Identification of bacterial pathogens and antimicrobial resistance directly from clinical urines by nanopore-based metagenomic sequencing

Sensitivity and specificity of Nanopore sequencing for detecting carbapenem and 3rd-generation cephalosporin-resistant Enterobacteriaceae in urine samples: Real-time simulation with public antimicrobial resistance gene database

Objectives

To evaluate the accuracy of beta-lactamase gene detection directly from urine samples by Nanopore sequencing.

Methods

DNA was extracted from bacterial pellets in spun urine. The purified DNA was then sequenced in native form by a Nanopore sequencer (MinION) to identify the organisms and beta-lactamase genes. Results were compared to routine urine cultures and standard antimicrobial susceptibility tests (AST).

Results

We processed 60 urine samples of which routine cultures grew Enterobacteriaceae, including 28 carbapenem-resistant (CRE), 17 extended-spectrum beta-lactamase (ESBL) or AmpC producing, and 15 non-ESBL/AmpC phenotypes. We excluded 7 samples with extremely low DNA amounts (<1 ng/μl) for a final case of 53 in total. The sensitivity of antimicrobial resistance gene detection within 6 h, the optimal duration from real-time simulation, of Nanopore sequencing for the diagnosis of carbapenem-resistant and ceftriaxone-resistant phenotypes was 73.9 % (95%CI 56.0-91.9 %) and 81.1 % (95%CI 68.5-93.7 %), while the specificity was 96.7 % (95%CI 90.2-100.0 %) and 56.3 % (95%CI 31.9-80.6 %), respectively. The median times for MinION to generate DNA reads containing carbapenemase and ESBL/AmpC genes were 93 min (IQR 17-245.5) and 99 min (IQR 31.25-269.75) after sequencing commencement, respectively.

Conclusions

Nanopore sequencing can identify bacterial genotypic resistance in urine and may enable clinicians to adjust antimicrobial therapy earlier than routine AST.

Nanoplasmonic Rapid Antimicrobial-Resistance Point-of-Care Identification Device: RAPIDx

The emergence of antibiotic resistance has become a global health crisis, and everyone must arm themselves with wisdom to effectively combat the "silent tsunami" of infections that are no longer treatable with antibiotics. However, the overuse or inappropriate use of unnecessary antibiotics is still routine for administering them due to the unavailability of rapid, precise, and point-of-care assays. Here, a rapid antimicrobial-resistance point-of-care identification device (RAPIDx) is reported for the accurate and simultaneous identification of bacterial species (genotype) and target enzyme activity (phenotype). First, a contamination-free active target enzyme is extracted via the photothermal lysis of preconcentrated bacteria cells on a nanoplasmonic functional layer on-chip. Second, the rapid, precise identification of pathogens is achieved by the photonic rolling circle amplification of DNA on a chip. Third, the simultaneous identification of bacterial species (genotype) and target enzyme activity (phenotype) is demonstrated within a sample-to-answer 45 min operation via the RAPIDx. It is believed that the RAPIDx will be a valuable method for solving the bottleneck of employing on-chip nanotechnology for antibiotic-resistant bioassay and other infectious diseases.

Comprehensive identification of pathogenic microbes and antimicrobial resistance genes in food products using nanopore sequencing-based metagenomics

Foodborne pathogens, particularly antimicrobial-resistant (AMR) bacteria, remain a significant threat to global health. Given the limitations of conventional culture-based approaches, which are limited in scope and time-consuming, metagenomic sequencing of food products emerges as a promising solution. This method provides a fast and comprehensive way to detect the presence of pathogenic microbes and antimicrobial resistance genes (ARGs). Notably, nanopore long-read sequencing provides more accurate bacterial taxonomic classification in comparison to short-read sequencing. Here, we revealed the impact of food types and attributes (origin, retail place, and food processing methods) on microbial communities and the AMR profile using nanopore metagenomic sequencing. We analyzed a total of 260 food products, including raw meat, sashimi, and ready-to-eat (RTE) vegetables. Clostridium botulinum, Acinetobacter baumannii, and Vibrio parahaemolyticus were identified as the top three foodborne pathogens in raw meat and sashimi. Importantly, even with low pathogen abundance, higher percentages of samples containing carbapenem and cephalosporin resistance genes were identified in chicken and RTE vegetables, respectively. In parallel, our results demonstrated that fresh, peeled, and minced foods exhibited higher levels of pathogenic bacteria. In conclusion, this comprehensive study offers invaluable data that can contribute to food safety assessments and serve as a basis for quality indicators.

