Amplicon sequencing detects, identifies, and quantifies minority variants in mixed-species infections of Cryptosporidium parasites

Authors: TURNER, RANDI - Oak Ridge Institute For Science And Education (ORISE); NAGUIB, DOAA - Oak Ridge Institute For Science And Education (ORISE); PIERCE, ELORA - Mississippi State University; LI, ALISON - Boston University; Valente, Matthew; GLENN, TRAVIS - University Of Georgia; Rosenthal, Benjamin; KISSINGER, JESSICA - University Of Georgia; Khan, Asis

Submitted to: mBio
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 8/11/2025
Publication Date: N/A
Citation: N/A

Interpretive Summary: Cryptosporidium is a eukaryotic parasite and a global leading cause of waterborne diarrhea, with over 40 recognized species infecting livestock, wildlife, and people. While we have effective tools for detecting Cryptosporidium in clinical and agriculture water samples, there is still a need for a method that can efficiently identify known species as well as infections with multiple Cryptosporidium species, which are increasingly being reported. In this study, we utilized sequencing of a specific region to develop a sensitive and accurate identification workflow for Cryptosporidium species based on high-throughput sequencing. This method can distinguish between all 40 recognized species and accurately detect the distinct species present when there is a mixed (multiple species) infection. Our approach provides a sensitive and reliable means to identify Cryptosporidium species in complex clinical and agricultural samples. This information can be incorporated into to improve clinical diagnostic methods used by clinicians or veterinarians to enable biosurveillance and understand the transmission of disease to help minimize the risk of contamination in agricultural products and disease in humans.

Technical Abstract: Cryptosporidium is a globally endemic parasite genus with over 40 recognized species. While C. hominis and C. parvum are responsible for most human infections, human cases involving other species have also been reported. Furthermore, there is increasing evidence of simultaneous infections with multiple species. Therefore, we devised a new means to identify various species of Cryptosporidium in mixed infections by sequencing a 431 bp amplicon of the 18S rRNA gene encompassing two variable regions. Using the DADA2 pipeline, amplicons were first identified to a genus using the SILVA 132 reference database; then Cryptosporidium amplicons to a species using a custom database. This approach demonstrated sensitivity, successfully detecting and accurately identifying as little as 0.001 ng of C. parvum DNA in a complex stool background. Notably, we differentiated mixed infections and demonstrated the ability to identify potentially novel species of Cryptosporidium both in situ and in vitro. Using this method, we identified Cryptosporidium parvum in Egyptian rabbits with three samples showing minor mixed infections. By contrast, no mixed infections were detected in Egyptian children, who were primarily infected with C. hominis. Thus, this pipeline provides a sensitive tool for Cryptosporidium species-level identification, allowing for the detection and accurate identification of minor variants and mixed infections.