Abstract Horizontal gene transfer (HGT) is a defining feature of plasmid biology, enabling plasmids to spread between bacterial cells and driving the global dissemination of antibiotic resistance and other adaptive traits. HGT and vertical gene transfer (VGT) have long been assumed to be subject to an evolutionary tradeoff, where improvements in one come at the expense of the other. Yet whether this tradeoff reliably constrains plasmid evolution remains unclear. Through the first cross-literature synthesis examining both transmission traits across 16 studies and 245 plasmid-host pairs, we find mixed empirical evidence: patterns consistent with a tradeoff alongside outcomes that a strict tradeoff should make impossible. We propose that this contradiction is resolved by recognizing that a tradeoff is ensured only when plasmid-host pairs are well-adapted to one another. Because HGT introduces plasmids into novel hosts where this adaptation is disrupted, it systematically creates the very conditions under which near-term evolution need not be bound by a tradeoff. We support this framework empirically by documenting the first mutation that simultaneously improves both transmission modes, arising from a non-coevolved plasmid-host pair. These findings reveal a fundamental irony: the defining feature of plasmid transmission is the very mechanism that relaxes the evolutionary constraints of its own tradeoff.

Abstract Understanding the environmental conditions that drive selection for increased horizontal plasmid transfer is crucial for predicting the spread of plasmid-encoded antibiotic resistance. In natural systems, plasmids exhibit diverse lifestyles, ranging from “host-centric” strategies, which favor vertical gene transfer (VGT) from mother to daughter cell at the expense of horizontal mobility, to “parasitic” strategies, which favor horizontal gene transfer (HGT) by conjugation at the expense of host fitness. However, laboratory evolution experiments are biased towards host-centric evolution, highlighting a gap in our ability to consistently select for horizontal mobility. To understand this experimental bias, we developed a mathematical model to explore the invasion of pleiotropic transfer mutations. Using local linear stability analysis, we derived an invasion criterion establishing that, for a given pleiotropic cost, the availability of plasmid-free cells determines whether increased transfer is selected. We expanded this model to better represent our previous evolution experiment, in which selection for a host-centric mutant occurred despite the addition of plasmid-free cells and periodic selection for transconjugants. We found that standard batch culture protocols inherently impose strong selective pressure on VGT, heavily limiting the laboratory observation of increases in HGT. We experimentally and theoretically demonstrated that a simple protocol modification—minimizing excess growth by eliminating batch culture passages—effectively tips selection towards HGT. Finally, we performed a parameter sweep to predict the invasion success of hypothetical mutants across HGT-VGT phenotypic space. Our predictive framework can be used to further explore the evolution of plasmid transfer under conditions more representative of natural environments where medically and environmentally relevant plasmids evolve.

Resistance evolution can undermine antiviral treatment. However, targeting antivirals to shared viral proteins could inhibit resistance evolution if susceptible viruses sensitize resistant ones during cellular coinfection. Pocapavir, a poliovirus capsid inhibitor, uses this sociovirological interference strategy. While susceptible viruses substantially suppress pocapavir resistance in cell culture, a pocapavir clinical trial found widespread resistance and limited clearance time improvements in treated participants. Here, to reconcile these findings, we present an intrahost eco-evolutionary model of pocapavir-treated poliovirus, which reproduces both in vitro interference and clinical resistance evolution. In the short term, high densities of susceptible viruses sensitize resistant ones, mirroring cell culture results. However, over multiple replication cycles, pocapavir's high potency collapses viral density, reducing coinfection and enabling resistance evolution, as observed clinically. Because resistance suppression relies on coinfection, enhancing susceptible virus survival could offer therapeutic advantages. Counterintuitively, we demonstrate that lessening antiviral potency can increase coinfection, limiting resistance while also maintaining low viral load. These findings suggest that antivirals relying on viral intracellular interactions must balance immediate neutralization with preserving future coinfection for sustained inhibition. Explicitly considering the eco-evolutionary feedback encompassing viral density, shared phenotypes and absolute fitness provides new insights for effective therapy design and illuminates viral evolutionary dynamics more broadly.

