Adaptation to the deleterious effects of antimicrobial drug resistance mutations by compensatory evolution

Prediction of contact residue pairs based on co-substitution between sites in protein structures

Residue-residue interactions that fold a protein into a unique three-dimensional structure and make it play a specific function impose structural and functional constraints in varying degrees on each residue site. Selective constraints on residue sites are recorded in amino acid orders in homologous sequences and also in the evolutionary trace of amino acid substitutions. A challenge is to extract direct dependences between residue sites by removing phylogenetic correlations and indirect dependences through other residues within a protein or even through other molecules. Rapid growth of protein families with unknown folds requires an accurate de novo prediction method for protein structure. Recent attempts of disentangling direct from indirect dependences of amino acid types between residue positions in multiple sequence alignments have revealed that inferred residue-residue proximities can be sufficient information to predict a protein fold without the use of known three-dimensional structures. Here, we propose an alternative method of inferring coevolving site pairs from concurrent and compensatory substitutions between sites in each branch of a phylogenetic tree. Substitution probability and physico-chemical changes (volume, charge, hydrogen-bonding capability, and others) accompanied by substitutions at each site in each branch of a phylogenetic tree are estimated with the likelihood of each substitution, and their direct correlations between sites are used to detect concurrent and compensatory substitutions. In order to extract direct dependences between sites, partial correlation coefficients of the characteristic changes along branches between sites, in which linear multiple dependences on feature vectors at other sites are removed, are calculated and used to rank coevolving site pairs. Accuracy of contact prediction based on the present coevolution score is comparable to that achieved by a maximum entropy model of protein sequences for 15 protein families taken from the Pfam release 26.0. Besides, this excellent accuracy indicates that compensatory substitutions are significant in protein evolution.

MDR1-associated resistance to artesunate+mefloquine does not impair blood-stage parasite fitness in a rodent malaria model

If drug-resistant malaria mutants are less fit than sensitive forms, they will wane over time when active drug pressure is removed and the overall sensitivity to the drug may be restored. However, most studies addressing this issue have been largely retrospective. Here, we undertook a predictive study, using mutant rodent malaria parasites resistant to the Artemisinin combination treatment (ACT) version of artesunate+mefloquine (ATN+MF) to gain insights about their ability to compete with ATN+MF-sensitive forms in untreated hosts. Previously, Plasmodium chabaudi parasites resistant to ATN+MF were selected in vivo through prolonged passaging in mice under increasing doses of the two drugs, and shown to harbour duplication of the mdr1 gene. Here, the resistant parasite, AS-ATNMF1, was mixed with its progenitor AS-ATN in different proportions and each mixture was injected into mice that were left untreated. Absolute percentage parasitaemias and the proportion of each parasite were then monitored by microscopy and proportional sequencing, respectively, every two days for a period of 14days. AS-ATNMF1 outperformed its progenitor AS-ATN over the whole sampling period regardless of the relative starting proportion of each parasite clone. In order to assess if consecutive sub-inoculations could have been responsible for the apparent fitness gain of the resistant parasite, its growth was compared to that of AS-ATN27P, a parasite which was passaged the same number of times as AS-ATNMF1, but left untreated. Although small fluctuations in the proportion of each parasite were observed through time, the relative abundance of each on the last day of sampling (Day 14) was virtually identical to that of the starting inoculum. We conclude that there is no fitness cost associated with MDR1-associated ATN+MF resistance in vivo. These observations offer the first insights about the within-host dynamics between ACT-resistant and -sensitive parasites in absence of drug pressure.

First steps in experimental cancer evolution

Evolutionary processes play a central role in the development, progression and response to treatment of cancers. The current challenge facing researchers is to harness evolutionary theory to further our understanding of the clinical progression of cancers. Central to this endeavour will be the development of experimental systems and approaches by which theories of cancer evolution can be effectively tested. We argue here that the experimental evolution approach - whereby evolution is observed in real time and which has typically employed microorganisms - can be usefully applied to cancer. This approach allows us to disentangle the ecological causes of natural selection, identify the genetic basis of evolutionary changes and determine their repeatability. Cell cultures used in cancer research share many of the desirable traits that make microorganisms ideal for studying evolution. As such, experimental cancer evolution is feasible and likely to give great insight into the selective pressures driving the evolution of clinically destructive cancer traits. We highlight three areas of evolutionary theory with importance to cancer biology that are amenable to experimental evolution: drug resistance, social evolution and resource competition. Understanding the diversity, persistence and evolution of cancers is vital for treatment and drug development, and an experimental evolution approach could provide strategic directions and focus for future research.

The heterogeneous evolution of multidrug-resistant Mycobacterium tuberculosis

Recent surveillance data of multidrug-resistant tuberculosis (MDR-TB) reported the highest rates of resistance ever documented. As further amplification of resistance in MDR strains of Mycobacterium tuberculosis occurs, extensively drug-resistant (XDR) and totally drug-resistant (TDR) TB are beginning to emerge. Although for the most part, the epidemiological factors involved in the spread of MDR-TB are understood, insights into the bacterial drivers of MDR-TB have been gained only recently, largely owing to novel technologies and research in other organisms. Herein, we review recent findings on how bacterial factors, such as persistence, hypermutation, the complex interrelation between drug resistance and fitness, compensatory evolution, and epistasis affect the evolution of multidrug resistance in M. tuberculosis. Improved knowledge of these factors will help better predict the future trajectory of MDR-TB, and contribute to the development of new tools and strategies to combat this growing public health threat.

A time-to-event pharmacodynamic model describing treatment response in patients with pulmonary tuberculosis using days to positivity in automated liquid mycobacterial culture

Days to positivity in automated liquid mycobacterial culture have been shown to correlate with mycobacterial load and have been proposed as a useful biomarker for treatment responses in tuberculosis. However, there is currently no quantitative method or model to analyze the change in days to positivity with time on treatment. The objectives of this study were to describe the decline in numbers of mycobacteria in sputum collected once weekly for 8 weeks from patients on treatment for tuberculosis using days to positivity in liquid culture. One hundred forty-four patients with smear-positive pulmonary tuberculosis were recruited from a tuberculosis clinic in Cape Town, South Africa. A nonlinear mixed-effects repeated-time-to-event modeling approach was used to analyze the time-to-positivity data. A biexponential model described the decline in the estimated number of bacteria in patients' sputum samples, while a logistic model with a lag time described the growth of the bacteria in liquid culture. At baseline, the estimated number of rapidly killed bacteria is typically 41 times higher than that of those that are killed slowly. The time to kill half of the rapidly killed bacteria was about 1.8 days, while it was 39 days for slowly killed bacteria. Patients with lung cavitation had higher bacterial loads than patients without lung cavitation. The model successfully described the increase in days to positivity as treatment progressed, differentiating between bacteria that are killed rapidly and those that are killed slowly. Our model can be used to analyze similar data from studies testing new drug regimens.

