Type VII secretion system promotes Streptococcus agalactiae virulence through magnesium acquisition and capsule maintenance
Abstract
Streptococcus agalactiae, also known as Group B Streptococcus (GBS), is a major pathogen causing substantial economic losses in global tilapia aquaculture. The type VII secretion systems (T7SS), present in Actinobacteria and Firmicutes, secrete effector proteins implicated in bacterial virulence, yet its functional mechanisms remain poorly defined. Here, we constructed an essC deletion mutant (∆essC) in S. agalactiae strain HN016 to investigate the role of T7SS in virulence. The ∆essC exhibited an impaired growth and declined intracellular magnesium ion concentration in THB or magnesium-limited chemically defined medium (1 mM Mg2+-CDM), these defect that were complemented by addition of wild-type culture supernatant. Transcriptomic and qRT-PCR analyses revealed altered sugar metabolism and significant downregulation of capsule biosynthesis genes (cpsA, cpsB, cpsD) in ∆essC. Consistent with this, the mutant produced markedly less capsular polysaccharide and displayed impaired capsule integrity. Furthermore, cellular assays confirmed that compared to HN016, the ∆essC mutant exhibited significantly reduced adhesion capacity, immune evasion ability and cytotoxicity. More importantly, the ∆essC mutant showed attenuated virulence in vivo, with reduced bacterial loads in host tissues and diminished ability to cross the blood-brain barrier (BBB). Our findings provide the first evidence that the T7SS influences magnesium homeostasis and is essential for maintaining capsule integrity, both of which contribute critically to pathogenicity. This study identifies T7SS as a potential target for novel therapeutic strategies against streptococcal disease in aquaculture.
Fields of Study & Subjects
Aquaculture disease management and microbiota
Bacterial Genetics and Biotechnology
Escherichia coli research studies
Publication details
- Journal / source
- Figshare
- Publication date
- 9 February 2026
- Language
- EN
- Document type
- Dataset