Stepwise acquisition of pyrimethamine resistance in the malaria parasite

Addressing epistasis in the design of protein function

Mutations in protein active sites can dramatically improve function. The active site, however, is densely packed and extremely sensitive to mutations. Therefore, some mutations may only be tolerated in combination with others in a phenomenon known as epistasis. Epistasis reduces the likelihood of obtaining improved functional variants and dramatically slows natural and lab evolutionary processes. Research has shed light on the molecular origins of epistasis and its role in shaping evolutionary trajectories and outcomes. In addition, sequence- and AI-based strategies that infer epistatic relationships from mutational patterns in natural or experimental evolution data have been used to design functional protein variants. In recent years, combinations of such approaches and atomistic design calculations have successfully predicted highly functional combinatorial mutations in active sites. These were used to design thousands of functional active-site variants, demonstrating that, while our understanding of epistasis remains incomplete, some of the determinants that are critical for accurate design are now sufficiently understood. We conclude that the space of active-site variants that has been explored by evolution may be expanded dramatically to enhance natural activities or discover new ones. Furthermore, design opens the way to systematically exploring sequence and structure space and mutational impacts on function, deepening our understanding and control over protein activity.

Two decades of molecular surveillance in Senegal reveal rapid changes in known drug resistance mutations over time

BACKGROUND

Drug resistance in Plasmodium falciparum is a major threat to malaria control efforts. Pathogen genomic surveillance could be invaluable for monitoring current and emerging parasite drug resistance.

METHODS

Data from two decades (2000-2020) of continuous molecular surveillance of P. falciparum parasites from Senegal were retrospectively examined to assess historical changes in malaria drug resistance mutations. Several known drug resistance markers and their surrounding haplotypes were profiled using a combination of single nucleotide polymorphism (SNP) molecular surveillance and whole genome sequence based population genomics.

RESULTS

This dataset was used to track temporal changes in drug resistance markers whose timing correspond to historically significant events such as the withdrawal of chloroquine (CQ) and the introduction of sulfadoxine-pyrimethamine (SP) in 2003. Changes in the mutation frequency at Pfcrt K76T and Pfdhps A437G coinciding with the 2014 introduction of seasonal malaria chemoprevention (SMC) in Senegal were observed. In 2014, the frequency of Pfcrt K76T increased while the frequency of Pfdhps A437G declined. Haplotype-based analyses of Pfcrt K76T showed that this rapid increase was due to a recent selective sweep that started after 2014.

DISCUSSION (CONCLUSION)

The rapid increase in Pfcrt K76T is troubling and could be a sign of emerging amodiaquine (AQ) resistance in Senegal. Emerging AQ resistance may threaten the future clinical efficacy of artesunate-amodiaquine (ASAQ) and AQ-dependent SMC chemoprevention. These results highlight the potential of molecular surveillance for detecting rapid changes in parasite populations and stress the need to monitor the effectiveness of AQ as a partner drug for artemisinin-based combination therapy (ACT) and for chemoprevention.

Sampling Strategies for Experimentally Mapping Molecular Fitness Landscapes Using High-Throughput Methods

Empirical studies of genotype-phenotype-fitness maps of proteins are fundamental to understanding the evolutionary process, in elucidating the space of possible genotypes accessible through mutations in a landscape of phenotypes and fitness effects. Yet, comprehensively mapping molecular fitness landscapes remains challenging since all possible combinations of amino acid substitutions for even a few protein sites are encoded by an enormous genotype space. High-throughput mapping of genotype space can be achieved using large-scale screening experiments known as multiplexed assays of variant effect (MAVEs). However, to accommodate such multi-mutational studies, the size of MAVEs has grown to the point where a priori determination of sampling requirements is needed. To address this problem, we propose calculations and simulation methods to approximate minimum sampling requirements for multi-mutational MAVEs, which we combine with a new library construction protocol to experimentally validate our approximation approaches. Analysis of our simulated data reveals how sampling trajectories differ between simulations of nucleotide versus amino acid variants and among mutagenesis schemes. For this, we show quantitatively that marginal gains in sampling efficiency demand increasingly greater sampling effort when sampling for nucleotide sequences over their encoded amino acid equivalents. We present a new library construction protocol that efficiently maximizes sequence variation, and demonstrate using ultradeep sequencing that the library encodes virtually all possible combinations of mutations within the experimental design. Insights learned from our analyses together with the methodological advances reported herein are immediately applicable toward pooled experimental screens of arbitrary design, enabling further assay upscaling and expanded testing of genotype space.

Evolutionary druggability for low-dimensional fitness landscapes toward new metrics for antimicrobial applications

The term 'druggability' describes the molecular properties of drugs or targets in pharmacological interventions and is commonly used in work involving drug development for clinical applications. There are no current analogues for this notion that quantify the drug-target interaction with respect to a given target variant's sensitivity across a breadth of drugs in a panel, or a given drug's range of effectiveness across alleles of a target protein. Using data from low-dimensional empirical fitness landscapes composed of 16 β-lactamase alleles and 7 β-lactam drugs, we introduce two metrics that capture (i) the average susceptibility of an allelic variant of a drug target to any available drug in a given panel ('variant vulnerability'), and (ii) the average applicability of a drug (or mixture) across allelic variants of a drug target ('drug applicability'). Finally, we (iii) disentangle the quality and magnitude of interactions between loci in the drug target and the seven drug environments in terms of their mutation by mutation by environment (G x G x E) interactions, offering mechanistic insight into the variant variability and drug applicability metrics. Summarizing, we propose that our framework can be applied to other datasets and pathogen-drug systems to understand which pathogen variants in a clinical setting are the most concerning (low variant vulnerability), and which drugs in a panel are most likely to be effective in an infection defined by standing genetic variation in the pathogen drug target (high drug applicability).

Epistasis facilitates functional evolution in an ancient transcription factor

A protein's genetic architecture - the set of causal rules by which its sequence produces its functions - also determines its possible evolutionary trajectories. Prior research has proposed that the genetic architecture of proteins is very complex, with pervasive epistatic interactions that constrain evolution and make function difficult to predict from sequence. Most of this work has analyzed only the direct paths between two proteins of interest - excluding the vast majority of possible genotypes and evolutionary trajectories - and has considered only a single protein function, leaving unaddressed the genetic architecture of functional specificity and its impact on the evolution of new functions. Here, we develop a new method based on ordinal logistic regression to directly characterize the global genetic determinants of multiple protein functions from 20-state combinatorial deep mutational scanning (DMS) experiments. We use it to dissect the genetic architecture and evolution of a transcription factor's specificity for DNA, using data from a combinatorial DMS of an ancient steroid hormone receptor's capacity to activate transcription from two biologically relevant DNA elements. We show that the genetic architecture of DNA recognition consists of a dense set of main and pairwise effects that involve virtually every possible amino acid state in the protein-DNA interface, but higher-order epistasis plays only a tiny role. Pairwise interactions enlarge the set of functional sequences and are the primary determinants of specificity for different DNA elements. They also massively expand the number of opportunities for single-residue mutations to switch specificity from one DNA target to another. By bringing variants with different functions close together in sequence space, pairwise epistasis therefore facilitates rather than constrains the evolution of new functions.

Deep mutational scanning of Pneumocystis jirovecii dihydrofolate reductase reveals allosteric mechanism of resistance to an antifolate

Pneumocystis jirovecii is a fungal pathogen that causes pneumocystis pneumonia, a disease that mainly affects immunocompromised individuals. This fungus has historically been hard to study because of our inability to grow it in vitro. One of the main drug targets in P. jirovecii is its dihydrofolate reductase (PjDHFR). Here, by using functional complementation of the baker's yeast ortholog, we show that PjDHFR can be inhibited by the antifolate methotrexate in a dose-dependent manner. Using deep mutational scanning of PjDHFR, we identify mutations conferring resistance to methotrexate. Thirty-one sites spanning the protein have at least one mutation that leads to resistance, for a total of 355 high-confidence resistance mutations. Most resistance-inducing mutations are found inside the active site, and many are structurally equivalent to mutations known to lead to resistance to different antifolates in other organisms. Some sites show specific resistance mutations, where only a single substitution confers resistance, whereas others are more permissive, as several substitutions at these sites confer resistance. Surprisingly, one of the permissive sites (F199) is without direct contact to either ligand or cofactor, suggesting that it acts through an allosteric mechanism. Modeling changes in binding energy between F199 mutants and drug shows that most mutations destabilize interactions between the protein and the drug. This evidence points towards a more important role of this position in resistance than previously estimated and highlights potential unknown allosteric mechanisms of resistance to antifolate in DHFRs. Our results offer unprecedented resources for the interpretation of mutation effects in the main drug target of an uncultivable fungal pathogen.

Meta-analysis on Plasmodium falciparum sulfadoxine-pyrimethamine resistance-conferring mutations in India identifies hot spots for genetic surveillance

BACKGROUND

India is on track to eliminate malaria by 2030 but emerging resistance to first-line antimalarials is a recognised threat. Two instances of rapid development, spread, and natural selection of drug-resistant mutant parasites in India (chloroquine across the country and artesunate + sulfadoxine-pyrimethamine [AS+SP] in the northeastern states) translated into drug policy changes for Plasmodium falciparum malaria in 2010 and 2013, respectively. Considering these rapid changes in the SP drug resistance-conferring mutation profile of P. falciparum, there is a need to systematically monitor the validated mutations in Pfdhfr and Pfdhps genes across India alongside AS+SP therapeutic efficacy studies. There has been no robust, systematic countrywide surveillance reported for these parameters in India, hence the current study was undertaken.