Dynamic population changes in Mycobacterium tuberculosis during acquisition and fixation of drug resistance in patients

BACKGROUND

Drug-resistant tuberculosis poses a growing challenge to global public health. However, the diversity and dynamics of the bacterial population during acquisition of drug resistance have yet to be carefully examined.

METHODS

Whole-genome sequencing was performed on 7 serial Mycobacterium tuberculosis (M. tuberculosis) populations from 3 patients during different stages in the development of drug resistance. The population diversity was assessed by the number and frequencies of unfixed mutations in each sample.

RESULTS

For each bacterial population, 8-41 unfixed mutations were monitored by the fraction of single-nucleotide polymorphisms at specific loci. Among them, as many as 4 to 5 resistance-conferring mutations were transiently detected in the same single sputum, but ultimately only a single type of mutant was fixed. In addition, we identified 14 potential compensatory mutations that occurred during or after the emergence of resistance-conferring mutations.

CONCLUSIONS

M. tuberculosis population within patients exhibited considerable genetic diversity, which underwent selections for most fit resistant mutant. These findings have important implications and emphasize the need for early diagnosis of tuberculosis to decrease the chance of evolving highly fit drug-resistant strains.

Cancer in light of experimental evolution

Cancer initiation, progression, and the emergence of therapeutic resistance are evolutionary phenomena of clonal somatic cell populations. Studies in microbial experimental evolution and the theoretical work inspired by such studies are yielding deep insights into the evolutionary dynamics of clonal populations, yet there has been little explicit consideration of the relevance of this rapidly growing field to cancer biology. Here, we examine how the understanding of mutation, selection, and spatial structure in clonal populations that is emerging from experimental evolution may be applicable to cancer. Along the way, we discuss some significant ways in which cancer differs from the model systems used in experimental evolution. Despite these differences, we argue that enhanced prediction and control of cancer may be possible using ideas developed in the context of experimental evolution, and we point out some prospects for future research at the interface between these traditionally separate areas.

Drug-resistant microorganisms with a higher fitness--can medicines boost pathogens?

Drug-resistant microorganisms (DRMs) are generally thought to suffer from a fitness cost associated with their drug-resistant trait, inflicting them a disadvantage when the drug pressure reduces. However, Leishmania resistant to pentavalent antimonies shows traits of a higher fitness compared to its sensitive counterparts. This is likely due the combination of an intracellular pathogen and a drug that targets the parasite's general defense mechanisms while at the same time stimulating the host's immune system, resulting in a DRM that is better adapted to withstand the host's immune response. This review aims to highlight how this fitter DRM has emerged and how it might affect the control of leishmaniasis. However, this unprecedented example of fitter antimony-resistant Leishmania donovani is also of significance for the control of other microorganisms, warranting more caution when applying or designing drugs that attack their general defense mechanisms or interact with the host's immune system.

The stepwise acquisition of fluconazole resistance mutations causes a gradual loss of fitness in Candida albicans

The pathogenic yeast Candida albicans can develop resistance to the widely used antifungal agent fluconazole, which inhibits ergosterol biosynthesis. Resistance is often caused by gain-of-function mutations in the transcription factors Mrr1, Tac1 and Upc2, which result in constitutive overexpression of multidrug efflux pumps and ergosterol biosynthesis genes respectively. It is not known how the permanently changed gene expression program in resistant strains affects their fitness in the absence of drug selection pressure. We have systematically investigated the effects of activating mutations in Mrr1, Tac1 and Upc2, individually and in all possible combinations, on the degree of fluconazole resistance and on the fitness of C. albicans in an isogenic strain background. All combinations of different resistance mechanisms resulted in a stepwise increase in drug resistance, culminating in 500-fold increased fluconazole resistance in strains possessing mutations in the three transcription factors and an additional resistance mutation in the drug target enzyme Erg11. The acquisition of resistance mutations was associated with reduced fitness under non-selective conditions in vitro as well as in vivo during colonization of a mammalian host. Therefore, without compensatory mutations, the inability to appropriately regulate gene expression results in a loss of competitive fitness of drug-resistant C. albicans strains.

A model of developmental evolution: selection, pleiotropy and compensation

Development and physiology translate genetic variation into phenotypic variation and determine the genotype-phenotype map, such as which gene affects which character (pleiotropy). Any genetic change in this mapping reflects a change in development. Here, we discuss evidence for variation in pleiotropy and propose the selection, pleiotropy and compensation model (SPC) for adaptive evolution. It predicts that adaptive change in one character is associated with deleterious pleiotropy in others and subsequent selection to compensate for these pleiotropic effects. The SPC model provides a unifying perspective for a variety of puzzling phenomena, including developmental systems drift and character homogenization. The model suggests that most adaptive signatures detected in genome scans could be the result of compensatory changes, rather than of progressive character adaptations.

"One-size-fits-all"? Optimizing treatment duration for bacterial infections

Historically, antibiotic treatment guidelines have aimed to maximize treatment efficacy and minimize toxicity, but have not considered the evolution of antibiotic resistance. Optimizing the duration and dosing of treatment to minimize the duration of symptomatic infection and selection pressure for resistance simultaneously has the potential to extend the useful therapeutic life of these valuable life-saving drugs without compromising the interests of individual patients.Here, using mathematical models, we explore the theoretical basis for shorter durations of treatment courses, including a range of ecological dynamics of bacteria that cause infections or colonize hosts as commensals. We find that immunity is an important mediating factor in determining the need for long duration of treatment. When immunity to infection is expected, shorter durations that reduce the selection for resistance without interfering with successful clinical outcome are likely to be supported. Adjusting drug treatment strategies to account for the impact of the differences in the ecological niche occupied by commensal flora relative to invasive bacteria could be effective in delaying the spread of bacterial resistance.

