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Given the multitude of challenges Earth is facing, sustainability science is of key importance to our continued existence. Evolution is the fundamental biological process underlying the origin of all biodiversity. This phylogenetic diversity fosters the resilience of ecosystems to environmental change, and provides numerous resources to society, and options for the future. Genetic diversity within species is also key to the ability of populations to evolve and adapt to environmental change. Yet, the value of evolutionary processes and the consequences of their impairment have not generally been considered in sustainability research. We argue that biological evolution is important for sustainability and that the concepts, theory, data, and methodological approaches used in evolutionary biology can, in crucial ways, contribute to achieving the UN Sustainable Development Goals (SDGs). We discuss how evolutionary principles are relevant to understanding, maintaining, and improving Nature Contributions to People (NCP) and how they contribute to the SDGs. We highlight specific applications of evolution, evolutionary theory, and evolutionary biology's diverse toolbox, grouped into four major routes through which evolution and evolutionary insights can impact sustainability. We argue that information on both within‐species evolutionary potential and among‐species phylogenetic diversity is necessary to predict population, community, and ecosystem responses to global change and to make informed decisions on sustainable production, health, and well‐being. We provide examples of how evolutionary insights and the tools developed by evolutionary biology can not only inspire and enhance progress on the trajectory to sustainability, but also highlight some obstacles that hitherto seem to have impeded an efficient uptake of evolutionary insights in sustainability research and actions to sustain SDGs. We call for enhanced collaboration between sustainability science and evolutionary biology to understand how integrating these disciplines can help achieve the sustainable future envisioned by the UN SDGs. [ABSTRACT FROM AUTHOR]

Classroom and staffroom floor swabs across six elementary schools in Ottawa, Canada were tested for SARS-CoV-2. Environmental test positivity did not correlate with student grade groups, school-level absenteeism, pediatric COVID-19-related hospitalizations, or community SARS-CoV-2 wastewater levels. Schools in neighbourhoods with historically elevated COVID-19 burden showed a negative but non-significant association with lower swab positivity. [ABSTRACT FROM AUTHOR]

Evolutionary biology was previously considered a historical science with predictions about evolutionary trajectories believed to be near impossible. The development of high throughput sequencing and data analysis technologies has challenged this belief, and provided an abundance of data that yields novel insights into evolutionary processes. Evolutionary predictions are now increasingly being used to develop fundamental knowledge of evolving systems and/or to demonstrate evolutionary control. Here we investigate the factors that make evolutionary repeatability more or less likely to increase the accuracy of evolutionary predictions. We identify outstanding questions and provide a potential starting point to determine how evolutionary repeatability is affected by genetic relatedness. [ABSTRACT FROM AUTHOR]

The evolution of antimicrobial resistance (AMR) in bacteria is a major public health concern, and antibiotic restriction is often implemented to reduce the spread of resistance. These measures rely on the existence of deleterious fitness effects (i.e. costs) imposed by AMR mutations during growth in the absence of antibiotics. According to this assumption, resistant strains will be outcompeted by susceptible strains that do not pay the cost during the period of restriction. The fitness effects of AMR mutations are generally studied in laboratory reference strains grown in standard growth environments; however, the genetic and environmental context can influence the magnitude and direction of a mutation's fitness effects. In this study, we measure how three sources of variation impact the fitness effects of Escherichia coli AMR mutations: the type of resistance mutation, the genetic background of the host, and the growth environment. We demonstrate that while AMR mutations are generally costly in antibiotic-free environments, their fitness effects vary widely and depend on complex interactions between the mutation, genetic background, and environment. We test the ability of the Rough Mount Fuji fitness landscape model to reproduce the empirical data in simulation. We identify model parameters that reasonably capture the variation in fitness effects due to genetic variation. However, the model fails to accommodate the observed variation when considering multiple growth environments. Overall, this study reveals a wealth of variation in the fitness effects of resistance mutations owing to genetic background and environmental conditions, which will ultimately impact their persistence in natural populations. [ABSTRACT FROM AUTHOR]