METHODS

Studies that reported data on WHO-validated SP resistance markers in P. falciparum across India from 2008 to January 2023 were included. Five major databases, PubMedⓇ, Web of ScienceTM, ScopusⓇ, EmbaseⓇ, and Google Scholar, were exhaustively searched. Individual and pooled prevalence estimates of mutations were obtained through random- and fixed-effect models. Data were depicted using forest plots created with a 95% confidence interval. The study is registered with PROSPERO (CRD42021236012).

RESULTS

A total of 37 publications, and 533 Pfdhfr and 134 Pfdhps National Centre of Biotechnology Information (NCBI) DNA sequences were included from >4000 samples. The study included information from 80 districts, 21 states and 3 union territories (UTs) from India. The two PfDHFR mutations, C59R (62%) and S108N (74%), were the most prevalent mutations (pooled estimates 61% and 71%, respectively) and appeared to be stabilised/fixed. Although rarest overall, the prevalence of I164L was observed to be as high as 32%. The PfDHFR double mutants were the most prevalent overall (51%; pooled 42%). The prevalence of triple and quadruple mutations was 6% and 5%, respectively, and is an immediate concern for some states. The most prevalent PfDHPS mutation was A437G (39%), followed by K540E (25%) and A581G (12%). There was a low overall prevalence of PfDHFR/PfDHPS quintuple and sextuple mutations but surveillance for these mutations is critical for some areas.

CONCLUSION

The analyses span the two critical policy changes, highlight the areas of concern, and guide policymakers in strategising and refining the anti-malaria drug policy for malaria elimination. The results of the analyses also highlight the SP-resistance hot spots, critical gaps and challenges, and indicate that focal and local malaria genetic surveillance (including drug-resistance markers) is needed until malaria is successfully eliminated.

A computational method for predicting the most likely evolutionary trajectories in the stepwise accumulation of resistance mutations

Pathogen evolution of drug resistance often occurs in a stepwise manner via the accumulation of multiple mutations that in combination have a non-additive impact on fitness, a phenomenon known as epistasis. The evolution of resistance via the accumulation of point mutations in the DHFR genes of Plasmodium falciparum (Pf) and Plasmodium vivax (Pv) has been studied extensively and multiple studies have shown epistatic interactions between these mutations determine the accessible evolutionary trajectories to highly resistant multiple mutations. Here, we simulated these evolutionary trajectories using a model of molecular evolution, parameterised using Rosetta Flex ddG predictions, where selection acts to reduce the target-drug binding affinity. We observe strong agreement with pathways determined using experimentally measured IC50 values of pyrimethamine binding, which suggests binding affinity is strongly predictive of resistance and epistasis in binding affinity strongly influences the order of fixation of resistance mutations. We also infer pathways directly from the frequency of mutations found in isolate data, and observe remarkable agreement with the most likely pathways predicted by our mechanistic model, as well as those determined experimentally. This suggests mutation frequency data can be used to intuitively infer evolutionary pathways, provided sufficient sampling of the population.

Limited Polymorphism in the Dihydrofolate Reductase (dhfr) and dihydropteroate synthase genes (dhps) of Plasmodium knowlesi isolate from Thailand

BACKGROUND

The 2022 malaria WHO reported around 4000 P. knowlesi infections in the South-East Asia region. In the same period, 72 positive cases were reported by the Department of Disease Control in Thailand, suggesting a persistent infection. Little is known about dihydrofolate reductase (pkdhfr) and dihydropteroate synthase (pkdhps), putative antimalarial resistance markers for P. knowlesi. The relevant amplification and sequencing protocol are presently unavailable. In this study, we developed a protocol for amplifying and evaluating pkdhps mutations. The haplotype pattern of pkdhfr-pkdhps in Thai isolates was analyzed, and the effects of these pkdhps mutations were predicted by using a computer program.

METHODS

Pkdhps were amplified and sequenced from 28 P. knowlesi samples collected in 2008 and 2020 from nine provinces across Thailand. Combining pkdhfr sequencing data from previous work with pkdhps data to analyze polymorphisms of pkdhfr and pkdhps haplotype. Protein modeling and molecular docking were constructed using two inhibitors, sulfadoxine and sulfamethoxazole, and further details were obtained through analyses of protein-ligand interactions by using the Genetic Optimisation for Ligand Docking program. A phylogenetic tree cluster analysis was reconstructed to compare the P. knowlesi Malaysia isolates.

RESULTS

Five nonsynonymous mutations in the pkdhps were detected outside the equivalence of the binding pocket sites to sulfadoxine and sulfamethoxazole, which are at N391S, E421G, I425R, A449S, and N517S. Based on the modeling and molecular docking analyses, the N391S and N517S mutations located close to the enzyme-binding pocket demonstrated a different docking score and protein-ligand interaction in loop 2 of the enzyme. These findings indicated that it was less likely to induce drug resistance. Of the four haplotypes of pkdhfr-pkdhps, the most common one is the R34L pkdhfr mutation and the pkdhps quadruple mutation (GRSS) at E421G, I425R, A449S, and N517S, which were observed in P. knowlesi in southern Thailand (53.57%). Based on the results of neighbor-joining analysis for pkdhfr and pkdhps, the samples isolated from eastern Thailand displayed a close relationship with Cambodia isolates, while southern Thailand isolates showed a long branch separated from the Malaysian isolates.

CONCLUSIONS

A new PCR protocol amplification and evaluation of dihydropteroate synthase mutations in Knowlesi (pkdhps) has been developed. The most prevalent pkdhfr-pkdhps haplotypes (53.57%) in southern Thailand are R34L pkdhfr mutation and pkdhps quadruple mutation. Further investigation requires additional phenotypic data from clinical isolates, transgenic lines expressing mutant alleles, or recombinant proteins.

A rugged yet easily navigable fitness landscape

Fitness landscape theory predicts that rugged landscapes with multiple peaks impair Darwinian evolution, but experimental evidence is limited. In this study, we used genome editing to map the fitness of >260,000 genotypes of the key metabolic enzyme dihydrofolate reductase in the presence of the antibiotic trimethoprim, which targets this enzyme. The resulting landscape is highly rugged and harbors 514 fitness peaks. However, its highest peaks are accessible to evolving populations via abundant fitness-increasing paths. Different peaks share large basins of attraction that render the outcome of adaptive evolution highly contingent on chance events. Our work shows that ruggedness need not be an obstacle to Darwinian evolution but can reduce its predictability. If true in general, the complexity of optimization problems on realistic landscapes may require reappraisal.

Diverse evolutionary pathways challenge the use of collateral sensitivity as a strategy to suppress resistance

Drug resistance remains a major obstacle to malaria control and eradication efforts, necessitating the development of novel therapeutic strategies to treat this disease. Drug combinations based on collateral sensitivity, wherein resistance to one drug causes increased sensitivity to the partner drug, have been proposed as an evolutionary strategy to suppress the emergence of resistance in pathogen populations. In this study, we explore collateral sensitivity between compounds targeting the Plasmodium dihydroorotate dehydrogenase (DHODH). We profiled the cross-resistance and collateral sensitivity phenotypes of several DHODH mutant lines to a diverse panel of DHODH inhibitors. We focus on one compound, TCMDC-125334, which was active against all mutant lines tested, including the DHODH C276Y line, which arose in selections with the clinical candidate DSM265. In six selections with TCMDC-125334, the most common mechanism of resistance to this compound was copy number variation of the dhodh locus, although we did identify one mutation, DHODH I263S, which conferred resistance to TCMDC-125334 but not DSM265. We found that selection of the DHODH C276Y mutant with TCMDC-125334 yielded additional genetic changes in the dhodh locus. These double mutant parasites exhibited decreased sensitivity to TCMDC-125334 and were highly resistant to DSM265. Finally, we tested whether collateral sensitivity could be exploited to suppress the emergence of resistance in the context of combination treatment by exposing wildtype parasites to both DSM265 and TCMDC-125334 simultaneously. This selected for parasites with a DHODH V532A mutation which were cross-resistant to both compounds and were as fit as the wildtype parent in vitro. The emergence of these cross-resistant, evolutionarily fit parasites highlights the mutational flexibility of the DHODH enzyme.

Evolutionary druggability: leveraging low-dimensional fitness landscapes towards new metrics for antimicrobial applications

The term "druggability" describes the molecular properties of drugs or targets in pharmacological interventions and is commonly used in work involving drug development for clinical applications. There are no current analogues for this notion that quantify the drug-target interaction with respect to a given target variant's sensitivity across a breadth of drugs in a panel, or a given drug's range of effectiveness across alleles of a target protein. Using data from low-dimensional empirical fitness landscapes composed of 16 β-lactamase alleles and seven β-lactam drugs, we introduce two metrics that capture (i) the average susceptibility of an allelic variant of a drug target to any available drug in a given panel ("variant vulnerability"), and (ii) the average applicability of a drug (or mixture) across allelic variants of a drug target ("drug applicability"). Finally, we (iii) disentangle the quality and magnitude of interactions between loci in the drug target and the seven drug environments in terms of their mutation by mutation by environment (G × G × E) interactions, offering mechanistic insight into the variant variability and drug applicability metrics. Summarizing, we propose that our framework can be applied to other datasets and pathogen-drug systems to understand which pathogen variants in a clinical setting are the most concerning (low variant vulnerability), and which drugs in a panel are most likely to be effective in an infection defined by standing genetic variation in the pathogen drug target (high drug applicability).

Therapeutic efficacy of artesunate-amodiaquine and artemether-lumefantrine for the treatment of uncomplicated falciparum malaria in Chad: clinical and genetic surveillance

BACKGROUND

Artesunate-amodiaquine (AS-AQ) and artemether-lumefantrine (AL) are the currently recommended first-and second-line therapies for uncomplicated Plasmodium falciparum infections in Chad. This study assessed the efficacy of these artemisinin-based combinations, proportion of day 3 positive patients, proportions of molecular markers associated with P. falciparum resistance to anti-malarial drugs and variable performance of HRP2-based malaria rapid diagnostic tests (RDTs).

