O uso de resíduos agrícolas como fonte de carbono para a geração de energia renovável parece uma solução promissora para reduzir nossa dependência em combustíveis fósseis. Na natureza, como na compostagem, comunidades microbianas formam redes metabólicas complexas que degradam eficientemente a biomassa disponível através de um conjunto de enzimas sinérgicas. Entretanto, a desconstrução da lignocelulose continua uma desafio para a indústria devido a natureza recalcitrante do substrato e a baixa atividade das enzimas, aumentando o preço do biocombustível produzido. Estudos de metagenômica e metatranscriptômica de comunidades microbianas complexas tornam possível acessar as funções metabólicas empregadas por consórcios lignocelulolíticos e revelar novos biocatalisadores que podem melhorar a conversão industrial da lignocelulose. Aqui, através de uma abordagem metagenômica, foi examinada a diversidade de microrganismos obtidos em condições laboratoriais quando um meio definido ou um complexo foi usado no seu crescimento. Em seguida, a comunidade microbiana derivada de compostagem foi crescida em meio mínimo com bagaço de cana-de-açúcar como única fonte de carbono. A degradação do substrato foi monitorada e o metatranscriptoma da cultura resultante foi sequenciado, seguido pela seleção e caracterização funcional de vários alvos. Durante as cinco semanas de estudo, a comunidade microbiana crescida em meio mínimo mostrou maior diversidade e enriquecimento em microrganismos capazes de degradar a lignocelulose do que a comunidade microbiana crescida no meio complexo. A partir do metatranscriptoma foi descoberta a primeira hidrolase de glicosídeo da família 11 com atividade exoxilanase (C21). A estrutura cristalográfica da C21, refinada à 1,76 Å, revelou que a atividade exoxilanase observada se deve a presença de duas alças que não estão presentes nas demais estruturas dos membros da família 11 de hidrolase de glicosídeo depositadas até então. A adição da C21 a um coquetel comercial provocou um aumento na velocidade de hidrólise do Avicel quando na presença de xilooligômeros. As análises metagenômica e metatranscriptômica da comunidade microbiana proveniente da compostagem revelaram que o uso de um meio definido pode deslocar espécies generalistas, levando a uma fonte enriquecida para explorar enzimas com aplicação biotecnológica. Também demonstrou a diversidade de mecanismos envolvidos na degradação in situ da lignocelulose. / Using of the globally abundant crop residues as carbon source for energy generation seems a promising solution to reduce our dependency on fossil fuels. In nature, such as in compost habitats, microbial communities create complex metabolic networks that efficiently degrade the available plant biomass using a set of synergistic enzymes. However, deconstruction of lignocellulose remains a challenge for industry due to recalcitrant nature of the substrate and enzymes low activity, raising the price of the produced biofuel. Metagenomics and metatranscriptomics studies on complex microbial communities can assess the metabolic functions employed by the lignocellulolytic consortia and unveil novel biocatalysts that could improve industrial lignocellulose conversion. Here, using 16S rRNA amplicon metagenomic approach, we examined the diversity of microorganisms obtained in the laboratory setting when a nutrient-limited or nutrient-rich media are used. Then, a microbial community derived from compost was grown in minimal medium with sugarcane bagasse as a sole carbon source. The substrate degradation was monitored and the metatranscriptome from the resulting cultures was sequenced; several target genes were selected and functional characterized. During a five-week time course, the microbial community grown in minimal medium showed greater diversity and enrichment in lignocellulose-degrading microorganisms than the one grown in nutrient rich medium. Metatranscriptomics analysis revealed the first glycoside hydrolase from family 11 with exo-xylanase activity (C21). C21 crystal structure, refined at 1.76 Å, explained the molecular basis of exo-xylanase activity due to two extra loops previously unseen in the other reported structures from members from glycoside hydrolase family 11. A supplementation of commercial enzyme mix with C21 showed improvement in Avicel hydrolysis in the presence of inhibitory xylooligomers. The combination of metagenomic and metatranscriptomic analysis of compost-derived microbial community showed that nutrient-limited medium may displace bacterial generalist species, leading to an enriched source for mining novel enzymes for biotechnology applications. It also unveiled a diversity of mechanisms involved in lignocellulose degradation in situ.

