Prediction of B-cell Linear Epitopes with a Combination of Support Vector Machine Classification and Amino Acid Propensity Identification

Epitopes are antigenic determinants that are useful because they induce B-cell antibody production and stimulate T-cell activation. Bioinformatics can enable rapid, efficient prediction of potential epitopes. Here, we designed a novel B-cell linear epitope prediction system called LEPS, Linear Epitope Prediction by Propensities and Support Vector Machine, that combined physico-chemical propensity identification and support vector machine (SVM) classification. We tested the LEPS on four datasets: AntiJen, HIV, a newly generated PC, and AHP, a combination of these three datasets. Peptides with globally or locally high physicochemical propensities were first identified as primitive linear epitope (LE) candidates. Then, candidates were classified with the SVM based on the unique features of amino acid segments. This reduced the number of predicted epitopes and enhanced the positive prediction value (PPV). Compared to four other well-known LE prediction systems, the LEPS achieved the highest accuracy (72.52%), specificity (84.22%), PPV (32.07%), and Matthews' correlation coefficient (10.36%)

A bioinformatic analysis of genes involved in stress responses in Arabidopsis thaliana

Hyaloperonospora arabidopsidis is an obligate biotrophic oomycete shown to cause downy mildew in Arabidopsis thaliana. The main focus of this project is examining plant stress response and the strategies employed by H. arabidopsidis to infect Arabidopsis and evade plant stress responses. Two regions of the H. arabidopsidis genome containing genes expressed in planta during infection were bioinformatically annotated. The results indicated the genes were involved in regulatory processes associated with the pathogenicity of H. arabidopsidis but not a direct role in pathogenicity. H. arabidopsidis infects its host by secreting effector proteins into the cytoplasm and apoplastic space of the host. The secretome of H. arabidopsidis was analysed to identify classes of cysteine rich apoplastic effectors. This identified 15 candidate elicitin (ELI) and elicitin-like (ELL) sequences, three Kazal-like serine protease inhibitors and four candidates similar to the protein sequences of Ppats 14 and 24, expressed during infection. A second set of aims was to identify potential signalling networks up activated during plant defence responses to infection by H. arabidopsidis using a new model developed by Beal et al (Beal, Falciani et al. 2005) to eventually engineer transcriptional networks. Unfortunately this failed due to problems with the experiment. However, it was still possible to identify signalling networks from a second microarray time course experimental data set centred on signalling networks up regulated in response to the onset of senescence, as they share overlapping signalling pathways. The modelling methodology was used to model the anthocyanin biosynthesis pathway. The model predicted the presence of AtMYB15 as a positive regulator of anthocyanin biosynthesis along with AtMYB90. Research carried out by Nichola Warner (Warner 2008) suggested that AtMYB90 was not essential for anthocyanin biosynthesis during senescence based on by comparing the phenotype of the MYB90 knock out, IM28, with the wild type (WT) Col-0 using a time course microarray. Models of networks of transcriptional regulation of the anthocyanin biosynthesis pathway for IM28 and WT implicate AtMYB29 as a positive regulator of anthocyanin biosynthesis

