Skip to main content
Download PDF

Phylogenetic and comparative genomics of the family Leptotrichiaceae and introduction of a novel fingerprinting MLVA for Streptobacillus moniliformis

BMC Genomics volume 17, Article number: 864 (2016) Cite this article

Abstract

Background

The Leptotrichiaceae are a family of fairly unnoticed bacteria containing both microbiota on mucous membranes as well as significant pathogens such as Streptobacillus moniliformis, the causative organism of streptobacillary rat bite fever. Comprehensive genomic studies in members of this family have so far not been carried out. We aimed to analyze 47 genomes from 20 different member species to illuminate phylogenetic aspects, as well as genomic and discriminatory properties.

Results

Our data provide a novel and reliable basis of support for previously established phylogeny from this group and give a deeper insight into characteristics of genome structure and gene functions. Full genome analyses revealed that most S. moniliformis strains under study form a heterogeneous population without any significant clustering. Analysis of infra-species variability for this highly pathogenic rat bite fever organism led to the detection of three specific variable number tandem analysis loci with high discriminatory power.

Conclusions

This highly useful and economical tool can be directly employed in clinical samples without laborious prior cultivation. Our and prospective case-specific data can now easily be compared by using a newly established MLVA database in order to gain a better insight into the epidemiology of this presumably under-reported zoonosis.

Background

The Leptotrichiaceae are a family of underexplored and rarely isolated microorganisms within the phylum Fusobacteria containing both species known from certain pathologies as well as colonising members of the resident microbiota. Many if not all species of the Leptotrichiaceae inhabit the oral cavities, gastrointestinal or urogenital tracts of humans and animals [1–3]. One of the reasons they are rarely encountered is the obligate anaerobic or capnophilic growth dependence of these fastidious bacteria and the usual presence of a high number of concomitant microorganisms. Some members of this family are well known pathogens, such as Streptobacillus (S.) moniliformis, one of the two causative organisms of the bacterial zoonosis rat bite fever [4]. Recently, a number of novel species have been described, most of which could be attributed to clinical disease [5–8]. It can also be concluded from numerous phylotypes, Leptotrichiaceae normally colonize mucous membranes [9–15], but when introduced into new tissue or host sites they are also able to shift their pathogenic potential and cause severe and even life-threatening disease. With increasing availability of next generation sequencing a number of single genomes have been published [6, 16–20]. However, almost no comprehensive genomic studies including these microorganisms have been completed, nor have virulence properties been identified in these species. Phylogenetic studies and identifications within the phylum Fusobacteria have been carried out and based on single or multiple gene sequences such as 16S rRNA, 16S–23S rRNA internal transcribed spacer, gyrB, groEL, recA, rpoB, conserved indels and genes for group-specific proteins, 43-kDa outer membrane protein and zinc protease [18, 21–30]. In an attempt to characterize different members of this phylum Gupta & Seti proposed various conserved signature indels (CSIs) in amino acid sequences for the Leptotrichiaceae from which three CSIs were found to be specific for this family [31]. On the other hand, no detailed phylogenetic and comparative genome studies dedicated to Leptotrichiaceae have been published up to now. Furthermore, and due to a general paucity of strains and attempts to differentiate members from the same species there is currently no tool available to type isolates in order to prove transmission chains. Our data, presented here, were derived from 46 complete genomes from 20 different taxa of the family Leptotrichiaceae aiming to provide the first such comparative analysis. Our study results confirm the picture of earlier phylogenies from this group that are now based on a larger scale of orthologous genes. We give a surveying insight into the investigated genomes, thereby also including recently described species from this family. With a novel approach it was, furthermore, possible to accurately and unequivocally type isolates of S. moniliformis based on three variable number tandem repeat (VNTR) sequences. With this, we are presenting a culture-independent, species-specific fingerprinting tool in order to type the most important causative organism of rat bite fever for the first time.

Results

Accession numbers

The GenBank/EMBL/DDBJ accession numbers for the genome sequences used in this study are summarized in Table 1.

Table 1 Strains as well as origins, clinical symptoms and host species of the Leptotrichiaceae members used in this study
Full size table

Phylogenetic analysis based on orthologous genes

To determine the phylogeny within the genus Streptobacillus we aligned the allelic variations of 281 orthologous genes from 29 strains of S. moniliformis, S. ratti, S. notomytis, S. felis and S. hongkongensis which resulted in 57,841 single nucleotide polymorphisms (SNPs). From these SNPs we inferred a maximum likelihood phylogeny showing the distance between the different species within this genus (Fig. 1). To zoom deeper into the phylogeny of the S. moniliformis group we repeated this analyses with 775 orthologous genes present in 23 S. moniliformis strains which resulted in 5,211 SNPs. These SNPs were also used to construct a maximum likelihood phylogeny (Fig. 2).

Fig. 1
figure 1

Maximum likelihood phylogenetic tree of the genus Streptobacillus (strains 1–29 according to Table 1). The tree is based on 281 orthologous genes including 57,841 SNPs

Full size image
Fig. 2
figure 2

Unrooted maximum likelihood phylogenetic tree of 23 Streptobacillus moniliformis strains from this study. The tree is based on 775 orthologous genes including 5,211 SNPs

Full size image

As shown in the tree, most S. moniliformis strains used for this study are unrelated and form a heterogeneous population without any significant clustering. Solely strains A378/1 and B5/1 that both originate from the same source but without a common epidemiological background were phylogenetically indistinguishable.

