4.1 Article

A deterministic oscillatory model of microtubule growth and shrinkage for differential actions of short chain fatty acids

Journal

MOLECULAR BIOSYSTEMS
Volume 12, Issue 1, Pages 93-101

Publisher

ROYAL SOC CHEMISTRY
DOI: 10.1039/c5mb00211g

Keywords

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Funding

  1. EPSRC [EP/E036252/1]
  2. Engineering and Physical Sciences Research Council [EP/E036252/1] Funding Source: researchfish

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Short chain fatty acids (SCFA), principally acetate, propionate, butyrate and valerate, are produced in pharmacologically relevant concentrations by the gut microbiome. Investigations indicate that they exert beneficial effects on colon epithelia. There is increasing interest in whether different SCFAs have distinct functions which may be exploited for prevention or treatment of colonic diseases including colorectal cancer (CRC), inflammatory bowel disease and obesity. Based on experimental evidence, we hypothesised that odd-chain SCFAs may possess anti-mitotic capabilities in colon cancer cells by disrupting microtubule (MT) structural integrity via dysregulation of beta-tubulin isotypes. MT dynamic instability is an essential characteristic of MT cellular activity. We report a minimal deterministic model that takes a novel approach to explore the hypothesised pathway by triggering spontaneous oscillations to represent MT dynamic behaviour. The dynamicity parameters in silico were compared to those reported in vitro. Simulations of untreated and butyrate (even-chain length) treated cells reflected MT behaviour in interphase or untreated control cells. The propionate and valerate (odd-chain length) simulations displayed increased catastrophe frequencies and longer periods of MT-fibre shrinkage. Their enhanced dynamicity was dissimilar to that observed in mitotic cells, but parallel to that induced by MT-destabilisation treatments. Antimicrotubule drugs act through upward or downward modulation of MT dynamic instability. Our computational modelling suggests that metabolic engineering of the microbiome may facilitate managing CRC risk by predicting outcomes of SCFA treatments in combination with AMDs.

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