Abstracts from the 25th Fungal Genetics Conference

Abstracts from the 25th Fungal Genetics Conferenc

Whole-transciptome analysis of [psi+] budding yeast via cDNA microarrays

Introduction: Prions of yeast present a novel analytical challenge in terms of both initial characterization and in vitro manipulation as models for human disease research. Presently, few robust analysis strategies have been successfully implemented which enable the efficient study of prion behavior in vivo. This study sought to evaluate the utilization of conventional dual-channel cDNA microarrays for the surveillance of transcriptomic regulation patterns by the [PSI+] yeast prion relative to an identical prion deficient yeast variant, [psi-]. Methods: A data analysis and normalization workflow strategy was developed and applied to cDNA array images, yielded quality-regulated expression ratios for a subset of genes exhibiting statistical congruence across multiple experimental repetitions and nested hybridization events. The significant gene list was analyzed using classical analytical approaches including several clustering-based methods and singular value decomposition. To add biological meaning to the differential expression data in hand, functional annotation using the Gene Ontology as well as several pathway-mapping approaches was conducted. Finally, the expression patterns observed were queried against all publicly curated microarray data performed using S. cerevisiae in order to discover similar expression behavior across a vast array of experimental conditions. Results: These data collectively implicate a low-level of overall genomic regulation as a result of the [PSI+] state, where the maximum statistically significant degree of differential expression was less than ±1 Log2(FC) in all cases. Notwithstanding, the [PSI+] differential expression was localized to several specific classes of structural elements and cellular functions, implying under homeostatic conditions significant up or down regulation is likely unnecessary but possible in those specific systems if environmental conditions warranted. As a result of these findings additional work pertaining to this system should include controlled insult to both yeast variants of differing environmental properties to promote a potential [PSI+] regulatory response coupled with co-surveillance of these conditions using transcriptomic and proteomic analysis methodologies

