Cubatão, o maior pólo industrial da américa latina também já foi uma das cidades mais poluídas do mundo. Os 30 anos de intensa atividade industrial vêm pressionando o meio ambiente com substâncias tóxicas e afetando gravemente a saúde da população. Dentre as substâncias contaminantes mais importantes da região estão os derivados de petróleo como o benzeno, tolueno, etilbenzeno e xilenos. Conhecidos como BTEX, eles são produzidos e utilizados em larga escala e a contaminação ocorre frequentemente através de vazamentos. Nos solos, devido à sua solubilidade em água, essas substâncias podem se espalhar por longas distâncias a partir do ponto afetado contaminando locais distantes. Já foi comprovada a capacidade de micro-organismos de sobreviver e até utilizar BTEX como fonte de carbono. Os micro-organismos adaptados catabolizam os contaminantes transformando-os em substâncias menos tóxicas e até mesmo eliminando-os do ambiente, capacidade de grande interesse econômico e ambiental. Nessa linha, nossa proposta visa o estudo das comunidades microbianas de solos afetados e não afetados por BTEX. Para isso foi utilizada a metagenômica como abordagem de estudo identificando-se diferenças qualitativas e quantitativas nas estruturas microbianas de três diferentes locais do município de Cubatão, sendo um deles afetado diretamente por BTEX. Pelo método utilizado e aqui desenvolvido, foi possível identificar um panorama metabólico geral identificando-se genes relevantes e o potencial de degradação de hidrocarbonetos aromáticos de micro-organismos conhecidos e desconhecidos, revelando melhor o potencial metabólico dos solos identificados. Os resultados apresentados podem contribuir para um melhor entendimento da dinâmica in situ de uma comunidade microbiana afetada por BTEX assim como melhorar o conhecimento sobre a comunidade microbiana de um local altamente impactado como Cubatão. / Cubatão is the largest industrial site in Latin America and was in the past one of the most polluted cities in the world. 30 years of intense industrial activity has pushed environmental limits with toxic substances and has severely affected the inhabitants\' health. Among the contaminants found in the region, the petroleum derivatives benzene, toluene, ethylbenzene and xylenes are the most important. Known collectively as BTEX, they are produced and used at a large scale and contamination frequently occurs. Because it is highly soluble in water, when in soil BTEX can spread long distances from the original contamination site, thus affecting large areas. Some microorganisms are known to live in contaminated environments and use contaminants such as BTEX as a unique carbon source for energy production. They catabolize contaminants into less dangerous products or even eliminate them from environment, a feature which has great commercial and environmental interest. We therefore compared the microbial communities in soils which were affected and un-affected by BTEX contamination. To this end, we used a metagenomics approach and developed a comparison method to identify microorganisms and degradation potential of soils studied. We found qualitative and quantitative differences in microbial structures from three different sites in Cubatão County, one of which is contaminated with BTEX. We constructed a metabolic overview identifying important genes, degradation potential and microorganisms related to BTEX degradation. The results presented here could contribute to understanding the in situ dynamics of a BTEX affected microbial community as well as improving our knowledge of the microbial community of Cubatão, a highly environmentally impacted place.

