML bootstrap replicates [13] (left) and from 1,000 maximum parsimony bootstrap replicates [14] (right) if larger than 60% if. Lineages with type strain genome sequencing projects registered in GOLD [15] are labeled with one asterisk, those also listed as 'Complete and Published' with two asterisks (see [16-19], CP002696 for Treponema brennaborense, CP002903 for S. thermophila, and CP002868 for S. caldaria). Also, genomes that are finished but are missing a second asterisk are S. africana CP003282, S. pleomorpha CP003155 and S. globosa CP002541.

In contrast to all other validly described spirochete species (except for those currently placed in the novel genus Sphaerochaeta [4]) the cells of S. coccoides SPN1T are cocci (0.5 to 2.0 µm in diameter) which are surrounded by an outer envelope. In the early growth phase cell aggregates are formed [1]. S. coccoides is a Gram-negative, non-motile and strictly anaerobic bacterium (Table 1). Strain SPN1T showed no catalase activity [1], although a gene probably coding a catalase (Spico_0266) was identified in the genome. The optimal growth temperature of strain SPN1T is 30°C, with no growth observed above 40°C or below 15°C [1]. The pH range for growth is 5.5-9.5, with an optimum at pH 7.4 [1]. Maltose is fermented to ethanol, with formate and acetate as the main fermentation products. Glucose, galactose, lactate, pyruvate, amino acids, and polysaccharides are not utilized, but the organism is able to grow with yeast extract as the sole carbon and energy source [1]. A minimum yeast concentration of 0.2% was required for growth [1]. Activities of β-D-glucosidase, α-D-glucosidase, α-D-galactosidase, α-L-arabinosidase, β-D-fucosidase, and β-D-xylosidase are exhibited [1]. These enzymatic activities seemed to be cell-bound, as no glycolytic activity was found in the supernatant of the culture [1].

Table 1

Classification and general features of S. coccoides SPN1T according to the MIGS recommendations [20] and the NamesforLife database [21].

MIGS ID

      Property

      Term

    Evidence code

      Current classification

      Domain Bacteria

    TAS [22]

      Phylum Spirochaetae

    TAS [23,24]

      Class Spirochaetes

    TAS [24,25]

      Order Spirochaetales

    TAS [26,27]

      Family Spirochaetaceae

    TAS [26,28]

      Genus Spirochaeta

    TAS [26,29-31]

      Species Spirochaeta coccoides

    TAS [1,2]

      Type strain SPN1

    TAS [1,2]

      Gram stain

      negative

    TAS [1]

      Cell shape

      coccoid

    TAS [1]

      Motility

      Non-motile

    TAS [1]

      Sporulation

      none

    TAS [1]

      Temperature range

      mesophile

    TAS [1]

      Optimum temperature

      30°C

    TAS [1]

      Salinity

      not reported

MIGS-22

      Oxygen requirement

      obligately anaerobic

    TAS [1]

      Carbon source

      pentoses (arabinose, xylose), oligosaccharides (maltose, cellobiose, maltotriose, maltotetraose),       yeast extract

    TAS [1]

      Energy metabolism

      chemoorganotroph

    TAS [1]

MIGS-6

      Habitat

      digestive tract of lower dry-wood termites

    TAS [1]

MIGS-15

      Biotic relationship

      host associated commensal

    TAS [1]

MIGS-14

      Pathogenicity

      none

    TAS [1]

      Biosafety level

      1

    TAS [32]

      Isolation

      hindgut of Neotermes castaneus

    TAS [1]

MIGS-4

      Geographic location

      not reported

MIGS-5

      Sample collection time

      2005 or before

    TAS [1]

MIGS-4.1

      Latitude

      not reported

MIGS-4.2

      Longitude

      not reported

MIGS-4.3

      Depth

      not reported

MIGS-4.4

      Altitude

      not reported

a) Evidence codes - 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 [27]. If the evidence code is IDA, then the property should have been directly observed, for the purpose of this specific publication, for a live isolate by one of the authors, or an expert or reputable institution mentioned in the acknowledgements.

Genome project history

This organism was selected for sequencing on the basis of its phylogenetic position [34], and is part of the Genomic Encyclopedia of Bacteria and Archaea project [35]. The genome project is deposited in the Genomes On Line Database [15] 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 (8.9 kb insert size), one Illumina library

MIGS-29

    Sequencing platforms

      Illumina GAii, 454 GS FLX Titanium

MIGS-31.2

    Sequencing coverage

      960.0 × Illumina; 40.0 × pyrosequence

MIGS-30

    Assemblers

      Newbler version 2.3, Velvet version 0.7.63, phrap version SPS - 4.24

MIGS-32

    Gene calling method

      Prodigal 1.4, GenePRIMP

    INSDC ID

      CP002659

    Genbank Date of Release

      April 27, 2011

    GOLD ID

      Gc01739

    NCBI project ID

      48121

    Database: IMG-GEBA

      2503904012

MIGS-13

    Source material identifier

      DSM 17374

    Project relevance

      Tree of Life, GEBA

Growth conditions and DNA isolation

S. coccoides strain SPN1T, DSM 17374, was grown anaerobically in DSMZ medium 1204 (Spirochaeta coccoides medium) [36] at 30°C. DNA was isolated from 0.5-1 g of cell paste using 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. 2009 [35]. DNA is available through the DNA Bank Network [37].