METHODS

A single-arm prospective study assessing the efficacy of AS-AQ and AL at three sites (Doba, Kelo and Koyom) was conducted between November 2020 to January 2021. Febrile children aged 6 to 59 months with confirmed uncomplicated P. falciparum infection were enrolled sequentially first to AS-AQ and then AL at each site and followed up for 28 days. The primary endpoint was PCR-adjusted adequate clinical and parasitological response (ACPR). Samples collected on day 0 were analysed for mutations in pfkelch13, pfcrt, pfmdr-1, pfdhfr, pfdhps genes and deletions in pfhrp2/pfhrp3 genes.

RESULTS

By the end of 28-day follow-up, per-protocol PCR corrected ACPR of 97.8% (CI 95% 88.2-100) in Kelo and 100% in Doba and Kayoma were observed among AL treated patients. For ASAQ, 100% ACPR was found in all sites. All, but one patient, did not have parasites detected on day 3. Out of the 215 day 0 samples, 96.7% showed pfkelch13 wild type allele. Seven isolates carried nonsynonymous mutations not known to be associated artemisinin partial resistance (ART-R). Most of samples had a pfcrt wild type allele (79% to 89%). The most prevalent pfmdr-1 allele detected was the single mutant 184F (51.2%). For pfdhfr and pfdhps mutations, the quintuple mutant allele N51I/C59R/S108N + G437A/540E responsible for SP treatment failures in adults and children was not detected. Single deletion in the pfhrp2 and pfhrp3 gene were detected in 10/215 (4.7%) and 2/215 (0.9%), respectively. Dual pfhrp2/pfhrp3 deletions, potentially threatening the efficacy of HRP2-based RDTs, were observed in 5/215 (2.3%) isolates.

CONCLUSION

The results of this study confirm that AS-AQ and AL treatments are highly efficacious in study areas in Chad. The absence of known pfkelch13 mutations in the study sites and the high parasite clearance rate at day 3 suggest the absence of ART-R. The absence of pfdhfr/pfdhps quintuple or sextuple (quintuple + 581G) mutant supports the continued use of SP for IPTp during pregnancy. The presence of parasites with dual pfhrp2/pfhrp3 deletions, potentially threatening the efficacy of HRP2-based RDTs, warrants the continued surveillance. Trial registration ACTRN12622001476729.

Polymorphism analysis of drug resistance markers in Plasmodium falciparum isolates from Benin

Like most countries in sub-Saharan African countries, Benin continues to bear a heavy malaria burden. In 2014, the National Malaria Control Programme (NMCP) changed its treatment policy, and recommended the use of artemisinin-based combination therapy (ACT) as first-line treatment for uncomplicated Plasmodium falciparum cases. The study presented here was conducted to investigate the impact of current antimalarial drug resistance on the country. Molecular surveillance targeting the Pfcrt, Pfmdr1, Pfkelch13, dhfr, and dhps genes was carried out on samples from patients positive for P. falciparum malaria by microscopy, LAMP and PCR diagnostic test. Molecular analysis was performed using targeted amplicon deep sequencing (TADS). In addition, the frequency of parasites with dual deletion of the histidine-rich protein 2 and 3 genes (pfhrp2 and pfhrp3), known to be responsible of the performance of HRP-based malaria rapid diagnostic tests (HRP-RDT), was estimated. Fifty-three falciparum samples collected at the Saint Jean de Dieu hospital in Tanguiéta, Benin, were tested. No Pfkelch13 validated or candidate artemisinin partial resistant variants were identified. A marked prevalence of Asn51Ile (N51I), Cys59Arg (C59R), and Ser108Asn (S108N) mutant alleles was found in the dhfr gene, representing the most frequent genotype (64%). Five-point mutations were detected in dhps, Ile431Val (I431V), Ser436Ala (S436A), Ala437Gly (A437G), Ala581Gly (A581G), Ala613Ser (A613S) of which the third was the most common (92%). No mutation was identified in dhps Lys540Glu (K540E). The quintuple mutant genotype resulting from the combination of the dhfr triple mutant (51I/59R/108N) with the dhps double mutant 436A/437G was detected at a frequency of 30%. Low levels of mutations in Pfcrt and no mutation at codon 86 in the Pfmdr1 DNA fragment were observed, whereas a high level of Tyr184Phe (Y184F) polymorphism in the Pfmdr1 gene was found. These results could be indicative, over a decade after the implementation of ACT therapy, of the return of chloroquine-sensitive but artemether-lumefantrine resistant falciparum genotypes in Benin. There was no evidence of HRP2 and HRP3 deletions. Data from the present study support the need for routine monitoring of molecular markers of antimalarial drug resistance as part of surveillance activities aimed to make informed treatment policy decisions at the national level.

Impact of population size on early adaptation in rugged fitness landscapes

Owing to stochastic fluctuations arising from finite population size, known as genetic drift, the ability of a population to explore a rugged fitness landscape depends on its size. In the weak mutation regime, while the mean steady-state fitness increases with population size, we find that the height of the first fitness peak encountered when starting from a random genotype displays various behaviours versus population size, even among small and simple rugged landscapes. We show that the accessibility of the different fitness peaks is key to determining whether this height overall increases or decreases with population size. Furthermore, there is often a finite population size that maximizes the height of the first fitness peak encountered when starting from a random genotype. This holds across various classes of model rugged landscapes with sparse peaks, and in some experimental and experimentally inspired ones. Thus, early adaptation in rugged fitness landscapes can be more efficient and predictable for relatively small population sizes than in the large-size limit. This article is part of the theme issue 'Interdisciplinary approaches to predicting evolutionary biology'.

The Fitness of Beta-Lactamase Mutants Depends Nonlinearly on Resistance Level at Sublethal Antibiotic Concentrations

Adaptive evolutionary processes are constrained by the availability of mutations which cause a fitness benefit and together make up the fitness landscape, which maps genotype space onto fitness under specified conditions. Experimentally derived fitness landscapes have demonstrated a predictability to evolution by identifying limited "mutational routes" that evolution by natural selection may take between low and high-fitness genotypes. However, such studies often utilize indirect measures to determine fitness. We estimated the competitive fitness of mutants relative to all single-mutation neighbors to describe the fitness landscape of three mutations in a β-lactamase enzyme. Fitness assays were performed at sublethal concentrations of the antibiotic cefotaxime in a structured and unstructured environment. In the unstructured environment, the antibiotic selected for higher-resistance types-but with an equivalent fitness for a subset of mutants, despite substantial variation in resistance-resulting in a stratified fitness landscape. In contrast, in a structured environment with a low antibiotic concentration, antibiotic-susceptible genotypes had a relative fitness advantage, which was associated with antibiotic-induced filamentation. These results cast doubt that highly resistant genotypes have a unique selective advantage in environments with subinhibitory concentrations of antibiotics and demonstrate that direct fitness measures are required for meaningful predictions of the accessibility of evolutionary routes. IMPORTANCE The evolution of antibiotic-resistant bacterial populations underpins the ongoing antibiotic resistance crisis. We aim to understand how antibiotic-degrading enzymes can evolve to cause increased resistance, how this process is constrained, and whether it can be predictable. To this end, competition experiments were performed with a combinatorially complete set of mutants of a β-lactamase gene subject to subinhibitory concentrations of the antibiotic cefotaxime. While some mutations confer on their hosts high resistance to cefotaxime, in competition these mutations do not always confer a selective advantage. Specifically, high-resistance mutants had equivalent fitnesses despite different resistance levels and even had selective disadvantages under conditions involving spatial structure. Together, our findings suggest that the relationship between resistance level and fitness at subinhibitory concentrations is complex; predicting the evolution of antibiotic resistance requires knowledge of the conditions that select for resistant genotypes and the selective advantage evolved types have over their predecessors.

Two decades of molecular surveillance in Senegal reveal changes in known drug resistance mutations associated with historical drug use and seasonal malaria chemoprevention

Drug resistance in Plasmodium falciparum is a major threat to malaria control efforts. We analyzed data from two decades (2000-2020) of continuous molecular surveillance of P. falciparum parasite strains in Senegal to determine how historical changes in drug administration policy may have affected parasite evolution. We profiled several known drug resistance markers and their surrounding haplotypes using a combination of single nucleotide polymorphism (SNP) molecular surveillance and whole-genome sequence (WGS) based population genomics. We observed rapid changes in drug resistance markers associated with the withdrawal of chloroquine and introduction of sulfadoxine-pyrimethamine in 2003. We also observed a rapid increase in Pfcrt K76T and decline in Pfdhps A437G starting in 2014, which we hypothesize may reflect changes in resistance or fitness caused by seasonal malaria chemoprevention (SMC). Parasite populations evolve rapidly in response to drug use, and SMC preventive efficacy should be closely monitored.

Molecular Docking Studies of Rifampicin - rpoB complex: Repurposing Drug Design Implications for against Plasmodium falciparum Malaria through a Computational Approach

Malaria is one of the world's most devastating diseases, infecting well over 300 million people annually and killing between 2 and 3 million worldwide. Increasing parasite resistance to many existing drugs is exacerbating disease. Resistance to commonly used malarial drugs is increasing the need to develop new drugs urgently. Due to the slow pace and substantial costs of new drug development, repurposing of old drugs which is recently increasingly becoming an attractive proposition of highly efficient and effective way of drug discovery led us to study the drug rifampicin for this purpose. The present paper aims to investigate the route of Plasmodium falciparum apicoplast-targeted proteins that putatively encode β subunits of RNA polymerase with an objective to develop an effective antimalarial drug. Homology searching for conserved binding site to the rifampicin drug and the functional analysis of rpoB gene were done. Multiple Sequence alignment analysis of rpoB was compared with that in E.coli - rpoB and M. tuberculosis - rpoB. Docking studies of Rifampicin - rpoB complex was also done for finding binding affinity. The results of computational studies showed that rifampicin is a potential drug for malaria.

