# Real-time drug resistance emergence and spread in Africa

> **NIH NIH P01** · UNIVERSITY OF NOTRE DAME · 2024 · $410,961

## Abstract

ABSTRACT
Genetic linkage using recombinant progeny from controlled experimental crosses is a powerful tool for locating
the genetic determinants that control important phenotypes. We have perfected the methods for quantitative trait
loci (QTL) mapping of malaria parasite traits using the humanized mouse model and have optimized bulk
segregant analysis (BSA) for streamlined identification of loci and prioritization of genes in the locus for functional
validation. The recent emergence of artemisinin resistant (ART-R) parasites in East Africa hastens the need to
understand the genes and mechanisms of fit, drug resistant parasites. The looming crisis of spreading resistance
to ART combination therapies (ACT) across Africa hinges on unique features associated with different kelch13
mutations appearing in different locales with different propensities to expand in frequency. Current surveillance
is to monitor kelch13 mutants and to assess cumbersome clinical phenotypes such as patient clearance half-life
and the labor-intensive Ring Stage Survival assay (RSA). We will partner with African researchers to target this
emerging crisis by generating experimental crosses between parasite strains that differ for important ART-R and
ACT-related traits to map the location of the genes and their mutations that control these phenotypes. We will
use both BSA selections (Aim 1) and clone-based QTL mapping (Aim 2). By judicious choice of parental lines
for constructing targeted experimental crosses Aim 1 will combine BSA with refined selection schemes; we
hypothesize that we can rapidly characterize kelch13 mutations and their phenotypic impacts, as well as their
broader whole genome profile to inform and improve surveillance. In Aim 2, we will deploy a range of novel
phenotypes we developed in the initial funding period, including a high-throughput adaptation of the traditional
RSA, along with an expansion of dosing regimens and recovery times. Aim 3 will apply these approaches to
individual progeny growth rates and comprehensive pair-wise competitive fitness. Working in concert with Core
B, we will identify additional genes and mechanisms that contribute to fit forms of ART-R. This approach will
allow us to test hypotheses about resistance evolution and characterize partner genes and pathways affected
by drug selections and identify the factors that influence the origins and spread of resistance.

## Key facts

- **NIH application ID:** 10863152
- **Project number:** 2P01AI127338-06A1
- **Recipient organization:** UNIVERSITY OF NOTRE DAME
- **Principal Investigator:** Michael T Ferdig
- **Activity code:** P01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $410,961
- **Award type:** 2
- **Project period:** 2017-08-01 → 2029-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10863152

## Citation

> US National Institutes of Health, RePORTER application 10863152, Real-time drug resistance emergence and spread in Africa (2P01AI127338-06A1). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10863152. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*