Genetic background has the potential to influence both the tempo and trajectory of adaptive change: Different genotypes of a given species may adopt varied solutions to the same environmental challenge, or they may approach the same solution at different rates. Laboratory selection has been widely used to experimentally examine the evolutionary consequences of variation in genetic background, although largely using genotypes differing by only a few mutations. Here, we leverage natural variation in the bacterium Pseudomonas aeruginosa to investigate whether different adaptive solutions are accessible from distant points of departure on an adaptive landscape. We evolved 17 diverse genotypes in a laboratory medium that partially mimics the lung sputum of cystic fibrosis patients, and we measured changes in 10 phenotypes as well as in fitness. Using phylogenetically informed analyses, we found that genetic background impacted the tempo, but not the trajectory, of phenotypic evolution: Different starting genotypes converged toward similar phenotypes, but at varying rates. Our findings add to a growing body of evidence supporting widespread diminishing return epistasis during adaptation. The importance of genetic background toward the trajectory of adaptation remains inconsistent across experimental systems and conditions. [ABSTRACT FROM AUTHOR]

Ecological interactions are crucial to the structure and function of biological communities, but we lack a causal understanding of the forces shaping their emergence during evolutionary diversification. Here we provide a conceptual framework linking different modes of diversification (e.g., ecological diversification), which depend on environmental characteristics, to the evolution of different forms of ecological interactions (e.g., resource partitioning) in asexual lineages. We tested the framework by examining the net interactions in communities of Pseudomonas aeruginosa produced via experimental evolution in nutritionally simple (SIM) or complex (COM) environments by contrasting the productivity and competitive fitness of whole evolved communities relative to their component isolates. As expected, we found that nutritional complexity drove the evolution of communities with net positive interactions whereas SIM communities had similar performance as their component isolates. A follow-up experiment revealed that high fitness in two COM communities was driven by rare variants (frequency <0.1%) that antagonized PA14, the ancestral strain and common competitor used in fitness assays. Our study suggests that the evolution of de novo ecological interactions in asexual lineages is predictable at a broad scale from environmental conditions. Further, our work demonstrates that rare variants can disproportionately impact the function of relatively simple microbial communities. [ABSTRACT FROM AUTHOR]

Whether and how the spatial arrangement of a population influences adaptive evolution has puzzled evolutionary biologists. Theoretical models make conflicting predictions about the probability that a beneficial mutation will become fixed in a population for certain topologies like stars, in which "leaf" populations are connected through a central "hub." To date, these predictions have not been evaluated under realistic experimental conditions. Here, we test the prediction that topology can change the dynamics of fixation both in vitro and in silico by tracking the frequency of a beneficial mutant under positive selection as it spreads through networks of different topologies. Our results provide empirical support that meta-population topology can increase the likelihood that a beneficial mutation spreads, broaden the conditions under which this phenomenon is thought to occur, and points the way toward using network topology to amplify the effects of weakly favored mutations under directed evolution in industrial applications. Lay Summary: Most natural populations are spatially structured, meaning that they are geographically subdivided and connected by migration. Whether spatial structure impacts adaptive evolution has been less clear as different theoretical approaches to modeling the spread of beneficial mutations through spatially structured populations make contrasting predictions. Our work uses evolution experiments and numerical simulations to show that spatial structure can impact the pace of adaptive evolution. Certain topologies, specifically a four-patch star with bidirectional migration through a central hub to each of three "leaf" populations, can accelerate the rate at which a beneficial mutation spreads through a population relative to an unstructured, well-mixed population. The cause of this acceleration is a reduced probability that beneficial mutations are stochastically lost when rare because they get concentrated in the central hub and then disperse outwards to the leaves. Our results offer the first experimental support for models of adaptive evolution in space based on evolutionary graph theory, may help understand the spread of invasive species or pathogens, and could be used in industrial settings to selectively enrich desired traits or biomolecules of interest. [ABSTRACT FROM AUTHOR]

