Infect Genet Evol

Hepatitis E virus (HEV) causes epidemic and sporadic cases of hepatitis worldwide. HEV genotypes 3 (HEV3) and 4 (HEV4) infect humans and animals, with swine being the primary reservoir. The relevance of HEV genetic diversity to host adaptation is poorly understood. We employed a Bayesian network (BN) analysis of HEV3 and HEV4 to detect epistatic connectivity among protein sites and its association with the host specificity in each genotype. The data imply coevolution among 3c70% of polymorphic sites from all HEV proteins and association of numerous coevolving sites with adaptation to swine or humans. BN models for individual proteins and domains of the nonstructural polyprotein detected the host origin of HEV strains with accuracy of 74-93% and 63-87%, respectively. These findings, taken together with lack of phylogenetic association to host, suggest that the HEV host specificity is a heritable and convergent phenotypic trait achievable through variety of genetic pathways (abundance), and explain a broad host range for HEV3 and HEV4.CC999999/Intramural CDC HHS/United States2017-12-28T00:00:00Z24667049PMC57458027469vault:2572

Pattern Discovery from Biosequences

In this thesis we have developed novel methods for analyzing biological data, the primary sequences of the DNA and proteins, the microarray based gene expression data, and other functional genomics data. The main contribution is the development of the pattern discovery algorithm SPEXS, accompanied by several practical applications for analyzing real biological problems. For performing these biological studies that integrate different types of biological data we have developed a comprehensive web-based biological data analysis environment Expression Profiler (http://ep.ebi.ac.uk/)

Conservation and synteny of long non-coding RNAs invertebrate genomes and their identification in novel transcriptomes

Long non-coding RNAs (IncRNAs) are a biological entity defined by what they are not, rather than by what they are. This indicates that our knowledge about them is sensibly limited. The aim of my PhD is to gain insights into the evolution and the functions of IncRNAs through computational approaches and the usage of large scale functional genomics dataset. I developed an annotation pipeline, which can effectively identify IncRNAs in entire transcriptomes. The pipeline is able to accurately annotate the coding genes while predicting a conservative estimate of the IncRNA population. It allowed me to show, for the first time, the presence of lncRNA transcription in a diverse range of organisms. Further, I analysed sequence and positional conservation of lncRNAs, demonstrating the presence of short segments of conserved sequence in IncRNAs and the existence of several syntenically conserved non-coding transcripts over large evolutionary distances. However, I also demonstrate that positional conservation of lncRNAs with a flanking coding gene is generally independent from the conservation of the lncRNA expression with respect to the coding gene. Finally, I have characterised the diversity of lncRNA transcription in specific cells and developmental stages of two teleost fishes. In summary, the work presented in the thesis provides novel findings and contributions in the field of lncRNAomics

Applications, challenges and new perspectives on the analysis of transcriptional regulation using epigenomic and transcriptomic data

The integrative analysis of epigenomics and transcriptomics data is an active research field in Bioinformatics. New methods are required to interpret and process large omics data sets, as generated within consortia such as the International Human Epigenomics Consortium. In this thesis, we present several approaches illustrating how combined epigenomics and transcriptomics datasets, e.g. for differential or time series analysis, can be used to derive new biological insights on transcriptional regulation. In this work we focus on regulatory proteins called transcription factors (TFs), which are essential for orchestrating cellular processes. In our novel approaches, we combine epigenomics data, such as DNaseI-seq, predicted TF binding scores and gene-expression measurements in interpretable machine learning models. In joint work with our collaborators within and outside IHEC, we have shown that our methods lead to biological meaningful results, which could be validated with wet-lab experiments. Aside from providing the community with new tools to perform integrative analysis of epigenomics and transcriptomics data, we have studied the characteristics of chromatin accessibility data and its relation to gene-expression in detail to better understand the implications of both computational processing and of different experimental methods on data interpretation. Overall, we provide easy to use tools to enable researchers to benefit from the era of Biological Data Science.In dieser Dissertation stellen wir mehrere Ansätze vor, um die häufigsten "omics" Daten, wie beispielsweise differentielle Datenstze oder auch Zeitreihen zu verwenden, um neue Erkenntnisse über Genregulation auf transkriptioneller Ebene gewinnen zu können. Dabei haben wir uns insbesondere auf sogenannte Transkriptionsfaktoren konzentriert. Dies sind Proteine, die essentiell für die Steuerung regulatorischer Prozesse in der Zelle sind. In unseren neuen Methoden kombinieren wir epigenetische Daten, zum Beispiel DNaseI-seq oder ATAC-seq Daten, vorhergesagte Transkriptionsfaktorbindestellen und Genexpressionsdaten in interpretierbaren Modellen des maschinellen Lernens. Zusammen mit unseren Kooperationspartnern haben wir gezeigt, dass unsere Methoden zu biologisch bedeutsamen Ergebnissen führen, die exemplarisch im Labor validiert werden konnten. Ferner haben wir im Detail Zusammenhänge zwischen der Struktur des Chromatins und der Genexpression untersucht. Dies ist von immenser Bedeutung, um den Einfluss von experimentellen Charakteristika aber auch von der Modellierung der Daten auf die biologische Interpretation zu vermeiden

