SIMPLseq: a high-sensitivity Plasmodium falciparum genotyping and PCR contamination tracking tool

Area of Science:

• Genomic epidemiology
• Molecular diagnostics
• Parasitology

Background:

• Polymerase chain reaction (PCR) amplicon sequencing (AmpSeq) is crucial for pathogen genotyping and disease surveillance.
• Existing large AmpSeq panels struggle with low-parasitemia samples (<10 parasites/μl), limiting their use in malaria drug resistance tracking.
• Managing PCR contamination is a significant challenge in AmpSeq methodology.

Purpose of the Study:

• To develop a high-sensitivity Plasmodium falciparum AmpSeq miniplex (SIMPLseq) for low-parasitemia samples.
• To integrate a contamination detection system into the miniplex using inline barcodes.
• To evaluate SIMPLseq's sensitivity, precision, and contamination detection capabilities.

Main Methods:

• Developed a 6-locus Plasmodium falciparum AmpSeq miniplex (SIMPLseq) with inline barcodes for first-round PCR (PCR1) contamination detection.
• Assessed in silico panel diversity using whole-genome sequencing (WGS) data.
• Used mock samples to compare SIMPLseq's sensitivity and precision against the 4CAST miniplex.
• Deliberately introduced contamination events to assess detection rigor and estimated unintentional contamination rates in samples from Mali.

Main Results:

• SIMPLseq demonstrated high in silico haplotypic diversity, distinguishing 96.0% of sample pairs.
• Achieved 100% average locus detection at ≥0.5 parasites/μl and ≥50% at 0.125 parasites/μl, outperforming 4CAST.
• Inline barcoding did not significantly impact yield and correctly identified all 24 deliberately introduced PCR1 contaminations.
• Identified 39 unintentional contaminations among 1420 samples from Mali.

Conclusions:

• SIMPLseq enhances malaria genomic epidemiology by providing high-sensitivity P. falciparum genotyping and PCR contamination detection.
• The protocol is simple, uses open-source reagents, and avoids costly pre-amplification.
• SIMPLseq is valuable for classifying recurrent infections, estimating polyclonality, and applying genotypic infection endpoints in trials.