Background: The lack of a continuous long-term in vitro culture system for Plasmodium vivax severely limits our knowledge of pathophysiology of the most widespread malaria parasite. To gain direct understanding of P. vivax human infections, we used Next Generation Sequencing data mining to unravel parasite in vivo expression profiles for P. vivax, and P. falciparum as comparison.
Results: We performed cloud and local computing to extract parasite transcriptomes from publicly available raw data of human blood samples. We developed a Poisson Modelling (PM) method to confidently identify parasite derived transcripts in mixed RNAseq signals of infected host tissues. We successfully retrieved and reconstructed parasite transcriptomes from infected patient blood as early as the first blood stage cycle; and the same methodology did not recover any significant signal from controls. Surprisingly, these first generation blood parasites already show strong signature of transmission, which indicates the commitment from asexual-to-sexual stages. Further, we place the results within the context of P. vivax's complex life cycle, by developing mathematical models for P. vivax and P. falciparum and using sensitivity analysis assess the relative epidemiological impact of possible early stage transmission.
Conclusion: The study uncovers the earliest onset of P. vivax blood pathogenesis and highlights the challenges of P. vivax eradication programs.
Keywords: Disease transmission; Malaria; Mathematical modelling; Plasmodium vivax; RNAseq.