Arresting Evolution

Evolution-strengthened knowledge graph enables predicting the targetability and druggability of genes

Identifying promising targets is a critical step in modern drug discovery, with causative genes of diseases that are an important source of successful targets. Previous studies have found that the pathogeneses of various diseases are closely related to the evolutionary events of organisms. Accordingly, evolutionary knowledge can facilitate the prediction of causative genes and further accelerate target identification. With the development of modern biotechnology, massive biomedical data have been accumulated, and knowledge graphs (KGs) have emerged as a powerful approach for integrating and utilizing vast amounts of data. In this study, we constructed an evolution-strengthened knowledge graph (ESKG) and validated applications of ESKG in the identification of causative genes. More importantly, we developed an ESKG-based machine learning model named GraphEvo, which can effectively predict the targetability and the druggability of genes. We further investigated the explainability of the ESKG in druggability prediction by dissecting the evolutionary hallmarks of successful targets. Our study highlights the importance of evolutionary knowledge in biomedical research and demonstrates the potential power of ESKG in promising target identification. The data set of ESKG and the code of GraphEvo can be downloaded from https://github.com/Zhankun-Xiong/GraphEvo.

The gut microbiota links disease to human genome evolution

A large number of studies have established a causal relationship between the gut microbiota and human disease. In addition, the composition of the microbiota is substantially influenced by the human genome. Modern medical research has confirmed that the pathogenesis of various diseases is closely related to evolutionary events in the human genome. Specific regions of the human genome known as human accelerated regions (HARs) have evolved rapidly over several million years since humans diverged from a common ancestor with chimpanzees, and HARs have been found to be involved in some human-specific diseases. Furthermore, the HAR-regulated gut microbiota has undergone rapid changes during human evolution. We propose that the gut microbiota may serve as an important mediator linking diseases to human genome evolution.

Can We Arrest the Evolution of Antibiotic Resistance? The Differences between the Effects of Silver Nanoparticles and Silver Ions

Silver nanoparticles (AgNPs) are effective antimicrobial substances that show promise in combatting multidrug resistance. The potential application and release of AgNPs into the environment may neutralize the selective advantage of antibiotic resistance. Systemic knowledge regarding the effect of NPs on the evolution of antibiotic resistance is lacking. Our results showed that bacteria slowly developed adaptive tolerance to ciprofloxacin (CIP) under cyclic CIP and silver ion (Ag⁺) cotreatment, and no resistance/tolerance was discernible when CIP and AgNP exposure was alternated. In contrast, rapid CIP resistance was induced under continuous selection by treatment with only CIP. To combat the effects of CIP and Ag⁺, bacteria developed convergent evolutionary strategies with similar adaptive mechanisms, including anaerobic respiration transitioning (to reduce oxidative stress) and stringent response (to survive harsh environments). Alternating AgNP exposure impeded evolutionary resistance by accelerating B12-dependent folate and methionine cycles, which reestablished DNA synthesis and partially offset high oxidative stress levels, in contrast with the effect of CIP-directed evolutionary pressure. Nevertheless, CIP/AgNP treatment was ineffective in attenuating virulence, and CIP/Ag⁺ exposure even induced the virulence-critical type III secretion system. Our results increase the basic understanding of the impacts of NPs on evolutionary biology and suggest prospective nanotechnology applications for arresting evolutionary antibiotic resistance.

Susceptibility of the Cowpea Aphid (Hemiptera: Aphididae) to Widely Used Insecticides in Australia

Globally, 27 aphid species have evolved resistance to almost 100 insecticide active ingredients. A proactive approach to resistance management in pest aphids is needed; this should include risk analysis, followed by regular baseline susceptibility assays for species deemed at high risk of evolving resistance. The cowpea aphid (Aphis craccivora Koch) has evolved insecticide resistance to multiple insecticides outside Australia and was recently identified as a high-risk species in Australia. In this study, we generated toxicity data against four insecticides (representing four unique chemical Mode of Action groups) for populations of A. craccivora collected across Australia. Alpha-cypermethrin was the most toxic chemical to A. craccivora in leaf-dip laboratory bioassays with an average LC50 value across nine populations of 0.008 mg a.i./L, which was significantly lower than dimethoate (1.17 mg a.i./L) and pirimicarb (0.89 mg a.i./L). Small, but significant, differences in sensitivity were detected in some populations against pirimicarb and dimethoate, whereas responses to alpha-cypermethrin and imidacloprid were not significantly different across all aphid populations examined in this study. For all insecticides, the field rate controlled 100% of individuals tested. The data generated will be important for future monitoring of insecticide responses of A. craccivora. Proactive management, including increased reliance on non-chemical pest management approaches and routine insecticide baseline sensitivity studies, is recommended for A. craccivora.

