New Delhi Metallo-Beta-Lactamase (NDM) plasmid predictions
The complete detection and genome sequencing of resistance plasmids is required to understand the co-occurrence of resistance genes on plasmids and their transmission, which is necessary to mitigate the spread of drug resistant bacterial infections. One group of multi-drug resistance plasmids of interest are the New Delhi Metallo-beta-lactamase (NDM) associ-ated plasmids. Bacteria pathogens with NDM genes are resistant to a broad range of beta-lactam antibiotics, including carbapenems, a mainstay for treating bacterial infections. We sequenced clinical isolates collected from patients that failed to respond to antibiotic treatments in the Hamilton-Niagara community using Next Generation Sequencing (NGS) technology, which is the standard technique for sequencing bacterial genomes. I analyzed their assembled genomes via the development of a new resistance plasmid prediction bioinformatics pipeline: RGI:Mobilome. RGI:Mobilome predicted NDM bearing plasmids in 15 isolates, along with other resistance genes on plasmids. However, the NDM plasmid predictions of all 15 isolates were fragmented due to incomplete genome assemblies, caused by repetitive sequences within bacterial genomes and use of short-read NGS technology. However, plasmid predictions greatly improved when we leveraged the high nucleotide accuracy of NGS reads and the structural resolving power of long reads generated with the Oxford Nanopore Technology (ONT) to produce ‘hybrid’ genome assemblies. From the 15 putative hybrid assembly NDM plasmids, one plasmid was a complete match to a known pKP-NDM1 plasmid, seven plasmids were “variants” of known and well characterized plasmids, and the remaining seven plasmids were “distant homologs” of known and well characterized plasmids, suggesting previously undescribed NDM-associated plasmids in our community. This thesis project reveals the diversity of NDM plasmid types within the Hamilton-Niagara community, which is valuable to epidemiologists and public health practitioners to devise actionable plans required to mitigate the spread of multi-drug resistance NDM plasmids and for clinicians to treat infections caused by NDM positive strains.
Jalees A. Nasir, Robert A. Kozak, Patryk Aftanas, Amogelang R. Raphenya, Kendrick M. Smith, Finlay Maguire, Hassaan Maan, Muhannad Alruwaili, Arinjay Banerjee, Hamza Mbareche, Brian P. Alcock, Natalie C. Knox, Karen Mossman, Bo Wang, Julian A. Hiscox, Andrew G. McArthur, & Samira Mubareka
Genome sequencing of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is increasingly important to monitor the transmission and adaptive evolution of the virus. The accessibility of high-throughput methods and polymerase chain reaction (PCR) has facilitated a growing ecosystem of protocols. Two differing protocols are tiling multiplex PCR and bait capture enrichment. Each method has advantages and disadvantages but a direct comparison with different viral RNA concentrations has not been performed to assess the performance of these approaches. Here we compare Liverpool amplification, ARTIC amplification, and bait capture using clinical diagnostics samples. All libraries were sequenced using an Illumina MiniSeq with data analyzed using a standardized bioinformatics workflow (SARS-CoV-2 Illumina GeNome Assembly Line; SIGNAL). One sample showed poor SARS-CoV-2 genome coverage and consensus, reflective of low viral RNA concentration. In contrast, the second sample had a higher viral RNA concentration, which yielded good genome coverage and consensus. ARTIC amplification showed the highest depth of coverage results for both samples, suggesting this protocol is effective for low concentrations. Liverpool amplification provided a more even read coverage of the SARS-CoV-2 genome, but at a lower depth of coverage. Bait capture enrichment of SARS-CoV-2 cDNA provided results on par with amplification. While only two clinical samples were examined in this comparative analysis, both the Liverpool and ARTIC amplification methods showed differing efficacy for high and low concentration samples. In addition, amplification-free bait capture enriched sequencing of cDNA is a viable method for generating a SARS-CoV-2 genome sequence and for identification of amplification artifacts.
