The nonstandard use of disinfectants can lead to the disinfectant resistance of bacteria and even increase antibiotic resistance. However, compared with the study of antibiotic resistance, studies of bacterial resistance to disinfectants are relatively few in number. In this study, we explored the standard strain screening procedure for the evaluation of disinfection efficacy. Staphylococcus aureus strains with different sources and substrates were selected from the National Pathogen Resource Center of China and screened the standard strains that could evaluate the long-term bacteriostatic effect of the chlorine-containing disinfectants through the determination of the physical properties, genome-based safety evaluation, and disinfection test evaluation. In this process, one S. aureus strain was more resistant to the long-term bacteriostasis of chlorine-containing disinfectants than the other strains. This strain and the standard strain ATCC 6538 were cultured in the medium containing a low concentration of chlorine-containing disinfectant synchronously. Then, comparative transcriptome analysis was carried out to investigate the potential mechanism of a high tolerance to chlorine-containing disinfectants. The pathway of significant differential expression is related to the oxocarboxylic acid metabolic mechanism, amino acid metabolic mechanism, and pyrimidine mechanism, which may be the molecular mechanism of S. aureus evolution to adapt to chlorine-containing disinfectants. Our study established a technical process for screening and evaluating standard strains for disinfection, which also provided a reference for studying the bacterial evolution mechanism toward chlorine tolerance.

Bacterial antimicrobial resistance (AMR) poses a significant global public health challenge. The escalation of AMR is primarily attributed to the horizontal gene transfer (HGT) of antibiotic resistance genes (ARGs), often facilitated by plasmids. This underscores the critical need for a comprehensive understanding of the resistance mechanisms and transmission dynamics of these plasmids. In this study, we utilized in vitro drug sensitivity testing, conjugation transfer assays, and whole-genome sequencing to investigate the resistance mechanism of an extensively drug-resistant (XDR) Pseudomonas aeruginosa clinical isolate, MAS152. We specifically focused on analyzing the drug-resistant plasmid pMAS152 it harbors and its potential for widespread dissemination. Bioinformatics analysis revealed that MAS152 carries a distinct IncpP-2A plasmid, pMAS152, characterized by a 44.8 kb multidrug resistance (MDR) region. This region houses a 16S rRNA methyltransferase (16S-RMTase) gene, rmtB, conferring high-level resistance to aminoglycoside antibiotics. Notably, this region also contains an extended-spectrum β-Lactamase (ESBL) gene, bla_PER-1, and an efflux pump operon, tmexCD-oprJ, which mediate resistance to β-Lactams and quinolone antibiotics, respectively. Such a combination of ARGs, unprecedented in reported plasmids, could significantly undermine the effectiveness of first-line antibiotics in treating P. aeruginosa infections. Investigation into the genetic environment of the MDR region suggests that Tn2 and IS91 elements may be instrumental in the horizontal transfer of rmtB. Additionally, a complex Class I integron with an ISCR1 structure, along with TnAs1, seems to facilitate the horizontal transfer of bla_PER-1. The conjugation transfer assay, coupled with the annotation of conjugation-related genes and phylogenetic analysis, indicates that the plasmid pMAS152 functions as a conjugative plasmid, with other genus Pseudomonas species as potential hosts. Our findings provide vital insights into the resistance mechanisms and transmission potential of the XDR P. aeruginosa isolate MAS152, underlining the urgent need for novel strategies to combat the spread of AMR. This study highlights the complex interplay of genetic elements contributing to antibiotic resistance and underscores the importance of continuous surveillance of emerging ARGs in clinical isolates.

Rapid and accurate identification of pathogenic bacteria phenotypic traits, including virulence, drug resistance, and metabolic activity, is essential for clinical diagnosis and infectious disease control. Traditional methods are time-consuming, highlighting the need for more efficient approaches. This study develops a single-cell Raman spectroscopy approach to detect multiple phenotypic traits of Staphylococcus aureus (S. aureus) as a proof of concept. We constructed a single-cell Raman spectral database encompassing 6240 spectra from 10 strains of S. aureus with diverse phenotypic traits and developed a convolutional neural network (CNN) to predict these phenotypes from the Raman spectra. The CNN model achieved 93.90%, 98.73%, and 98.66% accuracy in identifying enterotoxin-producing strains, methicillin-resistant S. aureus (MRSA), and growth stages, respectively. Characteristic Raman peaks for enterotoxin producers mainly appeared at 781, 939, 1161, 1337, 1451, and 1524 cm⁻¹, whereas MRSA primarily exhibited peaks at 723, 780, 939, 1095, 1162, 1340, 1451, 1523, and 1660 cm⁻¹. During culture, nucleic acid-related peaks weakened, lipid peaks increased, and protein peaks initially increased and subsequently decreased. This integration of Raman spectroscopy and machine learning demonstrates considerable potential for rapid bacterial phenotyping. Future research should expand to a wider range of bacterial species and phenotypes to enhance the diagnosis, prevention, and management of infectious diseases.