Challenges and solutions for analysing dual RNA ‐seq data for non‐model host–pathogen systems

RNA-seq analysis of parasitism by Intoshia linei (Orthonectida) reveals protein effectors of defence, communication, feeding and growth

Orthonectida is a group of multicellular endoparasites of a wide range of marine invertebrates. Their parasitic stage is a multinuclear shapeless plasmodium infiltrating host tissues. The development of the following worm-like sexual generation takes place within the cytoplasm of the plasmodium. The existence of the plasmodial stage and the development of a sexual stage within the plasmodium are unique features to Bilateria. However, the molecular mechanisms that maintain this peculiar organism, and hence enable parasitism in orthonectids, are unknown. Here, we present the first-ever RNA-seq analysis of the plasmodium, aimed at the identification and characterization of the plasmodium-specific protein-coding genes and corresponding hypothetical proteins that distinguish the parasitic plasmodium stage from the sexual stage of the orthonectid Intoshia linei Giard, 1877, parasite of nemertean Lineus ruber Müller, 1774. We discovered 119 plasmodium-specific proteins, 82 of which have inferred functions based on known domains. Thirty-five of the detected proteins are orphans, at least part of which may reflect the unique evolutionary adaptations of orthonectids to parasitism. Some of the identified proteins are known effector molecules of other endoparasites suggesting convergence. Our data indicate that the plasmodium-specific proteins might be involved in the plasmodium defense against the host, host-parasite communication, feeding and nutrient uptake, growth within the host, and support of the sexual stage development. These molecular processes in orthonectids have not been described before, and the particular protein effectors remained unknown until now.

dRNASb: a systems biology approach to decipher dynamics of host-pathogen interactions using temporal dual RNA-seq data

Infection triggers a dynamic cascade of reciprocal events between host and pathogen wherein the host activates complex mechanisms to recognise and kill pathogens while the pathogen often adjusts its virulence and fitness to avoid eradication by the host. The interaction between the pathogen and the host results in large-scale changes in gene expression in both organisms. Dual RNA-seq, the simultaneous detection of host and pathogen transcripts, has become a leading approach to unravelling complex molecular interactions between the host and the pathogen and is particularly informative for intracellular organisms. The amount of in vitro and in vivo dual RNA-seq data is rapidly growing, which demands computational pipelines to effectively analyse such data. In particular, holistic, systems-level, and temporal analyses of dual RNA-seq data are essential to enable further insights into the host-pathogen transcriptional dynamics and potential interactions. Here, we developed an integrative network-driven bioinformatics pipeline, dRNASb, a systems biology-based computational pipeline to analyse temporal transcriptional clusters, incorporate molecular interaction networks (e.g. protein-protein interactions), identify topologically and functionally key transcripts in host and pathogen, and associate host and pathogen temporal transcriptome to decipher potential between-species interactions. The pipeline is applicable to various dual RNA-seq data from different species and experimental conditions. As a case study, we applied dRNASb to analyse temporal dual RNA-seq data of Salmonella-infected human cells, which enabled us to uncover genes contributing to the infection process and their potential functions and to identify putative associations between host and pathogen genes during infection. Overall, dRNASb has the potential to identify key genes involved in bacterial growth or host defence mechanisms for future uses as therapeutic targets.