Establishment of Streptococcus suis Biofilm Infection Model In Vivo and Comparative Analysis of Gene Expression Profiles between In Vivo and In Vitro Biofilms.

Streptococcus suis is a zoonotic pathogen that continuously threatens animal husbandry and public health worldwide. Studies have shown that S. suis can cause persistent infection by forming biofilms. In this study, a model of S. suis biofilm-related infection was successfully constructed for the first time by simulating the natural infection of S. suis, and biofilm of S. suis in vivo was successfully observed in the lung tissue of infected pigs by a variety of detection methods. Subsequently, selective capture of transcribed sequences (SCOTS) was used to identify genes expressed by S. suis in vivo biofilms. Sixty-nine genes were captured in in vivo biofilms formed by S. suis for the first time by SCOTS; they were mainly involved in metabolism, cell replication, and division, transport, signal transduction, cell wall, etc. Genes related to S. suis in vitro biofilm formation were also identified by SCOTS and RNA sequencing. Approximately half of the genes captured by SCOTS in the in vivo and in vitro biofilms were found to be different. In summary, our study provides powerful clues for future exploration of the mechanisms of S. suis biofilm formation. IMPORTANCE Streptococcus suis is considered an important zoonotic pathogen, and persistent infection caused by biofilm is currently considered to be the reason why S. suis is difficult to control in swine. However, to date, a model of the biofilm of S. suis in vivo has not been successfully constructed. Here, we successfully detected biofilms of S. suis in vivo in lung tissues of piglets infected with S. suis. Selective capture of transcribed sequences and the transcriptome were used to obtain gene profiles of S. suis in vivo and in vitro biofilms, and the results showed large differences between them. Such data are of importance for future experimental studies exploring the mechanism of biofilm formation by S. suis in vivo .