Artificial selection of microbial communities: theory and/or experiments

Project ID: 2228cd1330 (You will need this ID for your application)

Under Offer

UCL Lead department: Division of Biosciences

Project Summary:

Why? Microbial communities often display community functions - biochemical activities that arise from interactions among member species. For example, one species can transform cellulose – an agricultural waste – into nutrients that can be used by a second species to produce a drug valuable to us.

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 in agriculture (e.g. crop breeding), 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 offspring communities for the next cycle. However, previous selection efforts have largely been unsuccessful, 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 [3].

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 can be used to select for synthetic microbial communities. To understand mechanisms of community-level evolution, evolved communities will be characterised.

Each Aim on its own can already serve as a PhD project. 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. Our lab is diverse, with researchers from biology, physics, and mathematics.

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 [3] Thomas, Rowland-Chandler, & Shou, Current Opinions in Microbiology, 2023. Accepted.