An identification protocol for ESBL-producing Gram-negative bacteria bloodstream infections using a MinION nanopore sequencer

Using nanopore sequencing to identify bacterial infection in joint replacements: a preliminary study

This project investigates if third-generation genomic sequencing can be used to identify the species of bacteria causing prosthetic joint infections (PJIs) at the time of revision surgery. Samples of prosthetic fluid were taken during revision surgery from patients with known PJIs. Samples from revision surgeries from non-infected patients acted as negative controls. Genomic sequencing was performed using the MinION device and the rapid sequencing kit from Oxford Nanopore Technologies. Bioinformatic analysis pipelines to identify bacteria included Basic Local Alignment Search Tool, Kraken2 and MinION Detection Software, and the results were compared with standard of care microbiological cultures. Furthermore, there was an attempt to predict antibiotic resistance using computational tools including ResFinder, AMRFinderPlus and Comprehensive Antibiotic Resistance Database. Bacteria identified using microbiological cultures were successfully identified using bioinformatic analysis pipelines. Nanopore sequencing and genomic classification could be completed in the time it takes to perform joint revision surgery (2-3 h). Genomic sequencing in this study was not able to predict antibiotic resistance in this time frame, this is thought to be due to a short-read length and low read depth. It can be concluded that genomic sequencing can be useful to identify bacterial species in infected joint replacements. However, further work is required to investigate if it can be used to predict antibiotic resistance within clinically relevant timeframes.

Short turnaround time of seven to nine hours from sample collection until informed decision for sepsis treatment using nanopore sequencing

Bloodstream infections (BSIs) and sepsis are major health problems, annually claiming millions of lives. Traditional blood culture techniques, employed to identify sepsis-causing pathogens and assess antibiotic susceptibility, usually take 2-4 days. Early and accurate antibiotic prescription is vital in sepsis to mitigate mortality and antibiotic resistance. This study aimed to reduce the wait time for sepsis diagnosis by employing shorter blood culture incubation times for BD BACTEC™ bottles using standard laboratory incubators, followed by real-time nanopore sequencing and data analysis. The method was tested on nine blood samples spiked with clinical isolates from the six most prevalent sepsis-causing pathogens. The results showed that pathogen identification was possible at as low as 102-104 CFU/mL, achieved after just 2 h of incubation and within 40 min of nanopore sequencing. Moreover, all the antimicrobial resistance genes were identified at 103-107 CFU/mL, achieved after incubation for 5 h and only 10 min to 3 h of sequencing. Therefore, the total turnaround time from sample collection to the information required for an informed decision on the right antibiotic treatment was between 7 and 9 h. These results hold significant promise for better clinical management of sepsis compared with current culture-based methods.

Metagenomic identification of pathogens and antimicrobial-resistant genes in bacterial positive blood cultures by nanopore sequencing

Nanopore sequencing workflows have attracted increasing attention owing to their fast, real-time, and convenient portability. Positive blood culture samples were collected from patients with bacterial bloodstream infection and tested by nanopore sequencing. This study compared the sequencing results for pathogen taxonomic profiling and antimicrobial resistance genes to those of species identification and phenotypic drug susceptibility using traditional microbiology testing. A total of 37 bacterial positive blood culture results of strain genotyping by nanopore sequencing were consistent with those of mass spectrometry. Among them, one mixed infection of bacteria and fungi was identified using nanopore sequencing and confirmatory quantitative polymerase chain reaction. The amount of sequencing data was 21.89 ± 8.46 MB for species identification, and 1.0 MB microbial strain data enabled accurate determination. Data volumes greater than or equal to 94.6 MB nearly covered all the antimicrobial resistance genes of the bacteria in our study. In addition, the results of the antimicrobial resistance genes were compared with those of phenotypic drug susceptibility testing for Escherichia coli, Klebsiella pneumoniae, and Staphylococcus aureus. Therefore, the nanopore sequencing platform for rapid identification of causing pathogens and relevant antimicrobial resistance genes complementary to conventional blood culture outcomes may optimize antimicrobial stewardship management for patients with bacterial bloodstream infection.

