Biology subjects

Kosterlitz, O.

Publications and source records attributed to Kosterlitz, O..

7 recordsLinked to original sources

bioRxiv2026

Horizontal gene transfer by plasmids relaxes the evolutionary constraints of its own tradeoff

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.

evolutionary biology↗

bioRxiv2026

Molecular pet or parasite? Exploring selection for vertical and horizontal plasmid transfer

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.

microbiology↗

bioRxiv2024

Evolution of a Plasmid Regulatory Circuit Ameliorates Plasmid Fitness Cost

Plasmids play a major role in rapid adaptation of bacteria by facilitating horizontal transfer of diverse genes, most notably those conferring antibiotic resistance. While most plasmids that replicate in a broad range of bacteria also persist well in diverse hosts, there are exceptions that are poorly understood. We investigated why a broad-host range plasmid, pBP136, originally found in clinical Bordetella pertussis isolates, quickly became extinct in laboratory Escherichia coli populations. Through experimental evolution we found that inactivation of a previously uncharacterized plasmid gene, upf31, drastically improved plasmid maintenance in E. coli. This gene inactivation resulted in decreased transcription of the global plasmid regulators (korA, korB, and korC) and numerous genes in their regulons. It also caused transcriptional changes in many chromosomal genes primarily related to metabolism. In silico analyses suggested that the change in plasmid transcriptome may be initiated by Upf31 interacting with the plasmid regulator KorB. Expression of upf31 in trans negatively affected persistence of pBP136{Delta}upf31 as well as the closely related archetypal IncP-1{beta} plasmid R751, which is stable in E. coli and natively encodes a truncated upf31 allele. Our results demonstrate that while the upf31 allele in pBP136 might advantageously modulate gene expression in its original host, B. pertussis, it has harmful effects in E. coli. Thus, evolution of a single plasmid gene can change the range of hosts in which that plasmid persists, due to effects on the regulation of plasmid gene transcription.

microbiology↗

bioRxiv2022

Evolutionary crowdsourcing: alignment of fitness landscapes allows cross-species adaptation of a horizontally transferred gene

Genes that undergo horizontal gene transfer (HGT) evolve in different genomic backgrounds as they move between hosts, in contrast to genes that evolve under strict vertical inheritance. Despite the ubiquity of HGT in microbial communities, the effects of host-switching on gene evolution have been understudied. Here, we present a novel framework to examine the consequences of host-switching on gene evolution by probing the existence and form of host-dependent mutational effects. We started exploring the effects of HGT on gene evolution by focusing on an antibiotic resistance gene (encoding a beta-lactamase) commonly found on conjugative plasmids in Enterobacteriaceae pathogens. By reconstructing the resistance landscape for a small set of mutationally connected alleles in three enteric species (Escherichia coli, Salmonella enterica, and Klebsiella pneumoniae), we uncovered that the landscape topographies were largely aligned with very low levels of host-dependent mutational effects. By simulating gene evolution with and without HGT using the species-specific empirical landscapes, we found that evolutionary outcomes were similar despite HGT. These findings suggest that the adaptive evolution of a mobile gene in one species can translate to adaptation in another species. In such a case, vehicles of cross-species HGT such as plasmids enable a distributed form of genetic evolution across a bacterial community, where species can crowdsource adaptation from other community members. The role of evolutionary crowdsourcing on the evolution of bacteria merits further investigation.

evolutionary biology↗

bioRxiv2022

The cost of information acquisition by natural selection

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 Kimuras basic theory. To overcome the restrictive assumptions of Kimuras 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 Kimuras 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 Kimuras 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.

evolutionary biology↗

bioRxiv2021

Estimating the rate of plasmid transfer with an adapted Luria-Delbrück fluctuation analysis and a case study on the evolution of plasmid transfer rate

To increase our basic understanding of the ecology and evolution of conjugative plasmids, we need a reliable estimate of their rate of transfer between bacterial cells. However, accurate estimates of plasmid transfer have remained elusive due to biological and experimental complexity. Current methods to measure transfer rate can be confounded by many factors. 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. Inspired by the classic fluctuation analysis of Luria and Delbruck, we develop a novel approach, the Luria-Delbruck method ( LDM), for estimating plasmid transfer rate. Our new approach embraces the stochasticity of conjugation departing from the current deterministic population dynamic methods. In addition, the LDM overcomes obstacles of traditional methods by not being affected by different 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. Significance StatementConjugative plasmids play significant roles in the ecology and evolution of microbial communities. Notably, antibiotic resistance genes are often encoded on conjugative plasmids. Thus, conjugation--the transfer of a plasmid copy from one cell to another--is a common way for antibiotic resistance to spread between important clinical pathogens. For both public health modeling and a basic understanding of microbial population biology, accurate estimates of this fundamental rate are of great consequence. We show that widely used methods can lead to biased estimates, deviating from true values by several orders of magnitude. Therefore, we developed a new approach, inspired by the classic fluctuation analysis of Luria and Delbruck, for accurately assessing the rate of plasmid conjugation under a variety of conditions.

microbiology↗

bioRxiv2018

Long-term population studies uncover the genome structure and genetic basis of xenobiotic and host plant adaptation in the herbivore Tetranychus urticae

Pesticide resistance arises rapidly in arthropod herbivores, as can host plant adaptation, and both are significant problems in agriculture. These traits have been challenging to study as both are often polygenic and many arthropods are genetically intractable. Here, we examined the genetic architecture of pesticide resistance and host plant adaptation in the two-spotted spider mite, Tetranychus urticae, a global agricultural pest. We show that the short generation time and high fecundity of T. urticae can be readily exploited in experimental evolution designs for high-resolution mapping of quantitative traits. As revealed by selection with spirodiclofen, an acetyl-CoA decarboxylase inhibitor, in populations from a cross between a spirodiclofen resistant and a susceptible strain, and which also differed in performance on tomato, we found that a limited number of loci could explain quantitative resistance to this compound. These were resolved to narrow genomic intervals, suggesting specific candidate genes, including acetyl-CoA decarboxylase itself, clustered and copy variable cytochrome P450 genes, and NADPH cytochrome P450 reductase, which encodes a redox partner for cytochrome P450s. For performance on tomato, candidate genomic regions for response to selection were distinct from those responding to the synthetic compound and were consistent with a more polygenic architecture. In accomplishing this work, we exploited the continuous nature of allele frequency changes across experimental populations to resolve the existing fragmented T.urticae draft genome to pseudochromosomes. This improved assembly was indispensable for our analyses, as it will be for future research with this model herbivore that is exceptionally amenable to genetic studies.

genetics↗