The evolutionary epidemiology of multilocus drug resistance

The evolution of resistance to drugs is a major public health concern as it erodes the efficacy of our therapeutic arsenal against bacterial, viral, and fungal pathogens. Increasingly, it is recognized that the evolution of resistance involves genetic changes at more than one locus, both in cases where multiple changes are required to obtain high-level resistance, and where compensatory changes at secondary loci ameliorate the costs of resistance. Similarly, multiple loci are often involved in the evolution of multidrug resistance. There has been widespread interest recently in understanding the evolutionary consequences of multilocus resistance, with many empirical studies documenting extensive patterns of genetic interactions (i.e., epistasis) among the loci involved. Currently, however, there are few general theoretical results available that bridge the gap between classical multilocus population genetics and mathematical epidemiology. Here, such theory is developed to shed new light on these previous studies, and to provide further guidance on the type of data required to predict the evolution of pathogens in response to drug pressure. Our results reveal the importance of feedbacks between the epidemiological and evolutionary dynamics, and illustrate how these feedbacks can be exploited to control resistance. In particular, we show how interventions such as social distancing and isolation can influence rates of recombination, and how this then can slow the spread of multilocus resistance and increase the likelihood of reversion to drug sensitivity once drug therapy has ceased.

Molecular characterization of HIV-1 CRF01_AE in Mekong Delta, Vietnam, and impact of T-cell epitope mutations on HLA recognition (ANRS 12159)

Background

To date, 11 HIV-1 subtypes and 48 circulating recombinant forms have been described worldwide. The underlying reason why their distribution is so heterogeneous is not clear. Host genetic factors could partly explain this distribution. The aim of this study was to describe HIV-1 strains circulating in an unexplored area of Mekong Delta, Vietnam, and to assess the impact of optimal epitope mutations on HLA binding.

Methods

We recruited 125 chronically antiretroviral-naive HIV-1-infected subjects from five cities in the Mekong Delta. We performed high-resolution DNA typing of HLA class I alleles, sequencing of Gag and RT-Prot genes and phylogenetic analysis of the strains. Epitope mutations were analyzed in patients bearing the HLA allele restricting the studied epitope. Optimal wild-type epitopes from the Los Alamos database were used as reference. T-cell epitope recognition was predicted using the immune epitope database tool according to three different scores involved in antigen processing (TAP and proteasome scores) and HLA binding (MHC score).

Results

All sequences clustered with CRF01_AE. HLA class I genotyping showed the predominance of Asian alleles as A*11:01 and B*46:01 with a Vietnamese specificity held by two different haplotypes. The percentage of homology between Mekong and B consensus HIV-1 sequences was above 85%. Divergent epitopes had TAP and proteasome scores comparable with wild-type epitopes. MHC scores were significantly lower in divergent epitopes with a mean of 2.4 (±0.9) versus 2 (±0.7) in non-divergent ones (p<0.0001).

Conclusions

Our study confirms the wide predominance of CRF01_AE in the Mekong Delta where patients harbor a specific HLA pattern. Moreover, it demonstrates the lower MHC binding affinity among divergent epitopes. This weak immune pressure combined with a narrow genetic diversity favors immune escape and could explain why CRF01_AE is still predominant in Vietnam, particularly in the Mekong area.

Evolutionary dynamics of Candida albicans during in vitro evolution

While mechanisms of resistance to major antifungal agents have been characterized in Candida albicans, little is known about the evolutionary trajectories during the emergence of drug resistance. Here, we examined the evolutionary dynamics of C. albicans that evolved in vitro in the presence or absence of fluconazole using the visualizing evolution in real-time (VERT) method, a novel experimental approach that facilitates the systematic isolation of adaptive mutants that arise in the population. We found an increase in the frequency of adaptive events in the presence of fluconazole compared to the no-drug controls. Analysis of the evolutionary dynamics revealed that mutations that led to increased drug resistance appeared frequently and that mutants with increased levels of resistance arose in independent lineages. Interestingly, most adaptive mutants with increased fitness in the presence of the drug did not exhibit a significant fitness decrease in the absence of the drug, supporting the idea that rapid resistance can arise from mutations in strains maintained in the population prior to exposure to the drug.

Microbial laboratory evolution in the era of genome-scale science

Advances in DNA sequencing, high-throughput technologies, and genetic manipulation systems have enabled empirical studies of the molecular and genomic bases of adaptive evolution. This review discusses key insights learned from direct observation of the evolution process.

Laboratory evolution studies provide fundamental biological insight through direct observation of the evolution process. They not only enable testing of evolutionary theory and principles, but also have applications to metabolic engineering and human health. Genome-scale tools are revolutionizing studies of laboratory evolution by providing complete determination of the genetic basis of adaptation and the changes in the organism's gene expression state. Here, we review studies centered on four central themes of laboratory evolution studies: (1) the genetic basis of adaptation; (2) the importance of mutations to genes that encode regulatory hubs; (3) the view of adaptive evolution as an optimization process; and (4) the dynamics with which laboratory populations evolve.

A unified approach to the estimation and interpretation of resistance costs in plants

Plants exhibit a number of adaptive defence traits that endow resistance to past and current abiotic and biotic stresses. It is generally accepted that these adaptations will incur a cost when plants are not challenged by the stress to which they have become adapted--the so-called 'cost of adaptation'. The need to minimise or account for allelic variation at other fitness-related loci (genetic background control) is frequently overlooked when assessing resistance costs associated with plant defence traits. We provide a synthesis of the various experimental protocols that accomplish this essential requirement. We also differentiate those methods that enable the identification of the trait-specific or mechanistic basis of costs (direct methods) from those that provide an estimate of the impact of costs by examining the evolutionary trajectories of resistance allele frequencies at the population level (indirect methods). The advantages and disadvantages for each proposed experimental design are discussed. We conclude that plant resistance systems provide an ideal model to address fundamental questions about the cost of adaptation to stress. We also propose some ways to expand the scope of future studies for further fundamental and applied insight into the significance of adaptation costs.

Compensatory evolution of pbp mutations restores the fitness cost imposed by β-lactam resistance in Streptococcus pneumoniae

The prevalence of antibiotic resistance genes in pathogenic bacteria is a major challenge to treating many infectious diseases. The spread of these genes is driven by the strong selection imposed by the use of antibacterial drugs. However, in the absence of drug selection, antibiotic resistance genes impose a fitness cost, which can be ameliorated by compensatory mutations. In Streptococcus pneumoniae, β-lactam resistance is caused by mutations in three penicillin-binding proteins, PBP1a, PBP2x, and PBP2b, all of which are implicated in cell wall synthesis and the cell division cycle. We found that the fitness cost and cell division defects conferred by pbp2b mutations (as determined by fitness competitive assays in vitro and in vivo and fluorescence microscopy) were fully compensated by the acquisition of pbp2x and pbp1a mutations, apparently by means of an increased stability and a consequent mislocalization of these protein mutants. Thus, these compensatory combinations of pbp mutant alleles resulted in an increase in the level and spectrum of β-lactam resistance. This report describes a direct correlation between antibiotic resistance increase and fitness cost compensation, both caused by the same gene mutations acquired by horizontal transfer. The clinical origin of the pbp mutations suggests that this intergenic compensatory process is involved in the persistence of β-lactam resistance among circulating strains. We propose that this compensatory mechanism is relevant for β-lactam resistance evolution in Streptococcus pneumoniae.