Benzalkonium chlorides (BACs) are widely used, broad-spectrum disinfectants and frequently detected in the environment, even at toxic levels for life. Since such disinfectants can induce broad resistance capabilities, BACs may fuel the emergence of antibiotic resistance in the environment. A substantial body of literature has reported that exposure to BACs causes antibiotic resistance; yet, other studies suggest that the resistance linkage is rare, unsystematic, and/or clinically insignificant. Accordingly, whether or not disinfectant exposure mediates antibiotic resistance and, if so, what molecular mechanisms underlie the resistance link remains to be clearly elucidated. Further, understanding how microbial communities degrade BACs is important not only for alleviating the possible occurrence of antibiotic resistance but also reducing the potential risks to environmental and public health. An integrated strategy that combines metagenomics, metatranscriptomics, genetics, and traditional culture-dependent approaches was employed to provide novel insights into these issues. The integrative approach showed that a microbial community exposed to BACs can acquire antibiotic resistance through two mechanisms: i) horizontal transfer of previously uncharacterized efflux pump genes conferring resistance to BACs and antibiotics, which were encoded on a conjugative plasmid and co-selected together upon BACs and ii) selective enrichment of intrinsically multi-drug resistant organisms. Further, a microbial community adapts to BAC exposure via a variety of mechanisms, including selective enrichment of BAC-degrading species and amino acid substitutions and horizontal transfer of genes related to BAC resistance and degradation. The metatranscriptomic data suggests that the BAC-adapted microbial community metabolized BACs by cooperative interactions among its members. More specifically, Pseudomonas nitroreducens cleaved (i.e., dealkylated) BACs, metabolized the alkyl chain (the dealkylated product of BACs), and released benzyldimethylamine (the other product of BACs), which was further metabolized by other community members (e.g., Pseudomonas putida). Collectively, this study demonstrates the role of BACs in promoting antibiotic resistance and advances current understanding of a microbial community degrading BACs. The results of this work have important implications for (appropriate) usage of disinfectants and for assessing, predicting, and optimizing biological engineering processes treating BAC-bearing waste streams.

O uso de resíduos agrícolas como fonte de carbono para a geração de energia renovável parece uma solução promissora para reduzir nossa dependência em combustíveis fósseis. Na natureza, como na compostagem, comunidades microbianas formam redes metabólicas complexas que degradam eficientemente a biomassa disponível através de um conjunto de enzimas sinérgicas. Entretanto, a desconstrução da lignocelulose continua uma desafio para a indústria devido a natureza recalcitrante do substrato e a baixa atividade das enzimas, aumentando o preço do biocombustível produzido. Estudos de metagenômica e metatranscriptômica de comunidades microbianas complexas tornam possível acessar as funções metabólicas empregadas por consórcios lignocelulolíticos e revelar novos biocatalisadores que podem melhorar a conversão industrial da lignocelulose. Aqui, através de uma abordagem metagenômica, foi examinada a diversidade de microrganismos obtidos em condições laboratoriais quando um meio definido ou um complexo foi usado no seu crescimento. Em seguida, a comunidade microbiana derivada de compostagem foi crescida em meio mínimo com bagaço de cana-de-açúcar como única fonte de carbono. A degradação do substrato foi monitorada e o metatranscriptoma da cultura resultante foi sequenciado, seguido pela seleção e caracterização funcional de vários alvos. Durante as cinco semanas de estudo, a comunidade microbiana crescida em meio mínimo mostrou maior diversidade e enriquecimento em microrganismos capazes de degradar a lignocelulose do que a comunidade microbiana crescida no meio complexo. A partir do metatranscriptoma foi descoberta a primeira hidrolase de glicosídeo da família 11 com atividade exoxilanase (C21). A estrutura cristalográfica da C21, refinada à 1,76 Å, revelou que a atividade exoxilanase observada se deve a presença de duas alças que não estão presentes nas demais estruturas dos membros da família 11 de hidrolase de glicosídeo depositadas até então. A adição da C21 a um coquetel comercial provocou um aumento na velocidade de hidrólise do Avicel quando na presença de xilooligômeros. As análises metagenômica e metatranscriptômica da comunidade microbiana proveniente da