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Introduction: Acinetobacter baumannii contributes significantly to the global issue of multidrug-resistant (MDR) nosocomial infections. Often, these strains demonstrate resistance to carbapenems (MDR-CRAB), the first-line treatment for infections instigated by MDR A. baumannii. Our study focused on the antimicrobial susceptibility and genomic sequences related to plasmids from 12 clinical isolates of A. baumannii that carry both the blaOXA-58 and bla NDM-1 carbapenemase genes. Methods: Whole-genome sequencing with long-read technology was employed for the characterization of an A. baumannii plasmid that harbors the bla OXA-58 and blaNDM-1 genes. The location of the bla OXA-58 and bla NDM-1 genes was confirmed through Southern blot hybridization assays. Antimicrobial susceptibility tests were conducted, and molecular characterization was performed using PCR and PFGE. Results: Multilocus Sequence Typing analysis revealed considerable genetic diversity among bla OXA-58 and bla NDM-1 positive strains in Brazil. It was confirmed that these genes were located on a plasmid larger than 300 kb in isolates from the same hospital, which also carry other antimicrobial resistance genes. Different genetic contexts were observed for the co-occurrence of these carbapenemase-encoding genes in Brazilian strains. Discussion: The propagation of bla OXA-58 and bla NDM-1 genes on the same plasmid, which also carries other resistance determinants, could potentially lead to the emergence of bacterial strains resistant to multiple classes of antimicrobials. Therefore, the characterization of these strains is of paramount importance for monitoring resistance evolution, curbing their rapid global dissemination, averting outbreaks, and optimizing therapy.

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BACKGROUND: Carbapenemase production is a global public health threat. Antimicrobial resistance (AMR) data analysis is critical to public health policy. Here we analyzed carbapenemase detection trends using the AMR Brazilian Surveillance Network. METHODS: Carbapenemase detection data from Brazilian hospitals included in the public laboratory information system dataset were evaluated. The detection rate (DR) was defined as carbapenemase detected by gene tested per isolate per year. The temporal trends were estimated using the Prais-Winsten regression model. The impact of COVID-19 on carbapenemase genes in Brazil was determined for the period 2015-2022. Detection pre- (October 2017 to March 2020) and post-pandemic onset (April 2020 to September 2022) was compared using the χ2 test. Analyses were performed with Stata 17.0 (StataCorp, College Station, TX). RESULTS: 83 282 blaKPC and 86 038 blaNDM were tested for all microorganisms. Enterobacterales DR for blaKPC and blaNDM was 68.6% (41 301/60 205) and 14.4% (8377/58 172), respectively. P. aeruginosa DR for blaNDM was 2.5% (313/12 528). An annual percent increase for blaNDM of 41.1% was observed, and a decrease for blaKPC of -4.0% in Enterobacterales, and an annual increase for blaNDM of 71.6% and for blaKPC of 22.2% in P. aeruginosa. From 2020 to 2022, overall increases of 65.2% for Enterobacterales, 77.7% for ABC, and 61.3% for P. aeruginosa were observed in the total isolates. CONCLUSIONS: This study shows the strengths of the AMR Brazilian Surveillance Network with robust data related to carbapenemases in Brazil and the impact of COVID-19 with a change in carbapenemase profiles with blaNDM rising over the years.

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Carbapenems are considered last-resort antibiotics for the treatment of infections caused by multidrug-resistant Gram-negative bacteria. Although the main mechanism of carbapenem-resistance in Pseudomonas aeruginosa is the loss of OprD porin, carbapenemases continue to be a problem worldwide. The aim of this study was to evaluate the performance of phenotypic tests (Carba NP, Blue Carba, and mCIM/eCIM) for detection of carbapenemase-producing Pseudomonas spp. in Brazil. One hundred twenty-seven Pseudomonas spp. clinical isolates from different Brazilian states were submitted to phenotypic and molecular carbapenemase detection. A total of 90 carbapenemase-producing P. aeruginosa and 5 Pseudomonas putida (35, blaVIM-2; 17, blaSPM-1; 2, blaIMP-10; 1, blaVIM-24; 1, blaNDM-1; 39, blaKPC-2). The phenotypic Carba NP, Blue Carba, and mCIM/eCIM showed sensitivity of 94.7%, 93.6%, and 93.6%, and specificity of 90.6%, 100%, and 96.8%, respectively. However, only the Carba NP presented the highest sensitivity and showed the ability in differentiating the carbapenemases between class A and class B using EDTA. Blue Carba failed to detect most of the class B carbapenemases, having the worst performance using EDTA. Our results show changes in the epidemiology of the spread of carbapenemases and the importance of their detection by phenotypic and genotypic tests. Such, it is essential to use analytical tools that faithfully detect bacterial resistance in vitro in a simple, sensitive, rapid, and cost-effective way. Much effort must be done to improve the current tests and for the development of new ones.

