Identifying and tracking mobile elements in evolving compost communities yields insights into the nanobiome.

Microbial evolution is driven by rapid changes in gene content mediated by horizontal gene transfer (HGT). While mobile genetic elements (MGEs) are important drivers of gene flux, the nanobiome-the zoo of Darwinian replicators that depend on microbial hosts-remains poorly characterised. New approaches are necessary to increase our understanding beyond MGEs shaping individual populations, towards their impacts on complex microbial communities. A bioinformatic pipeline (xenoseq) was developed to cross-compare metagenomic samples from microbial consortia evolving in parallel, aimed at identifying MGE dissemination, which was applied to compost communities which underwent periodic mixing of MGEs. We show that xenoseq can distinguish movement of MGEs from demographic changes in community composition that otherwise confounds identification, and furthermore demonstrate the discovery of various unexpected entities. Of particular interest was a nanobacterium of the candidate phylum radiation (CPR) which is closely related to a species identified in groundwater ecosystems (Candidatus Saccharibacterium), and appears to have a parasitic lifestyle. We also highlight another prolific mobile element, a 313 kb plasmid hosted by a Cellvibrio lineage. The host was predicted to be capable of nitrogen fixation, and acquisition of the plasmid coincides with increased ammonia production. Taken together, our data show that new experimental strategies combined with bioinformatic analyses of metagenomic data stand to provide insight into the nanobiome as a driver of microbial community evolution.

Barcoding Populations of Pseudomonas fluorescens SBW25.

In recent years, evolutionary biologists have developed an increasing interest in the use of barcoding strategies to study eco-evolutionary dynamics of lineages within evolving populations and communities. Although barcoded populations can deliver unprecedented insight into evolutionary change, barcoding microbes presents specific technical challenges. Here, strategies are described for barcoding populations of the model bacterium Pseudomonas fluorescens SBW25, including the design and cloning of barcoded regions, preparation of libraries for amplicon sequencing, and quantification of resulting barcoded lineages. In so doing, we hope to aid the design and implementation of barcoding methodologies in a broad range of model and non-model organisms.

The Fitness of Beta-Lactamase Mutants Depends Nonlinearly on Resistance Level at Sublethal Antibiotic Concentrations.

Adaptive evolutionary processes are constrained by the availability of mutations which cause a fitness benefit and together make up the fitness landscape, which maps genotype space onto fitness under specified conditions. Experimentally derived fitness landscapes have demonstrated a predictability to evolution by identifying limited "mutational routes" that evolution by natural selection may take between low and high-fitness genotypes. However, such studies often utilize indirect measures to determine fitness. We estimated the competitive fitness of mutants relative to all single-mutation neighbors to describe the fitness landscape of three mutations in a ß-lactamase enzyme. Fitness assays were performed at sublethal concentrations of the antibiotic cefotaxime in a structured and unstructured environment. In the unstructured environment, the antibiotic selected for higher-resistance types-but with an equivalent fitness for a subset of mutants, despite substantial variation in resistance-resulting in a stratified fitness landscape. In contrast, in a structured environment with a low antibiotic concentration, antibiotic-susceptible genotypes had a relative fitness advantage, which was associated with antibiotic-induced filamentation. These results cast doubt that highly resistant genotypes have a unique selective advantage in environments with subinhibitory concentrations of antibiotics and demonstrate that direct fitness measures are required for meaningful predictions of the accessibility of evolutionary routes. IMPORTANCE The evolution of antibiotic-resistant bacterial populations underpins the ongoing antibiotic resistance crisis. We aim to understand how antibiotic-degrading enzymes can evolve to cause increased resistance, how this process is constrained, and whether it can be predictable. To this end, competition experiments were performed with a combinatorially complete set of mutants of a ß-lactamase gene subject to subinhibitory concentrations of the antibiotic cefotaxime. While some mutations confer on their hosts high resistance to cefotaxime, in competition these mutations do not always confer a selective advantage. Specifically, high-resistance mutants had equivalent fitnesses despite different resistance levels and even had selective disadvantages under conditions involving spatial structure. Together, our findings suggest that the relationship between resistance level and fitness at subinhibitory concentrations is complex; predicting the evolution of antibiotic resistance requires knowledge of the conditions that select for resistant genotypes and the selective advantage evolved types have over their predecessors.

Minimal Surviving Inoculum in Collective Antibiotic Resistance.

A common strategy used by bacteria to resist antibiotics is enzymatic degradation or modification. This reduces the antibiotic threat in the environment and is therefore potentially a collective mechanism that also enhances the survival of nearby cells. Collective resistance is of clinical significance, yet a quantitative understanding at the population level is still incomplete. Here, we develop a general theoretical framework of collective resistance by antibiotic degradation. Our modeling study reveals that population survival crucially depends on the ratio of timescales of two processes: the rates of population death and antibiotic removal. However, it is insensitive to molecular, biological, and kinetic details of the underlying processes that give rise to these timescales. Another important aspect of antibiotic degradation is the degree of cooperativity, related to the permeability of the cell wall to antibiotics and enzymes. These observations motivate a coarse-grained, phenomenological model, with two compound parameters representing the population's race to survival and single-cell effective resistance. We propose a simple experimental assay to measure the dose-dependent minimal surviving inoculum and apply it to Escherichia coli expressing several types of ß-lactamase. Experimental data analyzed within the theoretical framework corroborate it with good agreement. Our simple model may serve as a reference for more complex situations, such as heterogeneous bacterial communities. IMPORTANCE Collective resistance occurs when bacteria work together to decrease the concentration of antibiotics in their environment, for example, by actively breaking down or modifying them. This can help bacteria survive by reducing the effective antibiotic concentration below their threshold for growth. In this study, we used mathematical modeling to examine the factors that influence collective resistance and to develop a framework to understand the minimum population size needed to survive a given initial antibiotic concentration. Our work helps to identify generic mechanism-independent parameters that can be derived from population data and identifies combinations of parameters that play a role in collective resistance. Specifically, it highlights the relative timescales involved in the survival of populations that inactivate antibiotics, as well as the levels of cooperation versus privatization. The results of this study contribute to our understanding of population-level effects on antibiotic resistance and may inform the design of antibiotic therapies.

