Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR32856700_1.fastq.gz | Fastqsanger.gz | |||
| SRR32856700_2.fastq.gz | Fastqsanger.gz | |||
| SRR32856701_1.fastq.gz | Fastqsanger.gz | |||
| SRR32856701_2.fastq.gz | Fastqsanger.gz | |||
| SRR32856702_1.fastq.gz | Fastqsanger.gz |
Items per page: 5 1 - 5 of 120 |
Similar Datasets
Project description:In this study, we used an -omics approach coupled with high resolution mass spectrometry to characterize twenty F. graminearum isolates collected from five distinct regions across Manitoba, containing both 3-acetyl deoxynivalenol (3ADON) and 15-acetyl deoxynivalenol (15ADON) chemotypes. These data identified regional F. graminearum populations within Manitoba that demonstrate distinct genomic variation and patterns of gene expression, particularly within pathogenicity associated processes. Further, we identified genetic variation and differential expression between isolates showing high and low levels of pathogenicity, allowing for the identification of previously characterized and novel putative pathogenicity factors, as well as regions of genetic diversity between these groups. Lastly, we detected production of 3ANX and/or NX mycotoxins within the majority of our twenty characterized F. graminearum isolates, suggesting the 3ANX chemotype may be more prevalent than previously expected in Canada. These findings highlight the diversity of F. graminearum across Manitoba, and more importantly uncover specific genomic regions and candidate pathogenicity factors influenced by this diversity. These data can ultimately help researchers develop improved disease management strategies against FHB and the dynamic populations of F. graminearum.
2025-03-25 | GSE292521 | GEO
Project description:We explore whether a low-energy diet intervention for Metabolic dysfunction-associated steatohepatitis (MASH) improves liver disease by means of modulating the gut microbiome. 16 individuals were given a low-energy diet (880 kcal, consisting of bars, soups, and shakes) for 12 weeks, followed by a stepped re-introduction to whole for an additional 12 weeks. Stool samples were obtained at 0, 12, and 24 weeks for microbiome analysis. Fecal microbiome were measured using 16S rRNA gene sequencing. Positive control (Zymo DNA standard D6305) and negative control (PBS extraction) were included in the sequencing. We found that low-energy diet improved MASH disease without lasting alterations to the gut microbiome.
2024-12-31 | E-MTAB-14061 | biostudies-arrayexpress
Project description:Pancreatic cancer is the 3rd most prevalent cause of cancer related deaths in United states alone, with over 55000 patients being diagnosed in 2019 alone and nearly as many succumbing to it. Late detection, lack of effective therapy and poor understanding of pancreatic cancer systemically contributes to its poor survival statistics. Obesity and high caloric intake linked co-morbidities like type 2 diabetes (T2D) have been attributed as being risk factors for a number of cancers including pancreatic cancer. Studies on gut microbiome has shown that lifestyle factors as well as diet has a huge effect on the microbial flora of the gut. Further, modulation of gut microbiome has been seen to contribute to effects of intensive insulin therapy in mice on high fat diet. In another study, abnormal gut microbiota was reported to contribute to development of diabetes in Db/Db mice. Recent studies indicate that microbiome and microbial dysbiosis plays a role in not only the onset of disease but also in its outcome. In colorectal cancer, Fusobacterium has been reported to promote therapy resistance. Certain intra-tumoral bacteria have also been shown to elicit chemo-resistance by metabolizing anti-cancerous agents. In pancreatic cancer, studies on altered gut microbiome have been relatively recent. Microbial dysbiosis has been observed to be associated with pancreatic tumor progression. Modulation of microbiome has been shown to affect response to anti-PD1 therapy in this disease as well. However, most of the studies in pancreatic cancer and microbiome have remained focused om immune modulation. In the current study, we observed that in a T2D mouse model, the microbiome changed significantly as the hyperglycemia developed in these animals. Our results further showed that, tumors implanted in the T2D mice responded poorly to Gemcitabine/Paclitaxel (Gem/Pac) standard of care compared to those in the control group. A metabolomic reconstruction of the WGS of the gut microbiota further revealed that an enrichment of bacterial population involved in drug metabolism in the T2D group.
2020-11-30 | E-MTAB-8739 | biostudies-arrayexpress
Project description:Aging is associated with declining immunity and inflammation as well as alterations in the gut microbiome with a decrease of beneficial microbes and increase in pathogenic ones. The aim of this study was to investigate aging associated gut microbiome in relation to immunologic and metabolic profile in a non-human primate (NHP) model. 12 old (age>18 years) and 4 young (age 3-6 years) Rhesus macaques were included in this study. Immune cell subsets were characterized in PBMC by flow cytometry and plasma cytokines levels were determined by bead based multiplex cytokine analysis. Stool samples were collected by ileal loop and investigated for microbiome analysis by shotgun metagenomics. Serum, gut microbial lysate and microbe-free fecal extract were subjected to metabolomic analysis by mass-spectrometry. Our results showed that the old animals exhibited higher inflammatory biomarkers in plasma and lower CD4 T cells with altered distribution of naïve and memory T cell maturation subsets. The gut microbiome in old animals had higher abundance of Archaeal and Proteobacterial species and lower Firmicutes than the young. Significant enrichment of metabolites that contribute to inflammatory and cytotoxic pathways was observed in serum and feces of old animals compared to the young. We conclude that aging NHP undergo immunosenescence and age associated alterations in the gut microbiome that has a distinct metabolic profile.
2022-02-01 | E-MTAB-10160 | biostudies-arrayexpress