acase@tulane.edu / Next generation sequencing (NGS) is a relatively new technology that has revolutionized the way scientists discover and investigate pathogens. It has been estimated that a staggering one in every five cancers worldwide is linked to an infectious agent. An understanding of the pathogen biology as well as the interactions with the host will lead to better therapies and outcomes for patients suffering from pathogen-associated malignancies. Despite the promise for this phenomenon through NGS-based approaches, we are still in the infancy of sequence analysis and are unable to fully appreciate the potential of NGS. To facilitate data mining, an automated computational pipeline for the simultaneous analysis of pathogen and host transcripts called RNA CoMPASS was developed. Using RNA CoMPASS to investigate a variety of sequencing datasets over the years, substantial bacterial contamination have been routinely identified in human-derived RNA-seq datasets that likely arose from environmental sources. Based on this analysis, a need for more stringent sequencing and analysis protocols to investigate sequence-based microbial signatures in clinical samples is crucial. NGS-based approaches were utilized to investigate the role of Epstein-Barr virus (EBV) in the pathogenesis of gastric carcinoma. A comprehensive assessment of the virome of various brain tissue samples was also performed, with the notion that an NGS-based detection method would be unbiased, sensitive, specific, and accurate. Taken together, these studies provide a framework for using NGS technology to study oncogenic pathogens and bring awareness to contamination issues within sequencing datasets. / 1 / Michael J Strong

