Experimental Design, Population Dynamics, and Diversity in Microbial Experimental Evolution

Adaptive laboratory evolution principles and applications in industrial biotechnology

Adaptive laboratory evolution (ALE) is an innovative approach for the generation of evolved microbial strains with desired characteristics, by implementing the rules of natural selection as presented in the Darwinian Theory, on the laboratory bench. New as it might be, it has already been used by several researchers for the amelioration of a variety of characteristics of widely used microorganisms in biotechnology. ALE is used as a tool for the deeper understanding of the genetic and/or metabolic pathways of evolution. Another important field targeted by ALE is the manufacturing of products of (high) added value, such as ethanol, butanol and lipids. In the current review, we discuss the basic principles and techniques of ALE, and then we focus on studies where it has been applied to bacteria, fungi and microalgae, aiming to improve their performance to biotechnological procedures and/or inspect the genetic background of evolution. We conclude that ALE is a promising and efficacious method that has already led to the acquisition of useful new microbiological strains in biotechnology and could possibly offer even more interesting results in the future.

Adaptation and correlated fitness responses over two time scales in Drosophila suzukii populations evolving in different environments

The process of local adaptation involves differential changes in fitness over time across different environments. Although experimental evolution studies have extensively tested for patterns of local adaptation at a single time point, there is relatively little research that examines fitness more than once during the time course of adaptation. We allowed replicate populations of the fruit pest Drosophila suzukii to evolve in one of eight different fruit media. After five generations, populations with the highest initial levels of maladaptation had mostly gone extinct, whereas experimental populations evolving on cherry, strawberry and cranberry media had survived. We measured the fitness of each surviving population in each of the three fruit media after five and after 26 generations of evolution. After five generations, adaptation to each medium was associated with increased fitness in the two other media. This was also true after 26 generations, except when populations that evolved on cranberry medium developed on cherry medium. These results suggest that, in the theoretical framework of a fitness landscape, the fitness optima of cherry and cranberry media are the furthest apart. Our results show that studying how fitness changes across several environments and across multiple generations provides insights into the dynamics of local adaptation that would not be evident if fitness were analysed at a single point in time. By allowing a qualitative mapping of an experimental fitness landscape, our approach will improve our understanding of the ecological factors that drive the evolution of local adaptation in D. suzukii.

Biotransformation of Daidzein, Genistein, and Naringenin by Streptomyces Species Isolated from High-Altitude Soil of Nepal

Flavonoids have achieved widespread importance in pharmaceutical, food, and cosmetics industries. Furthermore, modification of these naturally occurring flavonoids to structurally diverse compounds through whole cell biotransformation with enhanced biological activities has numerous biotechnological applications. The present study investigated the biotransformation potential of Streptomyces species isolated from a high-altitude-soil sample towards selected flavonoid molecules. The biotransformed metabolites were confirmed by comparing the HPLC chromatogram with authentic compounds and LC-MS/MS analysis. Of these isolates, Streptomyces species G-18 (Accession number: MW663767.1) catalyzed isoflavone molecules daidzein and genistein to produce hydroxylated products at 24 h of reaction condition in a whole cell system. The hydroxylation of daidzein (4′,7-dihydroxyisoflavone) was confirmed at 3′-position of the B ring to produce 3′,4′,7-trihydroxyisoflavone. In addition, Streptomyces species G-14 (Accession number: MW663770.1) and Streptomyces species S4L (Accession number: MW663769.1) also revealed the transformation of daidzein (4′,7-dihydroxyisoflavone) to hydroxy daidzein at a distinct position than that of G-18 isolates, whereas thee Streptomyces species S4L reaction mixture with naringenin as a substrate also revealed the hydroxylated product. Our results demonstrated that microorganisms isolated from different ecological niches have broad application.

Maintenance of Metabolic Plasticity despite Relaxed Selection in a Long-Term Evolution Experiment with Escherichia coli

AbstractTraits that are unused in a given environment are subject to processes that tend to erode them, leading to reduced fitness in other environments. Although this general tendency is clear, we know much less about why some traits are lost while others are retained and about the roles of mutation and selection in generating different responses. We addressed these issues by examining populations of a facultative anaerobe, Escherichia coli, that have evolved for >30 years in the presence of oxygen, with relaxed selection for anaerobic growth and the associated metabolic plasticity. We asked whether evolution led to the loss, improvement, or maintenance of anaerobic growth, and we analyzed gene expression and mutational data sets to understand the outcomes. We identified genomic signatures of both positive and purifying selection on aerobic-specific genes, while anaerobic-specific genes showed clear evidence of relaxed selection. We also found parallel evolution at two interacting loci that regulate anaerobic growth. We competed the ancestor and evolved clones from each population in an anoxic environment, and we found that anaerobic fitness had not decayed, despite relaxed selection. In summary, relaxed selection does not necessarily reduce an organism's fitness in other environments. Instead, the genetic architecture of the traits under relaxed selection and their correlations with traits under positive and purifying selection may sometimes determine evolutionary outcomes.

Experimental Evolution in Plant-Microbe Systems: A Tool for Deciphering the Functioning and Evolution of Plant-Associated Microbial Communities

In natural environments, microbial communities must constantly adapt to stressful environmental conditions. The genetic and phenotypic mechanisms underlying the adaptive response of microbial communities to new (and often complex) environments can be tackled with a combination of experimental evolution and next generation sequencing. This combination allows to analyse the real-time evolution of microbial populations in response to imposed environmental factors or during the interaction with a host, by screening for phenotypic and genotypic changes over a multitude of identical experimental cycles. Experimental evolution (EE) coupled with comparative genomics has indeed facilitated the monitoring of bacterial genetic evolution and the understanding of adaptive evolution processes. Basically, EE studies had long been done on single strains, allowing to reveal the dynamics and genetic targets of natural selection and to uncover the correlation between genetic and phenotypic adaptive changes. However, species are always evolving in relation with other species and have to adapt not only to the environment itself but also to the biotic environment dynamically shaped by the other species. Nowadays, there is a growing interest to apply EE on microbial communities evolving under natural environments. In this paper, we provide a non-exhaustive review of microbial EE studies done with systems of increasing complexity (from single species, to synthetic communities and natural communities) and with a particular focus on studies between plants and plant-associated microorganisms. We highlight some of the mechanisms controlling the functioning of microbial species and their adaptive responses to environment changes and emphasize the importance of considering bacterial communities and complex environments in EE studies.

