Project description:The human colon contains an extensively diverse microbial ecosystem and one of the most numerous communities of immune cells. Studies have highlighted dynamic crosstalk between immune cells and commensals. While studies have demonstrated increasing diversity of microbiota from stomach to stool, whether and how immune cell heterogeneity and microbiota diversity change across the colon is undefined. Furthermore, whether these changes are co-depended in the healthy colon is unknown. Here, tissue samples are collected from caecum, transverse colon, sigmoid colon and mLN of cadaveric donors by the Cambridge Biorepository of Translational Medicine (CBTM). We use single cell RNA sequencing (10X genomics) to assess the dynamics of immune cell populations across the colon and in matching lymph nodes. Associated microbiome 16S sequencing data is available.
Project description:The human colon contains an extensively diverse microbial ecosystem and one of the most numerous communities of immune cells. Studies have highlighted dynamic crosstalk between immune cells and commensals. While studies have demonstrated increasing diversity of microbiota from stomach to stool, whether and how immune cell heterogeneity and microbiota diversity change across the colon is undefined. Furthermore, whether these changes are co-depended in the healthy colon is unknown. Here, tissue samples are collected from caecum, transverse colon, sigmoid colon and mLN of cadaveric donors by the Cambridge Biorepository of Translational Medicine (CBTM). We use single cell RNA sequencing (10X genomics) to assess the dynamics of immune cell populations across the colon and in matching lymph nodes. Associated microbiome 16S sequencing data is available.
Project description:The human colon contains an extensively diverse microbial ecosystem and one of the most numerous communities of immune cells. Studies have highlighted dynamic crosstalk between immune cells and commensals. While studies have demonstrated increasing diversity of microbiota from stomach to stool, whether and how immune cell heterogeneity and microbiota diversity change across the colon is undefined. Furthermore, whether these changes are co-depended in the healthy colon is unknown. Here, tissue samples are collected from caecum, transverse colon, sigmoid colon and mLN of cadaveric donors by the Cambridge Biorepository of Translational Medicine (CBTM). We use single cell RNA sequencing (10X genomics) to assess the dynamics of immune cell populations across the colon and in matching lymph nodes. Associated microbiome 16S sequencing data is available.
Project description:The human colon contains an extensively diverse microbial ecosystem and one of the most numerous communities of immune cells. Studies have highlighted dynamic crosstalk between immune cells and commensals. While studies have demonstrated increasing diversity of microbiota from stomach to stool, whether and how immune cell heterogeneity and microbiota diversity change across the colon is undefined. Furthermore, whether these changes are co-depended in the healthy colon is unknown. Here, tissue samples are collected from caecum, transverse colon, sigmoid colon and mLN of cadaveric donors by the Cambridge Biorepository of Translational Medicine (CBTM). We use single cell RNA sequencing (10X genomics) to assess the dynamics of immune cell populations across the colon and in matching lymph nodes. Associated microbiome 16S sequencing data is available.
Project description:The human colon contains an extensively diverse microbial ecosystem and one of the most numerous communities of immune cells. Studies have highlighted dynamic crosstalk between immune cells and commensals. While studies have demonstrated increasing diversity of microbiota from stomach to stool, whether and how immune cell heterogeneity and microbiota diversity change across the colon is undefined. Furthermore, whether these changes are co-depended in the healthy colon is unknown. Here, tissue samples are collected from caecum, transverse colon, sigmoid colon and mLN of cadaveric donors by the Cambridge Biorepository of Translational Medicine (CBTM). We use single cell RNA sequencing (10X genomics) to assess the dynamics of immune cell populations across the colon and in matching lymph nodes. Associated microbiome 16S sequencing data is available.
Project description:Human saliva microbiota is phylogenetically divergent among host individuals yet their roles in health and disease are poorly appreciated. We employed a microbial functional gene microarray, HuMiChip 1.0, to reconstruct the global functional profiles of human saliva microbiota from ten healthy and ten caries-active adults. Saliva microbiota in the pilot population featured a vast diversity of functional genes. No significant distinction in gene number or diversity indices was observed between healthy and caries-active microbiota. However, co-presence network analysis of functional genes revealed that caries-active microbiota was more divergent in non-core genes than healthy microbiota, despite both groups exhibited a similar degree of conservation at their respective core genes. Furthermore, functional gene structure of saliva microbiota could potentially distinguish caries-active patients from healthy hosts. Microbial functions such as Diaminopimelate epimerase, Prephenate dehydrogenase, Pyruvate-formate lyase and N-acetylmuramoyl-L-alanine amidase were significantly linked to caries. Therefore, saliva microbiota carried disease-associated functional signatures, which could be potentially exploited for caries diagnosis. The DMFT INDEX (Decayed, Missing, Filled [DMF] teeth index used in dental epidemiology) values are provided for each sample We employed a microbial functional gene microarray, HuMiChip 1.0, to reconstruct the global functional profiles of human saliva microbiota from ten healthy and ten caries-active adults.
Project description:The link between the gut microbiota and the human physiological state has been demonstrated in recent years. High gut microbiota diversity has been linked to many beneficial functions necessary or human health, while dysbiosis has been correlated to different pathological states. In this context, the study of the gut microbiota results of high relevance been necessary the development of different techniques capable of characterizing this complex ecosystem. Metaproteomics has been proved useful in the characterization of complex protein samples becoming a suitable tool for the study of these microbial communities. However, due to the complexity of these samples, protein extraction protocols may affect metaproteomics results. In this context, we evaluated stool sample processing (SSP) and microbial cell disruption, assessing the impact of different protocol modifications in the number of peptides and proteins identified. We compared different stool processing conditions and microbial cell disruption methods in terms of protein and peptide identifications and taxonomic profiles.
Project description:Human saliva microbiota is phylogenetically divergent among host individuals yet their roles in health and disease are poorly appreciated. We employed a microbial functional gene microarray, HuMiChip 1.0, to reconstruct the global functional profiles of human saliva microbiota from ten healthy and ten caries-active adults. Saliva microbiota in the pilot population featured a vast diversity of functional genes. No significant distinction in gene number or diversity indices was observed between healthy and caries-active microbiota. However, co-presence network analysis of functional genes revealed that caries-active microbiota was more divergent in non-core genes than healthy microbiota, despite both groups exhibited a similar degree of conservation at their respective core genes. Furthermore, functional gene structure of saliva microbiota could potentially distinguish caries-active patients from healthy hosts. Microbial functions such as Diaminopimelate epimerase, Prephenate dehydrogenase, Pyruvate-formate lyase and N-acetylmuramoyl-L-alanine amidase were significantly linked to caries. Therefore, saliva microbiota carried disease-associated functional signatures, which could be potentially exploited for caries diagnosis. The DMFT INDEX (Decayed, Missing, Filled [DMF] teeth index used in dental epidemiology) values are provided for each sample