Dual transcriptomics data and detection of host-pathogen interactions

Abstract

Recent developments in high-throughput sequencing-based transcriptomics have expanded our understanding of host-pathogen interactions over the course of infection. Taking advantage of high-resolution spatiotemporal transcriptomics, we can measure simultaneously the expression profile of coding and noncoding genes in both pathogen and host without the need to physically separate their cells or RNA. Through this approach, known as “dual transcriptomics” or “RNA-Seq,” a range of immunological, metabolic, and physiological changes can be identified in both pathogen and host by in-depth analysis of interspecies gene regulatory networks. For these reasons, dual RNA-Seq has emerged as the high-throughput method of choice for elucidating the molecular mechanisms underlying host-pathogen interactions, examining the genetic characteristics of key virulence genes, assessing whole-body pathogen load, and identifying potential pathways for therapeutic targets. In this chapter, we review the most recent theoretical and experimental progress in dual RNA-Seq studies, best practices in analyzing dual RNA-Seq data, emerging applications, and ongoing challenges. This chapter provides a good starting point for researchers interested in harnessing the potential of dual RNA-Seq. © 2024 Elsevier Inc. All rights reserved.