Bacteria evolve macroscopic multicellularity by the genetic assimilation of phenotypically plastic cell clustering.

The evolutionary transition from unicellularity to multicellularity was a key innovation in the history of life. Experimental evolution is an important tool to study the formation of undifferentiated cellular clusters, the likely first step of this transition. Although multicellularity first evolved in bacteria, previous experimental evolution research has primarily used eukaryotes. Moreover, it focuses on mutationally driven (and not environmentally induced) phenotypes. Here we show that both Gram-negative and Gram-positive bacteria exhibit phenotypically plastic (i.e., environmentally induced) cell clustering. Under high salinity, they form elongated clusters of ~ 2 cm. However, under habitual salinity, the clusters disintegrate and grow planktonically. We used experimental evolution with Escherichia coli to show that such clustering can be assimilated genetically: the evolved bacteria inherently grow as macroscopic multicellular clusters, even without environmental induction. Highly parallel mutations in genes linked to cell wall assembly formed the genomic basis of assimilated multicellularity. While the wildtype also showed cell shape plasticity across high versus low salinity, it was either assimilated or reversed after evolution. Interestingly, a single mutation could genetically assimilate multicellularity by modulating plasticity at multiple levels of organization. Taken together, we show that phenotypic plasticity can prime bacteria for evolving undifferentiated macroscopic multicellularity.

Distribution of mutation rates challenges evolutionary predictability.

Natural selection is commonly assumed to act on extensive standing genetic variation. Yet, accumulating evidence highlights the role of mutational processes creating this genetic variation: to become evolutionarily successful, adaptive mutants must not only reach fixation, but also emerge in the first place, i.e. have a high enough mutation rate. Here, we use numerical simulations to investigate how mutational biases impact our ability to observe rare mutational pathways in the laboratory and to predict outcomes in experimental evolution. We show that unevenness in the rates at which mutational pathways produce adaptive mutants means that most experimental studies lack power to directly observe the full range of adaptive mutations. Modelling mutation rates as a distribution, we show that a substantially larger target size ensures that a pathway mutates more commonly. Therefore, we predict that commonly mutated pathways are conserved between closely related species, but not rarely mutated pathways. This approach formalizes our proposal that most mutations have a lower mutation rate than the average mutation rate measured experimentally. We suggest that the extent of genetic variation is overestimated when based on the average mutation rate.

Towards evolutionary predictions: Current promises and challenges.

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.

Forecasting of phenotypic and genetic outcomes of experimental evolution in Pseudomonas protegens.

Experimental evolution with microbes is often highly repeatable under identical conditions, suggesting the possibility to predict short-term evolution. However, it is not clear to what degree evolutionary forecasts can be extended to related species in non-identical environments, which would allow testing of general predictive models and fundamental biological assumptions. To develop an extended model system for evolutionary forecasting, we used previous data and models of the genotype-to-phenotype map from the wrinkly spreader system in Pseudomonas fluorescens SBW25 to make predictions of evolutionary outcomes on different biological levels for Pseudomonas protegens Pf-5. In addition to sequence divergence (78% amino acid and 81% nucleotide identity) for the genes targeted by mutations, these species also differ in the inability of Pf-5 to make cellulose, which is the main structural basis for the adaptive phenotype in SBW25. The experimental conditions were changed compared to the SBW25 system to test if forecasts were extendable to a non-identical environment. Forty-three mutants with increased ability to colonize the air-liquid interface were isolated, and the majority had reduced motility and was partly dependent on the Pel exopolysaccharide as a structural component. Most (38/43) mutations are expected to disrupt negative regulation of the same three diguanylate cyclases as in SBW25, with a smaller number of mutations in promoter regions, including an uncharacterized polysaccharide synthase operon. A mathematical model developed for SBW25 predicted the order of the three main pathways and the genes targeted by mutations, but differences in fitness between mutants and mutational biases also appear to influence outcomes. Mutated regions in proteins could be predicted in most cases (16/22), but parallelism at the nucleotide level was low and mutational hot spot sites were not conserved. This study demonstrates the potential of short-term evolutionary forecasting in experimental populations and provides testable predictions for evolutionary outcomes in other Pseudomonas species.

Predicting mutational routes to new adaptive phenotypes.

