Searching for molecular markers in head and neck squamous cell carcinomas (HNSCC) by statistical and bioinformatic analysis of larynx-derived SAGE libraries

Background: Head and neck squamous cell carcinoma (HNSCC) is one of the most common malignancies in humans. The average 5-year survival rate is one of the lowest among aggressive cancers, showing no significant improvement in recent years. When detected early, HNSCC has a good prognosis, but most patients present metastatic disease at the time of diagnosis, which significantly reduces survival rate. Despite extensive research, no molecular markers are currently available for diagnostic or prognostic purposes. Methods: Aiming to identify differentially-expressed genes involved in laryngeal squamous cell carcinoma (LSCC) development and progression, we generated individual Serial Analysis of Gene Expression (SAGE) libraries from a metastatic and non-metastatic larynx carcinoma, as well as from a normal larynx mucosa sample. Approximately 54,000 unique tags were sequenced in three libraries. Results: Statistical data analysis identified a subset of 1,216 differentially expressed tags between tumor and normal libraries, and 894 differentially expressed tags between metastatic and non-metastatic carcinomas. Three genes displaying differential regulation, one down-regulated (KRT31) and two up-regulated (BST2, MFAP2), as well as one with a non-significant differential expression pattern (GNA15) in our SAGE data were selected for real-time polymerase chain reaction (PCR) in a set of HNSCC samples. Consistent with our statistical analysis, quantitative PCR confirmed the upregulation of BST2 and MFAP2 and the downregulation of KRT31 when samples of HNSCC were compared to tumor-free surgical margins. As expected, GNA15 presented a non-significant differential expression pattern when tumor samples were compared to normal tissues. Conclusion: To the best of our knowledge, this is the first study reporting SAGE data in head and neck squamous cell tumors. Statistical analysis was effective in identifying differentially expressed genes reportedly involved in cancer development. The differential expression of a subset of genes was confirmed in additional larynx carcinoma samples and in carcinomas from a distinct head and neck subsite. This result suggests the existence of potential common biomarkers for prognosis and targeted-therapy development in this heterogeneous type of tumor.

Searching for molecular markers in head and neck squamous cell carcinomas (HNSCC) by statistical and bioinformatic analysis of larynx-derived SAGE libraries

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Bioinformatic analysis for exploring relationships between genes and gene products

To carry out their specific roles in the cell, genes and gene products often work together in groups, forming many relationships among themselves and with other molecules. Such relationships include physical protein-protein interaction relationships, regulatory relationships, metabolic relationships, genetic relationships, and much more. With advances in science and technology, some high throughput technologies have been developed to simultaneously detect tens of thousands of pairwise protein-protein interactions and protein-DNA interactions. However, the data generated by high throughput methods are prone to noise. Furthermore, the technology itself has its limitations, and cannot detect all kinds of relationships between genes and their products. Thus there is a pressing need to investigate all kinds of relationships and their roles in a living system using bioinformatic approaches, and is a central challenge in Computational Biology and Systems Biology. This dissertation focuses on exploring relationships between genes and gene products using bioinformatic approaches. Specifically, we consider problems related to regulatory relationships, protein-protein interactions, and semantic relationships between genes. A regulatory element is an important pattern or "signal", often located in the promoter of a gene, which is used in the process of turning a gene "on" or "off". Predicting regulatory elements is a key step in exploring the regulatory relationships between genes and gene products. In this dissertation, we consider the problem of improving the prediction of regulatory elements by using comparative genomics data. With regard to protein-protein interactions, we have developed bioinformatics techniques to estimate support for the data on these interactions. While protein-protein interactions and regulatory relationships can be detected by high throughput biological techniques, there is another type of relationship called semantic relationship that cannot be detected by a single technique, but can be inferred using multiple sources of biological data. The contributions of this thesis involved the development and application of a set of bioinformatic approaches that address the challenges mentioned above. These included (i) an EM-based algorithm that improves the prediction of regulatory elements using comparative genomics data, (ii) an approach for estimating the support of protein-protein interaction data, with application to functional annotation of genes, (iii) a novel method for inferring functional network of genes, and (iv) techniques for clustering genes using multi-source data.

