Bacterial pathogen-host interactions are highly dynamic, regulated processes that have been primarily investigated using in vitro assays. The dynamics of bacterial pathogen-host interplay in vivo are poorly understood. Using time-resolved dual RNA-seq in a Pseudomonas plecoglossicida-Epinephelus coioides infection model, we observed that bacterial genes encoding classical virulence factors and host genes involved in immune regulation were dynamically expressed during infection. Using network inferencing, we were able to predict interspecies regulatory networks linking bacterial virulence genes to host immune genes. Together with gene co-expression network analysis of the pathogen, secY was predicted to be a key virulence gene for P. plecoglossicida pathogenicity in the host, fliN was predicted to be a less important virulence gene. The results of bioinformatics prediction were confirmed by animal infection experiments. Our work provides the first paradigm to study dynamic alterations of bacterial pathogen and host interactions based on the elucidation of time-resolved interactive transcriptomes in vivo, and may be developed into a novel and universal method for revealing the true complexity of the bacterial infection process. © 2019 Society for Applied Microbiology and John Wiley & Sons Ltd.