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The MinION sequencer (Oxford Nanopore Technologies) is a paradigm shifting device allowing rapid, real time long read sequencing of nucleic acids. Yet external benchmarking of this technologies’ capabilities has not been extensively reported, nor has thorough evaluation of its utility for field-based analysis with sub-optimal sample types been described. The aim of this study was to evaluate the capability of the MinION sequencer for bacterial genomic and metagenomic applications, with specific emphasis placed on the quality, yield, and accuracy of generated sequence data. Two independent laboratories at the National Microbiology Laboratory (Public Health Agency of Canada), sequenced a set of microbes in replicate, using the currently available flowcells, sequencing chemistries, and software available at the time of the experiment. Overall sequencing yield and quality improved through the course of this set of experiments. Sequencing alignment accuracy was high reaching 97% for all 2D experiments, though was slightly lower for 1D sequencing (94%). 1D sequencing provided much longer sequences than 2D. Both sequencing chemistries performed equally well in constructing genomic assemblies. There was evidence of barcode cross-over using both the native and PCR barcoding methods. Despite the sub-optimal nature of samples sequenced in the field, sequences attributable to B. anthracis the target organism used in this scenario, could none-the-less be detected. Together, this report showcases the rapid advancement in this technology and its utility in the context of genomic sequencing of microbial isolates of importance to public health.

From pathogen detection to genome or plasmid closure, the utility of the Oxford Nanopore Technologies (ONT) MinION for microbiological analysis has been well documented. The MinION’s small footprint, portability, and real-time analytic capability situates it well to address challenges in the field of unbiased pathogen detection, as a component of a security investigation. To this end, a multicenter evaluation of the effect of alternative analytical approaches on the outcome of MinION-based sequencing, using a set of well-characterized samples, was explored in a field-based scenario. Three expert scientific response groups evaluated known bacterial DNA extracts as part of an international first responder (Chemical, Biological, Radiological) training exercise. Samples were prepared independently for analysis using the Rapid and/or Rapid PCR sequencing kits as per the best practices of each of the participating groups. Analyses of sequence data were in turn conducted using varied approaches including ONTs What’s in my pot (WIMP) architecture and in-house computational pipelines. Microbial community composition and the ability of each approach to detect pathogens was compared. Each group demonstrated the ability to detect all species present in samples, although several organisms were detected at levels much lower than expected with some organisms even falling below 1% abundance. Several ‘contaminant’ near neighbor species were also detected, at low abundance. Regardless of the sequencing approach chosen, the observed composition of the bacterial communities diverged from the input composition in each of the analyses, although sequencing conducted using the rapid kit produced the least distortion when compared to PCR-based library preparation methods. One of the participating groups generated drastically lower sequencing output than the other groups, likely attributed to the limited computer hard drive capacity, and occasional disruption of the internet connection. These results provide further consideration for conducting unbiased pathogen identification within a field setting using MinION sequencing. However, the benefits of this approach in providing rapid results and unbiased detection must be considered along with the complexity of sample preparation and data analytics, when compared to more traditional methods. When utilized by trained scientific experts, with appropriate computational resources, the MinION sequencing device is a useful tool for field-based pathogen detection in mixed samples.

The advent and widespread application of next-generation sequencing (NGS) technologies to the study of microbial genomes has led to a substantial increase in the number of studies in which whole genome sequencing (WGS) is applied to the analysis of microbial genomic epidemiology. However, microorganisms such as Mycobacterium tuberculosis (MTB) present unique problems for sequencing and downstream analysis based on their unique physiology and the composition of their genomes. In this study, we compare the quality of sequence data generated using the Nextera and TruSeq isolate preparation kits for library construction prior to Illumina sequencing-by-synthesis. Our results confirm that MTB NGS data quality is highly dependent on the purity of the DNA sample submitted for sequencing and its guanine-cytosine content (or GC-content). Our data additionally demonstrate that the choice of library preparation method plays an important role in mitigating downstream sequencing quality issues. Importantly for MTB, the Illumina TruSeq library preparation kit produces more uniform data quality than the Nextera XT method, regardless of the quality of the input DNA. Furthermore, specific genomic sequence motifs are commonly missed by the Nextera XT method, as are regions of especially high GC-content relative to the rest of the MTB genome. As coverage bias is highly undesirable, this study illustrates the importance of appropriate protocol selection when performing NGS studies in order to ensure that sound inferences can be made regarding mycobacterial genomes.

