Reducing and replacing the animal cost of functional genetics in African trypanosomiasis
Lead Research Organisation:
University of Nottingham
Department Name: School of Life Sciences
Abstract
One of the key applications of animal models to infectious disease is in understanding how pathogen genes affect disease outcome. This is critical, for example, in identification of virulence factors and mechanisms of drug resistance, which affect how we treat infected individuals.
African trypanosomes are parasites of the blood which cause a fatal disease in people in sub-Saharan Africa and a wasting disease of cattle that has a huge detrimental impact on meat and dairy production, creating losses of ~$4 billion from developing economies in Africa, Asia and South America. Closely related parasites called Leishmania cause a range of diseases whose symptoms include ulcerative lesions, complete destruction of the mucous membranes in the nose and mouth, and organ failure and death, with ~1 million new cases each year. Understanding the virulence of these parasites involves taking gene mutants through animal models. Traditionally, this is done by using an individual mutant to infect a set of animals, and comparing the disease progression to animals infected with non-mutant parasites. However, each parasite species contains ~10,000 genes and there are many different mutations for each, so even only looking at a very few genes means a lot of experimental animals are used for such studies. For technical reasons, these studies are also typically performed with strains of the parasite that do not recapitulate important aspects of the real disease. Moreover, because of variation in parasite levels between infections and different mutants of the same gene, the sensitivity of these studies to detect changes is relatively weak.
We have developed a method using contemporary genetic technology that can rapidly test the effect of mutants during infections in a complex mixture containing many 1000s of individual mutants. The method is compatible with parasite strains that capture real human disease biology and also species that cause animal disease. We have pilot data showing the method can be used in animal models of disease to robustly assess mutant fitness over the course of infections, capturing both variation between mutants in the same gene and animal-animal variation, but requiring fewer animals than would testing a single gene. In this project, we will demonstrate that the method can be translated to the most important trypanosome for human disease and validate its use to efficiently test sets of genes arising from experiments with minimal animal usage. We will also expand the use of the method to cover every gene in the genomes of trypanosomes causing human and animal disease, effectively eliminating the need for new experimental animal usage in basic tests of fitness during infection.
Demonstration of effectiveness in these infection models will encourage the wide adoption of these highly-parallel methods by labs, leading to substantial reduction in animal usage at the same time as resulting in better scientific outcome. It will also remove the need for one of the most common usages and demonstrate the potential to replace large animals with smaller models.
African trypanosomes are parasites of the blood which cause a fatal disease in people in sub-Saharan Africa and a wasting disease of cattle that has a huge detrimental impact on meat and dairy production, creating losses of ~$4 billion from developing economies in Africa, Asia and South America. Closely related parasites called Leishmania cause a range of diseases whose symptoms include ulcerative lesions, complete destruction of the mucous membranes in the nose and mouth, and organ failure and death, with ~1 million new cases each year. Understanding the virulence of these parasites involves taking gene mutants through animal models. Traditionally, this is done by using an individual mutant to infect a set of animals, and comparing the disease progression to animals infected with non-mutant parasites. However, each parasite species contains ~10,000 genes and there are many different mutations for each, so even only looking at a very few genes means a lot of experimental animals are used for such studies. For technical reasons, these studies are also typically performed with strains of the parasite that do not recapitulate important aspects of the real disease. Moreover, because of variation in parasite levels between infections and different mutants of the same gene, the sensitivity of these studies to detect changes is relatively weak.
We have developed a method using contemporary genetic technology that can rapidly test the effect of mutants during infections in a complex mixture containing many 1000s of individual mutants. The method is compatible with parasite strains that capture real human disease biology and also species that cause animal disease. We have pilot data showing the method can be used in animal models of disease to robustly assess mutant fitness over the course of infections, capturing both variation between mutants in the same gene and animal-animal variation, but requiring fewer animals than would testing a single gene. In this project, we will demonstrate that the method can be translated to the most important trypanosome for human disease and validate its use to efficiently test sets of genes arising from experiments with minimal animal usage. We will also expand the use of the method to cover every gene in the genomes of trypanosomes causing human and animal disease, effectively eliminating the need for new experimental animal usage in basic tests of fitness during infection.
Demonstration of effectiveness in these infection models will encourage the wide adoption of these highly-parallel methods by labs, leading to substantial reduction in animal usage at the same time as resulting in better scientific outcome. It will also remove the need for one of the most common usages and demonstrate the potential to replace large animals with smaller models.
Technical Summary
Human African trypanosomiasis (HAT), American trypanosomiasis and leishmaniasis affect >20 million people per annum. Related parasites cause animal African Trypanosomiasis (AAT), with ~70 million cases of livestock disease per year, creating a great economic burden on rural communities in Africa, Asia and South America. Many labs internationally use functional genetics in HAT and AAT models to identify genes important for infection establishment, survival in the host, transmission, and drug resistance. However, testing of trypanosome gene function in disease models usually involves gene-by-gene approaches of low statistical power, use laboratory-adapted strains that do not represent the behaviour of field isolates, and require large numbers of experimental animals. A substantial reduction of usage could be achieved by replacing traditional methods with parallelisation.
We have designed a method for highly-parallel phenotyping of mutants, Direct RNAi-Fragment Sequencing (DRiF-Seq), that is compatible with parasite strains that capture human disease biology. Pilot data from a set of 145 genes shows the method can be used in animal models to produce robust, quantitative measures of mutant fitness. By following 1000s of individual mutants in a single infection, in vivo DRiF-Seq also captures clonal variation and is sensitive at important points in infection where traditional methods are not, but requires fewer animals than testing a single gene mutant. This Project Grant will demonstrate and validate the applicability of in vivo DRiF-Seq to test gene sets in infection models of HAT such that it can be widely adopted (Reduction). We will also expand in vivo DRiF-Seq to genome scale in trypanosomes causing HAT and the most important AAT species - effectively eliminating new experimental animal usage in basic loss-of-fitness estimates, which make up a large proportion of current usage (Reduction/Replacement).
We have designed a method for highly-parallel phenotyping of mutants, Direct RNAi-Fragment Sequencing (DRiF-Seq), that is compatible with parasite strains that capture human disease biology. Pilot data from a set of 145 genes shows the method can be used in animal models to produce robust, quantitative measures of mutant fitness. By following 1000s of individual mutants in a single infection, in vivo DRiF-Seq also captures clonal variation and is sensitive at important points in infection where traditional methods are not, but requires fewer animals than testing a single gene mutant. This Project Grant will demonstrate and validate the applicability of in vivo DRiF-Seq to test gene sets in infection models of HAT such that it can be widely adopted (Reduction). We will also expand in vivo DRiF-Seq to genome scale in trypanosomes causing HAT and the most important AAT species - effectively eliminating new experimental animal usage in basic loss-of-fitness estimates, which make up a large proportion of current usage (Reduction/Replacement).