Oral cancer in early stages (I and II) may be curable by surgery or radiation therapy alone but advanced stage disease (III and IV) has a relatively low survival rate. The pathogenic pathways that contribute to Oral Squamous Cell Carcinoma (OSCC) remain poorly characterised and the critical factor in the lack of prognostic improvement is that a significant proportion of cancers initially are asymptomatic lesions and are not diagnosed or treated until they reach an advanced stage. Hence, a clinically applicable gene expression signature is in high demand and improved characterization of the OSCC gene expression profile would constitute substantial progress. For OSCC, possible themes that might be addressed using microarray data include distinguishing the disease from normal at the molecular level; determining whether specific biomarkers or profiles are predictive for tumour behaviour; and identifying biologic pathways necessarily altered in tumourigenesis, potentially illuminating novel therapeutic targets. However, OSCC is a heterogeneous disease, making diagnostic biomarker development difficult. Although this phenotypic variation is striking when one compares OSCC from different geographic locales, little is known about the underpinning biological mechanisms. Cancer may be accompanied by the production and release of a substantial number of proteins, metabolites and/or hormones into the blood, saliva, and other body fluids that could also serve as useful markers for assessing prognosis, metastasis, monitoring treatment, and detecting malignant disease at an early stage. The primary aim of this thesis is to investigate metabolomic and transcriptomic profiles using multiple bioinformatics approaches and biological annotation tools in an attempt to identify specific biomarkers and prediction models for OSCC from each profile as well as from the interface outcomes of integrating the two platforms. Additional aims of the thesis go further to identify the mechanisms underlying the biological changes during tumorigenic transformation of OSCC, as well as to determine biological processes underpinning the heterogeneity of the disease among populations. Two review studies were carried out in this thesis. The review study of published transcriptomic profiles of OSCC specified several genes and pathways exhibiting substantially altered expression in cancerous versus noncancerous states across studies. However, the result of the review suggests not relying on the final set of genes published by the individual studies, but to access the raw data of each study and start subsequent analysis from that stage using unified bioinformatics approaches to acquire useful and complete understanding of the systems biology. The other review study focused on the metabolic profiles of OSCC and revealed a systemic metabolic response to cancer, which bears great potential for biomarker development and diagnosis of oral cancer. However, the metabolic signature still needs to improve specificity for OSCC from other types of cancer. In an attempt to detect a robust gene signature of OSCC overcoming the limitation of the transcriptomic review in accessing the raw data from the previous works, four public microarray raw datasets (comprising 365 tumour and normal samples) of OSCC were successfully integrated using ComBat data integration method in R software, determining the common set of genes, biomarkers, and the relative regulatory pathways possibly accountable for tumour transformation and growth in OSCC. Examination of the meta-analysis datasets showed several discriminating gene expression signatures for OSCC relative to normal oral mucosa; with a signature of 8 genes (MMP1, LAMC2, PTHLH, TPBG, GPD1L, MAL, TMPRSS11B, and SLC27A6) exhibiting the best discriminating performance and show potential as a diagnostic biomarker set. In addition, 32 biomarkers specific to OSCC and HNSCC were identified with the majority involved in extracellular matrix (ECM), interleukins, and peptidase activity where around 2/3 of them are located in the extracellular space and plasma membrane. Additionally, investigation of the interactive network created by merging metabolic and transcriptomic profiles highlighted the significant molecular and cellular biofunctions, pathways, and biomarkers distinguishing OSCC from normal oral mucosa. The results highlighted interactions of significantly altered expression of Dglucose, ethanol, glutathione, GABA, taurine, choline, creatinine, and pyruvate metabolites with the expressed PTGS2, IL1B, IL8, IL6, MMP1, MMP3, MMP9, SERPINE1, COL1A1, COL4A1, LAMC2, POSTN, ADAM12, CDKN2A, PDPN, TGM3, SPINK5, TIMP4, KRT19, and CRYAB biomarkers of OSCC. Such a pattern may represent a clinically useful surrogate for the presence of OSCC which might help in deciphering some of the obscure multifaceted mechanisms underlying carcinogenesis of OSCC which emerged from dysregulated genetic and metabolic system of the body. In an attempt to define pathways of importance in two phenotypically different forms of OSCC, transcriptomic analysis of OSCC from UK and Sri Lankan patients was undertaken. The development of OSCCs in UK and Sri Lankan populations appears largely mediated by similar biological pathways despite the differences related to race, ethnicity, lifestyle, and/or exposure to environmental carcinogens. However, results revealed a highly activated “Cell-mediated Immune Response” in Sri Lankan tumour and normal samples relative to UK cohorts which may reflects a role in resistance of patients to invasiveness, metastasis, and mortality observed in Sri Lankan relative to UK patients. In conclusion, multiple molecular profiles were able to identify a unique transcriptomic profile for OSCC and could further discriminate the tumour from normal oral mucosa on the basis of 8 genes. Altered expression of several metabolic and transcriptomic biomarkers specific for OSCC were identified, along with several dysregulated pathways and molecular processes found common in patient with oral cancer. Integrating both metabolomic and transcriptomic signatures revealed a promising strategy in analysing the concurrent perturbation in both genetic and metabolic systems of the body. Additional results revealed possible impact of specific supplementary dietary components in boosting the immune system of the body against invasion, progression, and metastasis of the disease. Further clinical studies are required to confirm and validate the current results.