Inflammatory complications following ileal pouch-anal anastomosis (IPAA) for ulcerative colitis (UC) are common and thought to arise through mechanisms similar to de novo onset inflammatory bowel disease. The aim of this study was to determine whether specific organisms in the tissue-associated microbiota are associated with inflammatory pouch complications. Patients having previously undergone IPAA were recruited from Mount Sinai Hospital. Clinical and demographic information were collected and a pouchoscopy with biopsy of both the pouch and afferent limb was performed. Patients were classified based on post-surgical phenotype into four outcome groups: familial adenomatous polyposis controls (FAP), no pouchitis, pouchitis, and Crohn's disease-like (CDL). Pyrosequencing of the 16S rRNA V1-V3 hypervariable region, and quantitative PCR for bacteria of interest, were used to identify organisms present in the afferent limb and pouch. Associations with outcomes were evaluated using exact and non-parametric tests of significance. Analysis at the phylum level indicated that Bacteroidetes were detected significantly less frequently (P<0.0001) in the inflammatory outcome groups (pouchitis and CDL) compared to both FAP and no pouchitis. Conversely, Proteobacteria were detected more frequently in the inflammatory groups (P=0.01). At the genus level, organisms associated with outcome were detected less frequently among the inflammatory groups compared to those without inflammation. Several of these organisms, including Bacteroides (P<0.0001), Parabacteroides (P≤2.2x10(-3)), Blautia (P≤3.0x10(-3)) and Sutterella (P≤2.5x10(-3)), were associated with outcome in both the pouch and afferent limb. These associations remained significant even following adjustment for antibiotic use, smoking, country of birth and gender. Individuals with quiescent disease receiving antibiotic therapy displayed similar reductions in these organisms as those with active pouch inflammation. Specific genera are associated with inflammation of the ileal pouch, with a reduction of typically ubiquitous organisms characterizing the inflammatory phenotypes.

Background The reliability of culture-independent pathogen detection in foods using metagenomics is contingent on the quality and composition of the reference database. The inclusion of microbial sequences from a diverse representation of taxonomies in universal reference databases is recommended to maximize classification precision for pathogen detection. However, these sizable databases have high memory requirements that may be out of reach for some users. In this study, we aimed to assess the performance of a foodborne pathogen (FBP)-specific reference database (taxon-specific) relative to a universal reference database (taxon-agnostic). We tested our FBP-specific reference database's performance for detecting Listeria monocytogenes in two complex food matrices—ready-to-eat (RTE) turkey deli meat and prepackaged spinach—using three popular read-based DNA-to-DNA metagenomic classifiers: Centrifuge, Kraken 2 and KrakenUniq. Results In silico host sequence removal led to substantially fewer false positive (FP) classifications and higher classification precision in RTE turkey deli meat datasets using the FBP-specific reference database. No considerable improvement in classification precision was observed following host filtering for prepackaged spinach datasets and was likely a consequence of a higher microbe-to-host sequence ratio. All datasets classified with Centrifuge using the FBP-specific reference database had the lowest classification precision compared to Kraken 2 or KrakenUniq. When a confidence-scoring threshold was applied, a nearly equivalent precision to the universal reference database was achieved for Kraken 2 and KrakenUniq. Recall was high for both reference databases across all datasets and classifiers. Substantially fewer computational resources were required for metagenomics-based detection of L. monocytogenes using the FBP-specific reference database, especially when combined with Kraken 2. Conclusions A universal (taxon-agnostic) reference database is not essential for accurate and reliable metagenomics-based pathogen detection of L. monocytogenes in complex food matrices. Equivalent classification performance can be achieved using a taxon-specific reference database when the appropriate quality control measures, classification software, and analysis parameters are applied. This approach is less computationally demanding and more attainable for the broader scientific and food safety communities.

