A rapid bacterial pathogen and antimicrobial resistance diagnosis workflow using Oxford nanopore adaptive sequencing method

Analytical techniques and molecular platforms for detection and surveillance of antimicrobial resistance: advancements of the past decade

Developing countries have been able to control and minimise the mortality rates caused by pathogenic infections by ensuring affordable access to antibiotics. However, a large number of bacterial ailments are treated with wrong antibiotic prescription due to improper disease diagnosis. Apart from healthcare, antibiotics are also imprudently utilised in crop processing and animal husbandry. This unsupervised usage of antibiotics has propelled the generation of multidrug-resistant species of bacteria. Presently, several traditional antimicrobial susceptibility/resistance tests (AST/ART) are available; however, the accuracy and reproducibility of these tests are often debatable. Rigorous efforts are essential to develop techniques and methods which substantially decrease turnaround time for resistance screening. The present review has comprehensively incorporated the improvements in instrumentation and molecular methods for antimicrobial resistance studies. We have enlisted some innovative takes on conventional techniques such as isothermal calorimetry, Raman spectroscopy, mass spectrometry and microscopy. The contributions of modern molecular tools such as CRISPR-Cas, aptamers and Oxford-MinION sequencers have also been discussed. Persistent evolution has been observed towards adding innovation in diagnostic platforms for drug resistome screening, with the major attraction being the involvement of non-conventional analytical methods and technological improvements in existing setups. This review highlights these updates and provides a detailed account of principal developments in molecular methods for the testing of drug resistance in bacteria.

Antibiotic resistance genes in anaerobic digestion: Unresolved challenges and potential solutions

Antimicrobial resistance (AMR) threatens public health, necessitating urgent efforts to mitigate the global impact of antibiotic resistance genes (ARGs). Anaerobic digestion (AD), known for volatile solid reduction and energy generation, also presents a feasible approach for the removal of ARGs. This review encapsulates the existing understanding of ARGs and antibiotic-resistant bacteria (ARB) during the AD process, highlighting unresolved challenges pertaining to their detection and quantification. The questions raised and discussed include: Do current ARGs detection methods meet qualitative and quantitative requirements? How can we conduct risk assessments of ARGs? What happens to ARGs when they come into co-exposure with other emerging pollutants? How can the application of internal standards bolster the reliability of the AD resistome study? What are the potential future research directions that could enhance ARG elimination? Investigating these subjects will assist in shaping more efficient management strategies that employ AD for effective ARG control.

Portable solutions for plant pathogen diagnostics: development, usage, and future potential

The increasing prevalence of plant pathogens presents a critical challenge to global food security and agricultural sustainability. While accurate, traditional diagnostic methods are often time-consuming, resource-intensive, and unsuitable for real-time field applications. The emergence of portable diagnostic tools represents a paradigm shift in plant disease management, offering rapid, on-site detection of pathogens with high accuracy and minimal technical expertise. This review explores portable diagnostic technologies' development, deployment, and future potential, including handheld analyzers, smartphone-integrated systems, microfluidics, and lab-on-a-chip platforms. We examine the core technologies underlying these devices, such as biosensors, nucleic acid amplification techniques, and immunoassays, highlighting their applicability to detect bacterial, viral, and fungal pathogens in diverse agricultural settings. Furthermore, the integration of these devices with digital technologies, including the Internet of Things (IoT), artificial intelligence (AI), and machine learning (ML), is transforming disease surveillance and management. While portable diagnostics have clear advantages in speed, cost-effectiveness, and user accessibility, challenges related to sensitivity, durability, and regulatory standards remain. Innovations in nanotechnology, multiplex detection platforms, and personalized agriculture promise to further enhance the efficacy of portable diagnostics. By providing a comprehensive overview of current technologies and exploring future directions, this review underscores the critical role of portable diagnostics in advancing precision agriculture and mitigating the impact of plant pathogens on global food production.

