While the major events in prokaryotic cell cycle progression are likely to be coordinated with transcriptional and metabolic changes, these processes remain poorly characterized. Unlike many rapidly-growing bacteria, DNA replication and cell division are temporally-resolved in mycobacteria, making these slow-growing organisms a potentially useful system to investigate the prokaryotic cell cycle. To determine if cell-cycle dependent gene regulation occurs in mycobacteria, we characterized the temporal changes in the transcriptome of synchronously replicating populations of Mycobacterium tuberculosis (Mtb). By enriching for genes that display a sinusoidal expression pattern, we discover 485 genes that oscillate with a period consistent with the cell cycle. During cytokinesis, the timing of gene induction could be used to predict the timing of gene function, as mRNA abundance was found to correlate with the order in which proteins were recruited to the developing septum. Similarly, the expression pattern of primary metabolic genes could be used to predict the relative importance of these pathways for different cell cycle processes. Pyrimidine synthetic genes peaked during DNA replication and their depletion caused a filamentation phenotype that phenocopied defects in this process. In contrast, the IMP dehydrogenase guaB2 dedicated to guanosine synthesis displayed the opposite expression pattern and its depletion perturbed septation. Together, these data imply obligate coordination between primary metabolism and cell division, and identify periodically regulated genes that can be related to specific cell biological functions.

Benzo[a]pyrene (BaP) is a human carcinogen, which is metabolized by a variety of enzyms such as cytochrome P450 (CYP) and epoxide hydrolase. The aim of this work was to study BaP metabolism in vitro by the hepatic microsomal system of rats treated with CYP inducers and by human cytochrome P450 1A1 (CYP1A1) expressed in eukaryotic and prokaryotic systems. An eukaryotic expression system consisted of microsomes isolated from insect cells, whereas a prokaryotic expression system was formed by the membrane fragments of E. coli. In the case of recombinant human CYP1A1, we investigated the influence of cytochrome b5, NADPH:cytochrome P450 reductase (CPR) and epoxide hydrolase in BaP oxidation. Isolation and purification of rabbit hepatic CPR was another aim of this work. BaP metabolites were separated by HPLC. The results found in this work demostrate the fact that hepatic microsomal systems of rats treated with an inducer of CYP1A (Sudan I), an inducer of CYP2B (phenobarbital) and an inducer of CYP3A (PCN) exhibit higher efficiency of BaP oxidation than microsomes of control rats. BaP is oxidized by human CYP1A1 expressed in the eukaryotic system to six metabolites (BaP-9,10-dihydrodiol, BaP metabolite with unknown structure, BaP-7,8-dihydrodiol, BaP-1,6-dion, BaP-3,6-dion, BaP-3-ol), whereas by human...

Mieux comprendre les mécanismes de la résistance aux antibiotique est un enjeu important dans la lutte contre les maladies infectieuses, qui fait face à la propagation de bactéries multi-résistantes. Les études d'association à l'échelle des génomes sont des outils puissants pour explorer les polymorphismes liés aux variations phénotypiques dans une population. Leur cadre méthodologique est très documenté pour les eucaryotes, mais leur application aux bactéries est très récente. Durant cette thèse, j'ai cherché à rendre ces outils mieux adaptés aux génomes plastiques des bactéries, principalement en travaillant sur la représentation des variations génétiques. En effet, parce que les bactéries ont la capacité à échanger du matériel génétique avec leur environnement, leurs génomes peuvent être trop différents au sein d'une espèce pour être alignés contre une référence. La description des variations par des fragments de séquence de longueur k, les k-mers, offre la flexibilité nécessaire mais ne permet pas une interprétation directe des résultats obtenus. La méthode mise au point teste l'association de ces k-mers avec le phénotype, et s'appuie sur un graphe de De Bruijn pour permettre la visualisation du contexte génomique des k-mers identifiés par le test, sous forme de graphes. Cette vue synthétique renseigne sur la nature de la séquence identifiée: il peut par exemple s'agir de polymorphisme local dans un gène ou de l'acquisition d'un gène dans un plasmide. Le type de variant représenté dans un graphe peut être prédit avec une bonne performance à partir de descripteurs du graphe, rendant plus opérationnelles les approches par k-mers pour l'étude des génomes bactériens / The emergence and spread of multi-drug resistance has become a major worldwide public health concern, calling for better understanding of the underlying resistance mechanisms. Genome-wide association studies are powerful tools to finely map the genetic polymorphism linked to the phenotypic variability observed in a population. However well documented for eukaryotic genome analysis, these studies were only recently applied to prokaryota.Through this PhD project, I searched how to better adapt these tools to the highly plastic bacterial genomes, mainly by working on the representation of the genetic variations in these genomes. Indeed, because the bacteria have the faculty to acquire genetic material by a means other than direct inheritance from a parent cell, their genomes can differ too much within a species to be aligned against a reference. A representation using sequence fragments of length k - the so-called k-mers - offers the required flexibility but generates redundancy and does not allow for a direct interpretation of the identified associations. The method we set up tests the association of these k-mers with the phenotype, and takes advantage of a De Bruijn graph (DBG) built over all genomes to remove the local redundancy of k-mers, and offer a visualisation of the genomic context of the k-mers identified by the test. This synthetic view as DBG subgraphs informs on the nature of the identified sequence: e.g. local polymorphism in a gene or gene acquired through a plasmid. The type of variant can be predicted correctly in 96% of the cases from descriptors of the subgraphs, providing a tractable framework for k-mer-based association studies

A signal transduction process refers to chain of highly regulated biochemical steps which results in the transfer of signal in response to a stimulus in the extracellular environment to the intracellular compartments such as nucleus. Variety of biomolecules such as proteins and lipids participate in such processes. One of the superfamilies of proteins which actively participate in signaling processes is protein kinase which transfers γ-phosphate from Adenosine Triphosphate (ATP) to the specific hydroxyl group(s) in the protein substrates. Phosphorylation and dephosphorylation events are critical in many signal transduction pathways affecting biological system as a whole. Protein phosphorylation carried out by protein kinases has emerged as pre-eminent mechanism for the regulation of variety of cellular processes such as cell growth, development, differentiation, homeostasis, apoptosis, metabolism, transcription and translation. The current thesis encompasses the investigations carried out by the author, using various bioinformatics tools and methods, to comprehend the structural and functional roles of diverse set of protein kinase subfamilies in various eukaryotic and prokaryotic organisms. The present thesis has been divided into various chapters. Chapter 1 of the thesis provides introduction to the superfamily of protein kinases and covers the relevant literature. The database of Kinases in Genomes (KinG) set-up in the author’s group a few years ago (Krupa et al, 2004a), comprises of a collection of Serine/Threonine/Tyrosine protein kinases recognized using bioinformatics approaches, from the genomic data of various eukaryotes, prokaryotes and viruses (Krupa et al, 2004a). KinG database also provides classification of protein kinases into various groups and subfamilies (Hanks et al, 1988). Information on non-kinase domains which are tethered to the catalytic kinase domains is also available for every kinase in the KinG database. KinG is periodically (annually) updated with rise in the number of genome sequence datasets of various organisms, increase in the number of known protein domain families and refinement or reannotation of genomic datasets (Anamika et al, 2008c). Author describes the work on annual update of KinG database in Chapter 2 of the thesis. Availability of an improved