In July 2022, an unvaccinated young adult living in Rockland County, New York became paralyzed due to a vaccine-derived poliovirus type 2 (VDPV2) infection that was internationally transmitted. Wastewater surveillance in New York State uncovered VDPV2 in neighboring counties, showing silent community spread. These communities have strong epidemiological links to some vaccine-hesitant communities in Canada, spurring the need to monitor these populations for potential poliovirus importation. At the time, Canada did not have an established poliovirus wastewater method. We initiated this study to apply molecular methods to detect poliovirus in these communities and establish poliovirus wastewater surveillance capabilities in Canada. We sequence confirmed one poliovirus detection on August 30th, 2022 using both viral isolation and direct detection methods. Subsequent retrospective and prospective sampling was initiated, resulting in another sequence confirmed detection of VDPV2 in an overlapping catchment area collected on August 27th, 2022. Both VDPV2 detections were genetically linked to the New York clinical case. No clinical cases of poliomyelitis were detected in Canada during this study. The sporadic detection of VDPV2 in Canadian wastewater supports a travel-related shedding event without community transmission. Furthermore, we show that a direct detection method is sensitive to sequence confirm poliovirus in wastewater samples.

Background The advent of metagenomic sequencing provides microbial abundance patterns that can be leveraged for sample origin prediction. Supervised machine learning classification approaches have been reported to predict sample origin accurately when the origin has been previously sampled. Using metagenomic datasets provided by the 2019 CAMDA challenge, we evaluated the influence of variable technical, analytical and machine learning approaches for result interpretation and novel source prediction. Results Comparison between 16S rRNA amplicon and shotgun sequencing approaches as well as metagenomic analytical tools showed differences in normalized microbial abundance, especially for organisms present at low abundance. Shotgun sequence data analyzed using Kraken2 and Bracken, for taxonomic annotation, had higher detection sensitivity. As classification models are limited to labeling pre-trained origins, we took an alternative approach using Lasso-regularized multivariate regression to predict geographic coordinates for comparison. In both models, the prediction errors were much higher in Leave-1-city-out than in 10-fold cross validation, of which the former realistically forecasted the increased difficulty in accurately predicting samples from new origins. This challenge was further confirmed when applying the model to a set of samples obtained from new origins. Overall, the prediction performance of the regression and classification models, as measured by mean squared error, were comparable on mystery samples. Due to higher prediction error rates for samples from new origins, we provided an additional strategy based on prediction ambiguity to infer whether a sample is from a new origin. Lastly, we report increased prediction error when data from different sequencing protocols were included as training data. Conclusions Herein, we highlight the capacity of predicting sample origin accurately with pre-trained origins and the challenge of predicting new origins through both regression and classification models. Overall, this work provides a summary of the impact of sequencing technique, protocol, taxonomic analytical approaches, and machine learning approaches on the use of metagenomics for prediction of sample origin.

Whereas the infant gut microbiome is the subject of intense study, relatively little is known regarding the nares microbiome in newborns and during early life. This study aimed to survey the typical composition and diversity of human anterior nare microflora for developing infants over time, and to explore how these correlate to their primary caregivers. Single nare swabs were collected at five time points over a one-year period for each subject from infant-caregiver pairs. Our study comprised of 50 infants (recruited at 2 weeks, post delivery) and their 50 primary caregivers. Applying the chaperonin-60 (cpn60) universal target (UT) amplicon as our molecular barcoding marker to census survey the microbial communities, we longitudinally surveyed infant nares microbiota at 5 time points over the course of the first year of life. The inter- and intra-subject diversity was catalogued and compared, both longitudinally and relative to their adult primary caregivers. Although within-subject variability over time and inter-subject variability were both observed, the assessment detected only one or two predominant genera for individual infant samples, belonging mainly to phyla Actinobacteria, Firmicutes, and Proteobacteria. Consistent with previously observed microbial population dynamics in other body sites, the diversity of nares microflora increased over the first year of life and infants showed differential operational taxonomic units (OTUs) relative to their matched primary caregiver. The collected evidence also support that both temporal and seasonal changes occur with respect to carriage of potentially pathogenic bacteria (PPBs), which may influence host predisposition to infection. This pilot study surveying paired infant/caregiver nare microbiomes provides novel longitudinal diversity information that is pertinent to better understanding nare microbiome development in infants.