Sepsis is defined as a dysregulated immune response to infection causing organ dysfunction, and is a major area of unmet clinical need. Although conventionally considered a unified disease with a common pathway to organ failure and death, substantial clinical and molecular heterogeneity is seen, which has limited efforts to understand pathophysiology and improve therapeutic strategies. Sepsis is associated with global changes in gene expression, and genetic variants are known to affect the response to infection. This thesis therefore uses an integrated functional genomics approach to investigate disease mechanisms and variation in the sepsis response. Data are presented for 551 patients admitted to intensive care with sepsis due to community acquired pneumonia (CAP) or faecal peritonitis (FP). The sepsis response is explored using genome-wide gene expression and proteomics data, and molecular quantitative trait loci (QTL) are mapped in the context of disease. Comparisons with cardiac surgery patients are performed to identify shared and specific aspects of the host response. The host transcriptomic response was largely shared across sources of sepsis, although some specificity relating to viral infection and interferon signalling was observed and validated in prospectively recruited patients. Expression-based sepsis response signature (SRS) subgroups previously described in CAP were validated, and were additionally observed in FP. SRS1 is associated with higher early mortality, and shows enrichment of pathways relating to T cell exhaustion, cell death, and endotoxin tolerance. Differences between SRS groups were also observed in the FP plasma proteome. Serial sampling enabled the investigation of temporal changes in gene expression and protein abundance within patients. Lastly, disease-relevant expression QTL were identified, and interactions with source of sepsis and SRS determined, highlighting the potential impact of regulatory variation on the sepsis response. This thesis demonstrates the benefit of an integrative functional genomics approach to explore heterogeneity in sepsis, and highlights opportunities for patient stratification and personalised medicine.

acase@tulane.edu / 1 / Catherine Arnold

Mycobacteria is a genus characterized by its unique layer of mycomembrane, which enhances its pathogenicity causing notorious infections such as tuberculosis or leprosy in humans. Some pathogenic mycobacteria are part of the Mycobacterium tuberculosis complex (MTBC), while others are predominantly environmental and belong to the class of non-tuberculosis mycobacteria (NTM). Some of the NTMs are also opportunistic pathogens causing infections mostly in immunocompromised individuals. In this study, we focus on a recently discovered species of NTM known as M. riyadhense, originally isolated from a patient with TB-like symptoms in Riyadh. With prepublication access to the completely assembled and fully annotated genomes of M. riyadhense, we wanted to study the gene expression of M. riyadhense after establishing an infection model using a murine macrophage cell line. We performed transcriptomic analysis of M. riyadhense upon infection using RAW264.7 murine macrophages to determine the hallmarks of differentially expressed (DE) genes at early infection time points. Most DE genes observed belong to one of the crucial secretion systems known as ESX-1. Most genes were highly upregulated during 12-hour of infection, particularly esxA and esxB, which encode for ESAT-6 and CFP-10 secretion proteins. These substrates are essential for the virulence and pathogenicity of Mycobacterium tuberculosis (MTB). In addition, we observed downregulation of WhiB5, a transcriptional regulator that is a well-known controller of Mycobacterium tuberculosis virulence and reactivation, and regulates genes encoding the constituents of two type VII secretion systems, namely, ESX-2 and ESX-4. We have also identified other genes of yet unknown function that are highly upregulated during early infection needing functional characterization in future follow-up studies. Overall, we have established an in vitro cell infection model for M. riyadhense that can be used to study host pathogen cross talks during infection processes in tubercle bacilli.