The fitness cost of rifampicin resistance in Pseudomonas aeruginosa depends on demand for RNA polymerase

Bacterial resistance to antibiotics usually incurs a fitness cost in the absence of selecting drugs, and this cost of resistance plays a key role in the spread of antibiotic resistance in pathogen populations. Costs of resistance have been shown to vary with environmental conditions, but the causes of this variability remain obscure. In this article, we show that the average cost of rifampicin resistance in the pathogenic bacterium Pseudomonas aeruginosa is reduced by the addition of ribosome inhibitors (chloramphenicol or streptomycin) that indirectly constrain transcription rate and therefore reduce demand for RNA polymerase activity. This effect is consistent with predictions from metabolic control theory. We also tested the alternative hypothesis that the observed trend was due to a general effect of environmental quality on the cost of resistance. To do this we measured the fitness of resistant mutants in the presence of other antibiotics (ciprofloxacin and carbenicillin) that have similar effects on bacterial growth rate but bind to different target enzymes (DNA gyrase and penicillin-binding proteins, respectively) and in 41 single-carbon source environments of varying quality. We find no consistent effect of environmental quality on the average cost of resistance in these treatments. These results show that the cost of rifampicin resistance varies with demand for the mutated target enzyme, rather than as a simple function of bacterial growth rate or stress.

Predicting chemical impacts on vertebrate endocrine systems

Animals have evolved diverse protective mechanisms for responding to toxic chemicals of both natural and anthropogenic origin. From a governmental regulatory perspective, these protective responses complicate efforts to establish acceptable levels of chemical exposure. To explore this issue, we considered vertebrate endocrine systems as potential targets for environmental contaminants. Using the hypothalamic-pituitary-thyroid (HPT), hypothalamic-pituitary-gonad (HPG), and hypothalamic-pituitary-adrenal (HPA) axes as case examples, we identified features of these systems that allow them to accommodate and recover from chemical insults. In doing so, a distinction was made between effects on adults and those on developing organisms. This distinction was required because endocrine system disruption in early life stages may alter development of organs and organ systems, resulting in permanent changes in phenotypic expression later in life. Risk assessments of chemicals that impact highly regulated systems must consider the dynamics of these systems in relation to complex environmental exposures. A largely unanswered question is whether successful accommodation to a toxic insult exerts a fitness cost on individual animals, resulting in adverse consequences for populations. Mechanistically based mathematical models of endocrine systems provide a means for better understanding accommodation and recovery. In the short term, these models can be used to design experiments and interpret study findings. Over the long term, a set of validated models could be used to extrapolate limited in vitro and in vivo testing data to a broader range of untested chemicals, species, and exposure scenarios. With appropriate modification, Tier 2 assays developed in support of the U.S. Environmental Protection Agency's Endocrine Disruptor Screening Program could be used to assess the potential for accommodation and recovery and inform the development of mechanistically based models.

Compensatory mutations restore fitness during the evolution of dihydrofolate reductase

Whether a trade-off exists between robustness and evolvability is an important issue for protein evolution. Although traditional viewpoints have assumed that existing functions must be compromised by the evolution of novel activities, recent research has suggested that existing phenotypes can be robust to the evolution of novel protein functions. Enzymes that are targets of antibiotics that are competitive inhibitors must evolve decreased drug affinity while maintaining their function and sustaining growth. Utilizing a transgenic Saccharomyces cerevisiae model expressing the dihydrofolate reductase (DHFR) enzyme from the malarial parasite Plasmodium falciparum, we examine the robustness of growth rate to drug-resistance mutations. We assay the growth rate and resistance of all 48 combinations of 6 DHFR point mutations associated with increased drug resistance in field isolates of the parasite. We observe no consistent relationship between growth rate and resistance phenotypes among the DHFR alleles. The three evolutionary pathways that dominate DHFR evolution show that mutations with increased resistance can compensate for initial declines in growth rate from previously acquired mutations. In other words, resistance mutations that occur later in evolutionary trajectories can compensate for the fitness consequences of earlier mutations. Our results suggest that high levels of resistance may be selected for without necessarily jeopardizing overall fitness.

Hypermutability and compensatory adaptation in antibiotic-resistant bacteria

Hypermutable (mutator) bacteria have been associated with the emergence of antibiotic resistance. A simple yet untested prediction is that mutator bacteria are able to compensate more quickly for pleiotropic fitness costs often associated with resistance, resulting in the maintenance of resistance in the absence of antibiotic selection. By using experimental populations of a wild-type and a mutator genotype of the pathogenic bacterium Pseudomonas aeruginosa, we show that mutator bacteria can evolve resistance to antibiotics more rapidly than wild-type bacteria and, crucially, that mutators are better able to compensate for the fitness cost of resistance, to the extent that all costs of resistance were entirely compensated for in mutators. When competed against immigrant antibiotic-susceptible bacteria in the absence of antibiotics, antibiotic resistance remained at a high level in mutator populations but disappeared in wild-type populations. These results suggest that selection for mutations that offset the fitness cost associated with antibiotic resistance may help to explain the high frequency of mutator bacteria and antibiotic resistance observed in chronic infections.

The population genetics of antibiotic resistance: integrating molecular mechanisms and treatment contexts

Despite efforts from a range of disciplines, our ability to predict and combat the evolution of antibiotic resistance in pathogenic bacteria is limited. This is because resistance evolution involves a complex interplay between the specific drug, bacterial genetics and both natural and treatment ecology. Incorporating details of the molecular mechanisms of drug resistance and ecology into evolutionary models has proved useful in predicting the dynamics of resistance evolution. However, putting these models to practical use will require extensive collaboration between mathematicians, molecular biologists, evolutionary ecologists and clinicians.

