Bacteria produce natural products to adapt to their environments, with phage interactions as major ecological and evolutionary drivers. While some natural products protect bacteria from phages, the prevalence and diversity of chemical anti-phage defenses remain largely unexplored. Here, we identify a widespread family of lanthipeptide biosynthetic gene clusters (BGCs) in Actinobacteria, which we term lanthivirin BGCs, that confer anti-phage activity. Lanthivirin BGCs often colocalize with other defense systems in genomic defense islands. We demonstrate anti-phage activity both in a native Streptomyces context and through heterologous expression of six distinct lanthivirin systems. Mutational analyses of the biosynthetic machinery and core peptide show that lanthivirin maturation is required for anti-phage activity. Genetic and biochemical analyses during infection support a phage-protein-dependent inhibition of phage DNA replication, with no host toxicity. Our findings highlight the untapped potential of BGCs as sources of anti-phage natural products, offering a new avenue for discovering antiviral compounds.

Bacterial persisters are a subpopulation of cells that exhibit a transient non-susceptible phenotype in the presence of bactericidal antibiotic concentrations. This phenotype can lead to the survival and regrowth of bacteria after treatment, resulting in relapse of infections. It is also a contributing factor to antibacterial resistance. Multiple processes are believed to cause persister formation; however, identifying the proteins expressed during the induction of persistence is challenging because the persister state is rare, transient, and does not result in genetic changes. In this study, we used Bio-Orthogonal Non-Canonical Amino Acid Tagging (BONCAT) to label and retrieve the proteome expressed during persistence and recovery for two strains of Staphylococcus aureus exposed to β-lactam and fluoroquinolone antibiotics. After incubating antibiotic-exposed bacteria with the methionine ortholog L-azidohomoalanine to label the proteins of persister cells, we retrieved labeled proteins using click chemistry-pulldown methodology. Analysis of the retrieved proteome of persisters with Label-Free Quantification-Liquid chromatography mass spectrometry (LFQ-LCMS)-based proteomics revealed widespread changes in translation. Our analysis uncovered previously identified persister genes, including, for example, relA/spot-system, changes in purine and amino acid metabolism, the upregulation and downregulation of transcription factors, and changes to influx and efflux pumps, thus validating our methodology. In addition, we also identified numerous novel persister-associated proteins. Few changes were conserved across the two strains and both antibiotics. Instead, results suggest that the mechanisms of persister formation vary across genotypes and the drugs to which strains are exposed. These findings provide evidence that the entry into persistence is an active process that dramatically alters the translational behavior of cells and suggest that downregulation of metabolism, by diverse but functionally similar processes, in persister cells enables cells to survive antibiotic pressure.IMPORTANCEIn this study, we have applied a technique called "Bioorthogonal Non-Canonical Amino Acid-Tagging," or BONCAT, to identify which proteins are expressed when bacteria are in the persister state. Our work makes novel contributions to our understanding of persister cells, a bacterial sub-population that gives rise to recurrent infections, and establishes BONCAT as a valuable tool to study phenotypic heterogeneity in bacterial populations.

Streptomyces are among the most well-studied and important groups of bacteria, largely owing to their prolific production of biomedically important compounds like antibiotics and antifungals. Research over more than a half-century has elucidated the molecular and mechanistic details of Streptomyces multicellular development and the production of secondary metabolites. In contrast, the evolutionary and ecological mechanisms that underlie these phenotypes are comparatively understudied. Our aim in this review is to examine these aspects of Streptomyces biology, with a focus on the benefits associated with their complex life cycle, their multicellular architecture and development, and their production of antibiotics. In addition to highlighting existing studies, we point to clear knowledge gaps that can serve to motivate further research on these bacteria. A greater understanding of Streptomyces evolution and ecology is needed to improve our ability to exploit these organisms for biomedical and agricultural applications.