Professor Louis Bernatchez, a renowned figure in genomics applied to the conservation and management of aquatic resources, has passed away at the age of 63. He was the Editor-in-Chief for Evolutionary Applications and made significant contributions to the journal. Professor Bernatchez's work focused on microevolution's role in macroevolution using sympatric Lake Whitefish species pairs, and he emphasized the integration of molecular genetics and ecology. His legacy includes advancements in phylogeography, functional genomics, and conservation genomics, and he was highly active in fish research with Indigenous communities in Canada. The text is a collection of personal reflections and tributes to Professor Bernatchez, highlighting his mentorship, support, and contributions to the field. The authors celebrate his lasting impact on the scientific community and express their sadness at his passing. [Extracted from the article]

Background: SARS-CoV-2 can be detected from the built environment (e.g., floors), but it is unknown how the viral burden surrounding an infected patient changes over space and time. Characterizing these data can help advance our understanding and interpretation of surface swabs from the built environment. Methods: We conducted a prospective study at two hospitals in Ontario, Canada between January 19, 2022 and February 11, 2022. We performed serial floor sampling for SARS-CoV-2 in rooms of patients newly hospitalized with COVID-19 in the past 48 hours. We sampled the floor twice daily until the occupant moved to another room, was discharged, or 96 hours had elapsed. Floor sampling locations included 1 metre (m) from the hospital bed, 2 m from the hospital bed, and at the room's threshold to the hallway (typically 3 to 5 m from the hospital bed). The samples were analyzed for the presence of SARS-CoV-2 using quantitative reverse transcriptase polymerase chain reaction (RT-qPCR). We calculated the sensitivity of detecting SARS-CoV-2 in a patient with COVID-19, and we evaluated how the percentage of positive swabs and the cycle threshold of the swabs changed over time. We also compared the cycle threshold between the two hospitals. Results: Over the 6-week study period we collected 164 floor swabs from the rooms of 13 patients. The overall percentage of swabs positive for SARS-CoV-2 was 93% and the median cycle threshold was 33.4 (interquartile range [IQR]: 30.8, 37.2). On day 0 of swabbing the percentage of swabs positive for SARS-CoV-2 was 88% and the median cycle threshold was 33.6 (IQR: 31.8, 38.2) compared to swabs performed on day 2 or later where the percentage of swabs positive for SARS-CoV-2 was 98% and the cycle threshold was 33.2 (IQR: 30.6, 35.6). We found that viral detection did not change with increasing time (since the first sample collection) over the sampling period, Odds Ratio (OR) 1.65 per day (95% CI 0.68, 4.02; p = 0.27). Similarly, viral detection did not change with increasing distance from the patient's bed (1 m, 2 m, or 3 m), OR 0.85 per metre (95% CI 0.38, 1.88; p = 0.69). The cycle threshold was lower (i.e., more virus) in The Ottawa Hospital (median quantification cycle [Cq] 30.8) where floors were cleaned once daily compared to the Toronto hospital (median Cq 37.2) where floors were cleaned twice daily. Conclusions: We were able to detect SARS-CoV-2 on the floors in rooms of patients with COVID-19. The viral burden did not vary over time or by distance from the patient's bed. These results suggest floor swabbing for the detection of SARS-CoV-2 in a built environment such as a hospital room is both accurate and robust to variation in sampling location and duration of occupancy. [ABSTRACT FROM AUTHOR]

