Revisiting the Taxonomy of the Genus Arcobacter: Getting Order From the Chaos

fmicb-09-02077 September 1, 2018 Time: 10:25 # 1 ORIGINAL RESEARCH published: 04 September 2018 doi: 10.3389/fmicb.2018.02077 Edited by: Martha E. Trujillo, Universidad de Salamanca, Spain Reviewed by: John Phillip Bowman, University of Tasmania, Australia Javier Pascual, Deutsche Sammlung von Mikroorganismen und Zellkulturen (DSMZ), Germany *Correspondence: Jesus L. Romalde [email protected] María J. Figueras [email protected] Specialty section: This article was submitted to Evolutionary and Genomic Microbiology, a section of the journal Frontiers in Microbiology Received: 15 February 2018 Accepted: 14 August 2018 Published: 04 September 2018 Citation: Pérez-Cataluña A, Salas-Massó N, Diéguez AL, Balboa S, Lema A, Romalde JL and Figueras MJ (2018) Revisiting the Taxonomy of the Genus Arcobacter: Getting Order From the Chaos. Front. Microbiol. 9:2077. doi: 10.3389/fmicb.2018.02077 Revisiting the Taxonomy of the Genus Arcobacter: Getting Order From the Chaos Alba Pérez-Cataluña1, Nuria Salas-Massó1, Ana L. Diéguez2, Sabela Balboa2, Alberto Lema2, Jesús L. Romalde2*and Maria J. Figueras1* 1Departament de Ciències Mèdiques Bàsiques, Facultat de Medicina, Institut d’Investigació Sanitària Pere Virgili, Universitat Rovira i Virgili, Reus, Spain, 2Departamento de Microbiología y Parasitología, CIBUS-Facultad de Biología, Universidade de Santiago de Compostela, Santiago de Compostela, Spain Since the description of the genus Arcobacter in 1991, a total of 27 species have been described, although some species have shown 16S rRNA similarities below 95%, which is the cut-off that usually separates species that belong to different genera. The objective of the present study was to reassess the taxonomy of the genus Arcobacter using information derived from the core genome (286 genes), a Multilocus Sequence Analysis (MLSA) with 13 housekeeping genes, as well as different genomic indexes like Average Nucleotide Identity (ANI), in silico DNA–DNA hybridization (isDDH), Average Amino-acid Identity (AAI), Percentage of Conserved Proteins (POCPs), and Relative Synonymous Codon Usage (RSCU). The study included a total of 39 strains that represent all the 27 species included in the genus Arcobacter together with 13 strains that are potentially new species, and the analysis of 57 genomes. The different phylogenetic analyses showed that the Arcobacter species grouped into four clusters. In addition, A. lekithochrous and the candidatus species ‘A. aquaticus’ appeared, as did A. nitrofigilis, the type species of the genus, in separate branches. Furthermore, the genomic indices ANI and isDDH not only confirmed that all the species were welldefined, but also the coherence of the clusters. The AAI and POCP values showed intra-cluster ranges above the respective cut-off values of 60% and 50% described for species belonging to the same genus. Phenotypic analysis showed that certain test combinations could allow the differentiation of the four clusters and the three orphan species established by the phylogenetic and genomic analyses. The origin of the strains showed that each of the clusters embraced species recovered from a common or related environment. The results obtained enable the division of the current genus Arcobacter in at least seven different genera, for which the names Arcobacter,Aliiarcobacter gen. nov., Pseudoarcobacter gen. nov., Haloarcobacter gen. nov., Malacobacter gen. nov., Poseidonibacter gen. nov., and Candidate ‘Arcomarinus’ gen. nov. are proposed. Keywords: Arcobacter,Aliiarcobacter gen. nov., Pseudoarcobacter gen. nov., Haloarcobacter gen. nov., Malacobacter gen. nov., Poseidonibacter gen. nov., taxonomic criteria Frontiers in Microbiology | www.frontiersin.org 1September 2018 | Volume 9 | Article 2077 fmicb-09-02077 September 1, 2018 Time: 10:25 # 2 Pérez-Cataluña et al. Revisiting the Taxonomy of the Genus Arcobacter INTRODUCTION The genus Arcobacter was created by Vandamme et al. (1991) to accommodate Gram-negative, curved-shaped bacteria belonging to two species Campylobacter cryaerophila (now Arcobacter cryaerophilus) and Campylobacter nitrofigilis (now A. nitrofigilis), considered atypical campylobacters due to their ability to grow at lower temperatures (15◦C–30◦C) and without microaerophilic conditions (Vandamme et al., 1991). The latter species was selected as the type species for the new genus (Vandamme et al., 1991). One year later the genus was enlarged with the addition of two new species, A. skirrowii with an animal origin being isolated from aborted ovine, porcine and bovine fetuses, and from lambs with diarrhea, and A. butzleri, which was recovered from cases of human and animal diarrhea (Vandamme et al., 1992). Another two new species were incorporated into the genus in 2005. A. halophilus was isolated from water from a hypersaline lagoon in Hawaii (Donachie et al., 2005), and A. cibarius was isolated from broiled carcasses in Belgium (Houf et al., 2005). These species were assigned to the genus Arcobacter on the basis of the 16S rRNA gene similarity (94% and 95% for A. nitrofigilis with A. halophilus and A. cibarius, respectively). However, these values are equal, or even below, the cut-off of 95% for genus definition (Rosselló-Mora and Amann, 2001;Yarza et al., 2008, 2014;Tindall et al., 2010). From 2009 onward, new species were being described yearby-year, reaching a total number of 27 in 2017. In some of these descriptions, the similarity of the 16S rRNA gene was the decisive character for taxonomic assignation at genus level, although phylogeny based on housekeeping genes (rpoB first and then gyrB and hsp60) was also included as additional, more discriminatory tools for the species (Collado et al., 2009a, 2011;De Smet et al., 2011). Using this approach, A. molluscorum,A. ellisii,A. defluvii, or A. bivalviorum were defined, among others (Collado et al., 2009a, 2011;Figueras et al., 2011a,b;Levican et al., 2012), which showed 16S rRNA similarities ranging from 91.1 to 94.7%, not supporting their common affiliation. On the other hand, the most closely related species, which showed a similarity of 99.1% were A. ellisii