Automated centrifugal microfluidic system for the preparation of adaptor-ligated sequencing libraries.

The intensive workload associated with the preparation of high-quality DNA libraries remains a key obstacle toward widespread deployment of sequencing technologies in remote and resource-limited areas. We describe the development of single-use microfluidic devices driven by an advanced pneumatic centrifugal microfluidic platform, the PowerBlade, to automate the preparation of Illumina-compatible libraries based on adaptor ligation methodology. The developed on-chip workflow includes enzymatic DNA fragmentation coupled to end-repair, adaptor ligation, first DNA cleanup, PCR amplification, and second DNA cleanup. This complex workflow was successfully integrated into simple thermoplastic microfluidic devices that are amenable to mass production with injection molding. The system was validated by preparing, on chip, libraries from a mixture of genomic DNA extracted from three common foodborne pathogens (Listeria monocytogenes, Escherichia coli and Salmonella enterica serovar Typhimurium) and comparing them with libraries made via a manual procedure. The two types of libraries were found to exhibit similar quality control metrics (including genome coverage, assembly, and relative abundances) and led to nearly uniform coverage independent of GC content. This microfluidic technology offers a time-saving and cost-effective alternative to manual procedures and robotic-based automation, making it suitable for deployment in remote environments where technical expertise and resources might be scarce. Specifically, it facilitates field practices that involve mid- to low-throughput sequencing, such as tasks related to foodborne pathogen detection, characterization, and microbial profiling.

Exploiting a targeted resistome sequencing approach in assessing antimicrobial resistance in retail foods.

BACKGROUND: With the escalating risk of antimicrobial resistance (AMR), there are limited analytical options available that can comprehensively assess the burden of AMR carried by clinical/environmental samples. Food can be a potential source of AMR bacteria for humans, but its significance in driving the clinical spread of AMR remains unclear, largely due to the lack of holistic-yet-sensitive tools for surveillance and evaluation. Metagenomics is a culture-independent approach well suited for uncovering genetic determinants of defined microbial traits, such as AMR, present within unknown bacterial communities. Despite its popularity, the conventional approach of non-selectively sequencing a sample's metagenome (namely, shotgun-metagenomics) has several technical drawbacks that lead to uncertainty about its effectiveness for AMR assessment; for instance, the low discovery rate of resistance-associated genes due to their naturally small genomic footprint within the vast metagenome. Here, we describe the development of a targeted resistome sequencing method and demonstrate its application in the characterization of the AMR gene profile of bacteria associated with several retail foods. RESULT: A targeted-metagenomic sequencing workflow using a customized bait-capture system targeting over 4,000 referenced AMR genes and 263 plasmid replicon sequences was validated against both mock and sample-derived bacterial community preparations. Compared to shotgun-metagenomics, the targeted method consistently provided for improved recovery of resistance gene targets with a much-improved target detection efficiency (> 300-fold). Targeted resistome analyses conducted on 36 retail-acquired food samples (fresh sprouts, n = 10; ground meat, n = 26) and their corresponding bacterial enrichment cultures (n = 36) reveals in-depth features regarding the identity and diversity of AMR genes, most of which were otherwise undetected by the whole-metagenome shotgun sequencing method. Furthermore, our findings suggest that foodborne Gammaproteobacteria could be the major reservoir of food-associated AMR genetic determinants, and that the resistome structure of the selected high-risk food commodities are, to a large extent, dictated by microbiome composition. CONCLUSIONS: For metagenomic sequencing-based surveillance of AMR, the target-capture method presented herein represents a more sensitive and efficient approach to evaluate the resistome profile of complex food or environmental samples. This study also further implicates retail foods as carriers of diverse resistance-conferring genes indicating a potential impact on the dissemination of AMR.

Draft Genomes of 92 Vibrio Isolates from Warm-Water Shrimps Imported into Canada between 2009 and 2019.

Vibrio spp. were isolated from raw shrimps imported into Canada (2009 to 2019). A total of 92 isolates with various multidrug resistance profiles were sequenced, including 59 V. parahaemolyticus, 12 V. diabolicus, 10 V. cholerae, 7 V. alginolyticus, 1 V. campbellii, 1 V. harveyi, 1 V. owensii, and 1 V. vulnificus isolate.

Draft Genomes of 75 Vibrio Isolates from Retail Mollusks Collected in Canada between 2014 and 2018.

