Humans harbour a diverse suite of microorganisms in and on their bodies. These microorganisms collectively amount to 10 times more cells than human cells in the body, and their combined genomes have more than 100 times more genes than the human genome does. Despite our understanding of the composition, diversity, and abundance of microorganisms of the human body, it is surprising how little we know about the structure and function of the human microbiome. Here, I use network structure to describe interactions among human-associated microbiota and the human body by exploring differences in structure of human microbiomes across five regions of the body and the robustness of these networks to perturbations. My results show that positive interactions among microbiota are extremely important in structuring microbiome networks and those structural aspects of microbiome networks play a major role in their response to perturbations.

The numerous benefits associated with natural products isolated from the environmental sources, including soil bacteria, plants and fungi, are long known and well appreciated. Interestingly, the immense number of microorganisms that reside within our bodies and whose cell counts greatly outnumber our own represents a potentially new and practically untapped reservoir of bioactive compounds. With the advent of next generation sequencing we are only now starting to realize the complexity and biological diversity of the human microbiome. With this ever-increasing flow of genomic information, more bioactive potential in these microbes can be identified. For instance, biosynthetic assembly lines responsible for the production of two largest classes of bioactive compounds, polyketides and nonribosomal peptides, can be readily identified within the microbial genomes, providing us with a view of their bioactive profiles. In addition to the identification of biosynthetic assembly lines, the building blocks of polyketide and nonribosomal peptide products can also be accurately predicted, given the well-understood logic of assembly line operations. Nonetheless, the identification of actual products is still lagging behind. The discovery of these bioactive molecules can be achieved, however, by establishing a unique connection between genomes and molecules. Using several concrete examples, this thesis demonstrates how both metabolomic and biochemoinformatic platforms can assist in discovery of bioactive small molecules. More specifically, investigations involving three members of the human microbiome, Streptococcus mutans, Lactobacillus plantarum and Pseudomonas aeruginosa, provide distinct examples of identification of bioactive agents and assessment of their immunomodulatory potential. Interrogating the human microbiome form the angle of small molecules is critical for evaluation of microbial effects on our cells, and ultimately our health. Studying these agents will hopefully reveal interesting principles on how microorganisms speak to human cells and how this communication could lead to therapeutic strategies or downstream mechanistic revelations. / Thesis / Master of Science (MSc) / The numerous benefits associated with natural products isolated from the environmental sources, including soil bacteria, plants and fungi, are long known and well appreciated. Interestingly, the immense number of microorganisms that reside within our bodies and whose cell counts greatly outnumber our own represents a potentially new and practically untapped reservoir of bioactive compounds. With the advent of next generation sequencing we are only now starting to realize the complexity and biological diversity of the human microbiome. With this ever-increasing flow of genomic information, more bioactive potential in these microbes can be identified. For instance, biosynthetic assembly lines responsible for the production of two largest classes of bioactive compounds, polyketides and nonribosomal peptides, can be readily identified within the microbial genomes, providing us with a view of their bioactive profiles. In addition to the identification of biosynthetic assembly lines, the building blocks of polyketide and nonribosomal peptide products can also be accurately predicted, given the well-understood logic of assembly line operations. Nonetheless, the identification of actual products is still lagging behind. The discovery of these bioactive molecules can be achieved, however, by establishing a unique connection between genomes and molecules. Using several concrete examples, this thesis demonstrates how both metabolomic and biochemoinformatic platforms can assist in discovery of bioactive small molecules. More specifically, investigations involving three members of the human microbiome, Streptococcus mutans, Lactobacillus plantarum and Pseudomonas aeruginosa, provide distinct examples of identification of bioactive agents and assessment of their immunomodulatory potential. Interrogating the human microbiome form the angle of small molecules is critical for evaluation of microbial effects on our cells, and ultimately our health. Studying these agents will hopefully reveal interesting principles on how microorganisms speak to human cells and how this communication could lead to therapeutic strategies or downstream mechanistic revelations.

