Talk 1: Microtubules, molecular motors and malaria
Dr Clinton Lau; Biochemistry & Kavli, University of Oxford
The cytoskeleton of the cell is crucial for cell organization and function. The microtubules are one component of this system, extending throughout most eukaryotic cells. They are bound and regulated by a plethora of microtubule-binding proteins, many of which appear conserved from man to malaria. In the Lau Lab, we ask how both conserved and unique microtubule-binding proteins function in the malaria parasite, Plasmodium falciparum. In this talk, I will give an insight into three areas. First, I will talk about my previous work understanding how the microtubule motor dynein is regulated by Lis1. We find Lis1 tethers and activates dynein using cryo-EM and single-molecule TIRF microscopy. Secondly I’ll give an overview of our lab: we are identifying and characterizing microtubule-binding proteins from the Plasmodium parasite. Finally, I’ll discuss usage of AlphaFold2, with tips gathered from AlphaFold-ers that I’ve spoken to.
Talk 2: Chaos in bacterial oxidative stress response
Divya Choudhary; Uphoff Group, Biochemistry, University of Oxford
Genetically-identical bacterial cells commonly display different phenotypes. This phenotypic heterogeneity is well known for stress responses where it is often explained as bet hedging against unpredictable environmental threats. We explore phenotypic heterogeneity in a major stress response of Escherichia coli and find that it has a fundamentally different basis. We characterize the response of cells exposed to hydrogen peroxide (H2O2) stress in a microfluidic device under constant growth conditions. A machine learning model reveals that phenotypic heterogeneity arises from a precise and rapid feedback between each cell and its immediate environment. Moreover, we find that the heterogeneity rests upon cell-cell interaction, whereby cells shield each other from H2O2 via their individual stress responses. Identifying the drivers of heterogeneous dynamics using machine learning, we develop an explicit model of the response of E. coli to oxidative stress. The model incorporates underlying molecular networks, cell growth dynamics and cell-cell interactions. Our modeling results predict that the gene expression fluctuations of individual cells during H2O2 treatment are, in fact, driven by chaos. Although it has been suggested that chaos may play a role in various biological phenomena, it is challenging to disentangle chaos from noise as a source of variability in biological data. The close correspondence between our experiments and model allows us to show that chaos emerges from deterministic feedbacks between cells and their environment. These feedbacks amplify small differences in initial conditions, resulting in diverging stress response dynamics that lead to seemingly random phenotypic variability. Our work suggests that chaotic gene regulation can be employed by cell populations to generate strong and variable responses to changing environments.