O comportamento social pode ser descrito como qualquer atividade de interação intraespecífica incluindo a escolha entre parceiros reprodutivos, reconhecimento da espécie, comportamento altruísta e organização da sociedade animal. Entre as espécies de animais mais sintonizadas com seu ambiente social estão os insetos que, como por exemplo nas espécies de abelhas das tribos Apini e Meliponini, apresentam um padrão complexo de socialidade conhecido como comportamento altamente eussocial. As abelhas constituem um grupo ideal para o estudo das bases da evolução deste comportamento, pois apresentam uma grande diversidade de organização social, desde espécies solitárias até altamente eussociais. Embora a evolução da eussocialidade tenha sido motivo de muitos estudos, as mudanças genéticas envolvidas nesse processo não são completamente conhecidas. Dados da literatura fornecem um ponto de partida para o entendimento da relação entre alterações gênicas específicas e a eussocialidade, mas questões fundamentais na evolução do comportamento social ainda precisam ser respondidas. Recentemente, novas tecnologias de sequenciamento têm permitido o estudo de organismos modelo e não modelo de forma mais detalhada e não direcional. Análises deste tipo são promissoras para o estudo evolutivo de características complexas como o comportamento. Neste contexto, realizamos um amplo estudo sobre as bases moleculares envolvidas em diferentes características comportamentais relacionadas à evolução da socialidade em abelhas. Para tanto, o padrão global de expressão de genes, em espécies e fases do desenvolvimento distintas, foram analisados comparativamente através de múltiplas abordagens. No Capítulo 1, utilizamos contaminantes do transcriptoma da abelha solitária Tetrapedia diversipes para analisar os recursos florais utilizados por esta espécie em suas duas gerações reprodutivas. Neste estudo concluímos que a riqueza de espécies visitadas durante a primeira geração é muito maior do que durante a segunda geração, o que está provavelmente relacionado à floração de primavera durante o primeiro período reprodutivo. No Capítulo 2, verificamos que o padrão de expressão dos genes das fêmeas fundadoras possivelmente afeta o desenvolvimento larval em T. diversipes. O padrão bivoltino de reprodução desta espécie, com diapausa em uma das gerações, pode ser importante para a evolução do comportamento social. Além disso, entre os genes possivelmente envolvidos nessa característica, podemos encontrar genes mitocondriais e lncRNAs. Os resultados obtidos no Capítulo 3 sugerem que a especialização em subcastas de operárias ocorreu posteriormente nas diferentes linhagens de abelhas, envolvendo genes específicos. No entanto, esses genes afetam processos biológicos comuns nas diferentes espécies. Por sua vez, o Capítulo 4 apresenta um método promissor para a identificação de genes comportamentais em diferentes espécies de abelhas, através de uma análise de expressão comparativa. Com base nessas análises, 787 genes comportamentais, que possivelmente fazem parte de um toolkit eussocial em abelhas, foram encontrados. O padrão de metilação desses genes, em espécies com diferentes níveis sociais, indicou ainda que o contexto genômico da metilação pode ser relevante para eussocialidade. Os resultados obtidos nesses estudos apresentam novas perspectivas metodológicas e evolutivas para o estudo da evolução do comportamento social em abelhas / The social behaviour can be widely described as any intraspecific interaction in the animal life, including but not restricted to, female choice, species recognition, altruistic behaviour and the organization of animal society. Among the animal species most attuned to their social environment are the insects that, for example, in the Apini and Meliponini tribes, present a complex behaviour known as highly eusocial. Bees are an ideal group to study the evolution of the social behaviour because they have a great diversity of social life styles that evolved independently. The tribes Apini and Meliponini comprise only highly eusocial species whereas various levels of sociality can be detected in other tribes, being most bees indeed solitary. Although the evolution of eusociality has been the subject of many studies, the genetic changes involved in the process have not been completely understood. Results from studies conducted so far provide a starting point for the connection between specific genetic alterations and the evolution of eusocial behaviour. However fundamental questions about this process are still open. Recently, new sequencing technologies have allowed genetic studies of model and non-model organisms in a deep and non-directional way, which is promising for the study of complex characteristics. Herein, we present a broad analysis of the molecular bases of different behavioural characteristics related to the evolution of sociality in bees. To that end, the global expression pattern of genes involved in different behavioural features, in a number of bee species and distinct developmental stages, was comparatively studied using multiple approaches. Through these approaches different results were obtained. In Chapter 1, we used contaminant transcripts from the solitary bee Tetrapedia diversipes to identify the plants visited by this bee, during its two reproductive generations. These contaminant transcripts revealed that the richness of plant species visited during the first reproductive generation was considerably greater than during the second generation. Which is probably related to the floral boom occurring in spring during the first reproductive period. In Chapter 2, data suggests that the expression pattern in foundresses affect larval development in T. diversipes. The bivoltinism presented by this species, with diapause in one generation, might be an important feature for the evolution of sociality. Our results suggest that mitochondrial genes and lncRNAs are involved in this reproductive pattern. Results described in Chapter 3 indicate that specialization in worker subcastes occurred posteriorly in distinct bee lineages, driven by specific genes. However, these genes affected common biological processes in the different species. In Chapter 4 is described a promising analyses method to identify, comparatively, genes involved in bee social behaviour. Using this approach, we identified 787 behavioural genes that might be involved in social behaviour of different species. The methylation pattern of these genes suggests that the DNA context in which methylation marks occur, might be especially relevant to bee sociality. Results obtained here presents new methodological and evolutionary approaches to the study of social behaviour in bees

