# Detailed analysis of Cryptosporidium non-coding gene expression

> **NIH NIH R21** · UNIVERSITY OF GEORGIA · 2020 · $223,357

## Abstract

ABSTRACT
Cryptosporidium is a zoonotic apicomplexan protist parasite recently identified as the second most prevalent
diarrheal pathogen of infants globally (1-6). It is spread via an oral-fecal route and it can be lethal in the
immunocompromised since there are no therapeutics approved for use in this population. The molecular
parasitology of Cryptosporidium has been lacking but this situation is changing with the recent advent of in vitro
culture systems, better parasite enrichment protocols and a nascent genetic system (8-11). This project proposal
focuses on an analysis of Cryptosporidium transcription and the host-pathogen interaction. Specifically, we
propose to generate candidate molecules for experimental testing of the recent hypothesis that Cryptosporidium
alters host-cell gene expression in trans, via the export of long non-coding RNA molecules (lncRNA) that alter
host cell gene expression thereby affecting host cell response and pathogenesis. Recent work by our group and
others (7, 9, 12) has revealed that the C. parvum transcriptome is complex and laden with a variety of non-coding
RNAs, both long and short. Recent work by Dr. Xian-Ming Chen has detected C. parvum transcripts in host-cell
nuclei and demonstrated that several C. parvum lncRNAs, when introduced affect host-cell gene expression (13-
18). Sadly, due to the historical limitations of working with C. parvum, transcriptional data are sorely lacking for
this important pathogen. Building on our proven track record of generating and sharing C. parvum transcriptional
data, this project proposes to systematically characterize C. parvum coding and non-coding RNAs including
small RNAs from several developmental stages of the parasite, pre- and post-infection (in vitro) using PacBio
Iso-Seq (19) to identify complete transcripts and Illumina technologies to study small RNAs as Aim 1. Aim 2
focuses on examining the host-pathogen interaction. Bioinformatics will be used to identify select lncRNA
molecules that may warrant experimental testing in the laboratory of Dr. Chen for host cell effects or knockout
via CRISPR in the laboratory of Dr. Boris Striepen. Additionally, NovaSeq, which generates billions of reads (20)
will be used for deep RNA sequencing of in vitro heavily-infected (0-48 hr) and uninfected host cells to
characterize the gene transcriptional changes occurring in both the host and pathogen at three post-infection
time-points. It is imperative to characterize transcriptional responses that may play a role in the host-pathogen
interaction. They will expose new insights into parasite survival mechanisms, the development of pathogenesis
and reveal much needed new targets for future therapeutic interventions (21-24).

## Key facts

- **NIH application ID:** 9896376
- **Project number:** 1R21AI144779-01A1
- **Recipient organization:** UNIVERSITY OF GEORGIA
- **Principal Investigator:** Jessica C Kissinger
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $223,357
- **Award type:** 1
- **Project period:** 2020-02-01 → 2022-01-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9896376

## Citation

> US National Institutes of Health, RePORTER application 9896376, Detailed analysis of Cryptosporidium non-coding gene expression (1R21AI144779-01A1). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/9896376. Licensed CC0.

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