Mutational Steps Research Articles

Assessment of genetic variability in captive capuchin monkeys (Primates: Cebidae)

Capuchin monkeys (genera Cebus and Sapajus) show a wide range distribution, from Honduras to Argentina. The aim of this work was to evaluate the genetic and phenotypic variability of captive specimens putatively belonging to S. cay (SCY) and S. nigritus (SNI) at their southernmost distribution limit. Forty-four individuals held in five captive centers from Argentina were analyzed based on external morphology, karyology and DNA sequences of mitochondrial control region (mtDNA-CR). Three morphotypes associated with their probable geographical origin in SCY and a single morphotype in SNI were found. For SCY we could associate each morphotype with the most frequent karyotype. SNI showed a single phenotype and a homogenous karyotype. Heterochromatin showed geographical patterns within species. A 515-bp mtDNA-CR fragment was sequenced, defining fourteen haplotypes at 59 polymorphic sites. A network constructed with our 14 haplotypes and other 77 from S. apella, S. macrocephalus, S. cay and S. nigritus from bibliography revealed some phylogeographic signals. Our SCY and SNI samples rendered four groups that differed in multiple mutational steps, with SCY being more similar to S. apella than to S. macrocephalus. Also, we identified two genetic divergent SCY groups: samples from NOA and from NEA with high mitochondrial diversity. Our results highlight the relevance of using complementary genetic tools throughout the distribution ranges of SCY and SNI for a better assessment of their diversity.

A Genetic Crow Search Algorithm for Optimization of Operation Sequencing in Process Planning

Computer-aided process planning represents the main link between computer-aided design and computer-aided manufacturing. One of the crucial tasks in computer-aided process planning is an operation sequencing problem. In order to find the optimal process plan, operation sequencing problem is formulated as an NP hard combinatorial problem. To solve this problem, a novel genetic crow search approach (GCSA) is proposed in this paper. The traditional CSA is improved by employing genetic strategies such as tournament selection, three-string crossover, shift and resource mutation. Moreover, adaptive crossover and mutation probability coefficients were introduced to improve local and global search abilities of the GCSA. Operation precedence graph is adopted to represent precedence relationships among features and vector representation is used to manipulate the data in the Matlab environment. A new nearest mechanism strategy is added to ensure that elements of machines, tools and tool approach direction (TAD) vectors are integer values. Repair strategy to handle precedence constraints is adopted after initialization and shift mutation steps. Minimization of total production cost is used as the optimization criterion to evaluate process plans. To verify the performance of the GCSA, two case studies with different dimensions are carried out and comparisons with traditional and some modern algorithms from the literature are discussed. The results show that the GCSA performs well for operation sequencing problem in computer-aided process planning.

Current genetic conservation of Chinese indigenous horses revealed with Y-chromosomal and mitochondrial DNA polymorphisms.

To investigate the genetic diversity of Chinese indigenous horses and determine the genetic status of extant horse breeds, novel Y chromosomal microsatellite markers and known Y chromosomal SNPs and mtDNA loop sequences, were employed to study the genetic diversity levels of 13 Chinese indigenous horse populations and four introduced breeds. Sixteen Y-chromosomal microsatellite markers, including seven newly identified loci, were used in the genotyping. The results showed that 4 out of the 16 loci were highly polymorphic in Chinese indigenous horse populations, in which the polymorphisms of 3 loci, ECAYP12, ECAYP13, and ECAYCAU3, were first reported in the present study. The polymorphic Y chromosomal microsatellite markers result in 19 haplotypes in the studied horses and formed 24 paternal lines when merged with the 14 Y chromosomal SNPs reported previously. The haplotypes CHT18 and SS24 harboring AMELY gene mutation were the ancestral haplotypes, and other haplotypes were derived from them by one or more mutation steps. The horse populations in mountainous and remote areas of southwestern China have the most ancient paternal lines, which suggests that ancient paternal lines preserved in local populations attributed to less human interventions. Our results also showed that the northern local breeds had higher mtDNA diversity than the southern ones in China. The frequency of haplogroup B, F, and G of mtDNA in Chinese indigenous horses has declined in recent years, and some breeds are in endangered status mainly due to small population sizes. Urgent actions should be taken to conserve the genetic diversity of the indigenous horse populations, especially the rare paternal lines. Our findings help to elucidate the genetic diversity and evolutionary history of Chinese domestic horses, which will facilitate the conservation of the indigenous horses in the future.

