Decay of unused characters by selection and drift

The reduction and loss of redundant phenotypic characters is a common feature of evolution. However, the mechanisms that drive deterioration of unused characters remain unclear. Here, we outline a simple framework where the relative importance of selective and neutral processes varies with environmental factors, because of variation in the fitness costs associated with unused traits. We tested our hypotheses using experimental evolution of the bacterium Pseudomonas fluorescens in spatially uniform environments. Results show that an unused character, swimming motility, decayed over evolutionary time and the rate of this decay varied among selection environments with different levels of resource availability. This is explained in the context of an environment-specific genetic correlation between motility and fitness, which is negative when resources are limited but neutral at higher resource levels. Thus, selection against an unused character was most effective in environments where the fitness cost was the greatest. This suggests that the same character can decay by different mechanisms depending upon environmental factors and supports previous evidence to show that resource availability can critically affect the outcomes of evolution.     

Decreased thermal niche breadth as a trade-off of antibiotic resistance

Evolutionary theory predicts that adaptations, including antibiotic resistance, should come with associated fitness costs; yet, many resistance mutations seemingly contradict this prediction by inducing no growth rate deficit. However, most growth assays comparing sensitive and resistant strains have been performed under a narrow range of environmental conditions, which do not reflect the variety of contexts that a pathogenic bacterium might encounter when causing infection. We hypothesized that reduced niche breadth, defined as diminished growth across a diversity of environments, can be a cost of antibiotic resistance. Specifically, we test whether chloramphenicol-resistant Escherichia coli incur disproportionate growth deficits in novel thermal conditions. Here we show that chloramphenicol-resistant bacteria have greater fitness costs at novel temperatures than their antibiotic-sensitive ancestors. In several cases, we observed no resistance cost in growth rate at the historic temperature but saw diminished growth at warmer and colder temperatures. These results were consistent across various genetic mechanisms of resistance. Thus, we propose that decreased thermal niche breadth is an under-documented fitness cost of antibiotic resistance. Furthermore, these results demonstrate that the cost of antibiotic resistance shifts rapidly as the environment changes; these context-dependent resistance costs should select for the rapid gain and loss of resistance as an evolutionary strategy.Subject terms: Bacterial evolution, Microbial ecology, Antibiotics     

Suboptimal resource allocation in changing environments constrains response and growth in bacteria

To respond to fluctuating conditions, microbes typically need to synthesize novel proteins. As this synthesis relies on sufficient biosynthetic precursors, microbes must devise effective response strategies to manage depleting precursors. To better understand these strategies, we investigate the active response of Escherichia coli to changes in nutrient conditions, connecting transient gene expression to growth phenotypes. By synthetically modifying gene expression during changing conditions, we show how the competition by genes for the limited protein synthesis capacity constrains cellular response. Despite this constraint cells substantially express genes that are not required, trapping them in states where precursor levels are low and the genes needed to replenish the precursors are outcompeted. Contrary to common modeling assumptions, our findings highlight that cells do not optimize growth under changing environments but rather exhibit hardwired response strategies that may have evolved to promote fitness in their native environment. The constraint and the suboptimality of the cellular response uncovered provide a conceptual framework relevant for many research applications, from the prediction of evolution to the improvement of gene circuits in biotechnology.     

Protein Homeostasis Imposes a Barrier on Functional Integration of Horizontally Transferred Genes in Bacteria

Horizontal gene transfer (HGT) plays a central role in bacterial evolution, yet the molecular and cellular constraints on functional integration of the foreign genes are poorly understood. Here we performed inter-species replacement of the chromosomal folA gene, encoding an essential metabolic enzyme dihydrofolate reductase (DHFR), with orthologs from 35 other mesophilic bacteria. The orthologous inter-species replacements caused a marked drop (in the range 10–90%) in bacterial growth rate despite the fact that most orthologous DHFRs are as stable as E.coli DHFR at 37°C and are more catalytically active than E. coli DHFR. Although phylogenetic distance between E. coli and orthologous DHFRs as well as their individual molecular properties correlate poorly with growth rates, the product of the intracellular DHFR abundance and catalytic activity (k _cat/K_M), correlates strongly with growth rates, indicating that the drop in DHFR abundance constitutes the major fitness barrier to HGT. Serial propagation of the orthologous strains for ~600 generations dramatically improved growth rates by largely alleviating the fitness barriers. Whole genome sequencing and global proteome quantification revealed that the evolved strains with the largest fitness improvements have accumulated mutations that inactivated the ATP-dependent Lon protease, causing an increase in the intracellular DHFR abundance. In one case DHFR abundance increased further due to mutations accumulated in folA promoter, but only after the lon inactivating mutations were fixed in the population. Thus, by apparently distinguishing between self and non-self proteins, protein homeostasis imposes an immediate and global barrier to the functional integration of foreign genes by decreasing the intracellular abundance of their products. Once this barrier is alleviated, more fine-tuned evolution occurs to adjust the function/expression of the transferred proteins to the constraints imposed by the intracellular environment of the host organism.     