Colonies of the bacterim Streptomyces coelicolor divide labour between cells that specialize in growth and sporulation and cells that specialize in antibiotic production. This division of labour arises owing to costly chromosome deletions in the antibiotic overproducers. However, the spatial distribution and temporal emergence of these mutations in S. coelicolor colonies remain unknown, or whether mutation frequency-which we liken to the caste ratio in social insects-is phenotypically plastic. To elucidate changes in the proportions of specialized cells (measured as the mutation frequency), we sampled S. coelicolor colonies grown under different conditions. Temporally, mutation frequency increased linearly with colony age and size. Spatially, mutations accumulated disproportionately in the colony centre, despite greater growth and sporulation at the periphery. Exposing colonies to sub-inhibitory concentrations of some antibiotics, a competitive cue in Streptomyces, increased mutation frequencies. Finally, direct competition with other Streptomyces that naturally produce antibiotics increased mutation frequencies, while also increasing spore production. Our findings provide insights into the intrinsic and environmental factors driving division of labour in Streptomyces colonies by showing that mutation frequencies are dynamic and responsive to the competitive environment. These results show that chromosome deletions are phenotypically plastic and suggest that Streptomyces can flexibly adjust their caste ratio.This article is part of the theme issue 'Division of labour as key driver of social evolution'.

Larger body size often enhances survival and reproduction. While most organisms grow to achieve larger sizes, some can rapidly increase size through fusion. Fusion decisions are influenced by genetic relatedness and environmental factors, balancing potential benefits and costs. In Physarum polycephalum, a multinucleated slime mould, fusion is thought to occur mainly between genetically identical or highly related individuals. However, the frequency of fusion among close relatives, and the drivers and benefits of fusion, remain unclear. This study explored fusion frequency, morphology, and benefits among clonal and closely related individuals of Physarum. We also assessed the impact of abiotic stress on fusion and whether genetic relatedness between fusion partners influences survival during exposure to stress. Our results revealed variation in fusion frequency and morphology among different plasmodial lines and pairs of close relatives. Abiotic stress increased fusion rates between both clonal and compatible non-clonal pairs. However, the benefits of fusion did not depend on the whether fusion occurred between clones or non-clones. These findings demonstrate plasmodial fusion provides size-related survival benefits. Furthermore, the promotion of fusion in stressful conditions highlights its adaptive role in responding to environmental challenges. Collectively, these results underscore the evolutionary importance of fusion in Physarum, shaping its ecological success and resilience. ### Competing Interest Statement The authors have declared no competing interest.

Pseudomonas aeruginosa is a major pathogen in chronic biofilm-associated lung infections, particularly in patients with cystic fibrosis. Colistin is commonly used to treat these infections, although there is little understanding of how resistance evolves when cells are grown within biofilms. The current study compared the phenotypic dynamics and genetic adaptations of colistin resistance between planktonic and biofilm-grown P. aeruginosa. Using an in vitro experimental evolution approach, we passaged planktonic and biofilm cultures over 10 days under static or progressively increasing colistin concentrations. Population analysis profiling was performed daily to track resistance dynamics and heterogeneity. Whole-genome sequencing was conducted on evolved lineages. Biofilm-grown populations exhibited significantly slower resistance rates than planktonic cultures, particularly under treatments above 0.5 mg/L (1×MIC). Despite this initial delay, both biofilm- and planktonic cultures ultimately evolved similar frequencies of resistant subpopulations. Genetically, we observed shared mutations in canonical colistin resistance determinants such as phoQ and qseC. We also identified growth-mode-specific patterns: oprH mutations were primarily found in biofilm-evolved populations, while nfeD mutations were pervasive in planktonic cultures but rare in biofilms. Taken together, our results provide key insights into the role of biofilm in shaping the evolutionary trajectories of colistin resistance evolution in P. aeruginosa.

Soil is a competitive environment containing a variety of resources used for bacterial growth. Complex polysaccharides, like chitin or starch, require the secretion of enzymes that degrade these resources into smaller units before they can be consumed. However, exoenzymes and the products they create are public goods, meaning they can be used by competitors, called “cheaters”, who benefit from public goods even if they do not produce enzymes themselves. Here, we test the hypothesis that antibiotics produced by Streptomyces are used to privatize public goods by restricting access to resource cheaters. Using experiments with Streptomyces coelicolor and Bacillus subtilis , we first show that B. subtilis cheating significantly reduces S. coelicolor fitness on complex medium (starch) but not on a simple carbon source (maltose) which does not require exoenzyme secretion. Next, we show that antibiotics produced by S. coelicolor markedly increase fitness against resource cheaters, despite evidence that antibiotic production is metabolically costly. Finally, we find that the benefits of antibiotic production and the costs of resource cheating are both higher during growth on lower resource concentrations. Our results provide novel insights into the context-dependent costs and benefits of antibiotic secretion in Streptomyces and highlight the role of resource complexity and concentration in mediating competitive strategies in bacteria. ### Competing Interest Statement The authors have declared no competing interest. NWO, OCENW.M.22.076