Improved Salp Swarm Algorithm with mutation schemes for solving global optimization and engineering problems

Salp Swarm Algorithm (SSA) is a recent metaheuristic algorithm developed from the inspiration of salps’ swarming behavior and characterized by a simple search mechanism with few handling parameters. However, in solving complex optimization problems, the SSA may suffer from the slow convergence rate and a trend of falling into sub-optimal solutions. To overcome these shortcomings, in this study, versions of the SSA by employing Gaussian, Cauchy, and levy-flight mutation schemes are proposed. The Gaussian mutation is used to enhance neighborhood-informed ability. The Cauchy mutation is used to generate large steps of mutation to increase the global search ability. The levy-flight mutation is used to increase the randomness of salps during the search. These versions are tested on 23 standard benchmark problems using statistical and convergence curves investigations, and the best-performed optimizer is compared with some other state-of-the-art algorithms. The experiments demonstrate the impact of mutation schemes, especially Gaussian mutation, in boosting the exploitation and exploration abilities.

Y chromosome analysis for common surnames in the Japanese male population.

For many years of Japan's long history, Japanese surnames have been handed down patrilineally. This study investigated relations between major surnames and Y chromosomal polymorphism among the Japanese male population. To analyze genetic phylogeny in namesakes, the Y-single nucleotide polymorphism (SNP) plus Y-short tandem repeat (STR) approach was employed. A haplogroup based on SNPs and haplotypes at 17 STR loci were typed in 567 unrelated volunteers recruited in Kanagawa, Japan. Samples covered 27 common surnames such as Satoh and Suzuki, each name having 10-55 bearers. Significant difference was found for SNP haplogroup compositions and a multidimensional scaling plot using STR haplotypes in several surname groups. By contrast, these common surnames displayed wide diversity with phylogenetic networks, suggesting that no genetic drift event has occurred in their history. In all, 22 descent clusters were found, as judgcriteria ed by ad hoc of groups within five mutational steps in the 15 STR loci with the same haplogroup. The times of the most recent common ancestor ranged from 279 to over 2577 years. According to the approximate millennium span of Japanese surname history, descent criteria are expected to be reasonable for grouping within four step-neighbors. High heterogeneity of common surnames resembles that observed for England and Spain, but not for Ireland. Our results highlight that common Japanese surnames consist of descent clusters and many singletons, reflecting a mixture of long-term bearers and short-term bearers among the population. The genetic study of this population revealed characteristic features of Japanese surnames.

New Records of Anopheles benarrochi B (Diptera: Culicidae) in Malaria Hotspots in the Amazon Regions of Ecuador and Peru.

