Abstract: Quantitative understanding of microbial growth and how to manipulate it by the means of human induced control is a prerequisite to successfully combat pathogens and develop biotechnology applications. However, the task is complex as growth is the result of genotypic composition of the microbial population and the surrounding environment and their interactions, leading to complex dynamical scenarios, which are presently understood only in a limited way. Here we present a computational approach, that that can be used to convert massively parallel growth curve data, which suffer from various biases, to estimates of genotype dependent growth laws. The approach paves the way towards massively parallel eco-evolutionary experimentation where spatially mediated interactions between growing microbial colonies become a feature of interest rather than a bias that should be corrected.

Speakers:  Ville Mustonen is Professor of Bioinformatics at the University of Helsinki. He works at the Organismal and Evolutionary Biology Research Programme, Department of Computer Science and Institute of Biotechnology. His group develops evolutionary theory and its applications to solve problems such as drug resistance. In particular, they try to understand how predictable evolution is and how and to what extent evolving populations can be controlled. His group further develops bioinformatic algorithms needed to analyse big biological data sets. This work is fundamental science that can lead to applications relevant to human health, for example, in the context of infectious disease and evolution of drug resistance. They work across different scientific disciplines and have a record of successful research collaborations working together with clinicians and experimentalists.

Affiliation: University of Helsinki

Place of Seminar:  Kumpula exactum C323 (in person) & Otaniemi, T5 (streaming)