Population Bottlenecks Strongly Affect the Evolutionary Dynamics of Antibiotic Persistence

Bacterial persistence is a potential cause of antibiotic therapy failure. Antibiotic-tolerant persisters originate from phenotypic differentiation within a susceptible population, occurring with a frequency that can be altered by mutations. Recent studies have proven that persistence is a highly evolvable trait and, consequently, an important evolutionary strategy of bacterial populations to adapt to high-dose antibiotic therapy. Yet, the factors that govern the evolutionary dynamics of persistence are currently poorly understood. Theoretical studies predict far-reaching effects of bottlenecking on the evolutionary adaption of bacterial populations, but these effects have never been investigated in the context of persistence. Bottlenecking events are frequently encountered by infecting pathogens during host-to-host transmission and antibiotic treatment. In this study, we used a combination of experimental evolution and barcoded knockout libraries to examine how population bottlenecking affects the evolutionary dynamics of persistence. In accordance with existing hypotheses, small bottlenecks were found to restrict the adaptive potential of populations and result in more heterogeneous evolutionary outcomes. Evolutionary trajectories followed in small-bottlenecking regimes additionally suggest that the fitness landscape associated with persistence has a rugged topography, with distinct trajectories toward increased persistence that are accessible to evolving populations. Furthermore, sequencing data of evolved populations and knockout libraries after selection reveal various genes that are potentially involved in persistence, including previously known as well as novel targets. Together, our results do not only provide experimental evidence for evolutionary theories, but also contribute to a better understanding of the environmental and genetic factors that guide bacterial adaptation to antibiotic treatment.

Evolution of Pseudomonas aeruginosa toward higher fitness under standard laboratory conditions

Identifying genetic factors that contribute to the evolution of adaptive phenotypes in pathogenic bacteria is key to understanding the establishment of infectious diseases. In this study, we performed mutation accumulation experiments to record the frequency of mutations and their effect on fitness in hypermutator strains of the environmental bacterium Pseudomonas aeruginosa in comparison to the host-niche-adapted Salmonella enterica. We demonstrate that P. aeruginosa, but not S. enterica, hypermutators evolve toward higher fitness under planktonic conditions. Adaptation to increased growth performance was accompanied by a reversible perturbing of the local genetic context of membrane and cell wall biosynthesis genes. Furthermore, we observed a fine-tuning of complex regulatory circuits involving multiple di-guanylate modulating enzymes that regulate the transition between fast growing planktonic and sessile biofilm-associated lifestyles. The redundancy and local specificity of the di-guanylate signaling pathways seem to allow a convergent shift toward increased growth performance across niche-adapted clonal P. aeruginosa lineages, which is accompanied by a pronounced heterogeneity of their motility, virulence, and biofilm phenotypes.

Rapid selection response to ethanol in Saccharomyces eubayanus emulates the domestication process under brewing conditions

Although the typical genomic and phenotypic changes that characterize the evolution of organisms under the human domestication syndrome represent textbook examples of rapid evolution, the molecular processes that underpin such changes are still poorly understood. Domesticated yeasts for brewing, where short generation times and large phenotypic and genomic plasticity were attained in a few generations under selection, are prime examples. To experimentally emulate the lager yeast domestication process, we created a genetically complex (panmictic) artificial population of multiple Saccharomyces eubayanus genotypes, one of the parents of lager yeast. Then, we imposed a constant selection regime under a high ethanol concentration in 10 replicated populations during 260 generations (6 months) and compared them with propagated controls exposed solely to glucose. Propagated populations exhibited a selection differential of 60% in growth rate in ethanol, mostly explained by the proliferation of a single lineage (CL248.1) that competitively displaced all other clones. Interestingly, the outcome does not require the entire time‐course of adaptation, as four lineages monopolized the culture at generation 120. Sequencing demonstrated that de novo genetic variants were produced in all propagated lines, including SNPs, aneuploidies, INDELs and translocations. In addition, the different propagated populations showed correlated responses resembling the domestication syndrome: genomic rearrangements, faster fermentation rates, lower production of phenolic off‐flavours and lower volatile compound complexity. Expression profiling in beer wort revealed altered expression levels of genes related to methionine metabolism, flocculation, stress tolerance and diauxic shift, likely contributing to higher ethanol and fermentation stress tolerance in the evolved populations. Our study shows that experimental evolution can rebuild the brewing domestication process in ‘fast motion’ in wild yeast, and also provides a powerful tool for studying the genetics of the adaptation process in complex populations.

Resequencing of Microbial Isolates: A Lab Module to Introduce Novices to Command-Line Bioinformatics

Familiarity with genome-scale data and the bioinformatic skills to analyze it have become essential for understanding and advancing modern biology and human health, yet many undergraduate biology majors are never exposed to hands-on bioinformatics. This paper presents a module that introduces students to applied bioinformatic analysis within the context of a research-based microbiology lab course. One of the most commonly used genomic analyses in biology is resequencing: determining the sequence of DNA bases in a derived strain of some organism, and comparing it to the known ancestral genome of that organism to better understand the phenotypic differences between them. Many existing CUREs - Course Based Undergraduate Research Experiences - evolve or select new strains of bacteria and compare them phenotypically to ancestral strains. This paper covers standardized strategies and procedures, accessible to undergraduates, for preparing and analyzing microbial whole-genome resequencing data to examine the genotypic differences between such strains. Wet-lab protocols and computational tutorials are provided, along with additional guidelines for educators, providing instructors without a next-generation sequencing or bioinformatics background the necessary information to incorporate whole-genome sequencing and command-line analysis into their class. This module introduces novice students to running software at the command-line, giving them exposure and familiarity with the types of tools that make up the vast majority of open-source scientific software used in contemporary biology. Completion of the module improves student attitudes toward computing, which may make them more likely to pursue further bioinformatics study.

Microfluidic Evolution-On-A-Chip Reveals New Mutations that Cause Antibiotic Resistance

Microfluidic devices can mimic naturally occurring microenvironments and create microbial population heterogeneities ranging from planktonic cells to biofilm states. The exposure of such populations to spatially organized stress gradients can promote their adaptation into complex phenotypes, which are otherwise difficult to achieve with conventional experimental setups. Here a microfluidic chip that employs precise chemical gradients in consecutive microcompartments to perform microbial adaptive laboratory evolution (ALE), a key tool to study evolution in fundamental and applied contexts is described. In the chip developed here, microbial cells can be exposed to a defined profile of stressors such as antibiotics. By modulating this profile, stress adaptation in the chip through resistance or persistence can be specifically controlled. Importantly, chip-based ALE leads to the discovery of previously unknown mutations in Escherichia coli that confer resistance to nalidixic acid. The microfluidic device presented here can enhance the occurrence of mutations employing defined micro-environmental conditions to generate data to better understand the parameters that influence the mechanisms of antibiotic resistance.