Synonymous and Nonsynonymous Substitutions in Dictyostelium discoideum Ammonium Transporter amtA Are Necessary for Functional Complementation in Saccharomyces cerevisiae

Ammonium transporters are present in all three domains of life. They have undergone extensive horizontal gene transfer (HGT), gene duplication, and functional diversification and therefore offer an excellent paradigm to study protein evolution. We attempted to complement a mep1Δmep2Δmep3Δ strain of Saccharomyces cerevisiae (triple-deletion strain), which otherwise cannot grow on ammonium as a sole nitrogen source at concentrations of <3 mM, with amtA of Dictyostelium discoideum, an orthologue of S. cerevisiae MEP2. We observed that amtA did not complement the triple-deletion strain of S. cerevisiae for growth on low-ammonium medium. We isolated two mutant derivatives of amtA (amtA M1 and amtA M2) from a PCR-generated mutant plasmid library that complemented the triple-deletion strain of S. cerevisiae. amtA M1 bears three nonsynonymous and two synonymous substitutions, which are necessary for its functionality. amtA M2 bears two nonsynonymous substitutions and one synonymous substitution, all of which are necessary for functionality. Interestingly, AmtA M1 transports ammonium but does not confer methylamine toxicity, while AmtA M2 transports ammonium and confers methylamine toxicity, demonstrating functional diversification. Preliminary biochemical analyses indicated that the mutants differ in their conformations as well as their mechanisms of ammonium transport. These intriguing results clearly point out that protein evolution cannot be fathomed by studying nonsynonymous and synonymous substitutions in isolation. The above-described observations have significant implications for various facets of biological processes and are discussed in detail. IMPORTANCE Functional diversification following gene duplication is one of the major driving forces of protein evolution. While the role of nonsynonymous substitutions in the functional diversification of proteins is well recognized, knowledge of the role of synonymous substitutions in protein evolution is in its infancy. Using functional complementation, we isolated two functional alleles of the D. discoideum ammonium transporter gene (amtA), which otherwise does not function in S. cerevisiae as an ammonium transporters. One of them is an ammonium transporter, while the other is an ammonium transporter that also confers methylammonium (ammonium analogue) toxicity, suggesting functional diversification. Surprisingly, both alleles require a combination of synonymous and nonsynonymous substitutions for their functionality. These results bring out a hitherto-unknown pathway of protein evolution and pave the way for not only understanding protein evolution but also interpreting single nucleotide polymorphisms (SNPs).

Prevalence of Mutations in the Pfdhfr, Pfdhps, and Pfmdr1 Genes of Malarial Parasites Isolated from Symptomatic Patients in Dogondoutchi, Niger

The effectiveness of artemisinin-based combination therapies (ACTs) depends not only on that of artemisinin but also on that of partner molecules. This study aims to evaluate the prevalence of mutations in the Pfdhfr, Pfdhps, and Pfmdr1 genes from isolates collected during a clinical study. Plasmodium genomic DNA samples extracted from symptomatic malaria patients from Dogondoutchi, Niger, were sequenced by the Sanger method to determine mutations in the Pfdhfr (codons 51, 59, 108, and 164), Pfdhps (codons 436, 437, 540, 581, and 613), and Pfmdr1 (codons 86, 184, 1034, and 1246) genes. One hundred fifty-five (155) pre-treatment samples were sequenced for the Pfdhfr, Pfdhps, and Pfmdr1 genes. A high prevalence of mutations in the Pfdhfr gene was observed at the level of the N51I (84.97%), C59R (92.62%), and S108N (97.39%) codons. The key K540E mutation in the Pfdhps gene was not observed. Only one isolate was found to harbor a mutation at codon I431V. The most common mutation on the Pfmdr1 gene was Y184F in 71.43% of the mutations found, followed by N86Y in 10.20%. The triple-mutant haplotype N51I/C59R/S108N (IRN) was detected in 97% of the samples. Single-mutant (ICS and NCN) and double-mutant (IRS, NRN, and ICN) haplotypes were prevalent at 97% and 95%, respectively. Double-mutant haplotypes of the Pfdhps (581 and 613) and Pfmdr (86 and 184) were found in 3% and 25.45% of the isolates studied, respectively. The study focused on the molecular analysis of the sequencing of the Pfdhfr, Pfdhps, and Pfmdr1 genes. Although a high prevalence of mutations in the Pfdhfr gene have been observed, there is a lack of sulfadoxine pyrimethamine resistance. There is a high prevalence of mutation in the Pfmdr184 codon associated with resistance to amodiaquine. These data will be used by Niger’s National Malaria Control Program to better monitor the resistance of Plasmodium to partner molecules in artemisinin-based combination therapies.

A Family of Fitness Landscapes Modeled through Gene Regulatory Networks

Fitness landscapes are a powerful metaphor for understanding the evolution of biological systems. These landscapes describe how genotypes are connected to each other through mutation and related through fitness. Empirical studies of fitness landscapes have increasingly revealed conserved topographical features across diverse taxa, e.g., the accessibility of genotypes and "ruggedness". As a result, theoretical studies are needed to investigate how evolution proceeds on fitness landscapes with such conserved features. Here, we develop and study a model of evolution on fitness landscapes using the lens of Gene Regulatory Networks (GRNs), where the regulatory products are computed from multiple genes and collectively treated as phenotypes. With the assumption that regulation is a binary process, we prove the existence of empirically observed, topographical features such as accessibility and connectivity. We further show that these results hold across arbitrary fitness functions and that a trade-off between accessibility and ruggedness need not exist. Then, using graph theory and a coarse-graining approach, we deduce a mesoscopic structure underlying GRN fitness landscapes where the information necessary to predict a population's evolutionary trajectory is retained with minimal complexity. Using this coarse-graining, we develop a bottom-up algorithm to construct such mesoscopic backbones, which does not require computing the genotype network and is therefore far more efficient than brute-force approaches. Altogether, this work provides mathematical results of high-dimensional fitness landscapes and a path toward connecting theory to empirical studies.

Targeted Amplicon Deep Sequencing for Monitoring Antimalarial Resistance Markers in Western Kenya

Molecular surveillance of Plasmodium falciparum parasites is important to track emerging and new mutations and trends in established mutations and should serve as an early warning system for antimalarial resistance. Dried blood spots were obtained from a Plasmodium falciparum malaria survey in school children conducted across eight counties in western Kenya in 2019. Real-time PCR identified 500 P. falciparum-positive samples that were amplified at five drug resistance loci for targeted amplicon deep sequencing (TADS). The absence of important kelch 13 mutations was similar to previous findings in Kenya pre-2019, and low-frequency mutations were observed in codons 569 and 578. The chloroquine resistance transporter gene codons 76 and 145 were wild type, indicating that the parasites were chloroquine and piperaquine sensitive, respectively. The multidrug resistance gene 1 haplotypes based on codons 86, 184, and 199 were predominantly present in mixed infections with haplotypes NYT and NFT, driven by the absence of chloroquine pressure and the use of lumefantrine, respectively. The sulfadoxine-pyrimethamine resistance profile was a “superresistant” combination of triple mutations in both Pfdhfr (51I 59R 108N) and Pfdhps (436H 437G 540E), rendering sulfadoxine-pyrimethamine ineffective. TADS highlighted the low-frequency variants, allowing the early identification of new mutations, Pfmdr1 codon 199S and Pfdhfr codon 85I and emerging 164L mutations. The added value of TADS is its accuracy in identifying mixed-genotype infections and for high-throughput monitoring of antimalarial resistance markers.

Evidence for the early emergence of piperaquine-resistant Plasmodium falciparum malaria and modeling strategies to mitigate resistance

Multidrug-resistant Plasmodium falciparum parasites have emerged in Cambodia and neighboring countries in Southeast Asia, compromising the efficacy of first-line antimalarial combinations. Dihydroartemisinin + piperaquine (PPQ) treatment failure rates have risen to as high as 50% in some areas in this region. For PPQ, resistance is driven primarily by a series of mutant alleles of the P. falciparum chloroquine resistance transporter (PfCRT). PPQ resistance was reported in China three decades earlier, but the molecular driver remained unknown. Herein, we identify a PPQ-resistant pfcrt allele (China C) from Yunnan Province, China, whose genotypic lineage is distinct from the PPQ-resistant pfcrt alleles currently observed in Cambodia. Combining gene editing and competitive growth assays, we report that PfCRT China C confers moderate PPQ resistance while re-sensitizing parasites to chloroquine (CQ) and incurring a fitness cost that manifests as a reduced rate of parasite growth. PPQ transport assays using purified PfCRT isoforms, combined with molecular dynamics simulations, highlight differences in drug transport kinetics and in this transporter’s central cavity conformation between China C and the current Southeast Asian PPQ-resistant isoforms. We also report a novel computational model that incorporates empirically determined fitness landscapes at varying drug concentrations, combined with antimalarial susceptibility profiles, mutation rates, and drug pharmacokinetics. Our simulations with PPQ-resistant or -sensitive parasite lines predict that a three-day regimen of PPQ combined with CQ can effectively clear infections and prevent the evolution of PfCRT variants. This work suggests that including CQ in combination therapies could be effective in suppressing the evolution of PfCRT-mediated multidrug resistance in regions where PPQ has lost efficacy.

