Maintenance affects the stability of a two-tiered microbial ‘food chain’?

Xu, Aiping; Dolfing, Jan; Curtis, Tom; Montague, G.A.; Martin, E.B.

doi:10.1016/j.jtbi.2011.01.026

Cited by 28 publications

(60 citation statements)

References 18 publications

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“…Although numerical analysis of the steady-states was performed here, it is possible to get explicit quadratic functions of the parameter pair (S ph,in , D) for the steady-state partitions. Using the method described in Xu et al [1], the functions for the partitions are (in non-dimensionless form)…”

Section: A Two-tier Phenol Modelmentioning

confidence: 99%

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Emergent behaviour in a chlorophenol-mineralising three-tiered microbial ‘food web’

Wade

Pattinson

Parker

et al. 2016

Journal of Theoretical Biology

133

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Anaerobic digestion enables the water industry to treat wastewater as a resource for generating energy and recovering valuable by-products. The complexity of the anaerobic digestion process has motivated the development of complex models. However, this complexity makes it intractable to pin-point stability and emergent behaviour. Here, the widely used Anaerobic Digestion Model No. 1 (ADM1) has been reduced to its very backbone, a syntrophic two-tiered microbial ‘food chain’ and a slightly more complex three-tiered microbial ‘food web’, with their stability analysed as a function of the inflowing substrate concentration and dilution rate. Parameterised for phenol and chlorophenol degradation, steady-states were always stable and non-oscillatory. Low input concentrations of chlorophenol were sufficient to maintain chlorophenol- and phenol-degrading populations but resulted in poor conversion and a hydrogen flux that was too low to sustain hydrogenotrophic methanogens. The addition of hydrogen and phenol boosted the populations of all three organisms, resulting in the counterintuitive phenomena that (i) the phenol degraders were stimulated by adding hydrogen, even though hydrogen inhibits phenol degradation, and (ii) the dechlorinators indirectly benefitted from measures that stimulated their hydrogenotrophic competitors; both phenomena hint at emergent behaviour.

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Section: A Two-tier Phenol Modelmentioning

confidence: 99%

“…Steady-state diagram for operational parameters D and S ph,in , in the two-tier phenol model. Green lines between steady-states: explicit functions of the steady-state partitions, after Xu et al[1].…”

mentioning

confidence: 99%

Emergent behaviour in a chlorophenol-mineralising three-tiered microbial ‘food web’

Wade

Pattinson

Parker

et al. 2016

Journal of Theoretical Biology

133

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“…Indeed, in degrading the hydrogen -which is inhibiting microbial growth rate -methanogens allow their coexistence with acid producers: this fragile equilibrium has been thoroughly studied in the past years. In [11], a model of such a syntrophic relationship is studied. As underlined in this paper, for thermodynamic reasons propionate degradation is extremely sensitive to accumulation of hydrogen.…”

Section: Introductionmentioning

confidence: 99%

Steady state analysis of a syntrophic model: the effect of a new input substrate concentration

Daoud

Abdellatif

Sari

et al. 2018

Math. Model. Nat. Phenom.

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In this work, we are interested in a reduced and simplified model of the anaerobic digestion process. We focus on the acetogenesis and hydrogenetrophic methanogenesis phases. The model describes a syntrophic relashionship between two microbial species (the acetogenic bacteria and the hydrogenetrophic methanogenic bacteria) with two input substrates (the fatty acids and the hydrogen) including both decay terms and inhibition of the acetogenic bacteria growth by an excess of hydrogen in the system. The existence and stability analysis of the steady states of the model points out the existence of a new equilibrium point which can be stable according to the operating parameters of the system. By means of operating diagrams, we show that, whatever the region of space considered, there exists only one locally exponentially stable steady state.

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“…Microbial fuel cells are promising tools to tackle those issues, but traditional chemostat studies offer perspective as well, not only for studies on syntrophy but also for studies on other types of interactions like those between acetogenesis and methanogenesis (Lever, 2012;Oren, 2012). Given the long running times needed to obtain comprehensive data sets with chemostat systems, it seems prudent to start such studies with some modelling work to delineate at which dilution rates insightful results can be expected (Xu et al, 2011;Dolfing and Xu, 2012).…”

mentioning

confidence: 99%