INVESTIGADORES
RODRIGUEZ Maria Cecilia
congresos y reuniones científicas
Título:
Genomic Insights into Antimicrobial Metabolites of Lacticaseibacillus rhamnosus CRL 2244 Active Against multidrug-Resistant Acinetobacter baumannii
Autor/es:
CAMILA LEAL; GERMÁN TRAGLIA; RAMIREZ MARIA SOLEDAD; CECILIA RODRÍGUEZ
Lugar:
Córdoba
Reunión:
Congreso; Congreso SAIB 2025; 2025
Institución organizadora:
SAIB
Resumen:
The global rise of infections caused by multidrug-resistant (MDR) Acinetobacter baumannii underscores the urgent need to identify novel antimicrobial agents. We previously identified Lacticaseibacillus rhamnosus CRL 2244, isolate from wastewater, exhibiting strong antimicrobial activity against A. baumannii and other MDR pathogens. To investigate the genomic basis underlying the production of its active metabolite(s), we performed whole-genome sequencing followed by automated annotation and manual curation, which reduced hypothetical proteins by approximately 47% and improved functional interpretation. Comparative analyses using Average Nucleotide Identity (ANI) and pangenome reconstruction with Roary placed CRL 2244 within the Lcb. rhamnosus clade and revealed unique accessory genes potentially linked to antimicrobial metabolite production. Targeted genome mining with BAGEL4 identified three biosynthetic gene clusters (BGCs), including two RiPP-like regions. One corresponds to a class IIb bacteriocin operon (orf00017orf00021) enconding a two-component regulatory system, an ABC transporter, an immunity gene, and two double-glycine leader peptides, characteristic of two-peptide bacteriocins. Additional open reading frames were predicted by SignalP and PSORTb to be secreted and extracellular, while BLAST searches against DRAMP and CAMP database revealed significant similarity to known enterocins. The integration of functional annotation, pangenome analysis, and specialized mining tools provides a robust framework for identifying candidate antimicrobial metabolites in Lcb. rhamnosus CRL 2244. However, these findings remain in silico predictions and require experimental validation through chemical identification (LC-MS/MS), metabolite synthesis or isolation, and minimum inhibitory concentration testing to confirm the identity and activity of the active molecule(s).

