>Magister Scientiae - MSc / Heterologous metagenomic screening strategies have relied largely on the construction of DNA libraries and screening in Escherichia coli to access novel enzymes. There is an increased demand for the identification of novel lignocellulose degrading enzymes with enhanced biochemical properties which are suitable for applications in industrial processes; biofuels being one of them. The use of heterologous gene expression in function based metagenomic studies has resulted in the discovery of enormous novel bioactive compounds. However, there are limitations associated with using E. coli as a heterologous host which does not allow transcription and translation of all genes in the metagenome. E. coli can only express 40% of the environmental DNA because of promoter recognition, codon usage, and host toxicity of gene products. Therefore alternative strategies for expressing or producing novel enzymes are needed, which can also be employed in metagenomic gene discovery. In vitro protein synthesis is an important tool in molecular biology and used to obtain proteins from genes for functional and expression studies. These systems may hold the key to unlock more of the potential in metagenomic DNA. The broader aim of the study is to develop non- E. coli based cell-free protein synthesis systems to further the metagenomics screening. In this study, Rhodococcus erythropolis H8 was evaluated for its suitability in cell-free expression. Crude extracts containing the macromolecular components (70S or 80S ribosomes, tRNAs, initiation, elongation and termination factors) fromR. erythropolis were prepared using existing crude extract based cell-free protein synthesis (CFPS) protocols. Three genes were selected and used as templates for synthesis: cell11, xp12 and acetyl xylan esterase (axe10), all previously isolated from metagenomic libraries screened inE. coli. As judged by zymograms and enzyme assays, all enzymes were successfully expressedfrom their native promoters and in recombinants clones using the PtipA promoter, and wereactive. Furthermore, the amounts of XP12 protein produced using pFos-XP_12 was 1.2mg/mlfrom E. coli and 1.67mg/ml from R. erythropolis CFPS, showing that the R. erythropolismachinery was more efficient in the expression of XP12 than the E. coli machinery. To the best of our knowledge this is the first demonstration of a cell-free expression using an actinomycete.

Crude oil is a complex mixture of aromatic and aliphatic hydrocarbons of diverse molecular weight. In spite of its high hydrophobicity and toxicity, crude oil is a rich source of carbon for microorganisms. It has been proposed that microbial metabolism contributes to petroleum physicochemical characteristics, as highly specialized microorganisms are adapted to its extreme conditions. Deciphering these unique microbiomes will allow more in-depth characterization of crude oil and better understand its chemistry. The general aim of this study is to characterize the unique microbial communities of crude oil through a comparative metagenomics approach. I performed a survey of worldwide crude oil metagenomes in literature and databases. I identified 48 metagenomics datasets from five countries. The Comparative analysis of these metagenomes allowed us to identify how Methanogens are predominant in the North-American crude oil, being Methanoculleus and Methanosaeta the dominant genera in Canada and Methanothermococcus the predominant genus in the United States oil fields. In the case of Nigeria crude oil, Marinobacterium and Parvivaculum were the two dominant genera. In the case of Thailand, the dominant genus Thermus reflected the high-temperature environment of that oil field. Finally, metagenomes from China were the most diverse, reflecting the heterogeneity of the oil fields from that country. I generated metagenomics data from 27 Saudi Arabian crude oil samples originated in 6 different oil fields. As no crude oil metagenome has been reported yet for the Arabian Peninsula, the information provided in this dissertation is contributing towards a complete worldwide characterization of crude oils. Two genera, Peanibacilus and Thermospira, are proposed as the taxonomic markers for the set of Saudi crude oil analyzed. In this thesis I elucidated the structure of microbial communities in crude oils globally, suggesting that it may reflect the geological history of crude oils. This study sheds light on the importance of microorganisms for understanding petroleum geobiology. These findings suggest that it is possible to identify the distinctive microbiota associated with specific types of crude oil according to its location. The results presented here set the basis for developing novel methodologies for crude oil identification based on a microbial fingerprinting approach.

