Faster growth enhances low carbon fuel and chemical production through gas fermentation

Abstract

Gas fermentation offers both fossil carbon-free sustainable production of fuels and chemicals and recycling of gaseous and solid waste using gas-fermenting microbes. Bioprocess development, systems-level analysis of biocatalyst metabolism, and engineering of cell factories are advancing the widespread deployment of the commercialised technology. Acetogens are particularly attractive biocatalysts but effects of the key physiological parameter – specific growth rate (μ) – on acetogen metabolism and the gas fermentation bioprocess have not been established yet. Here, we investigate the (μ-dependent bioprocess performance of the model-acetogen Clostridium autoethanogenum in CO and syngas (CO+CO2+H2) grown chemostat cultures and assess systems-level metabolic responses using gas analysis, metabolomics, transcriptomics, and metabolic modelling. We were able to obtain steady-states up to μ ~2.8 day-1 (~0.12 h-1) and show that faster growth supports both higher yields and productivities for reduced by-products ethanol and 2,3-butanediol. Transcriptomics data revealed differential expression of 1,337 genes with increasing (μ) and suggest that C. autoethanogenum uses transcriptional regulation to a large extent for facilitating faster growth. Metabolic modelling showed significantly increased fluxes for faster growing cells that were, however, not accompanied by gene expression changes in key catabolic pathways for CO and H2 metabolism. Cells thus seem to maintain sufficient 'baseline' gene expression to rapidly respond to CO and H2 availability without delays to kick-start metabolism. Our work advances understanding of transcriptional regulation in acetogens and shows that faster growth of the biocatalyst improves the gas fermentation bioprocess.

RNA-seq sample preparation kits strongly affect transcriptome profiles of a gas-fermenting bacterium

“…specific growth rates; 1 or 2 day -1 ). Both feed gas composition (12) and specific growth rate (13) of the culture have profound effects on the culture phenotype (e.g. gas uptake, product distribution, metabolic fluxes).…”

“…Next, total RNA for each sample was split between the NuGEN, Qiagen, and Zymo kits for rRNA removal and strand-specific RNA-seq library construction according to vendors’ instructions. Finally, the 12 samples (four cultures times three kits) were examined by paired-end 75 bp sequencing on an Illumina MiSeq platform, followed by RNA-seq data analysis using established pipelines (6, 13).…”

“…Preparation of total RNA extracts. Full details of culture sampling, RNA extraction, and purification are reported in previous work (13). Briefly, culture samples were pelleted by centrifugation and treated with RNAlater (76106; Qiagen) before disrupting cells with glass beads using the Precellys® 24 instrument and extracting total RNA using the RNeasy Mini Kit (74104; Qiagen).…”

“…A derivate of Clostridium autoethanogenum DSM 10061 strain – DSM 23693 – deposited in the German Collection of Microorganisms and Cell Cultures (DSMZ) was used in all experiments and stored as a glycerol stock at -80°C. Full details of the cultivation conditions are reported in previous work (13). Shortly, cells were grown autotrophically in bioreactor chemostat continuous cultures under strictly anaerobic conditions at 37°C and pH 5 in chemically defined medium (without yeast extract) either on CO (60% CO and 40% Ar; AS Eesti AGA) or syngas (50% CO, 20% H 2 , 20% CO 2 , and 10% Ar; AS Eesti AGA).…”

“…Raw RNA-seq data of the reference dataset (high biomass concentration samples in GEO accession number GSE90792) (6) was analysed together with the data generated in this work to ensure comparability. Full details of RNA-seq data analysis, including R-scripts, are reported in previous work (13). Shortly, quality of sequencing reads was verified using MultiQC (20) and presence of read duplicates was examined using PicardTools (21).…”