Mathematical modelling supports the existence of a threshold hydrogen concentration and media-dependent yields in the growth of a reductive acetogen

Systems biology elucidates the distinctive metabolic niche filled by the human gut microbe Eggerthella lenta

Human gut bacteria perform diverse metabolic functions with consequences for host health. The prevalent and disease-linked Actinobacterium Eggerthella lenta performs several unusual chemical transformations, but it does not metabolize sugars and its core growth strategy remains unclear. To obtain a comprehensive view of the metabolic network of E. lenta, we generated several complementary resources: defined culture media, metabolomics profiles of strain isolates, and a curated genome-scale metabolic reconstruction. Stable isotope-resolved metabolomics revealed that E. lenta uses acetate as a key carbon source while catabolizing arginine to generate ATP, traits which could be recapitulated in silico by our updated metabolic model. We compared these in vitro findings with metabolite shifts observed in E. lenta-colonized gnotobiotic mice, identifying shared signatures across environments and highlighting catabolism of the host signaling metabolite agmatine as an alternative energy pathway. Together, our results elucidate a distinctive metabolic niche filled by E. lenta in the gut ecosystem. Our culture media formulations, atlas of metabolomics data, and genome-scale metabolic reconstructions form a freely available collection of resources to support further study of the biology of this prevalent gut bacterium.

Faster Growth Enhances Low Carbon Fuel and Chemical Production Through Gas Fermentation

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.

Examination of hydrogen cross-feeders using a colonic microbiota model

Background

Hydrogen cross-feeding microbes form a functionally important subset of the human colonic microbiota. The three major hydrogenotrophic functional groups of the colon: sulphate-reducing bacteria (SRB), methanogens and reductive acetogens, have been linked to wide ranging impacts on host physiology, health and wellbeing.

Results

An existing mathematical model for microbial community growth and metabolism was combined with models for each of the three hydrogenotrophic functional groups. The model was further developed for application to the colonic environment via inclusion of responsive pH, host metabolite absorption and the inclusion of host mucins. Predictions of the model, using two existing metabolic parameter sets, were compared to experimental faecal culture datasets. Model accuracy varied between experiments and measured variables and was most successful in predicting the growth of high relative abundance functional groups, such as the Bacteroides, and short chain fatty acid (SCFA) production. Two versions of the colonic model were developed: one representing the colon with sequential compartments and one utilising a continuous spatial representation. When applied to the colonic environment, the model predicted pH dynamics within the ranges measured in vivo and SCFA ratios comparable to those in the literature. The continuous version of the model simulated relative abundances of microbial functional groups comparable to measured values, but predictions were sensitive to the metabolic parameter values used for each functional group. Sulphate availability was found to strongly influence hydrogenotroph activity in the continuous version of the model, correlating positively with SRB and sulphide concentration and negatively with methanogen concentration, but had no effect in the compartmentalised model version.

Conclusions

Although the model predictions compared well to only some experimental measurements, the important features of the colon environment included make it a novel and useful contribution to modelling the colonic microbiota.

Competition for Hydrogen Prevents Coexistence of Human Gastrointestinal Hydrogenotrophs in Continuous Culture

Understanding the metabolic dynamics of the human gastrointestinal tract (GIT) microbiota is of growing importance as research continues to link the microbiome to host health status. Microbial strains that metabolize hydrogen have been associated with a variety of both positive and negative host nutritional and health outcomes, but limited data exists for their competition in the GIT. To enable greater insight into the behaviour of these microbes, a mathematical model was developed for the metabolism and growth of the three major hydrogenotrophic groups: sulphate-reducing bacteria (SRB), methanogens and reductive acetogens. In batch culture simulations with abundant sulphate and hydrogen, the SRB outcompeted the methanogen for hydrogen due to having a half-saturation constant 10⁶ times lower than that of the methanogen. The acetogen, with a high model threshold for hydrogen uptake of around 70 mM, was the least competitive. Under high lactate and zero sulphate conditions, hydrogen exchange between the SRB and the methanogen was the dominant interaction. The methanogen grew at 70% the rate of the SRB, with negligible acetogen growth. In continuous culture simulations, both the SRB and the methanogen were washed out at dilution rates above 0.15 h⁻¹ regardless of substrate availability, whereas the acetogen could survive under abundant hydrogen conditions. Specific combinations of conditions were required for survival of more than one hydrogenotroph in continuous culture, and survival of all three was not possible. The stringency of these requirements and the inability of the model to simulate survival of all three hydrogenotrophs in continuous culture demonstrates that factors outside of those modelled are vital to allow hydrogenotroph coexistence in the GIT.