Exploiting Anopheles gene expression regulation for molecular surveillance of insecticide resistance

This PhD opportunity is being offered as part of the LSTM and Lancaster University Doctoral Training Partnership. Find out more about the studentships and how to apply. 

Abstract Mosquito genetics is a keystone of vector-borne disease control. Devastating diseases such as malaria and dengue fever are transmitted by mosquitoes, and the most effective tool to control these diseases is to protect the populations at risk using insecticides. Inevitably, mosquitoes quickly become resistant to these insecticides. New compounds are being brought to market to combat this resistance, and history shows that resistance to these will also rapidly emerge. Understanding the genetic mechanisms of resistance is crucial to predict how resistance may evolve, and to detect and react to resistance in the field as soon as it emerges. The biggest weak point in our understanding is the genetic regions that control the level of expression of resistance genes, that is, the regions that allow a mosquito to make more of these genes’ products. Throughout the tree of life, the mechanisms of regulation are poorly understood. A wealth of whole-genome sequencing data from field samples are now available, with millions of mutations across the genome, but with no way of knowing which mutations are “red flags” for emerging resistance. The limiting factor is that we don’t know where to look for these mutations. This project will use state-of-the art molecular, genomic and cell-culture techniques to answer this fundamental and crucial question, using the major malaria vector Anopheles gambiae as a model species to disentangle the molecular keys to resistance gene expression. Previous research at LSTM (Dyer et al 2024) has established the use of allele specific expression and machine learning based computational predictions to study gene expression regulation in Anopheles gambiae. Building on this approach, aim 1 of this project is to identify the regulatory regions in the Anopheles gambiae genome responsible for expression of insecticide resistance genes, producing a shortlist of expression markers for molecular surveillance. These regulatory sequences will then be used to scan a databank of thousands of wild An. gambiae genomes to flag mutations at risk of causing insecticide resistance. Progressing this shortlist and candidate regulatory sequences from the published literature to viable “red flag” markers, aim 2 is to functionally validate regulatory regions and the mutations in them that putatively cause gene expression changes using high throughput cell culture-based assays. Working closely with LSTM experts in activity-based probes and “organ on a chip”, assays will be designed to be accurately represent whole organism physiology. In addition, by introducing novel mutations in cultured cells via gene synthesis, cell culture assays will be used to predict the effect on gene expression of mutations that have not yet occurred in wild mosquitoes. This approach will identify regulatory hotspots in the genome that have strong evolutionary potential to cause overexpression of resistance genes. Such predictive power combined with molecular surveillance of mosquito DNA could hugely increase the speed of responding to new mutations in the field as they occur.
Where does this project lie in the translational pathway? T1 - Basic Research
Methodological Aspects Quantitative elements are highlighted with *
  • Genetic crosses between laboratory mosquito strains
  • Quantification of gene transcription (including allele specific expression) in parental strains and F1 hybrids from large RNAseq data*
  • Integration of newly generated and already existing RNAseq data with whole genome sequences as well as putative gene regulatory sequences to identify candidate sequence variants for molecular surveillance*
  • Culture and genetic transformation of Anopheles cell lines
  • Motif analysis and targeted mutagenesis of regulatory sequences*
  • Reporter and CRISPR assays to regulatory sequence activity in cultured cells *
  • Measure the response of cultured cells to different environments and stimuli using microscopy or flow cytometry, high throughput image analysis, RNA sequencing and proteomic analysis*
Expected Outputs
  • High impact publications on the regulation of gene expression during the evolution of insecticide resistance, cell-based assays for high-throughput screening of molecular surveillance candidates and regulatory hotspot identification.
  • Technical skills in a wide range of quantitative bioinformatics analysis and integration of large datasets
  • Cell culture-based assays for high throughput functional validation of genetic variants in regulatory regions for molecular surveillance. These assays could easily be adapted for more targetted functional validation prior to costly mosquito experiments, such as investigating the effects of multiple nonsynonymous mutations in protein-coding genes, and as such will make funding applications to Wellcome Trust, MRC and BBSRC more competitive.
Training Opportunities
  • Training in insectary skills including mosquito rearing, genetic crosses, bioassays of insecticide toxicity
  • Laboratory skills including molecular biology, cell culture
  • Training in generation and analysis and integration of large ‘omics datasets and machine learning
  • Training in presenting research including at national and international conferences
  • Mentorship in writing and publishing high impact papers
Skills Required This project is suited to a highly motivated student who is both curious about fundamental biology and passionate about creating better tools for malaria control. Skills: problem solving, clear communication, taking initiative, responding to feedback Experience: experience of biomedical laboratory research and/or coding and data analysis would be beneficial Aptitudes: the student should be numerate and able to combine creativity with a systematic approach to research
Subject Areas Malaria and other vector borne diseases
Key Publications associated with this project

1. Dyer NA, Lucas ER, Nagi SC, McDermott DP, Brenas JH, Miles A, et al. Mechanisms of transcriptional regulation in Anopheles gambiae revealed by allele-specific expression. Proceedings Biological sciences / The Royal Society. 2024;291(2031):20241142. https://doi.org/10.1098/rspb.2024.1142

2. Lucas ER, Nagi SC, Egyir-Yawson A, Essandoh J, Dadzie S, Chabi J, et al. Genome-wide association studies reveal novel loci associated with pyrethroid and organophosphate resistance in Anopheles gambiae and Anopheles coluzzii. Nature communications. 2023;14(1):4946. https://doi.org/10.1038/s41467-023-40693-0

3. Ingham VA, Wagstaff S, Ranson H. Transcriptomic meta-signatures identified in Anopheles gambiae populations reveal previously undetected insecticide resistance mechanisms. Nature communications. 2018;9(1):5282. https://doi.org/10.1038/s41467-018-07615-x

4. Balaska S, Grigoraki L, Lycett G, Weetman D, Oladepo F, Colman F, Vontas J, Paine MJI, Ismail HM. Predictive chemoproteomics and functional validation reveal Coeae6g-mediated insecticide cross-resistance in the malaria vector Anopheles gambiae. Provisionally accepted, Nature Communications (pending final editorial revisions. This will soon be available in LSTM archive).

5. Ismail HM, O'Neill PM, Hong DW, Finn RD, Henderson CJ, Wright AT, et al. Pyrethroid activity-based probes for profiling cytochrome P450 activities associated with insecticide interactions. Proceedings of the National Academy of Sciences of the United States of America. 2013;110(49):19766-71. https://doi.org/10.1073/pnas.1320185110