Understanding microbial evolution lies at the heart of microbiology and environmental sciences. Numerous studies have been dedicated to elucidating the underlying mechanisms that create microbial genetic diversity and adaptation. However, due to technical limitations such as the high level of uncultured cells in almost every natural habitat, most of current knowledge is primarily based on axenic cultures grown under laboratory conditions, which typically do not simulate well the natural environment. How well the knowledge from isolates translates to in-situ processes and natural microbial communities remains essentially speculative. The recent development of culture-independent genomic techniques (aka metagenomics) provides possibilities to bypass some of these limitations and provide new insights into microbial evolution in-situ. To date, most of metagenomic studies have been focused on a few reduced-diversity model communities, e.g., acid mine drainage. Highly complex communities such as those of soil and sediment habitats remain comparatively less understood. Furthermore, a great power of metagenomics, which has not been fully capitalized yet, is the ability to follow the evolution of natural microbial communities over time and environmental perturbations, i.e., times-series metagenomics. Although the recent developments in DNA sequencing technologies have enabled (inexpensive) time-series studies, the bioinformatics approaches to analyze the resulting data have clearly fallen behind. Taken together, to scale up metagenomics for complex community studies, three major challenges remain: 1) the difficulty to process and analyze massive short read sequencing data, often at the terabyte level; 2) the difficulty to effectively assemble genomes from complex metagenomes; and 3) the lack of methods for tracking genotypes and mutational events such as horizontal gene transfer (HGT) through time. Therefore, developing efficient bioinformatics approaches to address these challenges represents an important and timely issue. This thesis aimed to develop novel bioinformatics pipelines and algorithms for high performance computing, and, subsequently, apply these tools to natural microbial communities to generate quantitative insights into the relative importance of the molecular mechanisms creating or maintaining microbial diversity. The tools are not specific to a particular habitat or group of organisms and thus, can be broadly used to advance our understanding of microbial evolution in different settings. In particular, the comparative whole-genome analysis of 24 Escherichia isolates form various habitats, including human and non-human associated habitats such as freshwater ecosystems and beaches, showed that organisms with more similar ecologies tend to exchange more genes, which has important implications for the prokaryotic species concept. To more directly test these findings from isolates and quantify the patterns of genetic exchange among co-occurring populations, three years of time-series metagenomics data from planktonic samples from Lake Lanier (Atlanta, GA) were analyzed. For this, it was first important to develop bioinformatics algorithms to robustly assemble population genomes from complex community metagenomes, identify the phylogenetic affiliation of assembled genome and contig sequences, and detect horizontal gene transfer among these sequences. Using these novel algorithms, in situ bacterial lineage evolution was quantitatively assessed, especially with respect to whether or not ecologically distinct lineages evolve according to the recently proposed fragmented speciation model (Retchless and Lawrence, Science 2008). Evidence in support of this model was rarely observed. Instead, it appeared that rampant HGT disseminated ecologically important genes within the population, maintaining intra-population diversity. By expanding the previous approaches to include methods to assess differential gene abundance and selection pressure between samples, it was possible to quantify how soil microbial communities respond to a decade of warming by 2 0C, which simulated the predicted effects of climate change. It was found that the heated communities showed significant shifts in composition and predicted metabolism, reflecting the release of additional soil carbon compared to the unheated (control) communities, and these shifts were community-wide as opposed to being attributable to a few taxa. These findings indicated that the microbial communities of temperate grassland soils play important roles in mediating the feedback responses to climate change. Collectively, the findings presented here advance our understanding of the modes and tempo of microbial community adaptation to environmental perturbations and have important implications for better modeling the microbial diversity on the planet. The bioinformatics algorithms and approaches developed as part of this thesis are expected to facilitate future genomic and metagenomic studies across the fields of microbiology, ecology, evolution and engineering.