Identification of bacterial and fungal pathogens directly from clinical blood cultures using whole genome sequencing

Bloodstream infections are a major cause of morbidity and mortality worldwide. Early administration of appropriate antimicrobial therapy can improve patient survival and prevent antimicrobial resistance (AMR). Whole genome sequencing (WGS) can provide information for pathogen identification, AMR prediction and sequence typing earlier than current phenotypic diagnostic methods. WGS was performed on 97 clinical blood specimens and matched culture isolate pairs. Specimen/isolate pairs were MLST sequence-typed and further characterization was performed on Streptococcus species. WGS correctly identified 91.7% of clinical specimens and 93.2% of matched isolates representing 35 different microbial species. MLST types were assigned for 89.9% of matched cultures and 21.7% of blood specimens, with higher success for blood culture specimens extracted within 3 days (52% characterized) than 7 days (9.3%). This study demonstrates the potential use of WGS for identification and characterization of pathogens directly from blood culture specimens to facilitate timely initiation of appropriate antimicrobial therapies.

Nanopore-based metagenomic sequencing for the rapid and precise detection of pathogens among immunocompromised cancer patients with suspected infections

Cancer patients are at high risk of infections and infection-related mortality; thereby, prompt diagnosis and precise anti-infectives treatment are critical. This study aimed to evaluate the performance of nanopore amplicon sequencing in identifying microbial agents among immunocompromised cancer patients with suspected infections. This prospective study enlisted 56 immunocompromised cancer patients with suspected infections. Their body fluid samples such as sputum and blood were collected, and potential microbial agents were detected in parallel by nanopore amplicon sequencing and the conventional culture method. Among the 56 body fluid samples, 47 (83.9%) samples were identified to have at least one pathogen by nanopore amplicon sequencing, but only 25 (44.6%) samples exhibited a positive finding by culture. Among 31 culture-negative samples, nanopore amplicon sequencing successfully detected pathogens in 22 samples (71.0%). Nanopore amplicon sequencing showed a higher sensitivity in pathogen detection than that of the conventional culture method (83.9% vs. 44.6%, P<0.001), and this advantage both existed in blood samples (38.5% vs. 0%, P=0.039) and non-blood samples (97.7% vs. 58.1%, P<0.001). Compared with the culture method, nanopore amplicon sequencing illustrated more samples with bacterial infections (P<0.001), infections from fastidious pathogens (P=0.006), and co-infections (P<0.001). The mean turnaround time for nanopore amplicon sequencing was about 17.5 hours, which was shorter than that of the conventional culture assay. This study suggested nanopore amplicon sequencing as a rapid and precise method for detecting pathogens among immunocompromised cancer patients with suspected infections. The novel and high-sensitive method will improve the outcomes of immunocompromised cancer patients by facilitating the prompt diagnosis of infections and precise anti-infectives treatment.

Nanopore Electrochemistry for Pathogen Detection

Pathogen infections have seriously threatened human health, and there is an urgent demand for rapid and efficient pathogen identification to provide instructions in clinical diagnosis and therapeutic intervention. Recently, nanopore technology, a rapidly maturing technology which delivers ultrasensitive sensing and high throughput in real-time and at low cost, has achieved success in pathogen detection. Furthermore, the remarkable development of nanopore sequencing, for example, the MinION sequencer from Oxford Nanopore Technologies (ONT) as a competitive sequencing technology, has facilitated the rapid analysis of disease-related microbiomes at the whole-genome level and on a large scale. Here, we highlighted recent advances in nanopore approaches for pathogen detection at the single-molecule level. We also overviewed the applications of nanopore sequencing in pathogenic bacteria identification and diagnosis. In the end, we discussed the challenges and future developments of nanopore technology as promising tools for the management of infections, which may be helpful to aid understanding as well as decision-making.

