Biology subjects

Lucas, E. R.

Publications and source records attributed to Lucas, E. R..

26 records · Page 2Linked to original sources

bioRxiv2021

Integration of whole genome sequencing and transcriptomics reveals a complex picture of insecticide resistance in the major malaria vector Anopheles coluzzii

Insecticide resistance is a major threat to gains in malaria control, which have been stalling and potentially reversing since 2015. Studies into the causal mechanisms of insecticide resistance are painting an increasingly complicated picture, underlining the need to design and implement targeted studies on this phenotype. In this study, we compare three populations of the major malaria vector An. coluzzii: a susceptible and two resistant colonies with the same genetic background. The original colonised resistant population rapidly lost resistance over a 6-month period, a subset of this population was reselected with pyrethroids a third population of this colony that did not lose resistance was also available. The original resistant, susceptible and re-selected colonies were subject to RNAseq and whole genome sequencing, which identified a number of changes across the transcriptome and genome linked with resistance. Firstly, an increase in the expression of genes within the oxidative phosphorylation pathway were seen in both resistant populations compared to the susceptible control; this translated phenotypically through an increased respiratory rate, indicating that elevated metabolism is linked directly with resistance. Genome sequencing highlighted several blocks clearly associated with resistance, including the 2Rb inversion. Finally, changes in the microbiome profile were seen, indicating that the microbial composition may play a role in the resistance phenotype. Taken together, this study reveals a highly complicated phenotype in which multiple transcriptomic, genomic and microbiome changes combine to result in insecticide resistance.

genomics↗

bioRxiv2021

A gene expression panel for estimating age in males and females of the sleeping sickness vector Glossina morsitans

Many vector-borne diseases are controlled by methods that kill the insect vectors responsible for disease transmission. Recording the age structure of vector populations provides information on mortality rates and vectorial capacity, and should form part of the detailed monitoring that occurs in the wake of control programmes, yet tools for obtaining estimates of individual age remain limited. We investigate the potential of using markers of gene expression to predict age in tsetse flies, which are the vectors of deadly and economically damaging African trypanosomiases. We use RNAseq to identify candidate expression markers, and test these markers using qPCR in laboratory-reared Glossina morstians morsitans of known age. Measuring the expression of six genes was sufficient to obtain a prediction of age with root mean squared error of less than 8 days, while just two genes were sufficient to classify flies into age categories of [≤] 15 and >15 days old. Further testing of these markers in field-caught samples and in other species will determine the accuracy of these markers in the field.

ecology↗

bioRxiv2021

Identification of a rapidly-spreading triple mutant for high-level metabolic insecticide resistance in Anopheles gambiae provides a real-time molecular diagnostic for anti-malarial intervention deployment.

Insecticide resistance provides both an increasingly pressing threat to the control of vector-borne diseases and insights into the remarkable capacity of natural populations to show rapid evolutionary responses to contemporary selection. Malaria control remains heavily dependent on deployment of pyrethroid insecticides, primarily in long lasting insecticidal nets (LLINs), but resistance in the major malaria vectors has increased over the last 15 years in concert with dramatic expansion of LLIN distributions. Identifying genetic mechanisms underlying high-level resistance in mosquitoes, which may almost entirely overcome pyrethroid efficacy, is crucial for the development and deployment of potentially resistance-breaking tools. Using the Anopheles gambiae 1000 genomes (Ag1000g) data we identified a very recent selective sweep in mosquitoes from Uganda which localized to a cluster of cytochrome P450 genes, including some commonly implicated in resistance. Further interrogation revealed a haplotype involving a trio of mutations, a nonsynonymous point mutation in Cyp6p4 (I236M), an upstream insertion of a partial Zanzibar-like transposable element (TE) and a duplication of the Cyp6aa1 gene. The mutations appear to have originated recently in An. gambiae from the Kenya-Uganda border region around Lake Victoria, with stepwise replacement of the double-mutant (Zanzibar-like TE and Cyp6p4-236M) with the triple-mutant haplotype (including Cyp6aa1 duplication), which has spread into the Democratic Republic of Congo and Tanzania. The triple-mutant haplotype is strongly associated with increased expression of genes able to metabolise pyrethroids and is strongly predictive of resistance to pyrethroids most notably deltamethrin, a commonly-used LLIN insecticide. Importantly, there was increased mortality in mosquitoes carrying the triple-mutation when exposed to nets co-treated with the synergist piperonyl butoxide (PBO). Frequencies of the triple-mutant haplotype remain spatially variable within countries, suggesting an effective marker system to guide deployment decisions for limited supplies of PBO-pyrethroid co-treated LLINs across African countries. Duplications of the Cyp6aa1 gene are common in An. gambiae across Africa and, given the enzymes metabolic activity, are likely to be a useful diagnostic for high levels of pyrethroid resistance.