The microbiome has become a focus of research, particularly in the field of human health and precision medicine, due to its role in human development, immunity, and nutrition. Microbiome profiling studies have become more tractable and advanced in large part thanks to advancements in metagenomics. One such study is the Black Women’s Health Study (BWHS), which aims to better understand health risks and disease development specific to Black women, who are more susceptible to certain health conditions. However, a major obstacle for reproducibility of microbiome research is the high sensitivity of microbial compositions to external factors and batch-to-batch technical variability, resulting in batch effects that often hinder analysis of factors of interest. While batch effect adjustment methods have been developed for other biomedical data, they do not appropriately account for two unique features of microbiome data: 1) its compositional nature, and 2) extreme overdispersion and zero-inflation. My dissertation addresses these challenges by evaluating and improving batch effect correction methods for microbiome data and then applies these approaches to data from BWHS. First, I evaluated ComBat-Seq, along with existing microbiome-specific tools, in removing batch effects from both simulated 16S rRNA and real-world shotgun metagenomic sequencing data while preserving effects belonging to biological factors of interest. Second, I applied ComBat-Seq in an epidemiological study in which I identified several oral health-related genera among adult Black women to be associated with the host’s geographic location in the US. Finally, I introduced an extension to ComBat-Seq that improves its performance in batch effect correction on rare taxa with outliers via imputation. I demonstrated that, by replacing zeroes with predicted non-zero read counts that follow the observed compositional structure of the data, imputation effectively reduced the number of problematic cases in which outliers were intensified after batch effect correction. Collectively, my thesis demonstrates that 1) when the specific features of microbiome data are accounted for, batch effect correction methods offer a promising solution to address batch effect in microbiome data and improve microbiome profiling studies and 2) it is important to consider social/environmental factors associated with the host’s physical location when studying the oral microbiome.

With the large-scale metagenome sequencing data produced currently, alignment-free metagenomic profiling approaches have demonstrated the effectiveness of Markov models in addressing the limitations of alignment-based techniques, particularly in handling unclassified reads. The development of POSMM (Python Optimized Standard Markov Model), employing SMM (Standard Markov Model) algorithm, initially showcased competitive performance when compared to tools such as Kraken2. However, when subjected to simulated damages present in ancient metagenomics data, shortcomings emerged, leading to false positives or misclassified sequences that compromised overall classification accuracy. To address this problem, we developed a segmental genome model (SGM) algorithm based on the generation of the ensemble of models representing distinct classes of DNA segments in a genome. SGM incorporated a recursive segmentation and clustering approach to segregate regions of distinct composition in a microbial genome. An ensemble of higher-order Markov models is trained on DNA clusters generated for each genome. A database of models of genomes, with each genome represented by multiple Markov models are then queried to infer the origin of reads from a metagenome. SGM was benchmarked using diverse synthetic metagenome datasets of varying composition, read lengths, and error profiles. The comparative assessment showed that SGM consistently outperformed SMM. SGM brings in significant advances in alignment-free profiling, offering a new promising avenue for metagenomic exploration through its integration in the next version of POSMM. Furthermore, leveraging the power of integration of alignment-free and alignment-based approaches and highlighting the versatility and practicality of these methods in addressing critical public health challenges, we developed a statistical analysis and machine learning pipeline to identify candidate microbes associated with COVID-19. This involved a meta-analysis of the whole genome sequencing data of COVID-19 patients' samples and its predictive modeling to discern the distinctive microbial features. We improve and explore alignment-free metagenome profiling to raise the bar in metagenome profiling in complex real-world samples.