Este trabalho teve como objetivo caracterizar a diversidade bacteriana presente em uma área de mineração. Os resultados mostraram que o filo mais abundante das bactérias classificadas foi o proteobacteria e 66% deste filo pertencem a classe betaproteobacteria. A diversidade de bactérias encontradas no solo de fora da mina mostrou-se diferente daquele encontrado dentro da mina, mostrando que a ação da mineração poderia ter modificado a comunidade microbiana nativa do local. Na tentativa de elucidar o mecanismo de resistência ao cobre presente nos isolados, foram escolhidas 2 cepas resistentes a altas concentrações de cobre: Acinetobacter sp. e Enterobacter sp. Os resultados de proteômica mostraram que as duas cepas possuem mecanismos diferentes de resistência. Acinetobacter teve a expressão de duas proteínas CopA e CopB em diferentes condições de cultivos (200 ppm de cobre 6h de cultivo; 24h e 72h de cultivo em 450 ppm de cobre). Com esses resultados foi possível elucidar que esta cepa tem o mesmo mecanismo de resistência encontrado em Enterococcus hirae, onde a proteína CopA tem como função o influxo de cobre e a proteína CopB o efluxo do excesso de cobre intracelular. Já a bactéria Enterobacter teve expressão apenas de proteínas de membranas e nenhuma proteína propriamente conhecida como de resistência à cobre. Este resultado foi corroborado por técnica de PCR, no qual não houve expressão para esse gene. Possivelmente as proteínas de membrana externa estão responsáveis pela homeostase do cobre realizada por esta cepa. / This work aimed to characterize the bacterial diversity present in a mining area. Results showed the most abundant phylum of the classified bacteria are proteobacteria and 66% of this phylum are class betaproteobacteria. The diversity of bacteria found in the soil outside the mine differed from those found within the mine, showing that the mining action may have modified the local microbial community. In an attempt to elucidate the mechanism of resistance to copper present in the isolates, two strains resistant to high concentrations of copper were chosen: Acinetobacter sp. and Enterobacter sp. Proteomics results showed these two strains have different mechanisms of resistance. Acinetobacter had the expression of two CopA and CopB proteins under different cultivation conditions (200 ppm of copper 6h of culture and 24h and also in 450 ppm of copper and 72h of culture). With these results it was possible to elucidate, this strain has the same mechanism of resistance found in Enterococcus hirae, which the CopA protein functions as the copper influx and the CopB protein the efflux of excess intracellular copper. On the other hand, Enterobacter bacterium had only membrane proteins, and no proteins known as copper resistance. This result was corroborated with PCR, where there was no expression for this gene. Possibly the outer membrane proteins are responsible for the copper homeostasis performed by this strain.

Vinyl chloride (VC) is a human carcinogen and common groundwater contaminant in the United States. Some of the indigenous bacteria can utilize VC for their growth, which is important for bioremediation. As previous studies have been majorly focused on VC-degrading bacteria in pure cultures, we initiated the study to investigate the microbial community structure and interactions in more complicated systems, such as mixed-pure cultures and groundwater enrichment cultures. Finally, we extended our study into the field by investigating the diversity and abundance of functional genes in VC-assimilating pathways at six contaminated sites. In our first study, Nocardioides was found to be the most dominant genus in Carver groundwater enrichment cultures via stable-isotope probing and 16S rRNA gene amplicon Illumina sequencing. As cross-feeding was observed, in the second study, mixed-pure culture experiment was conducted to explore the potential effects of VC-assimilating Nocardioides on other bacteria, which showed VC cometabolizer Mycobacterium strain JS622 would take up carbon from VC to sustain their growth when mixed with VC-assimilating Nocardioides sp. strain JS614. The third study was conducted with a different groundwater source from Fairbanks, AK, which again showed Nocardioides is dominant in the microbial community. A novel VC-assimilating Nocardioides sp. bacteria was isolated, named XL1. The putative genome of XL1 extracted from enrichment culture metagenome was 99% to 100% identical to strain JS614, with a plasmid genome bin similar to strain JS614 plasmid pNOCA01, though the morphology of strain XL1 was distinct from strain JS614. About 90% of the plasmid contigs could be mapped onto Nocardioides sp. strain JS614 plasmid with 100% identity, containing known aerobic ethene and VC degradation pathway genes encoding alkene monooxygenase and epoxyalkane: coenzyme M transferase (EaCoMT). Glutathione synthase and glutathione S-transferase genes, possibly involved in epoxide detoxification, were found in Polaromonas, Mesorhizobium and Pseudomonas-affiliated genome bins. The study also showed cultures adapted to VC faster after amended with ethene. The in-situ study (the fourth study) revealed 192 different EaCoMT T-RFs from six chlorinated ethene contamination sites via T-RFLP analysis, implicating higher EaCoMT diversity than previously known. Phylogenetic analysis revealed that a majority of the 139 cloned sequences (78.4%) grouped with EaCoMT genes found in VC- and ethene-assimilating Mycobacterium strains and Nocardioides sp. strain JS614. EaCoMT gene abundance was positively correlated with VC and ethene concentrations at the sites studied.

