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:Fungal secondary metabolites represent a rich and largely untapped source for bioactive molecules, including peptides with substantial structural diversity and pharmacological potential. As methods proceed to take a deep dive into fungal genomes, complimentary methods to identify bioactive components are required to keep pace with the expanding fungal repertoire. We developed PepSAVI-MS to expedite the search for natural product bioactive peptides and herein demonstrate proof-of-principle applicability of the pipeline for the discovery of bioactive peptides from fungal secretomes via identification of the antifungal killer toxin KP4 from Ustilago maydis P4. This work opens the door to investigating microbial secretomes with a new lens, and could have broad applications across human health, agriculture, and food safety.
Project description:The availability of organic carbon represents a major bottleneck for the development of soil microbial communities and the regulation of microbially-mediated ecosystem processes. However, there is still a lack of knowledge on how the lifestyle and population abundances are physiologically regulated by the availability of energy and organic carbon in soil ecosystems. To date, functional insights into the lifestyles of microbial populations have been limited by the lack of straightforward approaches to the tracking of the active microbial populations. Here, by the use of an comprehensiv metaproteomics and genomics, we reveal that C-availability modulates the lifestyles of bacterial and fungal populations in drylands and determines the compartmentalization of functional niches. This study highlights that the active diversity (evaluated by metaproteomics) but not the diversity of the whole microbial community (estimated by genome profiling) is modulated by the availability of carbon and is connected to the ecosystem functionality in drylands.
Project description:To effectively monitor microbial populations in acidic environments and bioleaching systems, a comprehensive 50-mer-based oligonucleotide microarray was developed based on most of the known genes associated with the acidophiles. This array contained 1,072 probes in which there were 571 related to 16S rRNA and 501 related to functional genes. Acid mine drainage (AMD) presents numerous problems to the aquatic life and surrounding ecosystems. However, little is known about the geographic distribution, diversity, composition, structure and function of AMD microbial communities. In this study, we analyzed the geographic distribution of AMD microbial communities from twenty sites using restriction fragment length polymorphism (RFLP) analysis of 16S rRNA genes, and the results showed that AMD microbial communities were geographically distributed and had high variations among different sites. Then an AMD-specific microarray was used to further analyze nine AMD microbial communities, and showed that those nine AMD microbial communities had high variations measured by the number of detected genes, overlapping genes between samples, unique genes, and diversity indices. Statistical analyses indicated that the concentrations of Fe, S, Ca, Mg, Zn, Cu and pH had strong impacts on both phylogenetic and functional diversity, composition, and structure of AMD microbial communities. This study provides insights into our understanding of the geographic distribution, diversity, composition, structure and functional potential of AMD microbial communities and key environmental factors shaping them. This study investigated the geographic distribution of Acid Mine Drainages microbial communities using a 16S rRNA gene-based RFLP method and the diversity, composition and structure of AMD microbial communities phylogenetically and functionally using an AMD-specific microarray which contained 1,072 probes ( 571 related to 16S rRNA and 501 related to functional genes). The functional genes in the microarray were involved in carbon metabolism (158), nitrogen metabolism (72), sulfur metabolism (39), iron metabolism (68), DNA replication and repair (97), metal-resistance (27), membrane-relate gene (16), transposon (13) and IST sequence (11).