Rapid Detection of Bacterial Pathogens and Antimicrobial Resistance Genes in Clinical Urine Samples With Urinary Tract Infection by Metagenomic Nanopore Sequencing

Urinary tract infections (UTIs) are among the most common acquired bacterial infections in humans. The current gold standard method for identification of uropathogens in clinical laboratories is cultivation. However, culture-based assays have substantial drawbacks, including long turnaround time and limited culturability of many potential pathogens. Nanopore sequencing technology can overcome these limitations and detect pathogens while also providing reliable predictions of drug susceptibility in clinical samples. Here, we optimized a metagenomic nanopore sequencing (mNPS) test for pathogen detection and identification in urine samples of 76 patients with acute uncomplicated UTIs. We first used twenty of these samples to show that library preparation by the PCR Barcoding Kit (PBK) led to the highest agreement of positive results with gold standard clinical culture tests, and enabled antibiotic resistance detection in downstream analyses. We then compared the detection results of mNPS with those of culture-based diagnostics and found that mNPS sensitivity and specificity of detection were 86.7% [95% confidence interval (CI), 73.5-94.1%] and 96.8% (95% CI, 82.4-99.9%), respectively, indicating that the mNPS method is a valid approach for rapid and specific detection of UTI pathogens. The mNPS results also performed well at predicting antibiotic susceptibility phenotypes. These results demonstrate that our workflow can accurately diagnose UTI-causative pathogens and enable successful prediction of drug-resistant phenotypes within 6 h of sample receipt. Rapid mNPS testing is thus a promising clinical diagnostic tool for infectious diseases, based on clinical urine samples from UTI patients, and shows considerable potential for application in other clinical infections.

Species- and strain-level assessment using rrn long-amplicons suggests donor's influence on gut microbial transference via fecal transplants in metabolic syndrome subjects

Fecal microbiota transplantation (FMT) is currently used for treating Clostridium difficile infection and explored for other clinical applications in experimental trials. However, the effectiveness of this therapy could vary, and partly depend on the donor's bacterial species engraftment, whose evaluation is challenging because there are no cost-effective strategies for accurately tracking the microbe transference. In this regard, the precise identification of bacterial species inhabiting the human gut is essential to define their role in human health unambiguously. We used Nanopore-based device to sequence bacterial rrn operons (16S-ITS-23S) and to reveal species-level abundance changes in the human gut microbiota of a FMT trial. By assessing the donor and recipient microbiota before and after FMT, we further evaluated whether this molecular approach reveals strain-level genetic variation to demonstrate microbe transfer and engraftment. Strict control over sequencing data quality and major microbiota covariates was critical for accurately estimating the changes in gut microbial species abundance in the recipients after FMT. We detected strain-level variation via single-nucleotide variants (SNVs) at rrn regions in a species-specific manner. We showed that it was possible to explore successfully the donor-bacterial strain (e.g., Parabacteroides merdae) engraftment in recipients of the FMT by assessing the nucleotide frequencies at rrn-associated SNVs. Our findings indicate that the engraftment of donors' microbiota is to some extent correlated with the improvement of metabolic health in recipients and that parameters such as the baseline gut microbiota configuration, sex, and age of donors should be considered to ensure the success of FMT in humans. The study was prospectively registered at the Dutch Trial registry - NTR4488 (https://www.trialregister.nl/trial/4488).

Long-Reads-Based Metagenomics in Clinical Diagnosis With a Special Focus on Fungal Infections

Identification of the causative infectious agent is essential in the management of infectious diseases, with the ideal diagnostic method being rapid, accurate, and informative, while remaining cost-effective. Traditional diagnostic techniques rely on culturing and cell propagation to isolate and identify the causative pathogen. These techniques are limited by the ability and the time required to grow or propagate an agent in vitro and the facts that identification based on morphological traits are non-specific, insensitive, and reliant on technical expertise. The evolution of next-generation sequencing has revolutionized genomic studies to generate more data at a cheaper cost. These are divided into short- and long-read sequencing technologies, depending on the length of reads generated during sequencing runs. Long-read sequencing also called third-generation sequencing emerged commercially through the instruments released by Pacific Biosciences and Oxford Nanopore Technologies, although relying on different sequencing chemistries, with the first one being more accurate both platforms can generate ultra-long sequence reads. Long-read sequencing is capable of entirely spanning previously established genomic identification regions or potentially small whole genomes, drastically improving the accuracy of the identification of pathogens directly from clinical samples. Long-read sequencing may also provide additional important clinical information, such as antimicrobial resistance profiles and epidemiological data from a single sequencing run. While initial applications of long-read sequencing in clinical diagnosis showed that it could be a promising diagnostic technique, it also has highlighted the need for further optimization. In this review, we show the potential long-read sequencing has in clinical diagnosis of fungal infections and discuss the pros and cons of its implementation.