and A. defluvii (Collado et al., 2011), giving evidence for the first time of the poor resolution of the 16S rRNA gene for separating closely related species in the genus Arcobacter. However, the phylogenetic analysis based on the concatenated sequences of gyrB, rpoB, and cpn60 genes, together with the DNA–DNA hybridization results, clearly supported the existence of these two differentiated taxa (Figueras et al., 2011a). Also in 2011, A. trophiarum was discovered from the intestinal tract of healthy fattening pigs, which interestingly showed the closest similarities (≥97.4%) with the other species also recovered from humans or animals, i.e., A. cryaerophilus,A. thereius,A. cibarius, or A. skirrowii (De Smet et al., 2011;Figueras et al., 2014;Van den Abeele et al., 2014). In 2013, the species A. cloacae and A. suis were described, using a Multilocus Sequence Analysis (MLSA) approach including five housekeeping genes (Levican et al., 2013) for the first time. Simultaneously, and due to the highest 16S rRNA gene similarity with A. marinus (95.5%), the species A. anaerophilus was incorporated to the genus (Sasi-Jyothsna et al., 2013). However, this species showed atypical characteristics, including lack of motility and obligate anaerobic metabolism, which led to the original description of the genus Arcobacter being emended (Sasi-Jyothsna et al., 2013). The most recently described species from shellfish are A. lekithochrous,A. haliotis, and A. canalis (Diéguez et al., 2017;Tanaka et al., 2017;Pérez-Cataluña et al., 2018a). The first one included several isolates recovered from scallop larvae and from tank seawater of a Norwegian hatchery (Diéguez et al., 2017), the second species came from an abalone of Japan (Tanaka et al., 2017) and the third from oysters submerged in a water channel contaminated with wastewater (Pérez-Cataluña et al., 2018a). However, Diéguez et al. (2018) evidenced that the species A. haliotis is a later heterotypic synonym of A. lekithochrous. Additionally, the low 16S rRNA gene similarity of A. lekithochrous with the known Arcobacter species (91.0–94.8%) found in the A. lekithochrous description made Diéguez et al. (2017) suggest that certain species might belong to other genera and recommend that a profound revision of the genus might clarify the taxonomy. On the other hand, adding 2.5% NaCl to the enrichment medium and subculturing on marine agar, Salas-Massó et al. (2016) recognized seven potential new species from water and shellfish (mussels and/or oysters), and recovered new isolates of A. halophilus and A. marinus of which only the type strains had been known. In addition, during the characterization of the most recently described species A. canalis (Pérez-Cataluña et al., 2018a) and when trying to define the seven mentioned new species, we observed that the Arcobacter species formed several different clusters distant enough to suspect they might correspond to different genera, in agreement with Diéguez et al. (2017). There are clear criteria for describing new bacterial species (Tindall et al., 2010;Figueras et al., 2011a,b). However, the description of a genus is usually based on a cut-off of <95% similarity in the 16S rRNA gene sequence, and a G+C (% mol) content differing by more than 10% (Rosselló-Mora and Amann, 2001;Yarza et al., 2008;Tindall et al., 2010;Yarza et al., 2014). Nowadays, genomic data like the Average Nucleotide Identity (ANI) and the in silico DNA–DNA hybridization (isDDH) are used to define bacterial species, although have not yet been fully explored for delineating genera (Konstantinidis and Tiedje, 2005; Goris et al., 2007;Richter and Rosselló-Móra, 2009;Qin et al., 2014;Chun et al., 2018). A percentage of Average Amino-acid Identity (AAI) ranging from 60 to 80% between the compared genomes of species or strains and a Percentage of Conserved Proteins (POCPs) above 50% has been proposed if they are to belong to the same genus (Konstantinidis and Tiedje, 2005;Qin et al., 2014). Finally, the Relative Synonymous Codon Usage (RSCU) has also been used by some authors to infer evolutionary and ecological links among bacterial species (Ma et al., 2015;Farooqi et al., 2016). Very recently, Waite et al. (2017) carried out a comparative genomic analysis of the class Epsilonproteobacteria. Using 16S and 23S rRNA, 120 single-copy marker proteins and AAI analysis they proposed its reclassification as the new phylum Epsilonbacteraeota. In that study, Waite et al. (2017) also proposed a reclassification of the genus Arcobacter as a new Frontiers in Microbiology | www.frontiersin.org 2September 2018 | Volume 9 | Article 2077 fmicb-09-02077 September 1, 2018 Time: 10:25 # 3 Pérez-Cataluña et al. Revisiting the Taxonomy of the Genus Arcobacter Family Arcobacteraceae, within the class Campylobacteria, order Campylobacterales. One weakness of this study, specifically regarding the genus Arcobacter, is that only seven validated species were included in the analysis. The new family therefore comprised only the genus Arcobacter. However, these findings also support the need for a clarification of the taxonomy of the current genus Arcobacter. The rise of genome sequencing has dramatically changed the landscape of systematics of prokaryotes, improving different aspects such as the identification of species, the functional characterization for resolving taxonomic groups, and the resolution of the phylogeny of higher taxa (Whitman, 2015). It seems clear that the incorporation of genomics into the taxonomy will boost its credibility providing reproducible, reliable, highly informative means to infer phylogenetic relationships among prokaryotes, and avoiding unreliable methods and subjective difficult-to-replicate data (Chun and Rainey, 2014;Chun et al., 2018). Within this modern taxonomy context, the objective of the present study was to reassess the taxonomy of the known and newly recognized Arcobacter species by using a MLSA of 13 housekeeping genes, the whole genome sequences and the derived genomic analysis. The latter analysis included ANI, isDDH, AAI, POCP, and RSCU of all Arcobacter type strains. In addition, phylogenies based on 16S and 23S rRNA gene sequences were also performed