version of the human genomic data has provided an opportunity to re-investigate protein kinase complement of the human genome and enabled an analysis of the splice variants. This analysis is also described in Chapter 2. Chapter 3, Chapter 4 and Chapter 5 report recognition and analysis of repertoire of protein kinases in Chimpanzee, two Plasmodium species (Plasmodium falciparum and Plasmodium yoelii yoelli) and Entamoeba histolytica respectively. A detailed analysis of the non-kinase domains which are tethered to catalytic protein kinase domains in eukaryotic organisms is presented in Chapter 6. Chapter 7 discusses a systematic classification framework developed by the author to classify Serine/Threonine protein kinases in prokaryotic organisms. Investigation carried out on 3-D structural aspects of protein kinase-substrate interactions is described in Chapter 8. While identifying protein kinases from genomic data occurrence of protein kinase-like non-kinases (PKLNK), which lack aspartate in a specific position in the amino acid sequence (and hence are unlikely to function as a kinase), has also been observed. Chapter 9 presents an analysis of PKLNKs with an objective of obtaining clues to their functions. Chapter 10 summarizes the main conclusions of the thesis and provides an outlook of the current study. Chapter 1: Chapter 1 provides an introduction to cell signaling and the involvement of protein kinases in various signaling pathways compiled from author’s literature survey. This chapter provides a description of molecular events in cell signaling in prokaryotic and eukaryotic organisms. The diversity, specificity and cellular roles of protein kinases are discussed in detail. Chapter 2: Chapter 2 describes KinG (Kinases in Genomes) database which was first established by Krupa et al (2004a). The KinG database is an on-line compilation of the putative Serine/Threonine/Tyrosine protein kinases encoded in the completely sequenced genomes of archaea, eubacteria, viruses and eukaryotes. Surge in the datasets of genomes, improvements in the quality of the genomic data for various organisms and growing number of protein domain families necessitates periodic update of KinG database. The updated version of KinG holds information on protein kinases for 483 organisms (Anamika et al, 2008c). Availability of draft version of the human genome data in 2001 enabled recognition of repertoire of human protein kinases (Krupa and Srinivasan, 2002a; Manning et al, 2002; Kostich et al, 2002). Over the last 7 years human genomic data is being refined and at present the quality of the human genomic data available is much superior to the one available in 2001. By gleaning the latest version of human genome data, 46 new human protein kinase splice variants have been identified which were not recognized in the earlier studies on human kinome. Improper regulation or mutant forms of many of these newly identified protein kinase splice variants are directly involved in various diseases such as different kinds of cancer, Severe Combined Immunodeficiency Disease (SCID) and Huntington disease. In addition, abnormal forms of mouse orthologues of some of the newly identified human kinase splice variants are known to cause various diseases in mice. This raises the possibility of the human orthologues playing similar roles in the disease processes. Such observations and detailed analysis of these protein kinase splice variants would have a profound influence on drug design and development against various diseases. Chapter 3: Investigations on the identification and analysis of protein kinases encoded in the genome of chimpanzee (chimp) has been discussed in Chapter 3. Further, the kinome complement has been compared between chimp and its evolutionary close relative, human (Anamika et al, 2008b). The shared core biology between chimp and human is characterized by many orthologous protein kinases which are involved in conserved pathways. Domain architectures specific to chimp/human kinases have been observed. Chimp kinases with unique domain architectures are characterized by deletion of one or more non-kinase domains present in the human kinases. Interestingly, counterparts of some of the multi-domain human kinases in chimp are characterized by identical domain architectures but with kinase-like non-kinase domain (PKLNK). Remarkably, for 160 out of 587 chimpanzee kinases no human orthologue with sequence identity greater than 95% could be identified. Variations in chimpanzee kinases compared to human kinases are brought about also by differences in functions of domains tethered to the catalytic kinase domain. For example, the heterodimer forming PB1 domain related to the fold of ubiquitin / Ras-binding domain is seen uniquely tethered to PKC-like chimpanzee kinase. Though chimpanzee and human have close evolutionary relationship, there are chimpanzee kinases with no close counterpart in the human suggesting differences in their functions. This chapter provides a direction for experimental analysis of human and chimpanzee protein kinases in order to enhance our understanding on their specific biological roles. Chapter 4: Chapter 4 describes genome-wide comparative analysis for protein kinases encoded in the two apicomplexa namely Plasmodium falciparum (P. falciparum) (3D7 strain) and Plasmodium yoelii yoelii (P. yoelii yoelii) (17XNL strain) genomes which are causative agents of malaria in human and rodent respectively (Anamika and Srinivasan, 2007). Sensitive bioinformatics techniques enable identification of 82 and 60 putative protein kinases in P. falciparum and P. yoelii yoelii respectively. These protein kinases have been classified further into subfamilies based on the extent of sequence similarity of their catalytic domains (Hanks et al, 1988). The most populated kinase subfamilies in both the Plasmodium species correspond to CAMK and CMGC groups. Analysis of domain architectures enables detection of uncommon domain organisation in kinases of both the organisms such as kinase domain tethered to EF hands as well as pleckstrin homology domain. Components of MAPK signaling pathway are not well conserved in Plasmodium species. Such observations suggest that Plasmodium protein kinases are highly divergent from other eukaryotes. A trans-membrane kinase with 6 membrane spanning segments in P. falciparum seems to have no orthologue in P. yoelii yoelii. 19 P. falciparum kinases (Anamika et al, 2005; Anamika and Srinivasan, 2007) have been found to cluster separately from P. yoelii yoelii kinases and hence these kinases are unique to P. falciparum genome. Only 28 orthologous pairs of kinases could be identified between these two Plasmodium species. Comparative kinome analysis of the two Plasmodium species has thus provided clues to the function of many protein kinases based upon their classification and domain organisation and also implicate marked differences even between two Plasmodium species. Chapter 5: Identification and analysis of the repertoire of protein kinases in the intracellular parasite Entamoeba histolytica (E. histolytica) using sensitive sequence and profile search methods forms the basis of Chapter 5. A systematic analysis of a set of 307 protein kinases in E. histolytica genome has been carried out by classifying them into different subfamilies originally defined by Hanks and Hunter (Hanks et al, 1988) and by examining the functional domains which are tethered to the catalytic kinase domains (Anamika et al, 2008a). Compared to other eukaryotic organisms, protein kinases from E. histolytica vary in terms of their domain organisation and displays features that may have a bearing in the unusual biology of this organism. Some of the parasitic kinases show high sequence similarity in the catalytic domain region with calmodulin/calcium dependent protein kinase subfamily. However, they are unlikely to act like calcium/calmodulin dependent kinases as they lack non-catalytic domains characteristic of such kinases in other organisms. Such kinases form the largest subfamily of protein kinases in E. histolytica. Interestingly a Protein Kinase A/Protein Kinase G-like hybrid kinase subfamily member is tethered to pleckstrin homology domain. Although potential cyclins and cyclin-dependent kinases could be identified in the genome the likely absence of other cell cycle proteins suggests unusual nature of cell cycle in E. histolytica. Some of the unusual kinases recognized in the analysis include the absence of Mitogen activated protein kinase kinase (MEK) as a part of the Mitogen Activated Kinase signaling pathway and identification of