Combatting Antibiotic Resistance Using Surveillance – click on the image to watch the 10 minute video. More details here.
The completion of the human genome project in 2001 sparked the beginning of a sequencing revolution with applications that are only now being realized by researchers. The decreasing cost of DNA sequencing has ignited a continuous generation of genomic data with a limited number of researchers able to manipulate the output. Consequentially the demand to examine this genetic information has forced bioinformaticians to improve the analytical tools involved in sequence analysis. Galaxy is a user-friendly analytical platform where researchers without a computational background can navigate their way through an investigation and use various analytical tools and workflows to assist them with their genomic research (1). Galaxy enables the addition of novel software into the environment by individual users to fill in the gaps of tools that haven’t been created by the Galaxy team. This project will focus on a particular analytical gap concerning tools related to antibiotic resistance, phylogenetics, and bacterial virulence. Currently, the proposed software to be adapted to the galaxy setting includes a resistance gene identifier (RGI) associated with the comprehensive antibiotic resistance database (CARD) (2), a single nucleotide polymorphism identifier (BANSP) , and novel virulence factor identification software associated with the virulence factor database (VFDB) (3). The combination of Galaxy’s existing ToolShed and these unique additions will create a comprehensive analytical environment that can be applied to realistic situations. One such situation that this project will concentrate on refers specifically to the outbreaks of Clostridium difficile (C. diff) in the health care system.
The loss of effective antimicrobials is reducing the ability to protect the global population from infectious diseases, leading to profound impacts on the healthcare system, international trade, agriculture, and environment. The field of antibiotic drug discovery and the monitoring of the dynamic and new antibiotic resistance elements have yet to fully exploit the power of the genome revolution. The curation and directed development of the Comprehensive Antibiotic Database (CARD) will advance the understanding of the genetics, genomics, and threat severity of antibiotic resistance, while simultaneously improving its ability to accurately predict and screen for antibiotic resistance genes within raw genomes. Strategically advancing the Antibiotic Resistance Ontology (ARO), the unique organizing principle of the CARD, allows the value of big data in disparate realms of research to be used and understood by the multidisciplinary efforts working to combat the emergence and prevalence of the ESKAPE pathogens, a critical driving force of the global health crisis.
Authors: Freschi et al. Front Microbiol. 2015 Sep 29;6:1036.
The International Pseudomonas aeruginosa Consortium is sequencing over 1000 genomes and building an analysis pipeline for the study of Pseudomonas genome evolution, antibiotic resistance and virulence genes. Metadata, including genomic and phenotypic data for each isolate of the collection, are available through the International Pseudomonas Consortium Database (http://ipcd.ibis.ulaval.ca/). Here, we present our strategy and the results that emerged from the analysis of the first 389 genomes. With as yet unmatched resolution, our results confirm that P. aeruginosa strains can be divided into three major groups that are further divided into subgroups, some not previously reported in the literature. We also provide the first snapshot of P. aeruginosa strain diversity with respect to antibiotic resistance. Our approach will allow us to draw potential links between environmental strains and those implicated in human and animal infections, understand how patients become infected and how the infection evolves over time as well as identify prognostic markers for better evidence-based decisions on patient care.
Authors: Graham CF, Glenn TC, McArthur AG, Boreham DR, Kieran T, Lance S, Manzon RG, Martino JA, Pierson T, Rogers SM, Wilson JY, Somers CM. Mol Ecol Resour. 2015 Nov;15(6):1304-15.
Degraded DNA from suboptimal field sampling is common in molecular ecology. However, its impact on techniques that use restriction site associated next-generation DNA sequencing (RADSeq, GBS) is unknown. We experimentally examined the effects of in situ DNA degradation on data generation for a modified double-digest RADSeq approach (3RAD). We generated libraries using genomic DNA serially extracted from the muscle tissue of 8 individual lake whitefish (Coregonus clupeaformis) following 0-, 12-, 48- and 96-h incubation at room temperature posteuthanasia. This treatment of the tissue resulted in input DNA that ranged in quality from nearly intact to highly sheared. All samples were sequenced as a multiplexed pool on an Illumina MiSeq. Libraries created from low to moderately degraded DNA (12-48 h) performed well. In contrast, the number of RADtags per individual, number of variable sites, and percentage of identical RADtags retained were all dramatically reduced when libraries were made using highly degraded DNA (96-h group). This reduction in performance was largely due to a significant and unexpected loss of raw reads as a result of poor quality scores. Our findings remained consistent after changes in restriction enzymes, modified fold coverage values (2- to 16-fold), and additional read-length trimming. We conclude that starting DNA quality is an important consideration for RADSeq; however, the approach remains robust until genomic DNA is extensively degraded.
The McArthur lab is proud to collaborate with colleagues in the Faculty of Science on the metabolic and transcriptional responses to human inactivity and aging under the leadership of Dr. Stuart Phillips (pictured) of the Department of Kinesiology’s Exercise Metabolism Research Group. Dr. Phillips successfully competed in Faculty of Science Call for Interdisciplinary Projects 2015 to obtain funding for this project, which also includes Dr. Martin Gibala (Department of Kinesiology) and Dr. Philip Britz‐McKibbin of the Department of Chemistry.