GSVA: gene set variation analysis for microarray and RNA-seq data

Gene set enrichment (GSE) analysis is a popular framework for condensing information from gene expression profiles into a pathway or signature summary. The strengths of this approach over single gene analysis include noise and dimension reduction, as well as greater biological interpretability. As molecular profiling experiments move beyond simple case-control studies, robust and flexible GSE methodologies are needed that can model pathway activity within highly heterogeneous data sets. To address this challenge, we introduce Gene Set Variation Analysis (GSVA), a GSE method that estimates variation of pathway activity over a sample population in an unsupervised manner. We demonstrate the robustness of GSVA in a comparison with current state of the art sample-wise enrichment methods. Further, we provide examples of its utility in differential pathway activity and survival analysis. Lastly, we show how GSVA works analogously with data from both microarray and RNA-seq experiments. GSVA provides increased power to detect subtle pathway activity changes over a sample population in comparison to corresponding methods. While GSE methods are generally regarded as end points of a bioinformatic analysis, GSVA constitutes a starting point to build pathway-centric models of biology. Moreover, GSVA contributes to the current need of GSE methods for RNA-seq data. GSVA is an open source software package for R which forms part of the Bioconductor project and can be downloaded at http://www.bioconductor.org.

Analysis of the Pasteurella multocida outer membrane sub-proteome and its response to the in vivo environment of the natural host

This study describes the identification of outer membrane proteins (OMPs) of the bacterial pathogen Pasteurella multocida and an analysis of how the expression of these proteins changes during infection of the natural host. We analysed the sarcosine-insoluble membrane fractions, which are highly enriched for OMPs, from bacteria grown under a range of conditions. Initially, the OMP-containing fractions were resolved by 2-DE and the proteins identified by MALDI-TOF MS. In addition, the OMP-containing fractions were separated by 1-D SDS-PAGE and protein identifications were made using nano LC MS/MS. Using these two methods a total of 35 proteins was identified from samples obtained from organisms grown in rich culture medium. Six of the proteins were identified only by 2-DE MALDI-TOF MS, whilst 17 proteins were identified only by 1-D LC MS/MS. We then analysed the OMPs from P. multocida which had been isolated from the bloodstream of infected chickens (a natural host) or grown in iron-depleted medium. Three proteins were found to be significantly up-regulated during growth in vivo and one of these (Pm0803) was also up-regulated during growth in iron-depleted medium. After bioinformatic analysis of the protein matches, it was predicted that over one third of the combined OMPs predicted by the bioinformatics sub-cellular localisation tools PSORTB and Proteome Analyst, had been identified during this study. This is the first comprehensive proteomic analysis of the P. multocida outer membrane and the first proteomic analysis of how a bacterial pathogen modifies its outer membrane proteome during infection.

Identification and analysis of novel genes expressed in the mouse embryonic facial primordia

Craniofacial anomalies are a common feature of human congenital dysmorphology syndromes, suggesting that genes expressed in the developing face are likely to play a wider role in embryonic development. To facilitate the identification of genes involved in embryogenesis, we previously constructed an enriched cDNA library by subtracting adult mouse liver cDNA from that of embryonic day (E)10.5 mouse pharyngeal arch cDNA. From this library, 273 unique clones were sequenced and known proteins binned into functional categories in order to assess enrichment of the library (1). We have now selected 31 novel and poorly characterised genes from this library and present bioinformatic analysis to predict proteins encoded by these genes, and to detect evolutionary conservation. Of these genes 61% (19/31) showed restricted expression in the developing embryo, and a subset of these was chosen for further in silico characterisation as well as experimental determination of subcellular localisation based on transient transfection of predicted full-length coding sequences into mammalian cell lines. Where a human orthologue of these genes was detected, chromosomal localisation was determined relative to known loci for human congenital disease.