Detection of single nucleotide and copy number variants in the Fabry disease-associated GLA gene using nanopore sequencing

More than 900 variants have been described in the GLA gene. Some intronic variants and copy number variants in GLA can cause Fabry disease but will not be detected by classical Sanger sequence. We aimed to design and validate a method for sequencing the GLA gene using long-read Oxford Nanopore sequencing technology. Twelve Fabry patients were blindly analyzed, both by conventional Sanger sequence and by long-read sequencing of a 13 kb PCR amplicon. We used minimap2 to align the long-read data and Nanopolish and Sniffles to call variants. All the variants detected by Sanger (including a deep intronic variant) were also detected by long-read sequencing. One patient had a deletion that was not detected by Sanger sequencing but was detected by the new technology. Our long-read sequencing-based method was able to detect missense variants and an exonic deletion, with the added advantage of intronic analysis. It can be used as an efficient and cost-effective tool for screening and diagnosing Fabry disease.

Pitfalls in genotypic antimicrobial susceptibility testing caused by low expression of blaKPC in Escherichia coli

BACKGROUND

There is a growing interest in the rapid genotypic identification of antimicrobial resistance (AMR). In routine diagnostics, we detected multiple KPC-positive Escherichia coli (KPC-Ec) with discordant phenotypic meropenem susceptibility from a single patient's blood cultures, which prompted a more thorough investigation.

OBJECTIVES

We investigated the potential clinical relevance of, and the mechanism behind, discordant phenotypic and genotypic meropenem susceptibility in KPC-Ec.

METHODS

WGS was used to perform a comparative analysis of the isolates' genetic characteristics and their blaKPC-2 locus. Expression of blaKPC-2 was determined by quantitative PCR and the potency of meropenem hydrolysis was determined using a semi-quantitative carbapenem inactivation method. An in vivo infection assay using Galleria mellonella was performed to assess the potential clinical relevance of KPC expression in E. coli.

RESULTS

Despite the presence of blaKPC-2, three of five isolates were susceptible to meropenem (MICVITEK2 ≤ 0.25 mg/L), while two isolates were resistant (MICVITEK2 ≥ 16 mg/L). The isolates with high MICs had significantly higher blaKPC-2 expression, which corresponds to phenotypic meropenem inactivation. The genetic environment of blaKPC-2, which may impact KPC production, was identical in all isolates. In vivo infection assay with G. mellonella suggested that meropenem was effective in reducing mortality following infection with low-expressing KPC-Ec.

CONCLUSIONS

Our findings clearly highlight a limitation of genotypic AMR prediction for blaKPC. For the time being, genotypic AMR prediction requires additional analysis for accurate antibiotic therapy decision-making.

Comprehensive Pathogen Identification, Antibiotic Resistance, and Virulence Genes Prediction Directly From Simulated Blood Samples and Positive Blood Cultures by Nanopore Metagenomic Sequencing

Bloodstream infection is a major cause of morbidity and mortality worldwide. We explored whether MinION nanopore sequencing could accelerate diagnosis, resistance, and virulence profiling prediction in simulated blood samples and blood cultures. One milliliter of healthy blood samples each from direct spike (sample 1), anaerobic (sample 2), and aerobic (sample 3) blood cultures with initial inoculation of ∼30 CFU/ml of a clinically isolated Klebsiella pneumoniae strain was subjected to DNA extraction and nanopore sequencing. Hybrid assembly of Illumina and nanopore reads from pure colonies of the isolate (sample 4) was used as a reference for comparison. Hybrid assembly of the reference genome identified a total of 39 antibiotic resistance genes and 77 virulence genes through alignment with the CARD and VFDB databases. Nanopore correctly detected K. pneumoniae in all three blood samples. The fastest identification was achieved within 8 h from specimen to result in sample 1 without blood culture. However, direct sequencing in sample 1 only identified seven resistance genes (20.6%) but 28 genes in samples 2–4 (82.4%) compared to the reference within 2 h of sequencing time. Similarly, 11 (14.3%) and 74 (96.1%) of the virulence genes were detected in samples 1 and 2–4 within 2 h of sequencing time, respectively. Direct nanopore sequencing from positive blood cultures allowed comprehensive pathogen identification, resistance, and virulence genes prediction within 2 h, which shows its promising use in point-of-care clinical settings.