compostagem revelaram que o uso de um meio definido pode deslocar espécies generalistas, levando a uma fonte enriquecida para explorar enzimas com aplicação biotecnológica. Também demonstrou a diversidade de mecanismos envolvidos na degradação in situ da lignocelulose. / Using of the globally abundant crop residues as carbon source for energy generation seems a promising solution to reduce our dependency on fossil fuels. In nature, such as in compost habitats, microbial communities create complex metabolic networks that efficiently degrade the available plant biomass using a set of synergistic enzymes. However, deconstruction of lignocellulose remains a challenge for industry due to recalcitrant nature of the substrate and enzymes low activity, raising the price of the produced biofuel. Metagenomics and metatranscriptomics studies on complex microbial communities can assess the metabolic functions employed by the lignocellulolytic consortia and unveil novel biocatalysts that could improve industrial lignocellulose conversion. Here, using 16S rRNA amplicon metagenomic approach, we examined the diversity of microorganisms obtained in the laboratory setting when a nutrient-limited or nutrient-rich media are used. Then, a microbial community derived from compost was grown in minimal medium with sugarcane bagasse as a sole carbon source. The substrate degradation was monitored and the metatranscriptome from the resulting cultures was sequenced; several target genes were selected and functional characterized. During a five-week time course, the microbial community grown in minimal medium showed greater diversity and enrichment in lignocellulose-degrading microorganisms than the one grown in nutrient rich medium. Metatranscriptomics analysis revealed the first glycoside hydrolase from family 11 with exo-xylanase activity (C21). C21 crystal structure, refined at 1.76 Å, explained the molecular basis of exo-xylanase activity due to two extra loops previously unseen in the other reported structures from members from glycoside hydrolase family 11. A supplementation of commercial enzyme mix with C21 showed improvement in Avicel hydrolysis in the presence of inhibitory xylooligomers. The combination of metagenomic and metatranscriptomic analysis of compost-derived microbial community showed that nutrient-limited medium may displace bacterial generalist species, leading to an enriched source for mining novel enzymes for biotechnology applications. It also unveiled a diversity of mechanisms involved in lignocellulose degradation in situ.

Marine micro-organisms are important components of various biogeochemical cycles, complex food webs and ecological niches. Metagenomic sequencing can provide rapid profile of metabolic activities within the sponge and resident microbes. However, the study of metatranscriptomes from sponges using high throughput sequencing technology has only recently begun. Through this study we isolated, characterized and compared metatranscriptome profiles of Axinella corrugata host and sponge-specific microbial communities using 454 pyrosequencing technology. Four cDNA libraries (two eukaryotic and two prokaryotic) were generated from Axinella corrugata sponge samples collected in December 2009 and May 2010, and were characterized to a) reveal which metabolic genes were actively expressed and b) reveal possible interactions between the sponge and its microbial symbionts. The techniques used for isolation of mRNA and cDNA normalization also helped in optimization of whole-transcriptome amplification. More than 130,000 ESTs were generated for the two seasonal sponge samples and the metagenomic data sets were analyzed using bioinformatics tool, MG-RAST. Several stress-related transcripts were found which can increase our understanding of sensitivity of the sponge to changes in physical parameters in nature. The involvement of the sponge and its microbial consortia is depicted through actively expressed nitrogen and sulfur metabolism genes. Novel genes involved in several functional pathways may be discovered upon further studying hypothetical genes found across all four metagenomic data sets. Metatranscriptomic data sheds light on the functional role of microbes within the sponges and the extent of their involvement in sponge metabolism. 16S rRNA analysis was also carried out using genomic DNA of the same samples, to better elucidate the bacterial taxa abundance in the sponge. This study provides a profile of active mRNA trancripts in Axinella corrugata which include eukaryotic as well as prokaryotic sequences. The data analysis of this research provides new information at the cross-disciplinary interface between molecular biology and computational science.