Massive sequencing has transformed the field of genome biology due to the continuous introduction and evolution of new methods. In recent years, the technologies available to read through genomes have undergone an unprecedented rate of development in terms of cost-reduction. Generating sequence data has essentially ceased to be a bottleneck for analyzing genomes instead to be replaced by limitations in sample preparation and data analysis. In this work, new strategies are presented to increase both the throughput of library generation prior to sequencing, and the informational content of libraries to aid post-sequencing data processing. The protocols developed aim to enable new possibilities for genome research concerning project scale and sequence complexity. The first two papers that underpin this thesis deal with scaling library production by means of automation. Automated library preparation is first described for the 454 sequencing system based on a generic solid-phase polyethylene-glycol precipitation protocol for automated DNA handling. This was one of the first descriptions of automated sample handling for producing next generation sequencing libraries, and substantially improved sample throughput. Building on these results, the use of a double precipitation strategy to replace the manual agarose gel excision step for Illumina sequencing is presented. This protocol considerably improved the scalability of library construction for Illumina sequencing. The third and fourth papers present advanced strategies for library tagging in order to multiplex the information available in each library. First, a dual tagging strategy for massive sequencing is described in which two sets of tags are added to a library to trace back the origins of up to 4992 amplicons using 122 tags. The tagging strategy takes advantage of the previously automated pipeline and was used for the simultaneous sequencing of 3700 amplicons. Following that, an enzymatic protocol was developed to degrade long range PCR-amplicons and forming triple-tagged libraries containing information of sample origin, clonal origin and local positioning for the short-read sequences. Through tagging, this protocol makes it possible to analyze a longer continuous sequence region than would be possible based on the read length of the sequencing system alone. The fifth study investigates commonly used enzymes for constructing libraries for massive sequencing. We analyze restriction enzymes capable of digesting unknown sequences located some distance from their recognition sequence. Some of these enzymes have previously been extensively used for massive nucleic acid analysis. In this first high throughput study of such enzymes, we investigated their restriction specificity in terms of the distance from the recognition site and their sequence dependence. The phenomenon of slippage is characterized and shown to vary significantly between enzymes. The results obtained should favor future protocol development and enzymatic understanding. Through these papers, this work aspire to aid the development of methods for massive sequencing in terms of scale, quality and knowledge; thereby contributing to the general applicability of the new paradigm of sequencing instruments. / <p>QC 20121126</p>

DNA sequence assembly is one of the fundamental areas of bioinformatics. It involves the correct formation of a genome sequence from its DNA fragments ("reads") by aligning and merging the fragments. There are different sequencing technologies -- some support long DNA reads and the others, shorter DNA reads. There are sequence assembly programs specifically designed for these different types of raw sequencing data.<p> This work explores and experiments with these different types of assembly software in order to compare their performance on the type of data for which they were designed, as well as their performance on data for which they were not designed, and on mixed data. Such results are useful for establishing good procedures and tools for sequence assembly in the current genomic environment where read data of different lengths are available. This work also investigates the effect of the presence or absence of quality information on the results produced by sequence assemblers.<p> Five strategies were used in this research for assembling mixed data sets and the testing was done using a collection of real and artificial data sets for six bacterial organisms. The results show that there is a broad range in the ability of some DNA sequence assemblers to handle data from various sequencing technologies, especially data other than the kind they were designed for. For example, the long-read assemblers PHRAP and MIRA produced good results from assembling 454 data. The results also show the importance of having an effective methodology for assembling mixed data sets. It was found that combining contiguous sequences obtained from short-read assemblers with long DNA reads, and then assembling this combination using long-read assemblers was the most appropriate approach for assembling mixed short and long reads. It was found that the results from assembling the mixed data sets were better than the results obtained from separately assembling individual data from the different sequencing technologies. DNA sequence assemblers which do not depend on the availability of quality information were used to test the effect of the presence of quality values when assembling data. The results show that regardless of the availability of quality information, good results were produced in most of the assemblies.<p> In more general terms, this work shows that the approach or methodology used to assemble DNA sequences from mixed data sources makes a lot of difference in the type of results obtained, and that a good choice of methodology can help reduce the amount of effort spent on a DNA sequence assembly project.