Population dynamics of cross-protection against ß-lactam antibiotics in droplet microreactors.

Introduction: Bacterial strains that are resistant to antibiotics may protect not only themselves, but also sensitive bacteria nearby if resistance involves antibiotic degradation. Such cross-protection poses a challenge to effective antibiotic therapy by enhancing the long-term survival of bacterial infections, however, the current understanding is limited. Methods: In this study, we utilize an automated nanoliter droplet analyzer to study the interactions between Escherichia coli strains expressing a ß-lactamase (resistant) and those not expressing it (sensitive) when exposed to the ß-lactam antibiotic cefotaxime (CTX), with the aim to define criteria contributing to cross-protection. Results: We observed a cross-protection window of CTX concentrations for the sensitive strain, extending up to approximately 100 times its minimal inhibitory concentration (MIC). Through both microscopy and enzyme activity analyses, we demonstrate that bacterial filaments, triggered by antibiotic stress, contribute to cross-protection. Discussion: The antibiotic concentration window for cross-protection depends on the difference in ß-lactamase activity between co-cultured strains: larger differences shift the 'cross-protection window' toward higher CTX concentrations. Our findings highlight the dependence of opportunities for cross-protection on the relative resistance levels of the strains involved and suggest a possible specific role for filamentation.

Adaptive evolution by spontaneous domain fusion and protein relocalization.

Knowledge of adaptive processes encompasses understanding the emergence of new genes. Computational analyses of genomes suggest that new genes can arise by domain swapping; however, empirical evidence has been lacking. Here we describe a set of nine independent deletion mutations that arose during selection experiments with the bacterium Pseudomonas fluorescens in which the membrane-spanning domain of a fatty acid desaturase became translationally fused to a cytosolic di-guanylate cyclase, generating an adaptive 'wrinkly spreader' phenotype. Detailed genetic analysis of one gene fusion shows that the mutant phenotype is caused by relocalization of the di-guanylate cyclase domain to the cell membrane. The relative ease by which this new gene arose, along with its functional and regulatory effects, provides a glimpse of mutational events and their consequences that are likely to have a role in the evolution of new genes.

Darwin was right: where now for experimental evolution?

Over the last two decades interest in direct realisation of evolutionary process and the possibilities presented by real time evolution experiments with microbes have escalated. Long-term selection experiments with bacteria have made increasingly transparent the process of evolution by natural selection. In this short article we consider what next for the field and do so by highlighting two areas of interest: the genotype-to-phenotype map and the constraints it imposes on evolution, and studies on major evolutionary transitions and in particular the importance of selection working over more than one timescale. The latter we discuss in light of new technologies that allow imposition of Darwinian properties on populations and communities and how this allows exploration of new avenues of research. We conclude by commenting on microbial communities and the operation of evolutionary processes that are likely intrinsic-and specific-to communities.

Evolutionary convergence in experimental Pseudomonas populations.

Model microbial systems provide opportunity to understand the genetic bases of ecological traits, their evolution, regulation and fitness contributions. Experimental populations of Pseudomonas fluorescens rapidly diverge in spatially structured microcosms producing a range of surface-colonising forms. Despite divergent molecular routes, wrinkly spreader (WS) niche specialist types overproduce a cellulosic polymer allowing mat formation at the air-liquid interface and access to oxygen. Given the range of ways by which cells can form mats, such phenotypic parallelism is unexpected. We deleted the cellulose-encoding genes from the ancestral genotype and asked whether this mutant could converge on an alternate phenotypic solution. Two new traits were discovered. The first involved an exopolysaccharide encoded by pgaABCD that functions as cell-cell glue similar to cellulose. The second involved an activator of an amidase (nlpD) that when defective causes cell chaining. Both types form mats, but were less fit in competition with cellulose-based WS types. Surprisingly, diguanylate cyclases linked to cellulose overexpression underpinned evolution of poly-beta-1,6-N-acetyl-d-glucosamine (PGA)-based mats. This prompted genetic analyses of the relationships between the diguanylate cyclases WspR, AwsR and MwsR, and both cellulose and PGA. Our results suggest that c-di-GMP regulatory networks may have been shaped by evolution to accommodate loss and gain of exopolysaccharide modules facilitating adaptation to new environments.

Experimental evolution reveals hidden diversity in evolutionary pathways.

Replicate populations of natural and experimental organisms often show evidence of parallel genetic evolution, but the causes are unclear. The wrinkly spreader morph of Pseudomonas fluorescens arises repeatedly during experimental evolution. The mutational causes reside exclusively within three pathways. By eliminating these, 13 new mutational pathways were discovered with the newly arising WS types having fitnesses similar to those arising from the commonly passaged routes. Our findings show that parallel genetic evolution is strongly biased by constraints and we reveal the genetic bases. From such knowledge, and in instances where new phenotypes arise via gene activation, we suggest a set of principles: evolution proceeds firstly via pathways subject to negative regulation, then via promoter mutations and gene fusions, and finally via activation by intragenic gain-of-function mutations. These principles inform evolutionary forecasting and have relevance to interpreting the diverse array of mutations associated with clinically identical instances of disease in humans.