Ontology highlight
ABSTRACT:
PROVIDER: PRJNA1074399 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Shotgun metagenomic sequencing data of a total 2,338 fecal DNA samples from adults of the Pinggu cohort.
| EGAD00001007064 | EGA
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
Project description:We applied metagenomic shotgun sequencing to investigate the effects of ZEA exposure on the change of mouse gut microbiota composition and function.
2019-11-09 | GSE140149 | GEO
Project description:The TransplantLines Gut Microbiome study includes raw data generated by shotgun metagenomic sequencing of fecal samples of solid organ transplant recipients and basic phenotypes (age and sex, BMI).
| EGAD00001008907 | EGA
Project description:The role of gut microbiome dysbiosis in the pathogenesis of psoriasis has gained increasing attention in recent years. Secukinumab, targeting interleukin (IL)-17, has a promising efficacy in psoriasis treatment. However, it remains unclear the gut microbiota alteration and related functional changes caused by successful secukinumab therapy in psoriatic patients. In our study, we compared fecal microbiome profile between psoriatic patients after secukinumab successful treatment (AT) and the other two groups, psoriatic patients without therapy (BT) and healthy people (H), respectively by using next-generation sequencing targeting 16S ribosomal RNA. Then, shotgun metagenomic sequencing was firstly used to characterize bacterial gut microbial communities and related functional change in AT group. We found that the diversity and structure of the microbial community in AT group were significantly changed compared to that of BT group and H group. AT group showed a microbiota profile characterized by increased proportions of the phylum Firmicute, families Ruminococcaceae, and a reduction in the phylum Bacteroidota (elevated F/B ratio). To detect functional alteration, we discovered that secukinumab treatment may construct a more stable homeostasis of gut microbiome with functional alteration. There were different KEGG pathways such as downregulated cardiovascular diseases pathway and upregulated infectious diseases in AT group. By metagenomic analysis, metabolic functional pathway was changed after secukinumab therapy. It seems that gut microbiota investigation during biologic drug treatment is useful for predicting the efficacy and risks of drug treatment in disease.
2023-08-07 | GSE239720 | GEO
Project description:The role of gut microbiome dysbiosis in the pathogenesis of psoriasis has gained increasing attention in recent years. Secukinumab, targeting interleukin (IL)-17, has a promising efficacy in psoriasis treatment. However, it remains unclear the gut microbiota alteration and related functional changes caused by successful secukinumab therapy in psoriatic patients. In our study, we compared fecal microbiome profile between psoriatic patients after secukinumab successful treatment (AT) and the other two groups, psoriatic patients without therapy (BT) and healthy people (H), respectively by using next-generation sequencing targeting 16S ribosomal RNA. Then, shotgun metagenomic sequencing was firstly used to characterize bacterial gut microbial communities and related functional change in AT group. We found that the diversity and structure of the microbial community in AT group were significantly changed compared to that of BT group and H group. AT group showed a microbiota profile characterized by increased proportions of the phylum Firmicute, families Ruminococcaceae, and a reduction in the phylum Bacteroidota (elevated F/B ratio). To detect functional alteration, we discovered that secukinumab treatment may construct a more stable homeostasis of gut microbiome with functional alteration. There were different KEGG pathways such as downregulated cardiovascular diseases pathway and upregulated infectious diseases in AT group. By metagenomic analysis, metabolic functional pathway was changed after secukinumab therapy. It seems that gut microbiota investigation during biologic drug treatment is useful for predicting the efficacy and risks of drug treatment in disease.
2023-08-07 | GSE239719 | GEO
Project description:Dysbiotic configurations of the human gut microbiota have been linked with colorectal cancer (CRC). Human small non-coding RNAs are also implicated in CRC and recent findings suggest that their release in the gut lumen contributes to shape the gut microbiota. Bacterial small RNAs (bsRNAs) may also play a role in carcinogenesis but their role is less explored. Here, we performed small RNA and shotgun sequencing on 80 stool specimens of patients with CRC, or adenomas, and healthy subjects collected in a cross-sectional study to evaluate their combined use as a predictive tool for disease detection. We reported a considerable overlap and correlation between metagenomic and bsRNA quantitative taxonomic profiles obtained from the two approaches. Furthermore, we identified a combined predictive signature composed by 32 features from human and microbial small RNAs and DNA-based microbiome able to accurately classify CRC from healthy and adenoma samples (AUC= 0.87). In summary we reported evidence that host-microbiome dysbiosis in CRC can be observed also by altered small RNA stool profiles. Integrated analyses of the microbiome and small RNAs in the human stool may provide insights for designing more accurate tools for diagnostic purposes.
2019-08-30 | GSE132236 | GEO