with comparative purposes. The new taxonomic criteria were stable when including whole genome sequences of a second strain of each species or of unassigned sequences obtained from the public databases. MATERIALS AND METHODS Bacterial Strains All 27 valid species included in the genus Arcobacter have been studied. They are represented by 39 strains, and 13 strains that are potentially new species (Table 1). Furthermore, 50 genomes of Arcobacter strains identified at species level were investigated, 39 of which were obtained in our laboratory (27 from known species and 13 from potentially new species) and the others from the public databases1,2. Five genomes that had been deposited as Arcobacter sp. in the databases were also included in the study. If there was more than one strain of a known Arcobacter species, two representative genomes for each species were included in the analysis. The only exceptions were: A. acticola (Park et al., 2016) and A. pacificus (Zhang et al., 2015), whose taxonomic positions were only inferred by the phylogenetic analysis of the 16S rRNA gene sequences published in their species descriptions, together with a MLSA of three housekeeping genes (atpA, gyrB, and rpoB) for A. pacificus (Zhang et al., 2015;Park et al., 2016). The strains considered potentially new species, and named hereafter as ‘candidate species,’ had been recognized with an MLSA analysis of five housekeeping genes (atpA, gyrA, gyrB, hsp60, and rpoB) (data not shown). 1https://www.ncbi.nlm.nih.gov/genome/ 2https://gold.jgi.doe.gov/ Culturing for genome sequencing was carried out either on blood agar (DIFCO, Madrid, Spain) or marine agar (Scharlau, Sentmenat, Spain) at 30◦C in aerobiosis for 24–72 h, depending on the requirements. DNA was extracted using Easy-DNATM gDNA Purification kit (Invitrogen, Madrid, Spain) following the manufacturer’s instructions. The integrity of the DNA was evaluated by electrophoresis of 10 µl of the sample in a 1.5% agarose gel. The total amount of DNA was quantified using QubitTM with the dsDNA Broad Range Assay kit (Invitrogen). Paired-end libraries were constructed with 50 ng of DNA using Nextera DNA Library Preparation Kit (Illumina, Lisbon, Portugal) and sequenced with MiSeq platform (Illumina). Sequencing generated 2 ×300 bp paired-end reads. Clean reads were assembled with SPAdes (Nurk et al., 2013) and the CGE assembler (Larsen et al., 2012) in order to select the better assembly. Before depositing the genomes in the NCBI database, FASTA files were screened for eukaryotic and prokaryotic sequences using BLASTn, and for adaptors with VecScreen standalone software3. The five housekeeping genes used in the first MLSA analysis (atpA, gyrA, gyrB, hsp60, and rpoB) were extracted from each genome and compared with the Sanger sequences of these genes obtained originally for the identification of the strain. The existence of a single and identical copy of these genes confirmed that the genomes were not contaminated and belonged to the correct strain. Finally, contigs were deleted if they had less than 200 bp. The genomes were deposited in the GenBank database and Table 1 lists the accession numbers. The 55 genomes were annotated with a local installation of Prokka v1.2 (Seemann, 2014) using an e-value of 1e-06. The annotation was performed with Prokka, with the prediction tools Prodigal v2.6 (Hyatt et al., 2010) and ARAGORN v1.2 (Laslett and Canback, 2004). The prediction tool Barrnap v0.64included in Prokka v1.2 was used for the annotation of rRNA genes. Coding sequences (CDS) were annotated, combining the Rapid Annotation Subsystems Technology (RAST) (Overbeek et al., 2014) using the classic RAST scheme and the Annotation Tools of PATRIC server (Wattam et al., 2017). The characteristics of each genome (i.e., N50, number of contigs, number of CDS, G+C content) were obtained from NCBI annotations. Analysis of Housekeeping Genes, Ribosomal Genes, and Core Genome Thirteen housekeeping genes (atpA, atpD, dnaA, dnaJ, dnaK, ftsZ, gyrA, hsp60, radA, recA, rpoB, rpoD, and tsf ) were obtained from the genomes using BLASTn search. Sequence similarities of housekeeping genes were determined using the MegAlign program (DNASTARR , Madison, WI, United States). Genes were aligned using ClustalW (Larkin et al., 2007) and phylogenies based on individual genes and on the concatenated sequences was constructed with MEGA version 6.0 (Tamura et al., 2013) using the Neighbor-Joining (NJ) and Maximum-Likelihood (ML) algorithms. 3ftp://ftp.ncbi.nlm.nih.gov/blast/demo/ 4http://www.vicbioinformatics.com/software.barrnap.shtml Frontiers in Microbiology | www.frontiersin.org 3September 2018 | Volume 9 | Article 2077 fmicb-09-02077 September 1, 2018 Time: 10:25 # 4 Pérez-Cataluña et al. Revisiting the Taxonomy of the Genus Arcobacter The phylogenetic analysis of the core genome was assessed with the Roary software (Page et al., 2015) using 80% as cut-off for the BLASTp search. The core genome alignment was extracted with the latter software and the phylogeny was inferred using SplitsTree version 4.14.2 as described in Sawabe et al. (2007) using SplitsTree version 4.14.2, with a neighbor net drawing and JukesCantor correction (Bandelt and Dress, 1992;Huson and Bryant, 2005). Furthermore, the 16S and 23S rRNA genes of each genome were obtained using RNammer (Lagesen et al., 2007). In some cases, 16S rRNA gene sequences were obtained in our laboratories by Sanger sequencing or from the GenBank. The similarity of the 16S rRNA genes was calculated using MegAlign version 7.0.0 (DNASTARR , Madison, WI, United States). Phylogenetic trees were reconstructed with MEGA version 6.0 (Tamura et al., 2013) also using the NJ and ML algorithms. Alignments obtained for both genes were visually analyzed in order to localize signature sequences for strains or groups of strains. Genomic Indices In order to ensure the correct assignation at species level of each analyzed genome, the ANI and the isDDH were calculated between all the genomes (Konstantinidis and Tiedje, 2005; Richter and Rosselló-Móra, 2009;Qin et al., 2014). The ANIb was calculated using JSpeciesWS (Richter et al., 2016), the resulting matrix was clustered and visualized