trans-membraneous kinases with catalytic kinase region showing a good sequence similarity to Src kinases which are usually cytosolic. Sequences which could not be classified into known subfamilies of protein kinases have unusual domain architectures. Many such unclassified protein kinases are tethered to domains which are cysteine-rich and to domains known to be involved in protein-protein interactions. The current chapter on kinome analysis of E. histolytica suggests that the organism possesses a complex protein phosphorylation network that involves many unusual protein kinases. Chapter 6: Protein kinases phosphorylating Serine/Threonine/Tyrosine residues in several cellular proteins exert tight control over their biological functions. They constitute the largest protein family in most eukaryotic species. Classification based on sequence similarity of their catalytic domains, results in clustering of protein kinases sharing gross functional properties into various subfamilies. Many protein kinases are associated or tethered covalently to domains that serve as adapter or regulatory modules, aiding substrate recruitment, specificity, and also serve as scaffolds. Hence the modular organisation of the protein kinases serves as guidelines to their molecular interaction which has been discussed in Chapter 6. Recent studies on repertoires of protein kinases in eukaryotes have revealed wide spectrum of domain organisation in model organisms across various subfamilies. Occurrence of organism-specific novel domain combinations suggests functional diversity achieved by the protein kinase in order to regulate variety of biological processes. In addition, domain architectures of protein kinases revealed existence of hybrid protein kinase subfamilies and their emerging roles in the signaling of eukaryotic organisms. The repertoire of non-kinase domains tethered to multi-domain kinases in the higher eukaryotes is discussed in Chapter 6. Similarities and differences in the domain architectures of protein kinases in these organisms indicate conserved and unique features that are critical to functional specialization. Chapter 7: Chapter 7 describes systematic classification of Serine/Threonine protein kinases encoded in archaeal and eubacterial genomes. Majority of the Serine/Threonine protein kinases which have been identified in archaeal and eubacterial genomes could not be classified into any of the well known subfamilies (Hanks et al, 1988) of protein kinases suggesting their diversity from kinases in eukaryotes. The extensive prokaryotic Serine/Threonine protein kinase dataset obtained from KinG (Krupa et al, 2004a, Anamika et al, 2008c) has given an opportunity to classify these prokaryotic Serine/Threonine protein kinases mainly into three categories based upon sequence identity based clustering: 1) Species/Genus-specific clusters: Species/Genus-specific Serine/Threonine protein kinases contain members from a particular species or genus of the eubacteria or archaea suggesting requirement of these Serine/Threonine protein kinases for certain lineage specific function. 2) Organism-specific clusters: Organism specific clusters has members from certain specific types of organisms which suggests role of these Serine/Threonine protein kinases in some specific function being carried out by limited sets of prokaryotes. 3) Organism-diverse clusters: Organism diverse clusters suggest common function performed by such kinases in wide variety of organisms. Interestingly, occurrence of several species/genus or organism specific subfamilies of prokaryotic kinases contrasts with classification of eukaryotic protein kinases in which most of the popular subfamilies of eukaryotic protein kinases occur diversely in several eukaryotes. Function-based classification has also been proposed which shows that members of each cluster has specific function to perform. In this analysis, almost 50% of the “clusters” obtained have only one member suggesting their sequence and probably functional divergence. Many prokaryotic Serine/Threonine protein kinases exhibit a wide variety of modular organisation which indicates a degree of complexity and protein-protein interactions in the signaling pathways in these microbes. Chapter 8: A wide spectrum of protein kinases belonging to different Hanks and Hunter groups of kinases and subfamilies has been identified in various eukaryotes. However, specific biological targets (substrates) of many protein kinase subfamilies are still unknown and this is one of the active areas of research. In the current analysis reported in Chapter 8, an attempt has been made to understand protein kinase-substrate interaction and substrate consensus prediction by analyzing known 3-D structures of complexes of kinases and peptide substrates/pseudosubstrates. Considering protein kinase ternary complex structures in their active states, it has been observed that protein kinase residues which are interacting with the substrate residues having constraint are at topologically equivalent positions despite belonging to different Hanks and Hunter protein kinase subfamilies. In this analysis, it has also been observed that the residues in a given kinase subfamily interacting with consensus substrate residues are usually conserved across homologues. Interestingly, in Protein Kinase B and Phosphorylase Kinase subfamily homologues, residues interacting with substrate residue/s having no constraint are not well conserved even within the kinase subfamily suggesting different evolutionary rate of substrate interacting residues. This result is anticipated to be helpful in furthering our understanding of protein kinase-substrate relationship which is likely to be helpful in drug design. Chapter 9: Protein Kinase-Like Non-kinases (PKLNKs) are closely related to protein kinases but they lack the crucial catalytic aspartate in the catalytic loop and hence cannot function as a protein kinase. PKLNKs have been analyzed (Chapter 9) with an objective of obtaining clues about their functions. Using various sensitive sequence analysis methods, 82 PKLNKs from four higher eukaryotic organisms namely, Homo sapiens, Mus Musculus, Rattus norvegicus and Drosophila melanogaster have been recognized. On the basis of their domain combinations and functions of tethered domains, PKLNKs have been classified mainly into four categories: 1) Ligand binding PKLNKs 2) PKLNKs having extracellular protein-protein interaction domain 3) PKLNKs involved in dimerization 4) PKLNKs with cytoplasmic protein-protein interaction module. While members of the first two classes of PKLNKs have transmembrane domain tethered to the PKLNK domain, members of the other two classes of PKLNKs are entirely cytoplasmic in nature. The current classification scheme hopes to provide a convenient framework to classify the PKLNKs from other eukaryotes and it should be helpful in deciphering their roles in cellular processes. Chapter 10: This is a chapter on conclusions of the entire thesis work. Summary of the major outcomes of this thesis work is provided and implications of the work in the area of signal transduction are discussed. In addition to above mentioned work, studies on repertoire of protein kinases from two plant organisms have been carried out and the kinomes have been comparatively analyzed (Krupa et al, 2006) (Appendix 1). Comparison of plant protein kinases with other eukaryotes revealed remarkable differences. Trans-genomic comparison of the protein kinase repertoires of Arabidopsis thaliana and Oryza sativa has enabled identification of members that are uniquely conserved within the two species. Analysis on the domain organisation of plant protein kinases has also been carried out. Appendix 2 presents the work done on Entamoeba histolytica (E. histolytica) ornithine decarboxylase (ODC)-like protein which regulates the polyamine biosynthesis. DFMO (Difluoromethylornithine) is unable to inhibit the E. histolytica ODC-like protein while it inhibits the homologues of ODC in other organisms. Modelling study has suggested substitution of three amino acids in the E. histolytica ODC-like protein because of which DFMO is unable to inhibit the activity of ODC-like protein (Jhingran et al, 2008). All the computational modeling work reported in Appendix 2 was performed by the author while all the laboratory experiments were performed in the laboratory of the collaborator Prof. Madhubala of JNU, New Delhi. The supplementary data pertaining to this thesis is presented in an accompanying CD. The supplementary data in this CD is organized into different folders corresponding to various chapters.