An analysis of selected secretion systems of Pseudomonas species

Direct secretion systems which deliver molecules from one cell to another have huge significance in shaping bacterial communities or in determining the outcome of bacterial associations with eukaryotic organisms. This work examines the roles of the Type III Secretion System (T3SS) and the Type VI Secretion System (T6SS) systems of Pseudomonas, a widespread genus including clinical pathogens and biocontrol strains. Bioinformatic analysis of T6SS phylogeny and associated gene content within Pseudomonas identified several T6SS phylogenetic groups, and linked T6SS components VgrG and Hcp encoded outside of T6SS gene loci with their cognate T6SS phylogenetic groups. Remarkably, such “orphan” vgrG and hcp genes were found to occur in diverse, horizontally transferred, operons often containing putative T6SS accessory components and effectors. The prevalence of a widespread superfamily of T6SS lipase effectors (Tle) was assessed in metagenomes from various environments. The abundance of the Tle superfamily and individual families varied between niches, suggesting there is niche specific selection and specialisation of Tle. Experimental work also discovered that P. fluorescens F113 uses the SPI-1 T3SS to avoid amoeboid grazing in mixed populations. This finding may represent a significant aspect of F113 rhizocompetence, and the rhizocompetence of other Rhizobacteria.

Identification of "pathologs" (disease-related genes) from the RIKEN mouse cDNA dataset using human curation plus FACTS, a new biological information extraction system

Background: A major goal in the post-genomic era is to identify and characterise disease susceptibility genes and to apply this knowledge to disease prevention and treatment. Rodents and humans have remarkably similar genomes and share closely related biochemical, physiological and pathological pathways. In this work we utilised the latest information on the mouse transcriptome as revealed by the RIKEN FANTOM2 project to identify novel human disease-related candidate genes. We define a new term patholog to mean a homolog of a human disease-related gene encoding a product ( transcript, anti-sense or protein) potentially relevant to disease. Rather than just focus on Mendelian inheritance, we applied the analysis to all potential pathologs regardless of their inheritance pattern. Results: Bioinformatic analysis and human curation of 60,770 RIKEN full-length mouse cDNA clones produced 2,578 sequences that showed similarity ( 70 - 85% identity) to known human-disease genes. Using a newly developed biological information extraction and annotation tool ( FACTS) in parallel with human expert analysis of 17,051 MEDLINE scientific abstracts we identified 182 novel potential pathologs. Of these, 36 were identified by computational tools only, 49 by human expert analysis only and 97 by both methods. These pathologs were related to neoplastic ( 53%), hereditary ( 24%), immunological ( 5%), cardio-vascular (4%), or other (14%), disorders. Conclusions: Large scale genome projects continue to produce a vast amount of data with potential application to the study of human disease. For this potential to be realised we need intelligent strategies for data categorisation and the ability to link sequence data with relevant literature. This paper demonstrates the power of combining human expert annotation with FACTS, a newly developed bioinformatics tool, to identify novel pathologs from within large-scale mouse transcript datasets.

Diagnóstico molecular de cancros hereditários por sequenciação de nova geração: cancro da mama e cancro colorretal