Overlapping genes in natural and engineered genomes

Modern genome-scale methods that identify new genes, such as proteogenomics and ribosome profiling, have revealed, to the surprise of many, that overlap in genes, open reading frames and even coding sequences is widespread and functionally integrated into prokaryotic, eukaryotic and viral genomes. In parallel, the constraints that overlapping regions place on genome sequences and their evolution can be harnessed in bioengineering to build more robust synthetic strains and constructs. With a focus on overlapping protein-coding and RNA-coding genes, this Review examines their discovery, topology and biogenesis in the context of their genome biology. We highlight exciting new uses for sequence overlap to control translation, compress synthetic genetic constructs, and protect against mutation.

Exploring Selective Pressure Trade-Offs for Synthetic Addiction to Extend Metabolite Productive Lifetimes in Yeast

Engineered microbes often suffer from reduced fitness resulting from metabolic burden and various stresses. The productive lifetime of a bioreactor with engineered microbes is therefore susceptible to the rise of nonproductive mutants with better fitness. Synthetic addiction is emerging as a concept to artificially couple the growth rate of the microbe to production to tackle this problem. However, only a few successful cases of synthetic addiction systems have been reported to date. To understand the limitations and design constraints in long-term cultivations, we designed and studied conditional synthetic addiction circuits in Saccharomyces cerevisiae. This allowed us to probe a range of selective pressure strengths and identify the optimal balance between circuit stability and production-to-growth coupling. In the optimal balance, the productive lifetime was greatly extended compared with suboptimal circuit tuning. With a too-high or -low pressure, we found that production declines mainly through homologous recombination. These principles of trade-off in the design of synthetic addition systems should lead to the better control of bioprocess performance.

Engineering gene overlaps to sustain genetic constructs in vivo

Evolution is often an obstacle to the engineering of stable biological systems due to the selection of mutations inactivating costly gene circuits. Gene overlaps induce important constraints on sequences and their evolution. We show that these constraints can be harnessed to increase the stability of costly genes by purging loss-of-function mutations. We combine computational and synthetic biology approaches to rationally design an overlapping reading frame expressing an essential gene within an existing gene to protect. Our algorithm succeeded in creating overlapping reading frames in 80% of E. coli genes. Experimentally, scoring mutations in both genes of such overlapping construct, we found that a significant fraction of mutations impacting the gene to protect have a deleterious effect on the essential gene. Such an overlap thus protects a costly gene from removal by natural selection by associating the benefit of this removal with a larger or even lethal cost. In our synthetic constructs, the overlap converts many of the possible mutants into evolutionary dead-ends, reducing the evolutionary potential of the system and thus increasing its stability over time.

Genomes are translated by triplets of nucleotides on two different strands, allowing for six different reading frames. This permits the existence of gene overlaps, often observed in microbial genomes, where two different proteins are encoded on the same piece of DNA, but in different reading frames. Gene overlaps are classically considered an obstacle for both evolution and genetic engineering, as mutations in overlapping regions likely have pleitrotropic effects on several genes. In 2013, we identified specific evolutionary scenarios where the decrease in evolutionary potential caused by gene overlaps could instead be advantageous and selected for. In this work, we demonstrate the use of gene overlaps in another context where reducing evolutionary potential can be useful: preventing evolution from inactivating synthetic circuits. We show that gene overlaps can be engineered to increase the evolutionary stability of genes that are costly to their hosts, by entangling these costly genes with essential genes.