Proteome constraints reveal targets for improving microbial fitness in nutrient‐rich environments

Cells adapt to different conditions via gene expression that tunes metabolism for maximal fitness. Constraints on cellular proteome may limit such expression strategies and introduce trade‐offs. Resource allocation under proteome constraints has explained regulatory strategies in bacteria. It is unclear, however, to what extent these constraints can predict evolutionary changes, especially for microorganisms that evolved under nutrient‐rich conditions, i.e., multiple available nitrogen sources, such as Lactococcus lactis. Here, we present a proteome‐constrained genome‐scale metabolic model of L. lactis (pcLactis) to interpret growth on multiple nutrients. Through integration of proteomics and flux data, in glucose‐limited chemostats, the model predicted glucose and arginine uptake as dominant constraints at low growth rates. Indeed, glucose and arginine catabolism were found upregulated in evolved mutants. At high growth rates, pcLactis correctly predicted the observed shutdown of arginine catabolism because limited proteome availability favored lactate for ATP production. Thus, our model‐based analysis is able to identify and explain the proteome constraints that limit growth rate in nutrient‐rich environments and thus form targets of fitness improvement.     

Phenotypic and Genetic Consequences of Protein Damage

Although the genome contains all the information necessary for maintenance and perpetuation of life, it is the proteome that repairs, duplicates and expresses the genome and actually performs most cellular functions. Here we reveal strong phenotypes of physiological oxidative proteome damage at the functional and genomic levels. Genome-wide mutations rates and biosynthetic capacity were monitored in real time, in single Escherichia coli cells with identical levels of reactive oxygen species and oxidative DNA damage, but with different levels of irreversible oxidative proteome damage (carbonylation). Increased protein carbonylation correlates with a mutator phenotype, whereas reducing it below wild type level produces an anti-mutator phenotype identifying proteome damage as the leading cause of spontaneous mutations. Proteome oxidation elevates also UV-light induced mutagenesis and impairs cellular biosynthesis. In conclusion, protein damage reduces the efficacy and precision of vital cellular processes resulting in high mutation rates and functional degeneracy akin to cellular aging.     

The basis of antagonistic pleiotropy in hfq mutations that have opposite effects on fitness at slow and fast growth rates

Mutations beneficial in one environment may cause costs in different environments, resulting in antagonistic pleiotropy. Here, we describe a novel form of antagonistic pleiotropy that operates even within the same environment, where benefits and deleterious effects exhibit themselves at different growth rates. The fitness of hfq mutations in Escherichia coli affecting the RNA chaperone involved in small-RNA regulation is remarkably sensitive to growth rate. E. coli populations evolving in chemostats under nutrient limitation acquired beneficial mutations in hfq during slow growth (0.1 h⁻¹) but not in populations growing sixfold faster. Four identified hfq alleles from parallel populations were beneficial at 0.1 h⁻¹ and deleterious at 0.6 h⁻¹. The hfq mutations were beneficial, deleterious or neutral at an intermediate growth rate (0.5 h⁻¹) and one changed from beneficial to deleterious within a 36 min difference in doubling time. The benefit of hfq mutations was due to the greater transport of limiting nutrient, which diminished at higher growth rates. The deleterious effects of hfq mutations at 0.6 h⁻¹ were less clear, with decreased viability a contributing factor. The results demonstrate distinct pleiotropy characteristics in the alleles of the same gene, probably because the altered residues in Hfq affected the regulation of expression of different genes in distinct ways. In addition, these results point to a source of variation in experimental measurement of the selective advantage of a mutation; estimates of fitness need to consider variation in growth rate impacting on the magnitude of the benefit of mutations and on their fitness distributions.     

