BEGIN:VCALENDAR VERSION:2.0 PRODID:researchseminars.org CALSCALE:GREGORIAN X-WR-CALNAME:researchseminars.org BEGIN:VEVENT SUMMARY:Jakob Ruess (INRIA) DTSTART:20250508T153000Z DTEND:20250508T160000Z DTSTAMP:20260421T124344Z UID:MoRN/123 DESCRIPTION:Title: F rom single cells to microbial consortia and back: stochastic chemical kine tics coupled to population dynamics\nby Jakob Ruess (INRIA) as part of Seminar on the Mathematics of Reaction Networks\n\n\nAbstract\nAt the sin gle-cell level\, biochemical processes are inherently stochastic. Such pro cesses are typically studied using models based on stochastic chemical kin etics\, governed by a chemical master equation (CME). The CME describes th e time evolution of the probability distribution over system states and ha s been a tremendously helpful tool in shedding light on the functioning of cellular processes. However\, single cells are not living in isolation bu t are part of a growing population or community. In such contexts\, stocha sticity at the single-cell scale leads to population heterogeneity and cel ls may be subject to population processes\, such as selection\, that drive the population distribution away from the probability distribution of the single-cell process.\n\nHere\, I will introduce a multi-scale modeling fr amework that allows one to capture coupled stochastic single-cell and popu lation process. I will show that the expected population distribution of s uch multi-scale models can be calculated by solving a modified version of the CME that is of the same dimensionality as the standard CME. I will the n show how such models can be used to explain experimental data on plasmid copy number fluctuations and population growth in media that selects agai nst cells that have lost the plasmid. Finally\, I will present an optogene tic recombination system that allows one to partition yeast populations in to different cell types via external application of blue light to cells an d show how our modeling framework can be used to predict and control emerg ing dynamics of the population composition in response to time-varying lig ht stimuli.\n LOCATION:https://researchseminars.org/talk/MoRN/123/ END:VEVENT END:VCALENDAR