The increase in malaria transmission in the Amazon region motivated vector control units of the Ministry of Health of Ecuador and Peru to investigate Anopheles (Diptera: Culicidae) species present in transmission hotspots. Mosquitoes were collected using prokopack aspirators and CDC light traps (Ecuador) and human landing catch in Peru. In Ecuador, 84 Anopheles were captured from Pastaza, Morona Santiago, and Orellana provinces and identified morphologically [An. (An.) apicimacula Dyar and Knab, An. (Nys.) near benarrochi, An. (Nys.) near oswaldoi, An. (Nys.) near strodei, An. (An.) nimbus (Theobald, 1902), and An. (Nyssorhynchus) sp.]. In Peru, 1,150 Anopheles were collected in Andoas District. A subsample of 166 specimens was stored under silica and identified as An. near oswaldoi, An. darlingi, and An. (An.) mattogrossensis Lutz and Neiva. COI barcode region sequences were obtained for 137 adults (107 from Peru, 30 from Ecuador) identified by ITS2 PCR-RFLP as An. benarrochi Gabaldon, Cova Garcia, and Lopez and retained in the final analysis. Haplotypes from the present study plus An. benarrochi B GenBank sequences grouped separately from Brazilian An. benarrochi GenBank sequences by 44 mutation steps, indicating that the present study specimens were An. benarrochi B. Our findings confirm the presence of An. benarrochi B in Ecuador and reported here for the first time from the Amazonian provinces of Orellana and Morona Santiago. Furthermore, we confirm that the species collected in Andoas District in the Datem del Maranon Province, Peru, is An. benarrochi B, and we observed that it is highly anthropophilic. Overall, the known distribution of An. benarrochi B has been extended and includes southern Colombia, much of Peru and eastern Ecuador.

Global Decoupling for Structural Reliability-Based Optimal Design Using Improved Differential Evolution and Chaos Control

This paper presents a new method for performing reliability-based design optimization (RBDO) of structures based on sequential optimization and reliability assessment (SORA). SORA is an effective method for solving RBDO that separates uncertainty analysis from optimization loops for reducing computational cost. However, SORA has some limitations, such as an inability to deal with problems involving discrete design variables or discontinuity in a domain, the dependency of solutions on the starting point of numerical solutions, and the lack of guarantee that global optimum solutions will be found. In this paper, a global decoupling method is proposed to tackle these limitations and improve the performance of SORA. This method links SORA enhanced with modified chaos control (ESORA) to an improved differential evolution (IDE) to perform RBDO. To deal with RBDO problems with discrete design variables, a rounding method is integrated into IDE. IDE also utilizes an adaptive selection scheme in a mutation step and an elitist strategy in the selection phase. To improve the efficiency of the method for RBDO problems with highly nonlinear performance functions and nonnormal random variables, a modified chaos control is employed to assess reliability constraints. Five numerical examples are considered to investigate the strength of the proposed method, illustrating its appropriate efficiency and accuracy. The proposed method is also extendable to more complex problems such as system reliability-based structural optimization and RBDO of nonlinear structures.

Rampant loss of social traits during domestication of a Bacillus subtilis natural isolate

Most model bacteria have been domesticated in laboratory conditions. Yet, the tempo with which a natural isolate diverges from its ancestral phenotype under domestication to a novel laboratory environment is poorly understood. Such knowledge, however is essential to understanding the rate of evolution, the time scale over which a natural isolate can be propagated without loss of its natural adaptive traits, and the reliability of experimental results across labs. Using experimental evolution, phenotypic assays, and whole-genome sequencing, we show that within a week of propagation in a common laboratory environment, a natural isolate of Bacillus subtilis acquires mutations that cause changes in a multitude of traits. A single adaptive mutational step in the gene coding for the transcriptional regulator DegU impairs a DegU-dependent positive autoregulatory loop and leads to loss of robust biofilm architecture, impaired swarming motility, reduced secretion of exoproteases, and to changes in the dynamics of sporulation across environments. Importantly, domestication also resulted in improved survival when the bacteria face pressure from cells of the innate immune system. These results show that degU is a target for mutations during domestication and underscores the importance of performing careful and extremely short-term propagations of natural isolates to conserve the traits encoded in their original genomes.

Quantum aspects of evolution: a contribution towards evolutionary explorations of genotype networks via quantum walks.