Interplay between Chaperones and Protein Disorder Promotes the Evolution of Protein Networks

Evolution is driven by mutations, which lead to new protein functions but come at a cost to protein stability. Non-conservative substitutions are of interest in this regard because they may most profoundly affect both function and stability. Accordingly, organisms must balance the benefit of accepting advantageous substitutions with the possible cost of deleterious effects on protein folding and stability. We here examine factors that systematically promote non-conservative mutations at the proteome level. Intrinsically disordered regions in proteins play pivotal roles in protein interactions, but many questions regarding their evolution remain unanswered. Similarly, whether and how molecular chaperones, which have been shown to buffer destabilizing mutations in individual proteins, generally provide robustness during proteome evolution remains unclear. To this end, we introduce an evolutionary parameter λ that directly estimates the rate of non-conservative substitutions. Our analysis of λ in Escherichia coli, Saccharomyces cerevisiae, and Homo sapiens sequences reveals how co- and post-translationally acting chaperones differentially promote non-conservative substitutions in their substrates, likely through buffering of their destabilizing effects. We further find that λ serves well to quantify the evolution of intrinsically disordered proteins even though the unstructured, thus generally variable regions in proteins are often flanked by very conserved sequences. Crucially, we show that both intrinsically disordered proteins and highly re-wired proteins in protein interaction networks, which have evolved new interactions and functions, exhibit a higher λ at the expense of enhanced chaperone assistance. Our findings thus highlight an intricate interplay of molecular chaperones and protein disorder in the evolvability of protein networks. Our results illuminate the role of chaperones in enabling protein evolution, and underline the importance of the cellular context and integrated approaches for understanding proteome evolution. We feel that the development of λ may be a valuable addition to the toolbox applied to understand the molecular basis of evolution.     

The Escherichia coli Proteome: Past, Present, and Future Prospects

Proteomics has emerged as an indispensable methodology for large-scale protein analysis in functional genomics. The Escherichia coli proteome has been extensively studied and is well defined in terms of biochemical, biological, and biotechnological data. Even before the entire E. coli proteome was fully elucidated, the largest available data set had been integrated to decipher regulatory circuits and metabolic pathways, providing valuable insights into global cellular physiology and the development of metabolic and cellular engineering strategies. With the recent advent of advanced proteomic technologies, the E. coli proteome has been used for the validation of new technologies and methodologies such as sample prefractionation, protein enrichment, two-dimensional gel electrophoresis, protein detection, mass spectrometry (MS), combinatorial assays with n-dimensional chromatographies and MS, and image analysis software. These important technologies will not only provide a great amount of additional information on the E. coli proteome but also synergistically contribute to other proteomic studies. Here, we review the past development and current status of E. coli proteome research in terms of its biological, biotechnological, and methodological significance and suggest future prospects.     

Lytic phages obscure the cost of antibiotic resistance in Escherichia coli

The long-term persistence of antibiotic-resistant bacteria depends on their fitness relative to other genotypes in the absence of drugs. Outside the laboratory, viruses that parasitize bacteria (phages) are ubiquitous, but costs of antibiotic resistance are typically studied in phage-free experimental conditions. We used a mathematical model and experiments with Escherichia coli to show that lytic phages strongly affect the incidence of antibiotic resistance in drug-free conditions. Under phage parasitism, the likelihood that antibiotic-resistant genetic backgrounds spread depends on their initial frequency, mutation rate and intrinsic growth rate relative to drug-susceptible genotypes, because these parameters determine relative rates of phage-resistance evolution on different genetic backgrounds. Moreover, the average cost of antibiotic resistance in terms of intrinsic growth in the antibiotic-free experimental environment was small relative to the benefits of an increased mutation rate in the presence of phages. This is consistent with our theoretical work indicating that, under phage selection, typical costs of antibiotic resistance can be outweighed by realistic increases in mutability if drug resistance and hypermutability are genetically linked, as is frequently observed in clinical isolates. This suggests the long-term distribution of antibiotic resistance depends on the relative rates at which different lineages adapt to other types of selection, which in the case of phage parasitism is probably extremely common, as well as costs of resistance inferred by classical in vitro methods.     