Advances in forensic genetics: Exploring the potential of long read sequencing

DNA-based technologies have been used in forensic practice since the mid-1980s. While PCR-based STR genotyping using Capillary Electrophoresis remains the gold standard for generating DNA profiles in routine casework worldwide, the research community is continually seeking alternative methods capable of providing additional information to enhance discrimination power or contribute with new investigative leads. Oxford Nanopore Technologies (ONT) and PacBio third-generation sequencing have revolutionized the field, offering real-time capabilities, single-molecule resolution, and long-read sequencing (LRS). ONT, the pioneer of nanopore sequencing, uses biological nanopores to analyze nucleic acids in real-time. Its devices have revolutionized sequencing and may represent an interesting alternative for forensic research and routine casework, given that it offers unparalleled flexibility in a portable size: it enables sequencing approaches that range widely from PCR-amplified short target regions (e.g., CODIS STRs) to PCR-free whole transcriptome or even ultra-long whole genome sequencing. Despite its higher error rate compared to Illumina sequencing, it can significantly improve accuracy in read alignment against a reference genome or de novo genome assembly. This is achieved by generating long contiguous sequences that correctly assemble repetitive sections and regions with structural variation. Moreover, it allows real-time determination of DNA methylation status from native DNA without the need for bisulfite conversion. LRS enables the analysis of thousands of markers at once, providing phasing information and eliminating the need for multiple assays. This maximizes the information retrieved from a single invaluable sample. In this review, we explore the potential use of LRS in different forensic genetics approaches.

Advancing quantitative PCR with color cycle multiplex amplification

Quantitative PCR (qPCR) is the gold standard for detection and quantitation of known DNA targets, but the scarcity of spectrally distinct fluorophores and filter sets limits the number of detectable targets. Here, we introduce color cycle multiplex amplification (CCMA) to significantly increase the number of detectable DNA targets in a single qPCR reaction using standard instrumentation. In CCMA, presence of one DNA target species results in a pre-programmed pattern of fluorescence increases. This pattern is distinguished by cycle thresholds (Cts) through rationally designed delays in amplification. For example, we design an assay wherein Staphylococcus aureus sequentially induces FAM, then Cy5.5, then ROX fluorescence increases with more than 3 cycles between each signal. CCMA offers notably higher potential for multiplexing because it uses fluorescence permutation rather than combination. With 4 distinct fluorescence colors, CCMA theoretically allows the detection of up to 136 distinct DNA target sequences using fluorescence permutation. Experimentally, we demonstrated a single-tube qPCR assay screening 21 sepsis-related bacterial DNA targets in samples of blood, sputum, pleural effusion and bronchoalveolar lavage fluid, with 89% clinical sensitivity and 100% clinical specificity, showing its potential as a powerful tool for advanced quantitative screening in molecular diagnostics.

PathoTracker: an online analytical metagenomic platform for Klebsiella pneumoniae feature identification and outbreak alerting

Clinical metagenomics (CMg) Nanopore sequencing can facilitate infectious disease diagnosis. In China, sub-lineages ST11-KL64 and ST11-KL47 Carbapenem-resistant Klebsiella pneumoniae (CRKP) are widely prevalent. We propose PathoTracker, a specially compiled database and arranged method for strain feature identification in CMg samples and CRKP traceability. A database targeting high-prevalence horizontal gene transfer in CRKP strains and a ST11-only database for distinguishing two sub-lineages in China were created. To make the database user-friendly, facilitate immediate downstream strain feature identification from raw Nanopore metagenomic data, and avoid the need for phylogenetic analysis from scratch, we developed data analysis methods. The methods included pre-performed phylogenetic analysis, gene-isolate-cluster index and multilevel pan-genome database and reduced storage space by 10-fold and random-access memory by 52-fold compared with normal methods. PathoTracker can provide accurate and fast strain-level analysis for CMg data after 1 h Nanopore sequencing, allowing early warning of outbreaks. A user-friendly page ( http://PathoTracker.pku.edu.cn/ ) was developed to facilitate online analysis, including strain-level feature, species identifications and phylogenetic analyses. PathoTracker proposed in this study will aid in the downstream analysis of CMg.