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 [38]. Pyrosequencing reads were assembled using the Newbler assembler (Roche). The initial Newbler assembly consisting of 97 contigs in one scaffold was converted into a phrap [39] assembly by making fake reads from the consensus, to collect the read pairs in the 454 paired end library. Illumina GAii sequencing data (2,245.3 Mb) was assembled with Velvet [40] and the consensus sequences were shredded into 2.0 kb overlapped fake reads and assembled together with the 454 data. The 454 draft assembly was based on 142.5 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 [39] 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 [38], Dupfinisher [41], or sequencing cloned bridging PCR fragments with subcloning. Gaps between contigs were closed by editing in Consed, by PCR and by Bubble PCR primer walks (J.-F. Chang, unpublished). A total of 308 additional reactions were necessary to close 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 [42]. 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 1,000.0 × coverage of the genome. The final assembly contained 137,682 pyrosequence and 58,694,953 Illumina reads.

Genome annotation

Genes were identified using Prodigal [43] as part of the Oak Ridge National Laboratory genome annotation pipeline, followed by a round of manual curation using the JGI GenePRIMP pipeline [44]. 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 [45].

Genome properties

The genome consists of a 2,227,296 bp long chromosome with a G+C content of 50.6% (Table 3 and Figure 2). Of the 1,924 genes predicted, 1,866 were protein-coding genes, and 58 RNAs; 44 pseudogenes were also identified. The majority of the protein-coding genes (74.6%) 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)

2,227,296

100.00%

DNA coding region (bp)

2,003,786

89.96%

DNA G+C content (bp)

1,126,077

50.56%

Number of replicons

1

Extrachromosomal elements

0

Total genes

1,924

100.00%

RNA genes

58

3.01%

rRNA operons

3

Protein-coding genes

1,866

96.99%

Pseudo genes

44

2.29%

Genes with function prediction

1,434

74.53%

Genes in paralog clusters

733

38.10%

Genes assigned to COGs

1,528

76.72%

Genes assigned Pfam domains

1,518

78.90%

Genes with signal peptides

314

16.32%

Genes with transmembrane helices

524

27.23%

CRISPR repeats

4

Figure 2

Graphical 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

    143

   8.5

       Translation, ribosomal structure and biogenesis

A

    0

   0.0

       RNA processing and modification

K

    118

   7.0

       Transcription

L

    99

   5.9

       Replication, recombination and repair

B

    0

   0.0

       Chromatin structure and dynamics

D

    58

   3.5

       Cell cycle control, cell division, chromosome partitioning

Y

    0

   0.0

       Nuclear structure

V

    25

   1.5

       Defense mechanisms

T

    59

   3.5

       Signal transduction mechanisms

M

    46

   2.7

       Cell wall/membrane/envelope biogenesis

N

    2

   0.1

       Cell motility

Z

    39

   2.4

       Cytoskeleton

W

    0

   0.0

       Extracellular structures

U

    19

   1.1

       Intracellular trafficking, secretion, and vesicular transport

O

    54

   3.2

       Posttranslational modification, protein turnover, chaperones

C

    77

   4.6

       Energy production and conversion

G

    260

   15.5

       Carbohydrate transport and metabolism

E

    160

   9.5

       Amino acid transport and metabolism

F

    58

   3.6

       Nucleotide transport and metabolism

H

    42

   2.5

       Coenzyme transport and metabolism

I

    44

   2.6

       Lipid transport and metabolism

P

    58

   3.6

       Inorganic ion transport and metabolism

Q

    15

   0.9

       Secondary metabolites biosynthesis, transport and catabolism

R

    193

   11.5

       General function prediction only

S

    109

   6.5

       Function unknown

-

    396

   20.6

       Not in COGs

Insights from the genome sequence, and taxonomic conclusions for S. coccoides

Taxonomic interpretation for S. coccoides and neighboring species in the family Spirochaetaceae according to 16S rRNA data

Based on its 16S rRNA sequence strain SPN1T was placed into the genus Spirochaeta [1], although it lacks the typical spiral morphology and is non-motile. SPN1T showed highest similarity in 16S rRNA gene sequences to Spirochaeta sp. strain Buddy and Spirochaeta sp. strain Grapes [1], two spherical isolates that were not formally named at that time, but preliminarily named 'free-living pleomorphic spirochaetes' [4]. Recently, these isolates were placed into the novel genus Sphaerochaeta, and validly published as S. globosa and S. pleomorpha, respectively [4].