Background: Environmental surveillance of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) through wastewater has become a useful tool for population-level surveillance. Built environment sampling may provide a more spatially refined approach for surveillance in congregate living settings. Methods: We conducted a prospective study in 10 long-term care homes (LTCHs) between September 2021 and November 2022. Floor surfaces were sampled weekly at multiple locations within each building and analyzed for the presence of SARS-CoV-2 using quantitative reverse transcriptase polymerase chain reaction. The primary outcome was the presence of a coronavirus disease 2019 (Covid-19) outbreak in the week that floor sampling was performed. Results: Over the 14-month study period, we collected 4895 swabs at 10 LTCHs. During the study period, 23 Covid-19 outbreaks occurred with 119 cumulative weeks under outbreak. During outbreak periods, the proportion of floor swabs that were positive for SARS-CoV-2 was 54.3% (95% confidence interval [CI], 52 to 56.6), and during non-outbreak periods it was 22.3% (95% CI, 20.9 to 23.8). Using the proportion of floor swabs positive for SARS-CoV-2 to predict Covid-19 outbreak status in a given week, the area under the receiver-operating characteristic curve was 0.84 (95% CI, 0.78 to 0.9). Among 10 LTCHs with an outbreak and swabs performed in the prior week, eight had positive floor swabs exceeding 10% at least 5 days before outbreak identification. For seven of these eight LTCHs, positivity of floor swabs exceeded 10% more than 10 days before the outbreak was identified. Conclusions: Detection of SARS-CoV-2 on floors is strongly associated with Covid-19 outbreaks in LTCHs. These data suggest a potential role for floor sampling in improving early outbreak identification. Wastewater testing has proven to be a valuable tool for forecasting Covid-19 outbreaks. Fralick et al. now report that swabbing of surfaces (i.e., floors) for SARS-CoV-2 may provide a similar benefit for predicting outbreaks in long-term care homes. [ABSTRACT FROM AUTHOR]

Pseudomonas aeruginosa is among the most problematic opportunistic pathogens for adults with cystic fibrosis (CF), causing repeated and resilient infections in the lung and surrounding airways. Evidence suggests that long-term infections are associated with diversification into specialized types but the underlying cause of that diversification and the effect it has on the persistence of infections remains poorly understood. Here, we use evolve-and-resequence experiments to investigate the genetic changes accompanying rapid, de novo phenotypic diversification in lab environments designed to mimic two aspects of human lung ecology: spatial structure and complex nutritional content. After ∼220 generations of evolution, we find extensive genetic variation present in all environments, including those that most closely resemble the CF lung. We use the abundance and frequency of nonsynonymous and synonymous mutations to estimate the ratio of mutations that are selectively neutral (hitchhikers) to those that are under positive selection (drivers). A significantly lower proportion of driver mutations in spatially structured populations suggests that reduced dispersal generates subpopulations with reduced effective population size, decreasing the supply of beneficial mutations and causing more divergent evolutionary trajectories. In addition, we find mutations in a handful of genes typically associated with chronic infection in the CF lung, including one gene associated with antibiotic resistance. This demonstrates that many of the genetic changes considered to be hallmarks of CF lung adaptation can arise as a result of adaptation to a novel environment and do not necessarily require antimicrobial treatment, immune system suppression, or competition from other microbial species to occur. [ABSTRACT FROM AUTHOR]

Synonymous mutations are often assumed to be neutral with respect to fitness because they do not alter the encoded amino acid and so cannot be "seen" by natural selection. Yet a growing body of evidence suggests that synonymous mutations can have fitness effects that drive adaptive evolution through their impacts on gene expression and protein folding. Here, we review what microbial experiments have taught us about the contribution of synonymous mutations to adaptation. A survey of site-directed mutagenesis experiments reveals the distributions of fitness effects for nonsynonymous and synonymous mutations are more similar, especially for beneficial mutations, than expected if all synonymous mutations were neutral, suggesting they should drive adaptive evolution more often than is typically observed. A review of experimental evolution studies where synonymous mutations have contributed to adaptation shows they can impact fitness through a range of mechanisms including the creation of illicit RNA polymerase binding sites impacting transcription and changes to mRNA folding stability that modulate translation. We suggest that clonal interference in evolving microbial populations may be the reason synonymous mutations play a smaller role in adaptive evolution than expected based on their observed fitness effects. We finish by discussing the impacts of falsely assuming synonymous mutations are neutral and discuss directions for future work exploring the role of synonymous mutations in adaptive evolution. [ABSTRACT FROM AUTHOR]

