Ontology highlight
ABSTRACT:
PROVIDER: PRJNA795815 | ENA |
REPOSITORIES: ENA
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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:Distinct types of dorsal root ganglion sensory neurons may have unique contributions to chronic pain. Identification of primate sensory neuron types is critical for understanding the cellular origin and heritability of chronic pain. However, molecular insights into the primate sensory neurons are missing. Here we classify non-human primate dorsal root ganglion sensory neurons based on their transcriptome and map human pain heritability to neuronal types. First, we identified cell correlates between two major datasets for mouse sensory neuron types. Machine learning exposes an overall cross-species conservation of somatosensory neurons between primate and mouse, although with differences at individual gene level, highlighting the importance of primate data for clinical translation. We map genomic loci associated with chronic pain in human onto primate sensory neuron types to identify the cellular origin of chronic pain. Genome-wide associations for chronic pain converge on two different neuronal types distributed between pain disorders that display different genetic susceptibilities, suggesting both unique and shared mechanisms between different pain conditions.
2021-01-27 | GSE165553 | GEO
Project description:Distinct types of dorsal root ganglion sensory neurons may have unique contributions to chronic pain. Identification of primate sensory neuron types is critical for understanding the cellular origin and heritability of chronic pain. However, molecular insights into the primate sensory neurons are missing. Here we classify non-human primate dorsal root ganglion sensory neurons based on their transcriptome and map human pain heritability to neuronal types. First, we identified cell correlates between two major datasets for mouse sensory neuron types. Machine learning exposes an overall cross-species conservation of somatosensory neurons between primate and mouse, although with differences at individual gene level, highlighting the importance of primate data for clinical translation. We map genomic loci associated with chronic pain in human onto primate sensory neuron types to identify the cellular origin of chronic pain. Genome-wide associations for chronic pain converge on two different neuronal types distributed between pain disorders that display different genetic susceptibilities, suggesting both unique and shared mechanisms between different pain conditions.
2021-01-27 | GSE165566 | GEO
Project description:GNPS-Non-human primate serum metabolomics using 2D GC-EI-ToF-MS
2018-12-18 | MSV000083256 | GNPS
Project description:Biogeography of protists and nematodes in the wild non-human primate gut microbiome
| PRJEB32407 | ENA
Project description:In the event of a large-scale radiation exposure incident, accurate and quick assessment of radiation dose would be critical for triage and medical treatment of large numbers of potentially exposed individuals. Current methods of biodosimetry, such as the dicentric chromosome assay, are time consuming and require sophisticated equipment and highly trained personnel. Therefore, scalable biodosimetry approaches, including gene expression profiles in peripheral blood cells, are being investigated. Due to limited availability of appropriate human samples, however, biodosimetry development has relied heavily on mouse models, which are not directly applicable to human response. Therefore, to explore the feasibility of using non-human primate models to build and test a biodosimetry algorithm for use in humans, we ex vivo-irradiated peripheral blood samples from both humans and rhesus macaques to 0, 2, 5, 6, and 7 Gy, and compared the gene expression profiles 24 hours later using Agilent human microarrays. Among the dose-responsive genes in human and using non-human primate, 52 genes showed highly correlated expression patterns between the species, and were enriched in p53/DNA damage response, apoptosis, and cell cycle-related genes. When these interspecies-correlated genes were used to build biodosimetry models with using non-human primate data, the mean prediction accuracy on non-human primate samples was about 90% within 1 Gy of delivered dose in leave-one-out cross-validation. However, tests on human samples suggested that human gene expression values may need to be adjusted prior to application of the non-human primate model. A ‘multi-gene’ approach utilizing all gene values for cross-species conversion and applying the converted values on the non-human primate biodosimetry models, gave a leave-one-out cross-validation prediction accuracy for human samples highly comparable (up to 94%) to that for non-human primate. Overall, this study demonstrates that a robust NHP biodosimetry model can be built using interspecies-correlated genes, and that, by using multiple regression-based cross-species conversion of expression values, absorbed dose in human samples can be accurately predicted by the non-human primate model.
2017-08-24 | GSE102971 | GEO
Project description:Patterns of microRNA Expression in Non-Human Primate
| PRJNA127979 | ENA
Project description:Burkholderia pseudomallei - Imported non-human primate associated - Texas
| PRJNA782614 | ENA
Project description:Comparison of human and non-human primate gene expression profiles
| PRJNA92273 | ENA