Analysis of genomes and protein functions

The genome size in members of the Leptotrichiaceae varies between 1.22 and 4.42 Mbp with Caviibacter (C.) abscessus and Sebaldella (Se.) termitidis being the smallest und largest genomes, respectively. Generally, and with the exception of Sebaldella termitidis, genomes are smaller than 2.45 Mbp. The genera Caviibacter and Sneathia (Sn.) are comparable with respect to genome size (1.22–1.34 Mbp) as are the genera Streptobacillus and Oceanivirga (O.) (1.38–1.90 Mbp). Members of the genus Leptotrichia (L.) are the second largest group with 2.31–2.47 Mbp. A general overview on the genomes of all strains under study is depicted in Table 2. A similar order can be observed with respect to coding DNA sequences (CDS), i.e., C. abscessus and Sneathia spp. possess 1212–1282 CDS, followed by Streptobacillus spp. and O. salmonicida (1293–1679), Leptotrichia spp. (1930–2365) and Sebaldella termitidis (4083). The average percentage of CDS within the whole genome displays a graded distribution within the family: a highly coding group consisting of the genera Caviibacter, Oceanivirga and Sneathia (89–93 %), an intermediate Streptobacillus spp. group (87 %) and a group containing the genera Leptotrichia and Sebaldella (84 %) with lower coding density. Nevertheless, intra-genus variability can be considerably high, the former results can inevitably also be shown for the average gene densities and the average intergenic regions (in parentheses average genes/Mbp; number of intergenic nt): O. salmonicida (1056; 79), C. abscessus (996; 76), Sneathia spp. (989; 84), Streptobacillus spp. (987; 115), Leptotrichia spp. (967; 144) and Sebaldella (936; 149). An organization of the genomes under study into clusters of orthologous groups (COGs) is depicted in Additional files 1 and 2 and shows, however, high intra-species as well as inter-species variations. On a generic level, gene contents of COG classes J, L, D and F are inversely correlated with increasing genome size, whereas COG classes K, N, T and Q are positively correlated (see Additional files 1 and 2).

Table 2 Analysis of genome data as well as predictions of coding regions of the Leptotrichiaceae members used in this study
Full size table

Multiple-Locus Variable number tandem repeat Analysis (MLVA)

In silico VNTR analysis

Under default conditions, 127 repeats were identified by the tandem repeat finder. For further analysis, the three most variable VNTRs were identified according to the degree of variability of allele types identified by alignment analysis (Table 3). These three allelic loci were only present in S. moniliformis and thus proved to be specific for this microorganism (all other members of the Leptotrichiaceae were negative). The combination of the three loci yielded a high discriminatory index (0.94296 DI; Table 4).

Table 3 Streptobacillus moniliformis specific Variable Number of Tandem Repeat (VNTR) primer sequences used in this study
Full size table
Table 4 VNTR allele types of the Streptobacillus moniliformis strains used in this study
Full size table

PCR-based validation of in silico results

The absence of the calculated VNTR loci could also be proven by polymerase chain reaction (PCR) in all Leptotrichiaceae members other than S. moniliformis (data not shown). Contrarily, each of the ten S. moniliformis strains exhibited a specific band corresponding to their predicted tandem repeats pattern. Analysis of the sequenced PCR products confirmed the allele type allocation determined in silico (Table 4). VNTR_Sm1 alleles of two isolates, which were not found in silico, were successfully assigned (Table 4). Re-calculation revealed a DI of 0.9529 after including these two isolates, as well as one isolate for which no genome data was available. In order to facilitate comparisons of results in future studies, every genotype (from the allele types of the three loci) was expressed as a specific allele combination resulting in a specific allele code (Table 4). An online database dedicated to MLVA results of S. moniliformis has been established on the webserver of University Paris-Saclay, Orsay, France (http://microbesgenotyping.i2bc.paris-saclay.fr/databases/public) which is open to future entries and strain comparisons.

Discussion

Members of the Leptotrichiaceae are rarely encountered microorganisms, a phenomenon that seems to be highly dependent on difficulties with cultivation. With the availability of molecular methods in this field the number of findings and frequencies has significantly increased [10–15, 32–36]. On the other hand, we still need deeper insight into the genomes of this group. In particular, the mechanisms involved in pathogenesis and virulence of pathogenic species are completely unexplored. We have undertaken a first step into this direction by analysing a broad spatio-temporal collection of strains, thereby including especially species with regular evidence for pathologies. Firstly, the large dataset from this study has been utilized for the confirmation of our phylogenetic picture from earlier studies [18, 30, 37, 38]. An intra-genus phylogeny that was based on 775 orthologous genes revealed a very similar picture to previous studies involving only four selected functional genes (Figs. 1 and 2). Conversely and in contrast to almost identical average nucleotide identity (ANI) values [30], full genome analyses revealed a high level of heterogeneity for all but two strains (no. 15 and 18) of S. moniliformis without any significant clustering. This is, albeit, not surprising, because the present study included a large spatio-temporal collection of 23 S. moniliformis strains that have been isolated over a period of 90 years from at least five different host species and from almost all subcontinents. We were also able to display the three predicted Leptotrichiaceae specific CSIs of MreB/MrI (2 aa deletion), AlaS and RecA (5 and 2 aa insertions, respectively) in all of our genomes as well as in the recently described members of the family (data not shown) [31].

