Active Plants, Animals & Ecology Food & Agriculture

The evolutionary ecology of interspecific microbial public-goods

In plain English

AI plain-English summary

Bacteria that detoxify metal-polluted soil are being recruited to clean up mine waste, but their cooperative behaviour can collapse when cheaters exploit the system. Metal demand is projected to increase more than 450% by 2050, driven by the shift to low-carbon technologies. Mine waste already contaminates soils worldwide, harming human health and ecosystems. Microbes can bind toxic metals with molecules called siderophores, but current understanding comes mostly from single-species studies. In real soil, multiple species interact, and cooperation breaks down when cheaters—bacteria that use siderophores without producing them—outcompete producers. This severely limits the use of microbes in remediation. The researcher has already shown that species stably coexist when they specialise on different metals, but cheaters rapidly destabilise this division of labour. The renewal adds a missing piece: plants. Plant roots alter soil structure and nutrient availability, which should affect bacterial cooperation. The project will test whether root-associated communities produce more siderophores, how this feeds back on plant metal uptake, and whether local adaptation or land management changes outcomes. If successful, the work could improve phytoremediation—using plants and their microbial partners to clean contaminated land—offering a sustainable, low-cost alternative to excavation or chemical treatment.

View original technical description
Mine waste is a major problem worldwide, having detrimental effects on human health as well as the environment. In a drive for low carbon technologies, metal demand is projected to increase >450% by 2050. There is thus a pressing need to develop long-term sustainable remediation strategies. Microbes play key roles in geochemical processes and their vast metabolic diversity may aid in the clean-up of mine-degraded soils. Detoxification in microbial communities not only depends on individual behaviour, but also on interactions between different species. However, we have limited understanding of metal-detoxification in multi-species contexts, severely curtailing their effective use in remediation. My FLF explores siderophore-mediated bioremediation, with a focus on divisions of labour within soil communities to maximise detoxification. Bacteria release siderophores into the environment which bind toxic metals, preventing diffusion into cells. Mine-degraded soils typically contain multiple toxic metals. In theory, if different species specialise to detoxify different metals, this can improve species coexistence and remediation. However, such cooperation can also break down when cheats (individuals that do not produce siderophores but reap benefits from others) are able to displace siderophore producers. From work on single species, we know that cheats should be less successful in structured environments as this restricts their access to siderophores. My original FLF tested this prediction using a combination of theory and controlled experiments with synthetic and natural soil communities. By tracking ecological and evolutionary changes, my work so far has shown that species stably coexist when they specialise to detoxify different metals, increasing community-wide siderophore levels. However, coexistence quickly breaks down when cheats newly evolve or when they can freely disperse into local patches of producers. The relative speed of ecological and evolutionary change is thus crucial to the maintenance of divisions of labour. My team and I are currently identifying the molecular mechanisms underpinning changes in siderophore production. During the renewal, I will build on these results and further increase realism by examining another key ecological factor underpinning bacterial divisions of labour: plants. Plant-microbe feedbacks are ubiquitous in nature and have important implications for phytoremediation. In theory, plant roots can alter social behaviour by providing structure and nutrients, both of which are predicted to affect cooperation by altering the relative costs and benefits of siderophores. We have limited knowledge of how cooperation and conflict within soil bacterial communities feeds back to influence plant fitness, for example by altering metal solubility. In the renewal I will fill these knowledge gaps by addressing five objectives: (1) as individuals can regulate siderophore production in response to environmental cues, I will determine the role of phenotypic plasticity versus mutation in underpinning siderophore changes; (2) I will test whether siderophore production is increased in relatively nutrient-rich root-associated communities versus bulk soil communities; (3) I will determine how variation in siderophore production affects plant fitness and plant metal uptake by increasing metal solubility; (4) I will assess the impact of adaptation to local environmental conditions on plant-microbe interactions, as and (5) I will focus on the effect of land management on metal mobility, using a citizen science approach. The data obtained in the renewal will result in a major advance in our understanding of plant-microbe interactions and phytoremediation. The insights gained will be of great interest to policy practitioners aiming to optimise microbiomes for environmental function and health.

View the original record at the funder ↗

Researchers

Elze Hesse (Principal Investigator)

Related Research

Grants with similar aims, by meaning.

The net effect of microbial siderophores on above- and belowground soil health
Unlocking the potential of iron biogeobatteries
Microbial reduction of metalloid oxyanions: significance of geochemical factors
Exploring how species interactions shape adaptive evolution in soil microbial communities
Mineral-Microbe interaction role in concentration and Fractionation of Rare Earth Elements (MM-FREE)

Original classification

Fellowship

Plain English summaries and category classifications on this site are generated by AI and may not perfectly reflect the original research.