Speaker
Description
Understanding how spatial structure and environmental variability shape microbial colony growth and inter-strain interactions remains a central challenge in systems biology. I will present an integrated experimental–computational framework for the quantitative analysis of Saccharomyces cerevisiae colonies on solid media under both standard and non-standard environmental conditions. Experimentally, we developed a scalable workflow combining automated sample preparation, time-lapse imaging, quantitative image analysis, and fluorescence microscopy to extract high-content measurements of colony expansion and spatial organization. Computationally, we introduced a similarity metric to compare colony growth trajectories and infer competitive dominance in mixed colonies, and validated these predictions against fluorescence-based measurements. W developed and parameterized a quantitative agent-based model to reproduce colony size and cell number across perturbations in humidity, nutrient availability, and inoculation geometry. The combined results reveal complex, environment-dependent interaction networks and demonstrate that initial colony spread has a stronger influence on final colony size and cell number than initial cell number. Together, this work establishes a general modelling and data-analysis framework for linking spatial growth dynamics, environmental heterogeneity, and microbial interactions in structured communities.
Bibliography
Gaizer, T., Juhász, J., Pillér, B., Szakadáti, H., Pongor, C. I., & Csikász-Nagy, A. (2024). Integrative analysis of yeast colony growth. Communications Biology, 7(1), 511.