Genome size dependent gene content has been described and could also be confirmed for the genomes from this study [19]. With increasing genome size gene contents of COG classes J, L, D and F involved in DNA replication, cell cycle regulation and protein translation are inversely correlated, whereas COG classes K, N, T and Q involved in transcription, signal transduction, cell motility and the biochemistry of secondary metabolites are positively correlated (see Additional files 1 and 2). This makes sense when essential gene functions are preserved in smaller genomes and less important gene functions which are dispensable or can be ‘outsourced’ to the host, are lost [19]. On first impression the group of S. moniliformis strains is highly similar as can be concluded from related morphological and phenotypical properties and also from their high intra-species ANI of 98.5–99.3 % (cf. Table S2 in [30]). Based on data from this study very similar COG classes were also observed within this group (see Additional files 1 and 2), but differences in coding densities suggested, on the other hand, remarkable discrepancies. Fuelled by the idea that these discrepancies could, furthermore, be utilized with respect to epidemiology, we have developed a specific MLVA typing scheme for the major pathogen from this group, S. moniliformis, and the causative organism of rat bite fever. This scheme proved to be sufficient in unequivocally typing all 23 S. moniliformis strains under study plus one additional isolate with high discriminatory power (0.9529 DI). Interestingly, only four allele codes (genotypes; LHL2, LHL5, LHL10 and LHL11) were found more than once among isolates (Table 4). At least for LHL2 isolates, a connection could be pursued in that both isolates have been stored in the same strain collection, although a direct transmission could not be proven. To check the clonality of isolates belonging to these four genotypes we have investigated further loci with high discriminatory potential, i.e., the clustered regularly interspaced short palindromic repeats (CRISPR) region known to occur in S. moniliformis (http://crispr.u-psud.fr/cgi-bin/crispr/SpecieProperties.cgi?Taxon_id=519441). In contrast to all other allele codes (LHL5, LHL10, LHL11), both strains (no. 15 and 18) belonging to the allele code LHL2 indeed shared an identical CRISPR region, thereby pointing towards a clonal relation of these two isolates (data not shown) as could also be concluded from the phylogenetic tree (Fig. 2). Due to its length of up to approximately 3,000 nucleotides and its high level of heterogeneity the CRISPR region seems, on the other hand, presently not very well suited as a direct typing tool, but could be useful in certain situations to confirm or negate clonality of strains. A second advantage of the MLVA method described in this study is that it can effectively be pursued directly from the original matrix (e.g., a mouth microbiota swab and a clinical sample) without prior cultivation of the organism, which offers the possibility to better understand transmission chains in the future. This seems to be especially relevant since established PCR assays are not species specific, but limited to genus level specificity [37, 39, 40]. The majority of diagnoses of rat bite fever cases in the recently published literature relies only on partial 16S rRNA gene sequence analysis that may – in the light of very similar novel Streptobacillus spp. that also colonize rats – be quite uncertain for proper pathogen identification [41]. Hopefully, the newly established MLVA database will help to clarify regional infectious clusters and confirm transmission of certain lineages.

Conclusion

We have undertaken a first analysis of Leptotrichiaceae genomes using a large spatiotemporal collection of strains also including novel members of this group. Our dataset unveiled a first insight into characteristics founding a stable phylogeny, genome structure and COG classes. Beside apparent intra-species similarities we have detected also genetic heterogeneities that provided a basis for fingerprinting the most relevant pathogen from this group, the rat bite fever organism, S. moniliformis. This highly useful and economical tool can be directly used from clinical samples without ambitious prior cultivation and with high discriminatory power. Our data form the basis for a newly established MLVA database that provides the opportunity to store and compare isolate-specific information in future cases with this neglected zoonosis.

Methods

Generation of genomic data

Twenty-two strains of S. moniliformis were sequenced in this study, ten strains were taken from previous publications of our group and 15 strains were descended from other projects (Table 1). Genomic DNA was extracted from a 72 h bacterial culture with a commercial kit according to the manufacturer’s instructions (MasterPure™ Complete DNA and RNA Purification Kit, Epicentre, distributed by Biozym Scientific, Hessisch Oldendorf, Germany). Whole genome sequencing of the strains was performed on an Illumina MiSeq with v3 chemistry resulting in 300 bp paired end reads and a coverage of greater than 90×. Quality trimming and de novo assembly was performed with CLC Genomics Workbench, Version 7.5 (CLC Bio, Aarhus, Denmark). For automatic annotation we used the RAST Server: Rapid Annotations using Subsystems Technology [42]. Data from further relevant reference genomes from the Leptotrichiaceae were also utilized and obtained from the National Center for Biotechnology Information (NCBI) database (http://www.ncbi.nlm.nih.gov). Sequence analyses and genome calculations as well as oligonucleotide primer generation were carried out with Geneious (v. 8.1.3; Biomatters, Auckland, NZ) [43]. Table 1 depicts the set of strains and reference genomes used for this study.

Phylogenetic analysis based on orthologous genes

The determination of the maximum common genome (MCG) alignment was done comprising those genes present in all genomes considered for comparison [44]. Based on the parameters sequence similarity (minimum 70 %) and coverage (minimum 90 %) the genes were clustered and those genes that were present in each genome, fulfilling the threshold parameters were defined as MCG. This resulted in 281 orthologous genes for the comparison of 29 strains of S. moniliformis, S. ratti, S. notomytis, S. felis and S. hongkongensis and in 775 orthologous genes for the comparison within 23 strains of S. moniliformis only.

The following extraction of the allelic variants of these genes from all genomes was performed by a blast based approach after which they were aligned individually for each gene and concatenated which resulted in an alignment of 219,961 bp for the 29 strains and of 546,508 bp for the 23 S. moniliformis strains [45].

This alignment was used to generate a phylogenetic tree with randomized axelerated maximum likelihood (RAxML) 8.1 [46] using a General Time Reversible model and gamma correction for among site rate variation.

Analysis of genomes and protein functions

Genes were predicted with Prodigal [47] and assigned to COGs with the NCBI’s Conserved Domain Database [48].