The phylogenetic tree shown in Figure 1 demonstrates that the current classification of the group suffers from a non-homogenous location of species featured as members of the genus Spirochaeta. Not only is Borrelia placed within Spirochaeta (without much branch support), but S. coccoides also appears as the sister group of Sphaerochaeta with maximum support. Support for a placement of S. caldaria, S. stenostrepta and S. zuelzerae more closely to Treponema than to the other Spirochaeta species (a topological arrangement that was observed earlier [46]) is also high and could only be considered a matter of rooting for the former two species (but note that the rooting is confirmed by a phylogenomic analysis described below and see the tree topology of the entire order Spirochaetales in [46,47]).

To measure phylogenetic conflict caused by the taxonomic classification in detail, we conducted both unconstrained heuristic searches for the best tree under the maximum likelihood (ML) [11] and maximum parsimony (MP) criterion [14] as well as searches constrained for the monophyly of all genera (for details of the data matrix see the caption of Figure 1). Our own re-implementation of CopyCat [48] in conjunction with AxPcoords and AxParafit [49] was used to determine those leaves (species) whose placement significantly deviated between the constrained and the unconstrained tree. AxParafit was applied to the ML trees with 1,000 rounds of random permutations of the associations.

The ParaFit test was originally introduced for comparing host and parasite phylogenies [50], but can be applied to the comparison of all kinds of trees. In contrast to other measures for the comparison of trees, it includes a statistical test for whether individual leaves significantly contribute to the agreement between two trees (a p-value indicates how likely it is that this contribution is no more than random). All other leaves apparently cause more conflict than agreement [50]. The rationale of comparing unconstrained trees with constrained trees inferred from the very same data is that the constraint might be in conflict with the original tree. In addition to assessing whether the trees are overall significantly different according to the data and a given optimality criterion in a paired-site test (see, e.g. chapter 21 in [51] for an in-depth description of such tests), the ParaFit test is a straightforward extension for assessing which leaves of the trees cause the conflict, if any.

The best-known ML tree had a log likelihood of -16,001.40, whereas the best tree found under the constraint had a log likelihood of -16,322.98. The constrained tree was significantly worse than the globally best one in the Shimodaira-Hasegawa test as implemented in RAxML [11] (α = 0.01). The best-known MP trees had a score of 3,105, whereas the best constrained trees found had a score of 3,260 and were significantly worse in the Kishino-Hasegawa test as implemented in PAUP* [14] (α < 0.0001). Accordingly, the current classification of the family as used by [3,46,47] is in significant conflict with the 16S rRNA data. Such discrepancies are not surprising in this group because many of the included taxa were described before 16S rRNA analysis could be applied [23,25,46], with Spirochaetaceae dating back to 1907 [28] and Spirochaeta even to 1835 [31]. Still uncultivated species and genera of Spirochaetales are described based on morphology alone, without depositing 16S rRNA sequences [52]. Table 5 shows the ParaFit test results obtained by comparing the unconstrained tree and the one obtained with the genus-based constraint. The largest conflict is caused by Spirochaeta aurantia, probably because of its placement close to Borrelia, followed by Sphaerochaeta and then by the other members of the main Spirochaeta group.

Table 5

Result (p-values) from the test of individual links with ParaFit

Species

   p-value, constraint 1

    p-value, constraint 2

Spirochaeta aurantia (M57740)

   0.2882

    0.0038

Sphaerochaeta globosa (AF357916)

   0.2844

    0.0230

Sphaerochaeta pleomorpha (AF357917)

   0.2754

    0.0201

Spirochaeta cellobiosiphila (EU448140)

   0.2076

    0.0080

Spirochaeta americana (AF373921)

   0.2001

    0.0149

Spirochaeta alkalica (X93927)

   0.1905

    0.0145

Spirochaeta asiatica (X93926)

   0.1830

    0.0280

Spirochaeta halophila (M88722)

   0.1806

    0.0124

Spirochaeta bajacaliforniensis (AJ698859)

   0.1765

    0.0490

Spirochaeta dissipatitropha (AY995150)

   0.1749

    0.0278

Spirochaeta africana (X93928)

   0.1656

    0.0241

Spirochaeta isovalerica (M88720)

   0.1654

    0.0039

Spirochaeta smaragdinae (U80597)

   0.1592

    0.0454

Spirochaeta thermophila (FR749903)

   0.1384

    0.0539

Spirochaeta litoralis (FR733665)

   0.1327

    0.0025

Spirochaeta coccoides (IMG2503956950)

   0.0863

    0.0217

Spirochaeta perfilievii (AY337318)

   0.0716

    0.0010

Result (p-values) from the test of individual links with ParaFit for the species with an insignificant result (α = 0.05) in the first approach. The comparison was done between an unconstrained ML tree and the first, genus-based constraint (second column) or the second constraint, based on a revised classification of the group (third column). Note that with a single exception the phylogenetic conflict was resolved by assigning S. coccoides to Sphaerochaeta [4] and three other Spirochaeta species to Treponema [46].