Les progrès technologiques des vingt dernières années ont permis l’avènement d'une biologie à haut-débit reposant sur l'obtention de données à grande échelle de façon automatique. Les statisticiens ont un rôle important à jouer dans la modélisation et l'analyse de ces données nombreuses, bruitées, parfois hétérogènes et recueillies à différentes échelles. Ce rôle peut être de plusieurs natures. Le statisticien peut proposer de nouveaux concepts ou méthodes inspirées par les questions posées par cette biologie. Il peut proposer une modélisation fine des phénomènes observés à l'aide de ces technologies. Et lorsque des méthodes existent et nécessitent seulement une adaptation, le rôle du statisticien peut être celui d'un expert, qui connaît les méthodes, leurs limites et avantages. Le travail présenté dans cette thèse se situe à l'interface entre mathématiques appliquées et biologie, et relève plutôt des deuxième et troisième type de rôles mentionnés.Dans une première partie, j’introduis différentes méthodes développées pour l'analyse de données biologiques à haut débit, basées sur des modèles à variables latentes. Ces modèles permettent d'expliquer un phénomène observé à l'aide de variables cachées. Le modèle à variables latentes le plus simple est le modèle de mélange. Les deux premières méthodes présentées en sont des exemples: la première dans un contexte de tests multiples et la deuxième dans le cadre de la définition d'un seuil d'hybridation pour des données issues de puces à ADN. Je présente également un modèle de chaînes de Markov cachées couplées pour la détection de variations du nombre de copies en génomique prenant en compte de la dépendance entre les individus, due par exemple à une proximité génétique. Pour ce modèle, nous proposons une inférence approchée fondée sur une approximation variationnelle, l'inférence exacte ne pouvant pas être envisagée dès lors que le nombre d'individus augmente. Nous définissons également un modèle à blocs latents modélisant une structure sous-jacente par bloc de lignes et colonnes adaptées à des données de comptage issue de l'écologie microbienne. Les données issues de méta-codebarres ou de métagénomique correspondent à l'abondance de chaque unité d'intérêt (par exemple micro-organisme) d'une communauté microbienne au sein d'environnement (rhizosphère de plante, tube digestif humain, océan par exemple). Ces données ont la particularité de présenter une dispersion plus forte qu'attendue sous les modèles les plus classiques (on parle de sur-dispersion). La classification croisée est une façon d'étudier les interactions entre la structure des communautés microbiennes et les échantillons biologiques dont elles sont issues. Nous avons proposé de modéliser ce phénomène à l'aide d'une distribution Poisson-Gamma et développé une autre approximation variationnelle pour ce modèle particulier ainsi qu'un critère de sélection de modèle. La flexibilité et la performance du modèle sont illustrées sur trois jeux de données réelles.Une deuxième partie est consacrée à des travaux dédiés à l'analyse de données de transcriptomique issues des technologies de puce à ADN et de séquençage de l’ARN. La première section concerne la normalisation des données (détection et correction de biais techniques) et présente deux nouvelles méthodes que j’ai proposées avec mes co-auteurs et une comparaison de méthodes à laquelle j’ai contribuée. La deuxième section dédiée à la planification expérimentale présente une méthode pour analyser les dispositifs dit en dye-switch.Dans une dernière partie, je montre à travers deux exemples de collaboration, issues respectivement d'une analyse de gènes différentiellement exprimés à partir de données issues de puces à ADN, et d'une analyse du traductome chez l'oursin à partir de données de séquençage de l'ARN, la façon dont les compétences statistiques sont mobilisées et la plus-value apportée par les statistiques aux projets de génomique. / The technological progress of the last twenty years allowed the emergence of an high-throuput biology basing on large-scale data obtained in a automatic way. The statisticians have an important role to be played in the modelling and the analysis of these numerous, noisy, sometimes heterogeneous and collected at various scales. This role can be from several nature. The statistician can propose new concepts, or new methods inspired by questions asked by this biology. He can propose a fine modelling of the phenomena observed by means of these technologies. And when methods exist and require only an adaptation, the role of the statistician can be the one of an expert, who knows the methods, their limits and the advantages.In a first part, I introduce different methods developed with my co-authors for the analysis of high-throughput biological data, based on latent variables models. These models make it possible to explain a observed phenomenon using hidden or latent variables. The simplest latent variable model is the mixture model. The first two presented methods constitutes two examples: the first in a context of multiple tests and the second in the framework of the definition of a hybridization threshold for data derived from microarrays. I also present a model of coupled hidden Markov chains for the detection of variations in