Modelling microbial adaptation

模拟微生物适应

基本信息

批准号：
238389-2011
负责人：
Wahl, Lindi
金额：
$ 3.35万
依托单位：
University of Western Ontario
依托单位国家：
加拿大
项目类别：
Discovery Grants Program - Individual
财政年份：
2018
资助国家：
加拿大
起止时间：
2018-01-01 至 2019-12-31
项目状态：
已结题

来源：
https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=667945
关键词：
Modelling microbial adaptation

项目摘要

Bacteria, viruses and other microbes adapt much more rapidly than humans. I use mathematical models to predict how quickly this microbial evolution unfolds. To do this, we need to predict which types of mutations might be beneficial to the organism, and how large their effects might be; this is called the "distribution of selective effects". Since many mutations, even if they are beneficial, are eventually lost from an evolving population, we would also like to predict whether new beneficial mutations will successfully spread through the microbial population, the "fixation probability". Finally, we would like to understand the "adaptive walk", that is, the process through which several beneficial mutations are acquired in sequence as the microbial population adapts to its environment.****Sophisticated mathematical treatments of each of these questions have been previously described in the literature. In particular, the fixation probability was first estimated, mathematically, nearly 90 years ago by some of the "founding fathers" of population genetics, but has never been tested. Although experimental techniques which could test these concepts have finally become available, recent work has demonstrated that our mathematical predictions must be precisely tailored to the organism and to the experimental protocol. Thus, quantitative experimental tests of these foundational quantities will only be possible after new mathematical predictions, specific for microbial populations, are developed. This is my research program.****The significance of understanding microbial adaptation is clear. The techniques developed here will be critical in predicting the rate of loss of microbial biodiversity, and the rate at which the microbiome will adapt to climate change. From a public health perspective, this work will also allow us to better predict the rate at which new pathogenic microbes will emerge, and the emergence of drug-resistance.****************

细菌、病毒和其他微生物的适应速度比人类快得多。我使用数学模型来预测这种微生物进化的速度。为此，我们需要预测哪些类型的突变可能对生物体有益，以及它们的影响有多大；这称为“选择性效应的分布”。由于许多突变，即使它们是有益的，最终也会从不断进化的种群中消失，因此我们还想预测新的有益突变是否会成功地在微生物种群中传播，即“固定概率”。最后，我们想了解“适应性行走”，即当微生物种群适应其环境时依次获得几种有益突变的过程。****对这些问题中的每一个都进行了复杂的数学处理。先前在文献中描述过。特别是，近 90 年前，一些群体遗传学的“奠基人”首次以数学方式估计了固定概率，但从未经过测试。尽管可以测试这些概念的实验技术终于可用，但最近的工作表明，我们的数学预测必须根据生物体和实验方案精确定制。因此，只有在开发出针对微生物种群的新数学预测后，才能对这些基本量进行定量实验测试。这是我的研究计划。****了解微生物适应的意义是显而易见的。这里开发的技术对于预测微生物生物多样性的丧失速度以及微生物组适应气候变化的速度至关重要。从公共卫生的角度来看，这项工作还将使我们能够更好地预测新病原微生物出现的速度以及耐药性的出现。****************