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      Noncontiguous finished genome sequence and description of Kallipyga gabonensis sp. nov.

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          Abstract

          Taxonogenomics coupled with culturomics promotes the isolation and characterization of bacteria. Kallipyga gabonensis sp. nov. strain GM4 is a strictly anaerobic, Gram-positive, and non motile coccus isolated from the stool of a Gabonese male teenager. The genome is 1,621,211 bp long with 50.01% G+C content and two scaffolds. Of the 1,536 predicted genes, 1,475 were protein-coding genes and 61 were RNA genes. A total of 931 genes were assigned a putative function, and 79 genes were identified as ORFans.

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          Digital DNA-DNA hybridization for microbial species delineation by means of genome-to-genome sequence comparison

          The pragmatic species concept for Bacteria and Archaea is ultimately based on DNA-DNA hybridization (DDH). While enabling the taxonomist, in principle, to obtain an estimate of the overall similarity between the genomes of two strains, this technique is tedious and error-prone and cannot be used to incrementally build up a comparative database. Recent technological progress in the area of genome sequencing calls for bioinformatics methods to replace the wet-lab DDH by in-silico genome-to-genome comparison. Here we investigate state-of-the-art methods for inferring whole-genome distances in their ability to mimic DDH. Algorithms to efficiently determine high-scoring segment pairs or maximally unique matches perform well as a basis of inferring intergenomic distances. The examined distance functions, which are able to cope with heavily reduced genomes and repetitive sequence regions, outperform previously described ones regarding the correlation with and error ratios in emulating DDH. Simulation of incompletely sequenced genomes indicates that some distance formulas are very robust against missing fractions of genomic information. Digitally derived genome-to-genome distances show a better correlation with 16S rRNA gene sequence distances than DDH values. The future perspectives of genome-informed taxonomy are discussed, and the investigated methods are made available as a web service for genome-based species delineation.
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            A polyphasic strategy incorporating genomic data for the taxonomic description of novel bacterial species.

            Currently, bacterial taxonomy relies on a polyphasic approach based on the combination of phenotypic and genotypic characteristics. However, the current situation is paradoxical in that the genetic criteria that are used, including DNA-DNA hybridization, 16S rRNA gene sequence nucleotide similarity and phylogeny, and DNA G+C content, have significant limitations, but genome sequences that contain the whole genetic information of bacterial strains are not used for taxonomic purposes, despite the decreasing costs of sequencing and the increasing number of available genomes. Recently, we diversified bacterial culture conditions with the aim of isolating uncultivated bacteria. To classify the putative novel species that we cultivated, we used a polyphasic strategy that included phenotypic as well as genomic criteria (genome characteristics as well as genomic sequence similarity). Herein, we review the pros and cons of genome sequencing for taxonomy and propose that the incorporation of genome sequences in taxonomic studies has the advantage of using reliable and reproducible data. This strategy, which we name taxono-genomics, may contribute to the taxonomic classification of bacteria.
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              Non-contiguous finished genome sequence and description of Anaerococcus senegalensis sp. nov.