using ggplot2 2.2.1 package (Wickham, 2009) and the isDDH was calculated with the GGDC software using results obtained with the formula 2 (Meier-Kolthoff et al., 2013). Two other indices (AAI and POCP) described for genus classification (Konstantinidis and Tiedje, 2005;Luo et al., 2014;Qin et al., 2014) were calculated among the genomes that corresponded to the type strains of the accepted species and the reference strains of the candidate species. The AAI was calculated with the Lycoming College Newman Lab AAIr Calculator5using the Sequence-Based Comparison Tools output file from RAST (Overbeek et al., 2014). The POCP was determined as described by Qin et al. (2014) using the following parameters to consider a peptide as a conserved protein: an e-value lower than 1e-5 and an identity percentage higher than 40% from an aligned region higher than 50%. Finally, the RSCU was computed using the Codon Adaptation Index (CAI) developed by Sharp and Li (1987) through the CAIcal web-server (Puigbò et al., 2008). Statistical differences in the RSCU were assessed by a multinomial regression approach using the R software environment (R Core Team, 2015). The principal component analysis (PCA) was performed by the R software environment (R Core Team, 2015, and visualized using ggplot2 2.2.1 and ggfortify 0.4.4 (Wickham, 2009;Horikoshi and Tang, 2015;Tang et al., 2016) or pca3d 0.10 (Weiner, 2017) packages. Phenotypic Analysis and Metabolic Inference Phenotypic characterization of each described species was obtained from this study, from the original descriptions or from 5http://lycofs01.lycoming.edu/∼newman/AAI/ the summary published by On et al. (2017). For the potentially new Arcobacter species, the phenotype was characterized following the recommended minimal standards described for new taxa of the family Campylobacteraceae (Ursing et al., 1994; On et al., 2017) and with complementary tests used in the description of other Arcobacter species (Levican et al., 2013). Inference of the metabolic routes from the genome sequences was performed with the software package Traitar (Microbial Trait Analyzer) (Weimann et al., 2016), using the protein coding genes files obtained with Prokka v1.2 (Seemann, 2014). Traitar software is based on phenotypic data extracted from the Global Infectious Disease and Epidemiology Online Network (GIDEON) and Bergey’s Systematic Bacteriology. The software uses two prediction models: the phypat classifier, which predicts the presence/absence of proteins found in the phenotype of 234 bacterial species; and the phypat+PGL classifier, which uses the same information as the phypat combined with the information of the acquisition and loss of protein families and phenotypes during evolutive events. A total of 67 traits available within the software, related to oxygen requirement, enzymatic activities, proteolysis, antibiotic resistance, morphology and motility and the use of different carbon sources, were tested and the combined results of the two predictors were analyzed using a heat map. RESULTS AND DISCUSSION Strains and Genomes All the 27 species currently included in the genus Arcobacter and 13 candidate species have been investigated in the present study, which has analyzed 55 genomes, 16 of them from the public databases and 39 sequenced in this study (Tables 1,2). It was not possible to analyze the genomes from A. acticola and A. pacificus because we were unable to get the type strains of the species. The contigs obtained and the N50 values complied with the recently proposed minimal standards for the use of genomes in taxonomic studies (Chun et al., 2018). The genome size ranged from 1.81 Mb for A. skirrowii F28 to 3.60 Mb for A. lekithochrous CECT 8942T(Table 2). The G+C content ranged from 26.1% in A. molluscorum CECT 7696Tto 34.9% in ‘A. aquaticus’ W112-28. The G+C values agree with the range from 24.6% (which corresponded to the type strain of A. anaerophilus) to 31% indicated for the genus Arcobacter in the recent emended description by Sasi-Jyothsna et al. (2013). Interestingly, 26 genomes (47.3%) showed the presence of Clustered Regularly Interspaced Short Palindromic Repeats (CRISPRs) and CRISPRassociated genes, related with the immune response of the bacteria. Taxonomic and Phylogenetic Analysis Similarities in the 16S rRNA gene sequences among type and representative strains of the different Arcobacter species (all the 27 species currently included in the genus and the 13 new candidate species) showed a wide range of values (Supplementary Tables S1, S4). They ranged from 90.8% (observed between A. anaerophilus and A. faecis) to 99.9% (between A. butzleri and ‘A. lacus’). The lower range of Frontiers in Microbiology | www.frontiersin.org 4September 2018 | Volume 9 | Article 2077 fmicb-09-02077 September 1, 2018 Time: 10:25 # 5 Pérez-Cataluña et al. Revisiting the Taxonomy of the Genus Arcobacter TABLE 1 | Strains used in this study, source of isolation and accession numbers of the available genomes. Species Strain Source Acc. No. Genome Species Strain Source Acc. No. Genome A. acticola KCTC 52212TSeawater NAaA. mytili T234 Seawater PDJW00b A. anaerophilus DSM 24636TEstuarine sediment PDKO00bA. nitrofigilis DSM7299TMarshland plant NC014166c IR-1 Utsira aquifer NZ_JXXG00cA. pacificus DSM 25018TSeawater NAa A. aquimarinus CECT 8442TMediterranean Sea NXIJ00bA. skirrowii LMG 6621TDiarrheic lamb NXIC00b A. bivalviorum CECT 7835TMussels PDKM00bF28 Wild pig PDJT00b F118-4 Mussels PDKL00bA. suis CECT 7833TPork meat NREO00b A. butzleri RM4018THuman (Clinical) NC_009850cA. thereius LMG 24486TAborted pig foetus LLKQ01c ED1 Microbial fuel cell NC_017187cDU22 Duck cloaca LCUJ01c A. canalis F138-33 Oyster PNCeNWVW01bA. trophiarum LMG 25534TPiglet feces PDKD00b SH-4D_Col1 Unknown FUYO00cCECT 7650 Chicken cloacal swab PDJS00b A. cibarius LMG 21996TBroiler, skin NZ_JABW00cA. venerupis CECT 7836TClams NREP00b A. cloacae CECT 7834TSewage NXII00bArcobacter sp. L Microbial fuel cell NC_017192c F26 Mussels PDJZ00bAF1028 Human feces JART01c A. cryaerophilus LMG 24291TAborted bovine foetus NXGK00bCAB Marine Go0012496d A. defluvii CECT 7697TSewage NXIH00bLA11 Marine BDIR01c A. ebronensis CECT 8441TMussels