The cephalopod clade Decapodiformes consists of Spirulida (ram’s horn squid), Sepiolida (bobtail squids), Sepiida (cuttlefishes), Myopsida (inshore squids), and Oegopsida (oceanic squids). While many unanswered questions remain regarding this clade, a thorough examination requires a multi-level taxonomic approach due to uneven data coverage within. This dissertation explores a diverse set of topics in decapodiform evolution and biogeography with a hierarchical approach, starting with the “superorder” Decapodiformes, moving to the “order” Oegopsida, and finally zooming in to the family level with Pyroteuthidae. addressing four main questions: 1) Does RNA editing affect the use of transcriptomics in cephalopod phylogenetics? 2) What is the evolutionary history of ammoniacal buoyancy in oegoposids? 3) What are the present and future niches of pyroteuthid squids? 4) What is the biogeographic history of pyroteuthid squids?

Whilst antidepressants are widely prescribed, there is a large degree of variation between patients in terms of treatment outcomes. Furthermore, the mechanisms by which these drugs exert their effects remain unclear. In this thesis, genetic biomarkers of antidepressant outcomes have been explored, in order to better understand the molecular mechanisms underpinning effective antidepressant treatment. The research presented here use data from the GENDEP project, which is a large pharmacogenetic study of depressed patients receiving antidepressant treatment. Firstly, the pharmacological underpinnings of antidepressant-associated side effects were used to categorise these side effects and conduct a candidate gene analysis. Whilst a significant association between variation within the HTR2C gene and serotonergic side effects was found, the observation was not replicated in a second sample. Secondly, the role of variability in drug metabolism rates in treatment outcomes was investigated. Examining genotypic information on the cytochrome P450 enzymes, no associations with treatment response, side effects or study discontinuation were observed. Furthermore, serum concentrations of antidepressant were unrelated to treatment response or overall burden of side effects, predicting only a minority of specific side effects. Thirdly, transcriptomic changes with drug administration were explored in relation to treatment efficacy. Two genes were identified where changes in expression levels were significantly associated with treatment response amongst patients taking nortriptyline. Furthermore, using a network-based approach, changes in gene expression across one module of coexpressed genes showed significant correlation with symptom improvement; this biological network generalised across different antidepressant medications. Finally, genomic and transcriptomic data were combined, in an examination of the genetic control of gene expression. This analysis then was used to gain an insight into the molecular processes that link genotype to phenotype. The evidence presented within this thesis, when considered in combination with existing literature, highlights that antidepressant efficacy is a complex trait, influenced by many genes of small effect. Nevertheless, by layering together different levels of information, we can begin to dissect the molecular mechanisms involved in antidepressant action.

Transcriptomic analyses from across eukaryotes indicate that most of the genome is transcribed at some point in the developmental trajectory of an organism. One class of these transcripts is termed long intergenic noncoding RNAs (lincRNAs). Recently, attention has focused on understanding the evolutionary dynamics of lincRNAs, particularly their conservation within genomes. Here, we take a comparative genomic and phylogenetic approach to uncover factors influencing lincRNA emergence and persistence in the plant family Brassicaceae, to which Arabidopsis thaliana belongs. We searched 10 genomes across the family for evidence of >5000 lincRNA loci from A. thaliana. From loci conserved in the genomes of multiple species, we built alignments and inferred phylogeny. We then used gene tree/species tree reconciliation to examine the duplication history and timing of emergence of these loci. Emergence of lincRNA loci appears to be linked to local duplication events, but, surprisingly, not whole genome duplication events (WGD), or transposable elements. Interestingly, WGD events are associated with the loss of loci for species having undergone relatively recent polyploidy. Lastly, we identify 1180 loci of the 6480 previously annotated A. thaliana lincRNAs (18%) with elevated levels of conservation. These conserved lincRNAs show higher expression, and are enriched for stress-responsiveness and cis-regulatory motifs known as conserved noncoding sequences (CNSs). These data highlight potential functional pathways and suggest that CNSs may regulate neighboring genes at both the genomic and transcriptomic level. In sum, we provide insight into processes that may influence lincRNA diversification by providing an evolutionary context for previously annotated lincRNAs.

No description available.