              Introduction Anaerococcus senegalensis strain JC48T (= CSUR P156 = DSM25366) is the type strain of A. senegalensis sp. nov. This bacterium is a Gram-positive, anaerobic, indole-negative coccus that was isolated from the stool of a healthy Senegalese patient as part of a “culturomics” study aimed at cultivating individually all species within human feces. Defining bacterial species is a matter of debate. This is notably due to the elevated cost and poor reproducibility and inter-laboratory comparability of the “gold standard” DNA-DNA hybridization and G+C content determination [1]. In contrast, the development of PCR and sequencing methods is now widely available and cost-effective, which profoundly changes the way Archaea, Bacteria and are classified. Using 16S rRNA sequences with internationally-validated cutoff values enabled the taxonomic classification or reclassification of hundreds of taxa [2]. More recently, high throughput genome sequencing and mass spectrometric analyses of bacteria gave unprecedented access to a wealth of genetic and proteomic information [3]. As a consequence, we propose to use a polyphasic approach [4] to describe new bacterial taxa that includes their genome sequence, MALDI-TOF spectrum and main phenotypic characteristics (habitat, Gram-stain reaction, culture and metabolic characteristics, and when applicable, pathogenicity). The genus Anaerococcus (Ezaki et al. 2001) was created in 2001 [5]. To date, this genus, comprised of saccharolytic and butyrate-producing anaerobic and non-motile Gram-positive cocci, contains seven species including A. hydrogenalis (Ezaki et al. 1990) Ezaki et al. 2001, A. lactolyticus (Li et al. 1992) Ezaki et al. 2001, A. murdochii (Song et al. 2010), A. octavius (Murdoch et al. 1997) Ezaki et al. 2001, A. prevotii (Foubert and Douglas 1948) Ezaki et al. 2001, A. tetradius (Ezaki et al. 1983) Ezaki et al. 2001, and A. vaginalis (Li et al. 1992) Ezaki et al. 2001. Members of the genus Anaerococcus have mainly been isolated from the human vagina, but have also occasionally been identified in the nasal cavity, on the skin, and various infectious processes including ovarian, peritoneal, sacral, digital and cervical abscesses, vaginoses, bacteremias, foot ulcers, a sternal wound, and a knee arthritis [5-9]. In addition, uncultured bacteria with 16S rRNA sequences highly similar to members of the Anaerococcus genus have been detected in metagenomes from the human skin flora [10]. However, to the best of our knowledge, our report is the first to describe the isolation of a member of the genus Anaerococcus from the normal fecal flora. Here we present a summary classification and a set of features for A. senegalensis sp. nov. strain JC48T together with the description of the complete genomic sequencing and annotation. These characteristics support the circumscription of the species A. senegalensis. Classification and features A stool sample was collected from a healthy 16-year-old male Senegalese volunteer patient living in Dielmo (a rural village in the Guinean-Sudanian zone in Senegal), who was included in a research protocol. The patient gave an informed and signed consent, and the agreement of the National Ethics Committee of Senegal and the local ethics committee of the IFR48 (Marseille, France) were obtained under agreement 09-022). The fecal specimen was preserved at -80°C after collection and sent to Marseille. Strain JC48 (Table 1) was isolated in June 2011 by anaerobic cultivation on 5% sheep blood-enriched Columbia agar (BioMerieux, Marcy l’Etoile, France). This strain exhibited two distinct 16S rRNA sequences, with a 97.8% nucleotide sequence similarity with A. vaginalis, the phylogenetically closest validated Anaerococcus species (Figure 1). This value was lower than the 98.7% 16S rRNA gene sequence threshold recommended by Stackebrandt and Ebers to delineate a new species without carrying out DNA-DNA hybridization [2]. By comparison to the GenBank database [26] strain JC48 also exhibited nucleotide sequence similarities greater than 99% with uncultured bacterial clones detected in a metagenomic study of the human skin flora [10]. These bacteria are most likely classified within the same species as strain JC48 (Figure 1). Figure 1 Phylogenetic tree highlighting the position of Anaerococcus senegalensis strain JC48T relative to other type strains within the Anaerococcus genus. GenBank accession numbers are indicated in parentheses. For A. senegalensis, the two different 16S rRNA sequences were included. Sequences were aligned using CLUSTALW, and phylogenetic inferences obtained using the maximum-likelihood method