Multiple-Locus Variable number tandem repeat Analysis (MLVA)

In silico VNTR analysis

The complete genome sequence of the S. moniliformis type strain DSM12112T (accession number CP001779.1) was used to search for potential VNTRs using a tandem repeat finder web tool (http://tandem.bu.edu/trf/trf.basic.submit.html). We focused our search on repeats that were characterized by high purity, large size, and/or large number of repeat copies [49]. Repeats of interest were aligned against a set of available genomes depicted in Table 1 using Geneious and allele types were determined as shown in repeat copy numbers. The DI was calculated for a combination of three most variable VNTRs using an online discriminatory power calculator (http://insilico.ehu.es/mini_tools/discriminatory_power/).

PCR-based validation of in silico results

Ten S. moniliformis strains (strain nos. 1, 2, 3, 12, 14, 15, 21, 22 and 23 according to Table 1 plus strain A40-13 for which complete genomic data were not available) as well as all accessible members of the Leptotrichiaceae other than S. moniliformis were used for validation. DNA was extracted from respective isolates (2–3 colonies) by boiling in 100 μL distilled water for 20 min (min.) followed by centrifugation at 20,817 × g for 5 min. The 20 μL final PCR reaction contained 10 μL of Hotstar Taq MasterMix (Qiagen, Hilden, Germany), 1 μL of each forward and reverse primer (10 pmol/μL) (TIB MOLBIOL, Berlin, Germany) (Table 3), 6 μL DNase free PCR grade water (Qiagen), and 2 μL of the extracted DNA. PCR conditions were as following: 1× (95 °C, 15 min), 40x (94 °C, 30 s; 58 °C, 30 s; 72 °C, 30 s), 1× (72 °C, 10 min). PCR products were stained with ethidium bromide in a 2 % agarose gel (100 V for 1.5 h) and then analyzed with a gel documentation system (BioDoc-It, UVP, UK). The PCR amplicons were purified using MicroElute DNA Cycle-Pure Kit (OMEGA bio-tek, Norcross, USA) and sequenced at Seqlab-Microsynth laboratories (Göttingen, Germany). All sequences were analyzed by tandem repeat finder web tool and/or BLASTN 2.3.1+ [50] hosted by NCBI website and compared to the in silico results.

Abbreviations

AHL:

Animal Health Laboratory South Perth, Australia

ANI:

Average nucleotide identity

ATCC:

American Type Culture Collection Rockville, USA

C.:

Caviibacter

°C:

Degrees Celsius

CDS:

Coding DNA sequences

CIP:

Collection Institut Pasteur Paris, France

COG:

Cluster of orthologous groups

CRISPR:

Clustered regularly interspaced short palindromic repeat

CSI:

Conserved signature indel

DDBJ:

DNA Data Bank of Japan

DI:

Discriminatory index

DNA:

Desoxyribonucleic acid

DKFZ:

Deutsches Krebsforschungszentrum Heidelberg, Germany

EMBL:

European Molecular Biology Laboratory

Fig.:

Figure

g :

Gravity

GC:

Guanine-cytosine content

h:

Hour

IPDH:

Institute for Poultry Diseases Hannover, Germany

kDa:

kilo Dalton

L. :

Leptotrichia

LHL:

Landesbetrieb Hessisches Landeslabor

Mbp:

Mega base pairs

MCG:

Maximum common genome

min:

minute

MVLA:

Multi locus variable number tandem repeat analysis

μL:

micro liter

NCBI:

National Center for Biotechnology Information

NCTC:

National Collection of Type Cultures London, UK

n. d. a.:

no data available

nt:

nucleotides

O.:

Oceanivirga

PCR:

Polymerase chain reaction

RAST:

Rapid annotations using subsystems technology

RaxML:

Randomized axelerated maximum likelihood

RBF:

Rat bite fever

RIVM:

Rijksinstituut voor Volksgezondheid en Milieuhygiene Bilthoven, The Netherlands

rRNA:

ribosomal ribonucleic acid

S. :

Streptobacillus

Se. :

Sebaldella

sec.:

second

Sn. :

Sneathia

SNPs:

Single nucleotide polymorphisms

T :

Type strain

TiHo:

Tierärztliche Hochschule Hannover, Germany

tRNA:

transfer ribonucleic acid

VNTR:

Variable number tandem repeat

ZfV:

Zentralinstitut für Versuchstierzucht, Hannover, Germany

References

  1. Gaastra W, Boot R, Ho HT, Lipman LJ. Rat bite fever. Vet Microbiol. 2009;133(3):211–28.

    Article  PubMed  Google Scholar 

  2. Eribe ER, Paster BJ, Caugant DA, Dewhirst FE, Stromberg VK, Lacy GH, Olsen I. Genetic diversity of Leptotrichia and description of Leptotrichia goodfellowii sp. nov., Leptotrichia hofstadii sp. nov., Leptotrichia shahii sp. nov. and Leptotrichia wadei sp. nov. Int J Syst Evol Microbiol. 2004;54(Pt 2):583–92.

    Article  CAS  PubMed  Google Scholar 

  3. Harwich Jr MD, Serrano MG, Fettweis JM, Alves JM, Reimers MA, Buck GA, Jefferson KK. Genomic sequence analysis and characterization of Sneathia amnii sp. nov. BMC Genomics. 2012;13 Suppl 8:S4.

    Article  PubMed  PubMed Central  Google Scholar 

  4. Levaditi C, Nicolau S, Poincloux P. Sur le rôle étiologique de Streptobacillus moniliformis (nov. spec.) dans l’érythème polymorphe aigu septicémique. C R Acad Sci. 1925;180:1188–90.

    Google Scholar 

  5. Eisenberg T, Glaeser S, Nicklas W, Mauder N, Contzen M, Aledelbi K, Kämpfer P. Streptobacillus felis sp. nov. isolated from a cat with pneumonia. Int J Syst Evol Microbiol. 2015;65(7):2172–8.

