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Data-driven models reveal mutant cell behaviors important for myxobacterial aggregation


Igoshin, Oleg et al. (2020), Data-driven models reveal mutant cell behaviors important for myxobacterial aggregation, Dryad, Dataset,


Single mutations frequently alter several aspects of cell behavior but rarely reveal whether a particular statistically significant change is biologically significant. To determine which behavioral changes are most important for multicellular self-organization, we devised a new methodology using Myxococcus xanthus as a model system. During development, myxobacteria coordinate their movement to aggregate into spore-filled fruiting bodies. We investigate how aggregation is restored in two mutants, csgA and pilC, that cannot aggregate unless mixed with wild type (WT) cells. To this end, we use cell tracking to follow  the movement of fluorescently labeled cells in combination with data-driven agent-based modeling. The results indicate that just like WT cells, both mutants bias their movement toward aggregates and reduce motility inside aggregates. However, several aspects of mutant behavior remain uncorrected by WT demonstrating that perfect recreation of WT behavior is unnecessary. In fact, synergies between errant behaviors can make aggregation robust.


Time-lapse movies of aggregation of WT, pilC and csgA mutants. Each file is archived (zip) file of a tiff stacks corresponding to a single experiment.