From genotypes to organisms: State-of-the-art and perspectives of a cornerstone in evolutionary dynamics

Understanding how genotypes map onto phenotypes, fitness, and eventually organisms is arguably the next major missing piece in a fully predictive theory of evolution. We refer to this generally as the problem of the genotype-phenotype map. Though we are still far from achieving a complete picture of these relationships, our current understanding of simpler questions, such as the structure induced in the space of genotypes by sequences mapped to molecular structures, has revealed important facts that deeply affect the dynamical description of evolutionary processes. Empirical evidence supporting the fundamental relevance of features such as phenotypic bias is mounting as well, while the synthesis of conceptual and experimental progress leads to questioning current assumptions on the nature of evolutionary dynamics-cancer progression models or synthetic biology approaches being notable examples. This work delves with a critical and constructive attitude into our current knowledge of how genotypes map onto molecular phenotypes and organismal functions, and discusses theoretical and empirical avenues to broaden and improve this comprehension. As a final goal, this community should aim at deriving an updated picture of evolutionary processes soundly relying on the structural properties of genotype spaces, as revealed by modern techniques of molecular and functional analysis.

Suppressing evolution in genetically engineered systems through repeated supplementation

Genetically engineered organisms are prone to evolve in response to the engineering. This evolution is often undesirable and can negatively affect the purpose of the engineering. Methods that maintain the stability of engineered genomes are therefore critical to the successful design and use of genetically engineered organisms. One potential method to limit unwanted evolution is by taking advantage of the ability of gene flow to counter local adaption, a process of supplementation. Here, we investigate the feasibility of supplementation as a mechanism to offset the evolutionary degradation of a transgene in three model systems: a bioreactor, a gene drive, and a transmissible vaccine. In each model, continual introduction from a stock is used to balance mutation and selection against the transgene. Each system has its unique features. The bioreactor system is especially tractable and has a simple answer: The level of supplementation required to maintain the transgene at a frequency p ^ is approximatelyp ^ s , where s is the selective disadvantage of the transgene. Supplementation is also feasible in the transmissible vaccine case but is probably not practical to prevent the evolution of resistance against a gene drive. We note, however, that the continual replacement of even a small fraction of a large population can be challenging, limiting the usefulness of supplementation as a means of controlling unwanted evolution.

Evolutionary principles and genetic considerations for guiding conservation interventions under climate change

Impacts of climate change are apparent in natural systems around the world. Many species are and will continue to struggle to persist in their current location as their preferred environment changes. Traditional conservation efforts aiming to prevent local extinctions have focused on two aspects that theoretically enhance genetic diversity-population connectivity and population size-through 'passive interventions' (such as protected areas and connectivity corridors). However, the exceptionally rapid loss of biodiversity that we are experiencing as result of anthropogenic climate change has shifted conservation approaches to more 'active interventions' (such as rewilding, assisted gene flow, assisted evolution, artificial selection, genetic engineering). We integrate genetic/genomic approaches into an evolutionary biology framework in order to discuss with scientists, conservation managers and decision makers about the opportunities and risks of interventions that need careful consideration in order to avoid unwanted evolutionary outcomes.

Short and long-read ultra-deep sequencing profiles emerging heterogeneity across five platform Escherichia coli strains

Reprogramming organisms for large-scale bioproduction counters their evolutionary objectives of fast growth and often leads to mutational collapse of the engineered production pathways during cultivation. Yet, the mutational susceptibility of academic and industrial Escherichia coli bioproduction host strains are poorly understood. In this study, we apply 2^nd and 3^rd generation deep sequencing to profile simultaneous modes of genetic heterogeneity that decimate engineered biosynthetic production in five popular E. coli hosts BL21(DE3), TOP10, MG1655, W, and W3110 producing 2,3-butanediol and mevalonic acid. Combining short-read and long-read sequencing, we detect strain and sequence-specific mutational modes including single nucleotide polymorphism, inversion, and mobile element transposition, as well as complex structural variations that disrupt the integrity of the engineered biosynthetic pathway. Our analysis suggests that organism engineers should avoid chassis strains hosting active insertion sequence (IS) subfamilies such as IS1 and IS10 present in popular E. coli TOP10. We also recommend monitoring for increased mutagenicity in the pathway transcription initiation regions and recombinogenic repeats. Together, short and long sequencing reads identified latent low-frequency mutation events such as a short detrimental inversion within a pathway gene, driven by 8-bp short inverted repeats. This demonstrates the power of combining ultra-deep DNA sequencing technologies to profile genetic heterogeneities of engineered constructs and explore the markedly different mutational landscapes of common E. coli host strains. The observed multitude of evolving variants underlines the usefulness of early mutational profiling for new synthetic pathways designed to sustain in organisms over long cultivation scales.