Significant advancements in genome sequencing techniques and other high-throughput initiatives have resulted in the availability of complete sequences of genomes of a large number of organisms, which provide an opportunity to study detailed biological information encoded therein. Identification of functional roles of proteins can aid in comprehension of various cellular activities in an organism, which is traditionally achieved using techniques pertaining to the field of molecular biology, protein chemistry and macromolecular crystallography. The established experimental methods for protein structure and function determination, although accurate and resourceful, are laborious and time consuming. Computational analyses of sequences of gene products and exploration of evolutionary relationships can give clues on protein structure and/or function with reasonable accuracy which can be used to direct experimental studies on proteins of interest, effectively. Moreover, with growing volumes of data, there has been a growing disparity in the number of well-characterized and uncharacterized proteins, further necessitating the use of computational methods for investigating evolutionary and structure-function relationships. The remarkable progress made in the development of computational techniques (Chapter 1) has immensely contributed to the state-of-the-art biological sequence analysis and recognition of protein structure and function in a reliable manner. These methods have largely influenced the exploration of protein sequence-structure-function space. One of the relevant applications of computational approaches is in the understanding of functional make-up of human pathogens, their complex interplay with the host and implications in pathogenesis. In this thesis, sensitive profile-based search procedures have been utilized to address various aspects in the context of three pathogens- Mycobacterium tuberculosis, Plasmodium falciparum and Trypanosoma brucei, which are causative agents of potentially life- threatening diseases. The existing drugs approved for the diseases, although of immense value in controlling the disease, have several shortcomings, the most important of them being the emergence of drug resistance that render the current treatment regimens futile. Thus, the identification of practicable targets and new drugs or new combination therapies become an important necessity. Analyses on structural and functional repertoire of proteins encoded in the pathogenic genomes can provide means for rational identification of therapeutic intervention strategies. This thesis begins with the computational analyses of proteins encoded in M. tuberculosis genome. M. tuberculosis is a primary aetiological agent of tuberculosis in humans, and is o responsible for an estimated 1.5 million deaths every year. The complete genome of the pathogen was sequenced and made available more than a decade ago, which has been valuable in determination of functional roles of its gene products. Yet, functions of many M. tuberculosis proteins remain unknown. Computational prediction of protein function is an on- going process based on ever growing information made available in public databases as well as the introduction of powerful homology recognition techniques. Hence, a continuous refinement is essential to make the most of the sequence data, ensuring its accuracy and relevance. With the use of multiple sequence and structural profile-based search procedures, an enhanced structural and functional characterization of M. tuberculosis proteins, totalling to 95% of the genome was achieved (Chapter 2). Following are the key findings. o Domain definitions were obtained for a total of 3566 of 4018 proteins. Amino acid residue coverage of >70% was achieved for 2295 proteins which constitute more than half of the proteome. o Domain assignments were newly identified for 244 proteins with domain-unassigned regions. Structure prediction for these proteins corroborated all the remote homologyrelationships recognized using profile-based methods, enhancing the reliability of the predictions. o Comparison on domain compositions of proteins between M. tuberculosis and human host, revealed presence of pathogen-specific domains that are not homologous to proteins in human. Such proteins in M. tuberculosis are mainly virulence factors involved in host-pathogen interactions such as immune-dominance and aiding entry and survival in human host macrophages, hence forming attractive targets for drug discovery. o Putative structural and functional information for proteins with no recognizable domains were inferred by means of fold recognition and an iterative profile-based search against sequence database. o Attributing putative structures and functions to 955 conserved hypothetical proteins in M. tuberculosis, 137 of which are reportedly essential to the pathogen, provide a basis to re-investigate their involvement in pathogenesis and survival in the host. Proteins with no detectable homologues were recognized as M. tuberculosis H37Rv-specific, which can serve as promising drug targets. An attempt was made to identify porin-like proteins in M. tuberculosis, considering MspA porin from M. smegmatis as a template. The difficulty in recognition of putative porins in M. tuberculosis is indicative of novel outer membrane channel proteins, not characterized yet, or high representation of ion-channels, symporters and transporters to compensate for the functional role of porins. In addition, MspA-like proteins were not readily recognized in other slow-growing mycobacterial pathogens that are known to infect human host, apart from M. tuberculosis. This indicates probable acquisition of physiological adaptations, i.e. absence of porins, to confer drug-resistance, in the course of their co-evolution with human hosts. Evolutionary relationships recognized between sequence (Pfam) and structural (SCOP) families aided in association of potential structures and/or functions for 55 uncharacterized Pfam domains recognized in M. tuberculosis. Such associations deliver useful insights into the structure and function of a protein housing the uncharacterized domain. The functional inferences drawn for M. tuberculosis proteins based on the predictions can provide valuable basis for experimental endeavours in understanding mechanisms of pathogenesis and can significantly impact anti-tubercular drug discovery programmes. An interesting outcome benefitted from the exercise of exploring relationships between Pfam and SCOP families, was the identification of evolutionary relationship between a Pfam domain of unknown function DUF2652 and class III nucleotidyl cyclases. A detailed investigation was undertaken to assess this relationship (Chapter 3). Nucleotidyl cyclases synthesize cyclic nucleotides which are critical second messengers in signalling pathways. The DUF2652 family predominantly comprises of bacterial proteins belonging to three lineages- Actinobacteria, Bacteroidetes and Proteobacteria. Thus, recognition of evolutionary relationship between these bacterial proteins and nucleotide cyclases is of particular interest due to the indispensability of cyclic nucleotides in regulation of varied biological activities in bacteria. Use of fold recognition program suggested presence of nucleotide cyclase-characteristic topological motif (βααββαβ) in all the members of the DUF2652 family. Detailed analyses on structural and functional features of the