Quorum sensing (QS) cell-cell communication systems are utilized by bacteria to coordinate their behaviour according to cell density. Several different types of QS signal molecules have been identified, among which acyl-homoserine lactones (AHLs) produced by Proteobacteria have been studied to the greatest extent. QS has been shown to be involved in many aspects of bacterial life, including virulence, bioluminescence, symbiosis, antibiotic production, swarming and swimming motility, biofilm formation, conjugation and growth inhibition. Although QS has been studied extensively in cultured microorganisms, little is known about the QS systems of uncultured microorganisms and the roles of these systems in microbial communities. To extend our knowledge of QS systems and to better understand the signalling that takes place in the natural environment, in the first part of this thesis, isolation and characterization of new QS systems from metagenomic libraries constructed using DNA from activated sludge and soil were described. Using an Agrobacterium biosensor strain, three cosmids (QS6-1, QS10-1 and QS10-2) that encode the production of QS signals were identified and DNA sequence analysis revealed that all three clones encode a novel luxI family AHL synthase and a luxR family transcriptional regulator. Thin layer chromatography revealed that these LuxI homolog proteins are able to synthesize multiple AHL signals. Tandem mass spectrometry analysis revealed that LuxIQS6-1 directs the synthesis of at least three AHLs, 3-O-C14:1 HSL, 3-O-C16:1 HSL and 3-O-C14 HSL; LuxIQS10-1 directs the synthesis of at least 3-O-C12 HSL and 3-O-C14 HSL; while LuxIQS10-2 directs the synthesis of at least C8 HSL and C10 HSL. Two possible new AHLs, C14:3 HSL and (?)-hydroxymethyl-3-O-C14 HSL, were also found to be synthesized by LuxIQS6-1. Agrobacterium tumefaciens is a plant pathogen that causes crown gall disease. Its ability to transfer and integrate foreign DNA into plant genome also makes it a useful tool for plant genetic engineering. Ethylene, the gaseous plant hormone, has been reported to be important for both crown gall development and A. tumefaciens mediated transformation efficiency to plants. ACC deaminase, an enzyme that can break down ACC, the direct precursor of ethylene biosynthesis in plants, is a mechanism used by some plant growth promoting bacteria (PGPB) to promote plant growth by reducing stress ethylene levels. In the second part of this thesis, the effect of ACC deaminase on A. tumefaciens induced crown gall development and on A. tumefaciens mediated transformation efficiency was studied. By either introduction of an ACC deaminase encoding gene into the virulent strain A. tumefaciens C58 or co-inoculation of A. tumefaciens C58 with an ACC deaminase containing PGPB P. putida UW4, using different plant systems including tomato plants and castor bean plants, it was found that the presence of an ACC deaminase significantly inhibited crown gall development. It was also found that introduction of an acdS gene into the disarmed A. tumefaciens strain GV3101::pMP90 reduced the ethylene levels evolved by plants during infection and cocultivation process and increased the transformation efficiency of commercialized canola cultivars. The A. tumefaciens D3 strain was reported to contain an ACC deaminase encoding gene (acdS). In this study it was determined that this strain is an avirulent strain and shows plant growth promoting activity. When co-inoculated with A. tumefaciens C58 on castor bean stems, both the wild type and the acdS knockout mutant showed biocontrol activity and were able to significantly inhibit crown gall formation, with the wild type strain showing slightly better tumor inhibition effects. The mutation of acdS and its regulatory gene lrpL in A. tumefaciens D3 was also found to affect QS signal production of this strain, which indicates a cross talk between the two sets of genes.