evolutionary biology↗

bioRxiv2020

Apparent negative density-dependent dispersal in tsetse (Glossina spp) is an artefact of inappropriate analysis

Analysis of genetic material from field-collected tsetse (Glossina spp) in ten study areas has been used to predict that the distance ({delta}) dispersed per generation increases as effective population densities (De) decrease, displaying negative density dependent dispersal (NDDD). This result is an artefact arising primarily from errors in estimates of S, the area occupied by a subpopulation, and thereby in De, the effective subpopulation density. The fundamental, dangerously misleading, error lies in the assumption that S can be estimated as the area ([S]) regarded as being covered by traps. Errors in the estimates of{delta} are magnified because variation in estimates of S is greater than for all other variables measured, and accounts for the greatest proportion of variation in{delta} . The errors result in anomalously high correlations between{delta} and S, and the appearance of NDDD, with a slope of -0.5 for the regressions of log({delta}) on log(e), even in simulations where dispersal has been set as density independent. A complementary mathematical analysis confirms these findings. Improved error estimates for the crucial parameter b, the rate of increase in genetic distance with increasing geographic separation, suggest that three of the study areas should have been excluded because b is not significantly greater than zero. Errors in census population estimates result from a fundamental misunderstanding of the relationship between trap placement and expected tsetse catch. These errors are exacerbated through failure to adjust for variations in trapping intensity, trap performance, and in capture probabilities between geographical situations and between tsetse species. Claims of support in the literature for NDDD are spurious. There is no suggested explanation for how NDDD might have evolved. We reject the NDDD hypothesis and caution that the idea should not be allowed to influence policy on tsetse and trypanosomiasis control. Author summaryGenetic analysis of field-sampled tsetse (Glossina spp) has been used to suggest that, as tsetse population densities decrease, rates of dispersal increase - displaying negative density dependent dispersal (NDDD). It is further suggested that NDDD might apply to all tsetse species and that, consequently, tsetse control operations might unleash enhanced invasion of areas cleared of tsetse, prejudicing the long-term success of control campaigns. We demonstrate that NDDD in tsetse is an artefact consequent on multiple errors of analysis and interpretation. The most serious of these errors stems from a fundamental misunderstanding of the way in which traps sample tsetse, resulting in huge errors in estimates of the areas sampled by the traps, and occupied by the subpopulations being sampled. Errors in census population estimates are made worse through failure to adjust for variations in trapping intensity, trap performance, and in capture probabilities between geographical situations, and between tsetse species. The errors result in the appearance of NDDD, even in modelling situations where rates of dispersal are expressly assumed independent of population density. We reject the NDDD hypothesis and caution that the idea should not be allowed to influence policy on tsetse and trypanosomiasis control.

zoology↗

bioRxiv2020

Resistance to pirimiphos-methyl in West African Anopheles is spreading via duplication and introgression of the Ace1 locus

Vector population control using insecticides is a key element of current strategies to prevent malaria transmission in Africa. The introduction of effective insecticides, such as the organophosphate pirimiphos-methyl, is essential to overcome the recurrent emergence of resistance driven by the highly diverse Anopheles genomes. Here, we use a population genomic approach to investigate the basis of pirimiphos-methyl resistance in the major malaria vectors Anopheles gambiae and A. coluzzii. A combination of copy number variation and a single non-synonymous substitution in the acetylcholinesterase gene, Ace1, provides the key resistance diagnostic in an A. coluzzii population from Cote dIvoire that we used for sequence-based association mapping, with replication in other West African populations. The Ace1 and substitution and duplications occur on a unique resistance haplotype that evolved in A. gambiae and introgressed into A. coluzzii, and is now common in West Africa probably due to cross-resistance with previously used insecticides. Our findings highlight the phenotypic value of this complex resistance haplotype and clarify its evolutionary history, providing tools to understand the current and future effectiveness of pirimiphos-methyl based interventions.

