Fitness surfaces and local thermal adaptation in Drosophila along a latitudinal gradient.

Local adaptation is commonly cited to explain species distribution, but how fitness varies along continuous geographical gradients is not well understood. Here, we combine thermal biology and life-history theory to demonstrate that Drosophila populations along a 2500 km latitudinal cline are adapted to local conditions. We measured how heat tolerance and viability rate across eight populations varied with temperature in the laboratory and then simulated their expected cumulative Darwinian fitness employing high-resolution temperature data from their eight collection sites. Simulations indicate a trade-off between annual survival and cumulative viability, as both mortality and the recruitment of new flies are predicted to increase in warmer regions. Importantly, populations are locally adapted and exhibit the optimal combination of both traits to maximize fitness where they live. In conclusion, our method is able to reconstruct fitness surfaces employing empirical life-history estimates and reconstructs peaks representing locally adapted populations, allowing us to study geographic adaptation in silico.

High temperature delays and low temperature accelerates evolution of a new protein phenotype.

Since the origin of life, temperatures on earth have fluctuated both on short and long time scales. How such changes affect the rate at which Darwinian evolution can bring forth new phenotypes remains unclear. On the one hand, high temperature may accelerate phenotypic evolution because it accelerates most biological processes. On the other hand, it may slow phenotypic evolution, because proteins are usually less stable at high temperatures and therefore less evolvable. Here, to test these hypotheses experimentally, we evolved a green fluorescent protein in E. coli towards the new phenotype of yellow fluorescence at different temperatures. Yellow fluorescence evolved most slowly at high temperature and most rapidly at low temperature, in contradiction to the first hypothesis. Using high-throughput population sequencing, protein engineering, and biochemical assays, we determined that this is due to the protein-destabilizing effect of neofunctionalizing mutations. Destabilization is highly detrimental at high temperature, where neofunctionalizing mutations cannot be tolerated. Their detrimental effects can be mitigated through excess stability at low temperature, leading to accelerated adaptive evolution. By modifying protein folding stability, temperature alters the accessibility of mutational paths towards high-fitness genotypes. Our observations have broad implications for our understanding of how temperature changes affect evolutionary adaptations and innovations.

Compensatory evolution in NusG improves fitness of drug-resistant M. tuberculosis.

Drug-resistant bacteria are emerging as a global threat, despite frequently being less fit than their drug-susceptible ancestors1-8. Here we sought to define the mechanisms that drive or buffer the fitness cost of rifampicin resistance (RifR) in the bacterial pathogen Mycobacterium tuberculosis (Mtb). Rifampicin inhibits RNA polymerase (RNAP) and is a cornerstone of modern short-course tuberculosis therapy9,10. However, RifR Mtb accounts for one-quarter of all deaths due to drug-resistant bacteria11,12. We took a comparative functional genomics approach to define processes that are differentially vulnerable to CRISPR interference (CRISPRi) inhibition in RifR Mtb. Among other hits, we found that the universally conserved transcription factor NusG is crucial for the fitness of RifR Mtb. In contrast to its role in Escherichia coli, Mtb NusG has an essential RNAP pro-pausing function mediated by distinct contacts with RNAP and the DNA13. We find this pro-pausing NusG-RNAP interface to be under positive selection in clinical RifR Mtb isolates. Mutations in the NusG-RNAP interface reduce pro-pausing activity and increase fitness of RifR Mtb. Collectively, these results define excessive RNAP pausing as a molecular mechanism that drives the fitness cost of RifR in Mtb, identify a new mechanism of compensation to overcome this cost, suggest rational approaches to exacerbate the fitness cost, and, more broadly, could inform new therapeutic approaches to develop drug combinations to slow the evolution of RifR in Mtb.

A quantitative genetic model of background selection in humans.

Across the human genome, there are large-scale fluctuations in genetic diversity caused by the indirect effects of selection. This "linked selection signal" reflects the impact of selection according to the physical placement of functional regions and recombination rates along chromosomes. Previous work has shown that purifying selection acting against the steady influx of new deleterious mutations at functional portions of the genome shapes patterns of genomic variation. To date, statistical efforts to estimate purifying selection parameters from linked selection models have relied on classic Background Selection theory, which is only applicable when new mutations are so deleterious that they cannot fix in the population. Here, we develop a statistical method based on a quantitative genetics view of linked selection, that models how polygenic additive fitness variance distributed along the genome increases the rate of stochastic allele frequency change. By jointly predicting the equilibrium fitness variance and substitution rate due to both strong and weakly deleterious mutations, we estimate the distribution of fitness effects (DFE) and mutation rate across three geographically distinct human samples. While our model can accommodate weaker selection, we find evidence of strong selection operating similarly across all human samples. Although our quantitative genetic model of linked selection fits better than previous models, substitution rates of the most constrained sites disagree with observed divergence levels. We find that a model incorporating selective interference better predicts observed divergence in conserved regions, but overall our results suggest uncertainty remains about the processes generating fitness variation in humans.

