Revista peruana de medicina experimental y salud publica · 2026
Lyell´s syndrome associated with the use of topical agents: case report.
Клинический случайСтатьяНазвание и аннотация: Перевод пока не подготовлен
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Núñez Figueroa Paulina, Sánchez Orozco Abel, Alfaro Pérez Ignacio, Andara Ramírez María Teresa, Balderramo Domingo, Bautista Sócrates, Cassella Federico, Cervera Caballero Luis Alberto, De León Rendón Jorge Luis, De Lucas Ocaña Juan, García Vilela Eduardo, Jara Alba Maria Luisa, Linares Serrano Melvin, Martínez-Vázquez Manuel Alejandro, Morínigo Bogado Sergio Daniel, Muñoz Camacho Ruben, Parra-Izquierdo Viviana, Pérez Baldíoceda Johana, Puentes-Manosalva Fabián Eduardo, Rodríguez Olaso Ximena, Saad-Hossne Rogério, Serrano Mariastella, Suarez Miosotis, Umaña Solis Elizabeth, Pardo-Turriago Rodrigo, Yuseff Sandra, Lozano Tatiana, Juliao-Baños Fabián
Аннотация
UNLABELLED: Pseudomonas aeruginosa AG1 (PaeAG1) is a Costa Rican strain that was isolated in 2010 in a major Hospital. This strain has resistance to multiple antibiotics such as β-lactams (including carbapenems), aminoglycosides, and fluoroquinolones. PaeAG1 is considered critical (Priority 1) due to its resistance to carbapenems, and it was the first report of a P. aeruginosa isolate carrying both VIM-2 and IMP-18 genes encoding for metallo-β-lactamases (MBL) enzymes (both with carbapenemase activity). Owing to these traits, we have studied this model for 10 years using diverse approaches including multi-omics. In this review, we summarize the main points of the different steps that we have studied in PaeAG1: preliminary analyses of this strain at the genomic and phenomic levels revealed that this microorganism has particular features of antibiotic resistance. In the multi-omics approach, the genome assembly was the initial step to identify the genomic determinants of this strain, including virulence factors, antibiotic resistance genes, as well as a complex accessory genome. Second, a comparative genomic approach was implemented to define and update the phylogenetic relationship among complete P. aeruginosa genomes, the genomic island content in other strains, and the architecture of the two MBL-carrying integrons. Third, the proteomic profile of PaeAG1 was studied after exposure to antibiotics using 2-dimensional gel electrophoresis (2D-GE). Fourth, to study the central response to multiple perturbations in P. aeruginosa, i.e., the core perturbome, a machine learning approach was used. The analysis revealed biological functions and determinants that are shared by different disturbances. Finally, to evaluate the effects of ciprofloxacin (CIP) on PaeAG1, a growth curve comparison, differential expression analysis (RNA-Seq), and network analysis were performed. Using the results of the core perturbome (pathways that also were found in this perturbation with CIP), it was possible to identify the "exclusive" response and determinants of PaeAG1 after exposure to CIP. Altogether, after a decade of study using a multi-omics approach (at genomics, comparative genomics, perturbomics, transcriptomics, proteomics, and phenomics levels), we have provided new insights about the genomic and transcriptomic determinants associated with antibiotic resistance in PaeAG1. These results not only partially explain the high-risk condition of this strain that enables it to conquer nosocomial environments and its multi-resistance profile, but also this information may eventually be used as part of the strategies to fight this pathogen.
SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s43657-021-00016-z.