PDKK00bLPB0137 Environmental CP019070c CECT 8993 Seawater PDKJ00b A. ellisii CECT 7837TMussels NXIG00b‘A. aquaticus’ W112-28 Freshwater PNCePDKN00b A. faecis LMG 28519THuman septic tank NZ_JARS00c‘A. caeni’ RW17-10 Recycled wastewater MUXE00b A. halophillus DSM 18005THypersaline lagoon PDJY00b‘A. hispanicus’ FW-54 Wastewater PDKI00b F166-45 Oyster PNCePDJY00b‘A. lacus’ RW43-9 Recycled wastewater MUXF00b A. lanthieri LMG 28516TPig manure JARU01c‘A. mediterraneus’ F156-34 Mussels Alfacs Bay NXIE00b LMG 28517 Dairy cattle manure JARV01c‘A. miroungae’ 9AntfCloaca elephant seal PDKH00b A. lekithochrous CECT 8942TGreat scallop larvae NZ_MKCO00b‘A. neptunis’ F146-38 Mussels Alfacs Bay PDKG00b LMG 28652 Abalon PZYW00c‘A. porcinus’ LMG 24487TAborted pig foetus LCUH01c A. marinus CECT 7727TSeawater NXAO01b‘A. ponticus’ F161-33 Cockle Alfacs Bay PDKF00b F140-37 Clams Alfacs Bay NWVX01b‘A. salis’ F155-33 Oyster PNCePDKE00b A. molluscorum CECT 7696TMussels NZ_NXFY00b‘A. viscosus’ F142-34gMussels PNCePDKC00b F91 Mussels PDJX00b‘A. vitoriensis’ FW59gWastewater PDKB00b A. mytili CECT 7386TMussels NXID00bArcobacter sp. F2176 Mussels PDJV00b aGenome not available; bGenome sequenced in this study; cGenome obtained from NCBI database; dGenome obtained from JGI Gold atabase; ePNC means PobleNou Channel, which is a freshwater channel heavily (geometric mean of E. coli counts 4.1 ×104c.f.u./100ml) contaminated with wastewater where shellfish were exposed for 72h (Salas-Massó et al., 2016, 2018). fThis strain was obtained from F.J. García from the Laboratorio Central de Veterinaria de Algete, MAGRAMA, Madrid, Spain; gThese strains were recovered at the Faculty of Pharmacy, University of the Basque Country (UPV-EHU), Vitoria-Gasteiz, Spain, by R. Alonso, I. Martinez-Malaxetxebarria and A. Fernández-Astorga. similarity (90.8%) is due to the fact that those species, as occurred with others, were assigned within the genus based on the premise that 16S rRNA gene similarity was higher with any type strain of Arcobacter than with other taxa. However, in some cases being below the 95% cut-off value for genus delimitation (Rosselló-Mora and Amann, 2001;Yarza et al., 2008; Tindall et al., 2010;Figueras et al., 2011a,b). It is interesting to point out that 16S rRNA gene sequence similarities among A. nitrofigilis, the type species of the genus, and the other described species ranged from 93.2% (with A. thereius) to 95.9% (with A. venerupis). Furthermore, A. nitrofigilis showed higher similarities than the threshold value of 95% with only seven species (A. acticola, ‘A. caeni,’ A. cloacae,A. defluvii, A. ellisii, A. suis, and A. venerupis) out of the 27 accepted species. In any case, from the analysis of the similarities in the 16S rRNA gene sequences among the Arcobacter species it is clear that this gene has limited value and that other approaches available in the genomic era of taxonomy are needed for their study. Phylogenetic analysis based on the core genome made up of 286 genes (Figure 1 and Supplementary Table S5) and also on the concatenated sequences of 13 housekeeping genes of the representative Arcobacter strains (Figure 2) revealed that the Arcobacter species could be grouped into 4 major monophyletic clusters. Cluster 1, comprised seven validated species: A. butzleri,A. cibarius,A. cryaerophilus,A. lanthieri, A. skirrowii,A. thereius, and A. trophiarum, together with A. faecis (species described but not validated yet) and five candidate taxa ‘A. hispanicus,’ ‘A. lacus,’ ‘A. miroungae,’ ‘A. porcinus,’ and ‘A. vitoriensis’ (Figure 1). Cluster 2 embraced the species A. aquimarinus,A. cloacae,A. defluvii,A. ellisii, A. suis, and A. venerupis, as well as the non-validated A. acticola and the candidatus ‘A. caeni.’ Cluster 3 included five species, A. canalis,A. halophilus,A. marinus,A. molluscorum, Frontiers in Microbiology | www.frontiersin.org 5September 2018 | Volume 9 | Article 2077 fmicb-09-02077 September 1, 2018 Time: 10:25 # 6 Pérez-Cataluña et al. Revisiting the Taxonomy of the Genus Arcobacter TABLE 2 | Genome characteristics and annotation results. Source of whole genome sequences as indicated in Table 1. Species No. Contigs N50 (Kb) CDS (Total) CDS (Coding) RNA Genes tRNAs ncRNAs CRISPR Arrays G+C (%) Size (Mb) A. anaerophilus DSM 24636T40 186 2,938 2,922 45 40 2 1 29.9 2.98 A. anaerophilus IR1 7 1,179 3,360 3,024 61 47 2 3 30.2 3.25 ‘A. aquaticus’ W112-28T20 370 2,500 2,487 55 45 3 0 34.9 2.53 A. aquimarinus CECT 8442T68 75 2,473 2,463 46 42 2 0 26.6 2.46 A. bivalviorum CECT 7835T179 461 2,786 2,728 50 41 3 0 28.2 2.75 A. bivalviorum F118-4 26 209 2,652 2,652 47 38 3 0 28.1 2.71 A. butzleri RM4018T1 – 2,261 2,256 71 54 2 0 27.0 2.34 A. butzleri ED1 1 – 2,151 2,145 71 54 2 0 27.1 2.26 ‘A. caeni RW17-10T59 123 2,357 2,337 58 51 3 0 27.1 2.42 A. canalis CECT8984T50 166 2,733 2,720 53 48 2 1 27.3 2.78 A. canalis SH-4D_Col1 69 72 2,716 2,663 63 52 2 1 27.1 2.82 A. cibarius LMG 21996T44 119 2,156 2,110 68 46 2 0 27.1 2.20 A. cloacae CECT 7834T135 135 2,826 2,795 58 51 2 3 26.8 2.78 A. cloacae F26 40 218 2,470 2,459 53 44 2 1 26.9 2.51 A. cryaerophilus LMG 24291T91 54 2,092 2,081 49 40 3 0 27.2 2.06 A. defluvii CECT 7697T80 166 2,921 2,894 57 49 2 2 26.3 2.94 A. ebronensis CECT 8441T103 188 3,089 3,072 47 39 3 1 29.2 3.15 A. ebronensis W129-34 126 217 3,206 3,171 46 40 3 2 29.2 3.23 A. ellisii CECT 7837T135 177 2,875 2,840 64 52 2 1 26.9 2.80 A. faecis LMG 28519T55 127 2,429 2,376 76 53 2 1 27.2 2.50 A. halophilus DSM 18005T111 56 2,677 2,660 54 46 3 2 27.4 2.75 A. halophilus F166-45 90 56 2,879 2,864 59 51 2 2 27.0 2.96 ‘A. hispanicus’ FW54T76 148 2,228 2,207 46 40 3 1 26.4 2.21 ‘A. lacus’ RW43-9T24 295 2,194 2,182 47 40 2 0 26.8 2.22 A. lanthieri LMG 28516T29 466 2,223 2,190 73 52 3 1 26.7 2.29 A. lanthieri AF1581 24 353 2,199 2,186 88 57 3 0 26.8 2.26 A. lekithochrous CECT 8942T436 343 3,628 3,316 88 75 3 0 28.6 3.61 A. lekithochrous LMG 28652 82 343 3,499 3,330 61 55 3 0 28.2 3.50 A. marinus CECT 7727T162 54 2,809 2,781 55 50 2 0 27.0 2.87 A. marinus F140-37 76 67 2,725 2,652 59 48 2 0 27.0 2.78 ‘A. mediterraneus’ F156-34T29 689 2,769 2,750 47 41 3 1 27.3 2.83 ‘A. miroungae’ 9AntT35 363 1,868 1,847 46 41 2 1 28.1 1.84 A. molluscorum