    Article  CAS  PubMed  Google Scholar 

  6. Eisenberg T, Glaeser SP, Ewers C, Semmler T, Nicklas W, Rau J, Mauder N, Hofmann N, Imaoka K, Kimura M, et al. Streptobacillus notomytis sp. nov. isolated from a spinifex hopping mouse (Notomys alexis THOMAS, 1922), and emended description of Streptobacillus Levaditi et al. 1925, Eisenberg et al. 2015 emend. Int J Syst Evol Microbiol. 2015;65(12):4823–9.

    Article  CAS  PubMed  Google Scholar 

  7. Eisenberg T, Nesseler A, Nicklas W, Spamer V, Seeger H, Zschöck M. Streptobacillus sp. isolated from a cat with pneumonia. J Clin Microbiol Case Reports. 2014;2014:1–7.

    Google Scholar 

  8. Woo PC, Wu AK, Tsang CC, Leung KW, Ngan AH, Curreem SO, Lam KW, Chen JH, Chan JF, Lau SK. Streptobacillus hongkongensis sp. nov., isolated from patients with quinsy and septic arthritis, and emended descriptions of the genus Streptobacillus and the species Streptobacillus moniliformis. Int J Syst Evol Microbiol. 2014;64(Pt 9):3034–9.

    Article  CAS  PubMed  Google Scholar 

  9. Bik EM, Rohlik CM, Chow E, Carlin KP, Jensen ED, Venn-Watson S, Relman DA. Indigenous microbiota of marine mammals. In: 13th International Symposium on Microbial Ecology. Seattle: International Society for Microbial Ecology; 2010. http://www.isme-microbes.org/isme13.

    Google Scholar 

  10. Chaves-Moreno D, Plumeier I, Kahl S, Krismer B, Peschel A, Oxley AP, Jauregui R, Pieper DH. The microbial community structure of the cotton rat nose. Environ Microbiol Rep. 2015;7(6):929–35.

    Article  CAS  PubMed  Google Scholar 

  11. Dewhirst FE, Klein EA, Thompson EC, Blanton JM, Chen T, Milella L, Buckley CM, Davis IJ, Bennett ML, Marshall-Jones ZV. The canine oral microbiome. PLoS One. 2012;7(4):e36067.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Hullar MA, Lancaster SM, Li F, Tseng E, Beer K, Atkinson C, Wahala K, Copeland WK, Randolph TW, Newton KM, et al. Enterolignan-producing phenotypes are associated with increased gut microbial diversity and altered composition in premenopausal women in the United States. Cancer Epidemiol Biomarkers Prev. 2015;24(3):546–54.

    Article  CAS  PubMed  Google Scholar 

  13. Strong T, Dowd S, Gutierrez AF, Coffman J. Amplicon pyrosequencing of wild duck eubacterial microbiome from a fecal sample reveals numerous species linked to human and animal diseases. Research. 2013;2(224):1–7. [v1; ref status: awaiting peer review, http://f1000r.es/1yy]. F1000.

    Google Scholar 

  14. Xenoulis PG, Palculict B, Allenspach K, Steiner JM, Van House AM, Suchodolski JS. Molecular-phylogenetic characterization of microbial communities imbalances in the small intestine of dogs with inflammatory bowel disease. FEMS Microbiol Ecol. 2008;66(3):579–89.

    Article  CAS  PubMed  Google Scholar 

  15. Bik EM, Costello EK, Switzer AD, Callahan BJ, Holmes SP, Wells RS, Carlin KP, Jensen ED, Venn-Watson S, Relman DA. Marine mammals harbor unique microbiotas shaped by and yet distinct from the sea. Nat Commun. 2016;7:10516.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Nolan M, Gronow S, Lapidus A, Ivanova N, Copeland A, Lucas S, Del Rio TG, Chen F, Tice H, Pitluck S, et al. Complete genome sequence of Streptobacillus moniliformis type strain (9901). Stand Genomic Sci. 2009;1(3):300–7.

    PubMed  PubMed Central  Google Scholar 

  17. Harmon-Smith M, Celia L, Chertkov O, Lapidus A, Copeland A, Glavina Del Rio T, Nolan M, Lucas S, Tice H, Cheng JF, et al. Complete genome sequence of Sebaldella termitidis type strain (NCTC 11300). Stand Genomic Sci. 2010;2(2):220–7.

    Article  PubMed  PubMed Central  Google Scholar 

  18. Eisenberg T, Imaoka K, Kimura M, Glaeser SP, Ewers C, Semmler T, Rau J, Nicklas W, Kämpfer P. Streptobacillus ratti sp. nov., isolated from a black rat (Rattus rattus). Int J Syst Evol Microbiol. 2016;66(4):1620–6.

    Article  PubMed  Google Scholar 

  19. Harwich Jr MD, Serrano MG, Fettweis JM, Alves JM, Reimers MA, Vaginal Microbiome Consortium (additional members), Buck GA, Jefferson KK. Genomic sequence analysis and characterization of Sneathia amnii sp. nov. BMC Genomics. 2012;13 Suppl 8:S4.

    Article  PubMed  PubMed Central  Google Scholar 

  20. Ivanova N, Gronow S, Lapidus A, Copeland A, Glavina Del Rio T, Nolan M, Lucas S, Chen F, Tice H, Cheng JF, et al. Complete genome sequence of Leptotrichia buccalis type strain (C-1013-b). Stand Genomic Sci. 2009;1(2):126–32.