Sphingolipids (SLs) are complex lipid-derived structures that are essential components of cell membranes in eukaryotes and some bacteria. SLs and their complex derivatives ceramides are known to be involved in multiple processes such as the formation of lipid rafts, cell signalling and membrane trafficking. The first step of SL biosynthesis is universal to all sphingolipid-producing organisms from bacteria to humans and is catalysed by the enzyme serine palmitoyltransferase (SPT). SPT is a member of the alpha-oxoamine synthase (AOS) family of pyridoxal- 5'-phosphate-dependent enzymes. All AOS family enzymes retain a high degree of structural homology and catalyse the decarboxylative Claisen-like condensation of amino acids with thioester substrates. The SPT enzyme catalyses the formation of the universal SL precursor, 3-ketodihydrosphingosine (KDS), by condensation of L-serine and coenzyme A-derived palmitic acid. Being the key controller in SL biosynthesis, SPT plays a big role in regulating natural and pathological processes. A lot of research interest has been recently generated by SLs isolated from bacterial members of the human microbiome and their roles in human health. Increasing evidence suggests that some of these SLs possess immunoregulatory effects and can have a direct impact on the immunity of the host. Bacteroides fragilis is a commensal gut-dwelling bacterium that belongs to a few human microbionts known to produce unique iso-branched sphingolipids (isoSLs); these have been shown to influence the human iNKT cell count. The production of SLs in B.fragilis is completely regulated by a gene product BF2461. In this work, BF2461 was expressed and purified; using a combination of UV-vis spectrometry, enzymatic assays, mass spectrometry and protein X-ray crystallography, it has been confirmed to be an SPT. The substrate specificity of the BfSPT has been assessed with a range of different chain-length substrates, including less common 15 and 17-carbon chain length coenzyme A substrates. The enzyme can produce different types of SL precursors with a preference for the 16-carbon chain substrate palmitoyl- CoA. However, at high levels of PCoA, a substrate inhibition is observed that might point to a natural control mechanism employed by the bacterium in favour of producing iso-branched SLs (isoSLs). The structure of BfSPT has been elucidated in a complex with its amino acid substrate L-serine. Search and analysis of putative SPTs from other microbiome-associated bacteria that produce isoSLs show that they share high similarity with an average amino acid conservation of 74%, suggesting they might be adapted to a particular type of substrate. In this respect, BfSPT might be the first isoSL-producing SPT to be structurally characterised, and the first one to have a direct impact on human health. Further structural data were obtained on protein complexes with L-cycloserine and L-penicillamine, some common inhibitors of the PLP-dependent enzymes. The structure obtained in the presence of L-penicillamine provides the first direct structural evidence of the inhibitory mechanism by a thiazolidine complex formation in the active site of a PLP-dependent enzyme. These findings shed light on certain aspects of the reaction and inhibition mechanisms of BfSPT as well as opening new prospects into researching this interesting target and its impact on the human microbiome.

The new field of ‘omics’ has spawned the development of metaproteomics, an approach that has the ability to identify and decipher the metabolic functions of a proteome derived from a microbial community that is largely uncultivable. With the development and availabilities of high throughput proteomics, high performance liquid chromatography coupled to mass spectrometry (MS) has been leading the field for metaproteomics. MS-based metaproteomics has been successful in its’ investigations of complex microbial communities from soils to the human body. Like the environment, the human body is host to a multitude of microorganisms that reside within the skin, oral cavity, vagina, and gastrointestinal tract, referred to as the human microbiome. The human microbiome is made up of trillions of bacteria that outnumber human genes by several orders of magnitude. These microbes are essential for human survival with a significant dependence on the microbes to encode and carryout metabolic functions that humans have not evolved on their own. Recently, metaproteomics has emerged as the primary technology to understand the metabolic functional signature of the human microbiome. Using a newly developed integrated approach that combines metagenomics and metaproteomics, we attempted to address the following questions: i) do humans share a core functional microbiome and ii) how do microbial communities change in response to disease. This resulted in a comprehensive identification and characterization of the metaproteome from two healthy human gut microbiomes. These analyses have resulted in an extended application to characterize how Crohn’s disease affects the functional signature of the microbiota. Contrary to measuring highly complex and representative gut metaproteomes is a less complex, controlled human-derived microbial community present in the gut of gnotobiotic mice. This human gut model system enhanced the capability to directly monitor fundamental interactions between two dominant phyla, Bacteroides and Firmicutes, in gut microbiomes colonized with two or more phylotypes. These analyses revealed membership abundance and functional differences between phylotypes when present in either a binary or 12-member consortia. This dissertation aims to characterize host microbial interactions and develop MS-based methods that can provide a better understanding of the human gut microbiota composition and function using both approaches.

