PROJECT SUMMARY:
Cryptosporidiosis, the diarrheal disease caused by Cryptosporidium parasites, is amongst the most
important causes of life-threatening diarrhea in children globally and causes incurable diarrhea in AIDS patients.
The only approved treatment is just over 50% effective for children and equivalent to a placebo for AIDS patients.
Improved anticryptosporidials are in development, but there is a concern that drug resistance will emerge if they
are not used carefully. Stressing the risk of resistance, drug-resistant mutants with amino acid-coding target
mutations emerged in under a week of drug treatment in a recent dairy calf study. The Cryptosporidium drug
development field is in some ways reminiscent of that for the related malaria parasite in the 1940s when
chloroquine became available and the inevitability of drug resistance and need for strategies to prevent it were
poorly understood. Based on the hard lessons from malaria and antimicrobial resistance in general, combination
therapy is now the standard for treating malaria and many other infectious diseases where the risk of resistance
is high (e.g., AIDS, tuberculosis). This R21 grant is based on the premise that a basic understanding of
anticryptosporidial resistance and its evolution is critical to maximize the benefits of newly developed drugs. The
current goal is to develop the essential methods to study Cryptosporidium drug resistance that are needed to
facilitate drug lead prioritization and, should combination therapy be needed, to identify optimal drug-drug
combinations. The strategy exploits knowledge gleaned from the dairy calf experiment noted above regarding
numbers of parasites and time required to select for Cryptosporidium resistance, and knowledge of resistance-
conferring mutations for two positive control compounds. Aim 1 begins with optimizing a method to select drug-
resistant parasites in immunocompromised mice by directly comparing results with wildtype C. parvum and a
`mutator' C. parvum line, with or without backcrossing resistant strains against wildtype to identify relevant
mutations. The optimized method will then be used to determine the relative genetic barrier to resistance for
three promising anticryptosporidial lead series, and resistance-linked mutations will be studied using CRISPR.
In aim 2, the effect of three known resistance-conferring mutations on parasite growth and in vivo reproductive
fitness will be determined when they are introduced alone or in combinations of two, which will provide methods
to formally measure fitness and identify epistasis between different resistance-conferring mutations. This
application addresses a time-sensitive and critical issue: Along with key data for three promising
anticryptosporidial lead chemical series, these studies will yield the methods needed to incorporate drug-
resistance testing into early stages of anticryptosporidial development and will lay the groundwork for future
development of a computer simulation model to guide animal work and begin selecting the most promising drug
combinations.