    Article  PubMed  PubMed Central  Google Scholar 

  21. Woo PC, Wong SS, Teng JL, Leung KW, Ngan AH, Zhao DQ, Tse H, Lau SK, Yuen KY. Leptotrichia hongkongensis sp. nov., a novel Leptotrichia species with the oral cavity as its natural reservoir. J Zhejiang Univ Sci B. 2010;11(6):391–401.

    Article  PubMed  PubMed Central  Google Scholar 

  22. Conrads G, Claros MC, Citron DM, Tyrrell KL, Merriam V, Goldstein EJ. 16S-23S rDNA internal transcribed spacer sequences for analysis of the phylogenetic relationships among species of the genus Fusobacterium. Int J Syst Evol Microbiol. 2002;52(Pt 2):493–9.

    Article  CAS  PubMed  Google Scholar 

  23. Sun D, Zhang H, Lv S, Wang H, Guo D. Identification of a 43-kDa outer membrane protein of Fusobacterium necrophorum that exhibits similarity with pore-forming proteins of other Fusobacterium species. Res Vet Sci. 2013;95(1):27–33.

    Article  CAS  PubMed  Google Scholar 

  24. Kim HS, Lee DS, Chang YH, Kim MJ, Koh S, Kim J, Seong JH, Song SK, Shin HS, Son JB, et al. Application of rpoB and zinc protease gene for use in molecular discrimination of Fusobacterium nucleatum subspecies. J Clin Microbiol. 2010;48(2):545–53.

    Article  CAS  PubMed  Google Scholar 

  25. Shah HN, Olsen I, Bernard K, Finegold SM, Gharbia S, Gupta RS. Approaches to the study of the systematics of anaerobic, gram-negative, non-sporeforming rods: current status and perspectives. Anaerobe. 2009;15(5):179–94.

    Article  CAS  PubMed  Google Scholar 

  26. Strauss J, White A, Ambrose C, McDonald J, Allen-Vercoe E. Phenotypic and genotypic analyses of clinical Fusobacterium nucleatum and Fusobacterium periodonticum isolates from the human gut. Anaerobe. 2008;14(6):301–9.

    Article  CAS  PubMed  Google Scholar 

  27. Jin J, Haga T, Shinjo T, Goto Y. Phylogenetic analysis of Fusobacterium necrophorum, Fusobacterium varium and Fusobacterium nucleatum based on gyrB gene sequences. J Vet Med Sci. 2004;66(10):1243–5.

    Article  CAS  PubMed  Google Scholar 

  28. Jalava J, Eerola E. Phylogenetic analysis of Fusobacterium alocis and Fusobacterium sulci based on 16S rRNA gene sequences: proposal of Filifactor alocis (Cato, Moore and Moore) comb. nov. and Eubacterium sulci (Cato, Moore and Moore) comb. nov. Int J Syst Bacteriol. 1999;49(Pt 4):1375–9.

    Article  CAS  PubMed  Google Scholar 

  29. Lawson PA, Gharbia SE, Shah HN, Clark DR, Collins MD. Intrageneric relationships of members of the genus Fusobacterium as determined by reverse transcriptase sequencing of small-subunit rRNA. Int J Syst Bacteriol. 1991;41(3):347–54.

    Article  CAS  PubMed  Google Scholar 

  30. Eisenberg T, Nicklas W, Mauder N, Rau J, Contzen M, Semmler T, Hofmann N, Aledelbi K, Ewers C. Phenotypic and genotypic characteristics of members of the genus Streptobacillus. PLoS One. 2015;10(8):e0134312.

    Article  PubMed  PubMed Central  Google Scholar 

  31. Gupta RS, Sethi M. Phylogeny and molecular signatures for the phylum Fusobacteria and its distinct subclades. Anaerobe. 2014;28:182–98.

    Article  CAS  PubMed  Google Scholar 

  32. Palmer R, Drinan E, Murphy T. A previously unknown disease of farmed Atlantic salmon: pathology and establishment of bacterial aetiology. Dis Aquat Org. 1994;19:7–14.

    Article  Google Scholar 

  33. Wouters EG, Ho HT, Lipman LJ, Gaastra W. Dogs as vectors of Streptobacillus moniliformis infection? Vet Microbiol. 2008;128(3–4):419–22.

    Article  PubMed  Google Scholar 

  34. Swartz JD, Lachman M, Westveer K, O’Neill T, Geary T, Kott RW, Berardinelli JG, Hatfield PG, Thomson JM, Roberts A, et al. Characterization of the vaginal microbiota of ewes and cows reveals a unique microbiota with low levels of lactobacilli and near-neutral pH. Front Vet Sci. 2014;1:19.

    Article  PubMed  PubMed Central  Google Scholar 

  35. Kong HH, Oh J, Deming C, Conlan S, Grice EA, Beatson MA, Nomicos E, Polley EC, Komarow HD, Program NCS, et al. Temporal shifts in the skin microbiome associated with disease flares and treatment in children with atopic dermatitis. Genome Res. 2012;22(5):850–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Eisenberg T, Glaeser SP, Kämpfer P, Schauerte N, Geiger C. Root sepsis associated with insect-dwelling Sebaldella termitidis in a lesser dwarf lemur (Cheirogaleus medius). Antonie Van Leeuwenhoek. 2015;108(6):1373–82.

    Article  CAS  PubMed  Google Scholar 

  37. Eisenberg T, Kämpfer P, Ewers C, Semmler T, Glaeser SP, Collins E, Ruttledge M, Palmer R. Oceanivirga salmonicida gen. nov. sp. nov., a novel member from the Leptotrichiaceae isolated from Atlantic salmon (Salmo salar). Int J Syst Evol Microbiol. 2016;66:2429–37.