Identificação de complexos proteicos na doença de Alzheimer

Doutoramento em Ciências BiomédicasA Doença de Alzheimer (AD) é a maior doença neurodegenerativa a nível mundial, e a principal causa de demência na população idosa. O processamento da proteína precursora de amilóide (APP) pelas β- e g- secretases origina o peptídeo Aβ, que agrega em oligómeros neurotóxicos e em placas senis. Estes são eventos-chave na patogénese da DA que levam à rutura da neurotransmissão sináptica, morte neuronal e inflamação neuronal do hipocampo e córtex cerebral, causando perda de memória disfunção cognitiva geral. Apesar dos grandes avanços no conhecimento do papel do processamento da APP na DA, a sua função fisiológica ainda não foi totalmente elucidada. Os mapas de interações proteína-proteína (PPI) humanos têm desempenhado um papel importante na investigação biomédica, em particular no estudo de vias de sinalização e de doenças humanas. O método dois-híbrido em levedura (YTH) consiste numa plataforma para a produção rápida de redes de PPI em larga-escala. Neste trabalho foram realizados vários rastreios YTH com o objetivo de identificar proteínas específicas de cérebro humano que interagissem com a APP, ou com o seu domínio intracelular (AICD), tanto o tipo selvagem como com os mutantes Y687F, que mimetizam o estado desfosforilado do resíduo Tyr-687. De facto, a endocitose da APP e a produção de Aβ estão dependentes do estado de fosforilação da Tyr-687. Os rastreios YTH permitiram assim obter de redes proteínas que interagem com a APP, utilizando como “isco” a APP, APPY687F e AICDY687F. Os clones positivos foram isolados e identificados através de sequenciação do cDNA. A maior parte dos clones identificados, 118, correspondia a sequências que codificam para proteínas conhecidas, resultando em 31 proteínas distintas. A análise de proteómica funcional das proteínas identificadas neste estudo e em dois projetos anteriores (AICDY687E, que mimetiza a fosforilação, e AICD tipo selvagem), permitiram avaliar a relevância da fosforilação da Tyr-687. Três clones provenientes do rastreio YTH com a APPY687F foram identificados como um novo transcrito da proteína Fe65, resultante de splicing alternativo, a Fe65E3a (GenBank Accession: EF103274), que codifica para a isoforma p60Fe65. A p60Fe65 está enriquecida no cérebro e os seus níveis aumentam durante a diferenciação neuronal de células PC12, evidenciando o potencial papel que poderá desempenhar na patologia da DA. A RanBP9 é uma proteína nuclear e citoplasmática envolvida em diversas vias de sinalização celulares. Neste trabalho caracterizou-se a nova interação entre a RanBP9 e o AICD, que pode ser regulada pela fosforilação da Tyr-687. Adicionalmente, foi identificada uma nova interação entre a RanBP9 e a acetiltransferase de histonas Tip60. Demonstrou-se ainda que a RanBP9 tem um efeito de regulação inibitório na transcrição mediada por AICD, através da interação com a Tip60, afastando o AICD dos locais de transcrição ativos. O estudo do interactoma da APP/AICD, modelado pela fosforilação da Tyr-687, revela que a APP poderá estar envolvida em novas vias celulares, contribuindo não só para o conhecimento do papel fisiológico da APP, como também auxilia a revelar as vias que levam à agregação de Aβ e neurodegeneração. A potencial relevância deste trabalho relaciona-se com a descoberta de algumas interações proteicas/vias de sinalização que podem que podem ser relevantes para o desenvolvimento de novas estratégias terapêuticas na DA.Alzheimer’s disease (AD) is the most prevalent neurodegenerative disorder worldwide and the leading cause of dementia in the elderly. Processing of amyloid-β precursor protein (APP) by β- and g-secretases produces Aβ, which aggregates into neurotoxic oligomers and senile plaques. These are key events in the pathogenesis of AD that lead to the disruption of synaptic neurotransmission, neuronal cell death, and inflammation in the hippocampus and cerebral cortex, thus causing memory loss and global cognitive dysfunction. Despite advances in understanding the role of APP processing in AD, the normal physiological function of this protein has proven more difficult to elucidate. Human protein-protein interaction (PPI) maps play an increasingly important role in biomedical research and have been shown to be highly valuable in the study of a variety of human diseases and signaling pathways. The yeast twohybrid (YTH) system provides a platform for the rapid generation of large scale PPI networks. Several YTH screens were performed to identify human brainspecific proteins interacting with APP, or with its intracellular domain (AICD), either the wild-type or the Y687F mutant, which mimics the dephosphorylated residue. In fact, APP endocytosis and Aβ generation are dependent upon Tyr- 687 phosphorylation. A human APP network comprised of the protein interactions was assembled through YTH screening, using as baits APP, APPY687F and AICDY687F. Positive clones were isolated and identified by DNA sequencing and database searching. The majority of these clones, 118, matched to a protein coding sequence, yielding 31 different proteins. Functional proteomics analysis of the proteins identified in this study, and two additional screens from previous projects (phospho-mutant AICDY687E and wild-type AICD), allowed to infer the relevance of Tyr-687 phosphorylation. Three clones from YTH with APPY687F were identified as a new splice variant of the APP binding protein Fe65, Fe65E3a (GenBank Accession EF103274), encoding the p60Fe65 isoform. Fe65E3a is expressed preferentially in the brain and the p60Fe65 protein levels increased during PC12 cell differentiation. This novel Fe65 isoform and the regulation of the splicing events leading to its production, may contribute to elucidating neuronal specific roles of Fe65 and its contribution to AD pathology. RanBP9 is an evolutionarily conserved nucleocytoplasmic protein implicated as a scaffolding protein in several signaling pathways. In this work a novel interaction between RanBP9 and AICD, which can be regulated by Tyr-687 phosphorylation, was characterized. Moreover, a novel interaction between RanBP9 and the histone acetyltransferase Tip60 was identified. RanBP9 was demonstrated to have an inhibitory regulatory effect on AICD-mediated transcription, through physical interaction with Tip60, relocating AICD away from transcription factories. Overall, the APP/AICD interactome shaped by the phosphorylation state of Tyr- 687 provided clues to elucidate APP pathways leading to amyloid deposition and neurodegeneration. As such the work here described brings us nearer to unravelling the physiological functions of APP. This in turn is of potential significant relevance in the pathology of AD, and for the design of effective novel therapeutic strategies

Metabolomics Data Processing and Data Analysis—Current Best Practices

Metabolomics data analysis strategies are central to transforming raw metabolomics data files into meaningful biochemical interpretations that answer biological questions or generate novel hypotheses. This book contains a variety of papers from a Special Issue around the theme “Best Practices in Metabolomics Data Analysis”. Reviews and strategies for the whole metabolomics pipeline are included, whereas key areas such as metabolite annotation and identification, compound and spectral databases and repositories, and statistical analysis are highlighted in various papers. Altogether, this book contains valuable information for researchers just starting in their metabolomics career as well as those that are more experienced and look for additional knowledge and best practice to complement key parts of their metabolomics workflows