Abstract Background Bacteria excrete costly toxins to defend their ecological niche. The evolution of such antagonistic interactions between individuals is expected to depend on both the social environment and the strength of resource competition. Antagonism is expected to be weak among highly similar genotypes because most individuals are immune to antagonistic agents and among dissimilar genotypes because these are unlikely to be competing for the same resources and antagonism should not yield much benefit. The strength of antagonism is therefore expected to peak at intermediate genetic distance. Results We studied the ability of laboratory strains of Pseudomonas aeruginosa to prevent growth of 55 different clinical P. aeruginosa isolates derived from cystic fibrosis patients. Genetic distance was determined using genetic fingerprints. We found that the strength of antagonism was maximal among genotypes of intermediate genetic distance and we show that genetic distance and resource use are linked. Conclusions Our results suggest that the importance of social interactions like antagonism may be modulated by the strength of resource competition.

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The importance of interference competition, where individuals compete through antagonistic traits such as the production of toxins, has long been recognized by ecologists, yet understanding how these types of interactions evolve remains limited. Toxin production is thought to be beneficial when competing with a competitor. Here, we explore if antagonism can evolve by long-term selection of the toxin (pyocin) producing strain Pseudomonas aeruginosa PAO1 in the presence (or absence) of one of three clinical isolates of the same species (Recipient) over ten serial transfers. We find that inhibition decreases in the absence of a recipient. In the presence of a recipient, antagonism evolved to be different depending on the recipient used. Our study shows that the evolution of interference competition by toxins can decrease or increase, experimentally demonstrating the importance of this type of interaction for the evolution of species interactions. [ABSTRACT FROM AUTHOR]

The comparative genomics of the transition of the opportunistic pathogen Pseudomonas aeruginosa from a free-living environmental strain to one that causes chronic infection in the airways of cystic fibrosis (CF) patients remain poorly studied. Chronic infections are thought to originate from colonization by a single strain sampled from a diverse, globally distributed population, followed by adaptive evolution to the novel, stressful conditions of the CF lung. However, we do not know whether certain clades are more likely to form chronic infections than others and we lack a comprehensive view of the suite of genes under positive selection in the CF lung. We analyzed whole-genome sequence data from 1,000  P. aeruginosa strains with diverse ecological provenances including the CF lung. CF isolates were distributed across the phylogeny, indicating little genetic predisposition for any one clade to cause chronic infection. Isolates from the CF niche experienced stronger positive selection on core genes than those derived from environmental or acute infection sources, consistent with recent adaptation to the lung environment. Genes with the greatest differential positive selection in the CF niche include those involved in core cellular processes such as metabolism, energy production, and stress response as well as those linked to patho-adaptive processes such as antibiotic resistance, cell wall and membrane modification, quorum sensing, biofilms, mucoidy, motility, and iron homeostasis. Many genes under CF-specific differential positive selection had regulatory functions, consistent with the idea that regulatory mutations play an important role in rapid adaptation to novel environments. [ABSTRACT FROM AUTHOR]

The ultimate causes of correlated evolution among sites in a genome remain difficult to tease apart. To address this problem directly, we performed a high‐throughput search for correlated evolution among sites associated with resistance to a fluoroquinolone antibiotic using whole‐genome data from clinical strains of Pseudomonas aeruginosa, before validating our computational predictions experimentally. We show that for at least two sites, this correlation is underlain by epistasis. Our analysis also revealed eight additional pairs of synonymous substitutions displaying correlated evolution underlain by physical linkage, rather than selection associated with antibiotic resistance. Our results provide direct evidence that both epistasis and physical linkage among sites can drive the correlated evolution identified by high‐throughput computational tools. In other words, the observation of correlated evolution is not by itself sufficient evidence to guarantee that the sites in question are epistatic; such a claim requires additional evidence, ideally coming from direct estimates of epistasis, based on experimental evidence. [ABSTRACT FROM AUTHOR]

