Evaluation of the BD Phoenix Carbapenemase-Producing Organism Panels for the Detection of Carbapenemase Producers in Escherichia coli, Klebsiella pneumoniae and Pseudomonas aeruginosa.

The classification of carbapenemases can help guide therapy. The present study evaluated the performance of the CPO detection test, included in the BD Phoenix™ NMIC-501 panel for the detection and classification of carbapenemases on the representative molecularly characterized strains collection from Mexico. Carbapenem non-susceptible isolates collected in Mexico were included. The clinical isolates (n = 484) comprised Klebsiella pneumoniae (n = 154), Escherichia coli (n = 150), and P. aeruginosa (n = 180). BD Phoenix CPO NMIC-504 and NMIC-501 panels were used for the identification of species, antimicrobial susceptibility tests, and detection of CPOs. For the detection of carbapenemase-encoding genes, E. coli and K. pneumoniae were evaluated using PCR assays for blaNDM-1, blaKPC, blaVIM, blaIMP, and blaOXA-48-like. For P. aeruginosa, blaVIM, blaIMP, and blaGES were detected using PCR. Regarding E. coli, the CPO panels had a sensitivity of 70% and specificity of 83.33% for the detection of a class B carbapenemase (blaNDM in the molecular test). Regarding K. pneumoniae, the panels had a sensitivity of 75% and specificity of 100% for the detection of a class A carbapenemase (blaKPC in the molecular test). The Phoenix NMIC-501 panels are reliable for detecting class B carbapenemases in E. coli. The carbapenemase classification in K. pneumoniae for class A carbapenemases has a high specificity and PPV; thus, a positive result is of high value.

Active Surveillance of Antimicrobial Resistance and Carbapenemase-Encoding Genes According to Sites of Care and Age Groups in Mexico: Results from the INVIFAR Network.

We analyzed the antimicrobial resistance (AMR) data of 6519 clinical isolates of Escherichia coli (n = 3985), Klebsiella pneumoniae (n = 775), Acinetobacter baumannii (n = 163), Pseudomonas aeruginosa (n = 781), Enterococcus faecium (n = 124), and Staphylococcus aureus (n = 691) from 43 centers in Mexico. AMR assays were performed using commercial microdilution systems (37/43) and the disk diffusion susceptibility method (6/43). The presence of carbapenemase-encoding genes was assessed using PCR. Data from centers regarding site of care, patient age, and clinical specimen were collected. According to the site of care, the highest AMR was observed in E. coli, K. pneumoniae, and P. aeruginosa isolates from ICU patients. In contrast, in A. baumannii, higher AMR was observed in isolates from hospitalized non-ICU patients. According to age group, the highest AMR was observed in the ≥60 years age group for E. coli, E. faecium, and S. aureus, and in the 19-59 years age group for A. baumannii and P. aeruginosa. According to clinical specimen type, a higher AMR was observed in E. coli, K. pneumoniae, and P. aeruginosa isolates from blood specimens. The most frequently detected carbapenemase-encoding gene in E. coli was blaNDM (84%).

Whole genome analysis of Gram-negative bacteria using the EPISEQ CS application and other bioinformatic platforms.

