Modelling of surface tension dynamics at the hydrocarbon - water interface during formation of actinobacterial clusters

Автор: Kuyukina M.S., Feoktistova E.V., Osipenko M.A., Ivshina I.B., Nyashin Yu.I.

Журнал: Российский журнал биомеханики @journal-biomech

Статья в выпуске: 1 (83) т.23, 2019 года.

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One of the main factors of environmental pollution is oil and petroleum products, which annual global emissions resulting from multiple accidents and leaks amount tens of thousands of tons. The problem of oil pollution of water resources has acquired a threatening scope due to a growing offshore oil production and transportation of petroleum products by sea and river transport. An effective way to eliminate the oil pollution of water environments is bioremediation using hydrocarbon-oxidizing microorganisms, in particular actinobacteria of the genus Rhodococcus . We studied the adsorption dynamics of Rhodococcus ruber IEGM 231 cells at the interface between bacterial suspension and liquid hydrocarbon ( n -hexadecane or n -dodecane). As a result, mathematical modelling of the initial stage of biofilm formation was performed based on thermodynamic description of cell cluster formation and destruction. The first developed biomechanical model of the surface (interfacial) tension time dependence is phenomenological, it describes the experimental graphs of the corresponding dependence obtained by high-precision tensiometry at different optical densities of bacterial suspensions. The second microlevel model is based on the theory of saturation of the bacterial adsorption layer and the biofilm formation at the hydrocarbon-water interface. In this model, a theoretical explanation of the revealed oscillatory dynamics of interfacial tension is proposed, thus relating to the measuring ring passages through the formed biofilm and the random nature of cell cluster formation-destruction to achieve thermodynamically stable state of the system.

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Rhodococcus, bacterial cells, biofilms, surface (interfacial) tension, deterministic model, probability model

Короткий адрес: https://sciup.org/146282117

IDR: 146282117   |   DOI: 10.15593/RZhBiomeh/2019.1.05

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