Nicole Ricker

This article presents Sequenoscope: a bioinformatics pipeline for analysing Oxford Nanopore Technologies (ONT) adaptive sampling sequencing data. Sequenoscope features three main modules: filter_ONT for filtering raw reads and creating a FASTQ file with a subset of reads for further analyses, analyze for generating sequencing and read mapping statistics against the provided reference taxon sequences and plot for interactive data summarization, comparison, and visualization between two datasets/test conditions. Here, we demonstrate the ability of the pipeline to analyse ONT adaptive sampling sequence data and provide examples of the outputs users can expect using data we generated. Adaptive sampling was performed on two ZymoBIOMICS Microbial Community DNA Standards, log-distributed (Cat# D6311) and even-distributed (Cat# D6306) formulations, with targeted depletions of Listeria monocytogenes . By comparing the test and control experimental data in FASTQ files from the sequencing runs, Sequenoscope showed that depletion of L. monocytogenes was successful by providing users with parameters to compare such as taxon coverage, read length and types of pore-level decisions made during sequencing. Although Sequenoscope was designed for ONT adaptive sampling data analysis, it supports short-read data from other sequencing platforms such as Illumina, allowing for the direct comparison of any two experimental conditions or cross-platform benchmarking.

The use of carbapenem antibiotics is threatened by the global spread of carbapenemase-producing Enterobacterales (CPE), bacterial pathogens which hydrolyze these last-resort antimicrobials. Rapid detection of CPE is vital to ensure timely administration of antimicrobial therapy to infected patients, as well as the implementation of infection control measures to prevent outbreaks in healthcare settings. In this study, we report the development of resaCPE, a rapid, low-cost CPE detection method that couples the inactivation of an imipenem disk with a cell viability assay employing a carbapenem-hypersusceptible Escherichia coli strain. Results are interpreted by a simple colorimetric readout in which CPE-positive samples turn pink, while CPE-negative samples remain purple. The assay was validated with a panel of 116 CPE and non-CPE isolates, and its performance was compared with two widely used CPE detection strategies: the modified carbapenem inactivation method (mCIM) and the CARBA-NP test. The resaCPE test demonstrated a sensitivity of 98.7%, outperforming the CARBA-NP (87.8% sensitivity) and the mCIM (96.3% sensitivity) assays. The resaCPE test provides results within 3.5 h, significantly faster than the mCIM, and demonstrated a high degree of specificity (94.1%). Due to the rapid turnaround time, minimal setup requirements, and low cost (~$1 USD/sample), the resaCPE test is a potentially attractive option for primary CPE screening, particularly in lower resource settings. IMPORTANCE: Carbapenem antibiotics serve as a last line of defense against severe bacterial infections. However, these antibiotics are endangered by bacterial pathogens which produce carbapenemases, enzymes that inactivate the carbapenem antibiotics, rendering them ineffective. Infections caused by carbapenemase-producing bacteria are associated with high mortality and pose a significant threat to global health. Rapid and reliable detection of these pathogens is critical to ensure timely treatment and prevent their spread in healthcare settings. Current detection methods suffer from long turnaround times, high cost, or the requirement of specialized laboratory equipment. In this study, we developed resaCPE, a simple, inexpensive, and rapid colorimetric test that identifies carbapenemase-producing bacteria in 3.5 h. This test demonstrated excellent performance when compared to currently employed assays. Due to the rapid turnaround time, low cost, and minimal equipment requirements, the resaCPE test could be a promising alternative for routine carbapenemase screening, particularly in laboratories with limited resources.

This paper presents Sequenoscope: a bioinformatics pipeline for analyzing Oxford Nanopore Technologies (ONT) adaptive sampling sequencing data. Sequenoscope features three main modules: filter_ONT for filtering raw reads and creating a FASTQ file with a subset of reads for further analyses, analyze for generating sequencing and read mapping statistics against the provided reference taxon sequences, and plot for interactive data summarization, comparison, and visualization between two datasets/test conditions. Here we demonstrate the ability of the pipeline to analyze ONT adaptive sampling sequence data and provide examples of the outputs users can expect using data we generated. Adaptive sampling was performed on two ZymoBIOMICS Microbial Community DNA Standards, log-distributed (Cat# D6311) and even-distributed (Cat# D6306) formulations, with targeted depletions of Listeria monocytogenes. By comparing the test and control experimental data in FASTQ files from the sequencing runs, Sequenoscope showed that depletion of L. monocytogenes was successful by providing users with parameters to compare such as taxon coverage, read length, and types of pore-level decisions made during sequencing. Although Sequenoscope was designed for ONT adaptive sampling data analysis, it supports short-read data from other sequencing platforms such as Illumina, allowing for the direct comparison of any two experimental conditions or cross-platform benchmarking.