Predicting evolutionary change poses numerous challenges. Here we take advantage of the model bacterium Pseudomonas fluorescens in which the genotype-to-phenotype map determining evolution of the adaptive 'wrinkly spreader' (WS) type is known. We present mathematical descriptions of three necessary regulatory pathways and use these to predict both the rate at which each mutational route is used and the expected mutational targets. To test predictions, mutation rates and targets were determined for each pathway. Unanticipated mutational hotspots caused experimental observations to depart from predictions but additional data led to refined models. A mismatch was observed between the spectra of WS-causing mutations obtained with and without selection due to low fitness of previously undetected WS-causing mutations. Our findings contribute toward the development of mechanistic models for forecasting evolution, highlight current limitations, and draw attention to challenges in predicting locus-specific mutational biases and fitness effects.

Probabilistic Models for Predicting Mutational Routes to New Adaptive Phenotypes.

Understanding the translation of genetic variation to phenotypic variation is a fundamental problem in genetics and evolutionary biology. The introduction of new genetic variation through mutation can lead to new adaptive phenotypes, but the complexity of the genotype-to-phenotype map makes it challenging to predict the phenotypic effects of mutation. Metabolic models, in conjunction with flux balance analysis, have been used to predict evolutionary optimality. These methods however rely on large scale models of metabolism, describe a limited set of phenotypes, and assume that selection for growth rate is the prime evolutionary driver. Here we describe a method for computing the relative likelihood that mutational change will translate into a phenotypic change between two molecular pathways. The interactions of molecular components in the pathways are modeled with ordinary differential equations. Unknown parameters are offset by probability distributions that describe the concentrations of molecular components, the reaction rates for different molecular processes, and the effects of mutations. Finally, the likelihood that mutations in a pathway will yield phenotypic change is estimated with stochastic simulations. One advantage of this method is that only basic knowledge of the interaction network underlying a phenotype is required. However, it can also incorporate available information about concentrations and reaction rates as well as mutational biases and mutational robustness of molecular components. The method estimates the relative probabilities that different pathways produce phenotypic change, which can be combined with fitness models to predict evolutionary outcomes.

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.

Variation in Mutational Robustness between Different Proteins and the Predictability of Fitness Effects.

Random mutations in genes from disparate protein classes may have different distributions of fitness effects (DFEs) depending on different structural, functional, and evolutionary constraints. We measured the fitness effects of 156 single mutations in the genes encoding AraC (transcription factor), AraD (enzyme), and AraE (transporter) used for bacterial growth on l-arabinose. Despite their different molecular functions these genes all had bimodal DFEs with most mutations either being neutral or strongly deleterious, providing a general expectation for the DFE. This contrasts with the unimodal DFEs previously obtained for ribosomal protein genes where most mutations were slightly deleterious. Based on theoretical considerations, we suggest that the 33-fold higher average mutational robustness of ribosomal proteins is due to stronger selection for reduced costs of translational and transcriptional errors. Whereas the large majority of synonymous mutations were deleterious for ribosomal proteins genes, no fitness effects could be detected for the AraCDE genes. Four mutations in AraC and AraE increased fitness, suggesting that slightly advantageous mutations make up a significant fraction of the DFE, but that they often escape detection due to the limited sensitivity of commonly used fitness assays. We show that the fitness effects of amino acid substitutions can be predicted based on evolutionary conservation, but those weakly deleterious mutations are less reliably detected. This suggests that large-effect mutations and the fraction of highly deleterious mutations can be computationally predicted, but that experiments are required to characterize the DFE close to neutrality, where many mutations ultimately fixed in a population will occur.

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.

Minor fitness costs in an experimental model of horizontal gene transfer in bacteria.

Genes introduced by horizontal gene transfer (HGT) from other species constitute a significant portion of many bacterial genomes, and the evolutionary dynamics of HGTs are important for understanding the spread of antibiotic resistance and the emergence of new pathogenic strains of bacteria. The fitness effects of the transferred genes largely determine the fixation rates and the amount of neutral diversity of newly acquired genes in bacterial populations. Comparative analysis of bacterial genomes provides insight into what genes are commonly transferred, but direct experimental tests of the fitness constraints on HGT are scarce. Here, we address this paucity of experimental studies by introducing 98 random DNA fragments varying in size from 0.45 to 5 kb from Bacteroides, Proteus, and human intestinal phage into a defined position in the Salmonella chromosome and measuring the effects on fitness. Using highly sensitive competition assays, we found that eight inserts were deleterious with selection coefficients (s) ranging from ≈ -0.007 to -0.02 and 90 did not have significant fitness effects. When inducing transcription from a PBAD promoter located at one end of the insert, 16 transfers were deleterious and 82 were not significantly different from the control. In conclusion, a major fraction of the inserts had minor effects on fitness implying that extra DNA transferred by HGT, even though it does not confer an immediate selective advantage, could be maintained at selection-transfer balance and serve as raw material for the evolution of novel beneficial functions.