The future of self-selecting and stable fermentations

Unfavorable cell heterogeneity is a frequent risk during bioprocess scale-up and characterized by rising frequencies of low-producing cells. Low-producing cells emerge by both non-genetic and genetic variation and will enrich due to their higher specific growth rate during the extended number of cell divisions of large-scale bioproduction. Here, we discuss recent strategies for synthetic stabilization of fermentation populations and argue for their application to make cell factory designs that better suit industrial needs. Genotype-directed strategies leverage DNA-sequencing data to inform strain design. Self-selecting phenotype-directed strategies couple high production with cell proliferation, either by redirected metabolic pathways or synthetic product biosensing to enrich for high-performing cell variants. Evaluating production stability early in new cell factory projects will guide heterogeneity-reducing design choices. As good initial metrics, we propose production half-life from standardized serial-passage stability screens and production load, quantified as production-associated percent-wise growth rate reduction. Incorporating more stable genetic designs will greatly increase scalability of future cell factories through sustaining a high-production phenotype and enabling stable long-term production.

Controlling evolutionary dynamics to optimize microbial bioremediation

Some microbes have a fascinating ability to degrade compounds that are toxic for humans in a process called bioremediation. Although these traits help microbes survive the toxins, carrying them can be costly if the benefit of detoxification is shared by all surrounding microbes, whether they detoxify or not. Detoxification can thereby be seen as a public goods game, where nondegrading mutants can sweep through the population and collapse bioremediation. Here, we constructed an evolutionary game theoretical model to optimize bioremediation in a chemostat initially containing "cooperating" (detoxifying) microbes. We consider two types of mutants: "cheaters" that do not detoxify, and mutants that become resistant to the toxin through private mechanisms that do not benefit others. By manipulating the concentration and flow rate of a toxin into the chemostat, we identified conditions where cooperators can exclude cheaters that differ in their private resistance. However, eventually, cheaters are bound to invade. To overcome this inevitable outcome and maximize detoxification efficiency, cooperators can be periodically reinoculated into the population. Our study investigates the outcome of an evolutionary game combining both public and private goods and demonstrates how environmental parameters can be used to control evolutionary dynamics in practical applications.

Chromatin Structure and Drug Resistance in Candida spp

Anti-microbial resistance (AMR) is currently one of the most serious threats to global human health and, appropriately, research to tackle AMR garnishes significant investment and extensive attention from the scientific community. However, most of this effort focuses on antibiotics, and research into anti-fungal resistance (AFR) is vastly under-represented in comparison. Given the growing number of vulnerable, immunocompromised individuals, as well as the positive impact global warming has on fungal growth, there is an immediate urgency to tackle fungal disease, and the disturbing rise in AFR. Chromatin structure and gene expression regulation play pivotal roles in the adaptation of fungal species to anti-fungal stress, suggesting a potential therapeutic avenue to tackle AFR. In this review we discuss both the genetic and epigenetic mechanisms by which chromatin structure can dictate AFR mechanisms and will present evidence of how pathogenic yeast, specifically from the Candida genus, modify chromatin structure to promote survival in the presence of anti-fungal drugs. We also discuss the mechanisms by which anti-chromatin therapy, specifically lysine deacetylase inhibitors, influence the acquisition and phenotypic expression of AFR in Candida spp. and their potential as effective adjuvants to mitigate against AFR.

Advances in Molecular Tools and In Vivo Models for the Study of Human Fungal Pathogenesis

Pathogenic fungi represent an increasing infectious disease threat to humans, especially with an increasing challenge of antifungal drug resistance. Over the decades, numerous tools have been developed to expedite the study of pathogenicity, initiation of disease, drug resistance and host-pathogen interactions. In this review, we highlight advances that have been made in the use of molecular tools using CRISPR technologies, RNA interference and transposon targeted mutagenesis. We also discuss the use of animal models in modelling disease of human fungal pathogens, focusing on zebrafish, the silkworm, Galleria mellonella and the murine model.

