Project description:This study aims to understand the systemic component of psoriasis pathogenesis since psoriasis patients have higher risk of developing diesases beyond skin inflammation. In this study, we collected sigmoidal gut biopsies to profile host transcriptomic changes associated with psoriasis patients and healthy subjects. This exepriment provided transcriptomic dataset of host response and is integrated with fecal metagenomic data and flow cytometry dataset as part of the multi-omic study.
Project description:Lean nonalcoholic fatty liver disease (NAFLD) is increasingly recognized as a distinct clinical phenotype with limited evidence for effective non-pharmacological interventions and unclear mechanistic pathways. Aerobic exercise is recommended for NAFLD management; however, its effects and the gut microbiota–associated mechanisms in lean NAFLD remain incompletely understood. This dataset was generated from a randomized controlled trial (ClinicalTrials.gov identifier: NCT04882644). Participants assigned to the aerobic exercise intervention group provided fecal samples at baseline and after the 3-month intervention. A total of 33 paired fecal samples were included in this dataset. Gut microbiota profiles were generated using shotgun metagenomic sequencing. The dataset includes processed and de-identified species-level relative abundance tables derived from fecal samples collected before and after the intervention. These data were used to characterize exercise-induced alterations in gut microbial composition and interindividual variability in microbiota responses to aerobic exercise in lean NAFLD. The data support integrative analyses with clinical phenotypes and circulating metabolomic profiles to explore gut microbiota–associated mechanisms underlying the metabolic benefits of aerobic exercise.
Project description:In this study we investigated whether gut microbiota profile of Italian healthy volunteers could differ based on their geaographical origin. To this purpose, fecal samples were collected from 31 healthy individuals living in 3 different italian regions (Lombardy, North; Lazio, Center; Apulia, South) and their respective microbiota profiles were analyzed employing 16S metagenomic sequencing method. This study identifies differences in the gut microbiota content and richness among individuals with the same ethnicity coming from three different Italian regions.
Project description:Metagenomic sequencing of mice with different treatments: Mice were randomly divided into donor control group (Donor + MRS), constipation model group (STC + MRS), or a Lactobacillus acidophilus treated group (STC + La): A humanized mouse model was established by intragastric administration of fecal bacterial liquid from healthy donors or STC patients on alternate days, followed by continuous administration of Lactobacillus acidophilus in treatment group. Finally, the feces of each group of mice were collected, and the intestinal microbial communities of the mice were analyzed through metagenomic sequencing. 16S rRNA sequencing of mice before and after the use antibiotics: Before and after treating the mice with antibiotics, the mice's feces were collected for 16s rRNA sequencing respectively.
Project description:This single cell RNA-seq experiment was performed to quantify DLL3 expression in tumor cells in small cell lung cancer patients.Tumors were rapidly dissociated after the surgical procedure using the Miltenyi Biotec Human Tumor Dissociation kit (cat# 130-095-929). Libraries were constructed using the VDJ NextGEM v1.1 10x Genomics Chromium kit according to the manufacturer's instructions. Samples were sequenced on a NextSeq 550 sequencer (Illumina). Corresponding EGA study number: EGAS50000001400, EGA dataset number: EGAD50000002034.
Project description:Single-cell RNA-seq libraries were generated from human PBMCs that were incubated with anti-HER2/CD3 TDB in the presence of KPL-4 cells. This dataset only contains the metadata and processed data. Raw data can be accessed via the EGA accession EGAS00001003734
Project description:In the past decades, the incidence of esophageal adenocarcinoma has increased dramatically in Western populations. Better understanding of disease etiology along with the identification of novel prognostic and predictive biomarkers are urgently needed to improve the dismal survival probabilities. Here, we performed comprehensive RNA (both coding and non-coding) profiling in various samples from 17 patients diagnosed with esophageal adenocarcinoma, high-grade dysplastic or non-dysplastic Barrett’s esophagus. Per patient, a blood plasma sample, and a healthy esophageal and disease tissue sample were included. In total, this comprehensive dataset consists of 102 RNA-seq libraries from 51 samples. The raw data for this study have been deposited to the controlled access archive EGA under submission EGAS00001004939.
Project description:In the past decades, the incidence of esophageal adenocarcinoma has increased dramatically in Western populations. Better understanding of disease etiology along with the identification of novel prognostic and predictive biomarkers are urgently needed to improve the dismal survival probabilities. Here, we performed comprehensive RNA (both coding and non-coding) profiling in various samples from 17 patients diagnosed with esophageal adenocarcinoma, high-grade dysplastic or non-dysplastic Barrett’s esophagus. Per patient, a blood plasma sample, and a healthy esophageal and disease tissue sample were included. In total, this comprehensive dataset consists of 102 RNA-seq libraries from 51 samples. The raw data for this study have been deposited to the controlled access archive EGA under submission EGAS00001004939.