Temperate phages (active prophages induced from bacteria) help control pathogenicity, modulate community structure, and maintain gut homeostasis. Complete phage genome sequences are indispensable for understanding phage biology. Traditional plaque techniques are inapplicable to temperate phages due to their lysogenicity, curbing their identification and characterization. Existing bioinformatics tools for prophage prediction usually fail to detect accurate and complete temperate phage genomes. This study proposes a novel computational temperate phage detection method (TemPhD) mining both the integrated active prophages and their spontaneously induced forms (temperate phages) from next-generation sequencing raw data. Applying the method to the available dataset resulted in 192 326 complete temperate phage genomes with different host species, expanding the existing number of complete temperate phage genomes by more than 100-fold. The wet-lab experiments demonstrated that TemPhD can accurately determine the complete genome sequences of the temperate phages, with exact flanking sites, outperforming other state-of-the-art prophage prediction methods. Our analysis indicates that temperate phages are likely to function in the microbial evolution by (i) cross-infecting different bacterial host species; (ii) transferring antibiotic resistance and virulence genes and (iii) interacting with hosts through restriction-modification and CRISPR/anti-CRISPR systems. This work provides a comprehensively complete temperate phage genome database and relevant information, which can serve as a valuable resource for phage research.

Quorum sensing (QS) is a cell-to-cell communication mechanism that regulates bacterial pathogenicity, biofilm formation, and antibiotic sensitivity. Among the identified quorum sensing, AI-2 QS exists in both Gram-negative and Gram-positive bacteria and is responsible for interspecies communication. Recent studies have highlighted the connection between the phosphotransferase system (PTS) and AI-2 QS, with this link being associated with protein-protein interaction (PPI) between HPr and LsrK. Here, we first discovered several AI-2 QSIs targeting the LsrK/HPr PPI site through molecular dynamics (MD) simulation, virtual screening, and bioassay evaluation. Of the 62 compounds purchased, eight compounds demonstrated significant inhibition in LsrK-based assays and AI-2 QS interference assays. Surface plasmon resonance (SPR) analysis confirmed that the hit compound 4171-0375 specifically bound to the LsrK-N protein (HPr binding domain, KD = 2.51 × 10−5 M), and therefore the LsrK/HPr PPI site. The structure-activity relationships (SARs) emphasized the importance of hydrophobic interactions with the hydrophobic pocket and hydrogen bonds or salt bridges with key residues of LsrK for LsrK/HPr PPI inhibitors. These new AI-2 QSIs, especially 4171-0375, exhibited novel structures, significant LsrK inhibition, and were suitable for structural modification to search for more effective AI-2 QSIs.

Introduction: Quorum sensing (QS) is a bacterial intracellular and intercellular communication system that regulates virulence factor production, biofilm formation, and antibiotic sensitivity. Quorum-sensing inhibitors (QSIs) are a novel class of antibiotics that can effectively combat antibiotic resistance. Autoinducer-2 (AI-2) is a universal signaling molecule that mediates inter- and intraspecies QS systems among different bacteria. Furthermore, LsrK plays an important role in regulating the activity and stability of the intracellular AI-2 signaling pathway. Thus, LsrK is considered an important target for the development of QSIs.Methods: We designed a workflow integrating molecular dynamic (MD) simulations, virtual screening, LsrK inhibition assays, cell-based AI-2-mediated QS interference assays, and surface plasmon resonance (SPR)-based protein affinity assays to screen for potential LsrK kinase inhibitors.Results: MD simulation results of the LsrK/ATP complex revealed hydrogen bonds and salt bridge formation among four key residues, namely, Lys 431, Tyr 341, Arg 319, and Arg 322, which are critical for the binding of ATP to LsrK. Furthermore, MD simulation results indicated that the ATP-binding site has an allosteric pocket that can become larger and be occupied by small molecule compounds. Based on these MD simulation results, a constraint of forming at least one hydrogen bond with Arg 319, Arg 322, Lys 431, or Tyr 341 residues was introduced when performing virtual screening using Glide’s virtual screening workflow (VSW). In the meantime, compounds with hydrophobic group likely to interact with the allosteric hydrophobic pocket are preferred when performing visual inspection. Seventy-four compounds were selected for the wet laboratory assays based on virtual screening and the absorption, distribution, metabolism, and excretion (ADME) properties of these compounds. LsrK inhibition assays revealed 12 compounds inhibiting LsrK by more than 60% at a 200 μM concentration; four of these (Y205-6768, D135-0149, 3284–1358, and N025-0038) had IC50 values below 50 μM and were confirmed as ATP-competitive inhibitors. Six of these 12 LsrK inhibitors exhibited high AI-2 QS inhibition, of which, Y205-6768 had the highest activity with IC50 = 11.28 ± 0.70 μM. The SPR assay verified that compounds Y205-6768 and N025-0038 specifically bound to LsrK. MD simulation analysis of the docking complexes of the four active compounds with LsrK further confirmed the importance of forming hydrogen bonds and salt bridges with key basic amino acid residues including Lys 431, Tyr 341, Arg 319, and Arg 322 and filling the allosteric hydrophobic pocket next to the purine-binding site of LsrK.Discussion: Our study clarified for the first time that there is an allosteric site near the ATP-binding site of Lsrk and that it enriches the structure–activity relationship information of Lsrk inhibitors. The four identified compounds showed novel structures, low molecular weights, high activities, and novel LsrK binding modes, rendering them suitable for further optimization for effective AI-2 QSIs. Our work provides a valuable reference for the discovery of QSIs that do not inhibit bacterial growth, thereby avoiding the emergence of drug resistance.