DNA sequence assembly is one of the fundamental areas of bioinformatics. It involves the correct formation of a genome sequence from its DNA fragments ("reads") by aligning and merging the fragments. There are different sequencing technologies -- some support long DNA reads and the others, shorter DNA reads. There are sequence assembly programs specifically designed for these different types of raw sequencing data.<p> This work explores and experiments with these different types of assembly software in order to compare their performance on the type of data for which they were designed, as well as their performance on data for which they were not designed, and on mixed data. Such results are useful for establishing good procedures and tools for sequence assembly in the current genomic environment where read data of different lengths are available. This work also investigates the effect of the presence or absence of quality information on the results produced by sequence assemblers.<p> Five strategies were used in this research for assembling mixed data sets and the testing was done using a collection of real and artificial data sets for six bacterial organisms. The results show that there is a broad range in the ability of some DNA sequence assemblers to handle data from various sequencing technologies, especially data other than the kind they were designed for. For example, the long-read assemblers PHRAP and MIRA produced good results from assembling 454 data. The results also show the importance of having an effective methodology for assembling mixed data sets. It was found that combining contiguous sequences obtained from short-read assemblers with long DNA reads, and then assembling this combination using long-read assemblers was the most appropriate approach for assembling mixed short and long reads. It was found that the results from assembling the mixed data sets were better than the results obtained from separately assembling individual data from the different sequencing technologies. DNA sequence assemblers which do not depend on the availability of quality information were used to test the effect of the presence of quality values when assembling data. The results show that regardless of the availability of quality information, good results were produced in most of the assemblies.<p> In more general terms, this work shows that the approach or methodology used to assemble DNA sequences from mixed data sources makes a lot of difference in the type of results obtained, and that a good choice of methodology can help reduce the amount of effort spent on a DNA sequence assembly project.

Specific and sensitive recognition of foreign agents is a critical attribute of the overall effective immune system required for maintaining host protection against challenge from pathogenic cells. In the humoral arm of the immune system, this recognition attribute is carried out by the cell surface bound immunoglobulin-like receptors (BCR) and its soluble forms i.e. antibodies. Over several million years of evolution, the immune system has adopted several strategies for diversifying the antibody sequence and thus its ability to recognize an astronomical variety of molecules through the combinatorial assembly of a small number of DNA segments or genes. Among these immunoglobulin gene diversification strategies, antibody somatic VDJ recombination and junctional diversity are the fundamental mechanisms in generating a broad range of antibody specificities. Understanding how the genetic diversity of antibodies is affected in health and disease is critical for a wide range of medical applications, from vaccine evaluation to diagnostics and therapeutics discovery. Because of the very large number of distinct antibodies encoded by the more than 100 billion B cells in humans, it is essential to use high throughput next generation sequencing technologies in order to obtain an adequate sampling of the sequences and relative abundance of different antibodies expressed by B cells in clinical samples. The process requires rigorous methods for first, experimentally determining the sequences of antibodies in a sample and for second, informatics tools designed for distilling this information for practical purposes. This dissertation describes a variety of experimental approaches and informatics tools developed for the determination and mining of the antibody repertoire. The information from this work has led to major conclusions regarding the nature of the antibody repertoire in healthy individuals, in volunteers following vaccination, and in HIV-1 patients. / text

A dominant ENU screen produced mouse line 7238 with large platelets. Sequence capture and Next Generation sequencing identified a mutation in Myh9 at Q1443L [1]. Mice were tested for aspects of MYH9-Related Disease (MYH9RD), a rare human condition caused by mutations within MYH9; macrothrombocytopenia and neutrophil inclusions are found in almost all cases, while deafness, cataracts and renal disease have variable penetrance and severity. Myh9Q1443L/+ and Myh9Q1443L/Q1443L animals have neutrophil inclusions [1] and increased cataracts at 2, 6 and 12 months; Myh9Q1443L/Q1443L animals at 12 months have changes in kidney output [2]. Immunofluoresence showed changes in protein expression in glomeruli at two months. This is the first ENU mouse model identified by a sequence capture mechanism, and the first mouse line to produce a point mutation within the Myh9 gene [1,2]. This mouse models MYH9RD, and is an invaluable tool to understand the role of this protein, and to determine mechanisms underlying this disease.