Ana T Duggan, Jennifer Klunk, Ashleigh F Porter, Anna N Dhody, Robert Hicks, Geoffrey L Smith, Margaret Humphreys, Andrea M McCollum, Whitni B Davidson, Kimberly Wilkins, Yu Li, Amanda Burke, Hanna Polasky, Lowell Flanders, Debi Poinar, Amogelang R Raphenya, Tammy T Y Lau, Brian Alcock, Andrew G McArthur, G Brian Golding, Edward C Holmes, Hendrik N Poinar
Vaccination has transformed public health, most notably including the eradication of smallpox. Despite its profound historical importance, little is known of the origins and diversity of the viruses used in smallpox vaccination. Prior to the twentieth century, the method, source and origin of smallpox vaccinations remained unstandardised and opaque. We reconstruct and analyse viral vaccine genomes associated with smallpox vaccination from historical artefacts. Significantly, we recover viral molecules through non-destructive sampling of historical materials lacking signs of biological residues. We use the authenticated ancient genomes to reveal the evolutionary relationships of smallpox vaccination viruses within the poxviruses as a whole.
Image: CDC/Dr. Fred Murphy; Sylvia Whitfield, CC BY
The ongoing COVID-19 pandemic is the greatest health-care challenge of this generation. Early viral genome sequencing studies of small cohorts have indicated the possibility of distinct severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genotypes.1 If these subtypes result in an altered virus tropism or pathogenesis in infected hosts, this could have immediate implications for vaccine design, drug development, and efforts to control the pandemic. Therefore, the genomic surveillance and characterisation of circulating viral strains is a high priority for research and development. To facilitate the epidemiological tracking of SARS-CoV-2, researchers worldwide have created various web-portals and tools, such as the Johns Hopkins University COVID-19 dashboard. An unprecedented effort to make COVID-19-related data accessible in near real-time has resulted in more than 25 000 publicly available genome sequences of SARS-CoV-2 on Global Initiative on Sharing All Influenza Data (GISAID). Although platforms to survey epidemiological data are prevalent, tools that summarise publicly available viral genome data are scarce and those that are available do not offer users the ability to analyse in-house sequencing data. To address this gap, we have developed an accessible application, the COVID-19 Genotyping Tool (CGT).
Full paper at The Lancet Digital Health.
Featured on CBC’s The National: Scientists develop an app that tracks how COVID-19 mutates person-to-person
Thanks to hard work by Jalees Nasir, Amos Raphenya, Dr. Kendrick Smith (Perimeter Institute), and Dr. Finlay Maguire (Dalhousie) with help from our Ontario Coronavirus Genomics Coalition (ONCoV) colleagues, particularly Dr. Jared Simpson (OICR), Dr. Hamza Mbareche (Sunnybrook Health Sciences Centre), Dr. Hassaan Mann (Vector Institute), and Dr. Natalie Knox (Public Health Agency of Canada), the McArthur lab is proud to release the SARS-CoV-2 Illumina GeNome Assembly Line (SIGNAL) bioinformatics workflow for SARS-CoV-2 genome analysis based on Illumina sequencing data, available here: https://github.com/jaleezyy/covid-19-signal
RNA sequencing (RNA-Seq) is a complicated protocol, both in the laboratory in generation of data and at the computer in analysis of results. Several decisions during RNA-Seq library construction have important implications for analysis, most notably strandedness during complementary DNA library construction. Here, we clarify bioinformatic decisions related to strandedness in both alignment of DNA sequencing reads to reference genomes and subsequent determination of transcript abundance.
The McArthur lab is honoured to collaborate with our clinical colleagues across Ontario in sequencing of SARS-CoV-2 clinical isolates, to better understand the epidemiology of the pandemic. Our colleague Dr. Samira Mubareka explains it best:
The McArthur lab welcomes back summer students Rachel Tran & Arman Edalatmand plus first timers Marcel Jansen & Emily Panousis! These four will be covering a lot of ground this summer, including AMR transmission dynamics, machine learning for automated bio curation, prediction of antibiotic production in Streptomycetes, algorithm development, and data harmonization.