Co-transcriptomic Analysis by RNA Sequencing to Simultaneously Measure Regulated Gene Expression in Host and Bacterial Pathogen

• Published in: Methods in molecular biology (Clifton, N.J.) Vol. 1390; p. 145
• Main Authors: Ravasi, Timothy, Mavromatis, Charalampos Harris, Bokil, Nilesh J, Schembri, Mark A, Sweet, Matthew J
• Format: Journal Article
• Language: English
• Published: United States 2016
• Subjects: Animals; Bacteria - genetics; Bacterial Infections - genetics; Bacterial Infections - immunology; Bacterial Infections - microbiology; Gene Expression Profiling; Gene Expression Regulation; Host-Pathogen Interactions - genetics; Host-Pathogen Interactions - immunology; Immunity, Innate; Macrophages - immunology; Macrophages - metabolism; Macrophages - microbiology; Mice; Microbial Viability - immunology; Sequence Analysis, RNA; Signal Transduction; Transcriptome; Host-pathogen; RNA sequencing; Intracellular pathogens; Transcriptomics; Toll-like receptors; Innate immunity; Urinary tract infections; Macrophages; Uropathogenic E. coli
• ISSN: 1940-6029
• DOI: 10.1007/978-1-4939-3335-8_10

Intramacrophage pathogens subvert antimicrobial defence pathways using various mechanisms, including the targeting of host TLR-mediated transcriptional responses. Conversely, TLR-inducible host defence mechanisms subject intramacrophage pathogens to stress, thus altering pathogen gene expression programs. Important biological insights can thus be gained through the analysis of gene expression changes in both the host and the pathogen during an infection. Traditionally, research methods have involved the use of qPCR, microarrays and/or RNA sequencing to identify transcriptional changes in either the host or the pathogen. Here we describe the application of RNA sequencing using samples obtained from in vitro infection assays to simultaneously quantify both host and bacterial pathogen gene expression changes, as well as general approaches that can be undertaken to interpret the RNA sequencing data that is generated. These methods can be used to provide insights into host TLR-regulated transcriptional responses to microbial challenge, as well as pathogen subversion mechanisms against such responses.