While the evolutionary interests of mobile genetic elements may differ from those of their bacterial hosts, these elements can be beneficial for their hosts by delivering, disrupting, or activating genes. A recent paper by Sastre-Domínguez et al. describes a novel synergistic effect of mobile elements in clinically relevant bacteria, whereby conjugative plasmids that carry transposable elements can be agents of rapid adaptive change through an elevation in transposition-mediated mutation rate.

Simple multicellularity evolves readily in diverse unicellular species, but nascent multicellular groups are prone to reversion to unicellularity. Successful transitions to multicellularity therefore require subsequent mutations that promote the entrenchment of the higher-level unit, stabilizing it through time. Here we explore the causes of entrenchment using digital evolution. When faced with a trade-off between cellular metabolic productivity and information fidelity, digital “multicells” often evolve reproductive division of labor. Because digital “unicells” cannot circumvent this trade-off, unicellular revertants tend to exhibit low fitness relative to their differentiated multicellular ancestors. Thus, division of labor can drive the entrenchment of multicellularity. More generally, division of labor may play a crucial role in major transitions, enriching the complexity and functionality of higher-level units while enhancing their evolutionary stability.

Genes that undergo horizontal gene transfer (HGT) evolve in different genomic backgrounds. Despite the ubiquity of cross-species HGT, the effects of switching hosts on gene evolution remains understudied. Here, we present a framework to examine the evolutionary consequences of host-switching and apply this framework to an antibiotic resistance gene commonly found on conjugative plasmids. Specifically, we determined the adaptive landscape of this gene for a small set of mutationally connected genotypes in 3 enteric species. We uncovered that the landscape topographies were largely aligned with minimal host-dependent mutational effects. By simulating gene evolution over the experimentally gauged landscapes, we found that the adaptive evolution of the mobile gene in one species translated to adaptation in another. By simulating gene evolution over artificial landscapes, we found that sufficient alignment between landscapes ensures such "adaptive equivalency" across species. Thus, given adequate landscape alignment within a bacterial community, vehicles of HGT such as plasmids may enable a distributed form of genetic evolution across community members, where species can "crowdsource" adaptation.

Natural selection enriches genotypes that are well-adapted to their environment. Over successive generations, these changes to the frequencies of types accumulate information about the selective conditions. Thus, we can think of selection as an algorithm by which populations acquire information about their environment. Kimura (1961) pointed out that every bit of information that the population gains this way comes with a minimum cost in terms of unrealized fitness (substitution load). Due to the gradual nature of selection and ongoing mismatch of types with the environment, a population that is still gaining information about the environment has lower mean fitness than a counter-factual population that already has this information. This has been an influential insight, but here we find that experimental evolution of Escherichia coli with mutations in a RNA polymerase gene (rpoB) violates Kimura’s basic theory. To overcome the restrictive assumptions of Kimura’s substitution load and develop a more robust measure for the cost of selection, we turn to ideas from computational learning theory. We reframe the ‘learning problem’ faced by an evolving population as a population versus environment (PvE) game, which can be applied to settings beyond Kimura’s theory – such as stochastic environments, frequency-dependent selection, and arbitrary environmental change. We show that the learning theoretic concept of ‘regret’ measures relative lineage fitness and rigorously captures the efficiency of selection as a learning process. This lets us establish general bounds on the cost of information acquisition by natural selection. We empirically validate these bounds in our experimental system, showing that computational learning theory can account for the observations that violate Kimura’s theory. Finally, we note that natural selection is a highly effective learning process in that selection is an asymptotically optimal algorithm for the problem faced by evolving populations, and no other algorithm can consistently outperform selection in general. Our results highlight the centrality of information to natural selection and the value of computational learning theory as a perspective on evolutionary biology.

