Anita Ghansah | bioRxiv Science

bioRxiv2016

Whole genome sequencing of Plasmodium falciparum from dried blood spots using selective whole genome amplification

Translating genomic technologies into healthcare applications for the malaria parasite Plasmodium falciparum has been limited by the technical and logistical difficulties of obtaining high quality clinical samples from the field. Sampling by dried blood spot (DBS) finger-pricks can be performed safely and efficiently with minimal resource and storage requirements compared with venous blood (VB). Here, we evaluate the use of selective whole genome amplification (sWGA) to sequence the P. falciparum genome from clinical DBS samples, and compare the results to current methods using leucodepleted VB. Parasite DNA with high (> 95%) human DNA contamination was selectively amplified by Phi29 polymerase using short oligonucleotide probes of 8-12 mers as primers. These primers were selected on the basis of their differential frequency of binding the desired (P. falciparum DNA) and contaminating (human) genomes. Using sWGA method, we sequenced clinical samples from 156 malaria patients, including 120 paired samples for head-to-head comparison of DBS and leucodepleted VB. Greater than 18-fold enrichment of P. falciparum DNA was achieved from DBS extracts. The parasitaemia threshold to achieve >5x coverage for 50% of the genome was 0.03% (40 parasites per 200 white blood cells). Over 99% SNP concordance between VB and DBS samples was achieved after excluding missing calls. The sWGA methods described here provide a reliable and scalable way of generating P. falciparum genome sequence data from DBS samples. Our data indicate that it will be possible to get good quality sequence data on most if not all drug resistance loci from the majority of symptomatic malaria patients. This technique overcomes a major limiting factor in P. falciparum genome sequencing from field samples, and paves the way for large-scale epidemiological applications.

Genomics↗

bioRxiv2016

ADRes: a computational pipeline for detecting molecular markers of Anti-malarial Drug Resistance, from Sanger sequencing data

BackgroundMalaria control efforts are stifled by the emergence and dispersal of parasite strains resistant to available anti-malarials. Amino acid changes in specific positions of proteins encoded by Plasmodium falciparum genes pfcrt, dhps, dhfr, and pfmdr1 are used as molecular markers of resistance to antimalarials such as chloroquine, sulphadoxine-pyrimethamine, as well as artemisinin derivatives. However, a challenge to the detection of single nucleotide polymorphisms (SNPs) in codons responsible for these amino acid changes, in several samples, is the scarcity of automated computational pipelines for molecular biologists to; rapidly analyze ABI (Applied Biosystems) Sanger sequencing data spanning the codons of interest in order to characterize these codons and detect these molecular markers of drug resistance. The pipeline described here is an attempt to address this need.\n\nMethodThis pipeline is a combination of existing tools, notably SAMtools and Burrows Wheeler Aligner (BWA), as well as custom Python and BASH scripts. It is designed to run on the UNIX shell, a command line interpreter. To characterize the codons associated with anti-malarial drug resistance (ADR) in a particular gene using this pipeline, the following options are required; a path to reference coding sequence of the gene in FASTA format, gene symbol (pfcrt, pfmdr1, dhps or dhfr), and a path to the directory of ABI sequencing trace files for the samples. With these inputs, the pipeline performs base calling and trimming, sequence alignment, and alignment parsing.\n\nResultsThe output of the pipeline is a CSV (Comma-separated values) file of sample names, codons and their corresponding encoded amino acids. The data generated can be readily analyzed using widely available statistical or spreadsheet software, to determine the frequency of molecular markers of resistance to anti-malarials such as chloroquine, sulphadoxine-pyrimethamine and artemisinin derivatives.\n\nConclusionsADRes is a quick and effective pipeline for detecting common molecular markers of anti-malarial drug resistance, and could be a useful tool for surveillance. The code, description, and instructions for using this pipeline are publicly available at http://setfelix.github.io/ADRes.

Bioinformatics↗