Spatial segregation and cooperation in radially expanding microbial colonies under antibiotic stress

Abstract

Antibiotic resistance in microbial communities reflects a combination of processes operating at different scales. The molecular mechanisms underlying antibiotic resistance are increasingly understood, but less is known about how these molecular events give rise to spatiotemporal behavior on longer length scales. In this work, we investigate the population dynamics of bacterial colonies comprised of drug-resistant and drug-sensitive cells undergoing range expansion under antibiotic stress. Using the opportunistic pathogen E. faecalis with plasmid-encoded (β -lactamase) resistance as a model system, we track colony expansion dynamics and visualize spatial pattern formation in fluorescently labeled populations exposed to ampicillin, a commonly-used β -lactam antibiotic. We find that the radial expansion rate of mixed communities is approximately constant over a wide range of drug concentrations and initial population compositions. Microscopic imaging of the final populations shows that resistance to ampicillin is cooperative, with sensitive cells surviving in the presence of resistant cells even at drug concentrations lethal to sensitive-only communities.Furthermore, despite the relative invariance of expansion rate across conditions, the populations exhibit a diverse range of spatial segregation patterns, with both the spatial structure and the population composition depending on drug concentration, initial composition, and initial population size. Simple mathematical models indicate that the observed dynamics are consistent with global cooperation, and experiments confirm that resistant colonies provide a protective effect to sensitive cells on length scales multiple times the size of a single colony. Furthermore, in the limit of small inoculum sizes, we experimentally show that populations seeded with (on average) no more than a single resistant cell can produce mixed communities in the presence of drug. Our results suggest that β -lactam resistance can be cooperative even in spatially extended systems where genetic segregation typically disfavors exploitation of locally produced public goods.

Social evolution of shared biofilm matrix components

“…The copyright holder for this preprint this version posted December 17, 2021. ; https://doi.org/10.1101/2021.12.16.472970 doi: bioRxiv preprint Finally, previous work has shown that in the cases of extracellular enzymes 27,71,72 , siderophores 23,73 , and autoinducers [74][75][76] as diffusive public goods, mostly studied in continuous films, clonal segregation and efficient consumption of public goods (or their enzymatic products and complexes) through high local cell density and a high uptake rate can minimize the potential for exploitation in the context of dense bacterial communities 21,26,27 . In the context of spatially discrete clonal clusters, we expect the evolutionary stability of these public goods to be determined by the interplay between the exploitation range and the spatial structure as shown here.…”

Microbial Interspecies Interactions and Their Impact on the Emergence and Spread of Antimicrobial Resistance

“…These so-called cheaters will compete against the resistant strain, preventing the resistant mutant from thriving during antibiotic treatment. Instead, in most cases, intraspecies experiments predict that an equilibrium will be reached with the survival of both resistant and sensitive strains, since at low frequencies the publicly resistant strain will no longer sufficiently protect the cheaters and negative frequency-dependent selection will stabilize the population of publicly resistant bacteria (3,21,69,90). In structured conditions, segregation between different lineages via competition or drift can also reduce the exploitation of producers and further stabilize public resistance mechanisms.…”

Metabolic interactions control the spread of plasmid-encoded functional novelty during microbial range expansion

“…During the range expansion process, different cell-types arrange themselves non-randomly across space (referred to as spatial self-organization [SSO]) (Ben-Jacob, Cohen et al 2000, Tolker-Nielsen and Molin 2000, Smith, Davit et al 2017. The patterns of SSO that develop depend on local environmental conditions (Gralka, Stiewe et al 2016, Mitri, Clarke et al 2016, Sharma and Wood 2021, Ciccarese, Micali et al 2022, the phenotypes expressed by individuals (Rudge, Federici et al 2013, Gralka, Stiewe et al 2016, Smith, Davit et al 2017, Xiong, Cao et al 2020, cell-cell interactions (Momeni, Waite et al 2013, Blanchard and Lu 2015, Nadell, Drescher et al 2016, Goldschmidt, Regoes et al 2017, Tecon and Or 2017, Kan, Del Valle et al 2018, and cell-surface interactions (Atis, Weinstein et al 2019, Ciccarese, Zuidema et al 2020, Fei, Mao et al 2020. Importantly, SSO can be an important determinant of the collective traits of communities and the evolutionary processes acting on those communities (Gralka, Stiewe et al 2016, Nadell, Drescher et al 2016, Weinstein, Lavrentovich et al 2017, Giometto, Nelson et al 2018, Kayser, Schreck et al 2018, Bosshard, Peischl et al 2019, Goldschmidt, Caduff et al 2021.…”