the number of copies in genomics taking into account the dependence between individuals, due for example to a genetic proximity. For this model we propose an approximate inference based on a variational approximation, the exact inference not being able to be considered as the number of individuals increases. We also define a latent-block model modeling an underlying structure per block of rows and columns adapted to count data from microbial ecology. Metabarcoding and metagenomic data correspond to the abundance of each microorganism in a microbial community within the environment (plant rhizosphere, human digestive tract, ocean, for example). These data have the particularity of presenting a dispersion stronger than expected under the most conventional models (we speak of over-dispersion). Biclustering is a way to study the interactions between the structure of microbial communities and the biological samples from which they are derived. We proposed to model this phenomenon using a Poisson-Gamma distribution and developed another variational approximation for this particular latent block model as well as a model selection criterion. The model's flexibility and performance are illustrated on three real datasets.A second part is devoted to work dedicated to the analysis of transcriptomic data derived from DNA microarrays and RNA sequencing. The first section is devoted to the normalization of data (detection and correction of technical biases) and presents two new methods that I proposed with my co-authors and a comparison of methods to which I contributed. The second section devoted to experimental design presents a method for analyzing so-called dye-switch design.In the last part, I present two examples of collaboration, derived respectively from an analysis of genes differentially expressed from microrrays data, and an analysis of translatome in sea urchins from RNA-sequencing data, how statistical skills are mobilized, and the added value that statistics bring to genomics projects.

La fermentation des fibres alimentaires est l’une des fonctions majeures du microbiote intestinal humain. Les bactéries fibrolytiques synthétisent un grand nombre d’enzymes, appelées Glycoside Hydrolases (GH), indispensables à la déconstruction de la grande variété structurelle des polysaccharides pariétaux que nous ingérons. Au cours de ce travail, nous avons exploré, grâce à une approche de métagénomique fonctionnelle, l’organisation et les propriétés des systèmes enzymatiques bactériens impliqués dans la dégradation des glycanes de parois végétales dans l’intestin humain.En premier lieu, nous avons cherché à déterminer si les bactéries de la muqueuse iléale étaient capables de dégrader les fibres pariétales dans un contexte sain. Cette fonction étant généralement décrite pour le microbiote colique par extrapolation de travaux menés à partir de selles humaines, nos connaissances de la dégradation des fibres dans la partie haute du tractus digestif sont donc très limitées. Un total de 20 000 clones issus du métagénome bactérien d’une partie saine de la muqueuse iléale d’un individu a été criblé pour des activités de dégradation de la carboxymethylcellulose et du xylane, deux substrats modèles des polysaccharides pariétaux. Douze clones métagénomiques positifs nous ont permis de mettre en évidence un arsenal de gènes bactériens codant pour des GH et d’autres protéines impliquées dans le métabolisme des fibres alimentaires dont certains organisés en PUL (Polysaccharide Utilization Loci), des clusters de gènes spécialisés dans la dégradation des polysaccharides complexes. Ces gènes proviennent de chromosomes bactériens assignés au genre Bacteroides ou à des espèces de Clostridiales, et codent pour des enzymes capables de dégrader également des β-glucanes à liaisons mixtes. L’étude de la prévalence de ces gènes dans les métagénomes de référence indique que plusieurs d’entre eux proviendraient de souches bactériennes plutôt spécifiques de la muqueuse iléale. De plus, certaines enzymes présentent des propriétés inédites potentiellement intéressantes dans le domaine biotechnologique. Nos recherches ont donc permis de revisiter la fonction fibrolytique du microbiote intestinal chez l’Homme et de proposer une localisation de cette fonction dès l’intestin grêle.Dans un second temps, en utilisant une approche méthodologique similaire, nous avons étudié la capacité du microbiote fécal d’un individu obèse à dégrader des polysaccharides pariétaux complexes, en général moins consommés par les individus obèses. Au total, nous avons identifié 50 clones appartenant à 14 espèces bactériennes des phyla suivants : Bacteroidetes, Firmicutes et Actinobacteria. Les inserts métagénomiques portent des gènes codant pour différentes familles de GH, impliquées dans la dégradation des polysaccharides d’intérêt. Les premières analyses de la prévalence de ces gènes chez plus d’une centaine d’individus (obèses ou non), par interrogations des catalogues de gènes microbiens de référence, suggèrent des associations avec le statut phénotypique « obèse ». / Among the crucial functions of the intestinal microbiota, extracting energy from food such as dietary fibres is of major importance. Facing the huge diversity of incoming complex carbohydrates, the fibrolytic