Optimizing and integrating depletion and precipitation methods for plasma proteomics through data-independent acquisition-mass spectrometry.

The application of plasma proteomics is a reliable approach for the discovery of biomarkers. However, the utilization of mass spectrometry-based proteomics in plasma encounters limitations due to the presence of high-abundant proteins (HAPs) and the vast dynamic range. To address this issue, we conducted an optimization and integration of depletion and precipitation strategies eliminating interference from HAPs. The optimized procedure involved utilizing 40 µL of beads for the removal of 1 µL of plasma, and maintaining a ratio of 1:1:1 between plasma, urea, and trichloroacetic acid for the precipitation of 50 µL of plasma. To facilitate high-throughput processing, experimental procedures were carried out utilizing 96-well plates. The depletion method identified a total of 1510 proteins, whereas the precipitated method yielded a total of 802 proteins. The integration of these methods yielded a total of 1794 proteins, including a wide concentration range spanning over 8 orders of magnitude. Furthermore, these approaches exhibited a commendable level of reproducibility, as indicated by median coefficients of variation of 14.7 % and 21.1 % for protein intensities, respectively. The integrative method was found to be effective in precisely quantifying yeast proteins that were intentionally spiked in plasma at predetermined rations of 5, 2, 0.5, and 0.2 with a high genuine positive recovery with a range of 71 % to 91 % of all yeast proteins. The use of a complementary and finely tuned approach involving depletion and precipitation demonstrates tremendous potential in the field of discovering protein biomarkers from large-scale cohort studies.

The impact of different Saccharomyces cerevisiae strains on microbial composition and quality of Chinese rice wine fermentations.

Chinese rice wine (CRW) is a popular fermented product in China, with complicated microbial composition and flavour compounds. To reveal the effects of different strains of Saccharomyces cerevisiae (N85 and XZ11) on the microbial composition in the process of brewing, metagenomic sequencing approaches were carried out to explore the dynamic changes of bacteria and fungi. Furthermore, the volatile compounds and organic acids in CRW were identified by headspace solid phase microextraction (HS-SPME)/gas chromatography-mass spectrometry (GC-MS) and liquid chromatography-mass spectrometry (LC-MS) at the end of the brewing. Our results indicated that different S. cerevisiae strains could influence microbial compositions and especially affected the growth of Lactobacillus brevis and Pantoea ananatis. The changes in the microbial community structure contributed to the remarkable difference in the content of lactic acid, esters, alcohols, and aldehydes. Moreover, functional network analysis provided insights into the biological correlations between microbial species and metabolic pathways, that is, Lactobacillus genus had negative effects on metabolic activities. This study expands the idea of improving the quality of CRW by controlling the microbiome.