Authors: McArthur AG, Wright GD. Curr Opin Microbiol. 2015 Jul 31;27:45-50.
Antimicrobial resistance is a global health challenge and has an evolutionary trajectory ranging from proto-resistance in the environment to untreatable clinical pathogens. Resistance is not static, as pathogenic strains can move among patient populations and individual resistance genes can move among pathogens. Effective treatment of resistant infections, antimicrobial stewardship, and new drug discovery increasingly rely upon genotype information, powered by decreasing costs of DNA sequencing. These new approaches will require advances in microbial informatics, particularly in development of reference databases of molecular determinants such as our Comprehensive Antibiotic Resistance Database and clinical metadata, new algorithms for prediction of resistome and resistance phenotype from genotype, and new protocols for global collection and sharing of high-throughput molecular epidemiology data.
McArthur, A.G., Waglechner, N., Nizam, F., Pereira, S.K., Jia, B., Sardar, D., Westman, E.L., Pawlowski, A.C., Johnson, T., Lo, R., Courtot, M., Brinkman, F.S., Williams, L.E., Frye, J.G., & Wright, G.D. 2015. The Comprehensive Antibiotic Resistance Database. Presentation at the 4th ASM Conference on Antimicrobial Resistance in Zoonotic Bacteria and Foodborne Pathogens, Washington, District of Columbia.
Antimicrobial resistance (AMR) is among the most pressing public health crises of the 21st Century. Despite the importance of resistance to health, this field has been slow to take advantage of genome scale tools. Rather, phenotype based criteria dominate the epidemiology of antibiotic action and effectiveness. As a result, there is a poor understanding of which antibiotic resistance genes are in circulation, which ones are a threat, and how clinicians and public health workers can manage the crisis of resistance. However, DNA sequencing is rapidly decreasing in cost and as such we are on the cusp of an age of high-throughput molecular epidemiology. What are needed are tools for rapid, accurate analysis of DNA sequence data for the genetic underpinnings of antibiotic resistance. In an effort to address this problem, we have created the Comprehensive Antibiotic Resistance Database (arpcard.mcmaster.ca). This database is a rigorously curated collection of known antibiotics, targets, and resistance determinants. It integrates disparate molecular and sequence data, provides a unique organizing principle in the form of the Antibiotic Resistance Ontology (ARO), and can quickly identify putative antibiotic resistance genes in raw genome sequences using the novel Resistance Gene Identifier (RGI). Here we review the current state of the CARD, particularly recent advances in the curation of resistance determinants and the structure of the ARO. We will also present our plans for development of semi- and fully-automated text mining algorithms for curation of broader AMR data, construction of Probabilistic Graphic Models for improved AMR phenotype prediction, and development of portable command-line genome analysis tools.
Williams, L.E., A.G. McArthur, N. Waglechner, F. Nizam, P.T. Desai, M. McClelland, G.M. Weinstock, J.B. Barrett, L.M. Hiott, C.R. Jackson, & J.G. Frye. 2014. Genetic variation and genomic context of antibiotic resistance genes and mobile genetic elements in Salmonella from non-human animals. Presentation at the 114th General Meeting of the American Society for Microbiology, Boston, Massachusetts.
Zittermann, S.I., A.G. McArthur, N.V. Fittipaldi, V. Braun, L. Vrbova, D. Middleton, G. Mallo, R. Ahmed, P. Huk, M. Lombos, V.G. Allen. 2014. Whole genome sequencing of Salmonella Enteritidis for public health investigation. Presentation at the 114th General Meeting of the American Society for Microbiology, Boston, Massachusetts.
Objective: To understand the spread of drug resistance and identifying diagnostic probes among the local tuberculosis (TB) strains in order to design rational control tools for tuberculosis controls. Methods: TA cloning and sequencing were used to characterize mutation associated with RIF resistance in 69 bp region of the gene, rpoB. The analysis identified two regions of mutations but no unusual insertion and deletion. No mutation was observed in RIF sensitive strains. Results: We employed Random Amplified Polymorphic DNA (RAPD) analysis for typing strains of M. tuberculosis to determine whether new strains were present among M. tuberculosis isolates circulating in Yaounde. Three groups (I to III) of M. tuberculosis were identified among 93 isolates randomly selected. RAPD analysis provided a rapid and easy means of identifying polymorphism in M. tuberculosis isolates, and it was found to be a valuable alternative epidemiological tool. RAPD was used to select the new site of diagnostic by PCR. Also single nucleotide polymorphisms between M. tuberculosis and M. bovis were found, suggesting that RAPD can be a useful technique for distinguishing between species. Conclusions: Molecular typing is defined as the integration of conventional epidemiological approach to track specific strains of pathogens in order to understand the distribution of disease in populations.