Extended-spectrum cephalosporin (ESC)-resistant Klebsiella pneumoniae are a problem in human patients and have been studied extensively. However, there is a paucity of information regarding ESC-resistant K. pneumoniae from livestock in general, and in Canada in particular. This study characterized ESC-resistant K. pneumoniae recovered from dairy manure in Ontario, Canada, and their ESC-resistance plasmids. ESC-resistant K. pneumoniae ( n = 73) and K. quasipneumoniae (n = 11) isolates were screened by PCR for bla _CTX-M , bla _CMY and bla _SHV prior to undergoing antimicrobial susceptibility testing using disk diffusion. Isolates from dairy manure carrying bla _CTX-M ( n = 74), and additional isolates from turkeys ( n = 8) and dogs ( n = 2), underwent short-read whole genome sequencing (WGS) and a subset of these ( n = 35) had additional long-read sequencing and hybrid assembly for confirmation. Isolates were characterized using multi-locus sequence typing (MLST) and antimicrobial resistance (AMR) gene profiles. Thirty known sequence types (STs) and four novel STs were identified for K. pneumoniae, and two STs among K. quasipneumoniae . The isolates were found at various treatment stages of the manure on one farm but were only sporadically found on any of the other farms investigated. The majority of isolates (86%) were multi-drug resistant. Variants of CTX-M were identified in diverse STs and included bla _CTX-M-15 ( n = 81), bla _CTX-M-1 ( n = 2) and bla _CTX-M-32 ( n = 1). The bla _CTX-M-15 gene was located on diverse IncF, IncHI1 or IncY replicons as well as on the chromosome, whereas bla _CTX-M-1 was harboured on the epidemic IncI1/ST3 plasmid, and bla _CTX-M-32 on an IncN plasmid. Plasmids were characterized based on core gene SNPs, replicon types and AMR genes, and compared to plasmids from Escherichia coli from a parallel study. Transfer of bla _CTX-M plasmids between bacterial species by conjugation was also assessed. Conjugation of IncI1 and IncFII plasmids occurred from K. pneumoniae to E. coli strains but not vice versa . Notably, IncY replicons were identified as conjugative plasmids and transfer was demonstrated between E. coli strains as well as from K. pneumoniae to E. coli . No strain overlap was observed between dairy manure isolates and those from turkey and dogs, however we did identify similarities between K. pneumoniae MLST and resistance profiles from publicly available human clinical isolates to our isolates found in dairy manure (ST37 and 405), turkeys (ST45) and dogs (ST711).

This paper presents Sequenoscope a bioinformatics pipeline for analyzing Oxford Nanopore Technologies (ONT) adaptive sampling sequencing data. Sequenoscope features three main modules: filter_ONT for filtering raw reads and creating a FASTQ file with a subset of reads for further analyses, analyze for generating sequencing and read mapping statistics against the provided reference taxon sequences, and plot for interactive data summarization, comparison, and visualization between two datasets/test conditions. Here we demonstrate the ability of the pipeline to analyze ONT adaptive sampling sequence data and provide examples of the outputs users can expect using data we generated. Adaptive sampling was performed on two ZymoBIOMICS Microbial Community DNA Standards (Cat# D6311 and D6306) with targeted depletions of Listeria monocytogenes. By comparing the test and control experimental data in FASTQ file from the sequencing runs, Sequenoscope showed that depletion of L. monocytogenes was successful by providing users with parameters to compare such as taxon coverage, read length, and types of pore-level decisions made during sequencing. Although Sequenoscope was designed for ONT adaptive sampling data analysis, it can also be used to compare any two experimental conditions and supports short-read data from other sequencing platforms.