Quorum sensing (QS) cell-cell communication systems are utilized by bacteria to coordinate their behaviour according to cell density. Several different types of QS signal molecules have been identified, among which acyl-homoserine lactones (AHLs) produced by Proteobacteria have been studied to the greatest extent. QS has been shown to be involved in many aspects of bacterial life, including virulence, bioluminescence, symbiosis, antibiotic production, swarming and swimming motility, biofilm formation, conjugation and growth inhibition. Although QS has been studied extensively in cultured microorganisms, little is known about the QS systems of uncultured microorganisms and the roles of these systems in microbial communities. To extend our knowledge of QS systems and to better understand the signalling that takes place in the natural environment, in the first part of this thesis, isolation and characterization of new QS systems from metagenomic libraries constructed using DNA from activated sludge and soil were described. Using an Agrobacterium biosensor strain, three cosmids (QS6-1, QS10-1 and QS10-2) that encode the production of QS signals were identified and DNA sequence analysis revealed that all three clones encode a novel luxI family AHL synthase and a luxR family transcriptional regulator. Thin layer chromatography revealed that these LuxI homolog proteins are able to synthesize multiple AHL signals. Tandem mass spectrometry analysis revealed that LuxIQS6-1 directs the synthesis of at least three AHLs, 3-O-C14:1 HSL, 3-O-C16:1 HSL and 3-O-C14 HSL; LuxIQS10-1 directs the synthesis of at least 3-O-C12 HSL and 3-O-C14 HSL; while LuxIQS10-2 directs the synthesis of at least C8 HSL and C10 HSL. Two possible new AHLs, C14:3 HSL and (?)-hydroxymethyl-3-O-C14 HSL, were also found to be synthesized by LuxIQS6-1. Agrobacterium tumefaciens is a plant pathogen that causes crown gall disease. Its ability to transfer and integrate foreign DNA into plant genome also makes it a useful tool for plant genetic engineering. Ethylene, the gaseous plant hormone, has been reported to be important for both crown gall development and A. tumefaciens mediated transformation efficiency to plants. ACC deaminase, an enzyme that can break down ACC, the direct precursor of ethylene biosynthesis in plants, is a mechanism used by some plant growth promoting bacteria (PGPB) to promote plant growth by reducing stress ethylene levels. In the second part of this thesis, the effect of ACC deaminase on A. tumefaciens induced crown gall development and on A. tumefaciens mediated transformation efficiency was studied. By either introduction of an ACC deaminase encoding gene into the virulent strain A. tumefaciens C58 or co-inoculation of A. tumefaciens C58 with an ACC deaminase containing PGPB P. putida UW4, using different plant systems including tomato plants and castor bean plants, it was found that the presence of an ACC deaminase significantly inhibited crown gall development. It was also found that introduction of an acdS gene into the disarmed A. tumefaciens strain GV3101::pMP90 reduced the ethylene levels evolved by plants during infection and cocultivation process and increased the transformation efficiency of commercialized canola cultivars. The A. tumefaciens D3 strain was reported to contain an ACC deaminase encoding gene (acdS). In this study it was determined that this strain is an avirulent strain and shows plant growth promoting activity. When co-inoculated with A. tumefaciens C58 on castor bean stems, both the wild type and the acdS knockout mutant showed biocontrol activity and were able to significantly inhibit crown gall formation, with the wild type strain showing slightly better tumor inhibition effects. The mutation of acdS and its regulatory gene lrpL in A. tumefaciens D3 was also found to affect QS signal production of this strain, which indicates a cross talk between the two sets of genes.

A metagenome originated from a shotgun sequencing of a microbial community is a heterogeneous mixture of rather short sequences. A vast majority of microbial species in a given community (99%) are likely to be non-cultivable. Many protein-coding regions in a new metagenome are likely to code for barely detectable homologs of already known proteins. Therefore, an ab initio method that would accurately identify the new genes is a vitally important tool of metagenomic sequence analysis. However, a heuristic model method for finding genes in short prokaryotic sequences with anonymous origin was proposed in 1999 prior to the advent of metagenomics. With hundreds of new prokaryotic genomes available it is now possible to enhance the original approach and to utilize direct polynomial and logistic approximations of oligonucleotide frequencies. The idea was to bypass traditional ways of parameter estimation such as supervised training on a set of validated genes or unsupervised training on an anonymous sequence supposed to contain a large enough number of genes. The codon frequencies, critical for the model parameterization, could be derived from frequencies of nucleotides observed in the short sequence. This method could be further applied for initializing the algorithms for iterative parameters estimation for prokaryotic as well as eukaryotic gene finders.

Metagenomics is the study of a collective microbial genetic content recovered directly from natural (e.g., soil, ocean, and freshwater) or host-associated (e.g., human gut, skin, and oral) environmental communities that contain microorganisms, i.e., microbiomes. The rapid technological developments in next generation sequencing (NGS) technologies, enabling to sequence tens or hundreds of millions of short DNA fragments (or reads) in a single run, facilitates the studies of multiple microorganisms lived in environmental communities. Metagenomics, a relatively new but fast growing field, allows us to understand the diversity of microbes, their functions, cooperation, and evolution in a particular ecosystem. Also, it assists us to identify significantly different metabolic potentials in different environments. Particularly, metagenomic analysis on the basis of functional features (e.g., pathways, subsystems, functional roles) enables to contribute the genomic contents of microbes to human health and leads us to understand how the microbes affect human health by analyzing a metagenomic data corresponding to two or multiple populations with different clinical phenotypes (e.g., diseased and healthy, or different treatments). Currently, metagenomic analysis has substantial impact not only on genetic and environmental areas, but also on clinical applications. In our study, we focus on the development of computational and statistical methods for functional metagnomic analysis of sequencing data that is obtained from various environmental microbial samples/communities.

