Abstract
The surveillance of health care-associated infection (HAI) is an essential element of the infection control program. While whole-genome sequencing (WGS) has widely been adopted for genomic surveillance, its data processing remains to be improved. Here, we propose a three-level data processing pipeline for the precision genomic surveillance of microorganisms without prior knowledge: species identification, multi-locus sequence typing (MLST), and sub-MLST clustering. The former two are closely connected to what have widely been used in current clinical microbiology laboratories, whereas the latter one provides significantly improved resolution and accuracy in genomic surveillance. Comparing to a broadly used reference-dependent alignment/mapping method and an annotation-dependent pan-/core-genome analysis, we implemented our reference- and annotation-independent, k-mer-based, simplified workflow to a collection of Acinetobacter and Enterococcus clinical isolates for tests. By taking both single nucleotide variants and genomic structural changes into account, the optimized k-mer-based pipeline demonstrated a global view of bacterial population structure in a rapid manner and discriminated the relatedness between bacterial isolates in more detail and precision. The newly developed WGS data processing pipeline would facilitate WGS application to the precision genomic surveillance of HAI. In addition, the results from such a WGS-based analysis would be useful for the precision laboratory diagnosis of infectious microorganisms.
Highlights
Health care-associated infection (HAI) is a significant cause of illness and death, continuing to threaten the health care system
The Centers for Disease Control and Prevention (CDC) in the United States estimates that approximately one in 31 hospital patients has at least one HAI every day, significant progress has been made in prevention and control
All bacterial isolates were recovered from patients, except one from environment surveillance (M170981), at the Clinical Microbiology Laboratory of Westchester Medical Center (WMC), a tertiary-care hospital in suburban New York City
Summary
Health care-associated infection (HAI) is a significant cause of illness and death, continuing to threaten the health care system. The Centers for Disease Control and Prevention (CDC) in the United States estimates (https://www.cdc.gov/hai/data/index.html) that approximately one in 31 hospital patients has at least one HAI every day, significant progress has been made in prevention and control. These nosocomial infections lead to the loss of tens of thousands of lives and pose a significant cost burden each year, millions to billions of dollars [1]. We used a collection of Acinetobacter baumannii and some rare species of vancomycin-resistant enterococci (VRE) clinical isolates Both VRE and Acinetobacter bacteria are recognized as critical major nosocomial pathogens (https: //www.cdc.gov/hai/data/index.html) due to their natural intrinsic resistance to several antimicrobials and capacity to quickly acquire virulence and multidrug resistance
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