The Interrelationship between Promoter Strength,Gene Expression,and Growth Rate

In exponentially growing bacteria, expression of heterologous protein impedes cellular growth rates. Quantitative understanding of the relationship between expression and growth rate will advance our ability to forward engineer bacteria, important for metabolic engineering and synthetic biology applications. Recently, a work described a scaling model based on optimal allocation of ribosomes for protein translation. This model quantitatively predicts a linear relationship between microbial growth rate and heterologous protein expression with no free parameters. With the aim of validating this model, we have rigorously quantified the fitness cost of gene expression by using a library of synthetic constitutive promoters to drive expression of two separate proteins (eGFP and amiE) in E. coli in different strains and growth media. In all cases, we demonstrate that the fitness cost is consistent with the previous findings. We expand upon the previous theory by introducing a simple promoter activity model to quantitatively predict how basal promoter strength relates to growth rate and protein expression. We then estimate the amount of protein expression needed to support high flux through a heterologous metabolic pathway and predict the sizable fitness cost associated with enzyme production. This work has broad implications across applied biological sciences because it allows for prediction of the interplay between promoter strength, protein expression, and the resulting cost to microbial growth rates.     

Evolutionary Consequence of a Trade-Off between Growth and Maintenance along with Ribosomal Damages

Microorganisms in nature are constantly subjected to a limited availability of resources and experience repeated starvation and nutrition. Therefore, microbial life may evolve for both growth fitness and sustainability. By contrast, experimental evolution, as a powerful approach to investigate microbial evolutionary strategies, often targets the increased growth fitness in controlled, steady-state conditions. Here, we address evolutionary changes balanced between growth and maintenance while taking nutritional fluctuations into account. We performed a 290-day-long evolution experiment with a histidine-requiring Escherichia coli strain that encountered repeated histidine-rich and histidine-starved conditions. The cells that experienced seven rounds of starvation and re-feed grew more sustainably under prolonged starvation but dramatically lost growth fitness under rich conditions. The improved sustainability arose from the evolved capability to use a trace amount of histidine for cell propagation. The reduced growth rate was attributed to mutations genetically disturbing the translation machinery, that is, the ribosome, ultimately slowing protein translation. This study provides the experimental demonstration of slow growth accompanied by an enhanced affinity to resources as an evolutionary adaptation to oscillated environments and verifies that it is possible to evolve for reduced growth fitness. Growth economics favored for population increase under extreme resource limitations is most likely a common survival strategy adopted by natural microbes.     

Costs of CRISPR-Cas-mediated resistance in Streptococcus thermophilus

CRISPR-Cas is a form of adaptive sequence-specific immunity in microbes. This system offers unique opportunities for the study of coevolution between bacteria and their viral pathogens, bacteriophages. A full understanding of the coevolutionary dynamics of CRISPR-Cas requires knowing the magnitude of the cost of resisting infection. Here, using the gram-positive bacterium Streptococcus thermophilus and its associated virulent phage 2972, a well-established model system harbouring at least two type II functional CRISPR-Cas systems, we obtained different fitness measures based on growth assays in isolation or in pairwise competition. We measured the fitness cost associated with different components of this adaptive immune system: the cost of Cas protein expression, the constitutive cost of increasing immune memory through additional spacers, and the conditional costs of immunity during phage exposure. We found that Cas protein expression is particularly costly, as Cas-deficient mutants achieved higher competitive abilities than the wild-type strain with functional Cas proteins. Increasing immune memory by acquiring up to four phage-derived spacers was not associated with fitness costs. In addition, the activation of the CRISPR-Cas system during phage exposure induces significant but small fitness costs. Together these results suggest that the costs of the CRISPR-Cas system arise mainly due to the maintenance of the defence system. We discuss the implications of these results for the evolution of CRISPR-Cas-mediated immunity.     

Metabolic Erosion Primarily Through Mutation Accumulation,and Not Tradeoffs,Drives Limited Evolution of Substrate Specificity in Escherichia coli