Mastreviruses (family Geminiviridae) are plant-infecting viruses with circular single-stranded (ss) DNA genomes (~2.7kb). The genus Mastrevirus is comprised of thirty-two species which are transmitted by leafhoppers belonging to the genus Cicadulina. Mastreviruses are widely distributed and have been found in the Middle East, Europe, Asia, Australia, Africa and surrounding islands. Only one species, dragonfly-associated mastrevirus has so far been identified in the Americas, isolated from a dragonfly in Puerto Rico. Species can be group based on the host(s) they infect, those which infect monocotyledonous (monocot) plants and those which infect dicotyledonous (dicot) plants. In recent years many new mastrevirus species have been discovered. Several of these new discoveries can largely been attributed to the development of new molecular tools. The current state of sequencing platforms has made it affordable and easier to characterise mastreviruses at a genome level thus allowing scientists to delve deeper into understanding the dynamics of mastreviruses. A few mastrevirus species have been identified as important agricultural pathogens and as a result have been the focus of much of the mastrevirus research. Maize streak virus, strain A (MSV-A) has been the most extensively studied due to the devastating impact it has on maize production in Africa. Studies have shown that MSV-A likely emerged as a pathogen of maize less than 250 years following introduction of maize in Africa by early European settlers. There is compelling evidence to suggest that MSV-A is likely the result of recombination events between wild grass adapted MSV strains. It therefore is equally important to monitor viruses infecting non-cultivated plants in order to gain a greater understanding of the epidemiological dynamics of mastreviruses, which in turn is essential for implementing disease management strategies. The objective of the research undertaken as part of this PhD thesis was to investigate global mastrevirus dynamics focusing on diversity, host and geographic ranges, mechanisms of evolution, phylogeography and possible origins of these viruses. In addition to this a viral metagenomic approach was used in order to identify novel mastreviruses or mastrevirus-like present in New Zealand. The dynamics of the monocot-infecting mastreviruses are investigated in Chapter Two and Three. The work described in these two chapters focus mainly on mastreviruses which infect non-cultivated grasses in Africa and Australia, a total of 161 full mastrevirus genomes were recovered collectively in the two studies. Chapter Two reveals a high level of mastrevirus diversity present in Australia with the discovery of four new species and several new strains of previously characterised species. An extensive sampling effort in Africa undertaken in Chapter Three reveals a broader host range and geographic distribution of the African monocot-infecting mastreviruses than previously documented. Mosaic patterns of recombination are evident among both the Australian and African monocot-infecting mastreviruses. In Chapters Four, Five and Six a comprehensive investigation was undertaken focusing on the dicot-infecting mastreviruses. The study undertaken in Chapter Four entailed the recovery of 49 full mastrevirus genomes from Australia, the Middle East, Africa, Turkey and the Indian Subcontinent to investigate the diversity of dicot-infecting mastreviruses from a global context. Analyses revealed a high degree of CpCDV strain diversity and extended the known geographic range of CpCDV. For the first time phylogeographic analysis was able to investigate the origins of the dicot-infecting mastreviruses. Results revealed the likely origin of the most recent common ancestor (MRCA) of these viruses is likely closer to Australia than anywhere else that dicot-infecting mastreviruses have been sampled and illuminated a supported series of historical movements following the emergence of the MRCA. In Chapter Five two novel mastreviruses Australian-like mastreviruses were isolated from chickpea material from Pakistan. A comprehensive analysis of CpCDV isolates in the major pulse growing regions of Sudan in Chapter Six reveals that this region harbours a high degree of strain diversity. Complex patterns of intra-species recombination indicate these strains are evidently circulating in these regions and infecting the same hosts, driving the emergence of new CpCDV strains. Collectively the results discussed in Chapters Two through Six extended the current knowledge of mastrevirus diversity. The natural host range of many mastreviruses has proven to be more extensive than previously documented, with many species having overlapping host ranges and hence these hosts could be acting as ‘mixing vessels’ enabling inter-species recombination. Patterns of recombination and selection were observed in both the monocot-infecting and the dicot-infecting mastreviruses further elucidating the mechanisms these viruses employ to evolve rapidly. Extensive sampling in a wide range of geographic regions provides insights into the true geographic range of species such as MSV and CpCDV. Given that mastreviruses have been able to move globally and Australia has been identified as a major mastrevirus diversity hotspot it is conceivable that mastreviruses are also present in New Zealand. In Chapter Seven and Eight this is explored by using a viral metagenomic approach to investigate the ssDNA viral populations associated with wild grasses and sewage material in New Zealand. Although no mastreviruses were recovered, this endeavour resulted in the discovery of more than 50 novel circular Rep-encoding ssDNA (CRESS DNA) viruses associated with non-cultivated grasses and treated sewage material, many of which are similar to mastreviruses and other geminiviruses. These discoveries expand current knowledge on the diversity of ssDNA viruses present in New Zealand and further highlight this viral metagenomic approach as an effective method for ssDNA virus discovery. Overall the results discussed in this thesis provide insights into mastrevirus diversity and dynamics as well as revealing a wealth of novel CRESS DNA viruses, some of which share similarities to geminiviruses.