Vibrio spp. isolated from fresh retail mollusk samples were selected for sequencing based on their antimicrobial resistance burden. The de novo genomes include those for Vibrio alginolyticus (n = 48), V. diabolicus (n = 15), V. parahaemolyticus (n = 3), V. cholerae (n = 2), V. metoecus (n = 1), V. vulnificus (n = 1), V. fluvialis (n = 1), and unidentified Vibrio spp. (n = 4).

Draft Genomes of 83 Vibrio Isolates from Fresh Canadian Mollusks.

A subset of Vibrio spp. isolated from fresh Canadian mollusks (2014 to 2018) were selected for sequencing based on antimicrobial resistance profiles. The resulting de novo draft genomes include 38 Vibrio alginolyticus, 32 V. diabolicus, 10 V. parahaemolyticus, 1 V. cholerae, 1 V. ordalii, and 1 Vibrio sp. isolate.

Enhanced annotations and features for comparing thousands of Pseudomonas genomes in the Pseudomonas genome database.

The Pseudomonas Genome Database (http://www.pseudomonas.com) is well known for the application of community-based annotation approaches for producing a high-quality Pseudomonas aeruginosa PAO1 genome annotation, and facilitating whole-genome comparative analyses with other Pseudomonas strains. To aid analysis of potentially thousands of complete and draft genome assemblies, this database and analysis platform was upgraded to integrate curated genome annotations and isolate metadata with enhanced tools for larger scale comparative analysis and visualization. Manually curated gene annotations are supplemented with improved computational analyses that help identify putative drug targets and vaccine candidates or assist with evolutionary studies by identifying orthologs, pathogen-associated genes and genomic islands. The database schema has been updated to integrate isolate metadata that will facilitate more powerful analysis of genomes across datasets in the future. We continue to place an emphasis on providing high-quality updates to gene annotations through regular review of the scientific literature and using community-based approaches including a major new Pseudomonas community initiative for the assignment of high-quality gene ontology terms to genes. As we further expand from thousands of genomes, we plan to provide enhancements that will aid data visualization and analysis arising from whole-genome comparative studies including more pan-genome and population-based approaches.

IslandViewer 3: more flexible, interactive genomic island discovery, visualization and analysis.

IslandViewer (http://pathogenomics.sfu.ca/islandviewer) is a widely used web-based resource for the prediction and analysis of genomic islands (GIs) in bacterial and archaeal genomes. GIs are clusters of genes of probable horizontal origin, and are of high interest since they disproportionately encode genes involved in medically and environmentally important adaptations, including antimicrobial resistance and virulence. We now report a major new release of IslandViewer, since the last release in 2013. IslandViewer 3 incorporates a completely new genome visualization tool, IslandPlot, enabling for the first time interactive genome analysis and gene search capabilities using synchronized circular, horizontal and vertical genome views. In addition, more curated virulence factors and antimicrobial resistance genes have been incorporated, and homologs of these genes identified in closely related genomes using strict filters. Pathogen-associated genes have been re-calculated for all pre-computed complete genomes. For user-uploaded genomes to be analysed, IslandViewer 3 can also now handle incomplete genomes, with an improved queuing system on compute nodes to handle user demand. Overall, IslandViewer 3 represents a significant new version of this GI analysis software, with features that may make it more broadly useful for general microbial genome analysis and visualization.

The origin and spread of a cooperative replicase in a prebiotic chemical system.

The origin of life requires the emergence of a system of autocatalytic polymers such as RNA. We consider a trans-acting replicase that catalyses replication of a template (either a copy of itself or another sequence). Our model includes alternating plus/minus strand replication where only the plus strand is a catalyst. Prebiotic chemistry generates random sequences and allows for non-catalysed, template-directed synthesis of new strands. These chemical reactions are insufficient to sustain replication, but they provide a background in which the first replicase can arise. In the well-mixed case, the minimum value of the catalytic rate parameter k for which a stable replicating state survives scales as 1/f, where f is the fraction of random sequences that are catalysts. When catalysts are rare (f→0), the replicating state is not stable in for any finite k because the replicases are overrun by parasitic templates already present in the prebiotic system, and by additional parasites created by mutation of the catalyst. In contrast, in 2d spatial simulations, the replicating state is stable for moderate k with appropriate values of the local diffusion constant. We calculate the probability of spread of the replicating state from a single isolated catalyst. This occurs in a parameter range that is narrower than that in which existing replicators are stable. The 2d model uses 'Two׳s Company' rules, where two molecules on a site may replicate, but crowding occurs when three molecules are on one site. A mean-field theory is presented which predicts the most important results of the spatial model. Our results emphasize that the origin of replication is a spatially-localized stochastic transition between a 'dead' state controlled by prebiotic chemistry and a 'living' state controlled by autocatalytic replication.