OBJECTIVES: To determine genomic characteristics and molecular epidemiology of carbapenem non-susceptible Klebsiella pneumoniae, Escherichia coli, Acinetobacter baumannii, and Pseudomonas aeruginosa from medical centres of Mexico using whole genome sequencing data analysed with the EPISEQⓇ CS application and other bioinformatic platforms. METHODS: Clinical isolates collected from 28 centres in Mexico included carbapenem-non-susceptible K. pneumoniae (n = 22), E. coli (n = 24), A. baumannii (n = 16), and P. aeruginosa (n = 13). Isolates were subjected to whole genome sequencing using the Illumina (MiSeq) platform. FASTQ files were uploaded to the EPISEQⓇ CS application for analysis. Additionally, the tools Kleborate v2.0.4 and Pathogenwatch were used as comparators for Klebsiella genomes, and the bacterial whole genome sequence typing database was used for E. coli and A. baumannii. RESULTS: For K. pneumoniae, both bioinformatic approaches detected multiple genes encoding aminoglycoside, quinolone, and phenicol resistance, and the presence of blaNDM-1 explained carbapenem non-susceptibility in 18 strains and blaKPC-3 in four strains. Regarding E. coli, both EPISEQⓇ CS and bacterial whole genome sequence typing database analyses detected multiple virulence and resistance genes: 20 of 24 (83.3%) strains carried blaNDM, 3 of 24 (12.4%) carried blaOXA-232, and 1 carried blaOXA-181. Genes that confer resistance to aminoglycosides, tetracyclines, sulfonamides, phenicols, trimethoprim, and macrolides were also detected by both platforms. Regarding A. baumannii, the most frequent carbapenemase-encoding gene detected by both platforms was blaOXA-72, followed by blaOXA-66. Both approaches detected similar genes for aminoglycosides, carbapenems, tetracyclines, phenicols, and sulfonamides. Regarding P. aeruginosa, blaVIM, blaIMP, and blaGES were the more frequently detected. Multiple virulence genes were detected in all strains. CONCLUSION: Compared to the other available platforms, EPISEQⓇ CS enabled a comprehensive resistance and virulence analysis, providing a reliable method for bacterial strain typing and characterization of the virulome and resistome.

Bacterial incidence and drug resistance from pathogens recovered from blood, cerebrospinal and pleural fluids in 2019-2020. Results of the Invifar network.

Background: Antimicrobial resistance is a global concern. Analysis of sterile fluids is essential because microorganisms are defined as significant in most cases. Blood, cerebrospinal, and pleural fluids are frequently received in the microbiology lab because they are associated with considerable rates of morbi-mortality. Knowledge of epidemiology in these samples is needed to choose proper empirical treatments due to the importance of reducing selection pressure. Methods: We used retrospective laboratory data of blood, CSF, and pleural fluid collected from patients in Mexico between 2019 and 2020. Each laboratory identified the strains and tested susceptibility using its routine methods. For Streptococcus pneumoniae, a comparative analysis was performed with data from the broth microdilution method. Results: Forty-five centers participated in the study, with 30,746 clinical isolates from blood, 2,429 from pleural fluid, and 2,275 from CSF. For blood and CSF, Staphylococcus epidermidis was the most frequent. For blood, among gram negatives, the most frequent was Escherichia coli. Among Enterobacterales, 9.8% of K. pneumoniae were carbapenem-resistant. For S. pneumoniae, similar resistance percentages were observed for levofloxacin, cefotaxime, and vancomycin. For CSF, the most frequent gram-negative was E. coli. In Acinetobacter baumannii, carbapenem resistance was 71.4%. The most frequent species detected for pleural fluid was E. coli; in A. baumannii, carbapenem resistance was 96.3%. Conclusion: Gram-negative bacteria, with E. coli most prevalent, are frequently recovered from CSF, blood, and pleural fluid. In S. pneumoniae, the routine, conventional methods showed good agreement in detecting resistance percentages for erythromycin, levofloxacin, and vancomycin.

Carbapenemase-Encoding Genes and Colistin Resistance in Gram-Negative Bacteria During the COVID-19 Pandemic in Mexico: Results from the Invifar Network.