Evolution and containment of transmissible recombinant vector vaccines

Transmissible vaccines offer a revolutionary approach for controlling infectious disease and may provide one of the few feasible methods for eliminating pathogens from inaccessible wildlife populations. Current efforts to develop transmissible vaccines use recombinant vector technology whereby pathogen antigens are engineered to be expressed from innocuous infectious viral vectors. The resulting vaccines can transmit from host to host, amplifying the number of vaccine-protected individuals beyond those initially vaccinated directly through parenteral inoculation. One main engineering challenge is the potential for natural selection to favor vaccine mutants that eliminate or reduce expression of antigenic inserts, resulting in immunogenic decay of the vaccine over time. Here, we study a mathematical model of vector mutation whereby continuous elimination of the antigenic insert results in reversion of the vaccine back into the insert-free vector. We use this model to quantify the maximum allowable rate of reversion that can be tolerated for a transmissible vaccine to maintain a critical threshold level of immunogenicity against a target pathogen. Our results demonstrate that even for transmissible vaccines where reversion is frequent, performance will often substantially exceed that of conventional, directly administered vaccines. Further, our results demonstrate the feasibility of designing transmissible vaccines that yield desired levels of immunogenicity, yet degrade at a rate sufficient for persistence of the recombinant vaccine within the environment to be minimized.

Recent advances in plasmid-based tools for establishing novel microbial chassis

A key challenge for domesticating alternative cultivable microorganisms with biotechnological potential lies in the development of innovative technologies. Within this framework, a myriad of genetic tools has flourished, allowing the design and manipulation of complex synthetic circuits and genomes to become the general rule in many laboratories rather than the exception. More recently, with the development of novel technologies such as DNA automated synthesis/sequencing and powerful computational tools, molecular biology has entered the synthetic biology era. In the beginning, most of these technologies were established in traditional microbial models (known as chassis in the synthetic biology framework) such as Escherichia coli and Saccharomyces cerevisiae, enabling fast advances in the field and the validation of fundamental proofs of concept. However, it soon became clear that these organisms, although extremely useful for prototyping many genetic tools, were not ideal for a wide range of biotechnological tasks due to intrinsic limitations in their molecular/physiological properties. Over the last decade, researchers have been facing the great challenge of shifting from these model systems to non-conventional chassis with endogenous capacities for dealing with specific tasks. The key to address these issues includes the generation of narrow and broad host plasmid-based molecular tools and the development of novel methods for engineering genomes through homologous recombination systems, CRISPR/Cas9 and other alternative methods. Here, we address the most recent advances in plasmid-based tools for the construction of novel cell factories, including a guide for helping with "build-your-own" microbial host.

CRISPR-interference-based modulation of mobile genetic elements in bacteria

Spontaneous mutagenesis of synthetic genetic constructs by mobile genetic elements frequently results in the rapid loss of engineered functions. Previous efforts to minimize such mutations required the exceedingly time-consuming manipulation of bacterial chromosomes and the complete removal of insertional sequences (ISes). To this aim, we developed a single plasmid-based system (pCRIS) that applies CRISPR-interference to inhibit the transposition of bacterial ISes. pCRIS expresses multiple guide RNAs to direct inactivated Cas9 (dCas9) to simultaneously silence IS1, IS3, IS5 and IS150 at up to 38 chromosomal loci in Escherichia coli, in vivo. As a result, the transposition rate of all four targeted ISes dropped to negligible levels at both chromosomal and episomal targets. Most notably, pCRIS, while requiring only a single plasmid delivery performed within a single day, provided a reduction of IS-mobility comparable to that seen in genome-scale chromosome engineering projects. The fitness cost of multiple IS-knockdown, detectable in flask-and-shaker systems was readily outweighed by the less frequent inactivation of the transgene, as observed in green fluorescent protein (GFP)-overexpression experiments. In addition, global transcriptomics analysis revealed only minute alterations in the expression of untargeted genes. Finally, the transposition-silencing effect of pCRIS was easily transferable across multiple E. coli strains. The plasticity and robustness of our IS-silencing system make it a promising tool to stabilize bacterial genomes for synthetic biology and industrial biotechnology applications.