Inbreeding effects on different lineages of Thrips tabaci (Thysanoptera: Thripidae).

Inbreeding can have detrimental effects on reproductive fitness, but the extent of lineage-specific variation in these effects remains poorly understood. This study investigated the effects of brother and sister inbreeding on reproductive fitness in 2 lineages (L1 and T) of T. tabaci. Inbred females from both lineages exhibited a significant reduction in longevity compared with the control group. The L1 lineage experienced a 27% and 43% decrease in longevity in the F2 and F3 generations, respectively, while the T lineage showed a similar trend with a 30% and 44% decrease. The T lineage consistently displayed slightly longer lifespans than the L1 lineage across all generations. Brother and sister inbreeding also led to a decrease in fecundity rates in both lineages. In the F3 generation, the number of eggs laid decreased by 59% compared with the F2 generation. The T lineage consistently exhibited slightly lower fecundity rates compared with the L1 lineage. Egg hatchability rates declined with subsequent inbreeding, with the F3 generation showing lower rates compared with the F2 generation. However, the T lineage did not exhibit a significant difference in inbreeding depression for egg hatchability rates, while the L1 lineage demonstrated a noticeable decrease. Deformities observed in male L1 lineage resulting from inbreeding were consistent with disruptions in normal developmental processes, affecting various body parts such as legs, antennae, and wings. Continued inbreeding increased susceptibility to inbreeding depression in terms of longevity, fecundity, and egg hatchability.

Genetic architecture of inbreeding depression may explain its persistence in a population of wild red deer.

Inbreeding depression is of major concern in declining populations, but relatively little is known about its genetic architecture in wild populations, such as the degree to which it is composed of large or small effect loci and their distribution throughout the genome. Here, we combine fitness and genomic data from a wild population of red deer to investigate the genomic distribution of inbreeding effects. Based on the runs of homozygosity (ROH)-based inbreeding coefficient, FROH, we use chromosome-specific inbreeding coefficients (FROHChr) to explore whether the effect of inbreeding varies between chromosomes. Under the assumption that within an individual the probability of being identical-by-descent is equal across all chromosomes, we used a multi-membership model to estimate the deviation of FROHChr from the average inbreeding effect. This novel approach ensures effect sizes are not overestimated whilst maximising the power of our available dataset of >3000 individuals genotyped on >35,000 autosomal SNPs. We find that most chromosomes confer a minor reduction in fitness-related traits, which when these effects are summed, results in the observed inbreeding depression in birth weight, survival and lifetime breeding success. However, no chromosomes had a significant detrimental effect compared to the overall effect of inbreeding, indicating no major effect loci. We conclude that in this population, inbreeding depression is likely the result of multiple mildly or moderately deleterious mutations spread across all chromosomes, which are difficult to detect with statistical confidence. Such mutations will be inefficiently purged, which may explain the persistence of inbreeding depression in this population.

Metabolic disruptions and impaired reproductive fitness in wild-caught freshwater turtles (Emydura macquarii macquarii) exposed to elevated per- and polyfluoroalkyl substances (PFAS).

Per- and poly-fluoroalkyl substances (PFAS) pose a threat to organisms and ecosystems due to their persistent nature. Ecotoxicology endpoints used in regulatory guidelines may not reflect multiple, low-level but persistent stressors. This study examines the biological effects of PFAS on Eastern short-necked turtles in Queensland, Australia. In this study, blood samples were collected and analysed for PFAS, hormone levels, and functional omics endpoints. High levels of PFAS were found in turtles at the impacted site, with PFOS being the dominant constituent. The PFAS profiles of males and females differed, with males having higher PFAS concentrations. Hormone concentrations differed between impacted and reference sites in male turtles, with elevated testosterone and corticosterone indicative of stress. Further, energy utilisation, nucleotide synthesis, nitrogen metabolism, and amino acid synthesis were altered in both male and female turtles from PFAS-impacted sites. Both sexes show similar metabolic responses to environmental stressors from the PFAS-contaminated site, which may adversely affect their reproductive fitness. Purine metabolism, caffeine metabolism, and ferroptosis pathway changes in turtles can cause gout, cell death, and overall health problems. Further, the study showed that prolonged exposure to elevated PFAS levels in the wild could compromise turtle reproductive fitness by disrupting reproductive steroids and metabolic pathways.