During the struggle for survival, populations occasionally evolve new functions that give them access to untapped ecological opportunities. Theory suggests that coevolution between species can promote the evolution of such innovations by deforming fitness landscapes in ways that open new adaptive pathways. We directly tested this idea by using high-throughput gene editing-phenotyping technology (MAGE-Seq) to measure the fitness landscape of a virus, bacteriophage λ, as it coevolved with its host, the bacterium Escherichia coli. An analysis of the empirical fitness landscape revealed mutation-by-mutation-by-host-genotype interactions that demonstrate coevolution modified the contours of λ’s landscape. Computer simulations of λ’s evolution on a static versus shifting fitness landscape showed that the changes in contours increased λ’s chances of evolving the ability to use a new host receptor. By coupling sequencing and pairwise competition experiments, we demonstrated that the first mutation λ evolved en route to the innovation would only evolve in the presence of the ancestral host, whereas later steps in λ’s evolution required the shift to a resistant host. When time-shift replays of the coevolution experiment were run where host evolution was artificially accelerated, λ did not innovate to use the new receptor. This study provides direct evidence for the role of coevolution in driving evolutionary novelty and provides a quantitative framework for predicting evolution in coevolving ecological communities.

To increase our basic understanding of the ecology and evolution of conjugative plasmids, we need reliable estimates of their rate of transfer between bacterial cells. Current assays to measure transfer rate are based on deterministic modeling frameworks. However, some cell numbers in these assays can be very small, making estimates that rely on these numbers prone to noise. Here, we take a different approach to estimate plasmid transfer rate, which explicitly embraces this noise. Inspired by the classic fluctuation analysis of Luria and Delbrück, our method is grounded in a stochastic modeling framework. In addition to capturing the random nature of plasmid conjugation, our new methodology, the Luria-Delbrück method ("LDM"), can be used on a diverse set of bacterial systems, including cases for which current approaches are inaccurate. A notable example involves plasmid transfer between different strains or species where the rate that one type of cell donates the plasmid is not equal to the rate at which the other cell type donates. Asymmetry in these rates has the potential to bias or constrain current transfer estimates, thereby limiting our capabilities for estimating transfer in microbial communities. In contrast, the LDM overcomes obstacles of traditional methods by avoiding restrictive assumptions about growth and transfer rates for each population within the assay. Using stochastic simulations and experiments, we show that the LDM has high accuracy and precision for estimation of transfer rates compared to the most widely used methods, which can produce estimates that differ from the LDM estimate by orders of magnitude.

A population under selection to improve one trait may evolve a sub-optimal state for another trait due to tradeoffs and other evolutionary constraints. How this evolution affects the capacity of a population to adapt when conditions change to favor the second trait is an open question. We investigated this question using isolates from a lineage spanning 60,000 generations of the Long-Term Evolution Experiment (LTEE) with Escherichia coli , where cells have access to a shared pool of resources, and have evolved increased competitive ability and a concomitant reduction in numerical yield. Using media-in oil emulsions we shifted the focus of selection to numerical yield, where cells grew in isolated patches with private resources. We found that the time spent evolving under shared resources did not affect the ability to re-evolve toward higher numerical yield. The evolution of numerical yield commonly occurred through mutations in the phosphoenolpyruvate phosphotransferase system. These mutants exhibit slower uptake of glucose, making them poorer competitors for public resources, and produce smaller cells that release less carbon as overflow metabolites. Our results demonstrate that mutations that were not part of adaptation under one selective regime may enable access to ancestral phenotypes when selection changes to favor evolutionary reversion.

Tradeoff theory, which postulates that virulence provides both transmission costs and benefits for pathogens, has become widely adopted by the scientific community. Although theoretical literature exploring virulence-tradeoffs is vast, empirical studies validating various assumptions still remain sparse. In particular, truncation of transmission duration as a cost of virulence has been difficult to quantify with robust controlled in vivo studies. We sought to fill this knowledge gap by investigating how transmission rate and duration were associated with virulence for infectious hematopoietic necrosis virus (IHNV) in rainbow trout (Oncorhynchus mykiss). Using host mortality to quantify virulence and viral shedding to quantify transmission, we found that IHNV did not conform to classical tradeoff theory. More virulent genotypes of the virus were found to have longer transmission durations due to lower recovery rates of infected hosts, but the relationship was not saturating as assumed by tradeoff theory. Furthermore, the impact of host mortality on limiting transmission duration was minimal and greatly outweighed by recovery. Transmission rate differences between high and low virulence genotypes were also small and inconsistent. Ultimately, more virulent genotypes were found to have the overall fitness advantage, and there was no apparent constraint on the evolution of increased virulence for IHNV. However, using a mathematical model parameterized with experimental data, it was found that host culling resurrected the virulence tradeoff and provided low virulence genotypes with the advantage. Human-induced or natural culling, as well as host population fragmentation, may be some of the mechanisms by which virulence diversity is maintained in nature. This work highlights the importance of considering non-classical virulence tradeoffs.