genomics↗

bioRxiv2019

Genome variation and population structure among 1,142 mosquitoes of the African malaria vector species Anopheles gambiae and Anopheles coluzzii

Mosquito control remains a central pillar of efforts to reduce malaria burden in sub-Saharan Africa. However, insecticide resistance is entrenched in malaria vector populations, and countries with high malaria burden face a daunting challenge to sustain malaria control with a limited set of surveillance and intervention tools. Here we report on the second phase of a project to build an open resource of high quality data on genome variation among natural populations of the major African malaria vector species Anopheles gambiae and Anopheles coluzzii. We analysed whole genomes of 1,142 individual mosquitoes sampled from the wild in 13 African countries, and a further 234 individuals comprising parents and progeny of 11 lab crosses. The data resource includes high confidence single nucleotide polymorphism (SNP) calls at 57 million variable sites, genome-wide copy number variation (CNV) calls, and haplotypes phased at biallelic SNPs. We used these data to analyse genetic population structure, and characterise genetic diversity within and between populations. We also illustrate the utility of these data by investigating species differences in isolation by distance, genetic variation within proposed gene drive target sequences, and patterns of resistance to pyrethroid insecticides. This data resource provides a foundation for developing new operational systems for molecular surveillance, and for accelerating research and development of new vector control tools.

genomics↗

bioRxiv2018

Improved spatial ecological sampling using open data and standardization: an example from malaria mosquito surveillance

Vector-borne disease control relies on efficient vector surveillance, mostly carried out using traps whose number and locations are often determined by expert opinion rather than a rigorous quantitative sampling design. In this work we first propose a framework for ecological sampling design which in its preliminary stages can take into account environmental conditions obtained from open data (i.e. remote sensing and meteorological stations). These environmental data are used to delimit the area into ecologically homogenous strata. By employing a model-based sampling design, the traps are deployed among the strata using a mixture of random and grid locations which allows balancing predictions and fitting accuracies. Sample sizes and the effect of ecological strata on sample sizes are estimated from previous sampling campaigns. Notably, we found that a configuration of 30 locations with 4 households each (120 traps) will have a similar accuracy in the estimates of mosquito abundance as 300 random samples. In addition, we show that random sampling independently from ecological strata, produces biased estimates of the mosquito abundance. Finally, we propose standardizing reporting of sampling designs to allow transparency and repetition / re-use in subsequent sampling campaigns.

ecology↗

bioRxiv2018

Whole genome sequencing reveals high complexity of copy number variation at insecticide resistance loci in malaria mosquitoes

BackgroundPolymorphisms in the copy number of a genetic region can influence gene expression, coding sequence and zygosity, making them powerful actors in the evolutionary process. Copy number variants (CNVs) are however understudied, being more difficult to detect than single nucleotide polymorphisms. We take advantage of the intense selective pressures on the major malaria vector Anopheles gambiae, caused by the widespread use of insecticides for malaria control, to investigate the role of CNVs in the evolution of insecticide resistance.\n\nResultsUsing the whole-genome sequencing data from 1142 samples in the An. gambiae 1000 genomes project, we identified 1557 independent increases in copy number, encompassing a total of 267 genes, which were enriched for gene families linked to metabolic insecticide resistance. The five major candidate genes for metabolic resistance were all found in at least one CNV, and were often the target of multiple independent CNVs, reaching as many as 16 CNVs in Cyp9k1. These CNVs have furthermore been spreading due to positive selection, indicated by high local CNV frequencies and extended haplotype homozygosity.\n\nConclusionsOur results demonstrate the importance of CNVs in the response to selection, with CNVs being closely associated with genes involved in the evolution of resistance to insecticides, highlighting the urgent need to identify their relative contributions to resistance and to track their spread as the application of insecticide in malaria endemic countries intensifies. Our detailed descriptions of CNVs found across the species range provides the tools to do so.

evolutionary biology↗