Dominance reversals: the resolution of genetic conflict and maintenance of genetic variation.

Beneficial reversals of dominance reduce the costs of genetic trade-offs and can enable selection to maintain genetic variation for fitness. Beneficial dominance reversals are characterized by the beneficial allele for a given context (e.g. habitat, developmental stage, trait or sex) being dominant in that context but recessive where deleterious. This context dependence at least partially mitigates the fitness consequence of heterozygotes carrying one non-beneficial allele for their context and can result in balancing selection that maintains alternative alleles. Dominance reversals are theoretically plausible and are supported by mounting empirical evidence. Here, we highlight the importance of beneficial dominance reversals as a mechanism for the mitigation of genetic conflict and review the theory and empirical evidence for them. We identify some areas in need of further research and development and outline three methods that could facilitate the identification of antagonistic genetic variation (dominance ordination, allele-specific expression and allele-specific ATAC-Seq (assay for transposase-accessible chromatin with sequencing)). There is ample scope for the development of new empirical methods as well as reanalysis of existing data through the lens of dominance reversals. A greater focus on this topic will expand our understanding of the mechanisms that resolve genetic conflict and whether they maintain genetic variation.

Disenfranchised DNA: biochemical analysis of mutant øX174 DNA-binding proteins may further elucidate the evolutionary significance of the unessential packaging protein A.

Most icosahedral DNA viruses package and condense their genomes into pre-formed, volumetrically constrained capsids. However, concurrent genome biosynthesis and packaging are specific to single-stranded (ss) DNA micro- and parvoviruses. Before packaging, ~120 copies of the øX174 DNA-binding protein J interact with double-stranded DNA. 60 J proteins enter the procapsid with the ssDNA genome, guiding it between 60 icosahedrally ordered DNA-binding pockets formed by the capsid proteins. Although J proteins are small, 28-37 residues in length, they have two domains. The basic, positively charged N-terminus guides the genome between binding pockets, whereas the C-terminus acts as an anchor to the capsid's inner surface. Three C-terminal aromatic residues, W30, Y31, and F37, interact most extensively with the coat protein. Their corresponding codons were mutated, and the resulting strains were biochemically and genetically characterized. Depending on the mutation, the substitutions produced unstable packaging complexes, unstable virions, infectious progeny, or particles packaged with smaller genomes, the latter being a novel phenomenon. The smaller genomes contained internal deletions. The juncture sequences suggest that the unessential A* (A star) protein mediates deletion formation.IMPORTANCEUnessential but strongly conserved gene products are understudied, especially when mutations do not confer discernable phenotypes or the protein's contribution to fitness is too small to reliably determine in laboratory-based assays. Consequently, their functions and evolutionary impact remain obscure. The data presented herein suggest that microvirus A* proteins, discovered over 40 years ago, may hasten the termination of non-productive packaging events. Thus, performing a salvage function by liberating the reusable components of the failed packaging complexes, such as DNA templates and replication enzymes.

Unraveling the dynamics of hepatitis C virus adaptive mutations and their impact on antiviral responses in primary human hepatocytes.