CECT 7696T117 121 2,746 2,736 58 49 3 6 26.1 2.76 (Continued) Frontiers in Microbiology | www.frontiersin.org 6September 2018 | Volume 9 | Article 2077 fmicb-09-02077 September 1, 2018 Time: 10:25 # 7 Pérez-Cataluña et al. Revisiting the Taxonomy of the Genus Arcobacter TABLE 2 | Continued Species No. Contigs N50 (Kb) CDS (Total) CDS (Coding) RNA Genes tRNAs ncRNAs CRISPR Arrays G+C (%) Size (Mb) A. molluscorum F91 240 150 2,951 2,889 71 58 3 2 26.3 2.89 A. mytili CECT 7386T126 70 2,950 2,934 58 48 3 1 26.3 2.97 A. mytili T234 145 37 2,735 2,723 54 48 3 0 26.4 2.77 ‘A. neptunis’ F146-38T36 267 2,627 2,614 57 45 3 0 27.1 2.65 A. nitrofigilis DSM 7299T1 – 3,101 3,086 69 55 2 1 28.4 3.19 ‘A. ponticus’ F161-33 24 597 2,632 2,621 46 36 3 0 28.1 2.74 ‘A. porcinus’ LMG 24487T70 123 2,186 2,112 47 41 2 0 27.0 2.14 ‘A. salis’ F155-33T153 169 2,932 2,904 50 43 3 0 29.0 2.93 A. skirrowii LMG 6621T62 306 2,029 2,006 48 42 2 2 27.7 1.97 A. skirrowii F28 110 40 1,911 1,897 46 41 2 0 27.8 1.81 A. suis CECT 7833T122 142 2,646 2,613 57 52 2 0 27.3 2.62 A. thereius LMG 24486T2 1,039 1,896 1,883 57 46 2 3 27.0 1.91 A. thereius DU22 19 252 2,006 1,983 47 42 2 1 26.8 2.01 A. trophiarum CECT 7650 37 152 1,911 1,894 48 37 3 0 28.0 1.90 A. trophiarum LMG 25534T266 86 2,167 2,071 49 41 3 0 29.4 2.00 A. venerupis CECT 7836T234 182 3,319 3,267 64 52 2 0 28.0 3.28 ‘A. viscosus’ F142-34T82 65 2,772 2,756 55 48 3 1 26.6 2.79 ‘A. vitoriensis’ FW59T144 179 2,617 2,570 53 46 2 0 27.4 2.58 Arcobacter sp. CAB 367 20 3,596 3,392 NA 31 NA NA 28.2 3.48 Arcobacter sp. F2176 99 178 3,212 3,186 67 57 2 0 28.1 3.27 Arcobacter sp. LA11 53 229 3,006 2,961 49 43 3 0 27.9 3.10 Arcobacter sp. LPB0137 1 – 2,731 2,698 85 64 2 0 27.7 2.87 Arcobacter sp. La1 – 2,847 2,834 73 56 2 1 26.6 2.95 Arcobacter sp. AF1028b46 148 2,336 2,285 71 51 2 1 27.2 2.41 aGenome sequenced in this study; bGenome obtained from NCBI database; cGenome obtained from JGI Gold database. Our results show that these strains belong to the species. dA. defluvii and eA. faecis. Frontiers in Microbiology | www.frontiersin.org 7September 2018 | Volume 9 | Article 2077 fmicb-09-02077 September 1, 2018 Time: 10:25 # 8 Pérez-Cataluña et al. Revisiting the Taxonomy of the Genus Arcobacter and A. mytili, together with two candidates, ‘A. neptunis’ and ‘A. viscosus.’ Finally, Cluster 4 included the species A. anaerophilus,A. bivalviorum, and A. ebronensis, as well as the candidates ‘A. mediterraneus,’ ‘A. ponticus,’ and ‘A. salis.’ The split decomposition network analysis of the core genome showed that the species A. lekithochrous CECT 8942Tand A. nitrofigilis DSM 7299Tappeared as orphan species. Furthermore, with this analysis the candidatus ‘A. aquaticus’ W112-28 also appeared in a separate branch near to A. nitrofigilis DSM 7299T. On the other hand, both analyses, MLSA and core genome, confirmed the existence of two sub-clusters in Cluster 1 (again A. butzleri and ‘A. lacus’ were located in the most distant branch within the cluster), and also two subgroups could be observed in Cluster 4, one comprising the species A. anaerophilus and A. ebronensis, and the other including the rest of species within this cluster (Figures 1,2). All the clusters and sub-clusters showed a similarity in the concatenated sequences of the 13 housekeeping genes higher than 85% (Figure 2). Phylogenies based on the 16S and 23S rRNA gene sequences, undertaken with the NJ and ML approacheserealso constructed with comparative purposes. 16S rRNA based tree showed also the four major clusters although less defined (Supplementary Figure S1A). Species within Cluster 1, showed 16S rRNA gene sequence similarities ranging from 96.1 to 99.9%. Cluster 2 yielded similarities among species for the 16S rRNA gene between 96.7 and 99.6%, whereas within Cluster 3 ranged between 93.0 and 99.1%. Finally, Cluster 4 included species with a range of 16S rRNA sequence similarity from 94.0 to 99.5%. With the exception of Cluster 3, similarity values within the clusters (>94–95%) were within the classical boundaries for genus assignation in bacterial taxonomy (Rosselló-Mora and Amann, 2001;Yarza et al., 2008, 2014;Tindall et al., 2010;Figueras et al., 2011a,b). Our results agree with those from a recent study by Yarza et al. (2014), who investigated 568 taxa and described a threshold in 16S rRNA sequence identity of 94.5% for genus delineation. Similar groups and topology, with only minor differences, were obtained when the 23S rRNA gene sequences were used to analyze the phylogeny of the genus (Supplementary Figure S2). In this analysis, the recently described species A. acticola, and A. pacificus could not be included because of the unavailability of the type strains and/or whole genome sequences. The same four major clusters formed in the 23S rRNA gene phylogenetic tree, and the species A. lekithochrous and A. nitrofigilis appeared also as orphan species (Supplementary Figure S2). Within Cluster 1 two subgroups could also be obtained, differentiating the species A. butzleri and ‘A. lacus’ from the rest of the species. Similarly, the species A. anaerophilus and A. ebronensis formed a differentiated subgroup in Cluster 4. The visual analysis of the alignments obtained with the sequences of the 16S and 23S rRNA genes allowed the localization of signature motifs, especially in the 16S rRNA gene, for the different clusters established in the phylogenetic analysis. In these sequences, a total of 16 locations were found, presenting nucleotide combinations characteristic for the clusters (Supplementary Figure S3). Some of these motifs were located in helix regions as interactions with proteins of the ribosomal 30S subunit, such as helix 21 (region V4) or helix 28/44 (region V9), and therefore had a considerable level of protection against mutations (Adilakshmi et al., 2008;Kitahara et al., 2012). There are some studies on the presence of signature regions with taxonomic/phylogenetic implications in the ribosomal genes (Martínez-Murcia et al., 1992, 2007;Ue et al., 2011;ˇ Reháková et al., 2014;Martínez-Murcia and Lamy, 2015). Some regions with signature motifs detected in the present study have also shown implications for phylogenetic analysis in