Rate and effects of spontaneous mutations that affect fitness in mutator Escherichia coli

Knowledge of the mutational parameters that affect the evolution of organisms is of key importance in understanding the evolution of several characteristics of many natural populations, including recombination and mutation rates. In this study, we estimated the rate and mean effect of spontaneous mutations that affect fitness in a mutator strain of Escherichia coli and review some of the estimation methods associated with mutation accumulation (MA) experiments. We performed an MA experiment where we followed the evolution of 50 independent mutator lines that were subjected to repeated bottlenecks of a single individual for approximately 1150 generations. From the decline in mean fitness and the increase in variance between lines, we estimated a minimum mutation rate to deleterious mutations of 0.005 (+/-0.001 with 95% confidence) and a maximum mean fitness effect per deleterious mutation of 0.03 (+/-0.01 with 95% confidence). We also show that any beneficial mutations that occur during the MA experiment have a small effect on the estimate of the rate and effect of deleterious mutations, unless their rate is extremely large. Extrapolating our results to the wild-type mutation rate, we find that our estimate of the mutational effects is slightly larger and the inferred deleterious mutation rate slightly lower than previous estimates obtained for non-mutator E. coli.

Compensation of fitness costs and reversibility of antibiotic resistance mutations

Strains of bacterial pathogens that have acquired mutations conferring antibiotic resistance often have a lower growth rate and are less invasive or transmissible initially than their susceptible counterparts. However, fitness costs of resistance mutations can be ameliorated by secondary site mutations. These so-called compensatory mutations may restore fitness in the absence and/or presence of antimicrobials. We review literature data and show that the fitness gains in the absence and presence of antibiotic treatment need not be correlated. The aim of this study is to gain a better conceptual grasp of how compensatory mutations with different fitness gains affect evolutionary trajectories, in particular reversibility. To this end, we developed a theoretical model with which we consider both a resistance and a compensation locus. We propose an intuitively understandable parameterization for the fitness values of the four resulting genotypes (wild type, resistance mutation only, compensatory mutation only, and both mutations) in the absence and presence of treatment. The differential fitness gains, together with the turnover rate and the mutation rate, strongly affected the success of antibacterial treatment, reversibility, and long-term abundance of resistant strains. We therefore propose that experimental studies of compensatory mutations should include fitness measurements of all possible genotypes in both the absence and presence of an antibiotic.

Fitness epistasis and constraints on adaptation in a human immunodeficiency virus type 1 protein region

Fitness epistasis, the interaction among alleles at different loci in their effects on fitness, has potentially important consequences for adaptive evolution. We investigated fitness epistasis among amino acids of a functionally important region of the human immunodeficiency virus type 1 (HIV-1) exterior envelope glycoprotein (gp120). Seven mutations putatively involved in the adaptation of the second conserved to third variable protein region (C2-V3) to the use of an alternative host-cell chemokine coreceptor (CXCR4) for cell entry were engineered singly and in combinations on the wild-type genetic background and their effects on viral infectivity were measured. Epistasis was found to be common and complex, involving not only pairwise interactions, but also higher-order interactions. Interactions could also be surprisingly strong, changing fitness by more than 9 orders of magnitude, which is explained by some single mutations being practically lethal. A consequence of the observed epistasis is that many of the minimum-length mutational trajectories between the wild type and the mutant with highest fitness on cells expressing the alternative coreceptor are selectively inaccessible. These results may help explain the difficulty of evolving viruses that use the alternative coreceptor in culture and the delayed evolution of this phenotype in natural infection. Knowledge of common, complex, and strong fitness interactions among amino acids is necessary for a full understanding of protein evolution.

Offsetting virulence and antibiotic resistance costs by MRSA

The prevalence of diverse MRSA (methicillin-resistant Staphylococcus aureus) types in both hospital and community settings is a major health problem worldwide. Here we compare hospital-acquired MRSAs with large type II SCCmec elements with those prevalent in both hospital and community settings with smaller type IV SCCmec elements. We find that the type II but not the type IV SCCmec element causes the bacteria to reduce their levels of costly toxin expression. We compare the relative growth rates of these MRSA types and show that the type II SCCmec carrying MRSAs are more affected than those carrying type IV elements and from this we hypothesize that offsetting the costs associated with antibiotic resistance and toxin expression is why the type II are confined to hospital environments where antibiotic use, the prevalence of immunocompromised individuals and vector-mediated transmission is high. In contrast, those MRSAs that are also successful in the community can maintain their high levels of toxin expression due to a lower fitness burden associated with the smaller SCCmec element.

Impact of azithromycin resistance mutations on the virulence and fitness of Chlamydia caviae in guinea pigs

Azithromycin (AZM) is a major drug used in the treatment and prophylaxis of infections caused by Chlamydia, yet no significant clinical resistance has been reported for these obligate intracellular bacteria. Nevertheless, spontaneous AZM resistance (Azm(r)) arose in vitro at frequencies ranging from 3 x 10(-8) to 8 x 10(-10) for clonal isolates of Chlamydia caviae, which is a natural pathogen of guinea pigs. Sequencing of the unique 23S rRNA gene copy in 44 independent Azm(r) isolates identified single mutations at position A(2058) or A(2059) (Escherichia coli numbering system). While SP(6)AZ(1) (A(2058)C) and SP(6)AZ(2) (A(2059)C) Azm(r) mutants showed growth defects in cell culture and were less pathogenic in the guinea pig ocular infection model than in the parent SP(6), the three isogenic C. caviae isolates grew equally well in the animal. On the other hand, coinoculation of the C. caviae parent strain with one of the Azm(r) strains was detrimental for the mutant strain. This apparent lack of association between pathology and bacterial load in vivo showed that virulence of the two Azm(r) mutants of C. caviae was attenuated. While chlamydial growth in vitro reflects the ability of the bacteria to multiply in permissive cells, survival in the host is a balance between cellular multiplication and clearance by the host immune system. The obligate intracellular nature of Chlamydia may therefore limit emergence of resistance in vivo due to the strength of the immune response induced by the wild-type antibiotic-sensitive bacteria at the time of antibiotic treatment.

