Pacific Symposium on Biocomputing 2023

The Pacific Symposium on Biocomputing (PSB) 2023 is an international, multidisciplinary conference for the presentation and discussion of current research in the theory and application of computational methods in problems of biological significance. Presentations are rigorously peer reviewed and are published in an archival proceedings volume. PSB 2023 will be held on January 3-7, 2023 in Kohala Coast, Hawaii. Tutorials and workshops will be offered prior to the start of the conference.PSB 2023 will bring together top researchers from the US, the Asian Pacific nations, and around the world to exchange research results and address open issues in all aspects of computational biology. It is a forum for the presentation of work in databases, algorithms, interfaces, visualization, modeling, and other computational methods, as applied to biological problems, with emphasis on applications in data-rich areas of molecular biology.The PSB has been designed to be responsive to the need for critical mass in sub-disciplines within biocomputing. For that reason, it is the only meeting whose sessions are defined dynamically each year in response to specific proposals. PSB sessions are organized by leaders of research in biocomputing's 'hot topics.' In this way, the meeting provides an early forum for serious examination of emerging methods and approaches in this rapidly changing field

An integrative polyomics investigation of bovine mastitis

Bovine mastitis, inflammation of the mammary gland, is one of the most costly and prevalent diseases in the dairy industry. It is commonly caused by bacteria, and Streptococcus uberis is one of the most prevalent causative agents. With advancements in omics technologies, the analysis of system-wide changes in the expression of proteins and metabolites in milk has become possible, and such analyses have broadened the knowledge of molecular changes in bovine mastitis. The work presented in this thesis aims to understand the dynamics of molecular changes in bovine mastitis caused by Streptococcus uberis through system-wide profiling and integrated analysis of milk proteins and metabolites. To this end, archived milk samples collected at specific intervals during the course of an experimentally induced model of Streptococcus uberis mastitis were used. Label-free quantitative proteomics and untargeted metabolomics data were generated from the archived milk samples obtained from six cows at six time-points (0, 36, 42, 57, 81 & 312 hours post-challenge). A total of 570 bovine proteins and 690 putative metabolites were quantified. Hierarchical cluster analysis and principal component analysis showed clustering of samples by the stage of infection, with similarities between pre-infection and resolution stages (0 and 312 hours post-challenge), early infection stages (36 and 42 hours post-challenge) and late infection stages (57 and 81 hours post-challenge). The proteomics and metabolomics data were analysed at both individual omics-layer level and combined inter-layer-level. At individual omics layer-level, the temporal changes identified include changes in the expression of proteins in acute-phase response signalling, FXR/RXR activation, complement system, IL-6 and IL-10 pathways, and changes in the expression of metabolites related to amino acid, carbohydrate, lipid and nucleotide metabolisms. The combined inter-layer-level analyses revealed functional relevance of proteins and metabolites enriched in the co-expression modules. For example, possible immunomodulatory role of bile acids via the FXR/RXR activation pathways could be inferred. Similarly, the actin-binding proteins could be linked to endocytic trafficking of signalling receptors. Overall, the work presented in this thesis provides deeper understanding of molecular changes in mastitis. On a secondary note, it also serves as a case study in the use of integrative polyomics analysis methods in the investigation of host-pathogen interactions