Adaptation reduces competitive dominance and alters community assembly

A growing body of theory predicts that evolution of an early-arriving species in a new environment can produce a competitive advantage against later arriving species, therefore altering community assembly (i.e. the community monopolization hypothesis). Applications of the community monopolization hypothesis are increasing. However, experimental tests of the hypothesis are rare. Here, we provide a rare experimental demonstration of the community monopolization hypothesis using two archaeal species. We first expose one species to low- and high-temperature environments for 135 days. Populations in the high-temperature treatment evolved a 20% higher median performance when grown at high temperature. We then demonstrate that early arrival and adaptation reduce the abundance of a late-arriving species in the high-temperature environment by 63% relative to when both species arrive simultaneously and neither species is adapted to high temperature. These results are consistent with the community monopolization hypothesis and suggest that adaptation can reduce competitive dominance to alter community assembly. Hence, community monopolization might be much more common in nature than previously assumed. Our results strongly support the idea that patterns of biodiversity might often stem from a race between local adaptation and colonization of pre-adapted species.

Omics-Driven Biotechnology for Industrial Applications

Biomanufacturing is a key component of biotechnology that uses biological systems to produce bioproducts of commercial relevance, which are of great interest to the energy, material, pharmaceutical, food, and agriculture industries. Biotechnology-based approaches, such as synthetic biology and metabolic engineering are heavily reliant on "omics" driven systems biology to characterize and understand metabolic networks. Knowledge gained from systems biology experiments aid the development of synthetic biology tools and the advancement of metabolic engineering studies toward establishing robust industrial biomanufacturing platforms. In this review, we discuss recent advances in "omics" technologies, compare the pros and cons of the different "omics" technologies, and discuss the necessary requirements for carrying out multi-omics experiments. We highlight the influence of "omics" technologies on the production of biofuels and bioproducts by metabolic engineering. Finally, we discuss the application of "omics" technologies to agricultural and food biotechnology, and review the impact of "omics" on current COVID-19 research.

LI Detector: a framework for sensitive colony-based screens regardless of the distribution of fitness effects

Microbial growth characteristics have long been used to investigate fundamental questions of biology. Colony-based high-throughput screens enable parallel fitness estimation of thousands of individual strains using colony growth as a proxy for fitness. However, fitness estimation is complicated by spatial biases affecting colony growth, including uneven nutrient distribution, agar surface irregularities, and batch effects. Analytical methods that have been developed to correct for these spatial biases rely on the following assumptions: (1) that fitness effects are normally distributed, and (2) that most genetic perturbations lead to minor changes in fitness. Although reasonable for many applications, these assumptions are not always warranted and can limit the ability to detect small fitness effects. Beneficial fitness effects, in particular, are notoriously difficult to detect under these assumptions. Here, we developed the linear interpolation-based detector (LI Detector) framework to enable sensitive colony-based screening without making prior assumptions about the underlying distribution of fitness effects. The LI Detector uses a grid of reference colonies to assign a relative fitness value to every colony on the plate. We show that the LI Detector is effective in correcting for spatial biases and equally sensitive toward increase and decrease in fitness. LI Detector offers a tunable system that allows the user to identify small fitness effects with unprecedented sensitivity and specificity. LI Detector can be utilized to develop and refine gene-gene and gene-environment interaction networks of colony-forming organisms, including yeast, by increasing the range of fitness effects that can be reliably detected.

Clonal Interference and Mutation Bias in Small Bacterial Populations in Droplets

Experimental evolution studies have provided key insights into the fundamental mechanisms of evolution. One striking observation is that parallel and convergent evolution during laboratory evolution can be surprisingly common. However, these experiments are typically performed with well-mixed cultures and large effective population sizes, while pathogenic microbes typically experience strong bottlenecks during infection or drug treatment. Yet, our knowledge about adaptation in very small populations, where selection strength and mutation supplies are limited, is scant. In this study, wild-type and mutator strains of the bacterium Escherichia coli were evolved for about 100 generations towards increased resistance to the β-lactam antibiotic cefotaxime in millifluidic droplets of 0.5 µL and effective population size of approximately 27,000 cells. The small effective population size limited the adaptive potential of wild-type populations, where adaptation was limited to inactivating mutations, which caused the increased production of outer-membrane vesicles, leading to modest fitness increases. In contrast, mutator clones with an average of ~30-fold higher mutation rate adapted much faster by acquiring both inactivating mutations of an outer-membrane porin and particularly inactivating and gain-of-function mutations, causing the upregulation or activation of a common efflux pump, respectively. Our results demonstrate how in very small populations, clonal interference and mutation bias together affect the choice of adaptive trajectories by mediating the balance between high-rate and large-benefit mutations.

Increasing Solvent Tolerance to Improve Microbial Production of Alcohols, Terpenoids and Aromatics

Fuels and polymer precursors are widely used in daily life and in many industrial processes. Although these compounds are mainly derived from petrol, bacteria and yeast can produce them in an environment-friendly way. However, these molecules exhibit toxic solvent properties and reduce cell viability of the microbial producer which inevitably impedes high product titers. Hence, studying how product accumulation affects microbes and understanding how microbial adaptive responses counteract these harmful defects helps to maximize yields. Here, we specifically focus on the mode of toxicity of industry-relevant alcohols, terpenoids and aromatics and the associated stress-response mechanisms, encountered in several relevant bacterial and yeast producers. In practice, integrating heterologous defense mechanisms, overexpressing native stress responses or triggering multiple protection pathways by modifying the transcription machinery or small RNAs (sRNAs) are suitable strategies to improve solvent tolerance. Therefore, tolerance engineering, in combination with metabolic pathway optimization, shows high potential in developing superior microbial producers.