The global rise of antibiotic-resistant pathogens has outpaced the development of new antibiotics, prompting the urgent need for alternative treatment strategies. One such approach is to leverage collateral sensitivity (CS), where resistance to one antibiotic increases susceptibility to another. However, the clinical implementation of CS-based therapies depends on the consistency of these responses, which is challenged by variable resistance mutations and the dynamics of resistant strains during infection. Here, we combined experiments and mathematical models to assess the consistency and consequences of CS responses in the Gram-positive pathogen Streptococcus pneumoniae following the de novo acquisition of resistance to five commonly used antibiotics. We found that many collateral responses were unpredictable and inconsistent between different resistance mutations. However, for two antibiotic pairs, we identified consistent unidirectional (RIF → FUS) and bidirectional (LNZ ↔ FUS) CS interactions, despite the divergent evolutionary trajectories of resistant strains, as revealed by whole-genome sequencing. To evaluate if CS for these combinations can be exploited to design dosing strategies to eradicate S. pneumoniae infections while suppressing resistance, we developed a mathematical stochastic pharmacokinetic-pharmacodynamic (PK-PD) model, which integrated our experimentally derived PD parameters with existing clinical PK models. Our model-based analyses confirmed the superiority of these antibiotic combinations over monotherapy and showed that their efficacy depends on the presence of CS interactions between the administered antibiotics. In summary, our study demonstrates how consistent CS interactions can be leveraged to inform treatment strategies, laying the groundwork for CS-guided therapies to preserve antibiotic efficacy. ### Competing Interest Statement The authors have declared no competing interest.

Although bacterial cells typically contain a single chromosome, some species are naturally polyploid and carry multiple copies of their chromosome. Polyploid chromosomes can be identical or heterogeneous, the latter giving rise to bacterial heterozygosity. Although the benefits of heterozygosity are well studied in eukaryotes, its consequences in bacteria are less understood. Here, we examine this question in the context of antibiotic resistance to understand how bacterial genomic heterozygosity affects bacterial survival. Using a cell-wall-deficient model system in the actinomycete Kitasatospora viridifaciens, we found that heterozygous cells that contain different chromosomes expressing different antibiotic resistance markers persist across a broad range of antibiotic concentrations. Recombinant cells containing the same resistance genes on a single chromosome also survive these conditions, but these cells pay a significant fitness cost due to the constitutive expression of these genes. By contrast, heterozygous cells can mitigate these costs by flexibly adjusting the ratio of their different chromosomes, thereby allowing rapid responses in temporally and spatially variable environments. Our results provide evidence that bacterial heterozygosity can increase adaptive plasticity in bacterial cells in a similar manner to the evolutionary benefits provided by multicopy plasmids in bacteria.

Streptomyces are a large genus of multicellular bacteria best known for their prolific production of bioactive natural products. In addition, they play key roles in the mineralisation of insoluble resources, such as chitin and cellulose. Because of their multicellular mode of growth, colonies of interconnected hyphae extend over a large area that may experience different conditions in different parts of the colony. Here, we argue that within-colony phenotypic heterogeneity can allow colonies to simultaneously respond to divergent inputs from resources or competitors that are spatially and temporally dynamic. We discuss causal drivers of heterogeneity, including competitors, precursor availability, metabolic diversity and division of labour, that facilitate divergent phenotypes within Streptomyces colonies. We discuss the adaptive causes and consequences of within-colony heterogeneity, highlight current knowledge (gaps) and outline key questions for future studies.

