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Mutation and Selection in Bacteria: Modelling and Calibration.
journal contribution
posted on 2019-06-25, 11:02 authored by C. D. Bayliss, C. Fallaize, R. Howitt, M. V. TretyakovTemporal evolution of a clonal bacterial population is modelled taking into account reversible mutation and selection mechanisms. For the mutation model, an efficient algorithm is proposed to verify whether experimental data can be explained by this model. The selection-mutation model has unobservable fitness parameters, and, to estimate them, we use an Approximate Bayesian Computation algorithm. The algorithms are illustrated using in vitro data for phase variable genes of Campylobacter jejuni.
Funding
We thank Alexander Lewis for creating the web-app illustrating the algorithm of Sect. 3 and the Wellcome Trust Biomedical Vacation Scholarship 206874/Z/17/Z for supporting Alexander’s work. We also thank Lea Lango-Scholey, Alex Woodacre and Mike Jones for provision of data used in Sects. 3 and 5 prior to publication. This work was supported by the Engineering and Physical Sciences Research Council [grant number EP/L50502X/1] through a PhD studentship to RH; and the Biotechnology and Biological Sciences Research Council [grant number BB/I024712/1] for CDB and MVT.
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Citation
Bulletin of Mathematical Biology, 2019, 81 (3), pp. 639-675Author affiliation
/Organisation/COLLEGE OF LIFE SCIENCES/Biological Sciences/Genetics and Genome BiologyVersion
- VoR (Version of Record)
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Bulletin of Mathematical BiologyPublisher
Springer (part of Springer Nature) for Society for Mathematical Biologyeissn
1522-9602Acceptance date
2018-10-26Copyright date
2018Available date
2019-06-25Publisher DOI
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https://link.springer.com/article/10.1007/s11538-018-0529-9Language
enAdministrator link
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