Project description:Evaluation of short-read-only, long-read-only, and hybrid assembly approaches on metagenomic samples demonstrating how they affect gene and protein prediction which is relevant for downstream functional analyses. For a human gut microbiome sample, we use complementary metatranscriptomic, and metaproteomic data to evaluate the metagenomic-based protein predictions.
Project description:Next-Generation-Sequencing (NGS) technologies have led to important improvement in the detection of new or unrecognized infective agents, related to infectious diseases. In this context, NGS high-throughput technology can be used to achieve a comprehensive and unbiased sequencing of the nucleic acids present in a clinical sample (i.e. tissues). Metagenomic shotgun sequencing has emerged as powerful high-throughput approaches to analyze and survey microbial composition in the field of infectious diseases. By directly sequencing millions of nucleic acid molecules in a sample and matching the sequences to those available in databases, pathogens of an infectious disease can be inferred. Despite the large amount of metagenomic shotgun data produced, there is a lack of a comprehensive and easy-use pipeline for data analysis that avoid annoying and complicated bioinformatics steps. Here we present HOME-BIO, a modular and exhaustive pipeline for analysis of biological entity estimation, specific designed for shotgun sequenced clinical samples. HOME-BIO analysis provides comprehensive taxonomy classification by querying different source database and carry out main steps in metagenomic investigation. HOME-BIO is a powerful tool in the hand of biologist without computational experience, which are focused on metagenomic analysis. Its easy-to-use intrinsic characteristic allows users to simply import raw sequenced reads file and obtain taxonomy profile of their samples.
Project description:<p>Microorganisms secrete extracellular vesicles (EVs) that transport bioactive molecules such as proteins, metabolites, and enzymes. While their functions are well studied in model microbes, their ecological contributions to natural ecosystems remain largely unexplored.To address this issue, we performed a year-long, integrative study investigating the role of environmental EVs in shaping microbial community assembly in the Xinglinwan Reservoir (XLR). By combining shotgun metagenomics, genome-scale metabolic modelling, and multi-omics of field EVs, we found that EVs mediated metabolite exchanges mainly through carrying signal molecules, amino acids, disaccharides, and CAZymes. These cargoes could be derived from the metabolisms within EVs or directly sourced from their donors, and were closely linked to the carbon cycle and nitrogen metabolism in aquatic environments. In addition, EVs increased the contribution of stochastic processes to the community assembly and improved the stability of the community by maintaining high functional redundancy. Our study demonstrates that EV-mediated metabolic exchanges are prevalent in aquatic communities and pivotal for shaping community assembly and driving biogeochemical cycles. These results clarify the ecological functions of EVs in natural habitats and provide new insights into manipulating microbial communities through controlling environmental EVs.</p>