Oxford nanopore sequencing in clinical microbiology and infection diagnostics

Extended turnaround times and large economic costs hinder the usage of currently applied screening methods for bacterial pathogen identification (ID) and antimicrobial susceptibility testing. This review provides an overview of current detection methods and their usage in a clinical setting. Issues of timeliness and cost could soon be circumvented, however, with the emergence of detection methods involving single molecule sequencing technology. In the context of bringing diagnostics closer to the point of care, we examine the current state of Oxford Nanopore Technologies (ONT) products and their interaction with third-party software/databases to assess their capabilities for ID and antimicrobial resistance (AMR) prediction. We outline and discuss a potential diagnostic workflow, enumerating (1) rapid sample prep kits, (2) ONT hardware/software and (3) third-party software and databases to improve the cost, accuracy and turnaround times for ID and AMR. Multiple studies across a range of infection types support that the speed and accuracy of ONT sequencing is now such that established ID and AMR prediction tools can be used on its outputs, and so it can be harnessed for near real time, close to the point-of-care diagnostics in common clinical circumstances.

MinION Nanopore-based detection of Clavibacter nebraskensis, the corn Goss's wilt pathogen, and bacteriomic profiling of necrotic lesions of naturally-infected leaf samples

The Goss’s bacterial wilt pathogen, Clavibacter nebraskensis, of corn is a candidate A1 quarantine organism; and its recent re-emergence and spread in the USA and Canada is a potential biothreat to the crop. We developed and tested an amplicon-based Nanopore detection system for C. nebraskensis (Cn), targeting a purine permease gene. The sensitivity (1 pg) of this system in mock bacterial communities (MBCs) spiked with serially diluted DNA of C. nebraskensis NCPPB 2581^T is comparable to that of real-time PCR. Average Nanopore reads increased exponentially from 125 (1pg) to about 6000 reads (1000 pg) after a 3-hr run-time, with 99.0% of the reads accurately assigned to C. nebraskensis. Three run-times were used to process control MBCs, Cn-spiked MBCs, diseased and healthy leaf samples. The mean Nanopore reads doubled as the run-time is increased from 3 to 6 hrs while from 6 to 12 hrs, a 20% increment was recorded in all treatments. Cn-spiked MBCs and diseased corn leaf samples averaged read counts of 5,100, 11,000 and 14,000 for the respective run-times, with 99.8% of the reads taxonomically identified as C. nebraskensis. The control MBCs and healthy leaf samples had 47 and 14 Nanopore reads, respectively. 16S rRNA bacteriomic profiles showed that Sphingomonas (22.7%) and Clavibacter (21.2%) were dominant in diseased samples while Pseudomonas had only 3.5% relative abundance. In non-symptomatic leaf samples, however, Pseudomonas (20.0%) was dominant with Clavibacter at 0.08% relative abundance. This discrepancy in Pseudomonas abundance in the samples was corroborated by qPCR using EvaGreen chemistry. Our work outlines a new useful tool for diagnosis of the Goss’s bacterial wilt disease; and provides the first insight on Pseudomonas community dynamics in necrotic leaf lesions.