A dominant ENU screen produced mouse line 7238 with large platelets. Sequence capture and Next Generation sequencing identified a mutation in Myh9 at Q1443L [1]. Mice were tested for aspects of MYH9-Related Disease (MYH9RD), a rare human condition caused by mutations within MYH9; macrothrombocytopenia and neutrophil inclusions are found in almost all cases, while deafness, cataracts and renal disease have variable penetrance and severity. Myh9Q1443L/+ and Myh9Q1443L/Q1443L animals have neutrophil inclusions [1] and increased cataracts at 2, 6 and 12 months; Myh9Q1443L/Q1443L animals at 12 months have changes in kidney output [2]. Immunofluoresence showed changes in protein expression in glomeruli at two months. This is the first ENU mouse model identified by a sequence capture mechanism, and the first mouse line to produce a point mutation within the Myh9 gene [1,2]. This mouse models MYH9RD, and is an invaluable tool to understand the role of this protein, and to determine mechanisms underlying this disease.

No description available.

Water sources are susceptible to faecal contamination from animal and human pollution sources. Pollution of our waterways has significant implications on human health, especially from a pathogen perspective. Microbial source tracking (MST) is a promising field which aims to identify the sources of faecal contamination, and thereby allowing for the development of effective management strategies to minimise pollution and the impact on human health. Many of the currently used methods rely on the identification of host-specific markers within the 16S ribosomal RNA (rRNA) gene of bacteria by use of amplification techniques such as polymerase chain reaction (PCR). However, these methods can be limited by sensitivity, quantification, geographical differences and issues of cost which can limit how many markers are evaluated. Developments in DNA sequencing technologies over the past decade have led to a number of next generation sequencing (NGS) platforms which have a rapid, high throughput approach, resulting in an exponential decrease in the cost of sequencing. This has enabled the development of sequence-based metagenomics, where entire communities from environmental samples can be analysed based on their genetic material. The ability to barcode allows for analysis of multiple samples at once, reducing the cost of sequencing environmental samples even further. This is a promising technique for MST, which has had little investigation to date. The primary focus of the studies described in this thesis was to evaluate the use of NGS technology through a metagenomic approach. Roche 454 amplicon sequencing was used to sequence a 16S rRNA gene target, amplified from faecal and water samples from various sources in New Zealand. Barcode strategies were incorporated in the amplification design to allow multiple samples to be sequenced simultaneously. A proof-of-concept study initially utilised a small sequence dataset to evaluate a range of analysis tools available. Taxonomic identification and diversity measures were used to evaluate a selection of currently available tools designed for analysing metagenomic data, with the Quantitative Insights Into Microbial Ecology (QIIME) platform decided upon for further studies. A larger study, including 35 faecal samples from 13 difference sources and 10 water samples, resulted in 522,065 raw sequencing reads. Diversity results suggest three phyla, Bacteroidetes, Firmicutes and Proteobacteria, are strongly represented across all faecal sources analysed. Microbial diversity analysis using clustering techniques provided evidence of host source being the largest influence on bacterial diversity, with samples from each source generally clustering together. This technique could not be used to identify sources of contamination sources in water samples as the water samples all clustered separately from the faecal samples. More successful was the use of taxonomic classifications to determine bacteria genera that were potentially specific to one source. Water samples were screened for these genera, with six out of the ten water samples being indicators of either ruminant or human contamination. Faecal and water samples were also analysed for a selection of published 16S rRNA PCR markers, using a computational motif-based search method. Of the twenty motifs screened for, 14 were found to be relatively source-specific for ruminant, human, dog or pig faecal samples, with some cross-reactivity with chicken and possum samples. Using this method, the contamination source for six of the ten water samples was identified, with the remaining four samples found to not have enough sequences to assess with confidence. Both metagenomic strategies produced comparable results which were consistent with previous MST analysis. This project demonstrates the potential application of next generation sequencing technologies to microbial source tracking, suggesting the possibility this approach to replace existing microbial source tracking methods.