Development of a multi-locus CRISPR gene drive system in budding yeast

The discovery of CRISPR/Cas gene editing has allowed for major advances in many biomedical disciplines and basic research. One arrangement of this biotechnology, a nuclease-based gene drive, can rapidly deliver a genetic element through a given population and studies in fungi and metazoans have demonstrated the success of such a system. This methodology has the potential to control biological populations and contribute to eradication of insect-borne diseases, agricultural pests, and invasive species. However, there remain challenges in the design, optimization, and implementation of gene drives including concerns regarding biosafety, containment, and control/inhibition. Given the numerous gene drive arrangements possible, there is a growing need for more advanced designs. In this study, we use budding yeast to develop an artificial multi-locus gene drive system. Our minimal setup requires only a single copy of S. pyogenes Cas9 and three guide RNAs to propagate three gene drives. We demonstrate how this system could be used for targeted allele replacement of native genes and to suppress NHEJ repair systems by modifying DNA Ligase IV. A multi-locus gene drive configuration provides an expanded suite of options for complex attributes including pathway redundancy, combatting evolved resistance, and safeguards for control, inhibition, or reversal of drive action.

Directed evolution of Escherichia coli with lower-than-natural plasmid mutation rates

Unwanted evolution of designed DNA sequences limits metabolic and genome engineering efforts. Engineered functions that are burdensome to host cells and slow their replication are rapidly inactivated by mutations, and unplanned mutations with unpredictable effects often accumulate alongside designed changes in large-scale genome editing projects. We developed a directed evolution strategy, Periodic Reselection for Evolutionarily Reliable Variants (PResERV), to discover mutations that prolong the function of a burdensome DNA sequence in an engineered organism. Here, we used PResERV to isolate Escherichia coli cells that replicate ColE1-type plasmids with higher fidelity. We found mutations in DNA polymerase I and in RNase E that reduce plasmid mutation rates by 6- to 30-fold. The PResERV method implicitly selects to maintain the growth rate of host cells, and high plasmid copy numbers and gene expression levels are maintained in some of the evolved E. coli strains, indicating that it is possible to improve the genetic stability of cellular chassis without encountering trade-offs in other desirable performance characteristics. Utilizing these new antimutator E. coli and applying PResERV to other organisms in the future promises to prevent evolutionary failures and unpredictability to provide a more stable genetic foundation for synthetic biology.

Viral Manipulation of Plant Stress Responses and Host Interactions With Insects

Do the alterations in plant defensive signaling and metabolism that occur in susceptible hosts following virus infection serve any purpose beyond directly aiding viruses to replicate and spread? Or indeed, are these modifications to host phenotype purely incidental consequences of virus infection? A growing body of data, in particular from studies of viruses vectored by whiteflies and aphids, indicates that viruses influence the efficiency of their own transmission by insect vectors and facilitate mutualistic relationships between viruses and their insect vectors. Furthermore, it appears that viruses may be able to increase the opportunity for transmission in the long term by providing reward to the host plants that they infect. This may be conditional, for example, by aiding host survival under conditions of drought or cold or, more surprisingly, by helping plants attract beneficial insects such as pollinators. In this chapter, we cover three main areas. First, we describe the molecular-level interactions governing viral manipulation of host plant biology. Second, we review evidence that virus-induced changes in plant phenotype enhance virus transmission. Finally, we discuss how direct and indirect manipulation of insects and plants might impact on the evolution of viruses and their hosts.

Innovation in an E. coli evolution experiment is contingent on maintaining adaptive potential until competition subsides

Key innovations are disruptive evolutionary events that enable a species to escape constraints and rapidly diversify. After 15 years of the Lenski long-term evolution experiment with Escherichia coli, cells in one of the twelve populations evolved the ability to utilize citrate, an abundant but previously untapped carbon source in the environment. Descendants of these cells became dominant in the population and subsequently diversified as a consequence of invading this vacant niche. Mutations responsible for the appearance of rudimentary citrate utilization and for refining this ability have been characterized. However, the complete nature of the genetic and/or ecological events that set the stage for this key innovation is unknown. In particular, it is unclear why it took so long for citrate utilization to evolve and why it still has evolved in only one of the twelve E. coli populations after 30 years of the Lenski experiment. In this study, we recapitulated the initial mutation needed to evolve citrate utilization in strains isolated from throughout the first 31,500 generations of the history of this population. We found that there was already a slight fitness benefit for this mutation in the original ancestor of the evolution experiment and in other early isolates. However, evolution of citrate utilization was blocked at this point due to competition with other mutations that improved fitness in the original niche. Subsequently, an anti-potentiated genetic background evolved in which it was deleterious to evolve rudimentary citrate utilization. Only later, after further mutations accumulated that restored the benefit of this first-step mutation and the overall rate of adaptation in the population slowed, was citrate utilization likely to evolve. Thus, intense competition and the types of mutations that it favors can lead to short-sighted evolutionary trajectories that hide a stepping stone needed to access a key innovation from many future generations.