La métagénomique sert à étudier les communautés microbiennes en analysant de l’ADN extrait directement d’échantillons pris dans la nature, elle permet également d’établir un catalogue très étendu des gènes présents dans les communautés microbiennes. Ce catalogue doit être comparé contre les gènes déjà référencés dans les bases des données afin de retrouver des séquences similaires et ainsi déterminer la fonction des séquences qui le composent. Au cours de cette thèse, nous avons développé MetaCLADE, une nouvelle méthodologie qui améliore la détection des domaines protéiques déjà référencés pour des séquences issues des données métagénomiques et métatranscriptomiques. Pour le développement de MetaCLADE, nous avons modifié un système d’annotations de domaines protéiques qui a été développé au sein du Laboratoire de Biologie Computationnelle et Quantitative appelé CLADE (CLoser sequences for Annotations Directed by Evolution) [17]. En général les méthodes pour l’annotation de domaines protéiques caractérisent les domaines connus avec des modèles probabilistes. Ces modèles probabilistes, appelés Sequence Consensus Models (SCMs) sont construits à partir d’un alignement des séquences homologues appartenant à différents clades phylogénétiques et ils représentent le consensus à chaque position de l’alignement. Cependant, quand les séquences qui forment l’ensemble des homologues sont très divergentes, les signaux des SCMs deviennent trop faibles pour être identifiés et donc l’annotation échoue. Afin de résoudre ce problème d’annotation de domaines très divergents, nous avons utilisé une approche fondée sur l’observation que beaucoup de contraintes fonctionnelles et structurelles d’une protéine ne sont pas globalement conservées parmi toutes les espèces, mais elles peuvent être conservées localement dans des clades. L’approche consiste donc à élargir le catalogue de modèles probabilistes en créant de nouveaux modèles qui mettent l’accent sur les caractéristiques propres à chaque clade. MetaCLADE, un outil conçu dans l’objectif d’annoter avec précision des séquences issues des expériences métagénomiques et métatranscriptomiques utilise cette libraire afin de trouver des correspondances entre les modèles et une base de données de séquences métagénomiques ou métatranscriptomiques. En suite, il se sert d’une étape pré-calculée pour le filtrage des séquences qui permet de déterminer la probabilité qu’une prédiction soit considérée vraie. Cette étape pré-calculée est un processus d’apprentissage qui prend en compte la fragmentation de séquences métagénomiques pour les classer.Nous avons montré que l’approche multi source en combinaison avec une stratégie de méta apprentissage prenant en compte la fragmentation atteint une très haute performance. / Metagenomics is used to study microbial communities by the analyze of DNA extracted directly from environmental samples. It allows to establish a catalog very extended of genes present in the microbial communities. This catalog must be compared against the genes already referenced in the databases in order to find similar sequences and thus determine their function. In the course of this thesis, we have developed MetaCLADE, a new methodology that improves the detection of protein domains already referenced for metagenomic and metatranscriptomic sequences. For the development of MetaCLADE, we modified an annotation system of protein domains that has been developed within the Laboratory of Computational and Quantitative Biology clade called (closer sequences for Annotations Directed by Evolution) [17]. In general, the methods for the annotation of protein domains characterize protein domains with probabilistic models. These probabilistic models, called sequence consensus models (SCMs) are built from the alignment of homolog sequences belonging to different phylogenetic clades and they represent the consensus at each position of the alignment. However, when the sequences that form the homolog set are very divergent, the signals of the SCMs become too weak to be identified and therefore the annotation fails. In order to solve this problem of annotation of very divergent domains, we used an approach based on the observation that many of the functional and structural constraints in a protein are not broadly conserved among all species, but they can be found locally in the clades. The approach is therefore to expand the catalog of probabilistic models by creating new models that focus on the specific characteristics of each clade. MetaCLADE, a tool designed with the objective of annotate with precision sequences coming from metagenomics and metatranscriptomics studies uses this library in order to find matches between the models and a database of metagenomic or metatranscriptomic sequences. Then, it uses a pre-computed step for the filtering of the sequences which determine the probability that a prediction is a true hit. This pre-calculated step is a learning process that takes into account the fragmentation of metagenomic sequences to classify them. We have shown that the approach multi source in combination with a strategy of meta-learning taking into account the fragmentation outperforms current methods.

