Journal Articles
Permanent URI for this collectionhttps://mro.massey.ac.nz/handle/10179/7915
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Item Mathematical modelling supports the existence of a threshold hydrogen concentration and media-dependent yields in the growth of a reductive acetogen.(Springer Nature Limited, 2020-05-01) Smith NW; Shorten PR; Altermann E; Roy NC; McNabb WCThe bacterial production of acetate via reductive acetogenesis along the Wood-Ljungdahl metabolic pathway is an important source of this molecule in several environments, ranging from industrial bioreactors to the human gastrointestinal tract. Here, we contributed to the study of reductive acetogens by considering mathematical modelling techniques for the prediction of bacterial growth and acetate production. We found that the incorporation of a hydrogen uptake concentration threshold into the models improves their predictions and we calculated this threshold as 86.2 mM (95% confidence interval 6.1-132.6 mM). Monod kinetics and first-order kinetics models, with the inclusion of two candidate threshold terms or reversible Michaelis-Menten kinetics, were compared to experimental data and the optimal formulation for predicting both growth and metabolism was found. The models were then used to compare the efficacy of two growth media for acetogens. We found that the recently described general acetogen medium was superior to the DSMZ medium in terms of unbiased estimation of acetogen growth and investigated the contribution of yeast extract concentration to acetate production and bacterial growth in culture. The models and their predictions will be useful to those studying both industrially and environmentally relevant reductive acetogenesis and allow for straightforward adaptation to similar cases with different organisms.Item Hydrogen cross-feeders of the human gastrointestinal tract.(Taylor & Francis Group, 2019-01-01) Smith NW; Shorten PR; Altermann EH; Roy NC; McNabb WCHydrogen plays a key role in many microbial metabolic pathways in the human gastrointestinal tract (GIT) that have an impact on human nutrition, health and wellbeing. Hydrogen is produced by many members of the GIT microbiota, and may be subsequently utilized by cross-feeding microbes for growth and in the production of larger molecules. Hydrogenotrophic microbes fall into three functional groups: sulfate-reducing bacteria, methanogenic archaea and acetogenic bacteria, which can convert hydrogen into hydrogen sulfide, methane and acetate, respectively. Despite different energy yields per molecule of hydrogen used between the functional groups, all three can coexist in the human GIT. The factors affecting the numerical balance of hydrogenotrophs in the GIT remain unconfirmed. There is increasing evidence linking both hydrogen sulfide and methane to GIT diseases such as irritable bowel syndrome, and strategies for the mitigation of such health problems through targeting of hydrogenotrophs constitute an important field for further investigation.Item Examination of hydrogen cross-feeders using a colonic microbiota model(BioMed Central Ltd, 2021-12) Smith NW; Shorten PR; Altermann E; Roy NC; McNabb WCBACKGROUND: 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.