Synthetic addiction extends the productive life time of engineered Escherichia coli populations

Bioproduction of chemicals offers a sustainable alternative to petrochemical synthesis routes by using genetically engineered microorganisms to convert waste and simple substrates into higher-value products. However, efficient high-yield production commonly introduces a metabolic burden that selects for subpopulations of nonproducing cells in large fermentations. To postpone such detrimental evolution, we have synthetically addicted production cells to production by carefully linking signals of product presence to expression of nonconditionally essential genes. We addict Escherichia coli cells to their engineered biosynthesis of mevalonic acid by fine-tuned control of essential genes using a product-responsive transcription factor. Over the course of a long-term fermentation equivalent to industrial 200-m³ bioreactors such addicted cells remained productive, unlike the control, in which evolution fully terminated production.

Bio-production of chemicals is an important driver of the societal transition toward sustainability. However, fermentations with heavily engineered production organisms can be challenging to scale to industrial volumes. Such fermentations are subject to evolutionary pressures that select for a wide range of genetic variants that disrupt the biosynthetic capacity of the engineered organism. Synthetic product addiction that couples high-yield production of a desired metabolite to expression of nonconditionally essential genes could offer a solution to this problem by selectively favoring cells with biosynthetic capacity in the population without constraining the medium. We constructed such synthetic product addiction by controlling the expression of two nonconditionally essential genes with a mevalonic acid biosensor. The product-addicted production organism retained high-yield mevalonic acid production through 95 generations of cultivation, corresponding to the number of cell generations required for >200-m³ industrial-scale production, at which time the nonaddicted strain completely abolished production. Using deep DNA sequencing, we find that the product-addicted populations do not accumulate genetic variants that compromise biosynthetic capacity, highlighting how synthetic networks can be designed to control genetic population heterogeneity. Such synthetic redesign of evolutionary forces with endogenous processes may be a promising concept for realizing complex cellular designs required for sustainable bio-manufacturing.

Biochemical mechanisms determine the functional compatibility of heterologous genes

Elucidating the factors governing the functional compatibility of horizontally transferred genes is important to understand bacterial evolution, including the emergence and spread of antibiotic resistance, and to successfully engineer biological systems. In silico efforts and work using single-gene libraries have suggested that sequence composition is a strong barrier for the successful integration of heterologous genes. Here we sample 200 diverse genes, representing >80% of sequenced antibiotic resistance genes, to interrogate the factors governing genetic compatibility in new hosts. In contrast to previous work, we find that GC content, codon usage, and mRNA-folding energy are of minor importance for the compatibility of mechanistically diverse gene products at moderate expression. Instead, we identify the phylogenetic origin, and the dependence of a resistance mechanism on host physiology, as major factors governing the functionality and fitness of antibiotic resistance genes. These findings emphasize the importance of biochemical mechanism for heterologous gene compatibility, and suggest physiological constraints as a pivotal feature orienting the evolution of antibiotic resistance.

Sequence composition is thought to be a major factor governing the functionality of horizontally transferred genes. In contrast, Porse et al. show that phylogenetic origin, and the type of resistance mechanism, are major factors affecting the functionality of horizontally transferred antibiotic resistance genes.

Evolutionary and genetic features of drug targets

In the modern drug discovery pipeline, identification of novel drug targets is a critical step. Despite rapid progress in developing biomedical techniques, it is still a great challenge to find promising new targets from the ample space of human genes. This fact is partially responsible for the situation of "more investments, fewer drugs" in the pharmaceutical industry. A series of recent researches revealed that successfully targeted genes share some common evolutionary and genetic features, which means that the knowledge accumulated in modern evolutionary biology and genetics is very helpful to identify potential drug targets and to find new drugs as well. In this article, we comprehensively summarize the links between human drug targets and genetic diseases and their evolutionary origins, with an attempt to introduce these novel concepts and their medical implications to the biomedical community.