A Nanopore Sequencing-based Pharmacogenomic Panel to Personalize Tuberculosis Drug Dosing

Rationale: Standardized dosing of antitubercular drugs leads to variable plasma drug levels, which are associated with adverse drug reactions, delayed treatment response, and relapse. Mutations in genes affecting drug metabolism explain considerable interindividual pharmacokinetic variability; however, pharmacogenomic assays that predict metabolism of antitubercular drugs have been lacking. Objectives: We sought to develop a Nanopore sequencing panel and validate its performance in patients with active tuberculosis (TB) to personalize treatment dosing. Methods: We developed a Nanopore sequencing panel targeting 15 SNPs in five genes affecting the metabolism of antitubercular drugs. For validation, we sequenced DNA samples (n = 48) from the 1,000 Genomes Project and compared the variant calling accuracy with that of Illumina genome sequencing. We then sequenced DNA samples from patients with active TB (n = 100) from South Africa on a MinION Mk1C and evaluated the relationship between genotypes and pharmacokinetic parameters for isoniazid (INH) and rifampin (RIF). Measurements and Main Results: The pharmacogenomic panel achieved 100% concordance with Illumina sequencing in variant identification for the samples from the 1,000 Genomes Project. In the clinical cohort, coverage was more than 100× for 1,498 of 1,500 (99.8%) amplicons across the 100 samples. Thirty-three percent, 47%, and 20% of participants were identified as slow, intermediate, and rapid INH acetylators, respectively. INH clearance was 2.2 times higher among intermediate acetylators and 3.8 times higher among rapid acetylators, compared with slow acetylators (P < 0.0001). RIF clearance was 17.3% (2.50-29.9) lower in individuals with homozygous AADAC rs1803155 G→A substitutions (P = 0.0015). Conclusions: Targeted sequencing can enable the detection of polymorphisms that influence TB drug metabolism on a low-cost, portable instrument to personalize dosing for TB treatment or prevention.

Suppression PCR-Based Selective Enrichment Sequencing for Pathogen and Antimicrobial Resistance Detection on Cell-Free DNA in Sepsis-A Targeted, Blood Culture-Independent Approach for Rapid Pathogen and Resistance Diagnostics in Septic Patients

Sepsis is a life-threatening syndrome triggered by infection and accompanied by high mortality, with antimicrobial resistances (AMRs) further escalating clinical challenges. The rapid and reliable detection of causative pathogens and AMRs are key factors for fast and appropriate treatment, in order to improve outcomes in septic patients. However, current sepsis diagnostics based on blood culture is limited by low sensitivity and specificity while current molecular approaches fail to enter clinical routine. Therefore, we developed a suppression PCR-based selective enrichment sequencing approach (SUPSETS), providing a molecular method combining multiplex suppression PCR with Nanopore sequencing to identify most common sepsis-causative pathogens and AMRs using plasma cell-free DNA. Applying only 1 mL of plasma, we targeted eight pathogens across three kingdoms and ten AMRs in a proof-of-concept study. SUPSETS was successfully tested in an experimental research study on the first ten clinical samples and revealed comparable results to clinical metagenomics while clearly outperforming blood culture. Several clinically relevant AMRs could be additionally detected. Furthermore, SUPSETS provided first pathogen and AMR-specific sequencing reads within minutes of starting sequencing, thereby potentially decreasing time-to-results to 11-13 h and suggesting diagnostic potential in sepsis.

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.

