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Open AccessFeature PaperArticle

An Analysis of Antimicrobial Resistance of Clinical Pathogens from Historical Samples for Six Countries

1
Department of Chemical Engineering, Villanova University, Villanova, PA 19085, USA
2
Department of Health, Nutrition & Exercise Sciences, Immaculata University, Immaculata, PA 19345, USA
*
Author to whom correspondence should be addressed.
Processes 2019, 7(12), 964; https://doi.org/10.3390/pr7120964
Received: 2 October 2019 / Revised: 27 November 2019 / Accepted: 2 December 2019 / Published: 17 December 2019
(This article belongs to the Special Issue Big Data in Biology, Life Sciences and Healthcare)
The spread of antimicrobial resistance pathogens in humans has increasingly become an issue that threatens public health. While the NCBI Pathogen Detection Isolates Browser (NPDIB) database has been collecting clinical isolate samples over time for various countries, few studies have been done to identify genes and pathogens responsible for the antimicrobial resistance in clinical settings. This study conducted the first multivariate statistical analysis of the high-dimensional historical data from the NPDIB database for six different countries from majorly inhabited landmasses, including Australia, Brazil, China, South Africa, the UK, and the US. The similarities among different countries in terms of genes and pathogens were investigated to understand the potential avenues for antimicrobial-resistance gene spreading. The genes and pathogens that were closely involved in antimicrobial resistance were further studied temporally by plotting time profiles of their frequency to evaluate the trend of antimicrobial resistance. It was found that several of these significant genes (i.e., aph(3″)-Ib, aph(6)-Id, blaTEM-1, and qacEdelta1) are shared among all six countries studied. Based on the time profiles, a large number of genes and pathogens showed an increasing occurrence. The most shared pathogens responsible for carrying the most important genes in the six countries in the clinical setting were Acinetobacter baumannii, E. coli and Shigella, Klebsiella pneumoniae and Salmonella enterica. South Africa carried the least similar antimicrobial genes to the other countries in clinical isolates. View Full-Text
Keywords: antimicrobial resistance; clinical pathogens; principal component analysis; hierarchical clustering; data analysis antimicrobial resistance; clinical pathogens; principal component analysis; hierarchical clustering; data analysis
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MDPI and ACS Style

Li, K.; Zheng, J.; Deng, T.; Peng, J.; Daniel, D.; Jia, Q.; Huang, Z. An Analysis of Antimicrobial Resistance of Clinical Pathogens from Historical Samples for Six Countries. Processes 2019, 7, 964.

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