Quantum biology seeks to explain biological phenomena via quantum mechanisms, such as enzyme reaction rates via tunnelling and photosynthesis energy efficiency via coherent superposition of states. However, less effort has been devoted to study the role of quantum mechanisms in biological evolution. In this paper, we used transcription factor networks with two and four different phenotypes, and used classical random walks (CRW) and quantum walks (QW) to compare network search behaviour and efficiency at finding novel phenotypes between CRW and QW. In the network with two phenotypes, at temporal scales comparable to decoherence time TD, QW are as efficient as CRW at finding new phenotypes. In the case of the network with four phenotypes, the QW had a higher probability of mutating to a novel phenotype than the CRW, regardless of the number of mutational steps (i.e. 1, 2 or 3) away from the new phenotype. Before quantum decoherence, the QW probabilities become higher turning the QW effectively more efficient than CRW at finding novel phenotypes under different starting conditions. Thus, our results warrant further exploration of the QW under more realistic network scenarios (i.e. larger genotype networks) in both closed and open systems (e.g. by considering Lindblad terms).

Gene Loss and Acquisition in Lineages of Pseudomonas aeruginosa Evolving in Cystic Fibrosis Patient Airways.

Genome analyses have documented that there are differences in gene repertoire between evolutionary distant lineages of the same bacterial species; however, less is known about microevolutionary dynamics of gene loss and acquisition within bacterial lineages as they evolve over years. Here, we analyzed the genomes of 45 Pseudomonas aeruginosa lineages evolving in the lungs of cystic fibrosis (CF) patients to identify genes that are lost or acquired during the first years of infection. On average, lineage genome content changed by 88 genes (range, 0 to 473). Genes were more often lost than acquired, and prophage genes were more variable than bacterial genes. We identified convergent loss or acquisition of the same genes across lineages, suggesting selection for loss and acquisition of certain genes in the host environment. We found that a notable proportion of such genes are associated with virulence; a trait previously shown to be important for adaptation. Furthermore, we also compared the genomes across lineages to show that the within-lineage variable genes (i.e., genes that had been lost or acquired during the infection) often belonged to genomic content not shared across all lineages. In sum, our analysis adds to the knowledge on the pace and drivers of gene loss and acquisition in bacteria evolving over years in a human host environment and provides a basis to further understand how gene loss and acquisition play roles in lineage differentiation and host adaptation.IMPORTANCE Bacterial airway infections, predominantly caused by P. aeruginosa, are a major cause of mortality and morbidity of CF patients. While short insertions and deletions as well as point mutations occurring during infection are well studied, there is a lack of understanding of how gene loss and acquisition play roles in bacterial adaptation to the human airways. Here, we investigated P. aeruginosa within-host evolution with regard to gene loss and acquisition. We show that during long-term infection P. aeruginosa genomes tend to lose genes, in particular, genes related to virulence. This adaptive strategy allows reduction of the genome size and evasion of the host's immune response. This knowledge is crucial to understand the basic mutational steps that, on the timescale of years, diversify lineages and adds to the identification of bacterial genetic determinants that have implications for CF disease.

Genetic variation and selection in the major histocompatibility complex Class II gene in the Guizhou pony.

The Guizhou pony (GZP) is an indigenous species of equid found in the mountains of the Guizhou province in southwest China. We selected four regions of the equine leukocyte antigen (ELA), including DQA, DRA, DQB, and DRB, and used them to assess the diversity of the major histocompatibility complex (MHC) class II gene using direct sequencing technology. DRA had the lowest dN/dS ratio (0.560) compared with the other three loci, indicating that DRA was conserved and could be conserved after undergoing selective processes. Nine DQA, five DQB, nine DRA, and seven DRB codons were under significant positive selection at the antigen binding sites (ABS), suggesting that the selected residues in ABS may play a significant role in the innate immune system of the GZP. Two GZP alleles were shared with Przewalski’s horse, and six older GZP haplotypes had a better relationship with other horse species by one or two mutational steps, indicating that the GZP may be a natural ancient variety of equid. The specific diversity of ABS and the numbers of unique haplotypes in the evolutionary process affords this species a better genetic fitness and ability to adapt to the native environment.