Evolutionary adaptation to a constant environment is often accompanied by specialization and a reduction of fitness in other environments. We assayed the ability of the Lenski Escherichia coli populations to grow on a range of carbon sources after 50,000 generations of adaptation on glucose. Using direct measurements of growth rates, we demonstrated that declines in performance were much less widespread than suggested by previous results from Biolog assays of cellular respiration. Surprisingly, there were many performance increases on a variety of substrates. In addition to the now famous example of citrate, we observed several other novel gains of function for organic acids that the ancestral strain only marginally utilized. Quantitative growth data also showed that strains with a higher mutation rate exhibited significantly more declines, suggesting that most metabolic erosion was driven by mutation accumulation and not by physiological tradeoffs. These reductions in growth by mutator strains were ameliorated by growth at lower temperature, consistent with the hypothesis that this metabolic erosion is largely caused by destabilizing mutations to the associated enzymes. We further hypothesized that reductions in growth rate would be greatest for substrates used most differently from glucose, and we used flux balance analysis to formulate this question quantitatively. To our surprise, we found no significant relationship between decreases in growth and dissimilarity to glucose metabolism. Taken as a whole, these data suggest that in a single resource environment, specialization does not mainly result as an inevitable consequence of adaptive tradeoffs, but rather due to the gradual accumulation of disabling mutations in unused portions of the genome.     

The cost of evolved constitutive lac gene expression is usually,but not always,maintained during evolution of generalist populations

Beneficial mutations can become costly following an environmental change. Compensatory mutations can relieve these costs, while not affecting the selected function, so that the benefits are retained if the environment shifts back to be similar to the one in which the beneficial mutation was originally selected. Compensatory mutations have been extensively studied in the context of antibiotic resistance, responses to specific genetic perturbations, and in the determination of interacting gene network components. Few studies have focused on the role of compensatory mutations during more general adaptation, especially as the result of selection in fluctuating environments where adaptations to different environment components may often involve trade‐offs. We examine whether costs of a mutation in lacI, which deregulated the expression of the lac operon in evolving populations of Escherichia coli bacteria, were compensated. This mutation occurred in multiple replicate populations selected in environments that fluctuated between growth on lactose, where the mutation was beneficial, and on glucose, where it was deleterious. We found that compensation for the cost of the lacI mutation was rare, but, when it did occur, it did not negatively affect the selected benefit. Compensation was not more likely to occur in a particular evolution environment. Compensation has the potential to remove pleiotropic costs of adaptation, but its rarity indicates that the circumstances to bring about the phenomenon may be peculiar to each individual or impeded by other selected mutations.     

Computation of condition-dependent proteome allocation reveals variability in the macro and micro nutrient requirements for growth

Sustaining a robust metabolic network requires a balanced and fully functioning proteome. In addition to amino acids, many enzymes require cofactors (coenzymes and engrafted prosthetic groups) to function properly. Extensively validated resource allocation models, such as genome-scale models of metabolism and gene expression (ME-models), have the ability to compute an optimal proteome composition underlying a metabolic phenotype, including the provision of all required cofactors. Here we apply the ME-model for Escherichia coli K-12 MG1655 to computationally examine how environmental conditions change the proteome and its accompanying cofactor usage. We found that: (1) The cofactor requirements computed by the ME-model mostly agree with the standard biomass objective function used in models of metabolism alone (M-models); (2) ME-model computations reveal non-intuitive variability in cofactor use under different growth conditions; (3) An analysis of ME-model predicted protein use in aerobic and anaerobic conditions suggests an enrichment in the use of peroxyl scavenging acids in the proteins used to sustain aerobic growth; (4) The ME-model could describe how limitation in key protein components affect the metabolic state of E. coli. Genome-scale models have thus reached a level of sophistication where they reveal intricate properties of functional proteomes and how they support different E. coli lifestyles.     

Evolution of Escherichia coli for Growth at High Temperatures

Evolution depends on the acquisition of genomic mutations that increase cellular fitness. Here, we evolved Escherichia coli MG1655 cells to grow at extreme temperatures. We obtained a maximum growth temperature of 48.5 °C, which was not increased further upon continuous cultivation at this temperature for >600 generations. Despite a permanently induced heat shock response in thermoresistant cells, only exquisitely high GroEL/GroES levels are essential for growth at 48.5 °C. They depend on the presence of lysyl-tRNA-synthetase, LysU, because deletion of lysU rendered thermoresistant cells thermosensitive. Our data suggest that GroEL/GroES are especially required for the folding of mutated proteins generated during evolution. GroEL/GroES therefore appear as mediators of evolution of extremely heat-resistant E. coli cells.     