Fitness costs of synonymous mutations in the rpsT gene can be compensated by restoring mRNA base pairing.

We previously reported that the distribution of fitness effects for non-synonymous and synonymous mutations in Salmonella typhimurium ribosomal proteins S20 and L1 are similar, suggesting that fitness constraints are present at the level of mRNA. Here we explore the hypothesis that synonymous mutations confer their fitness-reducing effect by alterating the secondary structure of the mRNA. To this end, we constructed a set of synonymous substitutions in the rpsT gene, encoding ribosomal protein S20, that are located in predicted paired regions in the mRNA and measured their effect on bacterial fitness. Our results show that for 3/9 cases tested, the reduced fitness conferred by a synonymous mutation could be fully or partly restored by introducing a second synonymous substitution that restore base pairing in a mRNA stem. In addition, random mutations in predicted paired regions had larger fitness effects than those in unpaired regions. Finally, we did not observe any correlation between fitness effects of the synonymous mutations and their rarity. These results suggest that for ribosomal protein S20, the deleterious effects of synonymous mutations are not generally due to codon usage effects, but that mRNA secondary structure is a major fitness constraint.

Mutational robustness of ribosomal protein genes.

The distribution of fitness effects (DFE) of mutations is of fundamental importance for understanding evolutionary dynamics and complex diseases and for conserving threatened species. DFEs estimated from DNA sequences have rarely been subject to direct experimental tests. We used a bacterial system in which the fitness effects of a large number of defined single mutations in two ribosomal proteins were measured with high sensitivity. The obtained DFE appears to be unimodal, where most mutations (120 out of 126) are weakly deleterious and the remaining ones are potentially neutral. The DFEs for synonymous and nonsynonymous substitutions are similar, suggesting that in some genes, strong fitness constraints are present at the level of the messenger RNA.

Compensatory gene amplification restores fitness after inter-species gene replacements.

Genes introduced by gene replacements and other types of horizontal gene transfer (HGT) represent a significant presence in many archaeal and eubacterial genomes. Most alien genes are likely to be neutral or deleterious upon arrival and their long-term persistence may require a mechanism that improves their selective contribution. To examine the fate of inter-species gene replacements, we exchanged three native S. typhimurium genes encoding ribosomal proteins with orthologues from various other microbes. The results show that replacement of each of these three genes reduces fitness to such an extent that it would provide an effective barrier against inter-species gene replacements in eubacterial populations. However, these fitness defects could be partially ameliorated by gene amplification that augmented the dosage of the heterologous proteins. This suggests that suboptimal expression is a common fitness constraint for inter-species gene replacements, with fitness costs conferred by either a lower expression level of the alien protein compared with the native protein or a requirement for an increased amount of the alien protein to maintain proper function. Our findings can explain the observation that duplicated genes are over-represented among horizontally transferred genes, and suggest a potential coupling between compensatory gene amplification after HGT and the evolution of new genes.

Whole-genome mutational biases in bacteria.

A fundamental biological question is what forces shape the guanine plus cytosine (GC) content of genomes. We studied the specificity and rate of different mutational biases in real time in the bacterium Salmonella typhimurium under conditions of strongly reduced selection and in the absence of the major DNA repair systems involved in repairing common spontaneous mutations caused by oxidized and deaminated DNA bases. The mutational spectrum was determined by whole-genome sequencing of two S. typhimurium mutants that were serially passaged for 5,000 generations. Analysis of 943 identified base pair substitutions showed that 91% were GC-to-TA transversions and 7% were GC-to-AT transitions, commonly associated with 8-oxoG- and deamination-induced damages, respectively. Other types of base pair substitutions constituted the remaining 2% of the mutations. With regard to mutational biases, there was a significant increase in C-to-T transitions on the nontranscribed strand, and for highly expressed genes, C/G-to-T mutations were more common than expected; however, no significant mutational bias with regard to leading and lagging strands of replication or chromosome position were found. These results suggest that, based on the experimentally determined mutational rates and specificities, a bacterial genome lacking the relevant DNA repair systems could, as a consequence of these underlying mutational biases, very rapidly reduce its GC content.