Technological advances have largely driven the revolution in our understanding of the structure and function of microbial communities. Culturing, long the primary tool to probe microbial life, was supplanted by sequencing and other -omics approaches, which allowed detailed quantitative insights into species composition, metabolic potential, transcriptional activity, secretory responses and more. Although the ability to characterize "who's there" has never been easier or cheaper, it remains technically challenging and expensive to understand what the diverse species and strains that comprise microbial communities are doing in situ, and how these behaviors change through time. Our aim in this brief review is to introduce a developing toolkit based on click chemistry that can accelerate and reduce the expense of functional analyses of the ecology and evolution of microbial communities. After first outlining the history of technological development in this field, we will discuss key applications to date using diverse labels, including BONCAT, and then end with a selective (biased) view of areas where click-chemistry and BONCAT-based approaches stand to have a significant impact on our understanding of microbial communities.

Division of labor can evolve when social groups benefit from the functional specialization of its members. Recently, a novel means of coordinating the division of labor was found in the antibiotic-producing bacterium Streptomyces coelicolor, where specialized cells are generated through large-scale genomic re-organization. We investigate how the evolution of a genome architecture enables such mutation-driven division of labor, using a multiscale computational model of bacterial evolution. In this model, bacterial behavior-antibiotic production or replication-is determined by the structure and composition of their genome, which encodes antibiotics, growth-promoting genes, and fragile genomic loci that can induce chromosomal deletions. We find that a genomic organization evolves, which partitions growth-promoting genes and antibiotic-coding genes into distinct parts of the genome, separated by fragile genomic loci. Mutations caused by these fragile sites mostly delete growth-promoting genes, generating sterile, and antibiotic-producing mutants from weakly-producing progenitors, in agreement with experimental observations. This division of labor enhances the competition between colonies by promoting antibiotic diversity. These results show that genomic organization can co-evolve with genomic instabilities to enable reproductive division of labor.

Evolution has traditionally been a historical and descriptive science, and predicting future evolutionary processes has long been considered impossible. However, evolutionary predictions are increasingly being developed and used in medicine, agriculture, biotechnology and conservation biology. Evolutionary predictions may be used for different purposes, such as to prepare for the future, to try and change the course of evolution or to determine how well we understand evolutionary processes. Similarly, the exact aspect of the evolved population that we want to predict may also differ. For example, we could try to predict which genotype will dominate, the fitness of the population or the extinction probability of a population. In addition, there are many uses of evolutionary predictions that may not always be recognized as such. The main goal of this review is to increase awareness of methods and data in different research fields by showing the breadth of situations in which evolutionary predictions are made. We describe how diverse evolutionary predictions share a common structure described by the predictive scope, time scale and precision. Then, by using examples ranging from SARS‐CoV2 and influenza to CRISPR‐based gene drives and sustainable product formation in biotechnology, we discuss the methods for predicting evolution, the factors that affect predictability and how predictions can be used to prevent evolution in undesirable directions or to promote beneficial evolution (i.e. evolutionary control). We hope that this review will stimulate collaboration between fields by establishing a common language for evolutionary predictions.

Phages are highly abundant in the environment and pose a major threat for bacteria. Therefore, bacteria have evolved sophisticated defence systems to withstand phage attacks. Here, we describe a previously unknown mechanism by which mono- and diderm bacteria survive infection with diverse lytic phages. Phage exposure leads to a rapid and near-complete conversion of walled cells to a cell-wall-deficient state, which remains viable in osmoprotective conditions and can revert to the walled state. While shedding the cell wall dramatically reduces the number of progeny phages produced by the host, it does not always preclude phage infection. Altogether, these results show that the formation of cell-wall-deficient cells prevents complete eradication of the bacterial population and suggest that cell wall deficiency may potentially limit the efficacy of phage therapy, especially in highly osmotic environments or when used together with antibiotics that target the cell wall.