uncharacterized set of bacterial proteins corresponding to 50 bacterial genomes, using profile- based alignments, revealed presence of key features typical of nucleotidyl cyclases, including metal-binding aspartates, substrate-specifying residues and transition-state stabilizing residues. Depending on the features, 20 proteins of Actinobacteria lineage, predominantly mycobacteria, of unknown structure and function were identified as putative nucleotide cyclases, 23 proteins of Bacteroidetes lineage were associated with guanylyl cyclases, while 8 uncharacterized proteins of Proteobacteria were recognized as nucleotide cyclase-like proteins (7 adenylyl and one guanylyl cyclase). Sequence similarity-based clustering of the predicted nucleotide cyclase-like proteins with established nucleotide cyclases indicated the apparent evolutionarily distinctness of the subfamily of class III nucleotidyl cyclases predicted. Furthermore, analysis of evolutionarily conserved gene clusters of the predicted nucleotide cyclase-like proteins indicated functional associations that support the predictions on their participation in cellular signalling events. The inferences made can be experimentally investigated further to ascertain the involvement of the uncharacterized bacterial proteins in signalling pathways, which can help in understanding the pathobiology of pathogenic species of interest. The next objective was the recognition of biologically relevant protein-protein interactions across M. tuberculosis and human host (Chapter 4). M. tuberculosis is well known for its ability to successfully co-evolve with human host in terms of establishing infection, survival and persistence. The current knowledge on the mechanisms of host invasion, immune evasion and persistence in the host environment can be attributed, and is limited, to the experimental studies pursued by numerous groups. Chapter 4 presents an approach for computational identification of biologically feasible protein-protein interactions across M. tuberculosis and human host. The approach utilizes crystal structures of intra-organism protein-protein complexes which are transient in nature. Identification of homologues of host and pathogen proteins in the database of known protein-protein interactions, formed the initial step, followed by identification of conserved interfacial patch and integration of information on tissue-specific expression of human proteins and subcellular localization of human and M. tuberculosis proteins. In addition, appropriate filters were used to extract biologically feasible host-pathogen protein-protein interactions. This resulted in recognition of 386 interactions potentially mediated by 59 M. tuberculosis proteins and 90 human proteins. A predominance of host-pathogen interactions (193 protein-protein interactions) brought about by M. tuberculosis proteins participating in cell wall processes, was observed, which is in concurrence with the experimental studies on immuno-modulatory activities brought about by such proteins. These set of mycobacterial proteins were predicted to interact with diverse set of host proteins such as those involved in ubiquitin conjugation pathways, metabolic pathways, signalling pathways, regulation of cell proliferation, transport, apoptosis and autophagy. The predictions have the potential to complement experimental observations at the molecular level. Details on couple of interesting cases are presented in the chapter, one of which is the probable mechanism of immune evasion adopted by M. tuberculosis to inhibit lysozyme activity in macrophages, and second is the mechanism of nutrient uptake from host. The set of M. tuberculosis proteins predicted to mediate interactions with host proteins have the potential to warrant an experimental follow-up on probable mechanisms of pathogenesis and also serve as attractive targets for chemotherapeutic interventions. proteins known to participate in P. falciparum metabolism. Pathway holes, where evidence on metabolic step exists but the catalysing enzyme is not known, have also been addressed in the study, several of which have been suggested to play an important role in growth and development of the parasite during its intra-erythrocytic stages in human host. A subsequent objective was the recognition P. falciparum proteins potentially capable of remodelling erythrocytes to suit their niche (Chapter 7). Exploitative mechanisms are brought about by the parasite to remodel erythrocytes for growth and survival during intra-erythrocytic stages of its life-cycle, the understanding of which is limited to experimental studies. To achieve physicochemically viable protein-protein interactions potentially mediated by proteins of human erythrocytes and P. falciparum proteins, a structure-influenced protocol, similar to the one demonstrated in Chapter 4, was employed. Information on subcellular localization and protein expression is crucial especially for parasites like P. falciparum, which reside in One of the major shortcomings with current treatment regimen for tuberculosis is the emergence of multidrug (MDR) and extensively drug-resistant (XDR) strains that render first-line and second-line drug treatments futile. This entails a need to explore target space in M. tuberculosis as well as explore the potential of existing drugs for repurposing against tuberculosis. A drug repurposing strategy i.e. exploring within-target-family selectivity of small molecules, has been implemented (Chapter 5) to contribute towards time and cost-saving anti-tubercular drug development efforts. With the use of profile-based search procedures, evolutionary relationships between targets (other than proteins of M. tuberculosis) of FDA-approved drugs and M. tuberculosis proteins were investigated. A key filter to exclude drugs capable of acting on human proteins substantially reduced the chances of obtaining anti-targets. Thus, total of 130 FDA-approved drugs were recognized that can be repurposed against 78 M. tuberculosis proteins, belonging to the functional categories- intermediary metabolism and respiration, information pathways, cell wall and cell processes and lipid metabolism. The catalogue of structure and function of M. tuberculosis proteins and their involvement in host-pathogen protein-protein interactions compiled from chapters 2 and 4 served as a guiding tool to explore the functional importance of targets identified. Many of the potential targets identified have been experimentally shown to be essential for growth and survival of the pathogen earlier, thus gaining importance in terms of pharmaceutical relevance. Polypharmacological drugs or drugs capable of acting of multiple targets were also identified (92 drugs) in the study. These drugs have the potential to stand tolerance against development of drug resistance in the pathogen. Comparative sequence and structure-based analysis of M. tuberculosis proteins homologous to known targets yielded credible inferences on putative binding sites of FDA-approved drugs in potential targets. Instances where information on binding sites could not be readily inferred from known targets, potentially druggable sites have been predicted. Comparison with earlier experimental studies that report anti-tubercular potential of several approved drugs enhanced the credibility of 74 of 130 FDA-approved drugs that can be readily prioritized for clinical studies. An additional exercise was pursued to identify prospective anti-tubercular