Capturing clinically relevant Campylobacter attributes through direct whole genome sequencing of stool

Campylobacter is the leading bacterial cause of infectious intestinal disease, but the pathogen typically accounts for a very small proportion of the overall stool microbiome in each patient. Diagnosis is even more difficult due to the fastidious nature of Campylobacter in the laboratory setting. This has, in part, driven a change in recent years, from culture-based to rapid PCR-based diagnostic assays which have improved diagnostic detection, whilst creating a knowledge gap in our clinical and epidemiological understanding of Campylobacter genotypes - no isolates to sequence. In this study, direct metagenomic sequencing approaches were used to assess the possibility of replacing genome sequences with metagenome sequences; metagenomic sequencing outputs were used to describe clinically relevant attributes of Campylobacter genotypes. A total of 37 diarrhoeal stool samples with Campylobacter and five samples with an unknown pathogen result were collected and processed with and without filtration, DNA was extracted, and metagenomes were sequenced by short-read sequencing. Culture-based methods were used to validate Campylobacter metagenome-derived genome (MDG) results. Sequence output metrics were assessed for Campylobacter genome quality and accuracy of characterization. Of the 42 samples passing quality checks for analysis, identification of Campylobacter to the genus and species level was dependent on Campylobacter genome read count, coverage and genome completeness. A total of 65% (24/37) of samples were reliably identified to the genus level through Campylobacter MDG, 73% (27/37) by culture and 97% (36/37) by qPCR. The Campylobacter genomes with a genome completeness of over 60% (n=21) were all accurately identified at the species level (100%). Of those, 72% (15/21) were identified to sequence types (STs), and 95% (20/21) accurately identified antimicrobial resistance (AMR) gene determinants. Filtration of stool samples enhanced Campylobacter MDG recovery and genome quality metrics compared to the corresponding unfiltered samples, which improved the identification of STs and AMR profiles. The phylogenetic analysis in this study demonstrated the clustering of the metagenome-derived with culture-derived genomes and revealed the reliability of genomes from direct stool sequencing. Furthermore, Campylobacter genome spiking percentages ranging from 0 to 2% total metagenome abundance in the ONT MinION sequencer, configured to adaptive sequencing, exhibited better assembly quality and accurate identification of STs, particularly in the analysis of metagenomes containing 2 and 1% of Campylobacter jejuni genomes. Direct sequencing of Campylobacter from stool samples provides clinically relevant and epidemiologically important genomic information without the reliance on cultured genomes.

Unveiling microbial diversity: harnessing long-read sequencing technology

Long-read sequencing has recently transformed metagenomics, enhancing strain-level pathogen characterization, enabling accurate and complete metagenome-assembled genomes, and improving microbiome taxonomic classification and profiling. These advancements are not only due to improvements in sequencing accuracy, but also happening across rapidly changing analysis methods. In this Review, we explore long-read sequencing's profound impact on metagenomics, focusing on computational pipelines for genome assembly, taxonomic characterization and variant detection, to summarize recent advancements in the field and provide an overview of available analytical methods to fully leverage long reads. We provide insights into the advantages and disadvantages of long reads over short reads and their evolution from the early days of long-read sequencing to their recent impact on metagenomics and clinical diagnostics. We further point out remaining challenges for the field such as the integration of methylation signals in sub-strain analysis and the lack of benchmarks.