In this study, we report the carbapenemase-encoding genes and colistin resistance in Escherichia coli, Klebsiella pneumoniae, Acinetobacter baumannii, and Pseudomonas aeruginosa in the second year of the COVID-19 pandemic. Clinical isolates included carbapenem-resistant K. pneumoniae, carbapenem-resistant E. coli, carbapenem-resistant A. baumannii, and carbapenem-resistant P. aeruginosa. Carbapenemase-encoding genes were detected by PCR. Carbapenem-resistant K. pneumoniae and carbapenem-resistant E. coli isolates were analyzed using the Rapid Polymyxin NP assay. mcr genes were screened by PCR. Pulsed-field gel electrophoresis and whole-genome sequencing were performed on representative isolates. A total of 80 carbapenem-resistant E. coli, 103 carbapenem-resistant K. pneumoniae, 284 carbapenem-resistant A. baumannii, and 129 carbapenem-resistant P. aeruginosa isolates were recovered. All carbapenem-resistant E. coli and carbapenem-resistant K. pneumoniae isolates were included for further analysis. A selection of carbapenem-resistant A. baumannii and carbapenem-resistant P. aeruginosa strains was further analyzed (86 carbapenem-resistant A. baumannii and 82 carbapenem-resistant P. aeruginosa). Among carbapenem-resistant K. pneumoniae and carbapenem-resistant E. coli isolates, the most frequent gene was blaNDM (86/103 [83.5%] and 72/80 [90%], respectively). For carbapenem-resistant A. baumannii, the most frequently detected gene was blaOXA-40 (52/86, 60.5%), and for carbapenem-resistant P. aeruginosa, was blaVIM (19/82, 23.2%). For carbapenem-resistant A. baumannii, five indistinguishable pulsotypes were detected. Circulation of K. pneumoniae New Delhi metallo-ß-lactamase (NDM) and E. coli NDM was detected in Mexico. High virulence sequence types (STs), such as K. pneumoniae ST307, E. coli ST167, P. aeruginosa ST111, and A. baumannii ST2, were detected. Among K. pneumoniae isolates, 18/101 (17.8%) were positive for the Polymyxin NP test (two, 11.0% positive for the mcr-1 gene, and one, 5.6% with disruption of the mgrB gene). All E. coli isolates were negative for the Polymyxin NP test. In conclusion, K. pneumoniae NDM and E. coli NDM were detected in Mexico, with the circulation of highly virulent STs. These results are relevant in clinical practice to guide antibiotic therapies considering the molecular mechanisms of resistance to carbapenems.

Increment Antimicrobial Resistance During the COVID-19 Pandemic: Results from the Invifar Network.

Aim: This study aims to assess the changes in antimicrobial resistance among some critical and high-priority microorganisms collected previously and during the coronavirus disease 2019 (COVID-19) pandemic in Mexico. Methods: We collected antimicrobial susceptibility data for critical and high-priority microorganisms from blood, urine, respiratory samples, and from all specimens, in which the pathogen may be considered a causative agent. Data were stratified and compared for two periods: 2019 versus 2020 and second semester 2019 (prepandemic) versus the second semester 2020 (pandemic). Results: In the analysis of second semester 2019 versus the second semester 2020, in blood samples, increased resistance to oxacillin (15.2% vs. 36.9%), erythromycin (25.7% vs. 42.8%), and clindamycin (24.8% vs. 43.3%) (p ≤ 0.01) was detected for Staphylococcus aureus, to imipenem (13% vs. 23.4%) and meropenem (11.2% vs. 21.4) (p ≤ 0.01), for Klebsiella pneumoniae. In all specimens, increased ampicillin and tetracycline resistance was detected for Enterococcus faecium (p ≤ 0.01). In cefepime, meropenem, levofloxacin, and gentamicin (p ≤ 0.01), resistance was detected for Escherichia coli; and in piperacillin-tazobactam, cefepime, imipenem, meropenem, ciprofloxacin, levofloxacin, and gentamicin (p ≤ 0.01), resistance was detected for Pseudomonas aeruginosa. Conclusion: Antimicrobial resistance increased in Mexico during the COVID-19 pandemic. The increase in oxacillin resistance for S. aureus and carbapenem resistance for K. pneumoniae recovered from blood specimens deserves special attention. In addition, an increase in erythromycin resistance in S. aureus was detected, which may be associated with high azithromycin use. In general, for Acinetobacter baumannii and P. aeruginosa, increasing resistance rates were detected.