Emergent microscale gradients give rise to metabolic cross-feeding and antibiotic tolerance in clonal bacterial populations

Co, Alma Dal; Vliet, Simon van; Ackermann, Martin

doi:10.1098/rstb.2019.0080

Cited by 80 publications

(83 citation statements)

References 38 publications

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“…In previous work, we showed that when glucose is supplied at low concentration in the flow channel (800 mM), the combined metabolic activity of the cells creates strong nutrient gradients along the depth of the chamber [34]. The local microenvironment varies over a length scale of a few cell lengths, and, as a result, the average phenotype of the cells changes with the depth in the chamber.…”

Section: Subpopulations Specialize In Different Metabolic Activities mentioning

confidence: 99%

“…All experiments were done with E. coli MG1655 carrying the low copy number pSV66-acs-gfp-ptsG-rfp plasmid, which contains a GFPmut2 transcriptional reporter for acs and a turboRFP transcriptional reporter for ptsG [34].…”

Section: Strains and Plasmidsmentioning

confidence: 99%

“…Moulds for the microfluidic devices were fabricated from SU8 photoresist on silicon wafers using a two-layer photolithography process (Microresist, Berlin). Microfluidic devices were manufactured from polydimethylsiloxane (Sylgard 184) as described in [34]. The devices were filled with culture medium using a pipette first to wet the channels.…”

Section: Microfluidic Devices and Experimentsmentioning

confidence: 99%

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Metabolic activity affects the response of single cells to a nutrient switch in structured populations

Ackermann

Vliet

2019

J. R. Soc. Interface.

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Microbes live in ever-changing environments where they need to adapt their metabolism to different nutrient conditions. Many studies have characterized the response of genetically identical cells to nutrient switches in homogeneous cultures; however, in nature, microbes often live in spatially structured groups such as biofilms where cells can create metabolic gradients by consuming and releasing nutrients. Consequently, cells experience different local microenvironments and vary in their phenotype. How does this phenotypic variation affect the ability of cells to cope with nutrient switches? Here, we address this question by growing dense populations of Escherichia coli in microfluidic chambers and studying a switch from glucose to acetate at the single-cell level. Before the switch, cells vary in their metabolic activity: some grow on glucose, while others cross-feed on acetate. After the switch, only few cells can resume growth after a period of lag. The probability to resume growth depends on a cells' phenotype prior to the switch: it is highest for cells cross-feeding on acetate, while it depends in a non-monotonic way on the growth rate for cells growing on glucose. Our results suggest that the strong phenotypic variation in spatially structured populations might enhance their ability to cope with fluctuating environments.

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Section: Subpopulations Specialize In Different Metabolic Activities mentioning

confidence: 99%

Section: Strains and Plasmidsmentioning

confidence: 99%

Section: Microfluidic Devices and Experimentsmentioning

confidence: 99%

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Metabolic activity affects the response of single cells to a nutrient switch in structured populations

Ackermann

Vliet

2019

J. R. Soc. Interface.

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“…The complexity of these communities might partly reflect the complexity of their environment, which can generate and maintain diversity by allowing specialisation on different niches [1][2][3][4][5][6][7][8][9][10] . Experimental evolution has shown how initially clonal populations can adaptively diversify into stably coexisting ecotypes, each specialised on pre-existing niches defined by available nutrients 1 , spatial structure 2,11 , temporal variability such as the feast and famine cycles in serial transfer [3][4][5][6][7][8][9] , or combinations thereof 10 . However, even in constant, unstructured environments with a single limiting carbon source metabolic diversification routinely evolves 4,[12][13][14] .…”

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confidence: 99%

Contingent evolution of alternative metabolic network topologies determines whether cross-feeding evolves

2020

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Metabolic exchange is widespread in natural microbial communities and an important driver of ecosystem structure and diversity, yet it remains unclear what determines whether microbes evolve division of labor or maintain metabolic autonomy. Here we use a mechanistic model to study how metabolic strategies evolve in a constant, one resource environment, when metabolic networks are allowed to freely evolve. We find that initially identical ancestral communities of digital organisms follow different evolutionary trajectories, as some communities become dominated by a single, autonomous lineage, while others are formed by stably coexisting lineages that cross-feed on essential building blocks. Our results show how without presupposed cellular trade-offs or external drivers such as temporal niches, diverse metabolic strategies spontaneously emerge from the interplay between ecology, spatial structure, and metabolic constraints that arise during the evolution of metabolic networks. Thus, in the long term, whether microbes remain autonomous or evolve metabolic division of labour is an evolutionary contingency.

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“…Here, microfluidics or micromodels are promising tools to mimic soil pore structure especially when combined with new imaging techniques allowing for small-scale observations (Aleklett et al, 2018;Baveye et al, 2018). Recently, Co et al (2019) applied microfluidics and observed an increase in antibiotic tolerance in spatially structured compared to intermixed populations (Co et al, 2019). However, the usage of microfluidics is an emerging field and until fully established, the application of simulation models to investigate microscale spatial disturbance effects is a powerful tool.…”

Section: Modeling Spatially Structured Disturbancesmentioning

confidence: 99%

Physical, Chemical and Biological Effects on Soil Bacterial Dynamics in Microscale Models

et al. 2020

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Soil is populated by highly diverse microbial communities mediating important processes and functions. The distribution of microbes, however, is neither uniform nor random. Instead, it is dictated by physical, chemical, and biological processes and conditions and varying over small spatial and temporal scales. The feedbacks between these processes make the soil-microbe complex a self-organizing system capable of adapting to the continuously changing conditions mainly driven by the highly fluctuating water content. For making meaningful predictions on the spatiotemporal dynamics of soil microbes and their functions, we need to integrate knowledge from physics, chemistry, and biology in our modeling approaches. Here, we review modeling studies with a focus on spatiotemporal dynamics of bacteria and bacterial functions in soil microhabitats. We compare these studies along four dimensions: specific aim, model type (individual-based, population-based), scale, and considered physical, chemical, biological processes and aspects. A special emphasis is laid on modeling approaches considering processes and aspects influencing the spatial distribution of bacteria such as motility, vector-based dispersal and biofilm formation. This includes factors like soil structure, carbon and oxygen gradients, temporal variations in hydration conditions or anthropogenic disturbance events. By assessing the importance of different microscale bacterial processes, this review should contribute to the ongoing discussion on challenges related to the upscaling from the microscopic via the profile to the landscape scale. Recent technical advances to observe bacteria in soils or soil-like environments combined with multidisciplinary collaborations will help to shed light on currently understudied physical, chemical and biological interactions in the soil-microbe complex.

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Emergent microscale gradients give rise to metabolic cross-feeding and antibiotic tolerance in clonal bacterial populations

Cited by 80 publications

References 38 publications

Metabolic activity affects the response of single cells to a nutrient switch in structured populations

Metabolic activity affects the response of single cells to a nutrient switch in structured populations

Contingent evolution of alternative metabolic network topologies determines whether cross-feeding evolves

Physical, Chemical and Biological Effects on Soil Bacterial Dynamics in Microscale Models

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