Adaptive evolution of nontransitive fitness in yeast

A common misconception is that evolution is a linear ‘march of progress’, where each organism along a line of descent is more fit than all those that came before it. Rejecting this misconception implies that evolution is nontransitive: a series of adaptive events will, on occasion, produce organisms that are less fit compared to a distant ancestor. Here we identify a nontransitive evolutionary sequence in a 1000-generation yeast evolution experiment. We show that nontransitivity arises due to adaptation in the yeast nuclear genome combined with the stepwise deterioration of an intracellular virus, which provides an advantage over viral competitors within host cells. Extending our analysis, we find that nearly half of our ~140 populations experience multilevel selection, fixing adaptive mutations in both the nuclear and viral genomes. Our results provide a mechanistic case-study for the adaptive evolution of nontransitivity due to multilevel selection in a 1000-generation host/virus evolution experiment.

It is widely accepted in biology that all life on Earth gradually evolved over billions of years from a single ancestor. Yet, there is still much about this process that is not fully understood. Evolution is often thought of as progressing in a linear fashion, with each new generation being better adapted to its environment than the last. But it has been proposed that evolution is also nontransitive: this means even if each generation is ‘fitter’ than its immediate predecessor, these series of adaptive changes will occasionally result in organisms that are less fit than their distant ancestors.

Laboratory experiments of evolution are a good way to test evolutionary theories because they allow researchers to create scenarios that are impossible to observe in natural populations, such as an organism competing against its extinct ancestors. Buskirk et al. set up such an experiment using yeast to determine whether nontransitive effects can be observed in the direct descendants of an organism.

At the start of the experiment, the yeast cells were host to a non-infectious ‘killer’ virus that is common among yeast. Cells containing the virus produce a toxin that destroys other yeast that lack the virus. The populations of yeast were given a nutrient-rich broth in which to grow and subjected to a simple evolutionary pressure: to grow fast, which limits the amount of resources available.

As the yeast evolved, they gained beneficial genetic mutations that allowed them to outcompete their neighbors, and they passed these traits down to their descendants. Some of these mutations occurred not in the yeast genome, but in the genome of the killer virus, and this stopped the yeast infected with the virus from producing the killer toxin. Over time, other mutations resulted in the infected yeast no longer being immune to the toxin. Thus, when Buskirk et al. pitted these yeast against their distant ancestors, the new generation were destroyed by the toxins the older generation produced.

These findings provide the first experimental evidence for nontransitivity along a line of descent. The results have broad implications for our understanding of how evolution works, casting doubts over the idea that evolution always involves a direct progression towards new, improved traits.

Tell Me Where You've Been and I'll Tell You How You'll Evolve

The reproducibility of adaptive evolution is a long-standing debate in evolutionary biology. Kempher et al. (M. L. Kempher, X. Tao, R. Song, B. Wu, et al., mBio 11:e00569-20, 2020, https://doi.org/10.1128/mBio.00569-20) used experimental evolution to investigate the effect of previous evolutionary trajectories on the ability of microbial populations to adapt to high temperatures. Despite the divergence caused by adaptation to previous environments, all populations reproducibly converged on similar final levels of fitness.

The reproducibility of adaptive evolution is a long-standing debate in evolutionary biology. Kempher et al. (M. L. Kempher, X. Tao, R. Song, B. Wu, et al., mBio 11:e00569-20, 2020, https://doi.org/10.1128/mBio.00569-20) used experimental evolution to investigate the effect of previous evolutionary trajectories on the ability of microbial populations to adapt to high temperatures. Despite the divergence caused by adaptation to previous environments, all populations reproducibly converged on similar final levels of fitness. Nevertheless, the genetic basis of adaptation depended on past selection experiments, reinforcing the idea that previous adaptation can dictate the trajectories of later evolutionary processes.

High-throughput analysis of adaptation using barcoded strains of Saccharomyces cerevisiae

BACKGROUND

Experimental evolution of microbes can be used to empirically address a wide range of questions about evolution and is increasingly employed to study complex phenomena ranging from genetic evolution to evolutionary rescue. Regardless of experimental aims, fitness assays are a central component of this type of research, and low-throughput often limits the scope and complexity of experimental evolution studies. We created an experimental evolution system in Saccharomyces cerevisiae that utilizes genetic barcoding to overcome this challenge.

RESULTS

We first confirm that barcode insertions do not alter fitness and that barcode sequencing can be used to efficiently detect fitness differences via pooled competition-based fitness assays. Next, we examine the effects of ploidy, chemical stress, and population bottleneck size on the evolutionary dynamics and fitness gains (adaptation) in a total of 76 experimentally evolving, asexual populations by conducting 1,216 fitness assays and analyzing 532 longitudinal-evolutionary samples collected from the evolving populations. In our analysis of these data we describe the strengths of this experimental evolution system and explore sources of error in our measurements of fitness and evolutionary dynamics.

CONCLUSIONS

Our experimental treatments generated distinct fitness effects and evolutionary dynamics, respectively quantified via multiplexed fitness assays and barcode lineage tracking. These findings demonstrate the utility of this new resource for designing and improving high-throughput studies of experimental evolution. The approach described here provides a framework for future studies employing experimental designs that require high-throughput multiplexed fitness measurements.

Phenotypic Parallelism during Experimental Adaptation of a Free-Living Bacterium to the Zebrafish Gut

Although animals encounter many bacterial species throughout their lives, only a subset colonize vertebrate digestive tracts, and these bacteria can profoundly influence the health and development of their animal hosts. We used experimental evolution to study a free-living bacterium as it adapts to a novel vertebrate host by serially passaging replicate populations of Shewanella oneidensis through the intestines of larval zebrafish (Danio rerio). Our results demonstrate that adaptation to the zebrafish gut is complex, with multiple evolutionary pathways capable of improving colonization, but that motility plays an important role during the onset of host association.

Although animals encounter a plethora of bacterial species throughout their lives, only a subset colonize vertebrate digestive tracts, and these bacteria can profoundly influence the health and development of their animal hosts. However, our understanding of how bacteria initiate symbioses with animal hosts remains underexplored, and this process is central to the assembly and function of gut bacterial communities. Therefore, we used experimental evolution to study a free-living bacterium as it adapts to a novel vertebrate host by serially passaging replicate populations of Shewanella oneidensis through the intestines of larval zebrafish (Danio rerio). After approximately 200 bacterial generations, isolates from evolved populations improved their ability to colonize larval zebrafish during competition against their unpassaged ancestor. Genome sequencing revealed unique sets of mutations in the two evolved isolates exhibiting the highest mean competitive fitness. One isolate exhibited increased swimming motility and decreased biofilm formation compared to the ancestor, and we identified a missense mutation in the mannose-sensitive hemagglutinin pilus operon that is sufficient to increase fitness and reproduce these phenotypes. The second isolate exhibited enhanced swimming motility but unchanged biofilm formation, and here the genetic basis for adaptation is less clear. These parallel enhancements in motility and fitness resemble the behavior of a closely related Shewanella strain previously isolated from larval zebrafish and suggest phenotypic convergence with this isolate. Our results demonstrate that adaptation to the zebrafish gut is complex, with multiple evolutionary pathways capable of improving colonization, but that motility plays an important role during the onset of host association.