Multidrug resistance (MDR) of pathogens is an ongoing public health crisis exacerbated by the horizontal transfer of antibiotic resistance genes via conjugative plasmids. Factors that stabilize these plasmids in bacterial communities contribute to an even higher incidence of MDR, given the increased likelihood that a host will already contain a plasmid when it acquires another through conjugation. Here, we show one such stabilizing factor is host–plasmid coevolution under antibiotic selection, which facilitated the emergence of MDR via two distinct plasmids in communities consisting of Escherichia coli and Klebsiella pneumoniae once antibiotics were removed. In our system, evolution promoted greater stability of a plasmid in its coevolved host. Further, pleiotropic effects resulted in greater plasmid persistence in both novel host–plasmid combinations and, in some cases, multi-plasmid hosts. This evolved stability favoured the generation of MDR cells and thwarted their loss within communities with multiple plasmids. By selecting for plasmid persistence, the application of antibiotics may promote MDR well after their original period of use. Experimental evolution shows that host–plasmid coevolution in the presence of antibiotics promoted the emergence of multidrug resistance via two distinct conjugative plasmids in communities of Escherichia coli and Klebsiella pneumoniae once antibiotics were removed.

Wright’s “adaptive landscape” has been influential in evolutionary thinking but controversial, especially because the landscape that organisms encounter is altered by the evolutionary process itself and the effects organisms have on their environments. Lewontin offered a mathematical heuristic describing the coupling of niche construction and adaptive evolution. Here, we propose a “dual landscape” model to view these relationships. Our model represents change as simultaneous movement on two landscapes, each a function of phenotype and environment. This model clarifies the evolutionary feedback generated by niche construction. We relate our model to Lewontin’s niche construction equations and illustrate it with three examples.

The astonishing complexity of the world around us is the result of major transitions in evolution where lower-level entities unite to form a higher-level unit: living and reproducing as one. These transitions give rise to many questions within evolutionary biology, but can prove challenging to study due to their rare occurrence in nature. Here, we describe a digital evolution approach where cells, organisms, and worlds all exist within the framework of a computer and as such have rapid generation times and are amenable to experimental control, replaying key events, and precise data tracking. Using this approach we describe our previous experiments exploring fraternal major transitions in evolution—transitions that occur when identical lower-level units (e.g., cells) remain together as one higher-level unit (e.g., a multicellular organism). We have performed experiments to test key hypotheses regarding the formation of higher-level units and the reproductive and task-based division of labor that can evolve once these units are in place.We then describe a series of on-going studies that explore hypotheses regarding the forces that prevent higher-level units from reverting to their lower-level origins, how plasticity may predispose the evolution of division of labor, and how egalitarian transitions (which occur when different lower-level units come together) may occur.

Journal of Political PhilosophyVolume 27, Issue 4 p. 403-421 Original Article Tolerance: A Hierarchical Analysis† Peter Godfrey-Smith, Peter Godfrey-Smith History and Philosophy of Science, University of SydneySearch for more papers by this authorBenjamin Kerr, Benjamin Kerr Biology, University of WashingtonSearch for more papers by this author Peter Godfrey-Smith, Peter Godfrey-Smith History and Philosophy of Science, University of SydneySearch for more papers by this authorBenjamin Kerr, Benjamin Kerr Biology, University of WashingtonSearch for more papers by this author First published: 14 February 2019 https://doi.org/10.1111/jopp.12178Citations: 5 †We are grateful to two anonymous referees for helpful comments. Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat Citing Literature Volume27, Issue4December 2019Pages 403-421 RelatedInformation

A new proposal submission policy announced by the U.S. National Science Foundation Biology Directorate mandates that researchers can serve as principal investigator or co-PI on only one proposal per fiscal year to each of the core tracks of the Divisions of Environmental Biology, Integrative Organismal Systems, and Molecular and Cellular Biosciences. The rationale for the restriction is apparently to prevent rapid resubmission of declined proposals; however other NSF programs without deadlines simply prohibit rapid resubmission of proposals and some place no restrictions on submissions. We are deeply concerned that the new restrictions will damage biological research by limiting researchers’ ability to collaborate. In addition, the restrictions will exacerbate pressure on early-career colleagues who may turn to safe, fundable submissions rather than novel and transformative ideas. We write this letter in hopes of raising the alarm about this misguided and harmful new policy.