Disentangling direct from indirect co-evolution of residues in protein alignments

Predicting protein structure from primary sequence is one of the ultimate challenges in computational biology. Given the large amount of available sequence data, the analysis of co-evolution, i.e., statistical dependency, between columns in multiple alignments of protein domain sequences remains one of the most promising avenues for predicting residues that are contacting in the structure. A key impediment to this approach is that strong statistical dependencies are also observed for many residue pairs that are distal in the structure. Using a comprehensive analysis of protein domains with available three-dimensional structures we show that co-evolving contacts very commonly form chains that percolate through the protein structure, inducing indirect statistical dependencies between many distal pairs of residues. We characterize the distributions of length and spatial distance traveled by these co-evolving contact chains and show that they explain a large fraction of observed statistical dependencies between structurally distal pairs. We adapt a recently developed Bayesian network model into a rigorous procedure for disentangling direct from indirect statistical dependencies, and we demonstrate that this method not only successfully accomplishes this task, but also allows contacts with weak statistical dependency to be detected. To illustrate how additional information can be incorporated into our method, we incorporate a phylogenetic correction, and we develop an informative prior that takes into account that the probability for a pair of residues to contact depends strongly on their primary-sequence distance and the amount of conservation that the corresponding columns in the multiple alignment exhibit. We show that our model including these extensions dramatically improves the accuracy of contact prediction from multiple sequence alignments.

Fitness costs associated with evolved herbicide resistance alleles in plants

Predictions based on evolutionary theory suggest that the adaptive value of evolved herbicide resistance alleles may be compromised by the existence of fitness costs. There have been many studies quantifying the fitness costs associated with novel herbicide resistance alleles, reflecting the importance of fitness costs in determining the evolutionary dynamics of resistance. However, many of these studies have incorrectly defined resistance or used inappropriate plant material and methods to measure fitness. This review has two major objectives. First, to propose a methodological framework that establishes experimental criteria to unequivocally evaluate fitness costs. Second, to present a comprehensive analysis of the literature on fitness costs associated with herbicide resistance alleles. This analysis reveals unquestionable evidence that some herbicide resistance alleles are associated with pleiotropic effects that result in plant fitness costs. Observed costs are evident from herbicide resistance-endowing amino acid substitutions in proteins involved in amino acid, fatty acid, auxin and cellulose biosynthesis, as well as enzymes involved in herbicide metabolism. However, these resistance fitness costs are not universal and their expression depends on particular plant alleles and mutations. The findings of this review are discussed within the context of the plant defence trade-off theory and herbicide resistance evolution.

Mutational neighbourhood and mutation supply rate constrain adaptation in Pseudomonas aeruginosa

Understanding adaptation by natural selection requires understanding the genetic factors that determine which beneficial mutations are available for selection. Here, using experimental evolution of rifampicin-resistant Pseudomonas aeruginosa, we show that different genotypes vary in their capacity for adaptation to the cost of antibiotic resistance. We then use sequence data to show that the beneficial mutations associated with fitness recovery were specific to particular genetic backgrounds, suggesting that genotypes had access to different sets of beneficial mutations. When we manipulated the supply rate of beneficial mutations, by altering effective population size during evolution, we found that it constrained adaptation in some selection lines by restricting access to rare beneficial mutations, but that the effect varied among the genotypes in our experiment. These results suggest that mutational neighbourhood varies even among genotypes that differ by a single amino acid change, and this determines their capacity for adaptation as well as the influence of population biology processes that alter mutation supply rate.

Genomic diversity among drug sensitive and multidrug resistant isolates of Mycobacterium tuberculosis with identical DNA fingerprints

Background

Mycobacterium tuberculosis complex (MTBC), the causative agent of tuberculosis (TB), is characterized by low sequence diversity making this bacterium one of the classical examples of a genetically monomorphic pathogen. Because of this limited DNA sequence variation, routine genotyping of clinical MTBC isolates for epidemiological purposes relies on highly discriminatory DNA fingerprinting methods based on mobile and repetitive genetic elements. According to the standard view, isolates exhibiting the same fingerprinting pattern are considered direct progeny of the same bacterial clone, and most likely reflect ongoing transmission or disease relapse within individual patients.

Methodology/Principal Findings

Here we further investigated this assumption and used massively parallel whole-genome sequencing to compare one drug-susceptible (K-1) and one multidrug resistant (MDR) isolate (K-2) of a rapidly spreading M. tuberculosis Beijing genotype clone from a high incidence region (Karakalpakstan, Uzbekistan). Both isolates shared the same IS6110 RFLP pattern and the same allele at 23 out of 24 MIRU-VNTR loci.

We generated 23.9 million (K-1) and 33.0 million (K-2) paired 50 bp purity filtered reads corresponding to a mean coverage of 483.5 fold and 656.1 fold respectively. Compared with the laboratory strain H37Rv both Beijing isolates shared 1,209 SNPs. The two Beijing isolates differed by 130 SNPs and one large deletion. The susceptible isolate had 55 specific SNPs, while the MDR variant had 75 specific SNPs, including the five known resistance-conferring mutations.

Conclusions

Our results suggest that M. tuberculosis isolates exhibiting identical DNA fingerprinting patterns can harbour substantial genomic diversity. Because this heterogeneity is not captured by traditional genotyping of MTBC, some aspects of the transmission dynamics of tuberculosis could be missed or misinterpreted. Furthermore, a valid differentiation between disease relapse and exogenous reinfection might be impossible using standard genotyping tools if the overall diversity of circulating clones is limited. These findings have important implications for clinical trials of new anti-tuberculosis drugs.

Extensive sequence turnover of the signal peptides of members of the GDF/BMP family: exploring their evolutionary landscape

We show that the predicted signal peptide (SP) sequences of the secreted factors GDF9, BMP15 and AMH are well conserved in mammals but dramatic divergence is noticed for more distant orthologs. Interestingly, bioinformatic predictions show that the divergent protein segments do encode SPs. Thus, such SPs have undergone extensive sequence turnover with full preservation of functionality. This can be explained by a pervasive accumulation of neutral and compensatory mutations. An exploration of the potential evolutionary landscape of some SPs is presented. Some of these signal sequences highlight an apparent paradox: they are encoded, by definition, by orthologous DNA segments but they are, given their striking divergence, examples of what can be called functional convergence.

REVIEWERS

This article was reviewed by Fyodor Kondrashov and Eugene V. Koonin.