    Article  PubMed  Google Scholar 

  38. Eisenberg T, Glaeser SP, Ewers C, Semmler T, Drescher B, Kämpfer P. Caviibacter abscessus gen. nov., sp. nov., a member from the family Leptotrichiaceae isolated from guinea pigs (Cavia porcellus). Int J Syst Evol Microbiol. 2016;66(4):1652–9.

    Article  PubMed  Google Scholar 

  39. Kimura M, Tanikawa T, Suzuki M, Koizumi N, Kamiyama T, Imaoka K, Yamada A. Detection of Streptobacillus spp. in feral rats by specific polymerase chain reaction. Microbiol Immunol. 2008;52(1):9–15.

    Article  CAS  PubMed  Google Scholar 

  40. Rohde J, Rapsch C, Fehr M. Case report: Abscessation due to Streptobacillus moniliformis in a rat [in German]. Prakt Tierarzt. 2008;89(6):466–73.

    Google Scholar 

  41. Eisenberg T, Ewers C, Rau J, Akimkin V, Nicklas W. Approved and novel strategies in diagnostics of rat bite fever and other Streptobacillus infections in humans and animals. Virulence. 2016;7(6):630–48.

    Article  CAS  PubMed  Google Scholar 

  42. Aziz RK, Bartels D, Best AA, DeJongh M, Disz T, Edwards RA, Formsma K, Gerdes S, Glass EM, Kubal M, et al. The RAST Server: rapid annotations using subsystems technology. BMC Genomics. 2008;9:75.

    Article  PubMed  PubMed Central  Google Scholar 

  43. Kearse M, Moir R, Wilson A, Stones-Havas S, Cheung M, Sturrock S, Buxton S, Cooper A, Markowitz S, Duran C, et al. Geneious Basic: an integrated and extendable desktop software platform for the organization and analysis of sequence data. Bioinformatics. 2012;28(12):1647–9.

    Article  PubMed  PubMed Central  Google Scholar 

  44. von Mentzer A, Connor TR, Wieler LH, Semmler T, Iguchi A, Thomson NR, Rasko DA, Joffre E, Corander J, Pickard D, et al. Identification of enterotoxigenic Escherichia coli (ETEC) clades with long-term global distribution. Nat Genet. 2014;46(12):1321–6.

    Article  Google Scholar 

  45. Eisenberg T, Fawzy A, Nicklas W, Semmler T, Ewers C. Data from: Phylogenetic and comparative genomics of the family Leptotrichiaceae and introduction of a novel fingerprinting MLVA for Streptobacillus moniliformis. Dryad Digital Repository. doi:10.5061/dryad.1q7q4; 2016.

  46. Stamatakis A. RAxML version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies. Bioinformatics. 2014;30(9):1312–3.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Hyatt D, Chen GL, Locascio PF, Land ML, Larimer FW, Hauser LJ. Prodigal: prokaryotic gene recognition and translation initiation site identification. BMC Bioinformatics. 2010;11:119.

    Article  PubMed  PubMed Central  Google Scholar 

  48. Marchler-Bauer A, Derbyshire MK, Gonzales NR, Lu S, Chitsaz F, Geer LY, Geer RC, He J, Gwadz M, Hurwitz DI, et al. CDD: NCBI’s conserved domain database. Nucleic Acids Res. 2015;43(Database issue):D222–6.

    Article  PubMed  Google Scholar 

  49. Legendre M, Pochet N, Pak T, Verstrepen KJ. Sequence-based estimation of minisatellite and microsatellite repeat variability. Genome Res. 2007;17(12):1787–96.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Zhang Z, Schwartz S, Wagner L, Miller W. A greedy algorithm for aligning DNA sequences. J Comput Biol. 2000;7(1–2):203–14.

    Article  CAS  PubMed  Google Scholar 

  51. Yamamoto R, Clark GT. Streptobacillus moniliformis infection in turkeys. Vet Rec. 1966;79(4):95–100.

    Article  CAS  PubMed  Google Scholar 

  52. Wullenweber M, Kaspareit-Rittinghausen J, Farouq M. Streptobacillus moniliformis epizootic in barrier-maintained C57BL/6 J mice and susceptibility to infection of different strains of mice. Lab Anim Sci. 1990;40(6):608–12.

    CAS  PubMed  Google Scholar 

  53. Boot R, Oosterhuis A, Thuis HC. PCR for the detection of Streptobacillus moniliformis. Lab Anim. 2002;36(2):200–8.

    Article  CAS  PubMed  Google Scholar 

  54. Wullenweber M, Jonas C, Kunstyr I. Streptobacillus moniliformis isolated from otitis media of conventionally kept laboratory rats. J Exp Anim Sci. 1992;35(1):49–57.

    CAS  PubMed  Google Scholar 

  55. Kondruweit M, Weyand M, Mahmoud FO, Geissdorfer W, Schoerner C, Ropers D, Achenbach S, Strecker T. Fulminant endocarditis caused by Streptobacillus moniliformis in a young man. J Thorac Cardiovasc Surg. 2007;134(6):1579–80.

    Article  PubMed  Google Scholar 

  56. Loridant S, Jaffar-Bandjee MC, La Scola B. Shell vial cell culture as a tool for Streptobacillus moniliformis “resuscitation”. Am J Trop Med Hyg. 2011;84(2):306–7.

    Article  PubMed  PubMed Central  Google Scholar 

  57. Hopkinson WI, Lloyd JM. Streptobacillus moniliformis septicaemia in spinifex hopping mice (Notomys alexis). Aust Vet J. 1981;57(11):533–4.

    Article  CAS  PubMed  Google Scholar 

  58. Hanff PA, Rosol-Donoghue JA, Spiegel CA, Wilson KH, Moore LH. Leptotrichia sanguinegens sp. nov., a new agent of postpartum and neonatal bacteremia. Clin Infect Dis. 1995;20 Suppl 2:S237–9.

