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

SIMPLseq:一种高灵敏度的恶性疟原虫基因分型和PCR污染追踪工具

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Abstract

BACKGROUND: Pathogen genotyping via polymerase chain reaction (PCR) amplicon sequencing (AmpSeq) is an informative disease surveillance tool. Several large AmpSeq panels containing > 100 multiplexed PCR amplicons have been developed as alternatives to whole-genome sequencing (WGS) methods for the Plasmodium spp. parasites that cause malaria, especially for parasite drug resistance tracking and relatedness analysis. However, these large multiplexes typically yield sparse data for samples with parasitemia below 10 parasites/μl. Smaller multiplexes optimized for low-parasitemia genotyping have received insufficient methodological work but have the potential to serve multiple important use cases. Managing contamination risk during PCR steps represents another key methodological gap that requires attention in the AmpSeq field. METHODS: Here we describe a new 6-locus Plasmodium falciparum AmpSeq 'miniplex' (SIMPLseq) optimized for high-sensitivity analyses that also integrates a contamination detection system based on well-specific inline barcodes applied during first-round PCR (PCR1; in addition to conventional indexing steps during second-round PCR). We assess panel diversity using publicly available WGS and use mock samples to estimate sensitivity and precision relative to 4CAST, a previously described miniplex. We also create deliberate contamination events to assess contamination detection rigor and estimate unintentional contamination rates during assay application to malaria-infected dried blood spots collected in Mali. RESULTS: SIMPLseq shows high haplotypic diversity in silico, distinguishing 96.0% of sample pairs drawn randomly from 12 subnational sample sets. SIMPLseq outperforms 4CAST in sensitivity analyses, achieving 100% average locus detection at ≥ 0.5 parasites/μl and ≥ 50% average locus detection at 0.25 and 0.125 parasites/μl, with zero false-positive haplotypes at a 1% detection limit across 25 replicates. Inline barcoding does not significantly affect yield when using a 'sentinel' design, whereby one of the six multiplexed PCR1 primer pairs contains the well-specific sequence pair. Sentinel barcoding correctly identified all 24 contaminations introduced deliberately during PCR1 product handling and identified 39 unintentional contaminations in the 1420-sample Malian run. CONCLUSIONS: SIMPLseq significantly extends the malaria genomic epidemiology toolkit, coupling high-sensitivity P. falciparum genotyping with PCR contamination detection in a simple laboratory protocol that uses only open-source reagents and does not require a costly pre-amplification step. Key prospective use cases for SIMPLseq include recurrent infection classification, polyclonality estimation, and genotypic infection endpoint application to intervention efficacy trials.

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