The impact of individual human immunodeficiency virus type 1 protease mutations on drug susceptibility is highly influenced by complex interactions with the background protease sequence

The requirement for multiple mutations for protease inhibitor (PI) resistance necessitates a better understanding of the molecular basis of resistance development. The novel bioinformatics resistance determination approach presented here elaborates on genetic profiles observed in clinical human immunodeficiency virus type 1 (HIV-1) isolates. Synthetic protease sequences were cloned in a wild-type HIV-1 background to generate a large number of close variants, covering 69 mutation clusters between multi-PI-resistant viruses and their corresponding genetically closely related, but PI-susceptible, counterparts. The vast number of mutants generated facilitates a profound and broad analysis of the influence of the background on the effect of individual PI resistance-associated mutations (PI-RAMs) on PI susceptibility. Within a set of viruses, all PI-RAMs that differed between susceptible and resistant viruses were varied while maintaining the background sequence from the resistant virus. The PI darunavir was used to evaluate PI susceptibility. Single sets allowed delineation of the impact of individual mutations on PI susceptibility, as well as the influence of PI-RAMs on one another. Comparing across sets, it could be inferred how the background influenced the interaction between two mutations, in some cases even changing antagonistic relationships into synergistic ones or vice versa. The approach elaborates on patient data and demonstrates how the specific mutational background greatly influences the impact of individual mutations on PI susceptibility in clinical patterns.

Down regulation of KMP-11 in Leishmania infantum axenic antimony resistant amastigotes as revealed by a proteomic screen

The therapeutic mainstay against the protozoan parasite Leishmania is still based on the antiquated pentavalent antimonials, but resistance is increasing in several parts of the world. Resistance is now partly understood in laboratory promastigote isolates, but the mechanism leading to drug resistance in amastigote isolates is lagging behind. Here we describe a comparative proteomic analysis of a genetically related pair of antimonial-sensitive and -resistant Leishmania infantum axenic amastigote strains. The proteomics screen has highlighted a number of proteins differentially expressed in the resistant parasite. The expression of the protein argininosuccinate synthetase (ARGG) was increased in the drug resistant mutant while a decrease in the expression of the kinetoplastid membrane protein (KMP-11) correlated with the drug resistance phenotype. This proteomic screen highlighted several novel proteins that are putatively involved in resistance to antimonials.

A case for sequencing the genome of Musca domestica (Diptera: Muscidae)

House flies are carriers of >100 devastating diseases that have severe consequences for human and animal health. Despite the fact that it is a passive vector, a key bottleneck to progress in controlling the human diseases transmitted by house flies is lack of knowledge of the basic molecular biology of this species. Sequencing of the house fly genome will provide important inroads to the discovery of novel target sites for house fly control, understanding of the house fly immune response, rapid elucidation of insecticide resistance genes, and understanding of numerous aspects of the basic biology of this insect pest. The ability of the house fly to prosper in a remarkably septic environment motivates analysis of its innate immune system. Its polymorphic sex determination system, with male-determining factors on either the autosomes or the Y chromosome, is ripe for a genomic analysis. Sequencing of the house fly genome would allow the first opportunity to study the interactions between a pest insect and its parasitoid (Nasonia vitripennis) at the whole genome level. In addition, the house fly is well placed phylogenetically to leverage analysis of the multiple Dipteran genomes that have been sequenced (including several mosquito and Drosophila species). The community of researchers investigating Musca domestica are well prepared and highly motivated to apply genomic analyses to their widely varied research programs.

Compensatory mutations are repeatable and clustered within proteins

Compensatory mutations improve fitness in genotypes that contain deleterious mutations but have no beneficial effects otherwise. As such, compensatory mutations represent a very specific form of epistasis. We show that intragenic compensatory mutations occur non-randomly over gene sequence. Compensatory mutations are more likely to appear at some sites than others. Moreover, the sites of compensatory mutations are more likely than expected by chance to be near the site of the original deleterious mutation. Furthermore, compensatory mutations tend to occur more commonly in certain regions of the protein even when controlling for clustering around the site of the deleterious mutation. These results suggest that compensatory evolution at the protein level is partially predictable and may be convergent.

The effect of three environmental conditions on the fitness of cytochrome P450 monooxygenase-mediated permethrin resistance in Culex pipiens quinquefasciatus

BACKGROUND

The evolution of insecticide resistance and persistence of resistance phenotypes are influenced by the fitness of resistance alleles in the absence of insecticide pressure. Experimental determination of fitness is difficult, but fitness can be inferred by measuring changes in allele frequencies in appropriate environments. We conducted allele competition experiments by crossing two highly related strains of Culex pipiens quinquefasciatus mosquitoes. One strain (ISOP450) was permethrin resistant (due to P450-mediated detoxification) and one was a susceptible strain. Allele and genotype frequencies were examined for 12 generations under three environmental conditions: standard laboratory, temephos exposure (an insecticide to which the P450 detoxification mechanism in ISOP450 confers no resistance and which is commonly used in mosquito control programs) and cold temperature stress (mimics the colder temperatures within the habitat of this mosquito).

RESULTS

A fitness cost was inferred for the P450 mechanism in the standard laboratory environment. A greater cost was associated with the temephos exposed environment, suggesting the temephos placed an additional stress on the P450 resistant mosquitoes. No observed cost was associated with the P450 resistance locus in the cold temperature environment, but there was a significant heterozygote advantage. In all environments the fitness of the resistant homozygotes was the lowest.

CONCLUSION

The cytochrome P450-mediated permethrin detoxification resistance in Cx. p. quinquefasciatus can have an associated fitness cost in the absence of permethrin, relative to a susceptible allele. The strength of the cost varies depending on the environmental conditions. P450-mediated resistance is expected to decrease over time if the permethrin application is relaxed and to decrease at an even faster rate if permethrin is replaced with temephos. Additionally, these results indicate that a P450 resistance allele can persist (especially in heterozygotes) in colder temperatures and could potentially be carried into the Culex pipiens hybrid zone.

Antiviral resistance and the control of pandemic influenza: the roles of stochasticity, evolution and model details

Antiviral drugs, most notably the neuraminidase inhibitors, are an important component of control strategies aimed to prevent or limit any future influenza pandemic. The potential large-scale use of antiviral drugs brings with it the danger of drug resistance evolution. A number of recent studies have shown that the emergence of drug-resistant influenza could undermine the usefulness of antiviral drugs for the control of an epidemic or pandemic outbreak. While these studies have provided important insights, the inherently stochastic nature of resistance generation and spread, as well as the potential for ongoing evolution of the resistant strain have not been fully addressed. Here, we study a stochastic model of drug resistance emergence and consecutive evolution of the resistant strain in response to antiviral control during an influenza pandemic. We find that taking into consideration the ongoing evolution of the resistant strain does not increase the probability of resistance emergence; however, it increases the total number of infecteds if a resistant outbreak occurs. Our study further shows that taking stochasticity into account leads to results that can differ from deterministic models. Specifically, we find that rapid and strong control cannot only contain a drug sensitive outbreak, it can also prevent a resistant outbreak from occurring. We find that the best control strategy is early intervention heavily based on prophylaxis at a level that leads to outbreak containment. If containment is not possible, mitigation works best at intermediate levels of antiviral control. Finally, we show that the results are not very sensitive to the way resistance generation is modeled.