within the MEGA software. Numbers at the nodes are bootstrap values obtained by repeating the analysis 500 times to generate a majority consensus tree. Peptoniphilus harei was used as outgroup. The scale bar represents a 2% nucleotide sequence divergence. Table 1. Classification and general features of Anaerococcus senegalensis strain JC48T MIGS ID      Property       Term      Evidence codea Domain Bacteria      TAS [11] Phylum Firmicutes      TAS [12-14] Class Clostridia      TAS [15,16]      Current classification Order Clostridiales      TAS [17,18] Family ClostridialesIncertae sedis XI      TAS [19] Genus Anaerococcus      TAS [5] Species Anaerococcus senegalensis      IDA       Type strain JC48T      IDA      Gram stain       Positive      IDA      Cell shape       Coccoid      IDA      Motility       Nonmotile      IDA      Sporulation       Nonsporulating      IDA      Temperature range       Mesophile      IDA      Optimum temperature       37°C      IDA MIGS-6.3      Salinity       Growth in BHI medium + 5% NaCl      IDA MIGS-22      Oxygen requirement       Anaerobic      IDA      Carbon source       Unknown      NAS      Energy source       Unknown      NAS MIGS-6      Habitat       Human gut      IDA MIGS-15      Biotic relationship       Free living      IDA MIGS-14      Pathogenicity     Biosafety level     Isolation       Unknown      2      Human feces      NAS MIGS-4      Geographic location       Senegal      IDA MIGS-5      Sample collection time       September 2010      IDA MIGS-4.1      Latitude       13.7167      IDA MIGS-4.2      Longitude       16.4167      IDA MIGS-4.3      Depth       Surface      IDA MIGS-4.4      Altitude       51 m above sea level      IDA Evidence codes - IDA: Inferred from Direct Assay; TAS: Traceable Author Statement (i.e., a direct report exists in the literature); NAS: Non-traceable Author Statement (i.e., not directly observed for the living, isolated sample, but based on a generally accepted property for the species, or anecdotal evidence). These evidence codes are from the Gene Ontology project [20]. If the evidence is IDA, then the property was directly observed for a live isolate by one of the authors or an expert mentioned in the acknowledgements. Different growth temperatures (25, 30, 37, 45°C) were tested; no growth occurred at 25°C and 45°C, growth occurred between 30 and 37°C, and optimal growth was observed at 37°C. Colonies were 0.5 mm to 1 mm in diameter on blood-enriched Columbia agar and Brain Heart Infusion (BHI) agar. Growth of the strain was tested under anaerobic and microaerophilic conditions using GENbag anaer and GENbag microaer systems, respectively (BioMérieux), and in the presence of air, with or without 5% CO2, and in aerobic conditions. Optimal growth was achieved anaerobically. Weak growth was observed in microaerophilic conditions and with 5% CO2.. No growth was observed in aerobic conditions. Gram staining showed Gram positive cocci. A motility test was negative. Cells grown on agar are Gram-positive (Figure 2) and have a mean diameter of 0.87 µm, and are mostly grouped in pairs, short chains or small clumps (Figure 3). Figure 2 Gram staining of A. senegalensis strain JC48T Figure 3 Transmission electron microscopy of A. senegalensis strain JC48T, using a Morgani 268D (Philips) at an operating voltage of 60kV. The scale bar represents 900 nm. Strain 48T exhibited catalase activity but not oxidase activity. Using API Rapid ID 32A, a positive reaction was obtained for urease, arginine dihydrolase, indole production, β glucuronidase, mannose fermentation, alkaline phosphatase, arginine arylamidase, leucyl glycine arylamidase, histidine arylamidase. A weak reaction was obtained for pyroglutamyl arylamidase. A. senegalensis is susceptible to penicillin G, imipeneme, amoxicillin + clavulanic acid, vancomycin, clindamycin and metronidazole. By comparison with A. vaginalis, strain 48T differed in urease and pyroglutamyl arylamidase production [5]. Matrix-assisted laser-desorption/ionization time-of-flight (MALDI-TOF) MS protein analysis was carried out as previously described [21]. Briefly, a pipette tip was used to pick one isolated bacterial colony from a culture agar plate, and to spread it as a thin film on a MTP 384 MALDI-TOF target plate (Bruker Daltonik, Leipzig, Germany). Four distinct deposits were done for strain JC48 from four isolated colonies. Each smear was overlaid with 2 µL of matrix solution (saturated solution of alpha-cyano-4-hydroxycinnamic acid) in 50% acetonitrile, 2.5% tri-fluoracetic-acid, and allowed to dry for five minutes. Measurements were performed with a Microflex spectrometer (Bruker). Spectra