Decoding drug resistance mutations with gene editing

A team from the Faculty of Life Sciences has scaled and deployed a parasite gene-editing technology to decode drug resistance mechanisms. The method, known as oligo targeting, involves delivering short DNA fragments to parasites using a pulse of electricity. The DNA, including the desired edits, is then incorporated into the genome.

The team of scientists work on a group of lethal parasites known as trypanosomatids, and were awarded the SLS Innovator of the year award in 2022 for initially developing the technique. Several new anti-trypanosomal drugs in clinical development or in clinical use show great promise. Indeed, an ambitious World Health Organisation’s goal is now elimination of sleeping sickness by 2030; a disease caused by African trypanosomes and transmitted by tsetse-flies. Although the new drugs often have known targets, potential resistance mechanisms remain largely uncharacterised, limiting approaches to surveillance and rational design of improved therapies.

In the paper, published in Nature Communications, the researchers scale the gene editing approach to survey all possible mutations at a drug binding site in the African trypanosome. They develop multiplex oligo targeting and generate libraries of mutant parasites, focussing on a priority drug target known as the proteasome, an essential cellular ‘waste-disposal unit’. Drug dose-response and fitness profiles were reconstructed using high-throughput DNA sequencing data, revealing more than 100 resistance-associated mutants. The researchers used these profiles to predict spontaneous resistance mechanisms in multiple trypanosomatids. Structural data and computational models were then used to understand the mechanisms underpinning resistance.

David Horn, Wellcome Trust Investigator, said, “We were surprised by the rarity of comprehensive mutational data available for drug binding sites, partly explained by limitations of CRISPR-Cas9 based gene editing tools. Oligo targeting is a relatively low-efficiency editing approach but presented an opportunity here, since it is scalable and precise, and allows the introduction of all possible types of base-edit”.

Simone Altmann, the first author on the paper said, “Oligo targeting is surprisingly straightforward and allowed us to assess more than 1000 mutations around a drug binding site in one experiment”.

Cesar Mendoza-Martinez, a senior computational chemist in the Drug Discovery Unit said “The current dataset provided an unprecedented opportunity to test computer-based predictions and revealed which approaches worked well (or not so well) to predict drug efficacy and resistance”.

The approach has also been used to identify resistance-associated mutations in a second priority drug target known as CPSF3 (see the preprint here) and to identify mutations associated with veterinary ‘African trypanosomes’ that have spread outside Africa; now being sexually transmitted or transmitted by biting flies or vampire bats (see the preprint here).

The researchers conclude that oligo targeting is a powerful and scalable gene editing approach that will help them understand how therapies work, and sometimes stop working. The insights that emerge should allow them to predict drug resistance, improve prospects for resistance surveillance, and enhance computational drug design strategies towards more effective and durable drugs.

See the paper here: Decoding efficacy and resistance space at a drug binding site

See a 4 min video on oligo targeting work here.