To assess whether placing S. coccoides in Sphaerochaeta [4] and the other three Spirochaeta species that cause conflict in Treponema [46] would solve the problem, an according second constraint was created and used in phylogenetic analysis. The resulting ML tree had a log likelihood of -16,025.93 and was significantly worse than the best-known ML tree only for α = 0.05. The MP trees inferred under the second constraint had a score of 3,123 and were not significantly worse than the best-known MP trees. Table 5 also shows the ParaFit test results obtained by comparing the unconstrained tree and the one obtained with the second constraint. Apparently the conflict is largely resolved; the only remaining p-value above 0.05 is the one for S. thermophilus, which is nevertheless only slightly above the chosen α-value (0.0539) and might become significant if more organisms were included [50].

Phylogenomic analyses

According to the results from 16S rRNA analysis and the whole-genome phylogenies described below, for a comparative analysis the genome sequences of S. globosa (GenBank CP002541) and S. pleomorpha (CP003155) [4], as well as the sequences of S. smaragdinae (GenBank CP002659) were used.

The genomes of the sequenced Spirochaeta and Sphaerochaeta species differ significantly in their size. The genome of S. coccoides (2.2 Mb, 1,866 protein-coding genes, G+C content 51 mol%) is the smallest in size. The genomes of S. pleomorpha (3.6 Mb, 3,216 protein coding genes, G+C content 46 mol%), and S. globosa (3.3 Mb, 3,057 protein-coding genes, G+C content 49 mol%) are bigger in size and the genome of S. smaragdinae counts 4.7 Mb with 4,306 protein-coding genes and a G+C content of 49 mol%.

An estimate of the overall similarity between S. coccoides, with both Sphaerochaeta species and S. smaragdinae was generated with the GGDC-Genome-to-Genome Distance Calculator [53,54]. This system calculates the distances by comparing the genomes to obtain HSPs (high-scoring segment pairs) and inferring distances from the set of formulas (1, HSP length / total length; 2, identities / HSP length; 3, identities / total length). Table 6 shows the results of the pairwise comparison.

Table 6

Pairwise comparison of S. coccoides with both Sphaerochaeta species and S. smaragdinae using the GGDC-Genome-to-Genome Distance Calculator.

   HSP length /   total length [%]

  identities /  HSP length [%]

    identities /    total length [%]

Spirochaeta coccoides

Sphaerochaeta globosa

   4.5

  83.2

    3.7

Spirochaeta coccoides

Sphaerochaeta pleomorpha

   3.9

  83.3

    3.3

Spirochaeta coccoides

Spirochaeta smaragdinae

   1.2

  84.6

    1.0

Sphaerochaeta globosa

Sphaerochaeta pleomorpha

   14.2

  82.0

    11.7

Sphaerochaeta globosa

Spirochaeta smaragdinae

   1.3

  84.6

    1.1

The comparison of S. coccoides with both Sphaerochaeta species revealed the highest scores using the GGDC. The comparison of S. coccoides with S. globosa and S. pleomorpha revealed that 4.5% and 3.9% of the average of genome length are covered with HSPs. The identity within the HSPs was 83.2% and 83.3%, respectively, whereas the identity over the whole genome was 3.7% and 3.3%, respectively. Lower similarity scores were observed in the comparison of S. coccoides with S. smaragdinae: only 1.2% of the average of either of the genome lengths are covered with HSPs. The identity within these HSPs was 84.6%, whereas the identity over the whole genome was only 1.0%.

As expected, those distances relating HSP coverage (formula 1) and number of identical base pairs within HSPs to total genome length (formula 3) are higher between the S. coccoides and the Sphaerochaeta species than between S. coccoides and S. smaragdinae. That the distances relating the number of identical base pairs to total HSP length (formula 2) are different indicates that the genomic similarities between S. coccoides and S. smaragdinae are strongly restricted to more conserved sequences, a kind of saturation phenomenon [54].