Nanopore adaptive sampling of a metagenomic sample derived from a human monkeypox case

In 2022, a series of human monkeypox cases in multiple countries led to the largest and most widespread outbreak outside the known endemic areas. Setup of proper genomic surveillance is of utmost importance to control such outbreaks. To this end, we performed Nanopore (PromethION P24) and Illumina (NextSeq. 2000) Whole Genome Sequencing (WGS) of a monkeypox sample. Adaptive sampling was applied for in silico depletion of the human host genome, allowing for the enrichment of low abundance viral DNA without a priori knowledge of sample composition. Nanopore sequencing allowed for high viral genome coverage, tracking of sample composition during sequencing, strain determination, and preliminary assessment of mutational pattern. In addition to that, only Nanopore data allowed us to resolve the entire monkeypox virus genome, with respect to two structural variants belonging to the genes OPG015 and OPG208. These SVs in important host range genes seem stable throughout the outbreak and are frequently misassembled and/or misannotated due to the prevalence of short read sequencing or short read first assembly. Ideally, standalone standard Illumina sequencing should not be used for Monkeypox WGS and de novo assembly, since it will obfuscate the structure of the genome, which has an impact on the quality and completeness of the genomes deposited in public databases and thus possibly on the ability to evaluate the complete genetic reason for the host range change of monkeypox in the current pandemic.

Antimicrobial resistance prediction by clinical metagenomics in pediatric severe pneumonia patients

BACKGROUND

Antimicrobial resistance (AMR) is a major threat to children's health, particularly in respiratory infections. Accurate identification of pathogens and AMR is crucial for targeted antibiotic treatment. Metagenomic next-generation sequencing (mNGS) shows promise in directly detecting microorganisms and resistance genes in clinical samples. However, the accuracy of AMR prediction through mNGS testing needs further investigation for practical clinical decision-making.

METHODS

We aimed to evaluate the performance of mNGS in predicting AMR for severe pneumonia in pediatric patients. We conducted a retrospective analysis at a tertiary hospital from May 2022 to May 2023. Simultaneous mNGS and culture were performed on bronchoalveolar lavage fluid samples obtained from pediatric patients with severe pneumonia. By comparing the results of mNGS detection of microorganisms and antibiotic resistance genes with those of culture, sensitivity, specificity, positive predictive value, and negative predictive value were calculated.

RESULTS

mNGS detected bacterial in 71.7% cases (86/120), significantly higher than culture (58/120, 48.3%). Compared to culture, mNGS demonstrated a sensitivity of 96.6% and a specificity of 51.6% in detecting pathogenic microorganisms. Phenotypic susceptibility testing (PST) of 19 antibiotics revealed significant variations in antibiotics resistance rates among different bacteria. Sensitivity prediction of mNGS for carbapenem resistance was higher than penicillins and cephalosporin (67.74% vs. 28.57%, 46.15%), while specificity showed no significant difference (85.71%, 75.00%, 75.00%). mNGS also showed a high sensitivity of 94.74% in predicting carbapenem resistance in Acinetobacter baumannii.

CONCLUSIONS

mNGS exhibits variable predictive performance among different pathogens and antibiotics, indicating its potential as a supplementary tool to conventional PST. However, mNGS currently cannot replace conventional PST.

Three Rounds of Read Correction Significantly Improve Eukaryotic Protein Detection in ONT Reads

BACKGROUND

Eukaryotes' whole-genome sequencing is crucial for species identification, gene detection, and protein annotation. Oxford Nanopore Technology (ONT) is an affordable and rapid platform for sequencing eukaryotes; however, the relatively higher error rates require computational and bioinformatic efforts to produce more accurate genome assemblies. Here, we evaluated the effect of read correction tools on eukaryote genome completeness, gene detection and protein annotation.

METHODS

Reads generated by ONT of four eukaryotes, C. albicans, C. gattii, S. cerevisiae, and P. falciparum, were assembled using minimap2 and underwent three rounds of read correction using flye, medaka and racon. The generates consensus FASTA files were compared for total length (bp), genome completeness, gene detection, and protein-annotation by QUAST, BUSCO, BRAKER1 and InterProScan, respectively.

