NEW YORK (GenomeWeb) – A metagenomic analysis of sewage samples has enabled an international team of researchers to develop a map of global antimicrobial resistance, a growing global public health concern.
Researchers led by the Technical University of Denmark's Frank Aarestrup sequenced DNA they isolated from sewage samples collected from 74 cities across 60 countries. As they reported in Nature Communications today, they found that countries fell largely into two groups, one with low levels of resistance and one with high levels of resistance. Those groups, they noted, broadly correlated with sanitary conditions in the country and the population's overall health.
"In the fight against antimicrobial resistance, our findings suggest that it would be a very effective strategy if concerted efforts were made to improve sanitary conditions in countries with high levels of antimicrobial resistance," Aarestrup said in a statement.
He and his colleagues sequenced DNA from the sewage samples using the Illumina HiSeq platform and assigned, on average, 0.03 percent of the reads to antimicrobial resistance genes. By comparison, 0.2 percent of the reads originated from people and 29 percent of the reads originated from bacteria.
In all, the researchers detected 1,546 different genera. The dominant bacteria genera included the fecal-linked Faecalibacterium, Bacteroides, and Escherichia, but also present were likely environmental bacteria such as Acidovorax and Acinetobacter, indicating that sewage has a complex bacterial composition. Still, they noted that their sewage samples more closely resembled human fecal microbiome samples than those of chickens, pigs, or mice.
Through these samples, the researchers identified 1,625 different antimicrobial resistance genes, including recently emerged resistance genes like CTX-M, NDM, mcr, and optrA.
When they analyzed these genes based on the class of antimicrobial to which they provide resistance, the researchers noted that samples from Europe and North America had more macrolide resistance genes, while samples from Asian and Africa had more sulfonamide and phenicol resistance genes.
Principal coordinate and heat map analyses likewise separated the samples by geography, with the samples from Europe, North America, and Oceania clustering together and samples from Africa, Asia, and South America clustering together. These groups, the researchers noted, were largely driven by the higher levels of resistance to tetracyclines, aminoglycosides, beta-lactams, sulfonamides, and trimethoprims in the Africa, Asia, and South America cluster.
In particular, they found samples from Australia and New Zealand had the lowest diversity of resistance genes, while Brazil, India, and Vietnam had the highest level of resistance gene diversity.
While some studies have suggested that increased antimicrobial use correlates with increased resistance to antimicrobials in general, the researchers found that to not be the case in their samples. Through two different models, the researchers noted an uptick in resistance genes was linked to increased use of the related antimicrobial, but that there no associated overall increase in resistance.
By examining the association of more than 1,500 variables from the World Bank's Health, Nutrition, and Population dataset and its Development indicator dataset, the research sought to tease out other factors influencing antimicrobial resistance. They found that variables associated with sanitation and general health were related to antimicrobial resistance levels.
They further found these variables could predict antimicrobial resistance, predicting, for instance, the Netherlands, New Zealand, and Sweden to have the lowest levels of antimicrobial resistance, and Tanzania, Vietnam, and Nigeria to have the highest.
The researchers plan to develop this approach into an antimicrobial surveillance system that monitors where resistance is present and gauge where it may spread.