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A Neonatal Imaging Model of Gram-Negative Bacterial Sepsis
Published on: August 12, 2020
Application of next-generation sequencing to investigate a Serratia marcescens outbreak in a neonatal intensive care
Michela Bulfoni1,2,3, Nicolò Gualandi4, Beatrice Krpan5
1Department of Medicine, University of Udine, Udine, Italy. michela.bulfoni@uniud.it.
Introduction:
Nosocomial infections in Neonatal Intensive Care Units (NICU) are a major concern due to the vulnerability of premature and immunocompromised infants. Serratia marcescens is an opportunistic pathogen often involved in these infections, contributing significantly to morbidity and mortality. Integrating Next-Generation Sequencing (NGS) into infection control programs can enhance detection, surveillance, and prevention efforts. This study aimed to develop a mapping-based pipeline for strain typing and phylogenetic analysis of nosocomial infections, enabling detailed comparison of microbial genomes.
Methods:
A retrospective study describing the outbreak was conducted on 18 S. marcescens strains from 14 patients and 2 from environmental swabs collected in the NICU of the University Hospital of Udine between 2023 and 2024. Genomic DNA was extracted and libraries were prepared using the FX DNA Library Preparation Kit (Qiagen). Whole Genome Sequencing (WGS) was performed using an Illumina MiSeq platform (2 × 300 bp paired-end). Data analysis was carried out with CLC Genomic Workbench (Qiagen), using a custom-optimized pipeline for sequence typing (ST). The bioinformatics workflow was developed and validated in-house to ensure accurate SNP-based phylogenetic analysis.
Results:
WGS revealed phylogenetic relationships among strains. Six isolates showed close genetic relatedness. Identical genotypes were detected in strains from patient blood samples, rectal swabs, and environmental sources, suggesting potential transmission links.
Conclusions:
NGS offers detailed insights into the molecular epidemiology of infections and colonization in the NICU. The genomic data generated can support real-time, evidence-based refinement of infection control strategies, contributing to improved patient safety and outbreak prevention.
Insights
Next-Generation Sequencing (NGS) identified close genetic links between Serratia marcescens strains in a Neonatal Intensive Care Unit (NICU), revealing potential transmission routes and informing infection control.
Area of Science:
- Microbiology
- Genomics
- Infectious Disease Epidemiology
Background:
- Nosocomial infections in Neonatal Intensive Care Units (NICUs) pose significant risks to vulnerable infants.
- Serratia marcescens is a key opportunistic pathogen contributing to NICU-related morbidity and mortality.
- Next-Generation Sequencing (NGS) offers advanced capabilities for microbial surveillance and outbreak investigation.
Purpose of the Study:
- To develop and validate a mapping-based bioinformatics pipeline for strain typing and phylogenetic analysis of Serratia marcescens.
- To investigate the genomic relatedness of S. marcescens isolates from patients and the environment within a NICU setting.
- To assess the utility of NGS in understanding microbial transmission dynamics and informing infection control strategies.
Main Methods:
- Retrospective analysis of 18 Serratia marcescens isolates from patients and environmental swabs collected in a NICU.
- Whole Genome Sequencing (WGS) using Illumina MiSeq platform.
- Development and application of a custom, validated bioinformatics pipeline for Single Nucleotide Polymorphism (SNP)-based phylogenetic analysis.
Main Results:
- Whole Genome Sequencing (WGS) elucidated phylogenetic relationships among the S. marcescens strains.
- Six isolates exhibited high genetic relatedness, indicating a potential clonal cluster.
- Identical genotypes were found in strains from patient samples (blood, rectal swabs) and environmental sources, suggesting transmission pathways.
Conclusions:
- NGS provides high-resolution insights into the molecular epidemiology of NICU infections and colonizations.
- Genomic data supports real-time, evidence-based adjustments to infection control protocols.
- This approach enhances patient safety and aids in the prevention of healthcare-associated outbreaks.
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