For conducting phylogenomic analyses of the group, amino-acid sequences from 16 Spirochaetaceae and outgroup (other Spirochaeta families) completed type-strain genomes were retrieved from INSDC and investigated as described in [55] with minor modifications. Orthologs were determined with parallel genome-against-genome protein NCBI BLAST version 2.2.17 [56] and our own re-implementation of the OrthoMCL algorithm [57] in conjunction with MCL version 08-312 [58,59] with the OrthoMCL default parameters (an e-value threshold of 10-5 and 2.0 as inflation parameter). OrthoMCL clusters containing inparalogs [57] were reduced as previously described [55] and aligned using MUSCLE version 3.7 under default settings [60]. The resulting alignments were filtered using RASCAL version 1.3.4 [61] and GBLOCKS version 0.91b [9] as in our earlier study [55]. Filtered alignments comprising at least four sequences were concatenated to form a supermatrix. As an extension of the approach in [55], the supermatrix was cleaned from relatively uninformative genes using MARE [62] under default values (except that deleting taxa was disallowed). Maximum-likelihood trees were inferred with RAxML [11] version 7.28 in conjunction with rapid bootstrapping and the bootstopping criterion [13] with subsequent search for the best tree. The best amino acid substitution model was determined beforehand by comparing the resulting log likelihoods on a maximum-parsimony starting tree. Maximum-parsimony tree search was conducted with PAUP* version 4b10 [14] as previously described [55].

In addition to the supermatrix analysis, homologous sequences were determined using our own re-implementation of the TribeMCL algorithm [63] in conjunction with MCL [58,59], applying an e-value threshold of 10-5 and an inflation parameter of 2.0. A gene-content (presence/absence) matrix was constructed, representing the occurrence of a gene of one genome within a cluster of homologs. Phylogenetic inference was done with the BINGAMMA model in RAxML and under maximum parsimony with PAUP*, other settings being as described above.

The supermatrix comprised 2,408 genes and 696,696 characters before, 522 genes and 140,413 characters after cleaning with MARE. The selected model was PROTGAMMALGF; the resulting tree had a log likelihood of -2,172,190.75 and is shown in Figure 3. The best maximum-parsimony tree found had a length of 346,334 steps (not counting uninformative characters) and was topologically identical. The gene-content matrix comprised 11,131 characters and yielded a best tree with a log likelihood of -61,799.49 and a parsimony score of 10,229, respectively. Bootstrapping support values from all four methods applied are shown in Figure 3 if larger then 60%.

Figure 3

Phylogenetic tree inferred from completely sequenced genomes of the Spirochaeta type strains. The tree was inferred from 140,413 aligned amino acid characters under the maximum likelihood (ML) criterion and rooted with Leptospira. The branches are scaled in terms of the expected number of substitutions per site. Numbers above the branches are bootstrapping support values (if larger than 60%) from (i) maximum-likelihood supermatrix analysis; (ii) maximum-parsimony supermatrix analysis; (iii) maximum-likelihood gene-content analysis; (iv) maximum-parsimony gene-content analysis. INSDC accession numbers are given in square brackets. Note that the placement of Borrelia is probably caused by long-branch attraction. For further details see the text.

The sister-group relationship of S. coccoides and Sphaerochaeta was unanimously supported by all methods, much like the placement of S. caldaria within Treponema. The trees differed however, regarding the support for the placement of Borrelia as sister group to all other ingroup taxa. For this reason, we assessed via long-branch extraction [64] whether this positioning could be caused by long-branch attraction [51] between Borrelia and the outgroup. Removal of Borrelia and subsequent phylogenetic inference yielded a maximum-parsimony tree with the same topology that would have been obtained by pruning Borrelia from the tree depicted in Figure 3. Removal of the outgroup from the alignment, however, yielded a maximum-parsimony tree in which Borrelia was placed as sister group of S. thermophila, supporting the long-branch attraction hypothesis (data not shown).

The phylogenomic analysis thus confirms the 16S rRNA tree (Figure 1) regarding the paraphyly of Spirochaeta but, of course, based on much more characters. A first step to resolve this taxonomic problem is to assign S. coccoides to the genus Sphaerochaeta. Given that S. caldaria and some other species are situated within Treponema [46], and that Borrelia probably is placed within the remaining Spirochaeta species, further taxonomic changes will probably be necessary in the future. But apparently in addition to sampling more characters (by replacing 16S rRNA with genome sequences) sampling more taxa (by obtaining whole genomes from more type strains) might by necessary to obtain a natural classification of the spirochetes.

Phenotypic data and taxonomic interpretation

Table 7 gives an overview of some morphological and physiological features of S. coccoides compared with the genus descriptions of Sphaerochaeta and Spirochaeta. The coccoid cell morphology, the cell size, the lack of motility as well as the products of fermentation support the reclassification of S. coccoides as a member of the genus Sphaerochaeta. S. coccoides is so close to the original description of the genus Sphaerochaeta that only its reported GC content needs to be modified.

Table 7

Typical features of reference taxa.