agents by means of structural comparison between ChEMBL compounds and 130 FDA-approved drugs. Only those compounds were retained that showed considerably high structural similarity with approved drugs. Such compounds with minor changes in terms of physicochemical properties provide a basis for exploration of compounds that may exhibit higher affinities to bind to M. tuberculosis targets. The set of approved drugs recognized as repurpose-able candidates against tuberculosis, in concert with the structurally similar compounds, can significantly impact anti-tubercular drug development and drug discovery. The next part of the thesis focuses on Plasmodium falciparum, an obligate intracellular protozoan parasite responsible for malaria. The parasite genome features unusual characteristics including abundance of low complexity regions and pronounced sequence divergence that render protein structure and function recognition difficult. The parasite also manifests remarkable plasticity in its metabolic organization throughout its developmental stages in two hosts-human and mosquito; thus obtaining an exhaustive list of metabolic proteins in the parasite gains importance. Considering the utility of multiple sensitive profile-based search approaches in enhanced annotation of M. tuberculosis genome, a similar exercise was employed to recognize potential metabolic proteins in P. falciparum (Chapter 6). A total of 172 metabolic proteins were identified as participants of 78 metabolic pathways, over and above 609heterogeneous environmental conditions at different stages in their lifecycle. Inclusion of such data aided in extraction of 208 biologically relevant protein-protein interactions potentially mediated by 59 P. falciparum proteins and 30 erythrocyte proteins. Host-parasite protein-protein interactions were predicted pertaining to several major strategies spanning intra-erythrocytic stages in P. falciparum pathogenesis including- gaining entry into the host erythrocytes (category: RBC invasion, protease), redirecting parasitic proteins to erythrocyte membrane (category: protein traffic), modulating erythrocyte machinery (category: rosette formation, putative adhesin, chaperone, kinase), evading immunity (category: immune evasion) and eventually egress (category: merozoite egress) to infect other uninfected erythrocytes. Elaborate means to analyse and evaluate the functional viability of a predicted interaction in terms of geometrical packing at the interfacial region, electrostatic complementarity of the interacting surfaces and interaction energies is also demonstrated. The protein-protein interactions, thus predicted between human erythrocytes and P. falciparum, have the potential to provide a useful basis in understanding probable mechanisms of pathogenesis, and indeed in pinning down attractive targets for antimalarial drug discovery. The emergence of drug resistance against all known antimalarial agents, currently in use, necessitates discovery and development of either new antimalarial agents or unexplored combination of drugs that may not only reduce mortality and morbidity of malaria, but also reduce the risk of resistance to antimalarial drugs. In an attempt to contribute towards the same, Chapter 8 explores the established concept of within-target-family selectivity of small molecules to recognize antimalarial potential of the approved drugs. Eighty six FDA-approved drugs, predominantly constituted by antibacterial agents, were identified as feasible candidates for repurposing against 90 P. falciparum proteins. Most of the potential parasite targets identified are known to participate in housekeeping machinery, protein biosynthesis, metabolic pathways and cell growth and differentiation, and thus are pharmaceutically relevant. During intra-erythrocytic growth of P. falciparum, the parasite resides within the erythrocyte, within a protective encasing, known as parasitophorous vacuole. Hence a drug, intended to target a parasite protein residing in an organelle, must be sufficiently hydrophilic or hydrophobic to be able to permeate cell membranes and reach its site of activity. On the basis of lipophilicity of the drugs, a physical property determined experimentally, 57 of 86 FDA-approved drugs were recognized as feasible candidates for use against P. falciparum during the course of blood-stages of infection, which can be prioritized for antimalarial drug development programmes. The final section of the thesis focuses on the protozoan parasite Trypanosoma brucei, a causative agent of African sleeping sickness (Chapter 9). This disease is endemic to sub-Saharan regions of Africa. Despite the availability of completely sequenced genome of T. brucei, structure and function for about 50% of the proteins encoded in the genome remain unknown. Absence of prophylactic chemotherapy and vaccine, compounded with emergence of drug-resistance renders anti-trypanosomal drug discovery challenging. Thus, considering the utility of frameworks established in earlier chapters for recognition of protein structure, function and drug-targets, similar steps were undertaken to understand functional repertoire of the parasite and use drug repurposing methods to accelerate anti-trypanosomal drug discovery efforts. Structures and functions were reliably recognized for 70% of the gene products (5894) encoded in T. brucei genome, with the use of multiple profile-based search procedures, coupled with information on presence of transmembrane domains and signal peptide cleavage sites. Consequently, a total of 282 uncharacterized T. brucei proteins could be newly coined as potential metabolic proteins. Integration of information on stage-specific expression profiles with Trypanosoma-specific and T-.brucei-specific proteins identified in the study, aided in pinning down potential attractive targets. Additionally, exploration of evolutionary relationships between targets of FDA-approved drugs and T. brucei proteins, 68 FDA-approved drugs were predicted as repurpose-able candidates against 42 potential T. brucei targets which primarily include proteins involved in regulatory processes and metabolism. Several targets predicted are reportedly essential in assisting the parasite to switch between differentiation forms (bloodstream and procyclic) in the course of its lifecycle. These targets are of high therapeutic relevance, hence the corresponding drug-target associations provide a useful resource for experimental endeavours. In summary, this thesis presents computational analyses on three pathogenic genomes in terms of enhancing the understanding of functional repertoire of the pathogens, addressing metabolic pathway holes, exploring probable mechanisms of pathogenesis brought about by potential host-pathogen protein-protein interactions, and identifying feasible FDA-approved drug candidates to repurpose against the pathogens. The studies are pursued primarily by taking advantage of powerful homology-detection techniques and the ever-growing biological information made available in public databases. Indeed, the inferences drawn for the three pathogenic genomes serve an excellent resource for an experimental follow-up. The set of protocols presented in the thesis are highly generic in nature, as demonstrated for three pathogens, and can be utilized for genome-wide analyses on many other pathogens of interest. The supplemental data associated with the chapters is provided in a compact disc attached with this thesis.

