Project description:We report the application of single cell RNA sequencing technology for high-throughput profiling of nasal microbiome Staphylococcus epidermidis in human nasal epithelial cells.
Project description:Chronic rhinitis (CR) is a frustrating clinical syndrome in dogs and our understanding of the disease pathogenesis in is limited. Increasingly, host-microbe interactions are considered key drivers of clinical disease in sites of persistent mucosal inflammation such as the nasal and oral cavities. Therefore, we applied next generation sequencing tools to interrogate abnormalities present in the nose of dogs with CR and compared immune and microbiome profiles to those of healthy dogs. Host nasal cell transcriptomes were evaluated by RNA sequencing, while microbial communities were assessed by 16S rRNA sequencing. Correlation analysis was then used to identify significant interactions between nasal cell transcriptomes and the nasal microbiome and how these interactions were altered in animals with CR. Notably, we observed significant downregulation of multiple genes associated with ciliary function in dogs with CR, suggesting a previously undetected role for ciliary dysfunction in this syndrome. We also found significant upregulation of immune genes related to the TNF-a and interferon pathways. The nasal microbiome was also significantly altered in CR dogs, with overrepresentation of several potential pathobionts. Interactome analysis revealed significant correlations between bacteria in the genus Porphyromonas and the upregulated host inflammatory responses in dogs with CR, as well as defective ciliary function which was correlated with Streptococcus abundance. These findings provide new insights into host-microbe interactions in a canine model of CR and indicate the presence of potentially causal relationships between nasal pathobionts and the development of nasal inflammation and ciliary dysfunction.
Project description:Antibiotics are commonly prescribed to treat chronic rhinosinusitis (CRS). However, the effects of antibiotics on the microbiome and secreted proteome remain unknown in regard to CRS.We analyzed the effects of antibiotics on the nasal secreted proteome inthe context of CRS using data-independent acqusition proteomics approach.
Project description:This project aimed to discover the protein-based biomarkers for tick resistance in cattle using cattle serum samples. The cattle were phenotyped into two groups, tick-resistant and susceptible after an artificial tick challenge. Mean tick scores were used to categorise cattle. The SWATH analysis was sued to measure the relative abundance of proteins in skin samples of the two groups at different time points.
Project description:This project aimed to discover the protein-based biomarkers for tick resistance in cattle using cattle skin samples. The cattle were phenotyped into two groups, tick-resistant and susceptible after artificial tick challenge. Mean tick scores were used to categorise cattle. The SWATH analysis was sued to measure the relative abundance of proteins in skin samples of the two groups at different time points.
Project description:This project aimed to characterise the immune response of cattle to buffalo fly infestation using cattle serum samples. The cattle were phenotyped into two groups, high buffalo fly burden and low buffalo fly burden cattle, following exposure to buffalo flies. The SWATH analysis was sued to measure the relative abundance of proteins in serum samples of the two groups at different time points.
Project description:Microbiome sample-material model is a Named Entity Recognition (NER) model that identifies and annotates the material of microbiome samples in texts. This is the final model version used to annotate metagenomics publications in Europe PMC and enrich metagenomics studies in MGnify with sample-material metadata from literature.
For more information, please refer to the following blogs:
http://blog.europepmc.org/2020/11/europe-pmc-publications-metagenomics-annotations.html
https://www.ebi.ac.uk/about/news/service-news/enriched-metadata-fields-mgnify-based-text-mining-associated-publications