    Spirochaeta coccoides [1]

   Genus Sphaerochaeta [4]

    Genus Spirochaeta [30]

Cell shape

    coccoid, spherical, not spiral

   coccoid, spherical, pleomorphic; not helical or spiral

    helical or spiral; spherical bodies under unfavorable growth conditions

Cell size

    0.5-2.0 µm

   0.4-2.5 µm

    0.2-0.75 by 5-250 µm

Motility

    non-motile

   non-motile

    motile

Flagellation

    no flagella

   no flagella

    2 periplasmic flagella (exception: S. plicatilis, with many flagella)

T-optimum

    30 °C

   mesophilic

    25-68 °C

pH-optimum

    7.4

   neutrophilic

Oxygen requirement

    anaerobe

   anaerobe

    obligately anaerobe or facultatively anaerobe

Fermentation products

    acetate, ethanol, formate

   acetate, ethanol, formate

    acetate, ethanol, CO2, H2

G+C content

    56.6-57.4 mol% [1]    51 mol%, this study

   45-48 mol%

    51-65 mol% [30]    44-65 mol% [29]

On the basis of the above mentioned physiological and phylogenetic characteristics of strain SPN1T, its reclassification into the genus Sphaerochaeta is proposed. The inclusion of Sphaerochaeta in Spirochaetaceae also makes an emendation of the family necessary, as its previous description excludes features specifically found in Sphaerochaeta.

Emended description of the family Spirochaetaceae Swellengrebel 1907 (Spirochaetaceae Swellengrebel 1907 emend. Abt, Göker, Kyprides and Klenk)

The description of the family Spirochaetaceae is given by Swellengrebel 1907 [26,28]. Some species form coccoid cells, have no flagella and are not motile. Some do not have L-ornithine in the peptidoglycan.

Emended description of the genus Sphaerochaeta (Sphaerochaeta Ritalahti et al. 2012 emend. Abt, Göker, Kyprides and Klenk)

The description of the genus Sphaerochaeta is as that given by Ritalahti et al. 2012 [4], with the following modification: DNA G+C content is 45-51 mol%.

Description of Sphaerochaeta coccoides (Dröge et al. 2006) Abt, Göker, Kyrpides and Klenk, comb. nov.

Basonym: Spirochaeta coccoides Dröge et al. 2006.

The characteristics of the species are given in the species description by Dröge et al. 2006 [1]. The type strain is SPN1T (= DSM 17374 = ATCC BAA-1237).

Declarations

Acknowledgements

We would like to gratefully acknowledge the help of Sabine Welnitz (DSMZ) for growing S. coccoides 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.

