Data-Driven Models Reveal Mutant Cell Behaviors Important for Myxobacterial Aggregation

Cell density, alignment, and orientation correlate with C-signal-dependent gene expression during Myxococcus xanthus development

Starving Myxococcus xanthus bacteria use short-range C-signaling to coordinate their movements and construct multicellular mounds, which mature into fruiting bodies as rods differentiate into spherical spores. Differentiation requires efficient C-signaling to drive the expression of developmental genes, but how the arrangement of cells within nascent fruiting bodies (NFBs) affects C-signaling is not fully understood. Here, we used confocal microscopy and cell segmentation to visualize and quantify the arrangement, morphology, and gene expression of cells near the bottom of NFBs at much higher resolution than previously achieved. We discovered that "transitioning cells" (TCs), intermediate in morphology between rods and spores, comprised 10 to 15% of the total population. Spores appeared midway between the center and the edge of NFBs early in their development and near the center as maturation progressed. The developmental pattern, as well as C-signal-dependent gene expression in TCs and spores, were correlated with cell density, the alignment of neighboring rods, and the tangential orientation of rods early in the development of NFBs. These dynamic radial patterns support a model in which the arrangement of cells within the NFBs affects C-signaling efficiency to regulate precisely the expression of developmental genes and cellular differentiation in space and time. Developmental patterns in other bacterial biofilms may likewise rely on short-range signaling to communicate multiple aspects of cellular arrangement, analogous to juxtacrine and paracrine signaling during animal development.

Differential response to prey quorum signals indicates predatory specialization of myxobacteria and ability to predate Pseudomonas aeruginosa

Multiomic analysis of transcriptional and metabolic responses from the predatory myxobacteria Myxococcus xanthus and Cystobacter ferrugineus exposed to prey signalling molecules of the acylhomoserine lactone and quinolone quorum signalling classes provided insight into predatory specialization. Acylhomoserine lactone quorum signals elicited a general response from both myxobacteria. We suggest that this is likely due to the generalist predator lifestyles of myxobacteria and ubiquity of acylhomoserine lactone signals. We also provide data that indicates the core homoserine lactone moiety included in all acylhomoserine lactone scaffolds to be sufficient to induce this general response. Comparing both myxobacteria, unique transcriptional and metabolic responses were observed from Cystobacter ferrugineus exposed to the quinolone signal 2‐heptylquinolin‐4(1H)‐one (HHQ) natively produced by Pseudomonas aeruginosa. We suggest that this unique response and ability to metabolize quinolone signals contribute to the superior predation of P. aeruginosa observed from C. ferrugineus. These results further demonstrate myxobacterial eavesdropping on prey signalling molecules and provide insight into how responses to exogenous signals might correlate with prey range of myxobacteria.

Quantification of Myxococcus xanthus Aggregation and Rippling Behaviors: Deep-Learning Transformation of Phase-Contrast into Fluorescence Microscopy Images

Myxococcus xanthus bacteria are a model system for understanding pattern formation and collective cell behaviors. When starving, cells aggregate into fruiting bodies to form metabolically inert spores. During predation, cells self-organize into traveling cell-density waves termed ripples. Both phase-contrast and fluorescence microscopy are used to observe these patterns but each has its limitations. Phase-contrast images have higher contrast, but the resulting image intensities lose their correlation with cell density. The intensities of fluorescence microscopy images, on the other hand, are well-correlated with cell density, enabling better segmentation of aggregates and better visualization of streaming patterns in between aggregates; however, fluorescence microscopy requires the engineering of cells to express fluorescent proteins and can be phototoxic to cells. To combine the advantages of both imaging methodologies, we develop a generative adversarial network that converts phase-contrast into synthesized fluorescent images. By including an additional histogram-equalized output to the state-of-the-art pix2pixHD algorithm, our model generates accurate images of aggregates and streams, enabling the estimation of aggregate positions and sizes, but with small shifts of their boundaries. Further training on ripple patterns enables accurate estimation of the rippling wavelength. Our methods are thus applicable for many other phenotypic behaviors and pattern formation studies.