Hepatitis C virus (HCV) infection progresses to chronicity in the majority of infected individuals. Its high intra-host genetic variability enables HCV to evade the continuous selection pressure exerted by the host, contributing to persistent infection. Utilizing a cell culture-adapted HCV population (p100pop) which exhibits increased replicative capacity in various liver cell lines, this study investigated virus and host determinants that underlie enhanced viral fitness. Characterization of a panel of molecular p100 clones revealed that cell culture adaptive mutations optimize a range of virus-host interactions, resulting in expanded cell tropism, altered dependence on the cellular co-factor micro-RNA 122 and increased rates of virus spread. On the host side, comparative transcriptional profiling of hepatoma cells infected either with p100pop or its progenitor virus revealed that enhanced replicative fitness correlated with activation of endoplasmic reticulum stress signaling and the unfolded protein response. In contrast, infection of primary human hepatocytes with p100pop led to a mild attenuation of virion production which correlated with a greater induction of cell-intrinsic antiviral defense responses. In summary, long-term passage experiments in cells where selective pressure from innate immunity is lacking improves multiple virus-host interactions, enhancing HCV replicative fitness. However, this study further indicates that HCV has evolved to replicate at low levels in primary human hepatocytes to minimize innate immune activation, highlighting that an optimal balance between replicative fitness and innate immune induction is key to establish persistence. IMPORTANCE: Hepatitis C virus (HCV) infection remains a global health burden with 58 million people currently chronically infected. However, the detailed molecular mechanisms that underly persistence are incompletely defined. We utilized a long-term cell culture-adapted HCV, exhibiting enhanced replicative fitness in different human liver cell lines, in order to identify molecular principles by which HCV optimizes its replication fitness. Our experimental data revealed that cell culture adaptive mutations confer changes in the host response and usage of various host factors. The latter allows functional flexibility at different stages of the viral replication cycle. However, increased replicative fitness resulted in an increased activation of the innate immune system, which likely poses boundary for functional variation in authentic hepatocytes, explaining the observed attenuation of the adapted virus population in primary hepatocytes.

A synthetic differentiation circuit in Escherichia coli for suppressing mutant takeover.

Differentiation is crucial for multicellularity. However, it is inherently susceptible to mutant cells that fail to differentiate. These mutants outcompete normal cells by excessive self-renewal. It remains unclear what mechanisms can resist such mutant expansion. Here, we demonstrate a solution by engineering a synthetic differentiation circuit in Escherichia coli that selects against these mutants via a biphasic fitness strategy. The circuit provides tunable production of synthetic analogs of stem, progenitor, and differentiated cells. It resists mutations by coupling differentiation to the production of an essential enzyme, thereby disadvantaging non-differentiating mutants. The circuit selected for and maintained a positive differentiation rate in long-term evolution. Surprisingly, this rate remained constant across vast changes in growth conditions. We found that transit-amplifying cells (fast-growing progenitors) underlie this environmental robustness. Our results provide insight into the stability of differentiation and demonstrate a powerful method for engineering evolutionarily stable multicellular consortia.

Inference of annealed protein fitness landscapes with AnnealDCA.

The design of proteins with specific tasks is a major challenge in molecular biology with important diagnostic and therapeutic applications. High-throughput screening methods have been developed to systematically evaluate protein activity, but only a small fraction of possible protein variants can be tested using these techniques. Computational models that explore the sequence space in-silico to identify the fittest molecules for a given function are needed to overcome this limitation. In this article, we propose AnnealDCA, a machine-learning framework to learn the protein fitness landscape from sequencing data derived from a broad range of experiments that use selection and sequencing to quantify protein activity. We demonstrate the effectiveness of our method by applying it to antibody Rep-Seq data of immunized mice and screening experiments, assessing the quality of the fitness landscape reconstructions. Our method can be applied to several experimental cases where a population of protein variants undergoes various rounds of selection and sequencing, without relying on the computation of variants enrichment ratios, and thus can be used even in cases of disjoint sequence samples.

Measuring differential fitness costs and interactions between genetic cassettes using fluorescent spectrophotometry.

In this article, we present a method for designing, executing, and analyzing data from a microbial competition experiment. We use fluorescent reporters to label different competing strains and resolve individual growth curves using a fluorescent spectrophotometer. Our comprehensive data analysis pipeline integrates multiple experiments to simultaneously infer sources of variation, extract selection coefficients, and estimate the genetic contributions to fitness for various synthetic genetic cassettes (SGCs). To demonstrate the method, we employ a synthetic biological system based on Escherichia coli. Strains carry 1 of 10 different plasmids and one of three genomically integrated fluorescent markers. All strains are co-cultured to obtain real-time measurements of optical density (total population density) and fluorescence (sub-population densities). We identify challenges in calibrating between fluorescence and density and of fluorescent proteins maturing at different rates. To resolve these issues, we compare two methods of fluorescence calibration and correct for maturation by measuring in vivo maturation times. We provide evidence of genetic interactions occurring between our SGCs and further show how to use our statistical model to test some hypotheses about microbial growth and the costs of protein expression.IMPORTANCEFluorescently labeled co-cultures are becoming increasingly popular. The approach proposed here offers a high standard for experimental design and data analysis to measure selection coefficients and growth rates in competition. Measuring competitive differences is useful in many laboratory studies, allowing for fitness cost-correction of growth rates and ecological interactions and testing hypotheses in synthetic biology. Using time-resolved growth curves, rather than endpoint measurements, for competition assays allows us to construct a detailed scientific model that can be used to ask questions about fine-grained phenomena, such as bacterial growth dynamics, as well as higher-level phenomena, such as the interactions between synthetic cassette expression.