Ebola viruses cause sever disease in humans and non-human primates. The resulting disease, Ebola virus disease (EVD), can have hemorrhagic manifestations and has mortality rates ranging from 20-90%. There is a strong need for better understanding of the disease as well as improved diagnostics and prognostics. One approach to improving diagnostic and prognostics for severe viral diseases such as EVD is to define how the host response to infection develops and produces indicators of disease and outcome. To create a better means to understand if a patient is likely to survive or succumb to Ebola (EBOV) infection, I have sought to develop an understanding of the host response to EBOV infection in humans from the recent outbreak. I analyzed RNA-Seq samples from the 2013-2016 West Africa outbreak. I identified that the innate immune pathways are in general over activated in EVD and is stronger in patients who succumbed to disease. Furthermore, I developed a set of 10 genes that can perform as a prognostic indicator of disease independent of the viral load. This is the first demonstration that the circulating transcriptional immune response to EBOV infection can be used to predict infection outcome. To work towards a diagnostic platform of disease, I analyzed multiple studies of time-resolved datasets in animal models of disease. I analyzed RNA-Seq and NanoString data coupled with telemetry data in EBOV-challenged macaques. The earliest and strongest changes seen in the pre-symptomatic stage of disease is the up-regulation of many innate immune genes. I used this information to develop a NanoString codeset that can act as a pre-symptomatic indicator of disease that was tested in further animal studies as a diagnostic in pre-symptomatic stages of disease. Together, this work has identified a sets of genes that can work as a diagnostic for pre-symptomatic patients of EBOV and act as a prognostic indicators of disease. In future outbreaks, this type of information will be important to help track primary contacts of infected individuals and first responders, as well as better inform clinical management of patients. This lays the groundwork for similar analysis to be performed on other severe viral diseases such as Lassa Fever and Marburg Fever. / 2019-11-27T00:00:00Z

O mexilhão marrom Perna perna (Linnaeus, 1758) auxilia no monitoramento de compostos químicos em ecossistemas marinhos. No entanto, os mecanismos moleculares de detoxificação e resposta ao estresse são desconhecidos. Elucidar esses mecanismos é crucial para entender os efeitos tóxicos dos poluentes químicos e desenvolver biomarcadores para avaliar a qualidade ambiental dos ecossistemas marinhos. No presente estudo, indivíduos da espécie P. perna foram expostos a antraceno (ANT) e os RNAs mensageiros (mRNA) das brânquias foram sequenciados com a plataforma Illumina. A análise química do tecido mole dos animais identificou concentrações de ANT 268 a 715 vezes mais alta no grupo exposto comparado ao grupo controle, demonstrando que a exposição foi realizada com sucesso. O sequenciamento do transcritoma do P. perna gerou 273.152.390 pares de reads, resultando na montagem de 231.728 contigs com tamanho médio de 720 pb e N50 de 1.083 pb, os quais 66.563 contigs (28,7%) pode ser anotado utilizando banco de dados como GenBank, Pfam, Gene Ontology e KEGG. Os resultados obtidos a partir da anotação funcional sugerem que as brânquias tenham papel na biotransformação de xenobióticos, resposta antioxidante, sinalização, resposta imunológica inata, e osmorregulação. Foi possível identificar genes de biotransformação de fase I, II e III, incluindo CYPs e GSTs. Transcritos similares a CYPs e GSTs estavam sendo expressos no grupo exposto, porém nenhum deles foram classificados como diferencialmente expressos. Contudo, muitos genes hipotéticos foram diferencialmente expressos, o que sugere que P. perna utilize mecanismos desconhecidos de biotransformação para lidar com a contaminação de ANT. Genes de sistema imune inato foram regulados tanto positivamente quanto negativamente, assim como observado para Perna viridis exposto a benzo(a)pireno, sugerindo que ANT promove alterações da capacidade de resposta do sistema imune inato do P. perna. / The brown mussel Perna perna (Linnaeus, 1758) helps the monitoring of chemical compounds in marine ecosystems. However its molecular mechanisms of detoxification and stress response remain unclear. Elucidating these mechanisms is crucial to understand the toxic effects of chemical pollutants and to develop biomarkers to assess marine ecosystems. In this study, P. perna individuals were exposed to anthracene (ANT) and its mRNA complement was sampled sequenced with Illumina technology. Chemical analysis of the soft tissue identified ANT concentrations 268 - 715 fold higher in the exposed group compared to controls, demonstrating that the exposure procedure was successfully accomplished. Transcriptome sequencing of P. perna generated 273.152.390 paired reads that were assembled in 231.728 contigs of average length 720 bp and N50 1.083 bp , which 66.563 contigs (28,7%) could be annotated using GenBank genes, Pfam domains, Gene Ontology (GO) terms and KEGG pathways. The results obtained from functional annotation suggest gills play a role in xenobiotics biotransformation, antioxidant response, signal transduction, innate immune response, and osmoregulation. It was possible to identify transcripts similar to genes related with biotransformation reactions of phases I, II and III, including CYPs and GSTs. Transcripts similar to CYPs and GSTs isoforms were highly expressed in the group exposed to ANT, however no CYP, GST, or even other genes related with biotransformation reactions were classified as differentially expressed. On the other hand, several hypothetical genes were differentially expressed, which suggests that P. perna uses unknown mechanisms of biotransformation to deal with ANT stress contamination. Immune related-genes were both up and down-regulated, as was also observed for Perna viridis exposed to benzo(a)pyrene, suggesting that ANT promotes alteration in the immune response of P. perna.