In colonies of the filamentous multicellular bacterium Streptomyces coelicolor , a subpopulation of cells arises that hyperproduces metabolically costly antibiotics, resulting in a division of labor that increases colony fitness. Because these cells contain large genomic deletions that cause massive reductions to individual fitness, their behavior is similar to altruistic worker castes in social insects or somatic cells in multicellular organisms. To understand these mutant cells’ reproductive and genomic fate after their emergence, we use experimental evolution by serially transferring populations via spore-to-spore transfer for 25 cycles, reflective of the natural mode of bottlenecked transmission for these spore-forming bacteria. We show that in contrast to wild-type cells, putatively altruistic mutant cells continue to decline in fitness during transfer while they lose more fragments from their chromosome ends. In addition, the base-substitution rate in mutants increases roughly 10-fold, possibly due to mutations in genes for DNA replication and repair. Ecological damage, caused by reduced sporulation, coupled with DNA damage due to point mutations and deletions, leads to an inevitable and irreversible type of mutational meltdown in these cells. Taken together, these results suggest the cells arising in the S. coelicolor division of labor are analogous to altruistic reproductively sterile castes of social insects.

Collateral sensitivity (CS), which arises when resistance to one antibiotic increases sensitivity toward other antibiotics, offers treatment opportunities to constrain or reverse the evolution of antibiotic resistance. The applicability of CS-informed treatments remains uncertain, in part because we lack an understanding of the generality of CS effects for different resistance mutations, singly or in combination. Here, we address this issue in the gram-positive pathogen Streptococcus pneumoniae by measuring collateral and fitness effects of clinically relevant gyrA and parC alleles and their combinations that confer resistance to fluoroquinolones. We integrated these results in a mathematical model that allowed us to evaluate how different in silico combination treatments impact the dynamics of resistance evolution. We identified common and conserved CS effects of different gyrA and parC alleles; however, the spectrum of collateral effects was unique for each allele or allelic pair. This indicated that allelic identity can impact the evolutionary dynamics of resistance evolution during monotreatment and combination treatment. Our model simulations, which included the experimentally derived antibiotic susceptibilities and fitness effects, and antibiotic-specific pharmacodynamics revealed that both collateral and fitness effects impact the population dynamics of resistance evolution. Overall, we provide evidence that allelic identity and interactions can have a pronounced impact on collateral effects to different antibiotics and suggest that these need to be considered in models examining CS-based therapies.

Division of labour occurs when different individuals, cells or tissues become specialised to perform complementary tasks that benefit the whole organism or social group. Although long studied in multicellular organisms and colonies of social insects, several recent studies have established that division of labour is common in microorganisms. We review recent work on the division of labour in unicellular and multicellular bacteria, with a particular focus on reproductive and metabolic divisions of labour in actinomycetes. Actinomycetes show enormous variation in sporophore morphology and spore production patterns that likely affect the potential for cooperative interactions within colonies. They also display both irreversible genetic and spatiotemporally regulated phenotypic divisions of labour that structure antibiotic production. We highlight outstanding questions in this group of multicellular bacteria and outline factors that can modify the expression of division of labour across microbes.

Fusion of cells is an important and common biological process that leads to the mixing of cellular contents and the formation of multinuclear cells. Cell fusion occurs when distinct membranes are brought into proximity of one another and merge to become one. Fusion holds promise for biotechnological innovations, for instance, for the discovery of urgently needed new antibiotics. Here, we used antibiotic-producing bacteria that can proliferate without their cell wall as a model to investigate cell-cell fusion. We found that fusion between genetically distinct cells yields heterokaryons that are viable, contain multiple selection markers, and show increased antimicrobial activity. The rate of fusion induced using physical and chemical methods was dependent on membrane fluidity, which is related to lipid composition as a function of cellular age. Finally, by using an innovative system of synthetic membrane-associated lipopeptides, we achieved targeted fusion between distinctly marked cells to further enhance fusion efficiency. These results provide a molecular handle to understand and control cell-cell fusion, which can be used in the future for the discovery of new drugs. IMPORTANCE Cell-cell fusion is instrumental in introducing different sets of genes in the same environment, which subsequently leads to diversity. There is need for new protocols to fuse cells of different types together for biotechnological applications like drug discovery. We present here wall-deficient cells as a platform for the same. We identify the fluidity of the membrane as an important characteristic for the process of fusion. We demonstrate a cell-specific approach for fusion using synthetically designed peptides yielding cells with modified antibiotic production profiles. Overall, wall-deficient cells can be a chassis for innovative metabolite production by providing an alternative method for cell-cell fusion.