Selective whole-genome amplification reveals population genetics ofLeishmania braziliensisdirectly from patient skin biopsies

Abstract

In Brazil, Leishmania braziliensis is the main causative agent of the neglected tropical disease, cutaneous leishmaniasis (CL). CL caused by L. braziliensis can present on a spectrum of disease severity with high rate of treatment failure. Yet the parasite factors that may contribute to disease presentation and treatment outcome are not well understood, in part because successfully isolating and culturing parasites from patient lesions remains a major technical challenge. Here we describe the development of selective whole genome amplification (SWGA) for Leishmania and show that this method enables culture-independent analysis of parasite genomes obtained directly from primary patient skin samples, allowing us to circumvent artifacts associated with adaptation to culture. We show that SWGA can be applied to multiple Leishmania species residing in different host species, suggesting that this method is broadly useful in both experimental infection models and clinical studies. Finally, we show that parasite genome sequencing data generated by SWGA of skin biopsies collected from patients in Corte de Pedra, Bahia, Brazil exhibit substantial genetic diversity and can be integrated with published whole genome data from parasite isolates to identify variants associated with high treatment failure rates observed in Northeast Brazil.

A fast machine-learning-guided primer design pipeline for selective whole genome amplification

“…Nevertheless, it is expected that approximately half of all designed sets are likely to give strong and even selective amplification results such that few sets need to be experimentally evaluated by researchers. Also similar to prior results [20], protocols developed with swga2.0 are expected to retain the ability to investigate within-host microbial diversity using SWGA enrichment [45], without introducing errors, as the SWGA biochemistry remains identical (S4 Table ). These advances reduce the up-front cost of developing the SWGA primer sets necessary for population genomic studies.…”

“…However, learning from prior data has its own challenges due to both limited data availability and experimental noise associated with short-read sequencing data. Despite these challenges, the swga2.0 program PLOS COMPUTATIONAL BIOLOGY provides the necessary pipeline to rapidly identify primer sets that have a high probability of selectively amplifying any target genome from any background DNA sample [45].…”

Detecting complex infections in Trypanosomatids using whole genome sequencing

“…Different strains might have different growth rates in media, and secondary clones in low proportions might be outcompeted in culture. The methodologies to sequence parasite genomes directly from patient tissue, such as Selective Whole Genome Ampli cation (SWGA) [72][73][74], SureSelect [22,75] and Nanopore adaptive sampling [76,77] are improving in the last years, and might allow WGS in Trypanosomatids to be done in large scale without a culturing step in a affordable way in the future. This might allow complex infection assessments using WGS data to be performed directly from host tissues, as long as allelic proportions are not altered by these methods.…”