O cancro da mama e o cancro colorretal constituem duas das principais causas de morte a nível mundial. Entre 5 a 10% destes casos estão associados a variantes germinais/hereditárias em genes de suscetibilidade para cancro. O objetivo deste trabalho consistiu em validar a utilização da sequenciação de nova geração (NGS) para identificar variantes previamente detetadas pelo método de Sanger em diversos genes de suscetibilidade para cancro da mama e colorretal. Foram sequenciadas por NGS 64 amostras de DNA de utentes com suspeita clínica de predisposição hereditária para cancro da mama ou colorretal, utilizando o painel de sequenciação TruSight Cancer e a plataforma MiSeq (Illumina). Estas amostras tinham sido previamente sequenciadas pelo método de Sanger para os genes BRCA1, BRCA2, TP53, APC, MUTYH, MLH1, MSH2 e STK11. A análise bioinformática dos resultados foi realizada com os softwares MiSeq Reporter, VariantStudio, Isaac Enrichment (Illumina) e Integrative Genomics Viewer (Broad Institute). A NGS demonstrou elevada sensibilidade e especificidade analíticas para a deteção de variantes de sequência em 8 genes de suscetibilidade para cancro colorretal e da mama, uma vez que permitiu identificar a totalidade das 412 variantes (93 únicas, incluindo 27 variantes patogénicas) previamente detetadas pelo método de Sanger. A utilização de painéis de sequenciação de genes de predisposição para cancro por NGS vem possibilitar um diagnóstico molecular mais abrangente, rápido e custo-eficiente, relativamente às metodologias convencionais.

Biosynthesis-Assisted Structural Elucidation of the Bartolosides, Chlorinated Aromatic Glycolipids from Cyanobacteria

The isolation of the bartolosides, unprecedented cyanobacterial glycolipids featuring aliphatic chains with chlorine substituents and C-glycosyl moieties, is reported. Their chlorinated dialkylresorcinol (DAR) core presented a major structural-elucidation challenge. To overcome this, we discovered the bartoloside (brt) biosynthetic gene cluster and linked it to the natural products through in vitro characterization of the DAR-forming ketosynthase and aromatase. Bioinformatic analysis also revealed a novel potential halogenase. Knowledge of the bartoloside biosynthesis constrained the DAR core structure by defining key pathway intermediates, ultimately allowing us to determine the full structures of the bartolosides. This work illustrates the power of genomics to enable the use of biosynthetic information for structure elucidation.

Studies on BolA and ribonuclease R: two important factors in the control of bacterial gene expression

Dissertation presented to obtain the Ph.D degree in Biology

Low-frequency drug-resistant HIV-1 and risk of virological failure to first-line NNRTI-based ART: a multicohort European case-control study using centralized ultrasensitive 454 pyrosequencing.

OBJECTIVES: It is still debated if pre-existing minority drug-resistant HIV-1 variants (MVs) affect the virological outcomes of first-line NNRTI-containing ART. METHODS: This Europe-wide case-control study included ART-naive subjects infected with drug-susceptible HIV-1 as revealed by population sequencing, who achieved virological suppression on first-line ART including one NNRTI. Cases experienced virological failure and controls were subjects from the same cohort whose viraemia remained suppressed at a matched time since initiation of ART. Blinded, centralized 454 pyrosequencing with parallel bioinformatic analysis in two laboratories was used to identify MVs in the 1%-25% frequency range. ORs of virological failure according to MV detection were estimated by logistic regression. RESULTS: Two hundred and sixty samples (76 cases and 184 controls), mostly subtype B (73.5%), were used for the analysis. Identical MVs were detected in the two laboratories. 31.6% of cases and 16.8% of controls harboured pre-existing MVs. Detection of at least one MV versus no MVs was associated with an increased risk of virological failure (OR = 2.75, 95% CI = 1.35-5.60, P = 0.005); similar associations were observed for at least one MV versus no NRTI MVs (OR = 2.27, 95% CI = 0.76-6.77, P = 0.140) and at least one MV versus no NNRTI MVs (OR = 2.41, 95% CI = 1.12-5.18, P = 0.024). A dose-effect relationship between virological failure and mutational load was found. CONCLUSIONS: Pre-existing MVs more than double the risk of virological failure to first-line NNRTI-based ART.