Background. Viruses strongly influence microbial population dynamics and ecosystem functions However, our ability to quantitatively evaluate those viral impads is limited to the few cultivated viruses and double-stranded DNA (dsDNA) viral genomes captured in quantitative viral metagenornes (vromes). This leaves the ecology of nondsDNA viruses nearly unlmovvn, including single-stranded DNA (ssDNA) viruses that have been frequently observed in viromes, but not quantified due to amplification biases in sequencing library preparations (Multiple Displacement Amplification, Linker Amplification or Tagmentation). Methods. Here we designed mock viral communities including both ssDNA and dsDNA viruses to evaluate the capability of a sequencing library preparation approach including an Adaptase step prior to Linker Amplification for quantitative amplification of both dsDNA and ssDNA templates. We then surveyed aquatic samples to provide first estimates of the abundance of ssDNA viruses. Results. Mock community experiments confirmed the biased nature of existing library preparation methods for ssDNA templates (either largely enriched or selected against) and showed that the protocol using Adaptase plus Linker Amplification yielded viromes that were 1.8-fold quantitative for ssDNA and dsDNA viruses. Application of this protocol to community virus DNA from three freshwater and three marine samples revealed that ssDNA viruses as a whole represent only a minor fraction (<5%) of DNA virus communities, though individual ssDNA genomes, both eukaryoteinfecting Circular Rep-Encoding Single-Stranded DNA (CRESS-DNA) viruses and bacteriophages from the Microviridae family, can be among the most abundant viral genomes in a sample. Discussion. Together these findings provide empirical data for a new virome library preparation protocol, and a first estimate of ssDNA virus abundance in aquatic systems.

Orientador: Eliana Gertrudes de Macedo Lemos / Coorientador: Elisângela Soares Gomes Pepe / Coorientador: Mariana Rangel Pereira / Banca: Gustavo Orlando Bonilla Rodriguez / Banca: João Martins Pizauro Junior / Resumo: O mercado industrial está se tornando cada vez mais dependente do uso de enzimas como catalisadores. Dentre as enzimas utilizadas industrialmente estão as de origem microbiana, por serem ativas nas mais diversas condições. As lacases são enzimas com alto potencial, pois atuam sobre diversos compostos, o que possibilita uma vasta diversidade de possíveis aplicações. Entre as formas de prospecção de novas enzimas microbianas, encontra-se a metagenômica. Diante disto, foi realizada a busca por potenciais lacases seguindo uma estratégia "sequence-driven" em uma base de dados metagenomicos composta por amostras de diversos ambientes, pertencente ao Laboratório de Bioquímica de Microrganismos e Plantas (LBMP). As ORFs previamente anotadas por similaridade de sequências e domínios conservados como possíveis "Multicopper oxidases" (grupo no qual se encontram as lacases) foram prospectadas pela região conservada para lacases L3 (HLHGH). Esta estratégia retornou três ORFs, a ORF50MF; a ORF51ME e a ORF13SE (lacmeta), as quais foram clonadas e submetidas as análises de super-expressão e purificação. LacMeta, similar em 82% com a sequência de proteína hipotética de Streptomyces rubidus [WP_069465126.1], foi a proteína que apresentou o melhor resultado de expressão e purificação, sendo então submetida a caracterização cinética. A proteína fusionada a uma cauda de hexa-histidina foi purificada na forma homo-trimérica, com 107 kDa, e apresentou atividade ótima em pH ácido para o substrato AB... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: The industrial market is becoming increasingly dependent on the use of enzymes as biocatalysts. Among the enzymes used industrially are those of microbial origin, because they are active in the most diverse conditions. Laccases are enzymes with high potential, since they act on several compounds, which allows a wide diversity of possible applications. Among the search for new forms of microbial enzymes, is the metagenomic. In this way, the search for potential laccases was carried out following a sequence-driven strategy in a metagenomic database composed of samples from different environments, belonging to the Laboratory of Biochemistry of Microorganisms and Plants (LBMP). The ORFs previously annotated by similarity of sequences and conserved domains as possible "Multicopper oxidases" (group in which the laccases are) were prospected by the region conserved for laccases L3 (HLHGH). This strategy returned three ORFs, the ORF50MF; the ORF51ME and the ORF13SE (lacmeta), which were cloned and subjected to super-expression and purification analyzes. LacMeta, similar in 82% to the hypothetical protein sequence of Streptomyces rubidus [WP_069465126.1], was the protein that presented the best expression and purification result and was then subjected to kinetic characterization. The protein fused to a hexa-histidine tail was purified in the homo-trimeric form with 128.22 kDa and presented optimum acidic pH activity for the ABTS substrate, for which obtained the catalytic parameters k... (Complete abstract click electronic access below) / Mestre