Microbial communities play important roles in human health and disease, are essential components of terrestrial and marine ecosystems, and are crucial for producing commercially valuable molecules in industrial processes. These communities consist of hundreds of species involved in complex interactions. Mapping the interrelationships between different species in a microbial community is vital for understanding and controlling ecosystem structure and function. Advances in sequencing and other omics technologies have led to thousands of datasets containing information about microbial composition, gene expression, and metabolism in microbial communities associated with human hosts and other environments. These provide valuable information in understanding how microbes interact with each other and how their interactions affect the health of their host (e.g., human or plant). Furthermore, understanding these interactions paves the way for the rational design and modulation of synthetic communities for producing antibiotics, biofuels, and pharmaceutical products. The first part of my thesis is focused on improving the workflow for the inference of microbial co-occurrence relationships from abundance data. Toward this goal, we developed Microbial Co-occurrence Network Explorer (MiCoNE), a pipeline that infers microbial co-occurrences from 16S ribosomal RNA (16S rRNA) amplicon data. This pipeline involves numerous complex steps that require specific tools and parameter choices, posing open questions about the robustness and uniqueness of the inferred networks. Through MiCoNE, we systematically analyzed how these choices of tools affect the final network and proposed guidelines on appropriate tool selection for a particular dataset. We envisage that this pipeline could be used to integrate multiple datasets and generate comparative analyses and consensus networks that can guide our understanding of microbial community assembly in different biomes. The second part of my thesis focuses on microbe-host interactions rather than microbe-microbe associations. In particular, we sought to predict the effects of microbial metabolites on human receptors and their associated regulatory pathways. We specifically focus on the Aryl hydrocarbon receptor (AHR), a ligand-mediated transcription factor involved in tumorigenesis. In this project, we aimed to systematically predict the binding of diverse microbial metabolites secreted from microorganisms found in the human oral microbiome to the AHR to identify links between the microbiome and cancer initiation. We further build a mathematical model of the AHR regulatory pathway and model the effects of ligand binding on downstream molecules. We envision that these methods could be used to predict the impact of microbial dysbioses on human regulatory pathways. In the final part of my thesis, we turn to the question of whether computational algorithms can help control microbial community growth to achieve specific objectives. In particular, we describe the development of a reinforcement learning algorithm to learn optimal environmental control strategies to steer a microbial community towards a certain goal, such as reaching a specific taxonomic distribution or producing desired metabolites. We train the reinforcement learning framework through community-level simulations of genome-scale metabolic models (GEMs) for different microbial species in bioreactor systems. In this project, we simulate a simple case study with two auxotrophic mutants to verify the algorithm's validity. Ultimately we aim to simulate the implementation of the algorithm in experimental bioreactor systems. Overall, the work presented in this thesis demonstrates how microbe-microbe and microbe-environment (including microbe-host) interactions represent plastic system-level properties whose understanding can help unravel the role of microbial communities in specific diseases. Correspondingly, manipulating these interactions, e.g., by appropriately modifying environmental conditions, can serve as a promising strategy for steering communities towards desired states, including producing valuable molecular products. / 2024-11-06T00:00:00Z

Lower respiratory tract infectious diseases are a world-wide healthcare burden with bacterial pathogens accounting for a large portion of primary and secondary infections. The human respiratory tract is home to hundreds of species of microbes that comprise the human airway microbiome. These commensals play a crucial role in human health in part by providing colonization resistance against pathogens. In a previous study from the Surette lab it was shown that specific bacterial isolates from the respiratory microbiome inhibits the growth of pathogens aerobically. This included an isolate of Staphylococcus aureus which inhibited the growth of Enterococcus faecium. This activity was further characterized in this thesis and the underlying mechanism was explored through comparative genomics. As well, this observation provided proof-of-concept for a large-scale screen for additional isolates which inhibit pathogen growth. I hypothesized that the respiratory tract microbiota included many other bacteria capable of inhibiting the growth of respiratory tract pathogens in both aerobic and anaerobic environments, and that anaerobic conditions will identify new activities not detected aerobically. To examine and identify potential beneficial bacteria, I have screened ~5000 respiratory tract bacteria from the Surette lab’s airway isolate collection against four pathogens: