Next-generation sequencing of barcoded Plasmodium falciparum mutants to dissect parasite fitness costs associated with drug resistance

Malaria is a disease that infected 214 million people in 2015, with 438000 of these infections being fatal. Although this is a great improvement on recent years, many challenges to the effective treatment and elimination of Malaria remain. One of the greatest challenges is the parasite's ability rapidly to develop resistance to antimalarial drugs. To date, the parasite developed resistance to every drug that it has ever been challenged with, and resistance has recently been observed to current first-line treatment drugs, artemisinin-based combination therapies. GSK has developed millions of compounds, the TCAMs, with diverse chemically active backbones, many of which target P.falciparum in cellular screens. One strategy to slow the development of resistance is to continually identify new drugs with novel targets within the parasite.
Another important part of combating drug resistance is to understand how resistance develops, and how it affects the fitness of the parasite. Many mutations that confer resistance to antimalarial drugs, can have a deleterious effect on parasite fitness. There is a very delicate balance between resistance to antimalarial compounds and the optimal function of the pathway that the mutation affects. Often after a parasite stops being exposed to a drug the resistance mutation soon disappears from the population. Currently, there is no standard experiment for measuring mutant parasite fitness.
Until recently the study of resistance by large-scale genome editing was very inefficient, due to the lack of tools to edit the genome in P.falciparum. The discovery of CRISPR/Cas9 however, has vastly increased the rate at which editing can occur. In this project, CRISPR will be used to introduce resistant mutations found in field isolates of P. falciparum into the respective alleles of lab strains with the same background. The known resistant mutations generated in key genes involved in drug resistance including PfCRT (chloroquine), cytBC1 (atovaquone), kelch13 (artemisinin), and DHFR (pyrimethamine) - as well as targets of new compounds under development or in clinical trials (e.g. PfATP4, PfPI4K, PfCARL, PfeEF2). A limited number of double mutations will also be created (e.g. PfATP4/PfCDPK5 or PfPI4K/PfRab11A). It is expect that a library of about 50 mutant parasite lines would be produced in all.
The mutant parasite lines would be distinguished from one another by utilizing bar-seq technology. A series of unique eleven base pair barcodes would be inserted into the Rh3 locus of the parasite lines. In this way by deep sequencing, different mutant parasites can be distinguished from one another, while they grow in competition with one another in the same culture, under identical conditions. Parallel quantification of barcoded lines by next-generation sequencing, will pinpoint resistance mutations that confer the greatest fitness cost, identifying biological pathways that tolerate mutation and those that do not.
This library of pooled mutants will allow profiling of resistance to novel antimalarial compounds from the GSK TCAMs. If any resistance mutation already exists to this compound this can quickly be discerned by sequencing the bar code of the surviving parasites. On the other hand, compounds that inhibit the growth of all the parasites in the pool probably target novel pathways and would require further investigation into their mode of action. The general fitness of these mutant parasites will also be assessed by growing them together under as a variety of challenge conditions including oxidative stress, and low nutrient media.