The recent emergence of Plasmodium falciparum parasite resistance to the antimalarial drug piperaquine (PPQ) has contributed to frequent treatment failures across Southeast Asia, originating in Cambodia. Here, we show that earlier reports of PPQ resistance in Yunnan Province, China could be explained by the unique China C variant of the P. falciparum chloroquine resistance transporter PfCRT. Gene-edited parasites show a loss of fitness and parasite resensitization to the chemically related former first-line antimalarial chloroquine, while acquiring PPQ resistance via drug efflux. Molecular features of drug resistance were examined using biochemical assays to measure mutant PfCRT-mediated drug transport and molecular dynamics simulations with the recently solved PfCRT structure to assess changes in the central drug-binding cavity. We also describe a new computational model that incorporates parasite mutation rates, fitness costs, antimalarial susceptibilities, and drug pharmacological profiles to predict how infections with parasite strains expressing distinct PfCRT variants can evolve and be selected in response to different drug pressures and regimens. Simulations predict that a three-day regimen of PPQ plus chloroquine would be fully effective at preventing recrudescence of drug-resistant infections.

Genetic surveillance for monitoring the impact of drug use on Plasmodium falciparum populations

The use of antimalarial drugs is an effective strategy in the fight against malaria. However, selection of drug resistant parasites is a constant threat to the continued use of this approach. Antimalarial drugs are used not only to treat infections but also as part of population-level strategies to reduce malaria transmission toward elimination. While there is strong evidence that the ongoing use of antimalarial drugs increases the risk of the emergence and spread of drug-resistant parasites, it is less clear how population-level use of drug-based interventions like seasonal malaria chemoprevention (SMC) or mass drug administration (MDA) may contribute to drug resistance or loss of drug efficacy. Critical to sustained use of drug-based strategies for reducing the burden of malaria is the surveillance of population-level signals related to transmission reduction and resistance selection. Here we focus on Plasmodium falciparum and discuss the genetic signatures of a parasite population that are correlated with changes in transmission and related to drug pressure and resistance as a result of drug use. We review the evidence for MDA and SMC contributing to malaria burden reduction and drug resistance selection and examine the use and impact of these interventions in Senegal. Throughout we consider best strategies for ongoing surveillance of both population and resistance signals in the context of different parasite population parameters. Finally, we propose a roadmap for ongoing surveillance during population-level drug-based interventions to reduce the global malaria burden.

Fitness of sulfadoxine-resistant Plasmodium berghei harboring a single mutation in dihydropteroate synthase (DHPS)

Genetic changes conferring drug resistance are generally believed to impose fitness costs to pathogens in the absence of the drug. However, the fitness of resistant parasites against sulfadoxine/pyrimethamine has been inconclusive in Plasmodium falciparum. This is because resistance is conferred by the complex combination of mutations in dihydropteroate synthase (dhps) and dihydrofolate reductase (dhfr), which makes it difficult to separately assess the extent and magnitude of the costs imposed by mutations in dhps and dhfr. To assess the fitness costs imposed by sulfadoxine resistance alone, we generated a transgenic rodent malaria parasite, P. berghei clone harboring an A394G mutation in dhps (PbDHPS-A394G), corresponding to the causative mutation for sulfadoxine resistance in P. falciparum (PfDHPS-A437G). A four-day suppressive test confirmed that the PbDHPS-A394G clone was resistant to sulfadoxine. PbDHPS-A394G and wild-type clones showed similar growth rates and gametocyte production. This observation was confirmed in competitive experiments in which PbDHPS-A394G and wild-type clones were co-infected into mice to directly assess the survival competition between them. In the mosquitoes, there were no significant differences in oocyst production between PbDHPS-A394G and wild-type. These results indicate that the PbDHPS-A394G mutation alters the parasites to sulfadoxine resistance but may not impose fitness disadvantages during the blood stages in mice and oocyst formation in mosquitoes. These results partly explain the persistence of the PfDHPS-A437G mutant in the natural parasite populations.

Decreased Susceptibility to Dihydrofolate Reductase Inhibitors Associated With Genetic Polymorphisms in Ugandan Plasmodium falciparum Isolates

BACKGROUND

The Plasmodium falciparum dihydrofolate reductase (PfDHFR) inhibitors pyrimethamine and cycloguanil (the active metabolite of proguanil) have important roles in malaria chemoprevention, but drug resistance challenges their efficacies. A new compound, P218, was designed to overcome resistance, but drug-susceptibility data for P falciparum field isolates are limited.

METHODS

We studied ex vivo PfDHFR inhibitor susceptibilities of 559 isolates from Tororo and Busia districts, Uganda, from 2016 to 2020, sequenced 383 isolates, and assessed associations between genotypes and drug-susceptibility phenotypes.

RESULTS

Median half-maximal inhibitory concentrations (IC50s) were 42 100 nM for pyrimethamine, 1200 nM for cycloguanil, 13000 nM for proguanil, and 0.6 nM for P218. Among sequenced isolates, 3 PfDHFR mutations, 51I (100%), 59R (93.7%), and 108N (100%), were very common, as previously seen in Uganda, and another mutation, 164L (12.8%), had moderate prevalence. Increasing numbers of mutations were associated with decreasing susceptibility to pyrimethamine, cycloguanil, and P218, but not proguanil, which does not act directly against PfDHFR. Differences in P218 susceptibilities were modest, with median IC50s of 1.4 nM for parasites with mixed genotype at position 164 and 5.7 nM for pure quadruple mutant (51I/59R/108N/164L) parasites.

CONCLUSIONS

Resistance-mediating PfDHFR mutations were common in Ugandan isolates, but P218 retained excellent activity against mutant parasites.

The adaptive landscape of a metallo-enzyme is shaped by environment-dependent epistasis

Enzymes can evolve new catalytic activity when environmental changes present them with novel substrates. Despite this seemingly straightforward relationship, factors other than the direct catalytic target can also impact adaptation. Here, we characterize the catalytic activity of a recently evolved bacterial methyl-parathion hydrolase for all possible combinations of the five functionally relevant mutations under eight different laboratory conditions (in which an alternative divalent metal is supplemented). The resultant adaptive landscapes across this historical evolutionary transition vary in terms of both the number of “fitness peaks” as well as the genotype(s) at which they are found as a result of genotype-by-environment interactions and environment-dependent epistasis. This suggests that adaptive landscapes may be fluid and molecular adaptation is highly contingent not only on obvious factors (such as catalytic targets), but also on less obvious secondary environmental factors that can direct it towards distinct outcomes.

The metaphor of an adaptive landscape is presented quantitatively by looking at molecular adaptations and their catalytic consequences in a recently evolved bacterial enzyme. The study identifies both genotype-by-environment interactions and environment-dependent epistasis as factors that can alter the fitness of functional mutations.

Relevance of Higher-Order Epistasis in Drug Resistance

We studied five chemically distinct but related 1,3,5-triazine antifolates with regard to their effects on growth of a set of mutants in dihydrofolate reductase. The mutants comprise a combinatorially complete data set of all 16 possible combinations of four amino acid replacements associated with resistance to pyrimethamine in the malaria parasite Plasmodium falciparum. Pyrimethamine was a mainstay medication for malaria for many years, and it is still in use in intermittent treatment during pregnancy or as a partner drug in artemisinin combination therapy. Our goal was to investigate the extent to which the alleles yield similar adaptive topographies and patterns of epistasis across chemically related drugs. We find that the adaptive topographies are indeed similar with the same or closely related alleles being fixed in computer simulations of stepwise evolution. For all but one of the drugs the topography features at least one suboptimal fitness peak. Our data are consistent with earlier results indicating that third order and higher epistatic interactions appear to contribute only modestly to the overall adaptive topography, and they are largely conserved. In regard to drug development, our data suggest that higher-order interactions are likely to be of little value as an advisory tool in the choice of lead compounds.

Geographical spread and structural basis of sulfadoxine-pyrimethamine drug-resistant malaria parasites

The global spread of sulfadoxine (Sdx, S) and pyrimethamine (Pyr, P) resistance is attributed to increasing number of mutations in DHPS and DHFR enzymes encoded by malaria parasites. The association between drug resistance mutations and SP efficacy is complex. Here we provide an overview of the geographical spread of SP resistance mutations in Plasmodium falciparum (Pf) and Plasmodium vivax (Pv) encoded dhps and dhfr genes. In addition, we have collated the mutation data and mapped it on to the three-dimensional structures of DHPS and DHFR which have become available. Data from genomic databases and 286 studies were collated to provide a comprehensive landscape of mutational data from 2005 to 2019. Our analyses show that the Pyr-resistant double mutations are widespread in Pf/PvDHFR (P. falciparum ∼61% in Asia and the Middle East, and in the Indian sub-continent; in P. vivax ∼33% globally) with triple mutations prevailing in Africa (∼66%) and South America (∼33%). For PfDHPS, triple mutations dominate South America (∼44%), Asia and the Middle East (∼34%) and the Indian sub-continent (∼27%), while single mutations are widespread in Africa (∼45%). Contrary to the status for P. falciparum, Sdx-resistant single point mutations in PvDHPS dominate globally. Alarmingly, highly resistant quintuple and sextuple mutations are rising in Africa (PfDHFR-DHPS) and Asia (Pf/PvDHFR-DHPS). Structural analyses of DHFR and DHPS proteins in complexes with substrates/drugs have revealed that resistance mutations map proximal to Sdx and Pyr binding sites. Thus new studies can focus on discovery of novel inhibitors that target the non-substrate binding grooves in these two validated malaria parasite drug targets.

From genotypes to organisms: State-of-the-art and perspectives of a cornerstone in evolutionary dynamics

Understanding how genotypes map onto phenotypes, fitness, and eventually organisms is arguably the next major missing piece in a fully predictive theory of evolution. We refer to this generally as the problem of the genotype-phenotype map. Though we are still far from achieving a complete picture of these relationships, our current understanding of simpler questions, such as the structure induced in the space of genotypes by sequences mapped to molecular structures, has revealed important facts that deeply affect the dynamical description of evolutionary processes. Empirical evidence supporting the fundamental relevance of features such as phenotypic bias is mounting as well, while the synthesis of conceptual and experimental progress leads to questioning current assumptions on the nature of evolutionary dynamics-cancer progression models or synthetic biology approaches being notable examples. This work delves with a critical and constructive attitude into our current knowledge of how genotypes map onto molecular phenotypes and organismal functions, and discusses theoretical and empirical avenues to broaden and improve this comprehension. As a final goal, this community should aim at deriving an updated picture of evolutionary processes soundly relying on the structural properties of genotype spaces, as revealed by modern techniques of molecular and functional analysis.