Streptococcus pneumoniae, Staphylococcus aureus, Pseudomonas aeruginosa and Klebsiella pneumoniae. The respiratory tract commensals were pinned onto the pathogen-lawn and their interaction was expressed as zones of clearing or altered growth phenotypes of the pathogen. The results of the screen showed that anti-pathogen activity was a common feature of respiratory tract commensals. In particular, S. pneumoniae was inhibited by taxonomically diverse members of the microbiota representing three phyla (Proteobacteria, Firmicutes and Actinobacteria). Many of the facultative anaerobes that inhibited S. pneumoniae expressed their activity in anerobic conditions. / Thesis / Master of Science (MSc) / The human respiratory tract harbours commensal and pathogenic bacteria, and the latter cause most of the lower respiratory tract infections. The commensal bacteria help to train the immune system and impede the growth of pathogens through colonization resistance. A previous study by the Surette lab identified bacterial isolates from the respiratory tract that inhibit the growth of select pathogens, among them, a particular strain of Staphylococcus aureus. Based on the results of the earlier study, I hypothesized that the respiratory tract bacteria is a good source of commensals that can inhibit the growth of S. aureus and other respiratory pathogens, such as Streptococcus pneumoniae, Pseudomonas aeruginosa and Klebsiella pneumoniae. To find potential therapeutic bacteria, I screened ~5000 respiratory tract isolates from the Surette lab’s strain collection for the ability to impair growth of target pathogens. Additionally, I further characterized the activity of the previously identified S. aureus strain against various Lactobacillalles strains and used comparative genomics to identify potential biosynthetic genes required for biosynthesis of molecules with antibacterial activity within the genome of S. aureus. The research reported in this thesis demonstrates that many commensal bacteria that live within our airways have the ability to inhibit the growth of bacterial pathogens. This work may provide a new source of antibiotics against respiratory infections and new strategies to reduce susceptibility to infections in vulnerable populations.

Complex microbiomes are part of the food we eat: they are naturally present on the raw material, they merge along the food system, or they can be intentionally inoculated. Whether their presence is desired, such as in case of fermentation or probiotic supplementation, or undesired, in case of pathogenic or spoilage microbes, depends on who they are and what they are doing and therefore several studies investigated the microbiota of specific foods. However, the diversity of food microbiomes remains largely unexplored and similar studies present inconsistencies in methods and results. The study of the food microbiome is relevant also in light of the human microbiome and its multifaceted connection to hosts’ health status. Diet is one of the main factors influencing the human microbiome and many studies investigated how nutrition impacts the endogenous microbial communities both in the gut and in the oral cavity. Nevertheless, they largely overlooked the possibility of direct contribution of food-origin microorganisms. The primary aim of my PhD was the comprehensive characterization of foodborne microbial communities with the ultimate goal of estimating their impact on the human microbiome. This research intended to be humble contribution to the global effort in understanding the microbial sources building these composite ecosystems inhabiting the human body. In order to explore the food microbiome diversity, I selected and collected 583 publicly available food (shotgun) metagenomes and integrated them with 1950 newly sequenced food metagenomes. Through an assembly-based pipeline, I reconstructed >10,000 metagenome-assembled genomes (MAGs) that resulted in 290 previously undescribed taxa and, hence, firstly observed in this work. I characterized the composition of microbial communities in food, proving strong specificity across food categories and types through statistical analysis and machine learning approaches. The uniformly and coherently processed curated metadata, taxonomic profiles and reconstructed genomes are publicly available in a resource called curatedFoodMetagenomicData (cFMD). To investigate the presence of food-associated bacteria among human oral and gut microbiomes, I analyzed 20,000 human metagenomes available in curatedMetagenomicData (cMD) through the same expanded pipeline used for food samples. The overlap between food and human microbiomes showed high variations according to host characteristics and the food prevalent species accounted on average for 3% of relative abundance in adult microbiomes. I recognized 43 bacterial species prevalent in both environments that were investigated at the strain level, showing close genomic similarities of strains found both in food and humans.To our knowledge this was the first attempt to investigate the global food microbiome and to estimate its involvement in human microbiome at a large-scale. Our results showedan expansion of known and yet-to-be-isolated species associated with food microbiomes, their characterization to uncover microbial diversity and provide insights on links with the human microbiome, and the release of a publicly-available resource as cFMD that will support the use of metagenomics in food microbiology and food safety, certificationand quality control applications.