Mapping the functional form of the trade-off between infection resistance and reproductive fitness under dysregulated immune signaling.

Immune responses benefit organismal fitness by clearing parasites but also exact costs associated with immunopathology and energetic investment. Hosts manage these costs by tightly regulating the induction of immune signaling to curtail excessive responses and restore homeostasis. Despite the theoretical importance of turning off the immune response to mitigate these costs, experimentally connecting variation in the negative regulation of immune responses to organismal fitness remains a frontier in evolutionary immunology. In this study, we used a dose-response approach to manipulate the RNAi-mediated knockdown efficiency of cactus (IκBα), a central regulator of Toll pathway signal transduction in flour beetles (Tribolium castaneum). By titrating cactus activity across four distinct levels, we derived the shape of the relationship between immune response investment and traits associated with host fitness, including infection susceptibility, lifespan, fecundity, body mass, and gut homeostasis. Cactus knock-down increased the overall magnitude of inducible immune responses and delayed their resolution in a dsRNA dose-dependent manner, promoting survival and resistance following bacterial infection. However, these benefits were counterbalanced by dsRNA dose-dependent costs to lifespan, fecundity, body mass, and gut integrity. Our results allowed us to move beyond the qualitative identification of a trade-off between immune investment and fitness to actually derive its functional form. This approach paves the way to quantitatively compare the evolution and impact of distinct regulatory elements on life-history trade-offs and fitness, filling a crucial gap in our conceptual and theoretical models of immune signaling network evolution and the maintenance of natural variation in immune systems.

Changing fitness effects of mutations through long-term bacterial evolution.

The distribution of fitness effects of new mutations shapes evolution, but it is challenging to observe how it changes as organisms adapt. Using Escherichia coli lineages spanning 50,000 generations of evolution, we quantify the fitness effects of insertion mutations in every gene. Macroscopically, the fraction of deleterious mutations changed little over time whereas the beneficial tail declined sharply, approaching an exponential distribution. Microscopically, changes in individual gene essentiality and deleterious effects often occurred in parallel; altered essentiality is only partly explained by structural variation. The identity and effect sizes of beneficial mutations changed rapidly over time, but many targets of selection remained predictable because of the importance of loss-of-function mutations. Taken together, these results reveal the dynamic-but statistically predictable-nature of mutational fitness effects.

In vivo functional phenotypes from a computational epistatic model of evolution.

Computational models of evolution are valuable for understanding the dynamics of sequence variation, to infer phylogenetic relationships or potential evolutionary pathways and for biomedical and industrial applications. Despite these benefits, few have validated their propensities to generate outputs with in vivo functionality, which would enhance their value as accurate and interpretable evolutionary algorithms. We demonstrate the power of epistasis inferred from natural protein families to evolve sequence variants in an algorithm we developed called sequence evolution with epistatic contributions (SEEC). Utilizing the Hamiltonian of the joint probability of sequences in the family as fitness metric, we sampled and experimentally tested for in vivo [Formula: see text]-lactamase activity in Escherichia coli TEM-1 variants. These evolved proteins can have dozens of mutations dispersed across the structure while preserving sites essential for both catalysis and interactions. Remarkably, these variants retain family-like functionality while being more active than their wild-type predecessor. We found that depending on the inference method used to generate the epistatic constraints, different parameters simulate diverse selection strengths. Under weaker selection, local Hamiltonian fluctuations reliably predict relative changes to variant fitness, recapitulating neutral evolution. SEEC has the potential to explore the dynamics of neofunctionalization, characterize viral fitness landscapes, and facilitate vaccine development.

A large-effect fitness trade-off across environments is explained by a single mutation affecting cold acclimation.