cyanobacteria, including regions H15, H17, H21, H22-H23, H41, and H44 (ˇ Reháková et al., 2014). A tree was also constructed weighting such positions (Supplementary Figure S1B), which allowed a better definition of the main clusters observed with the whole 16S rRNA sequences although, as expected, differentiation among species within each cluster was lower. Two sub-clusters were observed in Cluster 1, where the species A. butzleri and ‘A. lacus’ grouped into a well-differentiated branch with respect to the other species in the cluster (Supplementary Figure S1B). In this analysis, A. pacificus was clearly located in the Cluster 3, whereas in Cluster 4, A anaerophilus was the borderline species, while A. ebronensis and ‘A. mediterraneus’ were located in an independent branch (Supplementary Figure S1B). Therefore, the signature motifs described here might be a new tool for identification of the different clusters and/or genus. Genomic Indices The results of the calculations of the ANI and the isDDH among the 36 studied genomes are given in the Supplementary Table S2 and Supplementary Figure S4. The results of the ANI and isDDH calculations showed that the genomes grouped into the same clusters observed by the analyses of the MLSA of the 13 housekeeping and core genes (Figures 1,2). Ranges of ANI within each cluster were from 75.2 to 95.4%, whereas isDDH values were between 19.5 and 65.4% (Figure 2 and Table 3). These results confirm the phylogenetic analysis for the 13 new candidate species because all of them showed ANI and isDDH values of <96% and <70%, respectively, which are the cut-off values proposed for the delineation of new species (Konstantinidis and Tiedje, 2005;Goris et al., 2007; Richter and Rosselló-Móra, 2009;Figueras et al., 2017). As discussed in other studies, the ANI and isDDH indices provided reliable information for the delineation of Arcobacter species and are also included in the minimal guidelines to define species using genomes (Whiteduck-Léveillée et al., 2015, 2016;Figueras et al., 2017;Chun et al., 2018). Although those indices are not considered useful for delimiting genera, each of the four clusters showed values that ranged between 75.2 and 81.8% as their lowest ANI, which might be the suitable range for separating different, closely related genera. These values are relatively similar to those reported by Qin et al. (2014) that found 68–82% interspecies ANI values among the genera that they studied. Values of ANI obtained for the candidate species ‘A. aquaticus’ were lower than the other results, from 70.0% with A. cryaerophilus LMG 24291T to 71.9% with A. bivalviorum CECT 7835Tand more in line with the Qin et al. (2014) results of 68% (Supplementary Table S2). In the case of the isDDH the lower values among species in the same cluster ranged between 19.5 and 24.8%, and again these might be the levels associated to different genera. Frontiers in Microbiology | www.frontiersin.org 8September 2018 | Volume 9 | Article 2077 fmicb-09-02077 September 1, 2018 Time: 10:25 # 9 Pérez-Cataluña et al. Revisiting the Taxonomy of the Genus Arcobacter FIGURE 1 | Split decomposition network constructed with the concatenated sequences of 284 core genes from the genomes of 36 type and representative strains of Arcobacter. Scale bar, base substitutions per site. With the aim of confirming if the clusters observed might represent different genera, as suggested by the phylogenetic analyses, the similarity indices AAI and POCP were also calculated (Supplementary Table S3). In agreement with the 60–80% AAI that have been described for species belonging to the same genus (Konstantinidis and Tiedje, 2005) all our clusters showed lower ranges of between 67.6 to 80.3% (Table 3). All the clusters also complied with the POCP proposed for genus separation above 50% (Luo et al., 2014;Qin et al., 2014) because as shown in Table 3 all clusters showed the lowest values from 67.0 to 75.4%. It is widely known that synonymous codon usage varies among organisms and that it is related to differences in G+C content, replication strand skew, or gene expression (Suzuki et al., 2008;Farooqi et al., 2016). The interaction of these factors may vary among species depending on their evolutionary process (Ma et al., 2015). It has also been suggested that the extent of codon usage bias plays a role in the adaptation of prokaryotic organisms to their environments and lifestyles (Botzman and Margalit, 2011). To analyze the overall codon usage trends of the Arcobacter species, the frequencies of the different codons were obtained from the whole genomes and the RSCU was computed using the CAI, which is a useful tool for estimating codon usage bias (Ma et al., 2015;Farooqi et al., 2016). A first finding was that all the Arcobacter species presented a preferential use of the codons finishing in A or T (Supplementary Figure S5), which might be expected due to their low G+C% content. The characteristic pattern showed by A. aquaticus is noteworthy (Supplementary Figure S5), which supports its differentiation from the other species in Cluster 3 as well as its unique taxonomy. Such difference was the only statistically significant (p<0.05) in the multinomial regression analysis carried out. Next, the codon usage trends were analyzed by PCA to reveal possible evolutionary relationships. Interestingly, different groups of strains could be observed in the threedimensional graphic (Figure 3), which correlated with those clusters established in the different phylogenetic analyses, as shown above. As reported previously for different species of Mycoplasma (Marenda et al., 2005;Ma et al., 2015), PCA provides an additional pathway to investigate the evolutionary direction of the Arcobacter species. In addition, similarities in the synonymous codon usage patterns might reflect similar lifestyles (pathogenic vs. non-pathogenic) and adaptation to certain environments (marine water, shellfish, etc.). Metabolic Inference and Phenotypic Analysis Phylogenetic and genomic analysis confirmed the existence of four clusters among the validated and candidate Arcobacter Frontiers in Microbiology | www.frontiersin.org 9September 2018 | Volume 9 | Article 2077 