bacteria synthesize a set of diversified Carbohydrate-Active Enzymes (CAZymes) including Glycoside Hydrolases (GH) that specifically disrupt complex polysaccharides. Here, using functional metagenomic approaches, we explored the organization and properties of bacterial enzymatic systems involved in the breakdown of plant cell wall (PCW) glycans in the intestinal tract.Firstly, we investigated the capacity of the microbiota associated to the human ileum mucosa to degrade complex non-starch polysaccharides in a healthy context. This function has never been investigated in this part of the intestine, but it has been rather associated to microorganisms inhabiting the colon, due to more accessible fecal samples. Using a fosmid library derived from a healthy part of the human ileal mucosa, we screened 20,000 metagenomic clones for their activities against carboxymethylcellulose and xylan chosen as models of the major PCW polysaccharides from dietary fibres. Twelve positive clones revealed a broad range of CAZyme encoding genes from Bacteroides to Clostridiales species, as well as Polysaccharide Utilization Loci (PUL). Functional GH genes were identified and break-down products examined from different polysaccharides including mixed-linkage β-glucans. Revealed CAZymes and PUL were also examined for their prevalence in human gut microbiomes. Part of them belongs to unidentified strains rather specifically established in the ileum. Others were enzymes unclassified in identified GH families or with original properties addressing novel candidates for biotechnological applications. Thus, we evidenced for the first time that the ileal mucosa associated-microbiota encompasses the enzymatic potential for PCW complex polysaccharide degradation that might start in the small intestine.In a second time, by using the same methodology, we harvested the enzymatic capacities of the fecal microbiota from an obese person to disrupt complex polysaccharides from dietary fibres usually consumed in lower quantity in obese people. This study aimed at examining the links between genes encoding enzymes specifically dedicated to PCW complex carbohydrates and the obese phenotypic status using reference microbial gene catalogs. We screened a fecal metagenomic library from an obese individual on representative PCW substrates and identified 50 clones belonging to 14 different species from the Bacteroidetes, Firmicutes and Actinobacteria phyla. The metagenomic inserts harbor genes encoding enzymes from GH families specific from complex carbohydrate degradation. First querying of the prevalence of these genes in hundreds individuals (obese and control), using catalogs of reference microbial genes, suggest associations with the "obese" phenotypic status.

No description available.

In healthcare settings and beyond, the ESKAPE pathogens (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter species) among other pathogens exchange antibiotic resistance and virulence factors and emerge as new infectious clones. According to the Saudi General Authority for Statistics (stats.gov.sa), Saudi Arabia is a country where more than 27 million pilgrims meet in annual continual mass-gathering events. This massive influx of people could introduce novel pathogens to the community that could not necessarily be detected with traditional culture-dependent clinical microbiological tests. Conventional clinical microbiology and environmental pathogen detection methods have had many limitations and narrow search scope. These methods can only target known and culturable pathogens. Over the past decade, applications of next-generation sequencing (NGS) and bioinformatics tools have revolutionized the way pathogens are detected and their relevant phenotypes such as clonal types, antibiotic resistance are predicted to aid in clinical decision making as additional practice to traditional clinical microbiology-based testing protocols. The aim of this study was to apply whole-genome sequencing (WGS) and bioinformatic analysis tools on clinical samples and bacterial isolates in order to pave the way for transforming current clinical microbiology practices in a tertiary referral hospital in Jeddah, Saudi Arabia. My attempt to utilize WGS as a tool on pathogenic strains in this study combined with the clinical data has resulted in discovering a silent outbreak of an emerging hypervirulent strain of Klebsiella pneumoniae (Chapter 2). Analysis of the strains antimicrobial profiles genetically has yielded the first characterization of a misidentified Klebsiella quasipneumoniae harboring plasmid-mediated carbapenemases of Klebsiella pneumoniae carbapenemases (KPC) (Chapter 3). Similarly, I was able to study mobile colistin resistance genes in the isolates and identify a novel occurrence of mcr-1 and mcr-8 (Chapter 4). I applied clinical metagenomic protocol on an intestinal biopsy of an inflammatory bowel disease patient with Crohn’s disease, where I identified an association of three co-occurring and an actively replicating non-tuberculosis mycobacteria (Chapter 5). The deployment of whole-genome sequencing and metagenomic in infectious disease surveillance and diagnostics could prove beneficial in limiting epidemics and detect transmission patterns of antimicrobial-resistant genes.