Promoter region is the key regulatory region, which enables the gene to be transcribed or repressed by anchoring RNA polymerase and other transcription factors, but it is difficult to determine experimentally. Hence an in silico identification of promoters is crucial in order to guide experimental work and to pin point the key region that controls the transcription initiation of a gene. Analysis of various genome sequences in the vicinity of experimentally identified transcription start sites (TSSs) in prokaryotic as well as eukaryotic genomes had earlier indicated that they have several structural features in common, such as lower stability, higher curvature and less bendability, when compared with their neighboring regions. In this thesis work, the variation observed for these DNA sequence dependent structural properties have been used to identify and delineate promoter regions from other genomic regions. Since the number of bacterial genomes being sequenced is increasing very rapidly, it is crucial to have procedures for rapid and reliable annotation of their functional elements such as promoter regions, which control the expression of each gene or each transcription unit of the genome. The thesis work addresses this requirement and presents step by step protocols followed to get a generic method for promoter prediction that can be applicable across organisms. The each paragraph below gives an overall idea about the thesis organization into chapters. An overview of prokaryotic transcriptional regulation, structural polymorphism adapted by DNA molecule and its impact on transcriptional regulation has been discussed in introduction chapter of this thesis (chapter 1). Standardization of promoter prediction methodology - Part I Based on the difference in stability between neighboring upstream and downstream regions in the vicinity of experimentally determined transcription start sites, a promoter prediction algorithm has been developed to identify prokaryotic promoter sequences in whole genomes. The average free energy (E) over known promoter sequences and the difference (D) between E and the average free energy over the random sequence generated using the downstream region of known TSS (REav) are used to search for promoters in the genomic sequences. Using these cutoff values to predict promoter regions across entire E. coli genome, a reliability of 70% has been achieved, when the predicted promoters were cross verified against the 960 transcription start sites (TSSs) listed in the Ecocyc database. Reliable promoter prediction is obtained when these genome specific threshold values were used to search for promoters in the whole E. coli genome sequence. Annotation of the whole E. coli genome for promoter region has been carried out with 49% accuracy. Reference Rangannan, V. and Bansal, M. (2007) Identification and annotation of promoter regions inmicrobial genome sequences on the basis of DNA stability. J Biosci, 32, 851-862. Standardization of promoter prediction methodology - Part II In this chapter, it has been demonstrated that while the promoter regions are in general less stable than the flanking regions, their average free energy varies depending on the GC composition of the flanking genomic sequence. Therefore, a set of free energy threshold values (TSS based threshold values), from the genomic DNA with varying GC content in the vicinity of experimentally identified TSSs have been obtained. These threshold values have been used as generic criteria for predicting promoter regions in E. coli and B. subtilis and M. tuberculosis genomes, using an in-house developed tool ‘PromPredict’. On applying it to predict promoter regions corresponding to the 1144 and 612 experimentally validated TSSs in E. coli (genome %GC : 50.8) and B. subtilis (genome %GC : 43.5) sensitivity of 99% and 95% and precision values of 58% and 60%, respectively, were achieved. For the limited data set of 81 TSSs available for M. tuberculosis (65.6% GC) a sensitivity of 100% and precision of 49% was obtained. Reference Rangannan, V. and Bansal, M. (2009) Relative stability of DNA as a generic criterion for promoter prediction: whole genome annotation of microbial genomes with varying nucleotide base composition. Mol Biosyst, 5, 1758 - 1769. Standardization of promoter prediction methodology - Part III In this chapter, the promoter prediction algorithm and the threshold values have been improved to predict promoter regions on a large scale over 913 microbial genome sequences. The average free energy (AFE) values for the promoter regions as well as their downstream regions are found to differ, depending on their GC content even with respect to translation start sites (TLSs) from 913 microbial genomes. The TSS based cut-off values derived in chapter 3 do not have cut-off values for both extremes of GC-bins at 5% interval. Hence, threshold values have been derived from a subset of translation start sites (TLSs) from all microbial genomes which were categorized based on their GC-content. Interestingly the cut-off values derived with respect to TSS data set (chapter 3) and TLS data set are very similar for the in-between GC-bins. Therefore, TSS based cut-off values derived in chapter 2 with the TLS based cut-off values have been combined (denoted as TSS-TLS based cutoff values) to predict promoters over the complete genome sequences. An average recall value of 72% (which indicates the percentage of protein and RNA coding genes with predicted promoter regions assigned to them) and precision of 56% is achieved over the 913 microbial genome dataset. These predicted promoter regions have been given a reliability level (low, medium, high, very high and highest) based on the difference in its relative average free energy, which can help the users design their experiments with more confidence by using the predictions with higher reliability levels. Reference Rangannan, V. and Bansal, M. (2010) High Quality Annotation of Promoter Regions for 913 Bacterial Genomes. Bioinformatics, 26, 3043-3050. Web applications PromBase : The predicted promoter regions for 913 microbial genomes were deposited into a public domain database called, PromBase which can serve as a valuable resource for comparative genomics study for their general genomic features and also help the experimentalist to rapidly access the annotation of the promoter regions in any given genome. This database is freely accessible for the users via the World Wide Web http://nucleix.mbu.iisc.ernet.in/prombase/. EcoProm : EcoProm is a database that can identify and display the potential promoter regions corresponding to EcoCyc annotated TSS and genes. Also displays predictions for whole genomic sequence of E. coli and EcoProm is available at http://nucleix.mbu.iisc.ernet.in/ecoprom/index.htm. PromPredict : The generic promoter prediction methodology described in previous chapters has been implemented in to an algorithm ‘PromPredict’ and available at http://nucleix.mbu.iisc.ernet.in/prompredict/prompredict.html. Analysing the DNA structural characteristic of prokaryotic promoter sequences for their predominance Sequence dependent structural properties and their variation in genomic DNA are important in controlling several crucial processes such as transcription, replication, recombination and chromatin compaction. In this chapter 6, quantitative analysis of sequences motifs as well as sequence dependent structural properties, such as curvature, bendability and stability in the upstream region of TSS and TLS from E. coli, B. subtilis and M. tuberculosis has been carried out in order to assess their predictive power for promoter regions. Also the correlation between these structural properties and GC-content has been investigated. Our results have shown that AFE values (stability) gives finer discrimination rather than %GC in identifying promoter regions and stability have shown to be the better structural property in delineating promoter regions from non-promoter regions. Analysis of these DNA structural properties has been carried out in human promoter sequences and observed to be correlating with the inactivation status of the X-linked genes in human genome. Since, it is deviating from the theme of main thesis; this chapter has been included as appendix A to the main thesis. General conclusion Stability is the ubiquitous DNA structural property seen in promoter regions. Stability shows finer discrimination for promoter prediction rather than directly using %GC-content. Based on relative stability of DNA, a generic promoter prediction algorithm has been developed and implemented to predict promoter regions on a large scale over 913 microbial genome sequences. The analysis of the predicted regions across organisms showed highly reliable predictive performance of the algorithm.

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The main goal of this master thesis is introduction and investigation of extended version of jumping automata and grammars. New versions are primarily focused on bioinformatic applications - DNA computing. This thesis examine their power and other properties of new models and makes comparison with existing computer science models. Then thesis demontrates practical applications, specifically amino acid and protein detections inside DNA sequence and makes comparision with existing tools in DNA computing for example Mark´s probabilistic models.