As compostagens abrigam uma grande riqueza microbiológica, englobando populações com distintos requerimentos e tolerâncias fisiológicas que se sucedem ao longo do processo de biodegradação aeróbica da matéria orgânica e que resultam na elevação espontânea de temperatura até 80&#176; C. Com a utilização de abordagens de metagenômica e metatranscritômica, investigamos a composição e a diversidade taxonômica, bem como as funções metabólicas de comunidades microbianas da compostagem termofílica do Parque Zoológico de São Paulo. Foram analisadas amostras em série temporal de duas composteiras (ZC3 e ZC4), as quais exibiram temperaturas entre 50ºC-75ºC ao longo de 99 dias do processo. Verificamos que a degradação de toda a biomassa foi realizada essencialmente por bactérias, e que a estrutura e composição das comunidades microbianas variam ao longo do processo, com elevada abundância relativa das Ordens Clostridiales, Bacillales e Actinomycetales, assim como observado em outros sistemas de compostagem. Entre os organismos abundantes no processo, identificamos unidades taxonômicas operacionais (OTUs) referentes a organismos não-cultiváveis e/ou com genoma ainda desconhecido. O genoma parcial de uma destas OTUs foi reconstruído, a qual provavelmente pertence a um novo gênero da ordem Bacillales. A dinâmica do processo de compostagem foi evidenciada pela variação do número de OTUs e do índice de diversidade filogenética ao longo do tempo, sendo que o início do processo e a fase após a revira apresentaram a maior diversidade. Os resultados indicam que o processo de revira (aeração da massa de composto) impacta fortemente a estrutura e a composição da microbiota e que a desconstrução da biomassa vegetal ocorre de forma sinérgica e sequencial. A variedade de microrganismos e de funções metabólicas ativas na compostagem termofílica reforça o seu potencial de ser uma promissora fonte de bactérias e enzimas termorresistentes úteis em processos industriais. / Composting harbors considerable microbial richness, comprising populations with distinct physiological requirements and tolerances that succeed one another throughout the aerobic biodegradation of the organic matter, resulting in spontaneous temperature rise up to 80&#176; C. Using metagenomic- and metatranscritomic-based approaches, we investigated the composition and taxonomic diversity as well as metabolic functions of microbial communities of a thermophilic composting operation in the São Paulo Zoo Park. We have analyzed time-series samples from two composting cells (ZC3 and ZC4) which exhibited sustained thermophilic profile (50&#176;C-75&#176;C) over 99 days of the process. We found that all biomass degradation was essentially performed by bacteria. The structure and composition of microbial communities vary throughout the process with a high relative abundance of Clostridiales, Bacillales and Actinomycetales, as observed in other composting systems. Among the organisms abundant in the process, we identify Operational Taxonomic Units (OTUs) of uncultivated organisms or with unknown genomes. The partial genome of one of these OTUs was obtained and shown to belong probably to a new genus of Bacillales. Our time-series data showed that the number of OTUs and phylogenetic diversity index changed during composting revealing the dynamics of the process, with the beginning and the stage after turning procedure presenting the highest diverse microbiota. These results indicate that the turning procedure (compost aeration) strongly impacts the microbiota structure and composition and that the deconstruction of the biomass occurs synergistically and sequentially. The huge diversity of microorganisms and metabolic functions active in thermophilic composting strengthen its potential as a promising source of new bacteria and thermostable enzymes that may be helpful in industrial processes.

The Arctic is undergoing a rapid environmental shift with increasing temperatures and precipitations expected to continue over the next century. Yet, little is known about how microbial communities and their underlying metabolic processes will respond to ongoing climatic changes. To address this question, we focused on Lake Hazen, NU, Canada. As the largest High Arctic lake by volume, it is a unique site to investigate microbial responses to environmental changes. Over the past decade, glacial coverage of the lake has declined. Increasing glacial runoff and sedimentation rates in the lake has resulted in differential influx of nutrients through spatial gradients. I used these spatial gradients to study how environmental changes might affect microbial community structure and functional capacity in Arctic lakes. I performed a metagenomic analysis of microbial communities from hydrological regimes representing high, low, and negligible influence of glacial runoff and compared the observed structure and function to the natural geochemical gradients. Genes and reconstructed genomes found in different abundances across these sites suggest that high-runoff regimes alter geochemical gradients, homogenise the microbial structure, and reduce genetic diversity. This work shows how a genome-centric metagenomics approach can be used to predict future microbial responses to a changing climate.

