Bacteria have evolved a wide range of mechanisms to harm and kill their competitors, including chemical, mechanical and biological weapons. Here we review the incredible diversity of bacterial weapon systems, which comprise antibiotics, toxic proteins, mechanical weapons that stab and pierce, viruses, and more. The evolution of bacterial weapons is shaped by many factors, including cell density and nutrient abundance, and how strains are arranged in space. Bacteria also employ a diverse range of combat behaviours, including pre-emptive attacks, suicidal attacks, and reciprocation (tit-for-tat). However, why bacteria carry so many weapons, and why they are so often used, remains poorly understood. By comparison with animals, we argue that the way that bacteria live -often in dense and genetically diverse communities -is likely to be key to their aggression as it encourages them to dig in and fight alongside their clonemates. The intensity of bacterial aggression is such that it can strongly affect communities, via complex coevolutionary and ecoevolutionary dynamics, which influence species over space and time. Bacterial warfare is a fascinating topic for ecology and evolution, as well as one of increasing relevance. Understanding how bacteria win wars is important for the goal of manipulating the human microbiome and other important microbial systems. StrategyRule(s) defining the decisions of an actor in response to prevailing conditions (for example, fight back if attacked). TacticsBehaviours displayed in a given contest (the realised output of a strategy). ToxinSubstance that disrupts cell physiology. WarfareConflict involving weapons between two or more groups. WeaponCompetitive phenotype that damages and/or disrupts the physiology of recipients, and that evolved, at least in part, for that purpose (for example, bacteriocin production).

Bacteria often live in diverse communities where the spatial arrangement of strains and species is considered critical for their ecology. However, a test of this hypothesis requires manipulation at the fine scales at which spatial structure naturally occurs. Here we develop a droplet-based printing method to arrange bacterial genotypes across a sub-millimetre array. We print strains of the gut bacterium Escherichia coli that naturally compete with one another using protein toxins. Our experiments reveal that toxin-producing strains largely eliminate susceptible non-producers when genotypes are well-mixed. However, printing strains side-by-side creates an ecological refuge where susceptible strains can persist in large numbers. Moving to competitions between toxin producers reveals that spatial structure can make the difference between one strain winning and mutual destruction. Finally, we print different potential barriers between competing strains to understand how ecological refuges form, which shows that cells closest to a toxin producer mop up the toxin and protect their clonemates. Our work provides a method to generate customised bacterial communities with defined spatial distributions, and reveals that micron-scale changes in these distributions can drive major shifts in ecology.

Evolution is often an obstacle to the engineering of stable biological systems due to the selection of mutations inactivating costly gene circuits. Gene overlaps induce important constraints on sequences and their evolution. We show that these constraints can be harnessed to increase the stability of costly genes by purging loss-of-function mutations. We combine computational and synthetic biology approaches to rationally design an overlapping reading frame expressing an essential gene within an existing gene to protect. Our algorithm succeeded in creating overlapping reading frames in 80% of E. coli genes. Experimentally, scoring mutations in both genes of such overlapping construct, we found that a significant fraction of mutations impacting the gene to protect have a deleterious effect on the essential gene. Such an overlap thus protects a costly gene from removal by natural selection by associating the benefit of this removal with a larger or even lethal cost. In our synthetic constructs, the overlap converts many of the possible mutants into evolutionary dead-ends, reducing the evolutionary potential of the system and thus increasing its stability over time.

Evolution is often an obstacle to the engineering of stable biological systems due to the selection of mutations inactivating costly gene circuits. Gene overlaps induce important constraints on sequences and their evolution. We show that these constraints can be harnessed to increase the stability of synthetic circuits by purging loss-of-function mutations. We combine computational and synthetic biology approaches to rationally design an overlapping reading frame expressing an essential gene within an existing gene to protect. Our algorithm succeeded in creating overlapping reading frames in 80% of E. coli genes. Experimentally, scoring mutations in both genes of such overlapping construct, we found that a significant fraction of mutations impacting the gene to protect have a deleterious effect on the essential gene. Such an overlap thus protects a costly gene from removal by natural selection by associating the benefit of this removal with a larger or even lethal cost. In our synthetic constructs, the overlap converts many of the possible mutants into evolutionary dead-ends, effectively changing the fitness landscape and reducing the evolutionary potential of the system.