Soil microbiomes play pivotal roles to the health of the environment by maintaining metabolic cycles. One question is how will climate change affect soil bacteria over time and what could the repercussions be. To answer these questions, the Harvard Forest Long-Term Warming Experiment was established to mimic predicted climate change by warming plots of land 5℃ above ambient conditions. In 2017, 14 soil core samples were collected from Barre Woods warming experiment to mark 15 years since the establishment of the soil warming in that location. These samples underwent traditional metatranscriptomics to generate an mRNA library as well as a process coined cell-sorted or mini-metagenomics involving the sorting of single bacterial cells from the environment using FACS. This was followed by pooling into groups of 100 cells for more cost efficient genome recovery. 200 high-quality genomes were compiled, 12 of which were taxonomically identified as Acidobacteria. Acidobacteria are an extremely abundant and diverse phylum of bacteria that were found to be very well represented in the soil samples. Due to their abundance in many different soil environments as well as their known importance in many metabolic cycles, they were chosen as the candidate phylum to further investigate. Using a reference-based read mapping approach with the 12 Acidobacteria genomes and metatranscriptomic data, we identified over 3,000 differentially expressed genes within these organisms as a result of soil warming. Due to the diversity within the phylum itself, many of the genomes indicated different patterns of expression making it difficult to identify phylum-wide differential expression trends. However, the sigma70 factor, an important housekeeping gene used as a transcription regulator, was found to be up-regulated in a majority of the genomes. Over 30 different glycoside hydrolase encoding genes and glycosyltransferases were also found to be differentially expressed across the Acidobacteria reference genomes as well as 23 chemotaxis-related genes. Despite identifying four different groups of genes that showed statistically significant differences in expression levels, there may be more changes occurring in these soil bacteria and the soil microbiome as a whole due to climate change than previously measured by read-based analyses of metatranscriptomic data.

No description available.

L’exposition aux polluants environnementaux a été associée à de nombreux désordres métaboliques, immunitaires et reproductifs ainsi qu’à divers cancers. De plus en plus de travaux, indiquent que le microbiote intestinal, qui joue un rôle majeur dans l’immunité et le métabolisme de l’hôte, interagit avec les xénobiotiques dont les polluants organiques persistants (POPs) et les contaminants néoformés dans les aliments. Cette interaction peut avoir des conséquences toxicologiques importantes via la modification des fonctions du microbiote intestinal mais également via la métabolisation des xénobiotiques, entraînant une potentielle altération de l'homéostasie de l'hôte. Dans le cadre de cette thèse, nous avons démontré, en modèle in vitro, qu’une exposition aigüe du microbiote intestinal humain au benzo[a]pyrène (hydrocarbure aromatique polycyclique) a entraîné une altération des fonctions du microbiote intestinal au niveau du volatolome et du métatranscriptome microbien. Cependant, dans nos conditions expérimentales, aucun impact sur la structure microbienne n'a été observé. L’Homme étant continuellement exposé à un panel de composés chimiques environnementaux, nous avons par la suite étudié l'impact de divers POPs et produits néoformés dans les aliments sur le microbiote intestinal humain. Des familles de gènes ainsi que des composés volatiles microbiens ont été identifiés comme altérés après l’exposition, conduisant à une perturbation de l'activité microbienne. Nous avons finalement démontré que l'interaction microbiote-polluant pourrait conduire à l'établissement d'un état pro-inflammatoire modéré dans l'intestin avec une libération de cytokine IL-8 par les cellules épithéliales intestinales. Ces résultats appuient le concept émergent selon lequel les contaminants alimentaires pourraient altérer les activités du microbiote intestinal. / Exposure to environmental pollutants has been associated with various life-threatening disorders, including dysregulation of the immune and reproductive systems, metabolic diseases and various cancers. Growing evidences indicate that the gut microbiota, which plays major roles in host metabolic and immune functions, interacts with xenobiotics including persistent organic pollutants (POPs) and foodborne chemicals. The toxicological relevance of the gut microbiota-pollutant interplay is of great concern for the host since the chemicals may disrupt the gut microbiota functions leading to a potential impairment of the host homeostasis. During this PhD thesis, we demonstrated that in vitro acute exposure of the human gut microbiota with benzo[a]pyrene (polycyclic aromatic hydrocarbon) led to an impairment of the gut microbiota functions with a specific shift of the microbial volatolome and metatranscriptome. However, in our experimental conditions, no impact on the microbial structure was observed. Since humans are exposed to a wide range of environmental chemicals we investigated the impact of various POPs and foodborne chemicals on the human gut microbiota. We identified microbial volatiles and gene families that shifted after this exposure leading to an imbalance of the microbial activity. Furthermore, we demonstrated that the interaction between the pollutants and the gut microbiota lead to a significant release of pro-inflammatory IL-8 cytokine by the intestinal epithelial cells which may contribute to the establishment of a low-grade inflammatory state in the gut. All together, these data support the emerging concept that food pollutants could alter the gut microbiota activities.