No description available.

Orientador: Jackson Antônio Marcondes de Souza / Banca: Manoel Victor Franco Lemos / Banca: Amanda Azarias Guimarães / Resumo: Desde a expansão da indústria, a partir da revolução industrial, a população mundial tem crescido de forma exponencial. Este aumento populacional aliado aos avanços tecnológicos constantes alavancou o consumo mundial de energia. Este cenário tem incentivado países do mundo todo a buscar alternativas para aumentar a produção de energia. Uma das alternativas adotadas são os biocombustíveis, onde o etanol tem lugar de destaque. Para tanto, a degradação de biomassa vegetal, para a liberação dos açúcares estruturais da fibra vegetal para fermentação, tem se intensificado. O etanol é o principal biocombustível brasileiro e o uso de biomassa vegetal é uma alternativa para o aumento de sua produção. No entanto, a ação enzimática ineficiente na degradação de polissacarídeos estruturais impede a produção industrial. Uma solução é a prospecção de enzimas degradantes de biomassa e um ambiente para esta busca pode ser o rúmen. O qual é um ambiente rico em micro-organismos que degradam a lignocelulose. Considerando que cerca de 99% dos micro-organismos não são passíveis ao cultivo tradicional, a fim de romper com estas limitações foi usada a abordagem metagenômica neste estudo para caracterização de genes com potencial para degradar biomassa e também para avaliação da diversidade taxonômica do ambiente ruminal bovino. Foram coletadas amostras de rúmen de um gado Nelore para a obtenção de DNA, que posteriormente foi sequenciado pelo sequenciador HiScan SQ (Illumina). Foram obtidas 65 milhões de sequências, cada uma com 100 pb, que foram analisadas no servidor MG-RAST. Para montar o perfil taxonômico deste metagenoma foram usados três bancos de dados na análise das sequências: Ribossomal database Project (RDP), que encontrou 18 filos na amostra; Greengenes, que encontrou 16 filos; e SILVA Small SubUnit (SSU) onde foram encontrados 22 filos. Dentre todos os filos encontrados o Firmicutes foi o... / Abstract: Since the expansion of industry through the Industrial Revolution, the world population has increased unprecedented. This rise together the constant technological advances leveraged the world's energy consumption. This scenario has encouraged countries around the world to seek alternatives to higher energy production, being the biofuels one of the adopted alternatives, which ethanol has excelled. Therefore, the plant biomass degradation for the release of structural sugars from plant fiber fermentation has intensified. Ethanol is the main Brazilian biofuel and the use of plant biomass is an alternative for increasing its production. However, inefficient enzymatic action in the degradation of structural polysaccharides prevents industrial production. One solution is the prospect of biomass degrading enzymes and an environment for this search may be the rumen, which is an environment rich in microorganisms that degrade lignocellulose. Whereas about 99% of the microorganisms are not amenable to traditional growth, in order to break these limitations was used a metagenomics approach in this study to characterize genes with potential to degrade biomass and to evaluate the taxonomic diversity of bovine rumen environment. Rumen samples were collected from Nelore cattle for obtaining total DNA, which was subsequently sequenced by SQ HiScan (Illumina) sequencer. Sixtyfive million sequences were obtained, each with a 100 bp, which were analyzed by MG-RAST server. In order to mount the taxonomic profile of this metagenomic we used three databases on the analysis of sequences: Ribosomal Database Project (RDP), which found 18 phyla in the sample; GreenGenes, which found 16 phyla; and SILVA Small subunit (SSU) which found 22 phyla. Among all the phyla, Firmicutes was the most abundant, followed by Bacteroidetes and Proteobacteria by the three databases. For the functional analysis were used five databases for prospecting glycoside Hydrolases ... / Mestre