High-throughput discovery of phage receptors using transposon insertion sequencing of bacteria

As the most abundant microbes on Earth, novel bacteriophages (phages; bacteria-specific viruses) are readily isolated from environmental samples. However, it remains challenging to characterize phage-bacteria interactions, such as the host receptor(s) phages bind to initiate infection. Here, we tested whether transposon insertion sequencing (INSeq) could be used to identify bacterial genes involved in phage binding. As proof of concept, results showed that INSeq screens successfully identified genes encoding known receptors for previously characterized viruses of Escherichia coli (phages T6, T2, T4, and T7). INSeq screens were then used to identify genes involved during infection of six newly isolated coliphages. Results showed that candidate receptors could be successfully identified for the majority (five of six) of the phages; furthermore, genes encoding the phage receptor(s) were the top hit(s) in the analyses of the successful screens. INSeq screens provide a generally useful method for high-throughput discovery of phage receptors. We discuss limitations of our approach when examining uncharacterized phages, as well as usefulness of the method for exploring the evolution of broad versus narrow use of cellular receptors among phages in the biosphere.

Modeling microbial metabolic trade-offs in a chemostat

Microbes face intense competition in the natural world, and so need to wisely allocate their resources to multiple functions, in particular to metabolism. Understanding competition among metabolic strategies that are subject to trade-offs is therefore crucial for deeper insight into the competition, cooperation, and community assembly of microorganisms. In this work, we evaluate competing metabolic strategies within an ecological context by considering not only how the environment influences cell growth, but also how microbes shape their chemical environment. Utilizing chemostat-based resource-competition models, we exhibit a set of intuitive and general procedures for assessing metabolic strategies. Using this framework, we are able to relate and unify multiple metabolic models, and to demonstrate how the fitness landscape of strategies becomes intrinsically dynamic due to species-environment feedback. Such dynamic fitness landscapes produce rich behaviors, and prove to be crucial for ecological and evolutionarily stable coexistence in all the models we examined.

The omnistat: A flexible continuous-culture system for prolonged experimental evolution

Microbial evolution experiments provide a powerful tool to unravel the molecular basis of adaptive evolution but their outcomes can be difficult to interpret, unless the selective forces that are applied during the experiment are carefully controlled. In this respect, experimental evolution in continuous cultures provides advantages over commonly used sequential batch-culture protocols because continuous cultures allow for more accurate control over the induced selective environment. However, commercial continuous-culture systems are large and expensive, while available DIY continuous-culture systems are not versatile enough to allow for multiple sensors and rigorous stirring.We present a modular continuous-culture system that adopts the commonly used GL45 glass laboratory bottle as a bioreactor vessel. Our design offers three advantages: first, it is equipped with a large head plate, fitting two sensors and seven input/output ports, enabling the customization of the system for many running modes (chemostat, auxostat, etc.). Second, the bioreactor is small (25-250 ml), which makes it feasible to run many replicates in parallel. Third, bioreactor modules can be coupled by uni- or bi-directional flows to induce spatiotemporal variation in selection. These features result in a particularly flexible culturing platform that facilitates the investigation of a broad range of evolutionary and ecological questions.To illustrate the versatility of our culturing system, we outline two evolution experiments that impose a temporally or spatially variable regime of selection. The first experiment illustrates how controlled temporal variation in resource availability can be utilized to select for anticipatory switching. The second experiment illustrates a spatially structured morbidostat setup that is designed to probe epistatic interactions between adaptive mutations. Furthermore, we demonstrate how sensor data can be used to stabilize selection pressures or track evolutionary adaptation.Evolution experiments in which populations are exposed to controlled spatiotemporal variation, are essential to gain insight into the process of adaptation and the mechanisms that constrain evolution. Continuous-culture systems, like the one presented here, offer control over key environmental parameters and establish a well-defined regime of selection. As such, they create the opportunity to expose evolutionary constraints in the form of phenotypic trade-offs, contributing to a mechanistic understanding of adaptive evolution.

Causal mutations from adaptive laboratory evolution are outlined by multiple scales of genome annotations and condition-specificity

BACKGROUND

Adaptive Laboratory Evolution (ALE) has emerged as an experimental approach to discover mutations that confer phenotypic functions of interest. However, the task of finding and understanding all beneficial mutations of an ALE experiment remains an open challenge for the field. To provide for better results than traditional methods of ALE mutation analysis, this work applied enrichment methods to mutations described by a multiscale annotation framework and a consolidated set of ALE experiment conditions. A total of 25,321 unique genome annotations from various sources were leveraged to describe multiple scales of mutated features in a set of 35 Escherichia coli based ALE experiments. These experiments totalled 208 independent evolutions and 2641 mutations. Additionally, mutated features were statistically associated across a total of 43 unique experimental conditions to aid in deconvoluting mutation selection pressures.

RESULTS

Identifying potentially beneficial, or key, mutations was enhanced by seeking coding and non-coding genome features significantly enriched by mutations across multiple ALE replicates and scales of genome annotations. The median proportion of ALE experiment key mutations increased from 62%, with only small coding and non-coding features, to 71% with larger aggregate features. Understanding key mutations was enhanced by considering the functions of broader annotation types and the significantly associated conditions for key mutated features. The approaches developed here were used to find and characterize novel key mutations in two ALE experiments: one previously unpublished with Escherichia coli grown on glycerol as a carbon source and one previously published with Escherichia coli tolerized to high concentrations of L-serine.

CONCLUSIONS

The emergent adaptive strategies represented by sets of ALE mutations became more clear upon observing the aggregation of mutated features across small to large scale genome annotations. The clarification of mutation selection pressures among the many experimental conditions also helped bring these strategies to light. This work demonstrates how multiscale genome annotation frameworks and data-driven methods can help better characterize ALE mutations, and thus help elucidate the genotype-to-phenotype relationship of the studied organism.