No description available.

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

The idea of using a graphics processing unit (GPU) for more than simply graphic output purposes has been around for quite some time in scientific communities. However, it is only recently that its benefits for a range of bioinformatics and life sciences compute-intensive tasks has been recognized. This thesis investigates the possibility of improving the performance of the overlap determination stage of an Overlap Layout Consensus (OLC)-based assembler by using a GPU-based implementation of the Smith-Waterman algorithm. In this thesis an existing GPU-accelerated sequence alignment algorithm is adapted and expanded to reduce its completion time. A number of improvements and changes are made to the original software. Workload distribution, query profile construction, and thread scheduling techniques implemented by the original program are replaced by custom methods specifically designed to handle medium-length reads. Accordingly, this algorithm is the first highly parallel solution that has been specifically optimized to process medium-length nucleotide reads (DNA/RNA) from modern sequencing machines (i.e. Ion Torrent). Results show that the software reaches up to 82 GCUPS (Giga Cell Updates Per Second) on a single-GPU graphic card running on a commodity desktop hardware. As a result it is the fastest GPU-based implemen- tation of the Smith-Waterman algorithm tailored for processing medium-length nucleotide reads. Despite being designed for performing the Smith-Waterman algorithm on medium-length nucleotide sequences, this program also presents great potential for improving heterogeneous computing with CUDA-enabled GPUs in general and is expected to make contributions to other research problems that require sensitive pairwise alignment to be applied to a large number of reads. Our results show that it is possible to improve the performance of bioinformatics algorithms by taking full advantage of the compute resources of the underlying commodity hardware and further, these results are especially encouraging since GPU performance grows faster than multi-core CPUs.

Les arthropodes hématophages tels que les moustiques, les tiques et les puces ont une importance significative en santé publique en raison de leur capacité à transmettre des maladies majeures aux humains et aux animaux. La lutte anti-vectorielle et la surveillance épidémiologique des vecteurs sont essentielles dans la stratégie de lutte contre ces maladies. Cette dernière n'est réussie que grâce à une identification correcte et précise des vecteurs. Ainsi dans ce travail nous avons mis au point les protocoles pour la préparation des échantillons pour l'identification des moustiques adultes et leur stades aquatiques ainsi que des tiques et des puces par MALDI-TOF MS. Cet outil s'est déjà distingué comme étant fiable pour l'identification des arthropodes. La deuxième partie de notre travail a consisté en l'application de ces protocoles sur des larves de moustiques collectées sur terrain durant une enquête entomologique menée dans la ville de Marseille. Lors de cette étude, la pertinence et la fiabilité du MALDI-TOF MS pour l'identification des larves de moustiques collectées sur terrain a été vérifiée. Enfin, nous avons réalisé l'inventaire des communautés virales de trois espèces de moustiques collectées à Marseille par métagénomique, qui a révélé la présence de nombreux nouveaux virus. L'ensemble des résultats présentés dans cette thèse souligne que l'utilisation d'outils innovants tels que le MALDI-TOF MS et la métagénomique pour étudier les vecteurs et les agents qu'ils portent est une stratégie prometteuse qui contribuera dans la connaissance des cycles de transmission zoonotique et des risques potentiels d'émergence des maladies vectorielles en population humaine. / Hematophagous arthropods such as mosquitoes, ticks, and fleas are of significant importance in public health because of their ability to transmit major diseases to humans and animals. Vector control and epidemiological vector surveillance are essential in the strategy of combating vector-borne diseases. The latter is successful only by a correct and precise identification of the vectors. Thus in this work, we have developed and improved the protocols of samples preparation for the identification of adult mosquitoes and their aquatic stages, ticks, and fleas by MALDI-TOF MS. This tool has been already distinguished as being reliable for the arthropods identification. The second part of our work consisted in the application of these protocols on mosquito larvae collected in the field during an entomological investigation carried out in the city of Marseille. In this study, the relevance and reliability of MALDI-TOF MS for the identification of mosquito larvae collected in the field were verified. Finally, we carried out the inventory of the viral communities of three mosquito species collected in Marseille by metagenomics, which revealed the presence of numerous new viruses. All the results presented in this thesis emphasize that the use of innovative tools such as MALDI-TOF MS and metagenomics to study vectors and the agents they carry is a promising strategy that will contribute to the knowledge of zoonotic transmission cycles and the potential risks of the emergence of vector-borne diseases in human populations.