were recorded in the positive linear mode for the mass range of 2,000 to 20,000 Da (parameter settings: ion source 1 (IS1), 20 kV; IS2, 18.5 kV; lens, 7 kV). A spectrum was obtained after 675 shots at a variable laser power. The time of acquisition was between 30 seconds and 1 minute per spot. The four JC48 spectra were imported into the MALDI BioTyper software (version 2.0, Bruker) and analyzed by standard pattern matching (with default parameter settings) against the main spectra of 2,843 bacteria, including spectra from the seven validated Anaerococcus species used as reference data, in the BioTyper database. The method of identification included the m/z from 3,000 to 15,000 Da. For every spectrum, 100 peaks at most were taken into account and compared with the spectra in the database. A score enabled the identification, or not, from the tested species: a score > 2 with a validated species enabled the identification at the species level; a score > 1.7 but 100bp). Genome annotation Open Reading Frames (ORFs) were predicted using Prodigal [22] with default parameters but the predicted ORFs were excluded if they were spanning a sequencing GAP region. The predicted bacterial protein sequences were searched against the GenBank database and the Clusters of Orthologous Groups (COG) database using BLASTP. The tRNAScanSE tool [23] was used to find tRNA genes, whereas ribosomal RNAs were found by using RNAmmer [24] and BLASTn against the GenBank. ORFans were identified if their BLASTP E-value was lower than 1e-03 for alignment length greater than 80 amino acids. If alignment lengths were smaller than 80 amino acids, we used an E-value of 1e-05. Such parameter thresholds have already been used in previous works to define ORFans. To estimate the mean level of nucleotide sequence similarity at the genome level between Anaerococcus species, we compared the ORFs only using BLASTN at a query coverage of ≥ 70% and a minimum nucleotide length of 100 bp. Genome properties The genome is 1,790,835 bp long (one chromosome, no plasmid) with a 28.56% G + C content (Table 3). Of the 1,774 predicted genes, 1,721 were protein-coding genes, and 53 were RNAs. Two distinct copies of 16S rRNA, differing by two point mutations, were identified. A total of 1,296 genes (73.0%) were assigned a putative function. Fifty-one genes were identified as ORFans (3%). The remaining genes were annotated as hypothetical proteins. The distribution of genes into COGs functional categories is presented in Table 4. The properties and the statistics of the genome are summarized in Tables 3 and 4. Table 3 Nucleotide content and gene count levels of the genome Attribute     Value      %totala Genome size (bp)     1,790,835 100 DNA coding region (bp)     1,597,818 82.22 DNA G+C content (bp)     503,715 28.56 Total genes     1,774 100 RNA genes     53 3.0 Protein-coding genes     1,721 88.74 Genes with function prediction     1,296 73.0 Genes assigned to COGs     1,364 79.26 Genes with peptide signals     142 8.0 Genes with transmembrane helices     270 15.22 a) The total is based on either the size of the genome in base pairs or the total number of protein coding genes in the annotated genome. Table 4 Number of genes associated with the 25 general COG functional categories Code     Value     %age      Description J     132     7.67      Translation A     0     0      RNA processing and modification K     122     7.09      Transcription L     115     6.68      Replication, recombination and repair B     1     0.06      Chromatin structure and dynamics D     17     0.99      Cell cycle control, mitosis and meiosis Y     0     0      Nuclear structure V     63     3.66      Defense mechanisms T     45     2.61      Signal transduction mechanisms M     67     3.89      Cell wall/membrane biogenesis N     5     0.29      Cell motility Z     0     0      Cytoskeleton W     0     0      Extracellular structures U     19     1.10      Intracellular trafficking and secretion O     53     3.08      Posttranslational modification, protein turnover, chaperones C     87     5.06      Energy production and conversion G     112     6.51      Carbohydrate transport and metabolism E     104     6.04      Amino acid transport and metabolism F     54     3.14      Nucleotide transport and metabolism H     55     3.20      Coenzyme transport and metabolism I     31     1.80      Lipid transport and metabolism P     75     4.36      Inorganic ion transport and metabolism Q     16     0.93      Secondary metabolites biosynthesis, transport and catabolism R     170     9.88      General function prediction only S     121     7.03      Function unknown -     357     20.74      Not in COGs The total is based on the total number of protein coding genes in the annotated genome. Comparison with Anaerococcus prevotii To date, the genome from A. prevotii strain PC1T is the only genome from Anaerococcus species that has been sequenced [25]. By comparison with A. prevotii, A. senegalensis exhibited a lower G + C content (35.64% vs 28.56%, respectively) and a smaller number of genes (1,913 vs 1,774) and genes with peptide signals (337 vs 142). In contrast, A. senegalensis had higher ratios of genes per Mb (957 vs 990) and genes assigned to COGs (74.28% vs 79. 