Ontology highlight
ABSTRACT:
PROVIDER: PRJNA433977 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Characterization of a metagenomic regulatory sequence library derived from M. xanthus, E. coli, and O. urethralis genomes in strains expressing different RpoD ortholog variants. Targeted DNA and RNA seq used to profile relative DNA and RNA abundances, respectively of each regulatory sequence construct in the library.
2022-06-07 | E-MTAB-9111 | biostudies-arrayexpress
Project description:Metagenomic Detection and Genetic Characterization of Human Sapovirus among Children in Nigeria
| PRJNA1043841 | ENA
Project description:Elucidating the role of gut microbiota in physiological and pathological processes has recently emerged as a key research aim in life sciences. In this respect, metaproteomics (the study of the whole protein complement of a microbial community) can provide a unique contribution by revealing which functions are actually being expressed by specific microbial taxa. However, its wide application to gut microbiota research has been hindered by challenges in data analysis, especially related to the choice of the proper sequence databases for protein identification. Here we present a systematic investigation of variables concerning database construction and annotation, and evaluate their impact on human and mouse gut metaproteomic results. We found that both publicly available and experimental metagenomic databases lead to the identification of unique peptide assortments, suggesting parallel database searches as a mean to gain more complete information. Taxonomic and functional results were revealed to be strongly database-dependent, especially when dealing with mouse samples. As a striking example, in mouse the Firmicutes/Bacteroidetes ratio varied up to 10-fold depending on the database used. Finally, we provide recommendations regarding metagenomic sequence processing aimed at maximizing gut metaproteome characterization, and contribute to identify an optimized pipeline for metaproteomic data analysis.
2016-10-10 | PXD004039 | Pride
Project description:Metaproteomics offers a direct avenue to identify microbial proteins in microbiota, enabling 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 strains information of microbiota samples by directDIA. Then, sample-specific protein sequence database is built based on the strains information using Uniprot protein sequence for subsequent analysis of DIA data using directDIA or hybrid spectral library-based DIA analysis strategies. 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 species in microbiota samples, and that the peptides identified by HAPs-hyblibDIA shared a great common part with the peptides identified using metagenomic sequencing-derived database. At the peptide and species level, our results can serve as a complement to the results obtained by 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 control, highlighting its usability in biomedical research.
2023-07-19 | PXD043890 |
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.
2021-07-26 | E-MTAB-9189 | biostudies-arrayexpress
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.
2021-07-26 | E-MTAB-9191 | biostudies-arrayexpress