Project description:Few studies have investigated host-bacterial interactions at sites of infection in humans using transcriptomics and metabolomics. Haemophilus ducreyi causes cutaneous ulcers in children and the genital ulcer disease chancroid in adults. We developed a human challenge model in which healthy adult volunteers are infected with H. ducreyi on the upper arm until they develop pustules. Here, we characterized host-pathogen interactions in pustules using transcriptomics and metabolomics and examined interactions between the host transcriptome and metabolome using integrated omics. In a previous pilot study, we determined the human and H. ducreyi transcriptomes and the metabolome of pustule and wounded sites of 4 volunteers (B. Griesenauer, et al. mBio 10(3):e01193-19 https://doi.org/10.1128/mBio.01193-19). While we could form provisional transcriptional networks between the host and H. ducreyi, the study was underpowered to integrate the metabolome with the host transcriptome. To better define and integrate the transcriptomes and metabolome, we used samples from both the pilot study (n=4) and new volunteers (n=8) to identify 5,495 human differentially expressed genes (DEGs), 123 H. ducreyi DEGs, 205 differentially abundant positive ions, and 198 differentially abundant negative ions. We identified 42 positively correlated and 29 negatively correlated human-H. ducreyi transcriptome clusters. In addition, we defined human transcriptome-metabolome networks consisting of 9 total clusters, which highlighted changes in fatty acid metabolism and mitigation of oxidative damage. Taken together, the data suggest a mixed pro- and anti-inflammatory environment and rewired central metabolism in the host that provides a hostile, nutrient limited environment for H. ducreyi.
Project description:Few studies have investigated host-bacterial interactions at sites of infection in humans using transcriptomics and metabolomics. Haemophilus ducreyi causes cutaneous ulcers in children and the genital ulcer disease chancroid in adults. We developed a human challenge model in which healthy adult volunteers are infected with H. ducreyi on the upper arm until they develop pustules. Here, we characterized host-pathogen interactions in pustules using transcriptomics and metabolomics and examined interactions between the host transcriptome and metabolome using integrated omics. In a previous pilot study, we determined the human and H. ducreyi transcriptomes and the metabolome of pustule and wounded sites of 4 volunteers (B. Griesenauer, et al. mBio 10(3):e01193-19 https://doi.org/10.1128/mBio.01193-19). While we could form provisional transcriptional networks between the host and H. ducreyi, the study was underpowered to integrate the metabolome with the host transcriptome. To better define and integrate the transcriptomes and metabolome, we used samples from both the pilot study (n=4) and new volunteers (n=8) to identify 5,495 human differentially expressed genes (DEGs), 123 H. ducreyi DEGs, 205 differentially abundant positive ions, and 198 differentially abundant negative ions. We identified 42 positively correlated and 29 negatively correlated human-H. ducreyi transcriptome clusters. In addition, we defined human transcriptome-metabolome networks consisting of 9 total clusters, which highlighted changes in fatty acid metabolism and mitigation of oxidative damage. Taken together, the data suggest a mixed pro- and anti-inflammatory environment and rewired central metabolism in the host that provides a hostile, nutrient limited environment for H. ducreyi.
Project description:Endothelial cell (EC) metabolism is an emerging target for anti-angiogenic therapy in tumor and choroidal neovascularization (CNV), but little is known about individual EC metabolic transcriptomes. Here, by scRNA-sequencing 28,337 murine choroidal ECs (CECs) and sprouting CNV-ECs, we constructed a taxonomy to characterize their heterogeneity. Comparison with murine lung tumor ECs (TECs) revealed congruent marker gene expression by distinct EC phenotypes across tissues and diseases, suggesting similar angiogenic mechanisms. Trajectory inference of CNV-ECs revealed that differentiation of venous to angiogenic ECs was accompanied by metabolic transcriptome plasticity. EC phenotypes displayed metabolic transcriptome heterogeneity. Hypothesizing that conserved genes are more important, we used an integrated analysis, based on congruent transcriptome analysis, CEC-tailored genome scale metabolic modeling, and gene expression meta-analysis in multiple cross-species datasets, followed by functional validation, to identify the top-ranking metabolic targets SQLE and ALDH18A1, involved in EC proliferation and collagen production, respectively, as novel angiogenic targets. The effect of SQLE and ALDH18A1 silencing in ECs was investigated by transcriptomics and proteomics analysis.