fmicb-09-02077 September 1, 2018 Time: 10:25 # 16 Pérez-Cataluña et al. Revisiting the Taxonomy of the Genus Arcobacter Description of Malacobacter canalis comb. nov. Basonym: Arcobacter canalis Pérez-Cataluña et al., 2018b. The description is the same given by Pérez-Cataluña et al. (2018b). The type strain is F138-33T(= CECT 8984T= LMG 29148T). Description of Malacobacter molluscorum comb. nov. Basonym: Arcobacter molluscorum Figueras et al., 2011a. The description is the same given by Figueras et al. (2011a). The type strain is F98-3T(= CECT 7696T= LMG 25693T). Description of Malacobacter pacificus comb. nov. Basonym: Arcobacter pacificus Zhang et al., 2015. The description is the same given by Zhang et al. (2015). The type strain is SW028T(= DSM 25018T = JCM 17857T= LMG 26638T). Description of Haloarcobacter gen. nov. Haloarcobacter (Ha.lo.ar.co.bac’ter, Gr. n. halo, salt; N.L. masc. n. Arcobacter, a bacterial generic name; N.L. masc. n. Haloarcobacter, Arcobacter salt loving). Gram-negative, cells are rod shaped and motile. Cell size 0.1– 0.5 µm in diameter and 0.9–2.5 µm in length. Oxidase positive and catalase variable among species. Halophilic, growth can be obtained within the range of 0.5% (variable among species) and up to 4% NaCl. Growth occurs at 15–42◦C. Growth at 37◦C in microaerophilic conditions or at 42◦C in anaerobiosis variable among species. Carbohydrates are not fermented. Some species may reduce nitrate to nitrite. Negative for the hydrolysis of urea (with the exception of H. ebronensis). Some species may hydrolyze indoxyl acetate. Growth does not occur in the presence of oxgall (1% wt/vol) (with the exception of H. molluscorum) or 2,3,5-triphenyltetrazolium chloride (0.04%, wt/vol). No growth on CCDA. Some species may grow in the presence of glycine (1% wt/vol) or safranin (0.05% wt/vol). Sensitive to cefoperazone (64 mg/l). Range of DNA G+C content is 27.3–29.9 mol%. The type species is Haloarcobacter bivalviorum. Description of Haloarcobacter bivalviorum comb. nov. Basonym: Arcobacter bivalviorum Levican et al., 2012. The description is the same given by Levican et al. (2012). The type strain is F4T(= CECT 7835T= LMG 26154T). Description of Haloarcobacter anaerophilus comb. nov. Basonym: Arcobacter anaerophilus Sasi-Jyothsna et al., 2013. The description is the same given by Sasi-Jyothsna et al. (2013). The type strain is JC84T(= KCTC 15071T= MTCC 10956T= DSM 24636T). Description of Haloarcobacter ebronensis comb. nov. Basonym: Arcobacter ebronensis Levican et al., 2015. The description is the same given by Levican et al. (2015). The type strain is F128-2T(= CECT 8441T= LMG 27922T). Description of Poseidonibacter gen. nov. Poseidonibacter (Po.se.i.do.ni.bac’ter, Gr. n. Poseidon, God of the sea; Gr. n. bacter, rod; N.L. masc. n. Poseidonibacter referring to the marine habitat of this bacteria). Gram-negative, cells are rod shaped and motile. Oxidase and catalase positive. Halophilic, no growth can be obtained without seawater or the addition of combined marine salts to the medium. Growth occurs at 15◦C–25◦C, but not at 37◦C or 42◦C. Range of pH for growth is 6–8. Carbohydrates are not fermented. Reduce nitrate to nitrite. Negative for the hydrolysis of indoxyl acetate and urea. Growth occurs in the presence of safranin (0.05% wt/vol), and 2,3,5-triphenyltetrazolium chloride (0.04%, wt/vol), but not in the presence of glycine (1% wt/vol) sensitive to cefoperazone (30 µg). Possess ubiquinone MK-6 as a respiratory quinone. DNA G+C content is 28.7 mol%. The type species is Poseidonibacter lekithochrous. Description of Poseidonibacter lekithochrous comb. nov. Basonym: Arcobacter lekithochrous Diéguez et al., 2017. The description is the same given by Diéguez et al. (2017). The type strain is LFT1.7T(= CECT 8942T= DSM 100870T). AUTHOR CONTRIBUTIONS MF and JR designed the work. AP-C, NS-M, and AD performed the phenotypic and phylogenetic experiments. AP-C and SB carried out the genome sequencing and analysis. AP-C, AL, and JR performed the bioinformatic work. JR, MF, AP-C, and AD wrote the paper. FUNDING This work was supported in part by Grants JPIW2013-69095C03-03 from the Ministerio de Economía y Competitividad (MINECO), AQUAVALENS of the Seventh Framework Program (FP7/2007-2013) grant agreement 311846 from the European Union and AGL2013-42628-R and AGL2016-77539-R (AEI/FEDER UE) from the Agencia Estatal de Investigación (Spain). ACKNOWLEDGMENTS The authors thank Dr. F. J. García (Laboratorio Central de Veterinaria de Algete, MAGRAMA, Madrid, Spain) and Drs. R. Alonso, I. Martinez-Malaxetxebarria, and A. Fernandez-Astorga [Faculty of Pharmacy, University of the Basque Country (UPVEHU), Vitoria-Gasteiz, Spain], for kindly providing some of the Frontiers in Microbiology | www.frontiersin.org 16 September 2018 | Volume 9 | Article 2077 fmicb-09-02077 September 1, 2018 Time: 10:25 # 17 Pérez-Cataluña et al. Revisiting the Taxonomy of the Genus Arcobacter Arcobacter strains. AP-C thanks Institut d’Investigació Sanitària Pere Virgili (IISPV) for her Ph.D. fellowship and NS-M thanks the Universitat Rovira i Virgili (URV), the Institut de Recerca i Tecnologia Agroalimentària (IRTA) and the Banco Santander for her Ph.D. fellowship. SUPPLEMENTARY MATERIAL The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fmicb. 2018.02077/full#supplementary-material REFERENCES Adilakshmi, T., Bellur, D. L., and Woodson, S. A. (2008). Concurrent nucleation of 16S folding and induced fit in 30S ribosome assembly. Nature 455, 1268–1272. doi: 10.1038/nature07298 Bandelt, H. J., and Dress, A. W. M. (1992). Split decomposition: a new and useful approach to phylogenetic analysis of distance data. Mol. Phylogenet. Evol. 1, 242–252. doi: 10.1016/1055-7903(92)90021-8 Botzman, M., and Margalit, H. (2011). 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Microbiol. 66, 542–547. doi: 10.1099/ijsem.0.000751 Conflict of Interest Statement: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. Copyright © 2018 Pérez-Cataluña, Salas-Massó, Diéguez, Balboa, Lema, Romalde and Figueras. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. Frontiers in Microbiology | www.frontiersin.org 19 September 2018 | Volume 9 | Article 2077