RESULTS

Genome completeness was dependent on the assembly method rather than on the read correction tool; however, medaka performed better than flye and racon. Racon significantly performed better than flye and medaka in gene detection, while both racon and medaka significantly performed better than flye in protein-annotation.

CONCLUSION

We show that three rounds of read correction significantly affect gene detection and protein annotation, which are dependent on assembly quality in preference to assembly completeness.

Nanopore adaptive sampling enriches for antimicrobial resistance genes in microbial communities

Antimicrobial resistance (AMR) is a global public health threat. Environmental microbial communities act as reservoirs for AMR, containing genes associated with resistance, their precursors, and the selective pressures promoting their persistence. Genomic surveillance could provide insights into how these reservoirs change and impact public health. Enriching for AMR genomic signatures in complex microbial communities would strengthen surveillance efforts and reduce time-to-answer. Here, we tested the ability of nanopore sequencing and adaptive sampling to enrich for AMR genes in a mock community of environmental origin. Our setup implemented the MinION mk1B, an NVIDIA Jetson Xavier GPU, and Flongle flow cells. Using adaptive sampling, we observed consistent enrichment by composition. On average, adaptive sampling resulted in a target composition 4× higher than without adaptive sampling. Despite a decrease in total sequencing output, adaptive sampling increased target yield in most replicates. We also demonstrate enrichment in a diverse community using an environmental sample. This method enables rapid and flexible genomic surveillance.

NanoDeep: a deep learning framework for nanopore adaptive sampling on microbial sequencing

Nanopore sequencers can enrich or deplete the targeted DNA molecules in a library by reversing the voltage across individual nanopores. However, it requires substantial computational resources to achieve rapid operations in parallel at read-time sequencing. We present a deep learning framework, NanoDeep, to overcome these limitations by incorporating convolutional neural network and squeeze and excitation. We first showed that the raw squiggle derived from native DNA sequences determines the origin of microbial and human genomes. Then, we demonstrated that NanoDeep successfully classified bacterial reads from the pooled library with human sequence and showed enrichment for bacterial sequence compared with routine nanopore sequencing setting. Further, we showed that NanoDeep improves the sequencing efficiency and preserves the fidelity of bacterial genomes in the mock sample. In addition, NanoDeep performs well in the enrichment of metagenome sequences of gut samples, showing its potential applications in the enrichment of unknown microbiota. Our toolkit is available at https://github.com/lysovosyl/NanoDeep.

A novel culture-enriched metagenomic sequencing strategy effectively guarantee the microbial safety of drinking water by uncovering the low abundance pathogens

Assessing the presence of waterborne pathogens and antibiotic resistance genes (ARGs) is crucial for managing the environmental quality of drinking water sources. However, detecting low abundance pathogens in such settings is challenging. In this study, a workflow was developed to enrich for broad spectrum pathogens from drinking water samples. A mock community was used to evaluate the effectiveness of various enrichment broths in detecting low-abundance pathogens. Monthly metagenomic surveillance was conducted in a drinking water source from May to September 2021, and water samples were subjected to five enrichment procedures for 6 h to recover the majority of waterborne bacterial pathogens. Oxford Nanopore Technology (ONT) was used for metagenomic sequencing of enriched samples to obtain high-quality pathogen genomes. The results showed that selective enrichment significantly increased the proportions of targeted bacterial pathogens. Compared to direct metagenomic sequencing of untreated water samples, targeted enrichment followed by ONT sequencing significantly improved the detection of waterborne pathogens and the quality of metagenome-assembled genomes (MAGs). Eighty-six high-quality MAGs, including 70 pathogen MAGs, were obtained from ONT sequencing, while only 12 MAGs representing 10 species were obtained from direct metagenomic sequencing of untreated water samples. In addition, ONT sequencing improved the recovery of mobile genetic elements and the accuracy of phylogenetic analysis. This study highlights the urgent need for efficient methodologies to detect and manage microbial risks in drinking water sources. The developed workflow provides a cost-effective approach for environmental management of drinking water sources with microbial risks. The study also uncovered pathogens that were not detected by traditional methods, thereby advancing microbial risk management of drinking water sources.