Comparison of metagenomic and traditional methods for diagnosis of E. coli enteric infections

Diarrheagenic Escherichia coli, collectively known as DEC, is a leading cause of diarrhea, particularly in children in low- and middle-income countries. Diagnosing infections caused by different DEC pathotypes traditionally relies on the cultivation and identification of virulence genes, a resource-intensive and error-prone process. Here, we compared culture-based DEC identification with shotgun metagenomic sequencing of whole stool using 35 randomly drawn samples from a cohort of diarrhea-afflicted patients. Metagenomic sequencing detected the cultured isolates in 97% of samples, revealing, overall, reliable detection by this approach. Genome binning yielded high-quality E. coli metagenome-assembled genomes (MAGs) for 13 samples, and we observed that the MAG did not carry the diagnostic DEC virulence genes of the corresponding isolate in 60% of these samples. Specifically, two distinct scenarios were observed: diffusely adherent E. coli (DAEC) isolates without corresponding DAEC MAGs appeared to be relatively rare members of the microbiome, which was further corroborated by quantitative PCR (qPCR), and thus unlikely to represent the etiological agent in 3 of the 13 samples (~23%). In contrast, ETEC virulence genes were located on plasmids and largely escaped binning in associated MAGs despite being prevalent in the sample (5/13 samples or ~38%), revealing limitations of the metagenomic approach. These results provide important insights for diagnosing DEC infections and demonstrate how metagenomic methods can complement isolation efforts and PCR for pathogen identification and population abundance.

IMPORTANCE

Diagnosing enteric infections based on traditional methods involving isolation and PCR can be erroneous due to isolation and other biases, e.g., the most abundant pathogen may not be recovered on isolation media. By employing shotgun metagenomics together with traditional methods on the same stool samples, we show that mixed infections caused by multiple pathogens are much more frequent than traditional methods indicate in the case of acute diarrhea. Further, in at least 8.5% of the total samples examined, the metagenomic approach reliably identified a different pathogen than the traditional approach. Therefore, our results provide a methodology to complement existing methods for enteric infection diagnostics with cutting-edge, culture-independent metagenomic techniques, and highlight the strengths and limitations of each approach.

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.

Predictive phage therapy for Escherichia coli urinary tract infections: Cocktail selection for therapy based on machine learning models

This study supports the development of predictive bacteriophage (phage) therapy: the concept of phage cocktail selection to treat a bacterial infection based on machine learning (ML) models. For this purpose, ML models were trained on thousands of measured interactions between a panel of phage and sequenced bacterial isolates. The concept was applied to Escherichia coli associated with urinary tract infections. This is an important common infection in humans and companion animals from which multidrug-resistant (MDR) bloodstream infections can originate. The global threat of MDR infection has reinvigorated international efforts into alternatives to antibiotics including phage therapy. E. coli exhibit extensive genome-level variation due to horizontal gene transfer via phage and plasmids. Associated with this, phage selection for E. coli is difficult as individual isolates can exhibit considerable variation in phage susceptibility due to differences in factors important to phage infection including phage receptor profiles and resistance mechanisms. The activity of 31 phage was measured on 314 isolates with growth curves in artificial urine. Random Forest models were built for each phage from bacterial genome features, and the more generalist phage, acting on over 20% of the bacterial population, exhibited F1 scores of >0.6 and could be used to predict phage cocktails effective against previously untested strains. The study demonstrates the potential of predictive ML models which integrate bacterial genomics with phage activity datasets allowing their use on data derived from direct sequencing of clinical samples to inform rapid and effective phage therapy.

Development and proof-of-concept demonstration of a clinical metagenomics method for the rapid detection of bloodstream infection

BACKGROUND

The timely and accurate diagnosis of bloodstream infection (BSI) is critical for patient management. With longstanding challenges for routine blood culture, metagenomics is a promising approach to rapidly provide sequence-based detection and characterisation of bloodborne bacteria. Long-read sequencing technologies have successfully supported the use of clinical metagenomics for syndromes such as respiratory illness, and modified approaches may address two requisite factors for metagenomics to be used as a BSI diagnostic: depletion of the high level of host DNA to then detect the low abundance of microbes in blood.