Emerging Options for the Diagnosis of Bacterial Infections and the Characterization of Antimicrobial Resistance

Precise and rapid identification and characterization of pathogens and antimicrobial resistance patterns are critical for the adequate treatment of infections, which represent an increasing problem in intensive care medicine. The current situation remains far from satisfactory in terms of turnaround times and overall efficacy. Application of an ineffective antimicrobial agent or the unnecessary use of broad-spectrum antibiotics worsens the patient prognosis and further accelerates the generation of resistant mutants. Here, we provide an overview that includes an evaluation and comparison of existing tools used to diagnose bacterial infections, together with a consideration of the underlying molecular principles and technologies. Special emphasis is placed on emerging developments that may lead to significant improvements in point of care detection and diagnosis of multi-resistant pathogens, and new directions that may be used to guide antibiotic therapy.

Rapid identification of pathogens, antibiotic resistance genes and plasmids in blood cultures by nanopore sequencing

Bloodstream infections (BSI) and sepsis are major causes of morbidity and mortality worldwide. Blood culture-based diagnostics usually requires 1-2 days for identification of bacterial agent and an additional 2-3 days for phenotypic determination of antibiotic susceptibility pattern. With the escalating burden of antimicrobial resistance (AMR) rapid diagnostics becomes increasingly important to secure adequate antibiotic therapy. Real-time whole genome sequencing represents a genotypic diagnostic approach with the ability to rapidly identify pathogens and AMR-encoding genes. Here we have used nanopore sequencing of bacterial DNA extracted from positive blood cultures for identification of pathogens, detection of plasmids and AMR-encoding genes. To our knowledge, this is the first study to gather the above-mentioned information from nanopore sequencing and conduct a comprehensive analysis for diagnostic purposes in real-time. Identification of pathogens was possible after 10 minutes of sequencing and all predefined AMR-encoding genes and plasmids from monoculture experiments were detected within one hour using raw nanopore sequencing data. Furthermore, we demonstrate the correct identification of plasmids and bla_CTX-M subtypes using de novo assembled nanopore contigs. Results from this study hold great promise for future applications in clinical microbiology and for health care surveillance purposes.

Rapid and Accurate Species Identification of Mitis Group Streptococci Using the MinION Nanopore Sequencer

Differentiation between mitis group streptococci (MGS) bacteria in routine laboratory tests has become important for obtaining accurate epidemiological information on the characteristics of MGS and understanding their clinical significance. The most reliable method of MGS species identification is multilocus sequence analysis (MLSA) with seven house-keeping genes; however, because this method is time-consuming, it is deemed unsuitable for use in most clinical laboratories. In this study, we established a scheme for identifying 12 species of MGS (S. pneumoniae, S. pseudopneumoniae, S. mitis, S. oralis, S. peroris, S. infantis, S. australis, S. parasanguinis, S. sinensis, S. sanguinis, S. gordonii, and S. cristatus) using the MinION nanopore sequencer (Oxford Nanopore Technologies, Oxford, UK) with the taxonomic aligner "What's in My Pot?" (WIMP; Oxford Nanopore's cloud-based analysis platform) and Kraken2 pipeline with the custom database adjusted for MGS species identification. The identities of the species in reference genomes (n = 514), clinical isolates (n = 31), and reference strains (n = 4) were confirmed via MLSA. The nanopore simulation reads were generated from reference genomes, and the optimal cut-off values for MGS species identification were determined. For 31 clinical isolates (S. pneumoniae = 8, S. mitis = 17 and S. oralis = 6) and 4 reference strains (S. pneumoniae = 1, S. mitis = 1, S. oralis = 1, and S. pseudopneumoniae = 1), a sequence library was constructed via a Rapid Barcoding Sequencing Kit for multiplex and real-time MinION sequencing. The optimal cut-off values for the identification of MGS species for analysis by WIMP and Kraken2 pipeline were determined. The workflow using Kraken2 pipeline with a custom database identified all 12 species of MGS, and WIMP identified 8 MGS bacteria except S. infantis, S. australis, S. peroris, and S. sinensis. The results obtained by MinION with WIMP and Kraken2 pipeline were consistent with the MGS species identified by MLSA analysis. The practical advantage of whole genome analysis using the MinION nanopore sequencer is that it can aid in MGS surveillance. We concluded that MinION sequencing with the taxonomic aligner enables accurate MGS species identification and could contribute to further epidemiological surveys.