    Article  PubMed  Google Scholar 

  59. Collins MD, Hoyles L, Tornqvist E, von Essen R, Falsen E. Characterization of some strains from human clinical sources which resemble “Leptotrichia sanguinegens”: description of Sneathia sanguinegens sp. nov., gen. nov. Syst Appl Microbiol. 2001;24(3):358–61.

    Article  CAS  PubMed  Google Scholar 

  60. Sebald M. Etude sur les bacteries anaerobies gram-negatives asporulees. Laval: Theses de L’universite Paris, Imprimerie Barneoud S. A; 1962.

    Google Scholar 

  61. Maher M, Palmer R, Gannon F, Smith TJ. Relationship of a novel bacterial fish pathogen to Streptobacillus moniliformis and the Fusobacteria group, based on 16S ribosomal RNA analysis. Syst Appl Microbiol. 1995;18:79–84.

    Article  CAS  Google Scholar 

  62. Kapatral V, Anderson I, Ivanova N, Reznik G, Los T, Lykidis A, Bhattacharyya A, Bartman A, Gardner W, Grechkin G, et al. Genome sequence and analysis of the oral bacterium Fusobacterium nucleatum strain ATCC 25586. J Bacteriol. 2002;184(7):2005–18.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgement

We thank Ulrike Kling, Asmahan Omar, Anna Mohr, Katharina Engel, Mersiha Curić, Jens Heinbächer, Ursula Leidner, Andrea Erles-Kemna and Bernhard Berkus for excellent technical assistance and Barbara Gamb for making even the most exotic manuscripts available. We are greatly acknowledging the support of Walter Geißdörfer (Erlangen), Judith Rohde (Hannover), Bernard La Scola (Marseille), Koichi Imaoka (Tokyo) and Nobuhito Hayashimoto (Tokyo) for providing strains or DNA of strains no. 17, 18, 19, 21–28 and A40-13, respectively.

Funding

We declare that none of the authors has received funding for this work.

Availability of data and materials

The GenBank/EMBL/DDBJ accession numbers for the genome sequences used in this study are summarized in Table 1. Phylogenetic datasets generated during and analysed during the current study are available in the Dryad Digital Repository, http://dx.doi.org/10.5061/dryad.1q7q4 [45].

Authors’ contributions

TE, CE and TS conceived the study. TE, AF, WN, and TS carried out diagnostics and experiments. TE, CE and TS conducted the data analysis. TE wrote the manuscript and all the authors read and approved the final manuscript.

Competing interests

The authors declare that they have no competing interests.

Consent for publication

Not applicable.

Ethics approval and consent to participate

“Not applicable” (This manuscript does not contain any human or animal participants, human or animal data, or human or animal tissue and therefore does not require a statement on ethics approval and consent.)

Author information

Author notes

    Authors and Affiliations

    1. Abteilung Veterinärmedizin, Landesbetrieb Hessisches Landeslabor (LHL), Schubertstr. 60/H13, D-35392, Giessen, Germany

      Tobias Eisenberg & Ahmad Fawzy

    2. Department of Medicine and Infectious Diseases, Faculty of Veterinary Medicine, Cairo University, Giza Square, 12211, Egypt

      Ahmad Fawzy

    3. Deutsches Krebsforschungszentrum, D-69120, Heidelberg, Germany

      Werner Nicklas

    4. Robert Koch-Institut, D-13353, Berlin, Germany

      Torsten Semmler

    5. Institut für Hygiene und Infektionskrankheiten der Tiere, Justus-Liebig-Universität Giessen, D-35392, Giessen, Germany

      Ahmad Fawzy & Christa Ewers

    Authors
    1. Tobias Eisenberg
      View author publications

      You can also search for this author in PubMed Google Scholar

    2. Ahmad Fawzy
      View author publications

      You can also search for this author in PubMed Google Scholar

    3. Werner Nicklas
      View author publications

      You can also search for this author in PubMed Google Scholar

    4. Torsten Semmler
      View author publications

      You can also search for this author in PubMed Google Scholar

    5. Christa Ewers
      View author publications

      You can also search for this author in PubMed Google Scholar

    Corresponding author

    Correspondence to Tobias Eisenberg.

    Additional files

    Additional file 1: Table S1.

    Analysis of clusters of orthologous groups (COGs) of the Leptotrichiaceae members used in this study. COGs were assessed as described in the Materials and Methods. (XLSX 16 kb)

    Additional file 2: Figure S1.

    Relative abundances of clusters of orthologous groups (COGs) of the Leptotrichiaceae members used in this study. COGs were assessed as described in the Materials and Methods. (TIF 4188 kb)

    Rights and permissions

    Open Access This 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.

    Reprints and Permissions

    About this article

    Verify currency and authenticity via CrossMark

    Cite this article

    Eisenberg, T., Fawzy, A., Nicklas, W. et al. Phylogenetic and comparative genomics of the family Leptotrichiaceae and introduction of a novel fingerprinting MLVA for Streptobacillus moniliformis . BMC Genomics 17, 864 (2016). https://doi.org/10.1186/s12864-016-3206-0

    Download citation

    • Received:

    • Accepted:

    • Published:

    • DOI: https://doi.org/10.1186/s12864-016-3206-0

    Keywords

    • Next generation sequencing
    • Multi locus variable number tandem repeat analysis (MVLA)
    • Phylogeny
    • Typing
    • Fingerprinting
    • Streptobacillus
    • Leptotrichiaceae

    BMC Genomics

    ISSN: 1471-2164

    Contact us