METHODS

Blood samples from healthy donors were spiked with different concentrations of four prevalent causative species of BSI. All samples were then subjected to a modified saponin-based host DNA depletion protocol and optimised DNA extraction, whole genome amplification and debranching steps in preparation for sequencing, followed by bioinformatical analyses. Two related variants of the protocol are presented: 1mL of blood processed without bacterial enrichment, and 5mL of blood processed following a rapid bacterial enrichment protocol-SepsiPURE.

RESULTS

After first identifying that a large proportion of host mitochondrial DNA remained, the host depletion process was optimised by increasing saponin concentration to 3% and scaling the reaction to allow more sample volume. Compared to non-depleted controls, the 3% saponin-based depletion protocol reduced the presence of host chromosomal and mitochondrial DNA < 106 and < 103 fold respectively. When the modified depletion method was further combined with a rapid bacterial enrichment method (SepsiPURE; with 5mL blood samples) the depletion of mitochondrial DNA improved by a further > 10X while also increasing detectable bacteria by > 10X. Parameters during DNA extraction, whole genome amplification and long-read sequencing were also adjusted, and subsequently amplicons were detected for each input bacterial species at each of the spiked concentrations, ranging from 50-100 colony forming units (CFU)/mL to 1-5 CFU/mL.

CONCLUSION

In this proof-of-concept study, four prevalent BSI causative species were detected in under 12 h to species level (with antimicrobial resistance determinants) at concentrations relevant to clinical blood samples. The use of a rapid and precise metagenomic protocols has the potential to advance the diagnosis of BSI.

The Report Says What?: How the Medical Microbiologist can aid in the Interpretation of Next-Generation Sequencing Results

The applications of next-generation sequencing (NGS) in the clinical microbiology laboratory are expanding at a rapid pace. The medical microbiologist thus plays a key role in translating the results of these emerging technologies to the practicing clinician. Here we discuss the factors to consider to successfully develop standardized reporting for microbial targeted or metagenomic NGS testing in the clinical laboratory.

The application of nanopore targeted sequencing for pathogen diagnosis in bronchoalveolar lavage fluid of patients with pneumonia: a prospective multicenter study

OBJECTIVE

To evaluate the value of nanopore targeted sequencing in diagnosing pneumonia pathogens.

METHODS

This large-scale multicentre prospective study performed in 8 hospitals across China from April to October 2022. Hospitalised patients with a diagnosis of pneumonia at admission were included. Complete clinical data were collected, and bronchoalveolar lavage fluid were obtained from each patient. These samples underwent simultaneous testing using conventional microbial testing, metagenomic next-generation sequencing, and nanopore targeted sequencing.

RESULTS

A total of 218 patients were included. Among the 168 cases of pulmonary infection, 246 strains of pathogens were confirmed. Nanopore targeted sequencing outperformed conventional microbial testing, identifying more pathogens with a sensitivity increase of 47.9% (77.2% vs. 29.3%). Metagenomic next-generation sequencing had a sensitivity of 82.9%. Total of 70.1% patients had consistent results in both metagenomic next-generation sequencing and nanopore targeted sequencing. Nanopore targeted sequencing exhibited significantly higher sensitivity in detecting Pneumocystis jiroveci, cytomegalovirus, Mycobacterium tuberculosis, Nontuberculous mycobacteria, Streptococcus pneumoniae, and Mycoplasma pneumoniae compared to conventional microbial testing. However, metagenomic next-generation sequencing demonstrated higher sensitivity than nanopore targeted sequencing for Aspergillus (88.5% vs. 53.8%). Regarding the detection of co-infections, nanopore targeted sequencing displayed significantly higher sensitivity than conventional microbial testing (76.7% vs. 28.7%) and was on par with metagenomic next-generation sequencing (76.7% vs. 82.9%).

CONCLUSION

Nanopore targeted sequencing performs equally well as metagenomic next-generation sequencing in bronchoalveolar lavage fluid for pathogen diagnosis in pneumonia, both methods showing higher sensitivity than conventional microbial testing. Nanopore targeted sequencing can be considered a reliable method for diagnosing pathogens in pneumonia.

