Rapid and Routine Molecular Typing Using Multiplex Polymerase Chain Reaction and MinION Sequencer

Streamlining whole genome sequencing for clinical diagnostics with ONT technology

Recent advances in whole-genome sequencing (WGS) have increased the accessibility of this tool, offering substantial potential for pathogen surveillance, outbreak response, and diagnostics. However, the routine clinical adoption of WGS is hindered by factors such as high costs, technical complexity, and the requirement for bioinformatics expertise for data analysis. To address these challenges, we propose RapidONT, a workflow designed for cost-effective and accessible WGS-based pathogen analysis. RapidONT employs a mechanical shearing-based DNA extraction protocol, followed by library construction by using a multiplexing Oxford nanopore technologies (ONT) rapid barcoding kit. Flye software is used for de novo assembly without manual intervention, followed by basic assembly polishing using Medaka and Homopolish. The polished assemblies are then analyzed using the user-friendly web-based platform Pathogenwatch, which facilitates species identification, molecular typing, and antimicrobial resistance (AMR) prediction, all while requiring minimal bioinformatics expertise. The efficacy of RapidONT was evaluated using nine clinically relevant pathogens, encompassing a total of 90 gram-positive and gram-negative bacterial strains. The workflow demonstrated high accuracy in critical tasks such as multilocus sequence typing (MLST) and AMR identification, using only ONT R9.4.1 flowcell data. Notably, limitations were observed with Salmonella spp. and Neisseria gonorrhoeae. Furthermore, RapidONT enabled the generation of genomic information for 48 bacterial isolates by using a single flow cell, significantly reducing sequencing costs. This approach eliminates the need for extensive experimentation in obtaining crucial genomic information. This workflow facilitates broader WGS implementation in clinical pathogen analysis and diagnostics.

Targeted sputum sequencing for rapid and broad drug resistance of Mycobacterium tuberculosis

PURPOSE

Rapid detection of drug resistance in Mycobacterium tuberculosis (Mtb) from clinical samples facilitates the timely provision of optimal treatment regimens for tuberculosis (TB) patients.

METHODS

In November, 2023, the WHO released its second catalogue of resistance-conferring mutations in Mtb. Utilizing this information, we developed a single 17-plex PCR assay covering 16 key resistance genes and modified thermo-protection buffer to amplify 30 kbp DNA directly from sputum samples for nanopore sequencing. We implemented our protocol using rapid barcoding for sequencing with both a Flongle and a MinION flow cell.

RESULTS

The single multiplex PCR assay was successfully validated on clinical sputum samples using the thermo-protection buffer. The protocol was applied to both Flongle and MinION flow cells, analyzing 12 and 40 samples, respectively. Data analysis suggested that optimal performance could be achieved by processing 6 and 12 samples with similar microscope staining scores on these two platforms. This approach facilitated rapid antimicrobial resistance (AMR) predictions directly from sputum on the day of collection or the following day, with a cost of less than $35 per sample. Compared to AMR predictions based on whole-genome sequencing (WGS) using Mykrobe and TBProfiler, our amplicon-based analysis tool, ARapidTb, demonstrated superior resistance detection capabilities. When analyzing publicly available nanopore WGS datasets for 442 isolates, ARapidTb achieved agreement rates of 95.8% and 98.0%, outperforming Mykrobe (89.4% and 98.3%) and TBProfiler (75.6% and 89.8%).

CONCLUSIONS

Our study significantly reduces the time required for drug resistance detection, enabling quicker initiation of appropriate treatments and potentially improving patient outcomes and TB management.

NanoCore: core-genome-based bacterial genomic surveillance and outbreak detection in healthcare facilities from Nanopore and Illumina data

Genomic surveillance enables the early detection of pathogen transmission in healthcare facilities and contributes to the reduction of substantial patient harm. Fast turnaround times, flexible multiplexing, and low capital requirements make Nanopore sequencing well suited for genomic surveillance purposes; the analysis of Nanopore data, however, can be challenging. We present NanoCore, a user-friendly method for Nanopore-based genomic surveillance in healthcare facilities, enabling the calculation and visualization of cgMLST-like (core-genome multilocus sequence typing) sample distances directly from unassembled Nanopore reads. NanoCore implements a mapping, variant calling, and multilevel filtering strategy and also supports the analysis of Illumina data. We validated NanoCore on two 24-isolate data sets of methicillin-resistant Staphylococcus aureus (MRSA) and vancomycin-resistant Enterococcus faecium (VRE). In the Nanopore-only mode, NanoCore-based pairwise distances between closely related isolates were near-identical to Illumina-based SeqSphere+ distances, a gold standard commercial method (average differences of 0.75 and 0.81 alleles for MRSA and VRE; sd = 0.98 and 1.00), and gave an identical clustering into closely related and non-closely related isolates. In the "hybrid" mode, in which only Nanopore data are used for some isolates and only Illumina data for others, increased average pairwise isolate distance differences were observed (average differences of 3.44 and 1.95 for MRSA and VRE, respectively; sd = 2.76 and 1.34), while clustering results remained identical. NanoCore is computationally efficient (<15 hours of wall time for the analysis of a 24-isolate data set on a workstation), available as free software, and supports installation via conda. In conclusion, NanoCore enables the effective use of the Nanopore technology for bacterial pathogen surveillance in healthcare facilities.

