Differential Analysis of Longitudinal Methicillin-Resistant Staphylococcus aureus Colonization in Relation to Microbial Shifts in the Nasal Microbiome of Neonatal Piglets
Patel, Shriram; Vlasblom, Abel A; Verstappen, Koen M; Zomer, Aldert L; Fluit, Ad C; Rogers, Malbert R C; Wagenaar, Jaap A; Claesson, Marcus J; Duim, Birgitta
(2021) mSystems, volume 6, issue 4, pp. 1 - 15
(Article)
Abstract
Methicillin-resistant Staphylococcus aureus (MRSA) is an important human pathogen and often colonizes pigs. To lower the risk of MRSA transmission to humans, a reduction of MRSA prevalence and/or load in pig farms is needed. The nasal microbiome contains commensal species that may protect against MRSA colonization and may be used
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to develop competitive exclusion strategies. To obtain a comprehensive understanding of the species that compete with MRSA in the developing porcine nasal microbiome, and the moment of MRSA colonization, we analyzed nasal swabs from piglets in two litters. The swabs were taken longitudinally, starting directly after birth until 6 weeks. Both 16S rRNA and tuf gene sequencing data with different phylogenetic resolutions and complementary culture-based and quantitative real-time PCR (qPCR)-based MRSA quantification data were collected. We employed a compositionally aware bioinformatics approach (CoDaSeq 1 rmcorr) for analysis of longitudinal measurements of the nasal microbiota. The richness and diversity in the developing nasal microbiota increased over time, albeit with a reduction of Firmicutes and Actinobacteria, and an increase of Proteobacteria. Coabundant groups (CAGs) of species showing strong positive and negative correlation with colonization of MRSA and S. aureus were identified. Combining 16S rRNA and tuf gene sequencing provided greater Staphylococcus species resolution, which is necessary to inform strategies with potential protective effects against MRSA colonization in pigs.
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Keywords: Colonization, MRSA, Microbial shifts, Porcine nasal microbiome, Staphylococcus aureus, Microbiology, Ecology, Evolution, Behavior and Systematics, Biochemistry, Physiology, Modelling and Simulation, Molecular Biology, Genetics, Computer Science Applications
ISSN: 2379-5077
Publisher: American Society for Microbiology
Note: Funding Information: This research was supported in part by Science Foundation Ireland (grant no. SFI/12/ RC/2273_P2), the Irish Health Research Board, and the Dutch ZonMw (JPIAMR-2017-1-B grant no. 50-52900-98-043). S.P. was additionally funded from the European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement number 754535. Publisher Copyright: © 2021 Patel et al.
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