A modified biogeography-based optimization algorithm with improved mutation operator for job shop scheduling problem with time lags

Abstract This paper addresses the job shop scheduling problem including time lag constraints. This is an extension of the job shop scheduling problem with many applications in real production environments, where extra (minimum and maximum) delays can be introduced between successive operations of the same job. It belongs to a category of problems known as NP-hard problem due to large solution space. Biogeography-based optimization is an evolutionary algorithm which is inspired by the migration of species between habitats, recently proposed by Simon in 2008 to optimize hard combinatorial optimization problems. We propose a hybrid biogeography-based optimization (HBBO) algorithm for solving the job shop scheduling problem with additional time lag constraints with minimization of total completion time. In the proposed HBBO, the effective greedy constructive heuristic is adapted to generate the initial population of habitat. Moreover, a local search metaheuristic is investigated in the mutation step in order to ameliorate the solution quality and enhance the diversity of the population. To assess the performance of HBBO, a series of experiments on well-known benchmark instances for job shop scheduling problem with time lag constraints is performed.

Iterative taxonomic study of Pareiorhaphis hystrix (Siluriformes, Loricariidae) suggests a single, yet phenotypically variable, species in south Brazil.

Pareiorhaphis hystrix is a widely distributed species, occurring in the upper and middle Uruguay River and in the Taquari River basin, Patos Lagoon system, southern Brazil. Morphological variation has been detected throughout the distribution of P. hystrix, and this work seeks to test the conspecific nature of populations in several occurrence areas. Specimens from six areas in the Uruguay River basin and three in the Taquari River basin were compared. Variance analysis (ANOVA) was performed for the meristic data, and Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) were conducted for morphometric data. Molecular analyses used coI, cytb, 12S and 16S mitochondrial genes, examining nucleotide diversity, haplotype diversity, genetic distance, and delimitation of possible multiple species through the Generalized Mixed Yule Coalescent (GMYC) method. Phylogenetic relationships of studied populations were also investigated through Bayesian inference. While PCA indicated a tendency of overlap between areas, ANOVA and LDA detected a subtle differentiation between populations from the two hydrographic basins. Yet, both latter analyses recovered the population from Pelotas River, a tributary to Uruguay River, as more similar to populations from Taquari River, which is congruent to morphological observations of anterior abdominal plates. The molecular data indicated a nucleotide diversity lower than the haplotypic diversity, suggestive of recent expansion. The concatenated haplotype network points to slight differentiation between areas, with each locality presenting unique and non-shared haplotypes, although with few mutational steps in general. The species delimitation by coalescence analysis suggested the presence of a variable number of OTUs depending on the inclusion or exclusion of an outgroup. In general, the morphological data suggest a subtle variation by river basin, while the genetic data indicates a weak population structuration by hydrographic areas, especially the Chapecó and Passo Fundo rivers. However, there is still not enough differentiation between the specimens to suggest multiple species. The iterative analyses indicate that Pareiorhaphis hystrix is composed of a single, although variable, species.

Parameter identification of Bouc-Wen model for Magnetorheological (MR) fluid Damper by a Novel Genetic Algorithm

In this research, novel genetic algorithm (nGA) is proposed for Bouc-Wen modle parameters esstimation for magnetorheological (MR) fluid dampers. The optimization efficiency is improved by modifying the crossover and mutation steps of a GA. In the crossover stage, the probability of reproducing offspring from the same parent (same mother and father chromosome) is done to be zero, which may happen in the standard GA, and the probability of a chromosome to be selected for mating is based on error rank weighting of the chromosomes. Additional fitness evaluation of chromosomes will take place in between the crossover and mutation steps to save the best chromosome found so far, which is not implemented in the standard genetic algorithm (GA). The model is validated by comparing its simulation output force ( Fsim) with experimentally generated MR damper force ( Fexp). The mean absolute error, standard deviation and number of generations for convergence are taken as a criterias for performance evaluation. With these ctriterias, the proposed novel GA outperform better than the other researches. The accuracy is improved by 46.67% compared to standard GA. The proposed novel GA for Bouc-Wen model parameter identification can be used for any MR damper control system with better accuracy.