Multi-omics approaches to studying gastrointestinal microbiome in the context of precision medicine and machine learning

The human gastrointestinal (gut) microbiome plays a critical role in maintaining host health and has been increasingly recognized as an important factor in precision medicine. High-throughput sequencing technologies have revolutionized -omics data generation, facilitating the characterization of the human gut microbiome with exceptional resolution. The analysis of various -omics data, including metatranscriptomics, metagenomics, glycomics, and metabolomics, holds potential for personalized therapies by revealing information about functional genes, microbial composition, glycans, and metabolites. This multi-omics approach has not only provided insights into the role of the gut microbiome in various diseases but has also facilitated the identification of microbial biomarkers for diagnosis, prognosis, and treatment. Machine learning algorithms have emerged as powerful tools for extracting meaningful insights from complex datasets, and more recently have been applied to metagenomics data via efficiently identifying microbial signatures, predicting disease states, and determining potential therapeutic targets. Despite these rapid advancements, several challenges remain, such as key knowledge gaps, algorithm selection, and bioinformatics software parametrization. In this mini-review, our primary focus is metagenomics, while recognizing that other -omics can enhance our understanding of the functional diversity of organisms and how they interact with the host. We aim to explore the current intersection of multi-omics, precision medicine, and machine learning in advancing our understanding of the gut microbiome. A multidisciplinary approach holds promise for improving patient outcomes in the era of precision medicine, as we unravel the intricate interactions between the microbiome and human health.

Convergence of resistance and evolutionary responses in Escherichia coli and Salmonella enterica co-inhabiting chicken farms in China

Sharing of genetic elements among different pathogens and commensals inhabiting same hosts and environments has significant implications for antimicrobial resistance (AMR), especially in settings with high antimicrobial exposure. We analysed 661 Escherichia coli and Salmonella enterica isolates collected within and across hosts and environments, in 10 Chinese chicken farms over 2.5 years using data-mining methods. Most isolates within same hosts possessed the same clinically relevant AMR-carrying mobile genetic elements (plasmids: 70.6%, transposons: 78%), which also showed recent common evolution. Supervised machine learning classifiers revealed known and novel AMR-associated mutations and genes underlying resistance to 28 antimicrobials, primarily associated with resistance in E. coli and susceptibility in S. enterica. Many were essential and affected same metabolic processes in both species, albeit with varying degrees of phylogenetic penetration. Multi-modal strategies are crucial to investigate the interplay of mobilome, resistance and metabolism in cohabiting bacteria, especially in ecological settings where community-driven resistance selection occurs.

Drug resistance and vaccine target surveillance of Plasmodium falciparum using nanopore sequencing in Ghana

Malaria results in over 600,000 deaths annually, with the highest burden of deaths in young children living in sub-Saharan Africa. Molecular surveillance can provide important information for malaria control policies, including detection of antimalarial drug resistance. However, genome sequencing capacity in malaria-endemic countries is limited. We designed and implemented an end-to-end workflow to detect Plasmodium falciparum antimalarial resistance markers and diversity in the vaccine target circumsporozoite protein (csp) using nanopore sequencing in Ghana. We analysed 196 clinical samples and showed that our method is rapid, robust, accurate and straightforward to implement. Importantly, our method could be applied to dried blood spot samples, which are readily collected in endemic settings. We report that P. falciparum parasites in Ghana are mostly susceptible to chloroquine, with persistent sulfadoxine-pyrimethamine resistance and no evidence of artemisinin resistance. Multiple single nucleotide polymorphisms were identified in csp, but their significance is uncertain. Our study demonstrates the feasibility of nanopore sequencing for malaria genomic surveillance in endemic countries.

Metagenomics for the microbiological diagnosis of hospital-acquired pneumonia and ventilator-associated pneumonia (HAP/VAP) in intensive care unit (ICU): a proof-of-concept study

BACKGROUND

Hospital-acquired and ventilator-associated-pneumonia (HAP/VAP) are one of the most prevalent health-care associated infections in the intensive care unit (ICU). Culture-independent methods were therefore developed to provide faster route to diagnosis and treatment. Among these, metagenomic next-generation sequencing (mNGS) has shown considerable promise.