Temporal evolution of sulfadoxine-pyrimethamine resistance genotypes and genetic diversity in response to a decade of increased interventions against Plasmodium falciparum in northern Ghana

Background

Anti-malarial drug resistance remains a key concern for the global fight against malaria. In Ghana sulfadoxine-pyrimethamine (SP) is used for intermittent preventive treatment of malaria in pregnancy and combined with amodiaquine for Seasonal Malaria Chemoprevention (SMC) during the high malaria season. Thus, surveillance of molecular markers of SP resistance is important to guide decision-making for these interventions in Ghana.

Methods

A total of 4469 samples from uncomplicated malaria patients collected from 2009 to 2018 was submitted to the Wellcome Trust Sanger Institute, UK for DNA sequencing using MiSeq. Genotypes were successfully translated into haplotypes in 2694 and 846 mono infections respectively for pfdhfr and pfdhps genes and the combined pfhdfr/pfdhps genes across all years.

Results

At the pfdhfr locus, a consistently high (> 60%) prevalence of parasites carrying triple mutants (IRNI) were detected from 2009 to 2018. Two double mutant haplotypes (NRNI and ICNI) were found, with haplotype NRNI having a much higher prevalence (average 13.8%) than ICNI (average 3.2%) across all years. Six pfdhps haplotypes were detected. Of these, prevalence of five fluctuated in a downward trend over time from 2009 to 2018, except a pfdhps double mutant (AGKAA), which increased consistently from 2.5% in 2009 to 78.2% in 2018. Across both genes, pfdhfr/pfdhps combined triple (NRNI + AAKAA) mutants were only detected in 2009, 2014, 2015 and 2018, prevalence of which fluctuated between 3.5 and 5.5%. The combined quadruple (IRNI + AAKAA) genotype increased in prevalence from 19.3% in 2009 to 87.5% in 2011 before fluctuating downwards to 19.6% in 2018 with an average prevalence of 37.4% within the nine years. Prevalence of parasites carrying the quintuple (IRNI + AGKAA or SGEAA) mutant haplotypes, which are highly refractory to SP increased over time from 14.0% in 2009 to 89.0% in 2016 before decreasing to 78.9 and 76.6% in 2017 and 2018 respectively. Though quintuple mutants are rising in prevalence in both malaria seasons, together these combined genotypes vary significantly within season but not between seasons.

Conclusions

Despite high prevalence of pfdhfr triple mutants and combined pfdhfr/pfdhps quadruple and quintuple mutants in this setting SP may still be efficacious. These findings are significant as they highlight the need to continuously monitor SP resistance, particularly using deep targeted sequencing to ascertain changing resistance patterns.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12936-021-03693-3.

Asymptomatic recrudescence after artemether-lumefantrine treatment for uncomplicated falciparum malaria: a systematic review and meta-analysis

Background

In clinical trials of therapy for uncomplicated Plasmodium falciparum, there are usually some patients who fail treatment even in the absence of drug resistance. Treatment failures, which can be due to recrudescence or re-infection, are categorized as ‘clinical’ or ‘parasitological’ failures, the former indicating that symptoms have returned. Asymptomatic recrudescence has public health implications for continued malaria transmission and may be important for the spread of drug-resistant malaria. As the number of recrudescences in an individual trial is often low, it is difficult to assess how commonplace asymptomatic recrudescence is, and with what factors it is associated.

Methods

A systematic literature review was carried out on clinical trials of artemether-lumefantrine (AL) in patients seeking treatment for symptomatic uncomplicated falciparum malaria, and information on symptoms during treatment failure was recorded. Only treatment failures examined by polymerase chain reaction (PCR) were included, so as to exclude re-infections. A multivariable Bayesian regression model was used to explore factors potentially explaining the proportion of recrudescent infections which are symptomatic across the trials included in the study.

Results

Across 60 published trials, including 9137 malaria patients, 37.8% [95% CIs (26.6–49.4%)] of recrudescences were symptomatic. A positive association was found between transmission intensity and the observed proportion of recrudescences that were asymptomatic. Symptoms were more likely to return in trials that only enrolled children aged < 72 months [odds ratio = 1.62, 95% CIs (1.01, 2.59)]. However, 84 studies had to be excluded from this analysis, as recrudescences were not specified as symptomatic or asymptomatic.

Conclusions

AL, the most widely used treatment for uncomplicated P. falciparum in Africa, remains a highly efficacious drug in most endemic countries. However in the small proportion of patients where AL does not clear parasitaemia, the majority of patients do not develop symptoms again and thus would be unlikely to seek another course of treatment. This continued asymptomatic parasite carriage in patients who have been treated may have implications for drug-resistant parasites being introduced into high-transmissions settings.

Increased prevalence of pfdhfr and pfdhps mutations associated with sulfadoxine-pyrimethamine resistance in Plasmodium falciparum isolates from Jazan Region, Southwestern Saudi Arabia: important implications for malaria treatment policy

Background

Despite significant progress in eliminating malaria from the Kingdom of Saudi Arabia, the disease is still endemic in the southwestern region of the country. Artesunate plus sulfadoxine–pyrimethamine (AS + SP) has been used in Saudi Arabia since 2007 as a first-line treatment for uncomplicated Plasmodium falciparum malaria. This study aimed to investigate the prevalence of mutations associated with resistance to artemisinin and sulfadoxine–pyrimethamine (SP) resistance in P. falciparum parasites circulating in Jazan region, southwestern Saudi Arabia.

Methods

A total of 151 P. falciparum isolates were collected between April 2018 and March 2019 from 12 of the governorates in Jazan region. Genomic DNA was extracted from dried blood spots and amplified using nested PCR. Polymorphisms in the propeller domain of the P. falciparum k13 (pfkelch13) gene and point mutations in the P. falciparum dihydrofolate reductase (pfdhfr) and dihydropteroate synthase (pfdhps) genes were identified by sequencing.

Results

No mutations in the pfkelch13 propeller domain were found in any of the 151 isolates. However, point mutations in the pfdhfr and pfdhps genes were detected in 90.7% (137/151) of the isolates. The pfdhfr double mutations N51I + S108N (i.e. ACICNI haplotype) and triple mutations N51I + C59R + S108N (i.e. ACIRNI haplotype) were detected in 47% and 37.8% of the isolates, respectively. Moreover, the pfdhps single mutation at codon A437G and double mutations A437G + K540E (i.e. SGEAAI haplotype) were observed in 4.6% and 51.7% of the isolates, respectively. Interestingly, 23.8%, 25.1 and 12.6% of the isolates had quintuple, quadruple and triple mutated combined pfdhfr–pfdhps genotypes, respectively. Furthermore, significant associations were found between the prevalence of mutant haplotypes and the age, gender and nationality of the patients (P < 0.05).

Conclusion

This study revealed a high prevalence of point mutations in the pfdhfr and pfdhps genes of P. falciparum isolates from Jazan region, with quintuple and quadruple mutant pfdhfr–pfdhps genotypes reported for the first time in Saudi Arabia and the Arabian Peninsula. Despite the absence of the pfkelch13 mutation in the isolates examined, the pfdhfr and pfdhps mutations undermine the efficacy of SP partner drug, thereby threatening the main falciparum malaria treatment policy in Saudi Arabia, i.e. the use of AS + SP. Therefore, the continuous molecular and in-vivo monitoring of ACT efficacy in Jazan region is highly recommended.

Changes in the frequencies of Plasmodium falciparum dhps and dhfr drug-resistant mutations in children from Western Kenya from 2005 to 2018: the rise of Pfdhps S436H

BACKGROUND

Sulfadoxine-pyrimethamine (SP) is the only anti-malarial drug formulation approved for intermittent preventive treatment in pregnancy (IPTp). However, mutations in the Plasmodium falciparum dhfr (Pfdhfr) and dhps (Pfdhps) genes confer resistance to pyrimethamine and sulfadoxine, respectively. Here, the frequencies of SP resistance-associated mutations from 2005 to 2018 were compared in samples from Kenyan children with malaria residing in a holoendemic transmission region.

METHODS

Partial sequences of the Pfdhfr and Pfdhps genes were amplified and sequenced from samples collected in 2005 (n = 81), 2010 (n = 95), 2017 (n = 43), and 2018 (n = 55). The frequency of known mutations conferring resistance to pyrimethamine and sulfadoxine were estimated and compared. Since artemisinin-based combination therapy (ACT) is the current first-line treatment for malaria, the presence of mutations in the propeller domain of P. falciparum kelch13 gene (Pfk13) linked to ACT-delayed parasite clearance was studied in the 2017/18 samples.

RESULTS

Among other changes, the point mutation of Pfdhps S436H increased in frequency from undetectable in 2005 to 28% in 2017/18. Triple Pfdhfr mutant allele (CIRNI) increased in frequency from 84% in 2005 to 95% in 2017/18, while the frequency of Pfdhfr double mutant alleles declined (allele CICNI from 29% in 2005 to 6% in 2017/18, and CNRNI from 9% in 2005 to undetectable in 2010 and 2017/18). Thus, a multilocus Pfdhfr/Pfdhps genotype with six mutations (HGEAA/CIRNI), including Pfdhps S436H, increased in frequency from 2010 to 2017/18. Although none of the mutations associated with ACT-delayed parasite clearance was observed, the Pfk13 mutation A578S, the most widespread Pfk13 SNP found in Africa, was detected in low frequency (2.04%).

