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Docta Complutense
Conference object . 2021
Data sources: Docta Complutense
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Immersed boundary methods for biofilm spread

Authors: Carpio Rodríguez, Ana María; González Albaladejo, Rafael;

Immersed boundary methods for biofilm spread

Abstract

We propose a computational model to study the growth and spread of bacterial biofilms on surfaces. Bacterial membranes are represented by boundaries immersed in a fluid matrix and subject to interaction forces. Growth, division and death of bacterial cells follow dynamic energy budget rules, in response to variations in environmental concentrations of nutrients, substances released by the cells and toxicants. In this way, we create, enlarge and destroy boundaries, either spherical or rod-shaped. Appropriate forces represent details of the interaction between cells, and the interaction with the environment. Numerical simulations illustrate the evolution of small biofilm seeds. We are able reproduce experimentally observed features such as a tendency of rod-shaped bacteria to align and the formation of inner gaps (due the cell death and reabsorption) which fill with fluid. We calibrated the death parameters to reach a certain aggregate size in the absence of antibiotics, as a result of a balance between dead and newborn cells (as it happens in many tissues). When we add antibiotics small necrotic regions appear at the edges. Resorting to antibiotic cocktails targeting both active cells in the outer regions and dormant cells in the inner core we succeeded in eradicating the biofilm as observed in experiments.

Country
Spain
Keywords

Biomatemáticas, 1206 Análisis Numérico, 2404 Biomatemáticas, Análisis numérico

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green