Ontology highlight
ABSTRACT:
PROVIDER: PRJNA895230 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR22076800_1.fastq.gz | Fastqsanger.gz | |||
| SRR22076800_2.fastq.gz | Fastqsanger.gz | |||
| SRR22076801_1.fastq.gz | Fastqsanger.gz | |||
| SRR22076801_2.fastq.gz | Fastqsanger.gz | |||
| SRR22076802_1.fastq.gz | Fastqsanger.gz |
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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
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:Genome scale metabolic model of Drosophila gut microbe Acetobacter fabarum
Abstract -
An important goal for many nutrition-based microbiome studies is to identify the metabolic function of microbes in complex microbial communities and their impact on host physiology. This research can be confounded by poorly understood effects of community composition and host diet on the metabolic traits of individual taxa. Here, we investigated these multiway interactions by constructing and analyzing metabolic models comprising every combination of five bacterial members of the Drosophila gut microbiome (from single taxa to the five-member community of Acetobacter and Lactobacillus species) under three nutrient regimes. We show that the metabolic function of Drosophila gut bacteria is dynamic, influenced by community composition, and responsive to dietary modulation. Furthermore, we show that ecological interactions such as competition and mutualism identified from the growth patterns of gut bacteria are underlain by a diversity of metabolic interactions, and show that the bacteria tend to compete for amino acids and B vitamins more frequently than for carbon sources. Our results reveal that, in addition to fermentation products such as acetate, intermediates of the tricarboxylic acid (TCA) cycle, including 2-oxoglutarate and succinate, are produced at high flux and cross-fed between bacterial taxa, suggesting important roles for TCA cycle intermediates in modulating Drosophila gut microbe interactions and the potential to influence host traits. These metabolic models provide specific predictions of the patterns of ecological and metabolic interactions among gut bacteria under different nutrient regimes, with potentially important consequences for overall community metabolic function and nutritional interactions with the host.IMPORTANCE Drosophila is an important model for microbiome research partly because of the low complexity of its mostly culturable gut microbiota. Our current understanding of how Drosophila interacts with its gut microbes and how these interactions influence host traits derives almost entirely from empirical studies that focus on individual microbial taxa or classes of metabolites. These studies have failed to capture fully the complexity of metabolic interactions that occur between host and microbe. To overcome this limitation, we reconstructed and analyzed 31 metabolic models for every combination of the five principal bacterial taxa in the gut microbiome of Drosophila This revealed that metabolic interactions between Drosophila gut bacterial taxa are highly dynamic and influenced by cooccurring bacteria and nutrient availability. Our results generate testable hypotheses about among-microbe ecological interactions in the Drosophila gut and the diversity of metabolites available to influence host traits.
2021-07-01 | MODEL2002040002 | BioModels
Project description:HuMiChip was used to analyze human oral and gut microbiomes, showing significantly different functional gene profiles between oral and gut microbiome. The results were used to demonstarte the usefulness of applying HuMiChip to human microbiome studies.
2014-02-04 | E-GEOD-54290 | biostudies-arrayexpress
Project description:Inter-microbial and host–microbial interactions are thought to be critical for the functioning of the gut microbiome, but few substantive tools are available to measure these interactions. Here, we report a method for unbiased spatial sampling of microbiome-host interactions in the gut at high spatial resolution. This method combines enzymatic in situ polyadenylation of both bacterial and host transcripts with spatial RNA-sequencing. Application of this method revealed the biogeography of the mouse gut microbiome as function of location in the intestine, short-range intermicrobial interaction, local shaping of the microbiome by the host, and tumor-associated changes in the architecture of the host-microbiome interface. This method is compatible with broadly available commercial platforms for spatial RNA-sequencing, and can therefore be readily adopted to broadly study the role of short-range, bidirectional host-microbe interactions in microbiome health and disease.
2026-01-21 | GSE316869 | GEO
Project description:Inter-microbial and host–microbial interactions are thought to be critical for the functioning of the gut microbiome, but few substantive tools are available to measure these interactions. Here, we report a method for unbiased spatial sampling of microbiome-host interactions in the gut at high spatial resolution. This method combines enzymatic in situ polyadenylation of both bacterial and host transcripts with spatial RNA-sequencing. Application of this method revealed the biogeography of the mouse gut microbiome as function of location in the intestine, short-range intermicrobial interaction, local shaping of the microbiome by the host, and tumor-associated changes in the architecture of the host-microbiome interface. This method is compatible with broadly available commercial platforms for spatial RNA-sequencing, and can therefore be readily adopted to broadly study the role of short-range, bidirectional host-microbe interactions in microbiome health and disease.
2026-01-21 | GSE277197 | GEO
Project description:Inter-microbial and host–microbial interactions are thought to be critical for the functioning of the gut microbiome, but few substantive tools are available to measure these interactions. Here, we report a method for unbiased spatial sampling of microbiome-host interactions in the gut at high spatial resolution. This method combines enzymatic in situ polyadenylation of both bacterial and host transcripts with spatial RNA-sequencing. Application of this method revealed the biogeography of the mouse gut microbiome as function of location in the intestine, short-range intermicrobial interaction, local shaping of the microbiome by the host, and tumor-associated changes in the architecture of the host-microbiome interface. This method is compatible with broadly available commercial platforms for spatial RNA-sequencing, and can therefore be readily adopted to broadly study the role of short-range, bidirectional host-microbe interactions in microbiome health and disease.
2026-01-21 | GSE277196 | GEO
Project description:Inter-microbial and host–microbial interactions are thought to be critical for the functioning of the gut microbiome, but few substantive tools are available to measure these interactions. Here, we report a method for unbiased spatial sampling of microbiome-host interactions in the gut at high spatial resolution. This method combines enzymatic in situ polyadenylation of both bacterial and host transcripts with spatial RNA-sequencing. Application of this method revealed the biogeography of the mouse gut microbiome as function of location in the intestine, short-range intermicrobial interaction, local shaping of the microbiome by the host, and tumor-associated changes in the architecture of the host-microbiome interface. This method is compatible with broadly available commercial platforms for spatial RNA-sequencing, and can therefore be readily adopted to broadly study the role of short-range, bidirectional host-microbe interactions in microbiome health and disease.
2026-01-21 | GSE276866 | GEO
Project description:Inter-microbial and host–microbial interactions are thought to be critical for the functioning of the gut microbiome, but few substantive tools are available to measure these interactions. Here, we report a method for unbiased spatial sampling of microbiome-host interactions in the gut at high spatial resolution. This method combines enzymatic in situ polyadenylation of both bacterial and host transcripts with spatial RNA-sequencing. Application of this method revealed the biogeography of the mouse gut microbiome as function of location in the intestine, short-range intermicrobial interaction, local shaping of the microbiome by the host, and tumor-associated changes in the architecture of the host-microbiome interface. This method is compatible with broadly available commercial platforms for spatial RNA-sequencing, and can therefore be readily adopted to broadly study the role of short-range, bidirectional host-microbe interactions in microbiome health and disease.
2026-01-21 | GSE308507 | GEO