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Issue 20, 2019
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Physics-based prediction of biopolymer degradation

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In the natural environment, insoluble biomatter provides a preeminent source of carbon for bacteria. Its degradation by microbial communities thus plays a major role in the global carbon-cycle. The prediction of degradation processes and their sensitivity to changes in environmental conditions can therefore provide critical insights into globally occurring environmental adaptations. To elucidate and quantify this macro-scale phenomenon, we conduct micro-scale experiments that examine the degradation of isolated biopolymer particles and observe highly nonlinear degradation kinetics. Since conventional scaling arguments fail to explain these observations, it is inferred that the coupled influence of both the physical and biochemical processes must be considered. Hence, we develop a theoretical model that accounts for the bio-chemo-mechanically coupled kinetics of polymer degradation, by considering the production of bio-degraders and their ability to both dissociate the material from its external boundaries and to penetrate it to degrade its internal mechanical properties. This change in mechanical properties combined with the intake of solvent or moisture from the environment leads to chemo-mechanically coupled swelling of the material and, in-turn, influences the degradation kinetics. We show that the model quantitatively captures our experimental results and reveals distinct signatures of different bacteria that are independent of the specific experimental conditions (i.e. particle volume and initial concentrations). Finally, after validating our model against the experimental data we extend our predictions for degradation processes across various length and time scales that are inaccessible in a laboratory setting.

Graphical abstract: Physics-based prediction of biopolymer degradation

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Article information

05 Feb 2019
30 Apr 2019
First published
02 May 2019

This article is Open Access

Soft Matter, 2019,15, 4098-4108
Article type

Physics-based prediction of biopolymer degradation

R. Abi-Akl, E. Ledieu, T. N. Enke, O. X. Cordero and T. Cohen, Soft Matter, 2019, 15, 4098
DOI: 10.1039/C9SM00262F

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