26%). However, the distribution of genes into COG categories (Table 4) was highly similar in both genomes. In addition, A. senegalensis shared mean nucleotide sequence similarities at the genome level of 76.6% (range 62.5-100%) and 75.4% (range 62.7-100%) with A. prevotii strains PC1T and ACS065-V-Col13 (GenBank accession number AEXM00000000), respectively. Conclusion On the basis of phenotypic, phylogenetic and genomic analyses, we formally propose the creation of Anaerococcus senegalensis sp. nov. that contains the strain JC48T. This bacterium has been found in Senegal. Description of Anaerococcus senegalensis sp. nov. Anaerococcus senegalensis (se.ne.gal.e′n.sis. L. gen. masc. n. senegalensis, pertaining to, or originating from Senegal, the country from which the specimen was isolated). Colonies are 0.5 mm to 1 mm in diameter on blood-enriched Columbia agar and Brain Heart Infusion (BHI) agar. Cells are coccoid with a mean diameter of 0.87 µm, occurring mostly in pairs, short chains or small clumps. Optimal growth is achieved anaerobically. Weak growth is observed in microaerophilic conditions and with 5% CO2. No growth is observed in aerobic conditions. Growth occurs between 30-37°C, with optimal growth observed at 37°C, in BHI medium + 5% NaCl. Cells stain Gram-positive, are non-endospore-forming, and non-motile. Catalase, urease, arginine dihydrolase, β glucuronidase, alkaline phosphatase, arginine arylamidase, leucyl glycine arylamidase, and histidine arylamidase activity are present. Mannose fermentation and indole production are also present. A weak reaction is obtained for pyroglutamyl arylamidase. Oxidase activity is absent. Cells are susceptible to penicillin G, imipeneme, amoxicillin + clavulanic acid, vancomycin, clindamycin and metronidazole. The G + C content of the genome is 28.56%. The type strain JC48T (= CSUR P156 = DSM 25366) was isolated from the fecal flora of a healthy patient in Senegal.
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                Contributors
                Journal
                New Microbes New Infect
                New Microbes New Infect
                New Microbes and New Infections
                Elsevier
                2052-2975
                14 November 2015
                January 2016
                14 November 2015
                : 9
                : 15-23
                Affiliations
                [1) ]Aix Marseille Université, URMITE, UM63, CNRS 7278, IRD 198, INSERM 1095, Marseille, France
                [2) ]Ecole Doctorale Régionale d’Afrique Centrale, Franceville, Gabon
                [3) ]Unité de Parasitologie Médicale (UPARAM), CIRMF, Franceville, Gabon
                [4) ]Département de Parasitologie Mycologie et de Médecine Tropicale, Laboratoire national de référence IST/sida, Faculté de Médecine, Université des Sciences de la Santé, Libreville, Gabon
                [5) ]Département de Microbiologie, Laboratoire national de référence IST/sida, Faculté de Médecine, Université des Sciences de la Santé, Libreville, Gabon
                [6) ]Special Infectious Agents Unit, King Fahd Medical Research Center, King Abdulaziz University, Jeddah, Saudi Arabia
                Author notes
                [] Corresponding author: J.-C. Lagier, Aix Marseille Université, URMITE, UM63, CNRS 7278, IRD 198, INSERM 1095, Marseille, France jclagier@ 123456yahoo.fr
                Article
                S2052-2975(15)00101-8
                10.1016/j.nmni.2015.11.007
                4706609
                26862430
                966d69c4-f714-4233-b020-6b922bbbf13a
                © 2015 The Authors

                This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

                History
                : 5 October 2015
                : 4 November 2015
                : 5 November 2015
                Categories
                Taxonogenomics: Genome of a New Organism

                culturomics,gabon,genome,kallipyga gabonensissp. nov.,taxonogenomics

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