<p>Nonribosomal peptides, polyketides, and fatty acids comprise a distinct subset of microbial secondary metabolites produced by similar biosynthetic methods and exhibit broad structural diversity with a high propensity for biological activity. Dedicated studies of these specific microbial small molecules have identified numerous potent actions towards human cells with many clinical translations. Interestingly, most therapeutically used nonribosomal peptides and polyketides were discovered from soil bacteria, meanwhile, bacteria that have co-evolved within a human context, the human microbiota, have barely been explored for secondary metabolites. The central goal of this thesis is to explore the secondary metabolome of human microbiota for nonribosomal peptides and polyketides, which are hypothesized to possess biological activities significant within the human host context. Candidate organisms were chosen for their established connections to human health and evidence suggestive of secondary metabolite production. Specifically, questions about gene to molecule prediction capability, metabolite production, structural diversity, and biological activity were explored from studies of the dental caries linked Streptococcus mutans UA159, from the probiotic Lactobacillus plantarum WCFS1, and the Crohn’s disease associated Faecalibacterium prausnitzii.</p> / Master of Science (MSc)

L’interès creixent de la població general per la “medicina natural”, juntament amb els efectes beneficiosos que s’han demostrat per al resveratrol, ha incrementat la presència en els mercats d’aliments funcionals o nutracèutics basats en la seva composició. Per a poder fer al•legacions nutricionals i de propietats saludables en aquests tipus de productes és necessari un suport científic que recolzi, amb la màxima evidència, els efectes que es pretenen declarar, tenint en compte els paràmetres relacionats amb la biodisponibilitat i l’efecte de la matriu de l’aliment. La biodisponibilitat del resveratrol és baixa, donat el seu elevat metabolisme, de manera que els seus efectes beneficiosos es troben, actualment, en una certa controvèrsia. Les futures investigacions s’estan enfocant cap a la possible activitat dels metabòlits del resveratrol. Abans, però, es requereix informació més concreta sobre la biodisponibilitat del resveratrol i, sobretot, del seu metabolisme després del consum de quantitats moderades d'aliments que el continguin, per tal de conèixer les concentracions dels diferents metabòlits que es poden assolir en l’organisme. Per a dur a terme aquest tipus d’estudis es requereixen tècniques analítiques d’elevada sensibilitat i selectivitat que permetin una clara identificació del perfil metabòlic del resveratrol en mostres biològiques. L’objectiu principal d’aquesta Tesi Doctoral és conèixer el perfil metabòlic del resveratrol quan és administrat en dosis dietètiques en humans i la influència de la matriu de l’aliment en la seva biodisponibilitat, així com desenvolupar la metodologia adient per cromatografia líquida acoblada a espectrometria de masses (UPLC-MS/MS). Per a assolir aquest objectiu i gràcies a la disponibilitat d’estàndards purs dels metabòlits pròpiament, ja sigui per la seva recent disponibilitat comercial o expressament sintetitzats, s’ha desenvolupat una metodologia òptima per a l’anàlisi del perfil metabòlic del resveratrol, que ha estat validada segons els criteris establerts per la FDA. Amb aquesta metodologia, s’ha definit el perfil metabòlic del resveratrol més complet de tota la literatura actual, constituït per 21 compostos que engloben als metabòlits de fase II del resveratrol i el piceid i els derivats de l’acció microbiana, proposant les estructures químiques d’aquells dels quals no es disposa estàndard. La quantificació d’aquest perfil, excretat 4 hores després de la ingesta d’una beguda funcional a base d’extracte de raïm, ha demostrat diferències interindividuals significatives. El coneixement de la biodisponibilitat i el metabolisme del resveratrol al llarg del temps s’ha dut a terme amb un estudi farmacocinètic, en el qual s’ha demostrat que, després d’un consum moderat de vi negre i d’un nutracèutic a base d’extracte de raïm, el piceid pot ser absorbit ràpidament en la seva forma intacte, però assolint baixes concentracions; mentre que la formació de metabòlits de resveratrol requereix un temps major, que encara s’allarga més per als d’origen microbià. L’excreció més lenta dels sulfats de resveratrol ha aportat més evidència a la possible saturació de les vies de glucuronidació del resveratrol. Pel que fa a l’efecte de la matriu alimentària, s’ha demostrat que l’alcohol no afecta al metabolisme del resveratrol, estudiant-ne el perfil metabòlic excretat. A més a més, l’excreció urinària global del perfil metabòlic del resveratrol no s’ha vist afectada per la matriu que