Whole-Genome Sequencing for Outbreak Investigations of Methicillin-Resistant Staphylococcus aureus in the Neonatal Intensive Care Unit: Time for Routine Practice?
Autor: | Mobeen H. Rathore, Judith A. Johnson, J. Glenn Morris, Taj Azarian, Yvette S. McCarter, Noel Gomez, Nilmarie Guzman, Robert L. Cook, Marco Salemi |
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Rok vydání: | 2015 |
Předmět: |
Male
Methicillin-Resistant Staphylococcus aureus Microbiology (medical) medicine.medical_specialty Neonatal intensive care unit Epidemiology medicine.disease_cause Polymorphism Single Nucleotide Article Disease Outbreaks Microbiology Intensive Care Units Neonatal Internal medicine Humans Medicine Infection control Genotyping Genotyping Techniques Phylogeny Infection Control Genome business.industry Transmission (medicine) Infant Newborn Outbreak Staphylococcal Infections Methicillin-resistant Staphylococcus aureus Bacterial Typing Techniques Electrophoresis Gel Pulsed-Field Infectious Diseases Florida Multilocus sequence typing Female business |
Zdroj: | Infection Control & Hospital Epidemiology. 36:777-785 |
ISSN: | 1559-6834 0899-823X |
DOI: | 10.1017/ice.2015.73 |
Popis: | Methicillin-resistant Staphylococcus aureus (MRSA) is a leading cause of healthcare-associated infections (HAIs), significantly contributing to morbidity and mortality of hospitalized patients. Infants in the neonatal intensive care unit (NICU) are at increased risk for infection and colonization with MRSA, often resulting in poor outcomes and long-term sequelae.1 MRSA in the NICU may be acquired from colonized parents, healthcare workers (HCWs), and other neonates.2,3 The CDC estimates that ~50% of MRSA infections for patients 3–89 days old are hospital-onset cases.4 Community reservoirs have been implicated in the introduction of MRSA into NICUs by increasing colonization prevalence among patients and visitors.5 However, identifying reservoirs and tracking the source of implicated strains has proven difficult, resulting in the persistence of transmission despite aggressive control measures.6–8 Limitations in genotyping techniques available in clinical practice may hinder the investigation of MRSA outbreaks in healthcare settings.8 Genotyping is an indispensable component of epidemic detection and investigation because it discriminates among genetically similar strains for the identification of epidemiologically important isolates. Pulsed-field gel electrophoresis (PFGE), spa typing, antibiograms, and multilocus sequence typing (MLST) are commonly employed to investigate MRSA transmission. However, these methods may not be optimal, as the unit of categorization (eg, PFGE type, spa type, MLST profile) can encompass broad genetic and epidemiological diversity,6,8 making it difficult to differentiate sporadic from epidemic cases,9–14 particularly when a prevalent strain type is commonly identified. MRSA PFGE-typed USA300 is an important pathogen in community and healthcare settings. In the United States, these strains were historically associated with community-associated (CA) infections acquired outside of hospitals. However, in many healthcare facilities, including those in our study area, CA-MRSA strains are displacing healthcare-associated (HA) strains as a cause of HAIs. The increasing prevalence of USA300 emphasizes the need for advanced typing methods in clinical practice. Recently, phylogenetic analysis of whole-genome sequencing (WGS) data has provided the resolution to discriminate between closely related isolates of bacterial pathogens through comparison of single nucleotide polymorphisms (SNPs).15,16 As a result, epidemiologically important isolates may be identified among a sample that appears homogenous when analyzed using conventional genotyping methods. WGS technology is often not readily available to investigators of outbreaks in the healthcare setting.15,17–19 Epidemiological linkages between patients may then be spuriously attributed and transmission sources obscured, leading to ineffective interventions and uninterrupted transmission. We sought to determine whether phylogenetic analysis of SNPs would facilitate identification of the source of MRSA transmission amid a putative NICU outbreak, compared to the initial investigation that utilized traditional genotyping. We considered multiple typing methods including maximum likelihood (ML) and Bayesian phylogenetic analysis of SNP data. Epidemiological and phylogenetic data were covisualized to illustrate the temporal and genetic relationships among cases, allowing for assessment of patient-to-patient transmission events. We demonstrate how this approach would have enhanced the investigation, ruling out several sporadic cases of MRSA and potentially augmenting infection control interventions. |
Databáze: | OpenAIRE |
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