Schlegel, S. | Search bioRxiv

bioRxiv2024

A delivered DNase toxin creates population heterogeneity through transient intoxication of siblings.

Population heterogeneity is important for multicellular behavior and division of labor. Bacterial toxin delivery has been implicated in generating population heterogeneity, but the molecular mechanisms behind this are not well understood. Here we investigate how CdiA toxins generate heterogeneity in isogenic populations. Using a DNase toxin as proxy, we find that E. coli populations able to deliver the toxin show a heterogeneous expression of the SOS-response gene sulA. Heterogeneity results from excessive delivery of toxin into some cells, which become intoxicated due to insufficient immunity. Intoxication is transiently reversible, and intoxicated cells can be rescued by de novo synthesis of cognate immunity protein. Expression of sulA is regulated by both DNA damage and redox status. Interestingly, kin-delivery changes redox status, whereas intoxicated non-kin cells induce the SOS DNA damage response. The former results in changed expression of metabolic genes whereas the latter induces prophage excision, which may promote horizontal gene transfer. In conclusion, we identify a molecular mechanism by which heterogeneity is generated through toxin delivery among kin, and the consequences of said heterogeneity. Significance statementBacteria communicate through secretion of chemical signaling molecules to perform multicellular behavior. Recent advances suggest that contact-mediated toxin delivery allow bacteria to participate also in direct cell-cell communication. How such toxin-mediated communication would work mechanistically is however unclear. Here we elucidate a molecular mechanism of a toxin-mediated communication, where kin-cells transiently intoxicate each other, resulting in physiological changes. These changes depend on the toxic activity, i.e. other toxins with different activities are likely to give rise to other responses. Thus, the arsenal of toxins that a bacterium harbors could affect their ability to communicate. Understanding the molecular mechanism of how toxins could mediate polyphenism is important for our understanding of what this signaling is used for.

microbiology↗

bioRxiv2019

Short-range interactions govern cellular dynamics in microbial multi-genotype systems

Ecosystem processes result from interaction between organisms. When interactions are local, the spatial organization of organisms defines their network of interactions, and thus influences the systems functioning. This can be especially relevant for microbial systems, which often consist of spatially structured communities of cells connected by a dense interaction network. Here we measured the spatial interaction network between cells in microbial systems and identify the factors that determine it. Combining quantitative single-cell analysis of synthetic bacterial communities with mathematical modeling, we find that cells only interact with other cells in their immediate neighbourhood. This short interaction range impacts the functioning of the whole system by reducing its ability to perform metabolic processes collectively. Our experiments and models demonstrate that the spatial scale of cell-to-cell interaction plays a fundamental role in understanding and controlling natural communities, and in engineering microbial systems for specific purposes. Significance StatementCommunities of interacting microbes perform fundamental processes on earth. We do not understand well how these processes emerge from the interactions between individual microbial cells. Our work investigates how strongly individual cells interact and how the strength of the interaction depends on the distance between cells. The discovery that individual cells live in a small world, i.e. they only interact with a small number of cells around them, changes our understanding of how cells in natural microbial communities are metabolically coupled and how their spatial arrangement determines emergent properties at the community level. Our quantitative single-cell approach allows to address central questions on systems composed of interacting genotypes and to increase our understanding and ability to control microbial communities.

systems biology↗