constitueixen uns comprimits a base d’extracte de raïm, com a producte nutracèutic, en comparació amb la del vi negre; tot i que la dissolució del comprimit implica una absorció retardada dels compostos d’aquest, que fa augmentar la quantitat de metabòlits microbians excretats. / The beneficial effects reported for resveratrol have aroused interest in its consumption, and thus a lot of functional foods or nutraceuticals based on their composition have been developed. Before making nutritional and health claims about these products, more information is required on the resveratrol bioavailability and metabolism after moderate doses consumed and with a special regard on the effect of the food matrix. In such studies, high sensitivity analytical techniques are necessary to allow clear identification of the metabolic profile of resveratrol in biological samples. The aim of this thesis is to determine the metabolic profile of resveratrol when administered at dietary doses in humans and the influence of the food matrix on its bioavailability, as well as to develop a suitable methodology by liquid chromatography coupled to mass spectrometry (UPLC-MS/MS). With the pure metabolite standards now available, an optimized methodology was developed and validated for analysis of the resveratrol metabolic profile. This method defined the widest profile until now available, consisting of 21 compounds which include resveratrol and piceid phase II metabolites and those derived from microbiota, for whose chemical structures were suggested. The quantification of this profile, excreted 4 hours after ingestion of a grape extract functional beverage, demonstrated significant interindividual differences. The behaviour of resveratrol metabolism after the post-ingestion of natural products was studied in a pharmacokinetic study, which showed that, after a moderate consumption of red wine and a grape extract nutraceutical, piceid can be quickly absorbed in its intact form, but achieving low concentrations. Metabolites’ formation required more time and even though for the microbial ones. The slow excretion of resveratrol sulfates provided more evidence to the possible saturation of the glucuronidation pathway. Regarding the food matrix effect, it was demonstrated that alcohol does not affect resveratrol metabolism. In addition, overall urinary excretion of the resveratrol metabolic profile was not affected by the tablet matrix of the grape extract nutraceutical, compared to red wine. However, dissolution of the tablet delayed absorption of their compounds, which increases the amount of microbial metabolites excreted.

In human microbiome analysis, sequencing of bacterial 16S rRNA genes has revealed a role for the gut microbiota in maintaining health and contributing to various pathologies. Novel community analysis techniques must be evaluated in terms of bias, sensitivity, and reproducibility and compared to existing techniques to be effectively implemented. Next- generation sequencing technologies offer many advantages over traditional fingerprinting methods, but this extensive evaluation required for the most efficacious use of data has not been performed previously. Illumina libraries were generated from the V3 region of the 16S rRNA gene of samples taken from 12 unique sites within the gastrointestinal tract for each of 4 individuals. Fingerprint data were generated from these samples and prominent bands were sequenced. Sequenced bands were matched with OTUs within their respective libraries. The results demonstrate that denaturing gradient gel electrophoresis (DGGE) represents relatively abundant bacterial taxa (>0.1%) beta-diversity of all samples was compared using Principal Coordinates Analysis (PCoA) of UniFrac distances and Multi-Response Permutation Procedure (MRPP) was applied to measure sample cluster strength and significance; indicator species analysis of fingerprint bands and Illumina OTUs were also compared. The results demonstrate overall similarities between community profiling methods but also indicate that sequence data were not subject to the same limitations observed with the DGGE method (i.e., only abundant taxa bands are resolved, unable to distinguish disparate samples). In addition, the effect of stochastic fluctuations in ???????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????? differ for DGGE and next-generation sequencing. I compared pooled and individual reactions for samples of high and low template concentration for both Illumina and DGGE using the combined V3-V4 region of the 16S rRNA gene, and demonstrated that template concentration has a greater impact on reproducibility than pooling. This research shows congruity between two disparate molecular methods, identifies sources of bias, and establishes new guidelines for minimizing bias in microbial community analyses.