Journal Articles
Permanent URI for this collectionhttps://mro.massey.ac.nz/handle/10179/7915
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Item Genomic insights into the physiology of Quinella, an iconic uncultured rumen bacterium.(Nature Portfolio, 2022-10-20) Kumar S; Altermann E; Leahy SC; Jauregui R; Jonker A; Henderson G; Kittelmann S; Attwood GT; Kamke J; Waters SM; Patchett ML; Janssen PHQuinella is a genus of iconic rumen bacteria first reported in 1913. There are no cultures of these bacteria, and information on their physiology is scarce and contradictory. Increased abundance of Quinella was previously found in the rumens of some sheep that emit low amounts of methane (CH4) relative to their feed intake, but whether Quinella contributes to low CH4 emissions is not known. Here, we concentrate Quinella cells from sheep rumen contents, extract and sequence DNA, and reconstruct Quinella genomes that are >90% complete with as little as 0.20% contamination. Bioinformatic analyses of the encoded proteins indicate that lactate and propionate formation are major fermentation pathways. The presence of a gene encoding a potential uptake hydrogenase suggests that Quinella might be able to use free hydrogen (H2). None of the inferred metabolic pathways is predicted to produce H2, a major precursor of CH4, which is consistent with the lower CH4 emissions from those sheep with high abundances of this bacterium.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.