Probing the sequence space available for HIV-1 evolution

We designed a novel experimental approach to probe the sequence space available for HIV-1 evolution. Selective pressure was put on conserved HIV-1 genomic sequences by means of RNA interference (RNAi). Virus escape was monitored in many parallel cultures, and we scored the mutations selected in the RNAi target sequences. The experimentally induced sequence variation closely resembles the sequence variation of natural HIV-1 strains. This indicates that we actually mapped a restricted area of sequence space compatible with virus replication.

Comparison of adhesion and virulence of two predominant hospital-acquired methicillin-resistant Staphylococcus aureus clones and clonal methicillin-susceptible S. aureus isolates

The virulence of SCCmec type IV hospital-acquired methicillin-resistant Staphylococcus aureus (MRSA) clinical isolates belonging to the major sequence type 8 (ST8 [Lyon clone]) and to a minor upcoming clone, ST5, was compared with that of methicillin-susceptible S. aureus (MSSA) isolates of matching sequence types. In vitro adhesion to human airway epithelial cells (HAECs) as an indicator of dissemination and mortality in a murine sepsis model as an indicator of virulence were evaluated. Ten MRSA isolates and 8 MSSA isolates of ST8 and 8 MRSA isolates and 8 MSSA isolates of ST5 were characterized with respect to multilocus sequence type; agr, spa, and capsule typing; in vitro doubling time; toxin and adhesin gene profiles; and adherence to HAECs. Adherence was significantly lower in the MRSA ST5 group than in the ST8 groups. Infections with MRSA and MSSA isolates ST8 and ST5 were compared. No change in virulence related to the presence of SCCmec was observed, since ST8 but not ST5 caused a significantly lower mortality in its presence. Despite their similar genetic backgrounds, individual clonal MRSA and MSSA isolates were heterogeneous in adherence and virulence. No one of these specific virulence factors determined in vitro was related to mouse mortality. In conclusion, in a bacteremic model, mortality was dependent on the ST and was differentially modulated by SCCmec; within an ST, clonality was not associated with a homogenous outcome.

Optimal drug cocktail design: methods for targeting molecular ensembles and insights from theoretical model systems

Drug resistance is a significant obstacle in the effective treatment of diseases with rapidly mutating targets, such as AIDS, malaria, and certain forms of cancer. Such targets are remarkably efficient at exploring the space of functional mutants and at evolving to evade drug binding while still maintaining their biological role. To overcome this challenge, drug regimens must be active against potential target variants. Such a goal may be accomplished by one drug molecule that recognizes multiple variants or by a drug "cocktail"--a small collection of drug molecules that collectively binds all desired variants. Ideally, one wants the smallest cocktail possible due to the potential for increased toxicity with each additional drug. Therefore, the task of designing a regimen for multiple target variants can be framed as an optimization problem--find the smallest collection of molecules that together "covers" the relevant target variants. In this work, we formulate and apply this optimization framework to theoretical model target ensembles. These results are analyzed to develop an understanding of how the physical properties of a target ensemble relate to the properties of the optimal cocktail. We focus on electrostatic variation within target ensembles, as it is one important mechanism by which drug resistance is achieved. Using integer programming, we systematically designed optimal cocktails to cover model target ensembles. We found that certain drug molecules covered much larger regions of target space than others, a phenomenon explained by theory grounded in continuum electrostatics. Molecules within optimal cocktails were often dissimilar, such that each drug was responsible for binding variants with a certain electrostatic property in common. On average, the number of molecules in the optimal cocktails correlated with the number of variants, the differences in the variants' electrostatic properties at the binding interface, and the level of binding affinity required. We also treated cases in which a subset of target variants was to be avoided, modeling the common challenge of closely related host molecules that may be implicated in drug toxicity. Such decoys generally increased the size of the required cocktail and more often resulted in infeasible optimizations. Taken together, this work provides practical optimization methods for the design of drug cocktails and a theoretical, physics-based framework through which useful insights can be achieved.

Neuraminidase inhibitor resistance in influenza: assessing the danger of its generation and spread

Neuraminidase Inhibitors (NI) are currently the most effective drugs against influenza. Recent cases of NI resistance are a cause for concern. To assess the danger of NI resistance, a number of studies have reported the fraction of treated patients from which resistant strains could be isolated. Unfortunately, those results strongly depend on the details of the experimental protocol. Additionally, knowing the fraction of patients harboring resistance is not too useful by itself. Instead, we want to know how likely it is that an infected patient can generate a resistant infection in a secondary host, and how likely it is that the resistant strain subsequently spreads. While estimates for these parameters can often be obtained from epidemiological data, such data is lacking for NI resistance in influenza. Here, we use an approach that does not rely on epidemiological data. Instead, we combine data from influenza infections of human volunteers with a mathematical framework that allows estimation of the parameters that govern the initial generation and subsequent spread of resistance. We show how these parameters are influenced by changes in drug efficacy, timing of treatment, fitness of the resistant strain, and details of virus and immune system dynamics. Our study provides estimates for parameters that can be directly used in mathematical and computational models to study how NI usage might lead to the emergence and spread of resistance in the population. We find that the initial generation of resistant cases is most likely lower than the fraction of resistant cases reported. However, we also show that the results depend strongly on the details of the within-host dynamics of influenza infections, and most importantly, the role the immune system plays. Better knowledge of the quantitative dynamics of the immune response during influenza infections will be crucial to further improve the results.

Neuraminidase Inhibitors (NI) are currently the most effective drugs against influenza. Recent cases of NI resistance are a cause for concern. A number of studies have reported the fraction of treated patients from which resistant virus could be isolated. While these results provide some assessment of the danger of NI resistance, a more quantitative understanding is preferable. We specifically want to know how likely it is that an infected, treated patient infects another person with the resistant strain, and how likely it is that the resistant strain subsequently spreads. Knowing these quantities is important for studies of the population-wide emergence of resistance. While these parameters can often be estimated from epidemiological data, such data is lacking for NI resistance in influenza. Here, we use an alternative approach that combines data from influenza infections of human volunteers with a mathematical framework. We find that the initial generation of resistant cases is most likely lower than the fraction of resistant cases reported. However, our study also clearly shows that the results depend strongly on the role the immune response plays, an issue that needs to be addressed in future studies.