Colorectal cancer (CRC) is one of the most treatable cancers, with a 5-year survival rate of similar to 64%, yet over 50,000 deaths occur yearly in the United States. In 15% of cases, deficiency in mismatch repair leads to null mutations in transforming growth factor beta (TGF-beta) type II receptor, yet genotype alone is not responsible for tumorigenesis. Previous work in mice shows that disruptions in TGF-beta signaling combined with Helicobacter hepaticus cause tumorigenesis, indicating a synergistic effect between genotype and microbial environment. Here, we examine functional shifts in the gut microbiome in CRC using integrated - omics approaches to untangle the role of host genotype, inflammation, and microbial ecology. We profile the gut microbiome of 40 mice with/without deficiency in TGF-beta signaling from a Smad3 (mothers against decapentaplegic homolog-3) knockout and with/without inoculation with H. hepaticus. Clear functional differences in the microbiome tied to specific bacterial species emerge from four pathways related to human colon cancer: lipopolysaccharide (LPS) production, polyamine synthesis, butyrate metabolism, and oxidative phosphorylation (OXPHOS). Specifically, an increase in Mucispirillum schaedleri drives LPS production, which is associated with an inflammatory response. We observe a commensurate decrease in butyrate production from Lachnospiraceae bacterium A4, which could promote tumor formation. H. hepaticus causes an increase in OXPHOS that may increase DNA-damaging free radicals. Finally, multiple bacterial species increase polyamines that are associated with colon cancer, implicating not just diet but also the microbiome in polyamine levels. These insights into cross talk between the microbiome, host genotype, and inflammation could promote the development of diagnostics and therapies for CRC. IMPORTANCE Most research on the gut microbiome in colon cancer focuses on taxonomic changes at the genus level using 16S rRNA gene sequencing. Here, we develop a new methodology to integrate DNA and RNA data sets to examine functional shifts at the species level that are important to tumor development. We uncover several metabolic pathways in the microbiome that, when perturbed by host genetics and H. hepaticus inoculation, contribute to colon cancer. The work presented here lays a foundation for improved bioinformatics methodologies to closely examine the cross talk between specific organisms and the host, important for the development of diagnostics and pre/probiotic treatment.

The scope and application of high throughput techniques has expanded from studying a single genome, transcriptome or proteome to understanding complex environments at a greater resolution with the help of novel computational frameworks. Comprehensive structural annotation i.e. description of all functional elements in the genome, is required for measuring genome response accurately, using high throughput methods. Annotation of genome sequences using high throughput data from RNA-seq and proteomics experiments complement computational methods for identifying functional elements and can help validate existing in silico annotation, correct annotation errors, and could potentially identify novel functional elements. Re-annotation studies in recent times have revealed shortcomings of automated methods and the necessity to validate existing annotations using experimental data. This dissertation elucidates re-annotation of Mannheimia haemolytica, Pasteurella multocida and Histophilus somni, bacterial pathogens associated with bovine respiratory disease in cattle. Experimental re-annotation of these bacterial genomes using RNA-seq and proteomics enabled the validation of existing annotation and discovery of novel functional elements that can be utilized in future functional genomics studies. We also addressed the need for developing an automated bioinformatics workflow that is broadly applicable for bacterial genome re-annotation, by developing open source Perl pipeline that can use RNA-seq and proteomics data as input. Simultaneous analysis of host and pathogen gene expression profiling using metatranscriptomics approaches is necessary to improve our understanding of infectious diseases. Traditional methods for analysis of RNA-seq data do not address the impact of cross-mapping of reads to multiple genomes for data originating from a metatranscriptomic study. Analysis of sequence conservation between species can help determine a metric for cross mapping to correct for signal vs. noise. We generated artificial RNA-seq data and evaluated the impact of read length and sequence conservation on cross-mapping. Comparative genomics was used to identify a core and pan-genome for quantifying gene expression. Our results show that cross mapping between genomes can directly be related to evolutionary distance between these genomes and that an increase in RNA-seq read length tends to negate cross mapping.