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Buenestado-Serrano, S.

Publications and source records attributed to Buenestado-Serrano, S..

2 recordsLinked to original sources

Direct nanopore sequencing of M. tuberculosis on sputa and rescue of suboptimal results to enhance transmission surveillance

Whole-genome sequencing (WGS) enhances precision in predicting antimicrobial resistance and tracking Mycobacterium tuberculosis (MTB) transmission. Due to MTBs slow-growing nature, genomic results are delayed; however, few efforts have sought to accelerate them by performing WGS directly on respiratory specimens. Most culture-free efforts have focused on accelerating resistance prediction. The present study provides further evidence to the only preceding study aiming to accelerate precise delineation of transmission, coupling culture-free WGS to a surveillance programme. Our study is distinguished from its predecessor by being the first to apply flexible nanopore sequencing to further accelerate the process. A total of 71 sputa were selected, in which we applied only a procedure to deplete human DNA, thus avoiding costly and cumbersome capture-bait alternatives. Optimal results (>90% genome covered, mean coverage >45x and >70% genome covered >20x) were obtained from 33.8% of cases, allowing the assignment to transmission clusters close to diagnosis of every new case. A further 12.6% of samples yielded suboptimal results (15.5%-90.92% at >10x), which were exploited through a rescue pipeline. This approach was based on identifying informative SNPs acting as markers for relevant transmission clusters in our population. The pipeline enabled pre-allocation of new cases to pre-existing clusters and, in some cases, precise genomic relationships with the preceding cases in the cluster. In summary, this study demonstrates that epidemiologically valuable information can be obtained directly from sputum in approximately half the samples analysed. It represents a new advancement in the pursuit of faster comparative genomics, with epidemiological purposes, at diagnosis.

genomics↗

Characterization of a nosocomial outbreak caused by VIM-1 Klebsiella michiganensis using Fourier-Transform Infrared (FT-IR) Spectroscopy

Healthcare-associated infections (HAIs) are a significant concern worldwide due to their impact on patient safety and healthcare costs. Klebsiella spp., particularly Klebsiella pneumoniae and Klebsiella oxytoca, are frequently implicated in HAIs and often exhibit multidrug resistance mechanisms, posing challenges for infection control. In this study, we evaluated Fourier-transform Infrared (FT-IR) spectroscopy as a rapid method for characterizing a nosocomial outbreak caused by VIM-1-producing K. oxytoca. A total of 47 isolates, including outbreak strains and controls, were collected from Hospital Universitario Gregorio Maranon, Spain and the University Hospital Basel, Switzerland. FT-IR spectroscopy was employed for bacterial typing, offering rapid and accurate results compared to conventional methods like pulsed-field gel electrophoresis (PFGE) and correlating with whole-genome sequencing (WGS) results. The FT-IR spectra analysis revealed distinct clusters corresponding to outbreak strains, suggesting a common origin. Subsequent WGS analysis identified Klebsiella michiganensis as the causative agent of the outbreak, challenging the initial assumption based on FT-IR results. However, both FT-IR and WGS methods showed high concordance, with an Adjusted Rand index (AR) of 0.882 and an Adjusted Wallace coefficient (AW) of 0.937, indicating the reliability of FT-IR in outbreak characterization. Furthermore, FT-IR spectra visualization highlighted discriminatory features between outbreak and non-outbreak isolates, facilitating rapid screening in case and outbreak is suspected. In conclusion, FT-IR spectroscopy offers a rapid and cost-effective alternative to traditional typing methods, enabling timely intervention and effective management of nosocomial outbreaks. Its integration with WGS enhances the accuracy of outbreak investigations, demonstrating its utility in clinical microbiology and infection control practices.

microbiology↗