Identifying the genetic basis of local adaptation and fitness trade-offs across environments is a central goal of evolutionary biology. Cold acclimation is an adaptive plastic response for surviving seasonal freezing, and costs of acclimation may be a general mechanism for fitness trade-offs across environments in temperate zone species. Starting with locally adapted ecotypes of Arabidopsis thaliana from Italy and Sweden, we examined the fitness consequences of a naturally occurring functional polymorphism in CBF2. This gene encodes a transcription factor that is a major regulator of cold-acclimated freezing tolerance and resides within a locus responsible for a genetic trade-off for long-term mean fitness. We estimated the consequences of alternate genotypes of CBF2 on 5-y mean fitness and fitness components at the native field sites by comparing near-isogenic lines with alternate genotypes of CBF2 to their genetic background ecotypes. The effects of CBF2 were validated at the nucleotide level using gene-edited lines in the native genetic backgrounds grown in simulated parental environments. The foreign CBF2 genotype in the local genetic background reduced long-term mean fitness in Sweden by more than 10%, primarily via effects on survival. In Italy, fitness was reduced by more than 20%, primarily via effects on fecundity. At both sites, the effects were temporally variable and much stronger in some years. The gene-edited lines confirmed that CBF2 encodes the causal variant underlying this genetic trade-off. Additionally, we demonstrated a substantial fitness cost of cold acclimation, which has broad implications for potential maladaptive responses to climate change.

Competition-driven eco-evolutionary feedback reshapes bacteriophage lambda's fitness landscape and enables speciation.

A major challenge in evolutionary biology is explaining how populations navigate rugged fitness landscapes without getting trapped on local optima. One idea illustrated by adaptive dynamics theory is that as populations adapt, their newly enhanced capacities to exploit resources alter fitness payoffs and restructure the landscape in ways that promote speciation by opening new adaptive pathways. While there have been indirect tests of this theory, to our knowledge none have measured how fitness landscapes deform during adaptation, or test whether these shifts promote diversification. Here, we achieve this by studying bacteriophage [Formula: see text], a virus that readily speciates into co-existing receptor specialists under controlled laboratory conditions. We use a high-throughput gene editing-phenotyping technology to measure [Formula: see text]'s fitness landscape in the presence of different evolved-[Formula: see text] competitors and find that the fitness effects of individual mutations, and their epistatic interactions, depend on the competitor. Using these empirical data, we simulate [Formula: see text]'s evolution on an unchanging landscape and one that recapitulates how the landscape deforms during evolution. [Formula: see text] heterogeneity only evolves in the shifting landscape regime. This study provides a test of adaptive dynamics, and, more broadly, shows how fitness landscapes dynamically change during adaptation, potentiating phenomena like speciation by opening new adaptive pathways.

Trypanosoma cruzi infection reduces the population fitness of Mepraia spinolai, a Chagas disease vector.

The hematophagous insect Mepraia spinolai (Hemiptera: Reduviidae: Triatominae) is naturally infected with the protozoan parasite Trypanosoma cruzi, the agent of Chagas disease in humans. In this study, we compared the demographic parameters of M. spinolai with and without T. cruzi infection. We collected the immature life table data of 479 M. spinolai individuals of control cohort (reared on mice without T. cruzi infection) and 563 M. spinolai individuals of treatment cohort (reared on mice with T. cruzi infection). Nymphs were maintained in individual compartments inside a growth chamber (26°C; 65-75%) until adult emergence; moulting and survival were recorded daily. For the adult life table study of the control, we used 24 pairs of adults from the control cohort. For the adult life table study of T. cruzi-infected cohort, 25 infected females were paired with 25 males from the control cohort. Life table data were analysed using bootstrap-match technique based on the age-stage, two-sex life table. The preadult survival rate (0.5282) of the control cohort was significantly higher than that of the infected cohort (0.2913). However, the mean fecundity of reproductive females (Fr = 22.29 eggs/♀) and net reproductive rate of population (R0 = 5.07 offspring/individual) of the 0.5th percentile bootstrap-match control cohort were not significantly different from those of the infected cohort (Fr = 23.35 eggs/♀, R0 = 3.77 offspring/individual). Due to the shorter total preoviposition period and higher proportion of reproductive female, the intrinsic rate of increase (r = 0.0053 d-1 ) and finite rate of increase (λ = 1.0053 d-1 ) of control cohort of M. spinolai were significantly higher than those of the T. cruzi-infected cohort (r = 0.0035 d-1 , λ = 1.0035 d-1 ). These results suggest that T. cruzi infection reduces the population fitness of the Chagas disease vector M. spinolai.