CONCLUSIONS

There were changes in SP resistance mutant allele frequencies, including an increase in the Pfdhps S436H. Although these patterns seem consistent with directional selection due to drug pressure, there is a lack of information to determine the actual cause of such changes. These results suggest incorporating molecular surveillance of Pfdhfr/Pfdhps mutations in the context of SP efficacy studies for intermittent preventive treatment in pregnancy (IPTp).

Inferring a complete genotype-phenotype map from a small number of measured phenotypes

Understanding evolution requires detailed knowledge of genotype-phenotype maps; however, it can be a herculean task to measure every phenotype in a combinatorial map. We have developed a computational strategy to predict the missing phenotypes from an incomplete, combinatorial genotype-phenotype map. As a test case, we used an incomplete genotype-phenotype dataset previously generated for the malaria parasite’s ‘chloroquine resistance transporter’ (PfCRT). Wild-type PfCRT (PfCRT^3D7) lacks significant chloroquine (CQ) transport activity, but the introduction of the eight mutations present in the ‘Dd2’ isoform of PfCRT (PfCRT^Dd2) enables the protein to transport CQ away from its site of antimalarial action. This gain of a transport function imparts CQ resistance to the parasite. A combinatorial map between PfCRT^3D7 and PfCRT^Dd2 consists of 256 genotypes, of which only 52 have had their CQ transport activities measured through expression in the Xenopus laevis oocyte. We trained a statistical model with these 52 measurements to infer the CQ transport activity for the remaining 204 combinatorial genotypes between PfCRT^3D7 and PfCRT^Dd2. Our best-performing model incorporated a binary classifier, a nonlinear scale, and additive effects for each mutation. The addition of specific pairwise- and high-order-epistatic coefficients decreased the predictive power of the model. We evaluated our predictions by experimentally measuring the CQ transport activities of 24 additional PfCRT genotypes. The R² value between our predicted and newly-measured phenotypes was 0.90. We then used the model to probe the accessibility of evolutionary trajectories through the map. Approximately 1% of the possible trajectories between PfCRT^3D7 and PfCRT^Dd2 are accessible; however, none of the trajectories entailed eight successive increases in CQ transport activity. These results demonstrate that phenotypes can be inferred with known uncertainty from a partial genotype-phenotype dataset. We also validated our approach against a collection of previously published genotype-phenotype maps. The model therefore appears general and should be applicable to a large number of genotype-phenotype maps.

Biological macromolecules are built from chains of building blocks. The function of a macromolecule depends on the specific chemical properties of the building blocks that make it up. Macromolecules evolve through mutations that swap one building block for another. Understanding how biomolecules work and evolve therefore requires knowledge of the effects of mutations. The effects of mutations can be measured experimentally; however, because there are a vast number of possible combinations of mutations, it is often difficult to make enough measurements to understand biomolecular function and evolution. In this paper, we describe a simple method to predict the effects of mutations on biomolecules from a small number of measurements. This method works by appropriately averaging the effects of mutations seen in different contexts. We test the method by predicting the effects of mutations on a PfCRT—a macromolecule from the malarial parasite that confers drug resistance. We find that our method is fast and effective. Using a small number of measurements, we were able to gain insight into the evolutionary steps by which this macromolecule conferred drug resistance. To make this method accessible to other researchers, we have released it as an open-source software package: https://gpseer.readthedocs.io.

Mutation bias interacts with composition bias to influence adaptive evolution

Mutation is a biased stochastic process, with some types of mutations occurring more frequently than others. Previous work has used synthetic genotype-phenotype landscapes to study how such mutation bias affects adaptive evolution. Here, we consider 746 empirical genotype-phenotype landscapes, each of which describes the binding affinity of target DNA sequences to a transcription factor, to study the influence of mutation bias on adaptive evolution of increased binding affinity. By using empirical genotype-phenotype landscapes, we need to make only few assumptions about landscape topography and about the DNA sequences that each landscape contains. The latter is particularly important because the set of sequences that a landscape contains determines the types of mutations that can occur along a mutational path to an adaptive peak. That is, landscapes can exhibit a composition bias—a statistical enrichment of a particular type of mutation relative to a null expectation, throughout an entire landscape or along particular mutational paths—that is independent of any bias in the mutation process. Our results reveal the way in which composition bias interacts with biases in the mutation process under different population genetic conditions, and how such interaction impacts fundamental properties of adaptive evolution, such as its predictability, as well as the evolution of genetic diversity and mutational robustness.

Mutation is often depicted as a random process due its unpredictable nature. However, such randomness does not imply uniformly distributed outcomes, because some DNA sequence changes happen more frequently than others. Mutation bias can be an orienting factor in adaptive evolution, influencing the mutational trajectories populations follow toward higher-fitness genotypes. Because these trajectories are typically just a small subset of all possible mutational trajectories, they can exhibit composition bias—an enrichment of a particular kind of DNA sequence change, such as transition or transversion mutations. Here, we use empirical data from eukaryotic transcriptional regulation to study how mutation bias and composition bias interact to influence adaptive evolution.

A mechanistic view of enzyme evolution

New enzyme functions often evolve through the recruitment and optimization of latent promiscuous activities. How do mutations alter the molecular architecture of enzymes to enhance their activities? Can we infer general mechanisms that are common to most enzymes, or does each enzyme require a unique optimization process? The ability to predict the location and type of mutations necessary to enhance an enzyme's activity is critical to protein engineering and rational design. In this review, via the detailed examination of recent studies that have shed new light on the molecular changes underlying the optimization of enzyme function, we provide a mechanistic perspective of enzyme evolution. We first present a global survey of the prevalence of activity-enhancing mutations and their distribution within protein structures. We then delve into the molecular solutions that mediate functional optimization, specifically highlighting several common mechanisms that have been observed across multiple examples. As distinct protein sequences encounter different evolutionary bottlenecks, different mechanisms are likely to emerge along evolutionary trajectories toward improved function. Identifying the specific mechanism(s) that need to be improved upon, and tailoring our engineering efforts to each sequence, may considerably improve our chances to succeed in generating highly efficient catalysts in the future.

Allostery and Epistasis: Emergent Properties of Anisotropic Networks

Understanding the underlying mechanisms behind protein allostery and non-additivity of substitution outcomes (i.e., epistasis) is critical when attempting to predict the functional impact of mutations, particularly at non-conserved sites. In an effort to model these two biological properties, we extend the framework of our metric to calculate dynamic coupling between residues, the Dynamic Coupling Index (DCI) to two new metrics: (i) EpiScore, which quantifies the difference between the residue fluctuation response of a functional site when two other positions are perturbed with random Brownian kicks simultaneously versus individually to capture the degree of cooperativity of these two other positions in modulating the dynamics of the functional site and (ii) DCI_asym, which measures the degree of asymmetry between the residue fluctuation response of two sites when one or the other is perturbed with a random force. Applied to four independent systems, we successfully show that EpiScore and DCI_asym can capture important biophysical properties in dual mutant substitution outcomes. We propose that allosteric regulation and the mechanisms underlying non-additive amino acid substitution outcomes (i.e., epistasis) can be understood as emergent properties of an anisotropic network of interactions where the inclusion of the full network of interactions is critical for accurate modeling. Consequently, mutations which drive towards a new function may require a fine balance between functional site asymmetry and strength of dynamic coupling with the functional sites. These two tools will provide mechanistic insight into both understanding and predicting the outcome of dual mutations.

Predictable properties of fitness landscapes induced by adaptational tradeoffs

Fitness effects of mutations depend on environmental parameters. For example, mutations that increase fitness of bacteria at high antibiotic concentration often decrease fitness in the absence of antibiotic, exemplifying a tradeoff between adaptation to environmental extremes. We develop a mathematical model for fitness landscapes generated by such tradeoffs, based on experiments that determine the antibiotic dose-response curves of Escherichia coli strains, and previous observations on antibiotic resistance mutations. Our model generates a succession of landscapes with predictable properties as antibiotic concentration is varied. The landscape is nearly smooth at low and high concentrations, but the tradeoff induces a high ruggedness at intermediate antibiotic concentrations. Despite this high ruggedness, however, all the fitness maxima in the landscapes are evolutionarily accessible from the wild type. This implies that selection for antibiotic resistance in multiple mutational steps is relatively facile despite the complexity of the underlying landscape.

Antimalarial Drug Resistance Profiling of Plasmodium falciparum Infections in Ghana Using Molecular Inversion Probes and Next-Generation Sequencing

A key drawback to monitoring the emergence and spread of antimalarial drug resistance in sub-Saharan Africa is early detection and containment. Next-generation sequencing methods offer the resolution, sensitivity, and scale required to fill this gap by surveilling for molecular markers of drug resistance. We performed targeted sequencing using molecular inversion probes to interrogate five Plasmodium falciparum genes (pfcrt, pfmdr1, pfdhps, pfdhfr, and pfk13) implicated in chloroquine, sulfadoxine-pyrimethamine (SP), and artemisinin resistance in two sites in Ghana. A total of 803 dried blood spots from children aged between 6 months and 14 years presenting with uncomplicated P. falciparum malaria at the Begoro District Hospital in Begoro and the Ewim Polyclinic in Cape Coast, Ghana, from 2014 to 2017 were prepared on filter paper. Thirteen years after the removal of drug pressure, chloroquine-sensitive parasite strains with pfcrt K76 have increased nearly to fixation in Begoro, in the forest area (prevalence = 95%), but at a lower rate in Cape Coast, in the coastal region (prevalence = 71%, Z = -3.5, P < 0.001). In addition, pfmdr1 184F-bearing parasites are under strong selection. The pfdhfr/pfdhps quadruple genotype ( IRNG K), associated with SP resistance, is near saturation. Our study identified at a 2 to 10% prevalence pfdhps 581G, which is a sulfadoxine resistance marker that correlates with the failure of SP prophylaxis in pregnancy and which has not been observed in Ghana. The differences in the reexpansion of chloroquine-sensitive strains observed at the two study sites, the stronger SP resistance, and the high prevalence of pfmdr1 184F should be further monitored to inform malaria control strategies in Ghana.