Myriocin-induced adaptive laboratory evolution of an industrial strain of Saccharomyces cerevisiae reveals its potential to remodel lipid composition and heat tolerance

The modification of lipid composition allows cells to adjust membrane biophysical properties in response to changes in environmental temperature. Here, we use adaptive laboratory evolution (ALE) in the presence of myriocin, a sphingolipid (SLs) biosynthesis inhibitor, to remodel the lipid profile of an industrial yeast strain (LH) of Saccharomyces cerevisiae. The approach enabled to obtain a heterogeneous population (LHev) of myriocin-tolerant evolved clones characterized by its growth capacity at high temperature. Myriocin exposure also caused tolerance to soraphen A, an inhibitor of the acetyl-CoA carboxylase Acc1, the rate-limiting enzyme in fatty acid de novo production, supporting a change in lipid metabolism during ALE. In line with this, characterization of two randomly selected clones, LH03 and LH09, showed the presence of lipids with increased saturation degree and reduced acyl length. In addition, the clone LH03, which displays the greater improvement in fitness at 40°C, exhibited higher SL content as compared with the parental strain. Analysis of the LH03 and LH09 genomes revealed a loss of chromosomes affecting genes that have a role in fatty acid synthesis and elongation. The link between ploidy level and growth at high temperature was further supported by the analysis of a fully isogenic set of yeast strains with ploidy between 1N and 4N which showed that the loss of genome content provides heat tolerance. Consistent with this, a thermotolerant evolved population (LH40°) generated from the parental LH strain by heat-driven ALE exhibited a reduction in the chromosome copy number. Thus, our results identify myriocin-driven evolution as a powerful approach to investigate the mechanisms of acquired thermotolerance and to generate improved strains.

Evolutionary Repair Experiments as a Window to the Molecular Diversity of Life

Comparative genomics reveals an unexpected diversity in the molecular mechanisms underlying conserved cellular functions, such as DNA replication and cytokinesis. However, the genetic bases and evolutionary processes underlying this 'molecular diversity' remain to be explained. Here, we review a tool to generate alternative mechanisms for conserved cellular functions and test hypotheses concerning the generation of molecular diversity - evolutionary repair experiments, in which laboratory microbial populations adapt in response to a genetic perturbation. We summarize the insights gained from evolutionary repair experiments, the spectrum and dynamics of compensatory mutations, and the alternative molecular mechanisms used to repair perturbed cellular functions. We relate these experiments to the modifications of conserved functions that have occurred outside the laboratory. We end by proposing strategies to improve evolutionary repair experiments as a tool to explore the molecular diversity of life.

Evolution of mutualistic behaviour between Chlorella sorokiniana and Saccharomyces cerevisiae within a synthetic environment

Yeast and microalgae are microorganisms with widely diverging physiological and biotechnological properties. Accordingly, their fields of applications diverge: yeasts are primarily applied in processes related to fermentation, while microalgae are used for the production of high-value metabolites and green technologies such as carbon capture. Heterotrophic-autotrophic systems and synthetic ecology approaches have been proposed as tools to achieve stable combinations of such evolutionarily unrelated species. We describe an entirely novel synthetic ecology-based approach to evolve co-operative behaviour between winery wastewater isolates of the yeast Saccharomyces cerevisiae and microalga Chlorella sorokiniana. The data show that biomass production and mutualistic growth improved when co-evolved yeast and microalgae strains were paired together. Combinations of co-evolved strains displayed a range of phenotypes, including differences in amino acid profiles. Taken together, the results demonstrate that biotic selection pressures can lead to improved mutualistic growth phenotypes over relatively short time periods.

Experimental Evolution of Legume Symbionts: What Have We Learnt?

Rhizobia, the nitrogen-fixing symbionts of legumes, are polyphyletic bacteria distributed in many alpha- and beta-proteobacterial genera. They likely emerged and diversified through independent horizontal transfers of key symbiotic genes. To replay the evolution of a new rhizobium genus under laboratory conditions, the symbiotic plasmid of Cupriavidus taiwanensis was introduced in the plant pathogen Ralstonia solanacearum, and the generated proto-rhizobium was submitted to repeated inoculations to the C. taiwanensis host, Mimosa pudica L.. This experiment validated a two-step evolutionary scenario of key symbiotic gene acquisition followed by genome remodeling under plant selection. Nodulation and nodule cell infection were obtained and optimized mainly via the rewiring of regulatory circuits of the recipient bacterium. Symbiotic adaptation was shown to be accelerated by the activity of a mutagenesis cassette conserved in most rhizobia. Investigating mutated genes led us to identify new components of R. solanacearum virulence and C. taiwanensis symbiosis. Nitrogen fixation was not acquired in our short experiment. However, we showed that post-infection sanctions allowed the increase in frequency of nitrogen-fixing variants among a non-fixing population in the M. pudica-C. taiwanensis system and likely allowed the spread of this trait in natura. Experimental evolution thus provided new insights into rhizobium biology and evolution.

Biological amplification of low frequency mutations unravels laboratory culture history of the bio-threat agent Francisella tularensis

Challenges of investigating a suspected bio attack include establishing if microorganisms have been cultured to produce attack material and to identify their source. Addressing both issues, we have investigated genetic variations that emerge during laboratory culturing of the bacterial pathogen Francisella tularensis. Key aims were to identify genetic variations that are characteristic of laboratory culturing and explore the possibility of using biological amplification to identify genetic variation present at exceedingly low frequencies in a source sample. We used parallel serial passage experiments and high-throughput sequencing of F. tularensis to explore the genetic variation. We found that during early laboratory culture passages of F. tularensis, gene duplications emerged in the pathogen genome followed by single-nucleotide polymorphisms in genes for bacterial capsule synthesis. Based on a biological enrichment scheme and the use of high-throughput sequencing, we identified genetic variation that likely pre-existed in a source sample. The results support that capsule synthesis gene mutations are common during laboratory culture, and that a biological amplification strategy is useful for linking a F. tularensis sample to a specific laboratory variant among many highly similar variants.

Quality-quantity trade-offs drive functional trait evolution in a model microalgal 'climate change winner'

Phytoplankton are the unicellular photosynthetic microbes that form the base of aquatic ecosystems, and their responses to global change will impact everything from food web dynamics to global nutrient cycles. Some taxa respond to environmental change by increasing population growth rates in the short-term and are projected to increase in frequency over decades. To gain insight into how these projected 'climate change winners' evolve, we grew populations of microalgae in ameliorated environments for several hundred generations. Most populations evolved to allocate a smaller proportion of carbon to growth while increasing their ability to tolerate and metabolise reactive oxygen species (ROS). This trade-off drives the evolution of traits that underlie the ecological and biogeochemical roles of phytoplankton. This offers evolutionary and a metabolic frameworks for understanding trait evolution in projected 'climate change winners' and suggests that short-term population booms have the potential to be dampened or reversed when environmental amelioration persists.