IMPORTANCE

Genomic surveillance involves sequencing the genomes and measuring the relatedness of bacteria from different patients or locations in the same healthcare facility, enabling an improved understanding of pathogen transmission pathways and the detection of "silent" outbreaks that would otherwise go undetected. It has become an indispensable tool for the detection and prevention of healthcare-associated infections and is routinely applied by many healthcare institutions. The earlier an outbreak or transmission chain is detected, the better; in this context, the Oxford Nanopore sequencing technology has important potential advantages over traditionally used short-read sequencing technologies, because it supports "real-time" data generation and the cost-effective "on demand" sequencing of small numbers of bacterial isolates. The analysis of Nanopore sequencing data, however, can be challenging. We present NanoCore, a user-friendly software for genomic surveillance that works directly based on Nanopore sequencing reads in FASTQ format, and demonstrate that its accuracy is equivalent to traditional gold standard short read-based analyses.

High-throughput Oxford Nanopore sequencing-based approach for the multilocus sequence typing analysis of large-scale avian Escherichia coli study in Mississippi

Avian pathogenic Escherichia coli (APEC) cause avian colibacillosis and accurately distinguishing infectious isolates is critical for controlling its transmission. Multilocus sequence typing (MLST) is an accurate and efficient strain identification method for epidemiological surveillance. This research aimed to develop a fast and high-throughput workflow that simultaneously sequences the Achtman typing scheme's 7 housekeeping genes of multiple E. coli isolates using the Oxford Nanopore Technologies (ONT) platform for large-scale APEC study. E. coli strains were isolated from poultry farms, the housekeeping genes were amplified, and amplicons were sequenced on an R9.4 MinION flow cell using the Nanopore GridION sequencer (ONT, Oxford, UK) following the initial workflow (ONT-MLST). Moreover, the workflow was revised by introducing large-scale DNA extraction and multiplex PCR into the ONT-MLST workflow and applied to 242 new isolates, 18 isolates from the previous workflow, and 5 ATCC reference strains using Flongle flow cell on the Nanopore MinION Mk1C sequencer (ONT, Oxford, UK). Finally, the sequence type (ST) results of the 308 isolates collected from infected chickens and poultry farm environments were reported and analyzed. Data indicated that E. coli belonging to ST159, ST8578, and ST355 have the potential to infect multiple organs in broiler. In addition, zoonotic STs, ST69, ST10, ST38, and ST131, were detected from poultry farms. With the advantages of the high throughput of ONT, this study provides a rapid workflow for large-scale E. coli typing and identified frequently isolated sequence types related to APEC infection in poultry.

High-throughput rapid amplicon sequencing for multilocus sequence typing of Mycoplasma ovipneumoniae from archived clinical DNA samples

Introduction

Spillover events of Mycoplasma ovipneumoniae have devastating effects on the wild sheep populations. Multilocus sequence typing (MLST) is used to monitor spillover events and the spread of M. ovipneumoniae between the sheep populations. Most studies involving the typing of M. ovipneumoniae have used Sanger sequencing. However, this technology is time-consuming, expensive, and is not well suited to efficient batch sample processing.

Methods

Our study aimed to develop and validate an MLST workflow for typing of M. ovipneumoniae using Nanopore Rapid Barcoding sequencing and multiplex polymerase chain reaction (PCR). We compare the workflow with Nanopore Native Barcoding library preparation and Illumina MiSeq amplicon protocols to determine the most accurate and cost-effective method for sequencing multiplex amplicons. A multiplex PCR was optimized for four housekeeping genes of M. ovipneumoniae using archived DNA samples (N = 68) from nasal swabs.

Results

Sequences recovered from Nanopore Rapid Barcoding correctly identified all MLST types with the shortest total workflow time and lowest cost per sample when compared with Nanopore Native Barcoding and Illumina MiSeq methods.

Discussion

Our proposed workflow is a convenient and effective method for strain typing of M. ovipneumoniae and can be applied to other bacterial MLST schemes. The workflow is suitable for diagnostic settings, where reduced hands-on time, cost, and multiplexing capabilities are important.

Optimization of Oxford Nanopore Technology Sequencing Workflow for Detection of Amplicons in Real Time Using ONT-DART Tool

An optimized, well-tested and validated targeted genomic sequencing-based high-throughput assay is currently not available ready for routine biodefense and biosurveillance applications. Earlier, we addressed this gap by developing and establishing baseline comparisons of a multiplex end-point Polymerase Chain Reaction (PCR) assay followed by Oxford Nanopore Technology (ONT) based amplicon sequencing to real time PCR and customized data processing. Here, we expand upon this effort by identifying the optimal ONT library preparation method for integration into a novel software platform ONT-DART (ONT-Detection of Amplicons in Real-Time). ONT-DART is a dockerized, real-time, amplicon-sequence analysis workflow that is used to reproducibly process and filter read data to support actionable amplicon detection calls based on alignment metrics, within sample statistics, and no-template control data. This analysis pipeline was used to compare four ONT library preparation protocols using R9 and Flongle (FL) flow cells. The two 4-Primer methods tested required the shortest preparation times (5.5 and 6.5 h) for 48 libraries but provided lower fidelity data. The Native Barcoding and Ligation methods required longer preparation times of 8 and 12 h, respectively, and resulted in higher overall data quality. On average, data derived from R9 flow cells produced true positive calls for target organisms more than twice as fast as the lower throughput FL flow cells. These results suggest that utilizing the R9 flowcell with an ONT Native Barcoding amplicon library method in combination with ONT-DART platform analytics provides the best sequencing-based alternative to current PCR-based biodetection methods.