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BACKGROUND: Healthcare-associated infections due to multidrug-resistant (MDR) bacteria such as Pseudomonas aeruginosa are significant public health issues worldwide. A system biology approach can help understand bacterial behaviour and provide novel ways to identify potential therapeutic targets and develop new drugs. Gene regulatory networks (GRN) are examples of in silico representation of interaction between regulatory genes and their targets. OBJECTIVES: In this work, we update the MDR P. aeruginosa CCBH4851 GRN reconstruction and analyse and discuss its structural properties. METHODS: We based this study on the gene orthology inference methodology using the reciprocal best hit method. The P. aeruginosa CCBH4851 genome and GRN, published in 2019, and the P. aeruginosa PAO1 GRN, published in 2020, were used for this update reconstruction process. FINDINGS: Our result is a GRN with a greater number of regulatory genes, target genes, and interactions compared to the previous networks, and its structural properties are consistent with the complexity of biological networks and the biological features of P. aeruginosa. MAIN CONCLUSIONS: Here, we present the largest and most complete version of P. aeruginosa GRN published to this date, to the best of our knowledge.

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Antibacterial drugs are a widely used drug class due to the frequency of infectious diseases globally. Risks knowledge should ground these medicines' selection. Data mining in large databases is essential to identify early safety signals and to support pharmacovigilance systems. We conducted a cross-sectional study to assess adverse drug events related to antibiotics reporting between December 2018 and December 2021 in the Brazilian database (Vigimed/VigiFlow). We used the Reporting Odds Ratio (ROR) disproportionality analysis method to identify disproportionate reporting signals (SDR), referring to statistical combinations between drugs and adverse events. Vancomycin was the most reported antibiotic (n = 1,733), followed by ceftriaxone (n = 1,277) and piperacillin and tazobactam (n = 1,024). We detected 294 safety signals related to antibacterials. We identified azithromycin leading in the number of safety signals (n = 49), followed by polymyxin B (n = 25). Of these, 95 were not provided for in the drug label and had little or no reports in the medical literature. Three serious events are associated with ceftazidime and avibactam, a new drug in the Brazilian market. We also found suicide attempts as a sign associated with amoxicillin/clavulanate. Gait disturbance, a worrying event, especially in the elderly, was associated with azithromycin. Our findings may help guide further pharmacoepidemiologic studies and monitoring safety signals in pharmacovigilance.

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OBJECTIVES: In contrast to other qnr families, qnrVC has been reported mainly in Vibrio spp. and inserted in class 1 integrons. This study aimed to identify the variants of qnrVC genes detected in Klebsiella pneumoniae carbapenemase-2-producing Enterobacter and Klebsiella strains isolated from Brazilian coastal waters and the genetic contexts associated with their occurrence. METHODS: qnrVC variants were identified by Sanger sequencing. Stains were typified by pulsed-field gel electrophoresis. Antimicrobial susceptibility testing, conjugation assays, and whole genome sequencing (WGS) were applied to identify the strains' antimicrobial resistance profile, qnrVC and blaKPC-2 co-transference, and qnrVC genetic context. RESULTS: qnrVC1 was identified in 15 Enterobacter and 3 Klebsiella, and qnrVC4 in 2 Enterobacter strains. Pulsed-field gel electrophoresis revealed 12 clonal profiles of Enterobacter and one of Klebsiella. Strains were resistant to aminoglycosides, beta-lactams, fosfomycin, quinolones, and sulfamethoxazole-trimethoprim. Co-transference of qnrVC and blaKPC-2 were obtained from five representative Enterobacter strains, which showed resistance to ampicillin and amoxicillin-clavulanate, and reduced susceptibility to extended-spectrum cephalosporins, meropenem, and ciprofloxacin. WGS analysis from representative strains revealed one K. quasipneumoniae subsp. similipneumoniae, one E. soli, four E. kobei, and seven isolates belonging to Enterobacter Taxon 3. Long-read WGS showed qnrVC and blaKPC-2 were carried by the same replicon on Klebsiella and Enterobacter strains, and the qnrVC association with not previously described genetic environments composed of insertion sequences and truncated genes. These contexts occurred in small- and high-molecular-weight plasmids belonging to IncFII, IncP6, pKPC-CAV1321, and IncU groups. CONCLUSION: Our results suggest that the dissemination of qnrVC among Enterobacterales in Brazilian coastal waters is associated with several genetic recombination events.