METHODS

This proof-of-concept study describes the technical feasibility and evaluates the clinical validity of the mNGS for the detection and characterization of the etiologic agents causing hospital-acquired and ventilator-associated pneumonia. We performed a prospective study of all patients with HAP/VAP hospitalized in our intensive care unit for whom a bronchoalveolar lavage (BAL) was performed between July 2017 and November 2018. We compared BAL fluid culture and mNGS results of these patients.

RESULTS

A total of 32 BAL fluids were fully analyzed. Of these, 22 (69%) were positive by culture and all pathogens identified were also reported by mNGS. Among the culture-positive BAL samples, additional bacterial species were revealed by mNGS for 12 patients, raising the issue of their pathogenic role (colonization versus coinfection). Among BALF with culture-negative test, 5 were positive in mNGS test.

CONCLUSIONS

This study revealed concordant results for pneumonia panel pathogens between mNGS and culture-positive tests and identified additional pathogens potentially implicated in pneumonia without etiologic diagnosis by culture. mNGS has emerged as a promising methodology for infectious disease diagnoses to support conventional methods. Prospective studies with real-time mNGS are warranted to examine the impact on antimicrobial decision-making and clinical outcome.

Urinary tract infections: a review of the current diagnostics landscape

Urinary tract infections are the most common bacterial infections worldwide. Infections can range from mild, recurrent (rUTI) to complicated (cUTIs), and are predominantly caused by uropathogenic Escherichia coli (UPEC). Antibiotic therapy is important to tackle infection; however, with the continued emergence of antibiotic resistance there is an urgent need to monitor the use of effective antibiotics through better stewardship measures. Currently, clinical diagnosis of UTIs relies on empiric methods supported by laboratory testing including cellular analysis (of both human and bacterial cells), dipstick analysis and phenotypic culture. Therefore, development of novel, sensitive and specific diagnostics is an important means to rationalise antibiotic therapy in patients. This review discusses the current diagnostic landscape and highlights promising novel diagnostic technologies in development that could aid in treatment and management of antibiotic-resistant UTIs.

Next-Generation sequencing transforming clinical practice and precision medicine

Next-generation sequencing (NGS) has revolutionized the field of genomics and is rapidly transforming clinical diagnosis and precision medicine. This advanced sequencing technology enables the rapid and cost-effective analysis of large-scale genomic data, allowing comprehensive exploration of the genetic landscape of diseases. In clinical diagnosis, NGS has proven to be a powerful tool for identifying disease-causing variants, enabling accurate and early detection of genetic disorders. Additionally, NGS facilitates the identification of novel disease-associated genes and variants, aiding in the development of targeted therapies and personalized treatment strategies. NGS greatly benefits precision medicine by enhancing our understanding of disease mechanisms and enabling the identification of specific molecular markers for disease subtypes, thus enabling tailored medical interventions based on individual characteristics. Furthermore, NGS contributes to the development of non-invasive diagnostic approaches, such as liquid biopsies, which can monitor disease progression and treatment response. The potential of NGS in clinical diagnosis and precision medicine is vast, yet challenges persist in data analysis, interpretation, and protocol standardization. This review highlights NGS applications in disease diagnosis, prognosis, and personalized treatment strategies, while also addressing challenges and future prospects in fully harnessing genomic potential within clinical practice.

Clinical evaluation of metagenomic next-generation sequencing in unbiased pathogen diagnosis of urinary tract infection

BACKGROUND

Early availability of pathogen identification in urinary tract infections (UTIs) has critical importance in disease management. Metagenomic next-generation sequencing (mNGS) has the potential to transform how acute and serious infections are diagnosed by offering unbiased and culture-free pathogen detection. However, clinical experience with application of the mNGS test is relatively limited.