Canada has one of the lowest rates of tuberculosis (TB) in the world, however, among certain sub-populations, disease incidence rates approach those observed in sub-Saharan Africa, and other high incidence regions. In this study, we applied mycobacterial interspersed repetitive unit (MIRU) variable number of tandem repeat (VNTR) and whole genome sequencing (WGS) to the analysis of Mycobacterium tuberculosis isolates obtained from Northern communities in the territory of Nunavut. WGS was carried out using the Illumina MiSeq, with identified variants used to infer phylogenetic relationships and annotated to infer functional implications. Additionally, the sequencing data from these isolates were augmented with publically available WGS to evaluate data from the Nunavut outbreak in the broader Canadian context. In this study, isolates could be classified into four major clusters by MIRU-VNTR analysis. These could be further resolved into sub-clusters using WGS. No evidence for antimicrobial resistance, either genetic or phenotypic, was observed in this cohort. Among most subjects with multiple samples, reactivation/incomplete treatment likely contributed to recurrence. However, isolates from two subjects appeared more likely to have occurred via reinfection, based on the large number of genomic single nucleotide variants detected. Finally, although quite distinct from previously reported Canadian MTB strains, isolates obtained from Nunavut clustered most closely with a cohort of samples originating in the Nunavik region of Northern Quebec. This study demonstrates the benefit of using WGS for discriminatory analysis of MTB in Canada, especially in high incidence regions. It further emphasizes the importance of focusing epidemiological intervention efforts on interrupting transmission chains of endemic TB throughout Northern communities, rather than relying on strategies applied in regions where the majority of TB cases result from importation of foreign strains.

Mutations in the erm(41) gene of M.abscessus group organisms are associated with differences in inducible macrolide resistance, with current recommendations being to hold rapidly growing isolates for up to 14 days in order to ensure that resistance which develops more slowly can be detected. This study aimed to determine the ideal incubation time for accurate identification of inducible macrolide resistance as well as to determine if there was an association between the time taken to detect inducible resistance in M.abscessus group organisms and their erm(41) sequevar. We amplified and sequenced the erm(41) genes of a total of 104 M.abscessus group isolates and determined their sequevars. The isolates were tested for phenotypic clarithromycin resistance at days 7, 10, 14 and 21, using Trek Diagnostics Sensititre RAPMYCO microbroth dilution plates. Associations between erm(41) gene sequevars and time to detection of resistance were evaluated using Fisher's exact test in R. The samples included in this study fell into 14 sequevars, with the majority of samples falling into Sequevar02 (16), Sequevar06 (15), Sequevar08 (7) and Sequvar 15 (31), and several isolates that were in small clusters, or unique. The majority (82.7%) of samples exhibiting inducible macrolide resistance were interpreted as resistant by day 7. Two isolates in Sequevar02, which has a T28C mutation that is associated with sensitivity, showed intermediate resistance at day 14, though the majority (13) were sensitive at day 14. The majority of isolates with inducible macrolide resistance fell into Sequevars 06,08 and 15, none of which contain the T28C mutation. These sequevars were analyzed to determine if there was any correlation between sequevar and time to detection of resistance. None was found. Based on these findings, we recommend the addition of a day 7 read to the CLSI guidelines to improve turn-around-times for these isolates. It is also recommended that erm(41) gene sequencing be added to routine phenotypic testing for the resolution of cases with difficult-to-interpret phenotypic results.