The evolutionary plasticity of chromosome metabolism allows adaptation to constitutive DNA replication stress

Many biological features are conserved and thus considered to be resistant to evolutionary change. While rapid genetic adaptation following the removal of conserved genes has been observed, we often lack a mechanistic understanding of how adaptation happens. We used the budding yeast, Saccharomyces cerevisiae, to investigate the evolutionary plasticity of chromosome metabolism, a network of evolutionary conserved modules. We experimentally evolved cells constitutively experiencing DNA replication stress caused by the absence of Ctf4, a protein that coordinates the enzymatic activities at replication forks. Parallel populations adapted to replication stress, over 1000 generations, by acquiring multiple, concerted mutations. These mutations altered conserved features of two chromosome metabolism modules, DNA replication and sister chromatid cohesion, and inactivated a third, the DNA damage checkpoint. The selected mutations define a functionally reproducible evolutionary trajectory. We suggest that the evolutionary plasticity of chromosome metabolism has implications for genome evolution in natural populations and cancer.

Evolution, Microbes, and Changing Ocean Conditions

Experimental evolution and the associated theory are underutilized in marine microbial studies; the two fields have developed largely in isolation. Here, we review evolutionary tools for addressing four key areas of ocean global change biology: linking plastic and evolutionary trait changes, the contribution of environmental variability to determining trait values, the role of multiple environmental drivers in trait change, and the fate of populations near their tolerance limits. Wherever possible, we highlight which data from marine studies could use evolutionary approaches and where marine model systems can advance our understanding of evolution. Finally, we discuss the emerging field of marine microbial experimental evolution. We propose a framework linking changes in environmental quality (defined as the cumulative effect on population growth rate) with population traits affecting evolutionary potential, in order to understand which evolutionary processes are likely to be most important across a range of locations for different types of marine microbes.

Microbial evolution and ecological opportunity in the gut environment

Recent genomic and metagenomic studies have highlighted the presence of rapidly evolving microbial populations in the human gut. However, despite the fundamental implications of this intuitive finding for both basic and applied gut microbiome research, very little is known about the mode, tempo and potential functional consequences of microbial evolution in the guts of individual human hosts over a lifetime. Here I assess the potential relevance of ecological opportunity to bacterial adaptation, colonization and persistence in the neonate and germ-free mammalian gut environment as well as over the course of an individual lifetime using data emerging from mouse models as well as human studies to provide examples where possible. I then briefly outline how the continued development and application of experimental evolution approaches coupled to genomic and metagenomic analysis is essential to disentangling drift from selection and identifying specific drivers of evolution in the gut microbiome within and between individual human hosts and populations.

Evolutionary pathways to antibiotic resistance are dependent upon environmental structure and bacterial lifestyle

Bacterial populations vary in their stress tolerance and population structure depending upon whether growth occurs in well-mixed or structured environments. We hypothesized that evolution in biofilms would generate greater genetic diversity than well-mixed environments and lead to different pathways of antibiotic resistance. We used experimental evolution and whole genome sequencing to test how the biofilm lifestyle influenced the rate, genetic mechanisms, and pleiotropic effects of resistance to ciprofloxacin in Acinetobacter baumannii populations. Both evolutionary dynamics and the identities of mutations differed between lifestyle. Planktonic populations experienced selective sweeps of mutations including the primary topoisomerase drug targets, whereas biofilm-adapted populations acquired mutations in regulators of efflux pumps. An overall trade-off between fitness and resistance level emerged, wherein biofilm-adapted clones were less resistant than planktonic but more fit in the absence of drug. However, biofilm populations developed collateral sensitivity to cephalosporins, demonstrating the clinical relevance of lifestyle on the evolution of resistance.

A bacterium known as Acinetobacter baumannii causes serious lung infections in people with weakened immune systems. These illnesses are becoming more common largely because A. baumannii is increasingly developing resistance to antibiotics.

Inside the airways, individual A. baumannii cells can stick together and coat themselves in a slimy substance to form a structure called biofilm, which physically protects bacteria from antibiotics. This may be one of the reasons why it is often harder to treat bacterial infections associated with biofilms.

Another possibility is that bacteria may evolve differently in biofilms compared with cells living independently. For example, A. baumannii may colonize several regions of the lungs during an infection, leading to distinct groups of bacteria that experience different conditions and evolve separately. Each population may therefore respond differently to an antibiotic. In contrast, bacteria living independently in a well-mixed population – such as in the bloodstream of their host – would be more likely to all evolve in the same way.

Santos-Lopez, Marshall et al. tested this theory by exposing populations of A. baumannii that lived either independently or in biofilms to increasing levels of an antibiotic called ciprofloxacin. The genetic information of these cells was examined as the populations were evolving, and the bacteria were also put in contact with other types of antibiotics.

The analyses revealed that bacteria in well-mixed populations shared the same limited number of mutations: these gave the bacteria high levels of resistance to the antibiotic’s primary target, an enzyme involved in DNA processes. The bacteria had also become resistant to other classes of antibiotics.

In contrast, the bacteria in biofilm populations evolved to be more genetically diverse, exhibiting different types of mutations that helped the cells to pump out the drug. These bacteria were less resistant to ciprofloxacin and more sensitive to other types of antibiotics.

Further experiments looked into the fitness of the bacteria – their ability to survive, reproduce and compete with each other. High levels of antibiotic resistance came with lower fitness: biofilm bacteria had evolved to become being fitter than those from well-mixed population. Even in the absence of drugs, these populations were in fact fitter than the original cells.

Overall, understanding how the lifestyles of bacteria affect the way they respond to drugs may help researchers to develop new approaches that limit the spread of antibiotic resistance and improve treatment.

Microbial Experimental Evolution - a proving ground for evolutionary theory and a tool for discovery

Microbial experimental evolution uses controlled laboratory populations to study the mechanisms of evolution. The molecular analysis of evolved populations enables empirical tests that can confirm the predictions of evolutionary theory, but can also lead to surprising discoveries. As with other fields in the life sciences, microbial experimental evolution has become a tool, deployed as part of the suite of techniques available to the molecular biologist. Here, I provide a review of the general findings of microbial experimental evolution, especially those relevant to molecular microbiologists that are new to the field. I also relate these results to design considerations for an evolution experiment and suggest future directions for those working at the intersection of experimental evolution and molecular biology.

