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

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.