Evaluation of metagenomic assembly methods for the detection and characterization of antimicrobial resistance determinants and associated mobilizable elements

Antimicrobial resistance genes (ARGs) can be transferred between members of a bacterial population by mobile genetic elements (MGE). Understanding the risk of these transfer events is important in monitoring and predicting antimicrobial resistance (AMR), especially in the context of a One Health Continuum. However, there is no universally accepted method for detection of ARGs and MGEs, and especially for determining their linkages. This study used publicly available shotgun metagenomic DNA short-read (Illumina, 100 bp paired-end) sequence data from samples across the One Health Continuum (including beef cattle composite feces from feedlots, catch basin water at feedlots, agricultural soil from feedlot manured surrounding fields, and urban/municipal sewage influent from two municipal wastewater treatment plants) to develop a workflow to identify and associate ARGs and MGEs. ARG- and MGE-based targeted-assemblies with available short-read data were unable to meet this analysis goal. In contrast, de novo assembly of contigs provided enough sequence context to associate ARGs and MGEs, without compromising discovery rate. However, to estimate the relative abundance of these elements, unassembled sequence data must still be used.

Case Report: Metagenomic next-generation sequencing assists in dynamic pathogen monitoring: powerful tool for progressing severe pneumonia

BACKGROUND

Severe community-acquired pneumonia (sCAP) is life-threatening and characterized by intensive care unit (ICU) admission and high mortality. And they are vulnerable to hospital-acquired infection. In such a severe condition, metagenomic next-generation sequencing (mNGS) outperforms for short turnaround time and broad detection spectrum.

CASE PRESENTATION

A 15-year-old male with severe influenza and methicillin-resistant Staphylococcus aureus (MRSA) pneumonia progressed rapidly, initially misdiagnosed as influenza co-infected with Aspergillus for misleading bronchoscopy manifestations. The turnaround time of mNGS is 13 h, which has the potential to expedite the clinical medication process. With the powerful support of mNGS and extracorporeal membrane oxygenation (ECMO), anti-infective therapy was adjusted accordingly, and vital signs gradually stabilized. After tortuous treatment and unremitting efforts, the patient recovered well.

CONCLUSIONS

Rapid mNGS applications, timely medication adjustments, strong ECMO support and active family compliance contribute to this miracle of life. False-negative or false-positive results are alarming, anti-infective medications should be adjusted after a comprehensive review of physical status and other indicators.

Improving the assessment of ecosystem and wildlife health: microbiome as an early indicator

Human activities are causing dramatic declines in ecosystem health, compromising the functioning of the life-support system, economic activity, and animal and human health. In this context, monitoring the health of ecosystems and wildlife populations is crucial for determining ecological dynamics and assessing management interventions. A growing body of evidence indicates that microbiome provides a meaningful early indicator of ecosystem and wildlife health. Microbiome is ubiquitous and both environmental and host-associated microbiomes rapidly reflect anthropogenic disturbances. However, we still need to overcome current limitations such as nucleic acid degradation, sequencing depth, and the establishment of baseline data to maximize the potential of microbiome studies.

Genome enrichment of rare and unknown species from complicated microbiomes by nanopore selective sequencing

Rare species are vital members of a microbial community, but retrieving their genomes is difficult because of their low abundance. The ReadUntil (RU) approach allows nanopore devices to sequence specific DNA molecules selectively in real time, which provides an opportunity for enriching rare species. Despite the robustness of enriching rare species by reducing the sequencing depth of known host sequences, such as the human genome, there is still a gap in RU-based enriching of rare species in environmental samples whose community composition is unclear, and many rare species have poor or incomplete reference genomes in public databases. Therefore, here we present metaRUpore to overcome this challenge. When we applied metaRUpore to a thermophilic anaerobic digester (TAD) community and human gut microbial community, it reduced coverage of the high-abundance populations and modestly increased (∼2×) the genome coverage of the rare taxa, facilitating successful recovery of near-finished metagenome-assembled genomes (nf-MAGs) of rare species. The simplicity and robustness of the approach make it accessible for laboratories with moderate computational resources, and hold the potential to become the standard practice in future metagenomic sequencing of complicated microbiomes.