Dans les océans, les procaryotes sont des acteurs clés dans le cycle du carbone puisqu’ils consomment une fraction importante de la matière organique dissoute (MOD) relâchée par les producteurs primaires. Puisque cette matière organique est très complexe et de biodisponibilité variable, les communautés de procaryotes qui la consomme sont très diversifiées et spécialisées pour certains types de composés organiques. En utilisant cette matière organique, les procaryotes contribuent à réintroduire ce carbone dans le réseau trophique, une source d’énergie essentielle dans les gyres oligotrophes de l’océan. Toutefois, puisque cette consommation n’est pas parfaite, une quantité importante de carbone est relâchée sous forme de CO2 lors de la respiration, mais aussi sous forme de MOD récalcitrante, contribuant à séquestrer du carbone dans les océans. Le but de cette thèse est d’une part, de dresser un portrait global de la biodisponibilité de la MOD et d’autre part, de déterminer l’influence de la biodisponibilité de cette dernière sur la composition et le métabolisme des procaryotes dans la mer du Labrador, une mer dont le rôle est critique dans la régulation du climat. Plus spécifiquement, nous identifions pour la première fois comment la distribution spatiale des procaryotes influencent leur métabolisme et est influencée par leur préférence alimentaire dans les eaux de surface de la mer du Labrador. Finalement, nous regardons comment la matière organique produite en surface est transformée et séquestrée en profondeur suite à la convection hivernale dans la mer du Labrador. Le budget de carbone dans les océans n’est toujours pas balancé. Afin de mieux connaître les sources et la biodisponibilité du carbone dans les différents milieux aquatiques, nous avons évalué la biodisponibilité de la MOD à travers le continuum aquatique, des lacs jusqu’à l’océan. En menant une méta-analyse sur le sujet, nos résultats montrent que la proportion de matière organique labile, c’est-à-dire facilement utilisable par les procaryotes, est d’environ 6% dans tous les environnements aquatiques. Toutefois, la proportion de matière organique semi-labile, celle qui nécessite plus de transformation par les procaryotes, est grandement liée à la proximité au milieu terrestre. Les seuls écosystèmes aquatiques déviant de ces deux constats sont ceux en période d’efflorescence algale: ils contiennent beaucoup plus de carbone labile et semi-labile que ceux à l’équilibre. Nous avons estimé que le carbone semi-labile peut soutenir 62% de la biomasse de procaryotes dans les lacs et les milieux côtiers. Dans un deuxième temps, nous évaluons l’influence de la MOD sur le métabolisme et les communautés de procaryotes. Nous avons fait trois missions océanographiques sur la mer du Labrador à bord du navire Hudson pour déterminer la composition de la MOD et la communauté des procaryotes ainsi que leur métabolisme. En utilisant une approche novatrice, la modélisation de la distribution spatiale de l’abondance des procaryotes, nous avons montré à quel point celle-ci est importante pour déterminer leur préférence alimentaire ainsi que leur métabolisme. Nous avons également proposé un nouveau cadre conceptuel qui vise à faciliter la recherche à l’interface de la biogéochimie, de l’écologie microbienne et du métabolisme microbien. Dans un dernier temps, nous avons comparé la capacité des procaryotes venant de différentes profondeurs océaniques à séquestrer le carbone. Lors de la consommation de la MOD, les procaryotes en relâche une petite fraction sous forme plus récalcitrante. En répétant ce processus, le carbone résiduel devient très récalcitrant et peut résister à la consommation par les procaryotes durant des centaines d’années. Nous avons montré que les procaryotes de l’océan profond sont plus efficaces pour séquestrer le carbone de cette façon. Nos résultats montrent que ce sont les taxons rares des procaryotes qui sont les éléments clés dans cette suite de transformation qui mène à la séquestration du carbone appelée pompe microbienne. Cette thèse contribue à la compréhension du cycle du carbone dans la mer du Labrador et dans les écosystèmes aquatiques en général. Nous avons proposé une approche novatrice permettant de lier la qualité de la MOD à la composition des communautés de procaryotes qui la dégrade, un défi qui perdure depuis des dizaines d’années. De plus, nous montrons pour la première fois la que la pompe microbienne de carbone est un processus itératif fortement relié à la succession de la communauté de procaryotes. Nous montrons également que la pompe microbienne est active dans chaque strate océanique, mais que les procaryotes rares issus de l’océan profond sont plus efficaces à séquestrer le carbone. Mieux comprendre comment la composition de la MOD influence les procaryotes est primordial puisqu’ils sont centraux au cycle du carbone océanique. / Oceanic prokaryotes are key players in the carbon cycle by consuming dissolved organic mat-ter (DOM) produced by primary producers. As this organic matter is highly complex with varying degree of bioavailability, prokaryotic communities are highly diverse and different taxa target certain types of organic compounds. By consuming this organic matter, prokary-otes reintroduce this carbon into the food web, a critical energy flow in oligotrophic gyres. However, this consumption is not perfect and they release a lot of carbon as CO2 through respiration, but also as recalcitrant DOM. Thus, they contribute to carbon sequestration in aquatic ecosystems. The objective of this thesis is to characterize DOM bioavailability and its influence on the composition and metabolism of prokaryotic communities in the Labrador Sea, described as one of the Earth’s climate system tipping elements. More precisely, we quantify for the first time how the spatial abundance distribution of prokaryotes influences ecosystem metabolism and organic matter association in the surface waters of the Labrador Sea. Lastly, we look at how DOM produced at the surface is transformed and sequestered following the Labrador Sea winter convective mixing. The oceanic carbon budget is still unbalanced. In order to better understand its carbon sources and bioavailability, we characterize DOM bioavailability across the aquatic contin-uum, from lakes to the open ocean. Using a meta-analysis, our results show that the propor-tion of labile organic matter, i.e. readily available for prokaryotes, is similar at around 6% in all aquatic ecosystems. However, the proportion of semi-labile organic matter, i.e requiring transformations to be consumed by prokaryotes, is highly related to terrestrial connectivity. The only ecosystems that did not follow these patterns were in a phytoplankton bloom pe-riod and had a high proportion of labile and semi-labile organic matter as their counterparts at equilibrium. Finally, we estimated that semi-labile organic matter could sustain 62% of prokaryotic biomass in lakes and coastal zones. Second, we evaluated the influence of DOM on prokaryotic metabolism and community composition. In order to determine organic matter composition, prokaryotic community composition and metabolic rates, we did three oceanic cruises in the Labrador Sea onboard the Hudson ship. By using spatial abundance distribution modelling of prokaryotes, we identified strong associations between groups of this novel approach and organic matter composition. We also proposed a framework to bridge the gap between prokaryotic diversity, microbial ecology, and biogeochemistry among methods and across scales. Lastly, we compared how prokaryotic communities from different oceanic strata could se-quester carbon. When they consume organic matter, prokaryotes release a small amount in recalcitrant forms. Through this iterative process, called the microbial carbon pump, prokaryotes contribute to carbon sequestration by creating highly recalcitrant compounds that resist further degradation for hundreds of years. We have shown that all prokaryotes enable the microbial carbon pump, but that prokaryotes from deeper strata are more effi-cient. Our results also conclusively show that the rare prokaryotic taxa are key players in the microbial carbon pump. This thesis contributes to better understand the carbon cycle in the Labrador Sea and in all aquatic ecosystems. We proposed a novel framework to relate biogeochemistry, prokaryotic diversity and microbial ecology which has been a challenge for decades. Moreover, we con-clusively showed for the first time that the iterative process of the microbial carbon pump is related to prokaryotic succession. We also show that it happens in all oceanic strata, but that rare prokaryotes from the deep ocean are more efficient to sequester carbon. Better understanding how DOM composition influences prokaryotes is of prime importance as they are the main drivers of the oceanic carbon cycle.