Project description:Methanotrophs, which help regulate atmospheric levels of methane, are active in diverse natural and man-made environments. This range of habitats and the feast-famine cycles seen by many environmental methanotrophs suggest that methanotrophs dynamically mediate rates of methane oxidation. Global methane budgets require ways to account for this variability in time and space. Functional gene biomarker transcripts are increasingly being studied to inform the dynamics of diverse biogeochemical cycles. Previously, per-cell transcript levels of the methane oxidation biomarker, pmoA, were found to vary quantitatively with respect to methane oxidation rates in model aerobic methanotroph, Methylosinus trichosporium OB3b. In the present study, these trends were explored for two additional aerobic methanotroph pure cultures, Methylocystis parvus OBBP and Methylomicrobium album BG8. At steady-state conditions, per cell pmoA mRNA transcript levels strongly correlated with per cell methane oxidation across the three methanotrophs across many orders of magnitude of activity (R2 = 0.91). Additionally, genome-wide expression data (RNA-seq) were used to explore transcriptomic responses of steady state M. album BG8 cultures to short-term CH4 and O2 limitation. These limitations induced regulation of genes involved in central carbon metabolism (including carbon storage), cell motility, and stress response.
Project description:Methanogenesis allows methanogenic archaea (methanogens) to generate cellular energy for their growth while producing methane. Hydrogenotrophic methanogens thrive on carbon dioxide and molecular hydrogen as sole carbon and energy sources. Thermophilic and hydrogenotrophic Methanothermobacter spp. have been recognized as robust biocatalysts for a circular carbon economy and are now applied in power-to-gas technology. Here, we generated the first manually curated genome-scale metabolic reconstruction for three Methanothermobacter spp.. We investigated differences in growth performance and gas consumption/production of three wild-type strains and one genetically engineered strain in two independent quadruplicate chemostat bioreactor experiments: 1) with molecular hydrogen and carbon dioxide; and 2) with sodium formate. In the first experiment, we found the highest methane production rate for Methanothermobacter thermautotrophicus ΔH, while Methanothermobacter marburgensis Marburg reached the highest biomass growth rate. We collected statistically reliable transcriptomics and proteomics data sets from these steady-state bioreactors, which we integrated within our genome-scale metabolic models. The implementation of an pan-model that contains combined reactions from all three microbes allowed us to perform an interspecies comparison of the complete omics data set. While the observed differences in the growth behavior cannot be fully explained, the comparison enabled us to identify crucial differences in growth-related pathways, such as formate anabolism. In the second experiment, we found stable growth with a M. thermautotrophicus ΔH plasmid-carrying strain on formate with similar performance parameters compared to wild-type Methanothermobacter thermautotrophicus Z-245. The results of the two studies demonstrate the advantages of an integrative approach using fermentation and omics data with genome-scale modeling for the investigation of lesser studied metabolisms, and the biotechnological potential of Methanothermobacter spp. as production platform hosts.
Project description:GAS strains were grown in THY broth to early exponential phase and RNA extracted. cDNA was generated and the expression profiles were determined using the RMLgenechip. Comparisons between the sample groups allow the identification of genes differentially expressed between strains. This experiment compared pre- and post- mouse passaged GAS strains. Keywords: GAS comparison
Project description:Single-cell transcriptome-based strategy to determine the evolutionary trajectories of longitudinal tumor biopsies from liver cancer patients by measuring cellular lineage and ecology. Our study provides a framework for monitoring tumor evolution in response to therapeutic intervention.