High-Abundance Protein-Guided Hybrid Spectral Library for Data-Independent Acquisition Metaproteomics.

Metaproteomics offers a direct avenue to identify microbial proteins in microbiota, enabling the compositional and functional characterization of microbiota. Due to the complexity and heterogeneity of microbial communities, in-depth and accurate metaproteomics faces tremendous limitations. One challenge in metaproteomics is the construction of a suitable protein sequence database to interpret the highly complex metaproteomic data, especially in the absence of metagenomic sequencing data. Herein, we present a high-abundance protein-guided hybrid spectral library strategy for in-depth data independent acquisition (DIA) metaproteomic analysis (HAPs-hyblibDIA). A dedicated high-abundance protein database of gut microbial species is constructed and used to mine the taxonomic information on microbiota samples. Then, a sample-specific protein sequence database is built based on the taxonomic information using Uniprot protein sequence for subsequent analysis of the DIA data using hybrid spectral library-based DIA analysis. We evaluated the accuracy and sensitivity of the method using synthetic microbial community samples and human gut microbiome samples. It was demonstrated that the strategy can successfully identify taxonomic compositions of microbiota samples and that the peptides identified by HAPs-hyblibDIA overlapped greatly with the peptides identified using a metagenomic sequencing-derived database. At the peptide and species level, our results can serve as a complement to the results obtained using a metagenomic sequencing-derived database. Furthermore, we validated the applicability of the HAPs-hyblibDIA strategy in a cohort of human gut microbiota samples of colorectal cancer patients and controls, highlighting its usability in biomedical research.

Metabolomics and proteomics reveal the inhibitory effect of Lactobacillus crispatus on cervical cancer.

Cervical cancer remains a significant global health issue due to its high morbidity and mortality rates. Recently, Lactobacillus crispatus has been recognized for its crucial role in maintaining cervical health. While some studies have explored the use of L. crispatus to mitigate cervical cancer, the underlying mechanisms remain largely unknown. In this study, we employed non-targeted proteomics and metabolomics to investigate how L. crispatus affects the growth of cervical cancer cells (SiHa) and normal cervical cells (Ect1/E6E7). Our findings indicated that the inhibitory effect of L. crispatus on SiHa cells was associated with various biological processes, notably the ferroptosis pathway. Specifically, L. crispatus was found to regulate the expression of proteins such as HMOX1, SLC39A14, VDAC2, ACSL4, and LPCAT3 by SiHa cells, which are closely related to ferroptosis. Additionally, it activated the tricarboxylic acid (TCA) cycle in SiHa cells, leading to increased levels of reactive oxygen species (ROS) and lipid peroxides (LPO). These results revealed the therapeutic potential of L. crispatus in targeting the ferroptosis pathway for cervical cancer treatment, opening new avenues for research and therapy in cervical cancer.

Data-independent acquisition boosts quantitative metaproteomics for deep characterization of gut microbiota.

Metaproteomics can provide valuable insights into the functions of human gut microbiota (GM), but is challenging due to the extreme complexity and heterogeneity of GM. Data-independent acquisition (DIA) mass spectrometry (MS) has been an emerging quantitative technique in conventional proteomics, but is still at the early stage of development in the field of metaproteomics. Herein, we applied library-free DIA (directDIA)-based metaproteomics and compared the directDIA with other MS-based quantification techniques for metaproteomics on simulated microbial communities and feces samples spiked with bacteria with known ratios, demonstrating the superior performance of directDIA by a comprehensive consideration of proteome coverage in identification as well as accuracy and precision in quantification. We characterized human GM in two cohorts of clinical fecal samples of pancreatic cancer (PC) and mild cognitive impairment (MCI). About 70,000 microbial proteins were quantified in each cohort and annotated to profile the taxonomic and functional characteristics of GM in different diseases. Our work demonstrated the utility of directDIA in quantitative metaproteomics for investigating intestinal microbiota and its related disease pathogenesis.

Metaproteomics profiling of the microbial communities in fermentation starters (Daqu) during multi-round production of Chinese liquor.

Introduction: The special flavor and fragrance of Chinese liquor are closely related to microorganisms in the fermentation starter Daqu. The changes of microbial community can affect the stability of liquor yield and quality. Methods: In this study, we used data-independent acquisition mass spectrometry (DIA-MS) for cohort study of the microbial communities of a total of 42 Daqu samples in six production cycles at different times of a year. The DIA MS data were searched against a protein database constructed by metagenomic sequencing. Results: The microbial composition and its changes across production cycles were revealed. Functional analysis of the differential proteins was carried out and the metabolic pathways related to the differential proteins were explored. These metabolic pathways were related to the saccharification process in liquor fermentation and the synthesis of secondary metabolites to form the unique flavor and aroma in the Chinese liquor. Discussion: We expect that the metaproteome profiling of Daqu from different production cycles will serve as a guide for the control of fermentation process of Chinese liquor in the future.

Quantitative metaproteomics reveals composition and metabolism characteristics of microbial communities in Chinese liquor fermentation starters.

Introduction: Daqu, the Chinese liquor fermentation starter, contains complex microbial communities that are important for the yield, quality, and unique flavor of produced liquor. However, the composition and metabolism of microbial communities in the different types of high-temperature Daqu (i.e., white, yellow, and black Daqu) have not been well understood. Methods: Herein, we used quantitative metaproteomics based on data-independent acquisition (DIA) mass spectrometry to analyze a total of 90 samples of white, yellow, and black Daqu collected in spring, summer, and autumn, revealing the taxonomic and metabolic profiles of different types of Daqu across seasons. Results: Taxonomic composition differences were explored across types of Daqu and seasons, where the under-fermented white Daqu showed the higher microbial diversity and seasonal stability. It was demonstrated that yellow Daqu had higher abundance of saccharifying enzymes for raw material degradation. In addition, considerable seasonal variation of microbial protein abundance was discovered in the over-fermented black Daqu, suggesting elevated carbohydrate and amino acid metabolism in autumn black Daqu. Discussion: We expect that this study will facilitate the understanding of the key microbes and their metabolism in the traditional fermentation process of Chinese liquor production.