Environmental DNA/RNA for pathogen and parasite detection, surveillance, and ecology

Detection of pathogens, parasites, and other symbionts in environmental samples via eDNA/eRNA (collectively eNA) is an increasingly important source of information about their occurrence and activity. There is great potential for using such detections as a proxy for infection of host organisms in connected habitats, for pathogen monitoring and surveillance, and for early warning systems for disease. However, many factors require consideration, and appropriate methods developed and verified, in order that eNA detections can be reliably interpreted and adopted for surveillance and assessment of disease risk, and potentially inclusion in international standards, such as the World Organisation for Animal Health guidelines. Disease manifestation results from host-symbiont-environment interactions between hosts, demanding a multifactorial approach to interpretation of eNA signals.

Strategies and tools in illumina and nanopore-integrated metagenomic analysis of microbiome data

Metagenomic strategy serves as the foundation for the ecological exploration of novel bioresources (e.g., industrial enzymes and bioactive molecules) and biohazards (e.g., pathogens and antibiotic resistance genes) in natural and engineered microbial systems across multiple disciplines. Recent advancements in sequencing technology have fostered rapid development in the field of microbiome research where an increasing number of studies have applied both illumina short reads (SRs) and nanopore long reads (LRs) sequencing in their metagenomic workflow. However, given the high complexity of an environmental microbiome data set and the bioinformatic challenges caused by the unique features of these sequencing technologies, integrating SRs and LRs is not as straightforward as one might assume. The fast renewal of existing tools and growing diversity of new algorithms make access to this field even more difficult. Therefore, here we systematically summarized the complete workflow from DNA extraction to data processing strategies for applying illumina and nanopore-integrated metagenomics in the investigation in environmental microbiomes. Overall, this review aims to provide a timely knowledge framework for researchers that are interested in or are struggling with the SRs and LRs integration in their metagenomic analysis. The discussions presented will facilitate improved ecological understanding of community functionalities and assembly of natural, engineered, and human microbiomes, benefiting researchers from multiple disciplines.

Application of nanopore adaptive sequencing in pathogen detection of a patient with Chlamydia psittaci infection

Introduction

Nanopore sequencing has been widely used in clinical metagenomic sequencing for pathogen detection with high portability and real-time sequencing. Oxford Nanopore Technologies has recently launched an adaptive sequencing function, which can enrich on-target reads through real-time alignment and eject uninteresting reads by reversing the voltage across the nanopore. Here we evaluated the utility of adaptive sequencing in clinical pathogen detection.

Methods

Nanopore adaptive sequencing and standard sequencing was performed on a same flow cell with a bronchoalveolar lavage fluid sample from a patient with Chlamydia psittacosis infection, and was compared with the previous mNGS results.

Results

Nanopore adaptive sequencing identified 648 on-target stop receiving reads with the longest median read length(688bp), which account for 72.4% of all Chlamydia psittaci reads and 0.03% of total reads in enriched group. The read proportion matched to C. psittaci in the stop receiving group was 99.85%, which was much higher than that of the unblock (<0.01%) and fail to adapt (0.02%) groups. Nanopore adaptive sequencing generated similar data yield of C. psittaci compared with standard nanopore sequencing. The proportion of C. psittaci reads in adaptive sequencing is close to that of standard nanopore sequencing and mNGS, but generated lower genome coverage than mNGS.

Discussion

Nanopore adaptive sequencing can effectively identify target C. psittaci reads in real-time, but how to increase the targeted data of pathogens still needs to be further evaluated.