(157bm) Investigation of Incidents and Trends of Antimicrobial Resistance in Foodborne Pathogens in Eight Countries from Historical Sample Data

Antimicrobial resistance (AMR) is increasingly becoming a threat to global public health[1]. AMR-related infections limit the effectiveness of lifesaving antibiotic therapy necessary for the treatment of infectious disease and limit the success of advanced surgical procedures like organ transplants [2,3]. This results in millions of illnesses and deaths worldwide. For example, the US Centers for Disease Control and Prevention (CDC) estimated that AMR bacteria account for over 2 million illnesses and at least 23,000 deaths in the US every year [4]. Similarly, it is estimated that 426,000 infections and 33,000 deaths from antimicrobial resistant microorganisms occur in the European Union every year [5]. Furthermore, AMR places a considerable medical and financial burden on global societies and healthcare systems as a whole [1,3,6–8]. It is therefore essential to develop a better understanding of the cause and spread of AMR around the world.

In response to the need for further research into the spread of resistant foodborne pathogens and illness, the NCBI Pathogen Detection Isolates Browser (NPDIB) was created to integrate bacterial pathogen genomic sequences originating in food, patients, and environmental sources [9]. It analyzes samples from around the world and compares their genomic sequences to others already in the database. When AMR foodborne pathogens access humans, the AMR genes may be passed from the pathogens to human cells via horizontal gene transfer (HGT) through mechanisms of transformation, transduction, or conjugation[10]. This is implied by a study in which 13,514 high-confidence HGT genes were found in 308 human microbes [11]. The development of antibiotic resistance in foodborne bacteria and in HGT can significantly endanger human health. NPDIB clusters identify related sequences to uncover potential food contamination outbreaks and resistance genes. Through the database, people can search for foodborne pathogen isolates and identify pathogens with particular resistance genes. In previous literature, the database was typically only used to compare the DNA from detected pathogens to those in the database or to provide data for a historical analysis of resistance in specific pathogens [12,13]. Little research, however, has been done to examine specific AMR genes over large geographic areas.

To examine the rise and spread of antimicrobial resistance around the world, our study performs a multivariate statistical analysis of antimicrobial resistance gene data from eight different countries: the US, the UK, China, Brazil, Mexico, Canada, Australia, and South Africa. Multi-dimensional data points were projected onto a two-dimensional plane using principal component analysis and organized into a dendrogram utilizing hierarchical clustering to identify significant AMR genes and pathogens.

Given each sample’s large number of dimensions, principal component analysis (PCA) was applied to each country’s data to visualize the complex data matrices into two-dimensional plots, providing a clear image of the data points and their relationships. Utilizing dimensionality reduction, PCA created new individual dimensions that could retain the most information in the data matrix. These new dimensional variables, called principal components, were orthogonal vectors that represented different levels of variance in the data. In this way, the key highly occurring pathogens in each of the eight countries were identified using PCA and hierarchical clustering.

Certain outlier genes/pathogens were typically involved in high occurrences of antimicrobial resistance, and could be used to identify trends in antimicrobial resistances in the future. Statistical analysis of the data identified: (1) tet(A), aph(3”)-Ib,aph(6)-Id,blaEC,blaTEM-1,qacEdelta1,sul1,sul2,and aadA1 as the nine most common AMR genes among the studied countries; (2)Salmonella enterica and E.coli and Shigella as the most common AMR foodborne pathogens; and (3) chicken as the most prevalent meat carrier of antimicrobial resistance. Our study also shows that the overall number of reported antimicrobial resistance cases in foodborne pathogens is generally rising. One potential contributing factor is the increasing antimicrobial usage in the growing livestock industry.

The large number of highly occurring AMR genes and the wide dissemination of many of these genes implies a potential rise of antimicrobial resistance. The spread of many highly occurring genes to numerous geographically distant countries with varying antimicrobial policies highlights the role of the global livestock trade in the transfer of AMR genes and foodborne pathogens. The identification of the nine globally significant highly-occurring genes, highly-occurring pathogens, and most prevalent meat carrier offer valuable insight for future research and development of new solutions for antimicrobial resistance.

References

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