Derivatization protocol for mycolic acids detection using liquid chromatography/mass spectrometry, A

2012 Fall.Includes bibliographical references.New tools for the diagnosis and control of Tuberculosis are major challenges. In this context the use of biomarkers can be applied for detecting characteristic signatures from the tuberculosis-infected host and the pathogen. Mycolic acids are considered as a hallmark of the Mycobacterium genus being abundant in the mycobacterial cell wall. In this study a derivatization protocol was tested to enhance the detection of mycolic acid after the attachment of a quaternary amine and analysis of the derivatized products in the positive ionization mode with liquid chromatography/mass spectrometry. Three groups were considered i) mycolic acid standard ii) human urine spiked with mycolic acid standard, and iii) human serum spiked with mycolic acid standard. Each group included the analysis of a set of non-derivatized mycolic acids in positive and negative ionization mode, and derivatized mycolic acids in positive mode. The derivatization process applied to the mycolic acid standard and to the urine samples spiked with mycolic did not improve the ion volume value compared to the respective non-derivatized samples. Serum samples, however, showed a significant enhancement in the ion volume of the different mycolic acids analyzed compared to the non-derivatized serum samples (α=0.05). The method detection limit for the three groups was also achieved. Urine and serum samples spiked with mycolic acids showed higher detection limits compared to the mycolic acid standard; this was expected due the lipid extraction protocol and the complex nature of these fluids. The derivatization protocol did not improve the method detection limit compared to the non-derivatized samples. The overall results make the derivatization protocol questionable to be applied routinely in biological samples. However, the results obtained after the derivatization of serum samples could point to the advantages of using a derivatization protocol to study possible interactions between mycolic acids and other molecules present in serum that could be impeding their detection

Gene regulatory mechanisms controlling ageing in Caenorhabditis elegans

Mutations in the insulin/IGF-1 signalling (IIS) pathway lead to large lifespan extensions in the nematode Caenorhabiditis elegans. The role of IIS in ageing is evolutionarily conserved and requires the forkhead trancription factor DAF-16. In this thesis, I have attempted a novel strategy to identify genes involved in differential gene expression downstream of IIS in C. elegans. Using microarray data, I found that the H-ferritin gene ftn-1 is strongly regulated by IIS in a daf-16 – dependent manner. Ferritins act as intracellular iron-storage proteins. I then induced expression of a fluorescent GFP reporter of ftn-1 by introducing a mutation in daf-2. I subsequently screened a library of RNAi clones targeting transcription factors in order to identify mediators of IIS-dependent gene regulation. Candidate RNAi treatments were subsequently tested for their effects on expression of endogenous ftn-1 and on ageing. None of the genes identified had as important a role in either ftn- 1 expression or lifespan as daf-16, but several weaker determinants, like mdl-1, were identified. During the course of my screen, I found that loss of the hypoxia inducible factor hif-1 and its binding partner aha-1 leads to a large increase in expression from the ftn-1 GFP reporter, indicating that HIF-1 may act as a repressor of ftn-1 expression. Both HIF-1 protein levels and ftn-1 transcription are known to be responsive to iron levels. I found that regulation of the ftn-1 reporter by iron requires hif-1 and that repression of ftn-1 reporter expression occurs via a 63bp iron dependent element. An unexpected role of the upstream prolyl hydroxylase EGL-9 was also identified. I also contributed to a project aimed at identifying the consequences of overexpression of superoxide dismutases (SOD) on C. elegans ageing. Our efforts revealed that SOD over-expression extends lifespan by affecting signalling, not by reducing oxidative damage