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The propagation of active-passive interfaces in bacterial swarms.

ABSTRACT: Propagating interfaces are ubiquitous in nature, underlying instabilities and pattern formation in biology and material science. Physical principles governing interface growth are well understood in passive settings; however, our understanding of interfaces in active systems is still in its infancy. Here, we study the evolution of an active-passive interface using a model active matter system, bacterial swarms. We use ultra-violet light exposure to create compact domains of passive bacteria within Serratia marcescens swarms, thereby creating interfaces separating motile and immotile cells. Post-exposure, the boundary re-shapes and erodes due to self-emergent collective flows. We demonstrate that the active-passive boundary acts as a diffuse interface with mechanical properties set by the flow. Intriguingly, interfacial velocity couples to local swarm speed and interface curvature, raising the possibility that an active analogue to classic Gibbs-Thomson-Stefan conditions may control this boundary propagation.

SUBMITTER: Patteson AE

PROVIDER: S-EPMC6299137 | biostudies-literature | 2018 Dec

REPOSITORIES: biostudies-literature

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The propagation of active-passive interfaces in bacterial swarms.

Patteson Alison E AE Gopinath Arvind A Arratia Paulo E PE

Nature communications 20181218 1

Propagating interfaces are ubiquitous in nature, underlying instabilities and pattern formation in biology and material science. Physical principles governing interface growth are well understood in passive settings; however, our understanding of interfaces in active systems is still in its infancy. Here, we study the evolution of an active-passive interface using a model active matter system, bacterial swarms. We use ultra-violet light exposure to create compact domains of passive bacteria with ...[more]

PMID: 30560867

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Project description:This dataset contains transcription profiles of TOP10 E.coli transformed with 85 rewired network plasmids first described in: Evolvability and hierarchy in rewired bacterial gene networks. Nature 452:840-5 (2008). The data are described and analysed in an accompanying paper Baumstark et al.,The propagation of perturbations in shuffled bacterial gene networks (Submitted, 2015). 260 raw data microarrays are provided in total, representing biological triplicates (a,b and c; independent colonies grown from the same transformation, under standard growth conditions; LB, 16h). This is done for each of 255 promoter-ORF constructs (e.g. appY-crp, etc.) and 5 control construct microarrays (empty plasmid; Co). Co controls are provided for comparison, to show the relative effect of the rewiring genetic perturbation. The final processed data compares the number of perturbed genes, comparing between the average expression values of each rewired construct and Co. Methods: The 85 rewiring plasmids (Isalan et al, 2008) were transformed into E. coli TOP10 cells and grown under standardised conditions: bacteria were freshly plated onto LB Agar plates (with 100 μg/ml Ampicillin and 50 μg/ml Streptomycin) and incubated overnight at 37oC to form colonies. Single colonies (<3 days old) were used to inoculate 2 ml of LB in 14 ml culture tubes, containing 100 μg/ml Ampicillin and 50 μg/ml Streptomycin. Constructs were grown for 16h at 37oC, at 220 rpm in an orbital shaker. 10 μg of extracted total bacterial RNA (integrity number > 7.0) was used with Affymetrix GeneChip E. coli Genome 2.0 Arrays. Key to names: RAW DATA samples 1-260 _Co_1a.CEL = Control Co, colony a _Co_1b.CEL = Control Co, colony b etc. appY_O_30a.CEL = appY-promoter only, colony a appY_O_30b.CEL = appY-promoter only, colony b etc. appY_crp_34a.CEL = rewired construct, appY-promoter expressing crp ORF, colony a appY_crp_34b.CEL = rewired construct, appY-promoter expressing crp ORF, colony b appY_crp_34b.CEL = rewired construct, appY-promoter expressing crp ORF, colony c etc. PROCESSED DATA sample 261: probe_set_expression_value_norm_all - normalised data for all samples, for all E. coli K12 genes sample 262: probe_set_expression_value_norm_MG1655 - normalised data for all samples, for E. coli MG1655 subset of genes

Project description:UNLABELLED:Swarming bacteria are challenged by the need to invade hostile environments. Swarms of the flagellated bacterium Paenibacillus vortex can collectively transport other microorganisms. Here we show that P. vortex can invade toxic environments by carrying antibiotic-degrading bacteria; this transport is mediated by a specialized, phenotypic subpopulation utilizing a process not dependent on cargo motility. Swarms of beta-lactam antibiotic (BLA)-sensitive P. vortex used beta-lactamase-producing, resistant, cargo bacteria to detoxify BLAs in their path. In the presence of BLAs, both transporter and cargo bacteria gained from this temporary cooperation; there was a positive correlation between BLA resistance and dispersal. P. vortex transported only the most beneficial antibiotic-resistant cargo (including environmental and clinical isolates) in a sustained way. P. vortex displayed a bet-hedging strategy that promoted the colonization of nontoxic niches by P. vortex alone; when detoxifying cargo bacteria were not needed, they were lost. This work has relevance for the dispersal of antibiotic-resistant microorganisms and for strategies for asymmetric cooperation with agricultural and medical implications. IMPORTANCE:Antibiotic resistance is a major health threat. We show a novel mechanism for the local spread of antibiotic resistance. This involves interactions between different bacteria: one species provides an enzyme that detoxifies the antibiotic (a sessile cargo bacterium carrying a resistance gene), while the other (Paenibacillus vortex) moves itself and transports the cargo. P. vortex used a bet-hedging strategy, colonizing new environments alone when the cargo added no benefit, but cooperating when the cargo was needed. This work is of interest in an evolutionary context and sheds light on fundamental questions, such as how environmental antibiotic resistance may lead to clinical resistance and also microbial social organization, as well as the costs, benefits, and risks of dispersal in the environment.

Dataset Information

The propagation of active-passive interfaces in bacterial swarms.

Publications

The propagation of active-passive interfaces in bacterial swarms.

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