CryptoGenotyper: A new bioinformatics tool for rapid Cryptosporidium identification

Area of Science:

• * Parasitology and Molecular Biology
• * Foodborne and Waterborne Pathogen Research

Background:

• * Cryptosporidium is a protozoan parasite causing gastrointestinal illness (cryptosporidiosis) in humans and animals.
• * Zoonotic and anthroponotic transmission routes are common for Cryptosporidium.
• * Accurate genotyping of Cryptosporidium relies on analyzing small subunit (SSU) rRNA and gp60 genes, often via PCR and Sanger sequencing.

Purpose of the Study:

• * To develop an automated tool for analyzing Cryptosporidium Sanger sequencing data.
• * To improve the efficiency and accuracy of Cryptosporidium genotyping.
• * To address limitations of manual sequence chromatogram analysis, including errors and time consumption.

Main Methods:

• * Development of CryptoGenotyper, a software tool for raw Sanger sequencing data analysis.
• * Utilizes a curated reference database for sequence classification.
• * Incorporates heterozygous base calling algorithms for improved SSU rRNA gene analysis.

Main Results:

• * CryptoGenotyper achieved high genotyping accuracy: 99.3% for SSU rRNA single sequences and 95.1% for mixed sequences.
• * Accurate subtyping of 95.6% of gp60 sequences was achieved without manual intervention.
• * The tool successfully resolved previously inconclusive data from heterozygous peaks.

Conclusions:

• * CryptoGenotyper provides a user-friendly, fast, and reproducible method for analyzing Cryptosporidium SSU rRNA and gp60 gene sequences.
• * The tool enhances the reliability of Cryptosporidium genotyping, aiding in understanding transmission dynamics.
• * Automated analysis reduces human error and bias in sequence data interpretation.