METHODS

We therefore established a MinION-based mNGS pathogens diagnostic platform and evaluated its potential for clinical implementation in UTIs with clinical samples. 213 urine samples from patients with suspected UTIs were included and subjected to mNGS testing using the MinION platform. mNGS results were compared to the gold standard of clinical culture and composite standard of combining clinical testing, confirmatory qPCR testing, and clinical adjudication by doctors.

RESULTS

The mNGS exhibited a sensitivity of 81.4% and a specificity of 92.3%, along with a positive predictive value of 96.6%, a negative predictive value of 64.9%, and an overall accuracy of 84.4%, all of which were determined based on the gold standard of routine culture results. When assessed against the composite standard, the sensitivity and specificity both increased to 89.9% and 100%, respectively, while the accuracy rose to 92.4%. Notably, the positive predictive value and negative predictive value also saw improvements, reaching 100% and 76.8%, respectively. Moreover, this diagnostic platform successfully identified dsDNA viruses. Among the 65 culture-negative samples, the viral detection rate reached 33.8% (22/65) and was subsequently validated through qPCR. Furthermore, the automatic bioinformatics pipeline we developed enabled one-click analysis from data to results, leading to a significant reduction in diagnosis time.

CONCLUSION

These results demonstrate that the pathogen detection performance of mNGS is sufficient for diagnostic testing in clinical settings. As the method is generally unbiased, it can improve diagnostic testing of UTIs and other microbial infections.

Current and Future Technologies for the Detection of Antibiotic-Resistant Bacteria

Antibiotic resistance is a global public health concern, posing a significant threat to the effectiveness of antibiotics in treating bacterial infections. The accurate and timely detection of antibiotic-resistant bacteria is crucial for implementing appropriate treatment strategies and preventing the spread of resistant strains. This manuscript provides an overview of the current and emerging technologies used for the detection of antibiotic-resistant bacteria. We discuss traditional culture-based methods, molecular techniques, and innovative approaches, highlighting their advantages, limitations, and potential future applications. By understanding the strengths and limitations of these technologies, researchers and healthcare professionals can make informed decisions in combating antibiotic resistance and improving patient outcomes.

cgMSI: pathogen detection within species from nanopore metagenomic sequencing data

BACKGROUND

Metagenomic sequencing is an unbiased approach that can potentially detect all the known and unidentified strains in pathogen detection. Recently, nanopore sequencing has been emerging as a highly potential tool for rapid pathogen detection due to its fast turnaround time. However, identifying pathogen within species is nontrivial for nanopore sequencing data due to the high sequencing error rate.

RESULTS

We developed the core gene alleles metagenome strain identification (cgMSI) tool, which uses a two-stage maximum a posteriori probability estimation method to detect pathogens at strain level from nanopore metagenomic sequencing data at low computational cost. The cgMSI tool can accurately identify strains and estimate relative abundance at 1× coverage.

CONCLUSIONS

We developed cgMSI for nanopore metagenomic pathogen detection within species. cgMSI is available at https://github.com/ZHU-XU-xmu/cgMSI .

A Comprehensive Bioinformatics Resource Guide for Genome-Based Antimicrobial Resistance Studies

The use of high-throughput sequencing technologies and bioinformatic tools has greatly transformed microbial genome research. With the help of sophisticated computational tools, it has become easier to perform whole genome assembly, identify and compare different species based on their genomes, and predict the presence of genes responsible for proteins, antimicrobial resistance, and toxins. These bioinformatics resources are likely to continuously improve in quality, become more user-friendly to analyze the multiple genomic data, efficient in generating information and translating it into meaningful knowledge, and enhance our understanding of the genetic mechanism of AMR. In this manuscript, we provide an essential guide for selecting the popular resources for microbial research, such as genome assembly and annotation, antibiotic resistance gene profiling, identification of virulence factors, and drug interaction studies. In addition, we discuss the best practices in computer-oriented microbial genome research, emerging trends in microbial genomic data analysis, integration of multi-omics data, the appropriate use of machine-learning algorithms, and open-source bioinformatics resources for genome data analytics.

