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. 2025 Mar 19:18:1521-1537.
doi: 10.2147/IDR.S507908. eCollection 2025.

AI-2 Signaling: A Potential Driver of Bacteremia in Non-Typhoidal Salmonella Infections

Affiliations

AI-2 Signaling: A Potential Driver of Bacteremia in Non-Typhoidal Salmonella Infections

Yu Li et al. Infect Drug Resist. .

Abstract

Introduction: Non-typhoidal Salmonella (NTS) infections typically present as localized inflammation near the intestinal mucosal epithelium. However, some NTS strains can breach the intestinal barrier and enter the bloodstream, leading to bacteremia and severe systemic infections. The mechanisms by which NTS invades the bloodstream remain unclear.

Methods: In this study, we isolated 36 NTS strains from patients with diarrhea and bacteremia at First Affiliated Hospital of Huzhou University. Strains represented two distinct clinical manifestations, and were subjected to whole-genome sequencing, comparative genomics, and genetic differentiation analysis to identify genes potentially involved in bloodstream invasion. Additionally, we conducted inhibition assays using quercetin, a chemical inhibitor of the identified gene pathways, to validate our findings.

Results: Our analysis revealed that genes distinguishing the bloodstream Salmonella isolates from the fecal Salmonella isolates were primarily involved in the AI-2 quorum sensing pathway and biofilm-associated protein transport. Subsequent biofilm formation assays demonstrated that the bloodstream isolates exhibited significantly higher biofilm formation capacity compared to the fecal isolates. Upon the addition of quercetin, biofilm formation was equally inhibited in both groups. Collectively, these findings suggest that genes involved in the AI-2 pathway and biofilm-associated protein transport may be key factors contributing to the development of bacteremia in NTS infections.

Keywords: AI-2; biofilm; comparative genomics analysis; invasive non-typhoidal Salmonella; quorum sensing; whole genome sequencing.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Rainbow Plot of Sample Information, this comprehensive dataset visualization includes: Sample Origins, Patient Age Stratification, MLST Profiles, Multi-Drug Resistance Information.
Figure 2
Figure 2
The heat map of ARGs and plasmids in the studied Salmonella isolates. The presence of antibiotic resistance genes was marked with dark green color, while the absence was marked with light green color. The presence of plasmids was marked with big blue circles, while the absence was marked with little white circles.
Figure 3
Figure 3
The heat map of SPIs in the studied Salmonella isolates. The presence of SPIs was marked with dark green color, while the absence was marked with light green color.
Figure 4
Figure 4
The phylogenetic tree, constructed using core genome SNPs and the General Time Reversible (GTR) model, encompasses 36 Salmonella strains and incorporates metadata on year of isolation, serotype, and MLST. The tree is rooted with Salmonella enterica serovar Typhimurium LT2. The black bolded labels represent the blood group, while the non-bolded labels represent the fecal group.
Figure 5
Figure 5
Strain pan-genome and differential gene analysis results: (A) The pangenome analysis of the 36 isolates is illustrated as a flower plot, where the central number represents the count of core genes. The proximal part of each petal indicates the number of accessory genes, while the distal part denotes the number of unique genes and exclusively absent genes. (B) The pangenome analysis of the 30 fecal isolates is illustrated as a flower plot, where the central number represents the count of core genes. The proximal part of each petal indicates the number of accessory genes, while the distal part denotes the number of unique genes and exclusively absent genes. (C) The pangenome analysis of the 6 blood isolates is illustrated as a flower plot, where the central number represents the count of core genes. The proximal part of each petal indicates the number of accessory genes, while the distal part denotes the number of unique genes and exclusively absent genes. (D)Venn diagram of differentially expressed genes between blood and fecal core genomes.
Figure 6
Figure 6
The analysis of COG functional annotations.
Figure 7
Figure 7
KEGG pathway enrichment analysis.
Figure 8
Figure 8
(A) Comparison of biofilm staining at OD595nm between blood and fecal groups was conducted, with p< 0.05 considered as the threshold for statistical significance (*). (B) Comparison of biofilm inhibition rates between the blood and fecal groups after the addition of the AI-2 inhibitor. “NA” indicates no statistical significance. (C) The determination of biofilm formation in the microtiter plates is evidenced by the strong blue coloration of the crystal violet staining on the walls and bottom of each well. The positive reaction is evidenced for the Salmonella isolates, validated by the negative control (LB medium only) and positive (AI-2 inhibitor).

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