IAMBEE: a web-service for the identification of adaptive pathways from parallel evolved clonal populations

IAMBEE is a web server designed for the Identification of Adaptive Mutations in Bacterial Evolution Experiments (IAMBEE). Input data consist of genotype information obtained from independently evolved clonal populations or strains that show the same adapted behavior (phenotype). To distinguish adaptive from passenger mutations, IAMBEE searches for neighborhoods in an organism-specific interaction network that are recurrently mutated in the adapted populations. This search for recurrently mutated network neighborhoods, as proxies for pathways is driven by additional information on the functional impact of the observed genetic changes and their dynamics during adaptive evolution. In addition, the search explicitly accounts for the differences in mutation rate between the independently evolved populations. Using this approach, IAMBEE allows exploiting parallel evolution to identify adaptive pathways. The web-server is freely available at http://bioinformatics.intec.ugent.be/iambee/ with no login requirement.

Various Evolutionary Trajectories Lead to Loss of the Tobramycin-Potentiating Activity of the Quorum-Sensing Inhibitor Baicalin Hydrate in Burkholderia cenocepacia Biofilms

Combining antibiotics with potentiators that increase their activity is a promising strategy to tackle infections caused by antibiotic-resistant bacteria. As potentiators do not interfere with essential processes, it has been hypothesized that they are less likely to induce resistance. However, evidence supporting this hypothesis is lacking. In the present study, we investigated whether Burkholderia cenocepacia J2315 biofilms develop reduced susceptibility toward one such adjuvant, baicalin hydrate (BH). Biofilms were repeatedly and intermittently treated with tobramycin (TOB) alone or in combination with BH for 24 h. After treatment, the remaining cells were quantified using plate counting. After 15 cycles, biofilm cells were less susceptible to TOB and TOB+BH compared to the start population, and the potentiating effect of BH toward TOB was lost. Whole-genome sequencing was performed to probe which changes were involved in the reduced effect of BH, and mutations in 14 protein-coding genes were identified (including mutations in genes involved in central metabolism and in BCAL0296, encoding an ABC transporter). No changes in the MIC or MBC of TOB or changes in the number of persister cells were observed. However, basal intracellular levels of reactive oxygen species (ROS) and ROS levels found after treatment with TOB were markedly decreased in the evolved populations. In addition, in evolved cultures with mutations in BCAL0296, a significantly reduced uptake of TOB was observed. Our results indicate that B. cenocepacia J2315 biofilms rapidly lose susceptibility toward the antibiotic-potentiating activity of BH and point to changes in central metabolism, reduced ROS production, and reduced TOB uptake as mechanisms.

Evolved Biofilm: Review on the Experimental Evolution Studies of Bacillus subtilis Pellicles

For several decades, laboratory evolution has served as a powerful method to manipulate microorganisms and to explore long-term dynamics in microbial populations. Next to canonical Escherichia coli planktonic cultures, experimental evolution has expanded into alternative cultivation methods and species, opening the doors to new research questions. Bacillus subtilis, the spore-forming and root-colonizing bacterium, can easily develop in the laboratory as a liquid-air interface colonizing pellicle biofilm. Here, we summarize recent findings derived from this tractable experimental model. Clonal pellicle biofilms of B. subtilis can rapidly undergo morphological and genetic diversification creating new ecological interactions, for example, exploitation by biofilm non-producers. Moreover, long-term exposure to such matrix non-producers can modulate cooperation in biofilms, leading to different phenotypic heterogeneity pattern of matrix production with larger subpopulation of "ON" cells. Alternatively, complementary variants of biofilm non-producers, each lacking a distinct matrix component, can engage in a genetic division of labor, resulting in superior biofilm productivity compared to the "generalist" wild type. Nevertheless, inter-genetic cooperation appears to be evanescent and rapidly vanquished by individual biofilm formation strategies altering the amount or the properties of the remaining matrix component. Finally, fast-evolving mobile genetic elements can unpredictably shift intra-species interactions in B. subtilis biofilms. Understanding evolution in clonal biofilm populations will facilitate future studies in complex multispecies biofilms that are more representative of nature.

Experimental evolution: its principles and applications in developing stress-tolerant yeasts

Stress tolerance and resistance in industrial yeast strains are important attributes for cost-effective bioprocessing. The source of stress-tolerant yeasts ranges from extremophilic environments to laboratory engineered strains. However, industrial stress-tolerant yeasts are very rare in nature as the natural environment forces them to evolve traits that optimize survival and reproduction and not the ability to withstand harsh habitat-irrelevant industrial conditions. Experimental evolution is a frequent method used to uncover the mechanisms of evolution and microbial adaption towards environmental stresses. It optimizes biological systems by means of adaptation to environmental stresses and thus has immense power of development of robust stress-tolerant yeasts. This mini-review briefly outlines the basics and implications of evolution experiments and their applications to industrial biotechnology. This work is meant to serve as an introduction to those new to the field of experimental evolution, and as a guide to biologists working in the field of yeast stress response. Future perspectives of experimental evolution for potential biotechnological applications have also been elucidated.

Alternative Biochemistries for Alien Life: Basic Concepts and Requirements for the Design of a Robust Biocontainment System in Genetic Isolation

The universal genetic code, which is the foundation of cellular organization for almost all organisms, has fostered the exchange of genetic information from very different paths of evolution. The result of this communication network of potentially beneficial traits can be observed as modern biodiversity. Today, the genetic modification techniques of synthetic biology allow for the design of specialized organisms and their employment as tools, creating an artificial biodiversity based on the same universal genetic code. As there is no natural barrier towards the proliferation of genetic information which confers an advantage for a certain species, the naturally evolved genetic pool could be irreversibly altered if modified genetic information is exchanged. We argue that an alien genetic code which is incompatible with nature is likely to assure the inhibition of all mechanisms of genetic information transfer in an open environment. The two conceivable routes to synthetic life are either de novo cellular design or the successive alienation of a complex biological organism through laboratory evolution. Here, we present the strategies that have been utilized to fundamentally alter the genetic code in its decoding rules or its molecular representation and anticipate future avenues in the pursuit of robust biocontainment.