Social interactions have been invoked as potential major selective forces structuring natural microbial communities and thus may help explain the astonishing bacterial diversity of natural ecosystems. Here, we investigate the prevalence and structure of exotoxin-mediated antagonistic interactions among free-living soil Pseudomonas strains collected over the course of 2 years at distances of up to 1 km. Unlike some previous studies on antagonistic interactions among natural isolates, we found the prevalence of exotoxin-mediated inhibitions to be relatively low. When present, antagonistic interactions show a weakly positive relationship with genetic relatedness and metabolic similarity. Isolates sampled from the same growing season were significantly more likely to inhibit each other than they were to inhibit isolates from different growing seasons. Exotoxin-mediated antagonistic interactions between soil pseudomonads thus seem to be structured in time but do not appear to be a major selective force shaping free-living soil bacterial communities of pseudomonads. [ABSTRACT FROM AUTHOR]

Oxidative stress is a major cause of mutation but little is known about how growth in the absence of oxygen impacts the rate and spectrum of mutations. We employed long-term mutation accumulation experiments to directly measure the rates and spectra of spontaneous mutation events in Escherichia coli populations propagated under aerobic and anaerobic conditions. To detect mutations, whole genome sequencing was coupled with methods of analysis sufficient to identify a broad range of mutational classes, including structural variants (SVs) generated by movement of repetitive elements. The anaerobically grown populations displayed a mutation rate nearly twice that of the aerobic populations, showed distinct asymmetric mutational strand biases, and greater insertion element activity. Consistent with mutation rate and spectra observations, genes for transposition and recombination repair associated with SVs were up-regulated during anaerobic growth. Together, these results define differences in mutational spectra affecting the evolution of facultative anaerobes. [ABSTRACT FROM AUTHOR]

Our data and the available literature suggest that environmental surveillance may have an important role to play in pathogen surveillance, especially for areas where wastewater surveillance is impractical or prohibitively expensive. 2022;194:E1250-4. 2 Hinz A, Xing L, Doukhanine E. SARS-CoV-2 detection from the built environment and wastewater and its use for hospital surveillance. The authors highlighted that wastewater surveillance has been an innovative public health tool and can detect early transmission of SARS-CoV-2 in the community. [Extracted from the article]

Background: Natural genetic variation ultimately arises from the process of mutation. Knowledge of how the raw material for evolution is produced is necessary for a full understanding of several fundamental evolutionary concepts. We performed a mutation accumulation experiment with wild-type and mismatch-repair deficient, mutator lines of the pathogenic bacterium Pseudomonas aeruginosa, and used whole-genome sequencing to reveal the genome-wide rate, spectrum, distribution, leading/lagging bias, and context-dependency of spontaneous mutations. Results: Wild-type base-pair mutation and indel rates were ~10-10 and ~10-11 per nucleotide per generation, respectively, and deficiencies in the mismatch-repair system caused rates to increase by over two orders of magnitude. A universal bias towards AT was observed in wild-type lines, but was reversed in mutator lines to a bias towards GC. Biases for which types of mutations occurred during replication of the leading versus lagging strand were detected reciprocally in both replichores. The distribution of mutations along the chromosome was non-random, with peaks near the terminus of replication and at positions intermediate to the replication origin and terminus. A similar distribution bias was observed along the chromosome in natural populations of P. aeruginosa. Site-specific mutation rates were higher when the focal nucleotide was immediately flanked by C:G pairings. Conclusions: Whole-genome sequencing of mutation accumulation lines allowed the comprehensive identification of mutations and revealed what factors of molecular and genomic architecture affect the mutational process. Our study provides a more complete view of how several mechanisms of mutation, mutation repair, and bias act simultaneously to produce the raw material for evolution. [ABSTRACT FROM AUTHOR]