Corrosion in pipelines and reservoir tanks in oil plants is a serious problem in the energy industries around the world because it causes a huge economic loss due to not only frequent replacements of the parts of pipelines and tanks but also potential damage of the entire fields of crude oil. Previous studies have revealed that corrosions are generated mainly by microbial activities and they are now called as Microbial Influenced Corrosion (MIC) or simply bio-corrosion. Bacterial species actually causing bio-corrosion is crucial for the suppression of the corrosion. To diagnose and give proper treatment to pipelines in industrial plants, it is essential to identify the bacterial species responsible for bio-corrosions. For attaining at this aim, I conducted an analysis of the microbial community at the corrosion sites in pipelines of oil plants, using the comparative metagenomic analysis along with bioinformatics and statistics. In this study, I collected and analyzed various bio-corrosion samples from four different oil fields. First, I collected samples from the seawater pipelines that are essential in the oil fields to maintain seawater injection system (field#1), and then I conducted the metagenomic analysis of these samples. The metagenomes obtained revealed that samples in both sites contain a wide range of bacterial taxa. However, the comparative analysis of the microbial community with statistics in the comparison between sites with corrosion and without corrosion revealed the presence of microorganisms whose abundances were significantly higher in sites with corrosion. Some of these microbes can be sulfate reducers and sulfur oxidizers of which are considered to be casual agents in recent bio-corrosion models. In addition to the seawater pipelines, I also collect samples from corrosion sites in oil pipelines at Field #2 and #3. My metagenomic analysis combined with statistics showed that several microorganisms are speculated to be very active at the corrosion sites in the oil pipeline. Although biological mechanisms of forming bio-corrosion in the oil pipelines still remain unclear, these microbial species are suggested to be some of the responsible bacteria for bio-corrosion in the oil pipelines. Besides seawater injection systems, groundwater injection systems are often used, especially in inland oil fields. Therefore, more detailed understanding of biocorrosion in the groundwater injection system is also required in oil industries. In the present studies, I then analyzed the microbial communities in pipelines in the oil field where groundwater is used as injection water (field #4). I collected samples from four different facilities in the field #4. Metagenome analysis revealed that microbial community structures were largely different even among samples from the same facility. Treatments such as biocide and demineralization at each location in the pipeline may affect the microbial communities independently. The results indicated that microbial inspection throughout the pipeline network is important to protect industrial plants from bio-corrosions. Identifying the bacterial species responsible to bio-corrosion, this study provides us with information on bacterial indicators that will be available to classify and diagnose bio-corrosions. Furthermore, these species may be available as biomarkers to detect the events of bio-corrosion at an early stage. Then, any appropriate care such as the appropriate choice of biocides can be taken immediately and appropriately. Thus, my study will provide a platform for obtaining microbial information related to bio-corrosion that enables us to obtain a practical approach to protect them from bio-corrosion.

The main goal of this thesis was to design and implement a tool that would be able to classify the sequences of the 16S rRNA gene into taxonomic categories using the properties of the 16S rRNA gene. The created tool analyzes all input sequences simultaneously, which differs from common classification approaches, which classify input sequences individually. This tool relies on the fact that bacteria contain several copies of the 16S rRNA gene, which may differ in sequence. The main contribution of this work is design, implementation and evaluation of the capabilities of this tool. Experiments have shown that the proposed tool is able to identify the corresponding bacteria for smaller datasets and determine the correct ratios of their abundances. However, with larger datasets, the state space becomes very large and fragmented, which requires further improvements in order for it to search the state space in an efficient way.

The aim of this work is proposal of new method for bacteria classification based on sequences of marker genes. For this purpose was chosen 10 marker genes. Resulting MultiGene classifier processes data set by dividing it in several groups and choosing gene for each group which can distinguish this group with best results. This work describes implementation of MultiGene classifier and its results in comparison with other bacteria classifiers and with classification based entirely on gene 16S rRNA.