The level of ascorbate peroxidase is enhanced in benznidazole-resistant populations of Trypanosoma cruzi and its expression is modulated by stress generated by hydrogen peroxide

Ascorbate peroxidases (APX) are class I heme-containing enzymes that convert hydrogen peroxide into water molecules. The gene encoding APX has been characterized in 11 strains of Trypanosoma cruzi that are sensitive or resistant to benznidazole (BZ). Bioinformatic analysis revealed the presence of two complete copies of the T. cruzi APX (TcAPX) gene in the genome of the parasite, while karyotype analysis showed that the gene was present in the 2.000-kb chromosome of all of the strains analyzed. The sequence of TcAPX exhibited greater levels of similarity to those of orthologous enzymes from Leishmania spp than to APXs from the higher plant Arabidopsis thaliana. Northern blot and real-time reverse transcriptase polymerase chain reaction (RT-PCR) analyses revealed no significant differences in TcAPX mRNA levels between the T. cruzi strains analyzed. On the other hand, Western blots showed that the expression levels of TcAPX protein were, respectively, two and three-fold higher in T. cruzi populations with in vitro induced (17 LER) and in vivo selected (BZR) resistance to BZ, in comparison with their corresponding susceptible counterparts. Moreover, the two BZ-resistant populations exhibited higher tolerances to exogenous hydrogen peroxide than their susceptible counterparts and showed TcAPX levels that increased in a dose-dependent manner following exposure to 100 and 200 µM hydrogen peroxide.

Genomic organization and gene expression in a chromosomal region of Leishmania major.

Little is known about the relation between the genome organization and gene expression in Leishmania. Bioinformatic analysis can be used to predict genes and find homologies with known proteins. A model was proposed, in which genes are organized into large clusters and transcribed from only one strand, in the form of large polycistronic primary transcripts. To verify the validity of this model, we studied gene expression at the transcriptional, post-transcriptional and translational levels in a unique locus of 34kb located on chr27 and represented by cosmid L979. Sequence analysis revealed 115 ORFs on either DNA strand. Using computer programs developed for Leishmania genes, only nine of these ORFs, localized on the same strand, were predicted to code for proteins, some of which show homologies with known proteins. Additionally, one pseudogene, was identified. We verified the biological relevance of these predictions. mRNAs from nine predicted genes and proteins from seven were detected. Nuclear run-on analyses confirmed that the top strand is transcribed by RNA polymerase II and suggested that there is no polymerase entry site. Low levels of transcription were detected in regions of the bottom strand and stable transcripts were identified for four ORFs on this strand not predicted to be protein-coding. In conclusion, the transcriptional organization of the Leishmania genome is complex, raising the possibility that computer predictions may not be comprehensive.

p21 as a transcriptional co-repressor of S-phase and mitotic control genes.

It has been previously described that p21 functions not only as a CDK inhibitor but also as a transcriptional co-repressor in some systems. To investigate the roles of p21 in transcriptional control, we studied the gene expression changes in two human cell systems. Using a human leukemia cell line (K562) with inducible p21 expression and human primary keratinocytes with adenoviral-mediated p21 expression, we carried out microarray-based gene expression profiling. We found that p21 rapidly and strongly repressed the mRNA levels of a number of genes involved in cell cycle and mitosis. One of the most strongly down-regulated genes was CCNE2 (cyclin E2 gene). Mutational analysis in K562 cells showed that the N-terminal region of p21 is required for repression of gene expression of CCNE2 and other genes. Chromatin immunoprecipitation assays indicated that p21 was bound to human CCNE2 and other p21-repressed genes gene in the vicinity of the transcription start site. Moreover, p21 repressed human CCNE2 promoter-luciferase constructs in K562 cells. Bioinformatic analysis revealed that the CDE motif is present in most of the promoters of the p21-regulated genes. Altogether, the results suggest that p21 exerts a repressive effect on a relevant number of genes controlling S phase and mitosis. Thus, p21 activity as inhibitor of cell cycle progression would be mediated not only by the inhibition of CDKs but also by the transcriptional down-regulation of key genes.