An epigrammatic status of the 'azole'-based antimalarial drugs

The development of multidrug resistance in the malarial parasite has sabotaged majority of the eradication efforts by restraining the inhibition profile of first line as well as second line antimalarial drugs, thus necessitating the development of novel pharmaceutics constructed on appropriate scaffolds with superior potency against the drug-resistant and drug-susceptible Plasmodium parasite. Over the past decades, the infectious malarial parasite has developed resistance against most of the contemporary therapeutics, thus necessitating the rational development of novel approaches principally focused on MDR malaria. This review presents an epigrammatic collation of the epidemiology and the contemporary antimalarial therapeutics based on the 'azole' motif.

Model genotype-phenotype mappings and the algorithmic structure of evolution

Cancers are complex dynamic systems that undergo evolution and selection. Personalized medicine approaches in the clinic increasingly rely on predictions of tumour response to one or more therapies; these predictions are complicated by the inevitable evolution of the tumour. Despite enormous amounts of data on the mutational status of cancers and numerous therapies developed in recent decades to target these mutations, many of these treatments fail after a time due to the development of resistance in the tumour. The emergence of these resistant phenotypes is not easily predicted from genomic data, since the relationship between genotypes and phenotypes, termed the genotype-phenotype (GP) mapping, is neither injective nor functional. We present a review of models of this mapping within a generalized evolutionary framework that takes into account the relation between genotype, phenotype, environment and fitness. Different modelling approaches are described and compared, and many evolutionary results are shown to be conserved across studies despite using different underlying model systems. In addition, several areas for future work that remain understudied are identified, including plasticity and bet-hedging. The GP-mapping provides a pathway for understanding the potential routes of evolution taken by cancers, which will be necessary knowledge for improving personalized therapies.

AcrAB-TolC efflux pump system plays a role in carbapenem non-susceptibility in Escherichia coli

Background

Efflux pump mediated antibiotic resistance is an unnoticed and undetected mechanism in clinical microbiology laboratory. RND efflux systems are known for aminoglycoside and tetracycline resistance whereas their role in carbapenem non-susceptibility is not established. The study was undertaken to investigate the role of efflux pump in providing resistance against carbapenems and their response against concentration gradient carbapenem stress on the transcriptional level of the AcrAB gene in the clinical isolates of Escherichia coli from a tertiary referral hospital of Northeast India.

Results

Out of 298 non-susceptible Escherichia coli isolates 98 isolates were found to have efflux pump mediated carbapenem non-susceptibility. Among them thirty-five were non carbapenemase producers and their expressional levels were verified using qRT-PCR under concentration gradient carbapenem stress. In this study, a strong correlation between ertapenem resistance and AcrA overexpression was observed which has not been reported previously. Further, it was observed that imipenem stress increased AcrB expression in Escherichia coli which holds the novelty of this study. Additionally, the transcription of AcrR was insistently increased which is much higher than the transcriptional level of AcrA under concentration gradient carbapenem stress condition.

Conclusion

The study established that AcrAB pump is a relevant antibiotic resistance determinant in bacterial pathogen, has an important role in developing resistance against carbapenem group of antibiotics.

Electronic supplementary material

The online version of this article (10.1186/s12866-019-1589-1) contains supplementary material, which is available to authorized users.

John ME. How to Investigate the Origins of Novelty: Insights Gained from Genetic, Behavioral, and Fitness Perspectives

Biologists are drawn to the most extraordinary adaptations in the natural world, often referred to as evolutionary novelties, yet rarely do we understand the microevolutionary context underlying the origins of novel traits, behaviors, or ecological niches. Here we discuss insights gained into the origins of novelty from a research program spanning biological levels of organization from genotype to fitness in Caribbean pupfishes. We focus on a case study of the origins of novel trophic specialists on San Salvador Island, Bahamas and place this radiation in the context of other rapid radiations. We highlight questions that can be addressed about the origins of novelty at different biological levels, such as measuring the isolation of novel phenotypes on the fitness landscape, locating the spatial and temporal origins of adaptive variation contributing to novelty, detecting dysfunctional gene regulation due to adaptive divergence, and connecting behaviors with novel traits. Evolutionary novelties are rare, almost by definition, and we conclude that integrative case studies can provide insights into this rarity relative to the dynamics of adaptation to more common ecological niches and repeated parallel speciation, such as the relative isolation of novel phenotypes on fitness landscapes and the transient availability of ecological, genetic, and behavioral opportunities.

Lexical Landscapes as large in silico data for examining advanced properties of fitness landscapes

In silico approaches have served a central role in the development of evolutionary theory for generations. This especially applies to the concept of the fitness landscape, one of the most important abstractions in evolutionary genetics, and one which has benefited from the presence of large empirical data sets only in the last decade or so. In this study, we propose a method that allows us to generate enormous data sets that walk the line between in silico and empirical: word usage frequencies as catalogued by the Google ngram corpora. These data can be codified or analogized in terms of a multidimensional empirical fitness landscape towards the examination of advanced concepts-adaptive landscape by environment interactions, clonal competition, higher-order epistasis and countless others. We argue that the greater Lexical Landscapes approach can serve as a platform that offers an astronomical number of fitness landscapes for exploration (at least) or theoretical formalism (potentially) in evolutionary biology.

High-Order Epistasis in Catalytic Power of Dihydrofolate Reductase Gives Rise to a Rugged Fitness Landscape in the Presence of Trimethoprim Selection

Evolutionary fitness landscapes of several antibiotic target proteins have been comprehensively mapped showing strong high-order epistasis between mutations, but understanding these effects at the biochemical and structural levels remained open. Here, we carried out an extensive experimental and computational study to quantitatively understand the evolutionary dynamics of Escherichia coli dihydrofolate reductase (DHFR) enzyme in the presence of trimethoprim-induced selection. To facilitate this, we developed a new in vitro assay for rapidly characterizing DHFR steady-state kinetics. Biochemical and structural characterization of resistance-conferring mutations targeting a total of ten residues spanning the substrate binding pocket of DHFR revealed distinct changes in the catalytic efficiencies of mutated DHFR enzymes. Next, we measured biochemical parameters (Km, Ki, and kcat) for a mutant library carrying all possible combinations of six resistance-conferring DHFR mutations and quantified epistatic interactions between them. We found that the high-order epistasis in catalytic power of DHFR (kcat and Km) creates a rugged fitness landscape under trimethoprim selection. Taken together, our data provide a concrete illustration of how epistatic coupling at the level of biochemical parameters can give rise to complex fitness landscapes, and suggest new strategies for developing mutant specific inhibitors.

The role of mutation bias in adaptive molecular evolution: insights from convergent changes in protein function

An underexplored question in evolutionary genetics concerns the extent to which mutational bias in the production of genetic variation influences outcomes and pathways of adaptive molecular evolution. In the genomes of at least some vertebrate taxa, an important form of mutation bias involves changes at CpG dinucleotides: if the DNA nucleotide cytosine (C) is immediately 5' to guanine (G) on the same coding strand, then-depending on methylation status-point mutations at both sites occur at an elevated rate relative to mutations at non-CpG sites. Here, we examine experimental data from case studies in which it has been possible to identify the causative substitutions that are responsible for adaptive changes in the functional properties of vertebrate haemoglobin (Hb). Specifically, we examine the molecular basis of convergent increases in Hb-O₂ affinity in high-altitude birds. Using a dataset of experimentally verified, affinity-enhancing mutations in the Hbs of highland avian taxa, we tested whether causative changes are enriched for mutations at CpG dinucleotides relative to the frequency of CpG mutations among all possible missense mutations. The tests revealed that a disproportionate number of causative amino acid replacements were attributable to CpG mutations, suggesting that mutation bias can influence outcomes of molecular adaptation. This article is part of the theme issue 'Convergent evolution in the genomics era: new insights and directions'.

Noise-precision tradeoff in predicting combinations of mutations and drugs

Many biological problems involve the response to multiple perturbations. Examples include response to combinations of many drugs, and the effects of combinations of many mutations. Such problems have an exponentially large space of combinations, which makes it infeasible to cover the entire space experimentally. To overcome this problem, several formulae that predict the effect of drug combinations or fitness landscape values have been proposed. These formulae use the effects of single perturbations and pairs of perturbations to predict triplets and higher order combinations. Interestingly, different formulae perform best on different datasets. Here we use Pareto optimality theory to quantitatively explain why no formula is optimal for all datasets, due to an inherent bias-variance (noise-precision) tradeoff. We calculate the Pareto front of log-linear formulae and find that the optimal formula depends on properties of the dataset: the typical interaction strength and the experimental noise. This study provides an approach to choose a suitable prediction formula for a given dataset, in order to best overcome the combinatorial explosion problem.

Sometimes a combination of drugs works much better than each drug alone. Finding such drug cocktails is a pressing challenge in order to combat drug resistance and to improve drug effects. However, it is impossible to test all combinations of multiple drug experimentally. Therefore, researchers are looking for computational rather than experimental approaches to overcome this problem. One approach is to measure the effect of few drugs and plug it into a formula that predicts the effect of many drugs together. Existing prediction formulae typically perform best on the dataset that they were developed on, but less well on other datasets. Here we explain this observation and give a guide for the choice of an optimal prediction formula for a given dataset. The optimal formula depends on two main properties of the dataset: 1) The interaction strength between the drugs and 2) The experimental noise in the data. This study may help researchers discover effective combinations of multiple drugs and multiple perturbations in general.