Genetic Diversity and Phylogeography of the Important Medical Herb, Cultivated Huang-Lian Populations, and the Wild Relatives Coptis Species in China.

Huang-lian (Coptis plants in China) are essential medicinal plants in China, C. chinensis var. chinensis and C. deltoidea have been domesticated and cultivated for 700 years. In this study, the genetic diversity patterns and biogeographical information of cultivated Huang-lian and their wild relatives Coptis species were assessed using three plastids DNA regions. A total of 186 individuals from twenty-seven populations representing two species of cultivated Huang-lian and four species of wild relatives were collected and analyzed. Twenty-four haplotypes of six species were identified when three plastid spacers were combined. Historical biogeography inference revealed multiple dispersal events in the groups of cultivated Huang-lian and C. omeiensis. This evidence can infer that large initial population size and interbreeding with co-existing wild relatives in expanding new planting areas might be the main reason for maintaining the high genetic diversity of cultivated Huang-lian. Nevertheless, the multimodal curve of mismatch analysis and positive or negative differed among species and populations by neutrality tests indicated some groups of cultivated Huang-lian experienced genetic bottlenecks. Phylogeny analysis (NJ, MP, BI) showed that cultivated Huang-lian and C. omeiensis were clustered into a monophyletic group while C. chinensis var. brevisepala was paraphyletic, having earlier divergence time from C. chinensis var. chinensis (7.6 Ma) than C. omeiensis. Parsimony network demonstrated that C. deltoidea had more shared haplotypes with C. omeiensis than C. chinensis var. chinensis, and other haplotypes of C. deltoidea and C. omeiensis had less mutation steps than that of C. chinensis var. chinensis and C. omeiensis. This evidence suggests that C. omeiensis has a closer relationship with cultivated Huang-lian and might be a potential wild relative to C. deltoidea. The results reported here provide the baseline data for preserving genetic resources of Huang-lian and also evaluating the genetic impacts of long-term cultivation on medicinal plants, which could be instructive to future cultivation projects of traditional Chinese medicinal plants.

Lotka\u2013Volterra approximations for evolutionary trait-substitution processes

A set of axioms is formulated characterizing ecologically plausible community dynamics. Using these axioms, it is proved that the transients following an invasion into a sufficiently stable equilibrium community by a mutant phenotype similar to one of the community's finitely many resident phenotypes can always be approximated by means of an appropriately chosen Lotka–Volterra model. To this end, the assumption is made that similar phenotypes in the community form clusters that are well-separated from each other, as is expected to be generally the case when evolution proceeds through small mutational steps. Each phenotypic cluster is represented by a single phenotype, which we call an approximate phenotype and assign the cluster’s total population density. We present our results in three steps. First, for a set of approximate phenotypes with arbitrary equilibrium population densities before the invasion, the Lotka–Volterra approximation is proved to apply if the changes of the population densities of these phenotypes are sufficiently small during the transient following the invasion. Second, quantitative conditions for such small changes of population densities are derived as a relationship between within-cluster differences and the leading eigenvalue of the community’s Jacobian matrix evaluated at the equilibrium population densities before the invasion. Third, to demonstrate the utility of our results, the ‘invasion implies substitution’ result for monomorphic populations is extended to arbitrarily polymorphic populations consisting of well-recognizable and -separated clusters.

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.

Evidence for both sequential mutations and recombination in the evolution of kdr alleles in Aedes aegypti.