References

  1. Dröge S, Fröhlich J, Radek R and König H. Spirochaeta coccoides sp. nov., a novel coccoid spirochete from the hindgut of the termite Neotermes castaneus. Appl Environ Microbiol. 2006; 72:392-397 View ArticlePubMed
  2. Validation List No 110. Int J Syst Evol Microbiol. 2006; 56:1459-1460 View ArticlePubMed
  3. Euzéby JP. List of bacterial names with standing in nomenclature: A folder available on the Internet. Int J Syst Bacteriol. 1997; 47:590-592 View ArticlePubMed
  4. Ritalahti KM, Justicia-Leon SD, Cusick KD, Ramos-Hernandez N, Rubin M, Dornbush J and Löffler FE. Sphaerochaeta globosa gen. nov., sp. nov. and Sphaerochaeta pleomorpha sp. nov., free-living, spherical spirochaetes. Int J Syst Evol Microbiol. 2012; 62:210-216 View ArticlePubMed
  5. Altschul SF, Gish W, Miller W, Myers EW and Lipman DJ. Basic local alignment search tool. J Mol Biol. 1990; 215:403-410PubMed
  6. Korf I, Yandell M, Bedell J. BLAST, O'Reilly, Sebastopol, 2003
  7. 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
  8. Porter MF. An algorithm for suffix stripping. Program: electronic library and information systems 1980; 14:130-137.
  9. Castresana J. Selection of conserved blocks from multiple alignments for their use in phylogenetic analysis. Mol Biol Evol. 2000; 17:540-552 View ArticlePubMed
  10. Lee C, Grasso C and Sharlow MF. Multiple sequence alignment using partial order graphs. Bioinformatics. 2002; 18:452-464 View ArticlePubMed
  11. Stamatakis A, Hoover P and Rougemont J. A rapid bootstrap algorithm for the RAxML Web servers. Syst Biol. 2008; 57:758-771 View ArticlePubMed
  12. Hess PN and De Moraes Russo CA. An empirical test of the midpoint rooting method. Biol J Linn Soc Lond. 2007; 92:669-674 View Article
  13. 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
  14. Swofford DL. PAUP*: Phylogenetic Analysis Using Parsimony (*and Other Methods), Version 4.0 b10. Sinauer Associates, Sunderland, 2002.
  15. Pagani I, Liolios K, Jansson J, Chen IM, Smirnova T, Nosrat B, Markowitz VM and Kyrpides NC. The Genomes OnLine Database (GOLD) v.4: status of genomic and metagenomic projects and their associated metadata. Nucleic Acids Res. 2012; 40:D571-D579 View ArticlePubMed
  16. Seshadri R, Myers GS, Tettelin H, Eisen JA, Heidelberg JF, Dodson RJ, Davidsen TM, DeBoy RT, Fouts DE and Haft DH. Comparison of the genome of the oral pathogen Treponema denticola with other spirochete genomes. Proc Natl Acad Sci USA. 2004; 101:5646-5651 View ArticlePubMed
  17. Han C, Gronow S, Teshima H, Lapidus A, Nolan M, Lucas S, Hammon N, Deshpande S, Cheng JF and Zeytun A. Complete genome sequence of Treponema succinifaciens type strain (6091T). Stand Genomic Sci. 2011; 4:361-370 View ArticlePubMed
  18. Rosenthal AZ, Matson EG, Eldar A and Leadbetter JR. RNA-seq reveals cooperative metabolic interactions between two termite-gut spirochaete species in co-culture. ISME J. 2011; (In press). View ArticlePubMed
  19. Mavromatis K, Yasawong M, Chertkov O, Lapidus A, Lucas S, Nolan M, Glavina Del Rio T, Tice H, Cheng JF and Pitluck S. Complete genome sequence of Spirochaeta smaragdinae type strain (SEBR4228T). Stand Genomic Sci. 2010; 3:136-144PubMed
  20. 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
  21. Garrity G. NamesforLife. BrowserTool takes expertise out of the database and puts it right in the browser. Microbiol Today. 2010; 37:9
  22. 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
  23. Garrity G, Holt JG. Phylum B17 Spirochaetes phy. nov. Garrity and Holt. In: Garrity GM, Boone DR, Castenholz RW (eds), Bergey's Manual of Systematic Bacteriology, Second Edition, Volume 1, Springer, New York, 2001, p. 138.
  24. . The nomenclatural types of the orders Acholeplasmatales, Halanaerobiales, Halobacteriales, Methanobacteriales, Methanococcales, Methanomicrobiales, Planctomycetales, Prochlorales, Sulfolobales, Thermococcales, Thermoproteales and Verrucomicrobiales are the genera Acholeplasma, Halanaerobium, Halobacterium, Methanobacterium, Methanococcus, Methanomicrobium, Planctomyces, Prochloron, Sulfolobus, Thermococcus, Thermoproteus and Verrucomicrobium, respectively. Opinion 79. Int J Syst Evol Microbiol. 2005; 55:517-518 View ArticlePubMed
  25. 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
  26. Skerman VBD, McGowan V and Sneath PHA. Approved Lists of Bacterial Names. Int J Syst Bacteriol. 1980; 30:225-420 View Article
  27. Buchanan RE. Studies in the nomenclature and classification of bacteria. II. The primary subdivisions of the Schizomycetes. J Bacteriol. 1917; 2:155-164PubMed
  28. Swellengrebel NH. Sur la cytologie comparée des spirochètes et des spirilles. [Paris]. Ann Inst Pasteur (Paris). 1907; 21:562-586
  29. Pikuta EV, Hoover RB, Bej AK, Marsic D, Whitman WB and Krader P. Spirochaeta dissipatitropha sp. nov., an alkaliphilic, obligately anaerobic bacterium, and emended description of the genus Spirochaeta Ehrenberg 1835. Int J Syst Evol Microbiol. 2009; 59:1798-1804PubMed
