Modeling Co-Infection by Streptococcus suis and Haemophilus parasuis Reveals Influences on Biofilm Formation and Host Response.

Abstract

Streptococcus suis (S. suis) and Haemophilus parasuis (H. parasuis) are two primary pathogens currently affecting the porcine industry. They often cause encephalitis and arthritis. They also frequently co-infect in clinical settings. In the current study, we identified significant correlations between S. suis and H. parasuis. The results from CI versus RIR suggested that S. suis and H. parasuis were competitive in general. Compared to mono-species biofilm, the biomass, bio-volume, and thickness of mixed-species biofilms were significantly higher, which was confirmed using crystal violet staining, confocal laser scanning microscopy, and scanning electron microscopy. Compared to mono-species biofilm, the viable bacteria in the mixed-species biofilms were significantly lower, which was confirmed using the enumeration of colony-forming units (CFU cm-2). The susceptibility of antibiotics in the co-culture decreased in the planktonic state. In contrast, biofilm state bacteria are significantly more difficult to eradicate with antibiotics than in a planktonic state. Whether in planktonic or biofilm state, the expression of virulence genes of S. suis and H. parasuis in mixed culture was very different from that in single culture. Subsequently, by establishing a mixed infection model in mice, we found that the colonization of the two pathogens in organs increased after mixed infection, and altered the host's inflammatory response. In summary, our results indicate that S. suis and H. parasuis compete when co-cultured in vitro. Surprisingly, S. suis and H. parasuis synergistically increased colonization capacity after co-infection in vivo. This study elucidated the interaction between S. suis and H. parasuis during single infections and co-infections. Future studies on bacterial disease control and antibiotic treatment should consider the interaction of mixed species.

• Authors: Mengxia Gao, Jing Zuo, Yamin Shen, Shuo Yuan, Shuji Gao, Yuxin Wang, Yang Wang, Li Yi
• Journal: Animals : an open access journal from MDPI (Animals (Basel)) Vol. 13 Issue 9 (Apr 29 2023) ISSN: 2076-2615 [Print] Switzerland
• PMID: 37174548 (Publication Type: Journal Article)