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NC3Rs: National Centre for the Replacement Refinement & Reduction of Animals in Research
Partnerships and impact awards

Integrated training and data sharing to accelerate adoption of 3Rs technology in trypanosome infection research

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At a glance

Pending start
Award date
March 2025 - February 2027
Grant amount
£183,989
Principal investigator
Dr Catarina Gadelha

Co-investigator(s)

Institute
University of Nottingham

R

  • Reduction

Overview

Catarina’s award will facilitate the use of Direct RNAi-Fragment Sequencing (DRiF-Seq) technology, a cutting-edge genetic tool developed with an NC3Rs Project grant, for the study of African trypanosomes – insect-borne parasites that cause deadly infections in humans and cattle. Traditional genetic methods used to assess parasite infection, survival, transmission and drug resistance typically require the use of large numbers of mice as only one mutant can be tested per animal, whereas the DRiF-Seq technology allows for the high-throughput phenotyping of more than 5,000 trypanosome mutants simultaneously within a single animal. During the project Catarina will provide hands-on training in the DRiF-Seq methods (including mutant library production, processing, sequencing and analysis of datasets) to four leading trypanosome research labs based in the UK, Portugal and the Czech Republic. The collaborating labs will apply the technology to study fundamental trypanosome biology including functional genetic studies, investigate parasite drug resistance and identify new therapeutics, reducing the use of approximately 8,000 mice. Catarina will also create comprehensive protocols to allow for independent and wider adoption of these methods.

Application abstract

Human African trypanosomiasis, caused by subspecies of Trypanosoma brucei, is a deadly neglected tropical disease of sub-Saharan Africa. Related diseases in cattle (caused predominantly by T. congolense and T. vivax) place an estimated ~$4 billion burden on developing economies in Africa, Asia and South America. No vaccine currently exists, and drug resistance is a known issue. As such, the function of trypanosome genes and their role in disease is of great scientific interest for understanding parasite biology, identifying virulence factors and tackling drug resistance. Typically, functional genetic studies in trypanosome research infect genetically identical single mutants into cohorts of animals and, as a result, use a large (and growing) number of experimental animals.

There is great opportunity for reduction in animal usage in infection research by exploiting next-generation sequencing and organism barcoding to test pathogen gene mutant phenotypes in parallel. Building directly on on-going NC3Rs funding, we have demonstrated that replacing traditional gene-by-gene approaches with parallelisation can achieve a very substantial reduction in animal usage in trypanosome functional genetics. Our high-throughput phenotyping technology (DRiF-Seq) generates and quantitatively tracks 1000s of mutants in individual animals with greater statistical power than gene-by-gene approaches. This increases robustness and reliability, measures mutant-mutant variation and potentially achieves >100-fold reduction of animal usage for specific tests. Here we propose to accelerate the adoption of parallelisation in trypanosome research by transfer of skills in DRiF-Seq to a number of
key early-adopter labs. These partner labs encompass multiple disciplines and applications (medical, veterinary, and basic biology), are trans-national, and have animal experiments that could immediately be reduced by parallelisation. They are also very well placed to encourage uptake of methods to further labs in infection biology. In this proposal, we will provide direct, hands-on training in the developers’ lab in the methods of mutant library production, processing and analysis, while also creating comprehensive protocols documentation for know-how transfer that can be followed elsewhere. This will greatly accelerate uptake of this specific reduction method in trypanosomes to maximise the 3Rs impact of on-going work, but also provides an example that should stimulate adoption of similar parallelisation approaches more widely in infection research.