Organisms often modify their environments to their advantage through a process of niche construction. Environments that are improved through positive niche construction can be viewed as a public good. If free riders appear that do not contribute to the shared resource and therefore do not incur any associated costs, the constructed niche may become degraded, resulting in a tragedy of the commons and the extinction of niche constructors. Niche construction can persist if free riders are excluded, for example, if niche constructors monopolize the resource they produce to a sufficient degree. We suggest, however, that the problem of free riders remains because it is possible that nonniche constructors with an enhanced ability to access the resource appear and invade a population of constructors. Using mathematical models we show that positive niche construction can be maintained if it is inextricably linked to a mechanism that makes free riding costly, such as a trait that confers a benefit to only niche constructors. We discuss this finding in terms of genetic interactions and illustrate the principle with a two-locus model. We conclude that positive niche construction can both evolve and be maintained when it has other beneficial effects via pleiotropy. This situation may apply generally to the evolutionary maintenance of cooperation.

Environments can change in incremental fashions, where a shift from one state to another occurs over multiple organismal generations. The rate at which the environment changes is expected to influence how and how well populations adapt to the ultimate environment. We used a model system, the lytic RNA bacteriophage Φ6, to investigate this question empirically. We evolved viruses for thermostability by exposing them to heat shocks that increased to a maximum temperature at different rates. We observed increases in the ability of many heat-shocked populations to survive high temperature heat shocks, and on their first exposure to the highest temperature, populations that experienced a gradual increase in temperature had higher average survival than populations that experienced a rapid temperature increase. However, at the end of the experiment, neither the survival of populations at the highest temperature nor the number of mutations per population varied significantly according to the rate of thermal change. We also evaluated mutations from the endpoint populations for their effects on viral thermostability and growth. As expected, some mutations did increase viral thermostability. However, other mutations decreased thermostability but increased growth rate, suggesting that benefits of an increased replication rate may have sometimes outweighed the benefits of enhanced thermostability. Our study highlights the importance of considering the effects of multiple selective pressures, even in environments where a single factor is changing.

Viral replication and shedding are key components of transmission and fitness, the kinetics of which are heavily dependent on virus, host, and environmental factors. To date, no studies have quantified the shedding kinetics of infectious hematopoietic necrosis virus (IHNV) in rainbow trout (Oncorhynchus mykiss), or how they are associated with replication, making it difficult to ascertain the transmission dynamics of this pathogen of high agricultural and conservation importance. Here, the replication and shedding kinetics of two M genogroup IHNV genotypes were examined in their naturally co-evolved rainbow trout host. Within host virus replication began rapidly, approaching maximum values by day 3 post-infection, after which viral load was maintained or gradually dropped through day 7. Host innate immune response measured as stimulation of Mx-1 gene expression generally followed within host viral loads. Shedding also began very quickly and peaked within 2days, defining a generally uniform early peak period of shedding from 1 to 4days after exposure to virus. This was followed by a post-peak period where shedding declined, such that the majority of fish were no longer shedding by day 12 post-infection. Despite similar kinetics, the average shedding rate over the course of infection was significantly lower in mixed compared to single genotype infections, suggesting a competition effect, however, this did not significantly impact the total amount of virus shed. The data also indicated that the duration of shedding, rather than peak amount of virus shed, was correlated with fish mortality. Generally, the majority of virus produced during infection appeared to be shed into the environment rather than maintained in the host, although there was more retention of within host virus during the post-peak period. Viral virulence was correlated with shedding, such that the more virulent of the two genotypes shed more total virus. This fundamental understanding of IHNV shedding kinetics and variation at the individual fish level could assist with management decisions about how to respond to disease outbreaks when they occur.

Fitness landscapes are visual metaphors that appeal to our intuition for real-world landscapes to help us understand how populations evolve. The object inspiring the metaphor is better described as...