Background: H3 influenza A viruses (IAV) have been shown to frequently cross the species barrier which can be an important factor in sustained transmission and spread. Machine learning methods have been widely explored for host prediction of IAV using genomic data; however, this is often done using data from only one of the eight IAV segments or by using all available IAV data to predict broad categories of hosts. Objective: The objective of this study was to combine machine learning algorithms with H3 IAV sequence data from all eight segments to train predictive machine learning models for distinct host prediction and validate model performance. Methods: Models were trained on both k-mers and amino acid properties alongside machine learning algorithms that included random forest and XGBoost for each of the eight IAV genome segments. Models were then validated on a test dataset through analytics of model class predicted probabilities and subsequently used to investigate between-species transmission patterns within case studies including canine H3N8, swine H3N2 2010.2, and duck H3 sequences. Results: Models demonstrated strong performance in host prediction across all eight segments on the test dataset, with overall accuracies and κ (kappa) values ranging from 0.995–0.997, 0.984–0.990, respectively. Misclassified test dataset sequences with high predicted probabilities (> 90%) were validated using available literature and were identified to be frequently associated with between-species transmission events. Between-species transmission patterns within case study model class predicted probabilities were also identified to be consistent with the literature in cases of both correct and incorrect classification. Conclusions: These models allow for rapid and accurate host prediction of H3 IAV datasets from any of the eight IAV segments and provide a solid framework that allows for identification of variants with higher than typical between-species transmission potential. However, results obtained on selected case studies suggest further improvements of the training and validation processes should be considered.

The use of carbapenem antibiotics is threatened by the global spread of carbapenemase-producing Enterobacterales (CPE), bacterial pathogens which hydrolyze these last-resort antimicrobials. Rapid detection of CPE is vital to ensure timely administration of antimicrobial therapy to infected patients, as well as the implementation of infection control measures to prevent outbreaks in healthcare settings. In this study, we report the development of resaCPE, a rapid, low-cost CPE detection method that couples the inactivation of an imipenem disk with a cell viability assay employing a carbapenem-hyper-susceptible Escherichia coli strain. Results are interpreted by a simple colourimetric readout in which CPE-positive samples turn pink, while CPE-negative samples remain purple. The assay was validated with a panel of 91 CPE and non-CPE isolates, and its performance compared to two widely used CPE detection strategies, the modified carbapenem inactivation method (mCIM) and the CARBA-NP test. The resaCPE test demonstrated the same level of performance as the mCIM (100 % sensitivity and specificity), while providing results in significantly less time (3.5 h vs. 20-24 h, respectively). We also observed that the resaCPE test outperformed the CARBA-NP test (95.3 % sensitivity, 100 % specificity), specifically when applied to the detection of CPE isolates producing carbapenemases with weaker hydrolytic activity. Due to the rapid turnaround time, minimal setup requirements, and low cost (∼$1 USD/sample), the resaCPE test is a potentially attractive option for primary CPE screening, particularly in lower resource settings.

The One Health (OH) approach recognizes the interconnectedness of the health of people, animals, plants/crops and ecosystems, and is central to addressing antimicrobial resistance (AMR). The 7th Environmental Dimension of Antimicrobial Resistance Conference (EDAR7), held in Montreal in May 2024, exemplified this approach by convening international experts and stakeholders to discuss AMR research and policy progress. EDAR7 workshop #8 focused on 1) barriers to establishing effective OH AMR research programs, 2) gaps in OH AMR research priorities, and 3) potential solutions/approaches or ‘tools’ to ensure programs develop in accordance with OH principles and generate insightful data that maximizes limited resources. Key workshop outcomes included identifying critical principles for OH AMR research programs and highlighting the pivotal role of sustainable data management strategies. Additionally, the importance of considering AMR policy and risk assessment needs when planning and designing research was emphasized. Discussions explored specific tools and approaches that support the standardized and harmonized collection and analysis of data, and associated challenges of integrating genomics data into current risk assessments and models. Synthesis of the workshop’s discussions outlined critical considerations that interdisciplinary OH AMR research programs and networks should prioritize to enhance the impact of their outputs.

This paper presents Sequenoscope a bioinformatics pipeline for analyzing Oxford Nanopore Technologies (ONT) adaptive sampling sequencing data. Sequenoscope features three main modules: filter_ONT for filtering raw reads and creating a FASTQ file with a subset of reads for further analyses, analyze for generating sequencing and read mapping statistics against the provided reference taxon sequences, and plot for interactive data summarization, comparison, and visualization between two datasets/test conditions. Here we demonstrate the ability of the pipeline to analyze ONT adaptive sampling sequence data and provide examples of the outputs users can expect using data we generated. Adaptive sampling was performed on two ZymoBIOMICS Microbial Community DNA Standards (Cat# D6311 and D6306) with targeted depletions of Listeria monocytogenes. By comparing the test and control experimental data in FASTQ file from the sequencing runs, Sequenoscope showed that depletion of L. monocytogenes was successful by providing users with parameters to compare such as taxon coverage, read length, and types of pore-level decisions made during sequencing. Although Sequenoscope was designed for ONT adaptive sampling data analysis, it can also be used to compare any two experimental conditions and supports short-read data from other sequencing platforms.