BackgroundAedes aegypti is a globally distributed vector of human diseases including dengue, yellow fever, chikungunya, and Zika. Pyrethroid insecticides are the primary means of controlling adult A. aegypti populations to suppress arbovirus outbreaks, but resistance to pyrethroid insecticides has become a global problem. Mutations in the voltage-sensitive sodium channel (Vssc) gene are a major mechanism of pyrethroid resistance in A. aegypti. Vssc resistance alleles in A. aegypti commonly have more than one mutation. However, our understanding of the evolutionary dynamics of how alleles with multiple mutations arose is poorly understood.Methodology/Principal findingsWe examined the geographic distribution and association between the common Vssc mutations (V410L, S989P, V1016G/I and F1534C) in A. aegypti by analyzing the relevant Vssc fragments in 25 collections, mainly from Asia and the Americas. Our results showed all 11 Asian populations had two types of resistance alleles: 1534C and 989P+1016G. The 1534C allele was more common with frequencies ranging from 0.31 to 0.88, while the 989P+1016G frequency ranged from 0.13 to 0.50. Four distinct alleles (410L, 1534C, 410L+1534C and 410L+1016I+1534C) were detected in populations from the Americas. The most common was 410L+1016I+1534C with frequencies ranging from 0.50 to 1.00, followed by 1534C with frequencies ranging from 0.13 to 0.50. Our phylogenetic analysis of Vssc supported multiple independent origins of the F1534C mutation. Our results indicated the 410L+1534C allele may have arisen by addition of the V410L mutation to the 1534C allele, or by a crossover event. The 410L+1016I+1534C allele was the result of one or two mutational steps from a 1534C background.Conclusions/SignificanceOur data corroborated previous geographic distributions of resistance mutations and provided evidence for both recombination and sequential accumulation of mutations contributing to the molecular evolution of resistance alleles in A. aegypti.

Deep Dive into Machine Learning Models for Protein Engineering.

Protein redesign and engineering has become an important task in pharmaceutical research and development. Recent advances in technology have enabled efficient protein redesign by mimicking natural evolutionary mutation, selection, and amplification steps in the laboratory environment. For any given protein, the number of possible mutations is astronomical. It is impractical to synthesize all sequences or even to investigate all functionally interesting variants. Recently, there has been an increased interest in using machine learning to assist protein redesign, since prediction models can be used to virtually screen a large number of novel sequences. However, many state-of-the-art machine learning models, especially deep learning models, have not been extensively explored. Moreover, only a small selection of protein sequence descriptors has been considered. In this work, the performance of prediction models built using an array of machine learning methods and protein descriptor types, including two novel, single amino acid descriptors and one structure-based three-dimensional descriptor, is benchmarked. The predictions were evaluated on a diverse collection of public and proprietary data sets, using a variety of evaluation metrics. The results of this comparison suggest that Convolution Neural Network models built with amino acid property descriptors are the most widely applicable to the types of protein redesign problems faced in the pharmaceutical industry.

Epidemics with mutating infectivity on small-world networks

Epidemics and evolution of many pathogens occur on similar timescales so that their dynamics are often entangled. Here, in a first step to study this problem theoretically, we analyze mutating pathogens spreading on simple SIR networks with grid-like connectivity. We have in mind the spatial aspect of epidemics, which often advance on transport links between hosts or groups of hosts such as cities or countries. We focus on the case of mutations that enhance an agent’s infection rate. We uncover that the small-world property, i.e., the presence of long-range connections, makes the network very vulnerable, supporting frequent supercritical mutations and bringing the network from disease extinction to full blown epidemic. For very large numbers of long-range links, however, the effect reverses and we find a reduced chance for large outbreaks. We study two cases, one with discrete number of mutational steps and one with a continuous genetic variable, and we analyze various scaling regimes. For the continuous case we derive a Fokker-Planck-like equation for the probability density and solve it for small numbers of shortcuts using the WKB approximation. Our analysis supports the claims that a potentiating mutation in the transmissibility might occur during an epidemic wave and not necessarily before its initiation.