Asymmetrical Damage Partitioning in Bacteria: A Model for the Evolution of Stochasticity,Determinism, and Genetic Assimilation

Non-genetic phenotypic variation is common in biological organisms. The variation is potentially beneficial if the environment is changing. If the benefit is large, selection can favor the evolution of genetic assimilation, the process by which the expression of a trait is transferred from environmental to genetic control. Genetic assimilation is an important evolutionary transition, but it is poorly understood because the fitness costs and benefits of variation are often unknown. Here we show that the partitioning of damage by a mother bacterium to its two daughters can evolve through genetic assimilation. Bacterial phenotypes are also highly variable. Because gene-regulating elements can have low copy numbers, the variation is attributed to stochastic sampling. Extant Escherichia coli partition asymmetrically and deterministically more damage to the old daughter, the one receiving the mother’s old pole. By modeling in silico damage partitioning in a population, we show that deterministic asymmetry is advantageous because it increases fitness variance and hence the efficiency of natural selection. However, we find that symmetrical but stochastic partitioning can be similarly beneficial. To examine why bacteria evolved deterministic asymmetry, we modeled the effect of damage anchored to the mother’s old pole. While anchored damage strengthens selection for asymmetry by creating additional fitness variance, it has the opposite effect on symmetry. The difference results because anchored damage reinforces the polarization of partitioning in asymmetric bacteria. In symmetric bacteria, it dilutes the polarization. Thus, stochasticity alone may have protected early bacteria from damage, but deterministic asymmetry has evolved to be equally important in extant bacteria. We estimate that 47% of damage partitioning is deterministic in E. coli. We suggest that the evolution of deterministic asymmetry from stochasticity offers an example of Waddington’s genetic assimilation. Our model is able to quantify the evolution of the assimilation because it characterizes the fitness consequences of variation.     

Evolutionary Tuning of Protein Expression Levels of a Positively Autoregulated Two-Component System

Cellular adaptation relies on the development of proper regulatory schemes for accurate control of gene expression levels in response to environmental cues. Over- or under-expression can lead to diminished cell fitness due to increased costs or insufficient benefits. Positive autoregulation is a common regulatory scheme that controls protein expression levels and gives rise to essential features in diverse signaling systems, yet its roles in cell fitness are less understood. It remains largely unknown how much protein expression is ‘appropriate’ for optimal cell fitness under specific extracellular conditions and how the dynamic environment shapes the regulatory scheme to reach appropriate expression levels. Here, we investigate the correlation of cell fitness and output response with protein expression levels of the E. coli PhoB/PhoR two-component system (TCS). In response to phosphate (Pi)-depletion, the PhoB/PhoR system activates genes involved in phosphorus assimilation as well as genes encoding themselves, similarly to many other positively autoregulated TCSs. We developed a bacteria competition assay in continuous cultures and discovered that different Pi conditions have conflicting requirements of protein expression levels for optimal cell fitness. Pi-replete conditions favored cells with low levels of PhoB/PhoR while Pi-deplete conditions selected for cells with high levels of PhoB/PhoR. These two levels matched PhoB/PhoR concentrations achieved via positive autoregulation in wild-type cells under Pi-replete and -deplete conditions, respectively. The fitness optimum correlates with the wild-type expression level, above which the phosphorylation output saturates, thus further increase in expression presumably provides no additional benefits. Laboratory evolution experiments further indicate that cells with non-ideal protein levels can evolve toward the optimal levels with diverse mutational strategies. Our results suggest that the natural protein expression levels and feedback regulatory schemes of TCSs are evolved to match the phosphorylation output of the system, which is determined by intrinsic activities of TCS proteins.     

The evolution of parental care in stochastic environments

Parental care is of fundamental importance to understanding reproductive strategies and allocation decisions. Here, we explore how parental care strategies evolve in variable environments. Using a set of life-history trait trade-offs, we explore the relative costs and benefits of parental care in stochastic environments. Specifically, we consider the cases in which environmental variability results in varying adult death rates, egg death rates, reproductive rate and carrying capacity. Using a measure of fitness appropriate for stochastic environments, we find that parental care has the potential to evolve over a wide range of life-history characteristics when the environment is variable. A variable environment that affects adult or egg death rates can either increase or decrease the fitness of care relative to that in a constant environment, depending on the specific costs of care. Variability that affects carrying capacity or adult reproductive rate has negligible effects on the fitness associated with care. Increasing parental care across different life-history stages can increase fitness gains in variable environments. Costly investment in care is expected to affect the overall fitness benefits, the fitness optimum and rate of evolution of parental care. In general, we find that environmental variability, the life-history traits affected by such variability and the specific costs of care interact to determine whether care will be favoured in a variable environment and what levels of care will be selected.