###Artificial selection of microbial communities: theory and/or experiments
Project ID: 2228bd1027 (You will need this ID for your application)
Research Theme: Physical Sciences
UCL Lead department: Division of Biosciences
Lead Supervisor: Wenying Shou
Project Summary:
Why? Microbial communities often display community functions - biochemical activities that arise from interactions among member species. For example, during sewer treatment, complex organic compounds are first broken down into simpler ones, then fermented to organic acids, which are converted to hydrogen, which is finally turned into methane (an energy source). Each of these steps are catalysed by different types of microbes. However, interactions among microbes are complex and often difficult to decipher, making it challenging to design communities with desired functions. Alternatively, similar to artificial selection for individuals in agriculture, one could repeatedly grow many communities to allow mutations to occur, and then choose those with the highest functions to reproduce by randomly partitioning each into multiple “Newborn” communities for the next cycle. However, previous selection efforts have often encountered difficulties, and theoretical work (including those from our lab, [1,2]) has started to unravel the challenges associated with community selection, as well as means to overcome these challenges.
What? We will investigate how to improve community selection efficacy. Aim 1: Use mathematical modelling to compare different selection strategies. Computer simulations and possibly analytical calculations will be used. Aim 2: Experimentally test model predictions. A liquid-handling robot will be used to select for synthetic yeast communities. To understand mechanisms of community-level evolution, genetic and phenotypic compositions of evolved communities can be characterised. Each Aim on its own can already serve as a PhD project, and the two aims synergise. We are also open to the student formulating his/her own project, as long as the project is roughly aligned with our lab’s interest.
Who? This project can suit a mathematics/physics student interested in biology, or a biology student with or wanting quantitative training.
References: [1] Xie et al., PLoS Biology, 2019 https://journals.plos.org/plosbiology/article/authors?id=10.1371/journal.pbio.3000295
[2] Xie & Shou, Nature Communications, 2021 https://www.nature.com/articles/s41467-021-26647-4