A Comprehensive RNA Handling and Transcriptomics Guide for High-Throughput Processing of Plasmodium Blood-Stage Samples.

Abstract

Abstract Background Sequencing technology advancements opened new opportunities to use transcriptomics for studying malaria pathology and epidemiology. Even though in recent years the study of whole parasite transcriptome proved to be essential in understanding parasite biology there is no compiled up-to-date reference protocol for the efficient generation of transcriptome data from growing number of samples. Here, we present a comprehensive methodology on how to preserve, extract, amplify, and sequence full-length mRNA transcripts from Plasmodium -infected blood samples that can be fully streamlined for high-throughput studies. Results We evaluated the utility of various commercially available RNA-preserving reagents in a range of storage conditions. Similarly, we compared several RNA extraction protocols and established the one most suitable for the extraction of high-quality total RNA from low-parasitemia and low-volume blood samples. Furthermore, we updated the criteria needed to evaluate the quality and integrity of Plasmodium RNA in the presence of human RNA. Optimization of SMART-seq2 amplification method to better suit AT-rich P. falciparum RNA samples allowed us to generate high-quality transcriptomes from as little as 10ng of total RNA and a lower parasitemia limit of 0.05%. Finally, we designed a modified method for depletion of unwanted human hemoglobin transcripts using in vitro CRISPR-Cas9 treatment, thus improving parasite transcriptome coverage in low parasitemia samples. To prove the functionality of the pipeline for both laboratory and field strains, we generated the highest 2-hour resolution RNA-seq transcriptome for Plasmodium falciparum 3D7 intraerythrocytic lifecycle available up-to-date and also applied the entire protocol to create the largest transcriptome data from Southeast Asian field isolates. Conclusions Overall, our methodology presents an inclusive pipeline for generation of good quality transcriptomic data from a diverse range of Plasmodium -infected blood samples with varying parasitemia and RNA inputs. The flexibility of this pipeline to be adapted to robotic handling will facilitate both small and large scale future transcriptomic studies in the field of malaria.