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The high rates of carbapenem resistance among Brazilian Pseudomonas aeruginosa isolates are mainly associated with the clone ST277 producing the carbapenemase SPM-1. Here, the complete genetic composition of a IncP plasmid harboring blaKPC-2 in isolates of this endemic clone carrying chromosomal blaSPM-1 was described using whole genome sequencing. These results confirm the association of these two carbapenemases in ST277 and also describe the genetic composition of a novel blaKPC-2-plasmid. Considering the fact that this association occurs in a high-risk clone, monitoring the dissemination of this plasmid should be a public health concern.

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This study was conducted to determine the molecular epidemiology of blaKPC-encoding Klebsiella pneumoniae recovered from three public hospitals in Brazil. Molecular investigation of blaOXA-48, blaKPC, blaNDM, blaCTX-M, blaSHV, blaTEM, blaIMP, and blaVIM resistance genes was performed in 99 K. pneumoniae isolates from inpatients of intensive care units. Antimicrobial susceptibility was determined with a Vitek-2 System, except for polymyxin B, which was evaluated by the microbroth dilution test. Clonal relatedness was established by pulsed-field gel electrophoresis and multilocus sequence typing. Screening resistance genes showed that K. pneumoniae isolates carried the blaKPC (88.9%), blaSHV (73.5%), blaTEM (72.2%), and blaCTX-M (43.9%) genes. The most frequent sequence types (STs) were ST273, ST11, ST 1298, ST13, ST2687, and ST37. We report new STs in K. pneumoniae that have not been detected previously in Brazil. K. pneumoniae belonging to the same clone is present in different hospitals in the same region, showing the spread of multidrug-resistant K. pneumoniae.

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Pseudomonas aeruginosa is an opportunistic human pathogen that has been a constant global health problem due to its ability to cause infection at different body sites and its resistance to a broad spectrum of clinically available antibiotics. The World Health Organization classified multidrug-resistant Pseudomonas aeruginosa among the top-ranked organisms that require urgent research and development of effective therapeutic options. Several approaches have been taken to achieve these goals, but they all depend on discovering potential drug targets. The large amount of data obtained from sequencing technologies has been used to create computational models of organisms, which provide a powerful tool for better understanding their biological behavior. In the present work, we applied a method to integrate transcriptome data with genome-scale metabolic networks of Pseudomonas aeruginosa. We submitted both metabolic and integrated models to dynamic simulations and compared their performance with published in vitro growth curves. In addition, we used these models to identify potential therapeutic targets and compared the results to analyze the assumption that computational models enriched with biological measurements can provide more selective and (or) specific predictions. Our results demonstrate that dynamic simulations from integrated models result in more accurate growth curves and flux distribution more coherent with biological observations. Moreover, identifying drug targets from integrated models is more selective as the predicted genes were a subset of those found in the metabolic models. Our analysis resulted in the identification of 26 non-host homologous targets. Among them, we highlighted five top-ranked genes based on lesser conservation with the human microbiome. Overall, some of the genes identified in this work have already been proposed by different approaches and (or) are already investigated as targets to antimicrobial compounds, reinforcing the benefit of using integrated models as a starting point to selecting biologically relevant therapeutic targets.

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Multidrug-resistant microorganisms are a well-known global problem, and gram-negative bacilli are top-ranking. When these pathogens are associated with bloodstream infections (BSI), outcomes become even worse. Here we applied whole-genome sequencing to access information about clonal distribution, resistance mechanism diversity and other molecular aspects of gram-negative bacilli (GNB) isolated from bloodstream infections in Brazil. It was possible to highlight international high-risk clones circulating in the Brazilian territory, such as CC258 for Klebsiella pneumoniae, ST79 for Acinetobacter baumannii and ST233 for Pseudomonas aeruginosa. Important associations can be made such as a negative correlation between CRISPR-Cas and K. pneumoniae CC258, while the genes bla TEM, bla KPC and bla CTX-M are highly associated with this clone. Specific relationships between A. baumannii clones and bla OXA-51 variants were also observed. All P. aeruginosa ST233 isolates showed the genes bla VIM and bla OXA486. In addition, some trends could be identified, where a new P. aeruginosa MDR clone (ST3079), a novel A. baumannii clonal profile circulating in Brazil (ST848), and important resistance associations in the form of bla VIM-2 and bla IMP-56 being found together in one ST233 strain, stand out. Such findings may help to develop approaches to deal with BSI and even other nosocomial infections caused by these important GNB.