Spatial Organization of Expanding Bacterial Colonies Is Affected by Contact-Dependent Growth Inhibition

Abstract

SummaryIdentifying how microbes are able to manipulate, survive, and thrive in complex multispecies communities has expanded our understanding of how microbial ecosystems impact human health and the environment. The ability of bacteria to negatively affect neighbors, through explicit toxin delivery systems, provides them with an opportunity to manipulate the composition of growing microbial communities. Contact-dependent inhibition (CDI) systems (a Type Vb secretion system) are a distinct subset of competition systems whose contribution to shaping the development of spatially structured bacterial communities are yet to be fully understood. Here, we compare the impact of different CDI systems, at both the single-cell and population level, to determine the key drivers of CDI-mediated competition within spatially structured bacterial populations. Through an iterative approach using both an Escherichia coli experimental system and computational modeling, we show that CDI systems have subtle and system-specific effects at the single-cell level, generating single-cell-wide boundaries between CDI-expressing inhibitor cells and their neighboring targets. Despite the subtle effects of CDI at a single-cell level, CDI systems greatly diminished the ability of susceptible targets to expand their range during colony growth. The inoculum density of the population, together with the CDI system-specific variables of the speed of inhibition after contact and biological cost of CDI, strongly affects CDI-mediated competition. In contrast, the magnitude of the toxin-induced growth retardation of target cells only weakly impacts the composition of the population. Our work reveals how distinct CDI systems can differentially affect the composition and spatial arrangement of bacterial populations.

Accumulation of dead cells from contact killing facilitates coexistence in bacterial biofilms

“…We observe similar temporal 73 dynamics in experiments with mutually killing strains (S2 Fig): again, a transition from 74 rapid killing to almost no killing occurs after ∼ 3 hours (S1 Fig b). These observations 75 are consistent with previously reported observations of small but long-lived target 76 populations [23]. Why does T6SS-mediated killing stop after just a few hours?…”

“…While we only perform experiments with T6SS killing, results presented here 333 potentially apply to many other contact killing mechanisms [4]. In fact, comparable 334 phenomena of inhibited killing were seen in contact dependent growth inhibition 335 experiments, in which live but non-reproducing cells were observed to prevent further 336 contact between antagonistic cells and their targets [75]. Further, similar phenomena 337 may impact killing mechanisms that act over longer distances, e.g., via diffusible deadly 338 bio-molecules [76], phages [77] and bacteriocins [78].…”

Contact-Dependent Growth Inhibition in Bacteria: Do Not Get Too Close!

“…A mathematical model was proposed by Blanchard et al which predicts that CDI-like competition systems may result in localized aggregation of inhibiting cells within one-and two-dimensional populations [84]. Using computational modeling and E. coli as an example, Bottery et al showed that CDI systems have subtle and system-specific effects at the single-cell level, generating single-cell-wide boundaries between CDI-expressing inhibitor cells and their neighboring targets [24]. Together, all these studies demonstrate that specific toxin-immunity protein binding interactions can control a "self"/"non-self" discrimination in bacteria, and CDI mechanisms thus serve as a tool for recognizing genetically identical relatives in mixed bacterial populations.…”

“…In our review, we consider the phenomenon of contact-dependent growth inhibition (CDI) mediated by the Vb type secretion system. Despite the general similarity in purpose (delivery of a toxin to a neighboring cell) and design (a multi-protein "docking" complex for making contact with a target cell) with a "molecular syringe", a notable feature of the CDI system is the need for specific receptors on the surface of the target cell to interact with the receptor recognizing site of the CDI toxin [21][22][23][24][25][26][27][28].…”

A data-based mathematical modelling study to quantify the effects of ciprofloxacin and ampicillin on the within-host dynamics of Salmonella enterica during treatment and relapse

“…Conclusions drawn from these studies provide insights into the mode of action of different antibiotic agents on their bacterial targets; however, their clinical relevance remains unknown, as in vivo bacterial populations are characterised by heterogeneity in their growth and dissemination dynamics [6][7][8][9]. Upon successful colonisation, in vivo bacterial behaviour is multifactorially shaped by nutrient availability [6,10], host immunity [11][12][13], spatial arrangement of the infectious foci [14], and host cell composition in the immediate bacterial vicinity [15][16]. The landscape of within-host bacterial dynamics is further complicated by the induction of stress responses in bacterial populations exposed to antibiotics, which alter the bacterial metabolic and transcriptional profile, slow down or stop replication, and ultimately affect the pathogen's susceptibility to the antibiotic [17].…”