  30. Canale-Parola E. Genus I. Spirochaeta Ehrenberg 1835, 313. In: Buchanan RE, Gibbons NE (eds), Bergey's Manual of Determinative Bacteriology, Eighth Edition, The Williams and Wilkins Co., Baltimore, 1974, p. 168-171.
  31. Ehrenberg CG. Dritter Beitrag zur Erkenntniss grosser Organisation in der Richtung des kleinsten Raumes. Abhandlungen der Preussischen Akademie der Wissenschaften (Berlin), 1835, p. 143-336.
  32. BAuA. 2010, Classification of bacteria and archaea in risk groups. TRBA 466, p. 206.Web Site
  33. 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
  34. Klenk HP and Göker M. En route to a genome-based classification of Archaea and Bacteria? Syst Appl Microbiol. 2010; 33:175-182 View ArticlePubMed
  35. 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
  36. List of growth media used at DSMZ: Web Site
  37. Gemeinholzer B, Dröge G, Zetzsche H, Haszprunar G, Klenk HP, Güntsch A, Berendsohn WG and Wägele JW. The DNA Bank Network: the start from a German initiative. Biopreserv Biobank. 2011; 9:51-55 View Article
  38. JGI website. Web Site
  39. The Phred/Phrap/Consed software package. Web Site
  40. 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
  41. Han C, Chain P. Finishing repeat regions automatically with Dupfinisher. In: Proceeding of the 2006 international conference on bioinformatics & computational biology. Arabnia HR, Valafar H (eds), CSREA Press. June 26-29, 2006: 141-146.
  42. 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.
  43. 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
  44. 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
  45. 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
  46. Paster BJ. Phylum XV Spirochaetes Garrity and Holt 2001. In: Goodfellow MJ, Kämpfer P, Chun J, De Vos P, Rainey FA, Whitman WB (eds), Bergey's Manual of Systematic Bacteriology, Second Edition, Volume 4, Springer, New York, 2011, p. 471.
  47. Yarza P, Ludwig W, Euzéby J, Amann R, Schleifer KH, Glöckner FO and Rosselló-Móra R. Update of the All-Species Living Tree Project based on 16S and 23S rRNA sequence analyses. Syst Appl Microbiol. 2010; 33:291-299 View ArticlePubMed
  48. Meier-Kolthoff JP, Auch AF, Huson DH and Göker M. COPYCAT: Co-phylogenetic Analysis tool. Bioinformatics. 2007; 23:898-900 View ArticlePubMed
  49. Stamatakis A, Auch AF, Meier-Kolthoff J and Göker M. AxPcoords & parallel AxParafit: statistical co-phylogenetic analyses on thousands of taxa. BMC Bioinformatics. 2007; 8:405 View ArticlePubMed
  50. Legendre P, Desdevises Y and Bazen E. A Statistical Test for Host–Parasite Coevolution. Syst Biol. 2002; 51:217-234 View ArticlePubMed
  51. Felsenstein J. Inferring phylogenies. Sinauer Associates Inc., Sunderland, Massachusetts 2004.
  52. Bermudes D, Chase D and Margulis L. Morphology as a basis for taxonomy of large spirochetes symbiotic in wood-eating cockroaches and termites: Pillotina gen. nov., nom. rev.; Pillotina calotermitidis sp. nov., nom. rev.; Diplocalyx gen. nov., nom. rev.; Diplocalyx calotermitidis sp. nov., nom. rev.; Hollandina gen. nov., nom. rev.; Hollandina pterotermitidis sp. nov., nom. rev.; and Clevelandina reticulitermitidis gen. nov., sp. nov. Int J Syst Bacteriol. 1988; 38:291-302 View ArticlePubMed
  53. Auch AF, Von Jan M, Klenk HP and Göker M. Digital DNA-DNA hybridization for microbial species delineation by means of genome-to-genome sequence comparison. Stand Genomic Sci. 2010; 2:117-134 View ArticlePubMed
  54. Auch AF, Klenk HP and Göker M. Standard operating procedure for calculating genome-to-genome distances based on high-scoring segment pairs. Stand Genomic Sci. 2010; 2:142-148 View ArticlePubMed
  55. Anderson I, Scheuner C, Göker M, Mavromatis K, Hooper SD, Porat I, Klenk HP, Ivanova N and Kyrpides N. Novel insights into the diversity of catabolic metabolism from ten haloarchaeal genomes. PLoS ONE. 2011; 6:e20237 View ArticlePubMed
  56. NCBI BLAST version 2.2.17. Web Site
  57. Li L, Stoeckert CJ and Roos DS. OrthoMCL: Identification of ortholog groups for eukaryotic genomes. Genome Res. 2003; 13:2178-2189 View ArticlePubMed
  58. van Dongen S. Graph clustering by flow simulation. PhD thesis, University of Utrecht, The Netherlands, 2000 ().Web Site
  59. MCL version 08-312. Web Site
  60. Edgar RC. MUSCLE: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res. 2004; 32:1792-1797 View ArticlePubMed
  61. Thompson JD, Thierry JC and Poch O. RASCAL: rapid scanning and correction of multiple sequence alignments. Bioinformatics. 2003; 19:1155-1161 View ArticlePubMed
  62. Meusemann K, von Reumont BM, Simon S, Roeding F, Strauss S, Kück P, Ebersberger I, Walzl M, Pass G and Breuers S. A Phylogenomic approach to resolve the arthropod tree of life. Mol Biol Evol. 2010; 27:2451-2464 View ArticlePubMed
  63. Enright AJ, Van Dongen S and Ouzounis CA. An efficient algorithm for large-scale detection of protein families. Nucleic Acids Res. 2002; 30:1575-1584 View ArticlePubMed
  64. Siddall ME and Whiting MF. Long-branch abstractions. Cladistics. 1999; 15:9-24 View Article