Abstract

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.IMPORTANCE Self-organization into spatial patterns is evident in many multicellular phenomena. Even for the best-studied systems, our ability to dissect the mechanisms driving coordinated cell movement is limited. While genetic approaches can identify mutations perturbing multicellular patterns, the diverse nature of the signaling cues coupled to significant heterogeneity of individual cell behavior impedes our ability to mechanistically connect genes with phenotype. Small differences in the behaviors of mutant strains could be irrelevant or could sometimes lead to large differences in the emergent patterns. Here, we investigate rescue of multicellular aggregation in two mutant strains of Myxococcus xanthus mixed with wild-type cells. The results demonstrate how careful quantification of cell behavior coupled to data-driven modeling can identify specific motility features responsible for cell aggregation and thereby reveal important synergies and compensatory mechanisms. Notably, mutant cells do not need to precisely recreate wild-type behaviors to achieve complete aggregation.

Highlights

  • Single mutations frequently alter several aspects of cell behavior but rarely reveal whether a particular statistically significant change is biologically significant

  • One of the most remarkable features of all types of development is how robust it is in the face of genetic and environmental perturbations, suggesting that backup systems are in place [1]

  • In combination with mathematical modeling, these data sets unambiguously identified individual cell behaviors that are essential for aggregation [14, 15]

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Summary

Introduction

Single mutations frequently alter several aspects of cell behavior but rarely reveal whether a particular statistically significant change is biologically significant. 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 demonstrate how careful quantification of cell behavior coupled to datadriven modeling can identify specific motility features responsible for cell aggregation and thereby reveal important synergies and compensatory mechanisms. In combination with mathematical modeling, these data sets unambiguously identified individual cell behaviors that are essential for aggregation [14, 15] These behaviors include reduced movement inside the aggregate and bias in the directed movement toward the aggregation centers, likely via chemotaxis [15]. The extent of the response is expected to reveal signaling and sensory transduction pathways that are essential for WT development and are defective in the mutants

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