A mathematical Deep-sequenced mRNA transcripts can be combined to predict mass spectrometry derived protein levels in human Th1-activation
Abstract
A large-scale mathematical model description of T-cell differentiation could open up the possibility to perform largs-scale screening of drug effects using computational modelling. For this purpose, we aim to characterize the early time-series dynamics of the phospo-proteomce, splice variants and proteome and use this to form differential equation based models using mass-spectronomy and RNA-seq. We have therefore built preliminary statistical models between the transcription factor regulations and mRNA –protein translation and work to refine these.
Time-resolved genome-wide gene expression analysis of the plant pathogen Xanthomonas oryzae pv. oryzae
Abstract
Plant-pathogen interactions at early stages of infection are important to the fate of interaction. Xanthomonas oryzae pv. oryzae (Xoo) causes bacterial blight, which is a devastating disease in rice. Although in vivo and in vitro systems have been developed to study rice-Xoo interactions, both systems have limitations. We developed a novel in vitro system that can activate pathogenicity-related genes in Xoo using rice leaf extract (RLX) and combined the in vitro assay with RNA-Seq and proteomics to analyze the time-resolved genome-wide gene expression of Xoo. RNA-Seq was performed with samples from seven different time points within 1 h post-RLX treatment and the expression of up- or downregulated genes in RNA-Seq was validated by qRT-PCR. Proteomics data were obtained every 30 min for 2 h. The in vitro system combined with RNA-Seq and proteomics generated a genome-wide time-resolved pathogenic gene expression profile of initial rice-Xoo interactions, demonstrating the expression order and interaction dependency of pathogenic genes. This combined system can be used as a novel tool to study the initial interactions between rice and Xoo during bacterial blight progression.
Graduate School of Pharmaceutical Sciences, Kyoto University, Japan
Title
Peptide Chromatographic Approaches for Illuminating Human Proteome
Abstract
Moderan mass spectrometric instruments allow identifying approximately ten thousand proteins from human cultured cell lines with pre-fractionation at peptide level. Further improvement could be achieved by increasing the resolution both in m/z and retention time in LC/MS separation and/or by adding another dimension such as ion mobility to expand the separation space. We have employed meter-long monolithic silica C18 columns to improve LC separation, Together with high-resolution and accurate-mass (HR/AM) mass spectrometers, ultrahigh resolution LC based on meter-long monolithic silica capillary columns have been employed to unveil the complex human proteomes, resulting in higher sensitivity and specificity in quantitative proteomics. We explored this approach to develop other types of columns such as HILIC, zwitterionic HILIC and anionic HILIC to provide complementary separation selectivity to the C18 silica monolith columns. Using tryptic peptides from human HeLa cell lysate proteins, we identified comparable numbers of peptides and proteins in HILIC with those in RPLC using a C18-modified monolithic silica column when shallow gradients were applied. Since HILIC mode LC/MS shows orthogonal selectivity to RPLC mode LC/MS, it is powerful to use two-dimensional LC modes to increase proteome coverage, although the total measurement time is increased. To solve this issue, we introduced another approach called ‘slice-shot proteomics’, where only a single representative fraction in the first dimension separation is analyzed by the second dimension LC. Using meter-long nanoHILIC/nanoRPLC/MS/MS with silica monolithic formats, we successfully identified more proteins in slice-shot mode than one-shot mode due to the reduction of the sample complexity. In this presentation, I will also show other examples of high resolution chromatography-driven proteomics to target particular groups of peptides of interests to unveil the human proteome.
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