A Nanopore sequencing-based pharmacogenomic panel to personalize tuberculosis drug dosing

Rationale

Standardized dosing of anti-tubercular (TB) drugs leads to variable plasma drug levels, which are associated with adverse drug reactions, delayed treatment response, and relapse. Mutations in genes affecting drug metabolism explain considerable interindividual pharmacokinetic variability; however, pharmacogenomic (PGx) assays that predict metabolism of anti-TB drugs have been lacking.

Objectives

To develop a Nanopore sequencing panel and validate its performance in active TB patients to personalize treatment dosing.

Measurements and Main Results

We developed a Nanopore sequencing panel targeting 15 single nucleotide polymorphisms (SNP) in 5 genes affecting the metabolism of isoniazid (INH), rifampin (RIF), linezolid and bedaquiline. For validation, we sequenced DNA samples (n=48) from the 1000 genomes project and compared variant calling accuracy with Illumina genome sequencing. We then sequenced DNA samples from patients with active TB (n=100) from South Africa on a MinION Mk1C and evaluated the relationship between genotypes and pharmacokinetic parameters for INH and RIF.

Results

The PGx panel achieved 100% concordance with Illumina sequencing in variant identification for the samples from the 1000 Genomes Project. In the clinical cohort, coverage was >100x for 1498/1500 (99.8%) amplicons across the 100 samples. One third (33%) of participants were identified as slow, 47% were intermediate and 20% were rapid isoniazid acetylators. Isoniazid clearance was significantly impacted by acetylator status (p<0.0001) with median (IQR) clearances of 11.2 L/h (9.3-13.4), 27.2 L/h (22.0-31.7), and 45.1 L/h (34.1-51.1) in slow, intermediate, and rapid acetylators. Rifampin clearance was 17.3% (2.50-29.9) lower in individuals with homozygous AADAC rs1803155 G>A substitutions (p=0.0015).

Conclusion

Targeted sequencing can enable detection of polymorphisms influencing TB drug metabolism on a low-cost, portable instrument to personalize dosing for TB treatment or prevention.

Machine learning and metagenomics reveal shared antimicrobial resistance profiles across multiple chicken farms and abattoirs in China

China is the largest global consumer of antimicrobials and improving surveillance methods could help to reduce antimicrobial resistance (AMR) spread. Here we report the surveillance of ten large-scale chicken farms and four connected abattoirs in three Chinese provinces over 2.5 years. Using a data mining approach based on machine learning, we analysed 461 microbiomes from birds, carcasses and environments, identifying 145 potentially mobile antibiotic resistance genes (ARGs) shared between chickens and environments across all farms. A core set of 233 ARGs and 186 microbial species extracted from the chicken gut microbiome correlated with the AMR profiles of Escherichia coli colonizing the same gut, including Arcobacter, Acinetobacter and Sphingobacterium, clinically relevant for humans, and 38 clinically relevant ARGs. Temperature and humidity in the barns were also correlated with ARG presence. We reveal an intricate network of correlations between environments, microbial communities and AMR, suggesting multiple routes to improving AMR surveillance in livestock production.

Rapid metagenomic sequencing for diagnosis and antimicrobial sensitivity prediction of canine bacterial infections

Antimicrobial resistance is a major threat to human and animal health. There is an urgent need to ensure that antimicrobials are used appropriately to limit the emergence and impact of resistance. In the human and veterinary healthcare setting, traditional culture and antimicrobial sensitivity testing typically requires 48-72 h to identify appropriate antibiotics for treatment. In the meantime, broad-spectrum antimicrobials are often used, which may be ineffective or impact non-target commensal bacteria. Here, we present a rapid, culture-free, diagnostics pipeline, involving metagenomic nanopore sequencing directly from clinical urine and skin samples of dogs. We have planned this pipeline to be versatile and easily implementable in a clinical setting, with the potential for future adaptation to different sample types and animals. Using our approach, we can identify the bacterial pathogen present within 5 h, in some cases detecting species which are difficult to culture. For urine samples, we can predict antibiotic sensitivity with up to 95 % accuracy. Skin swabs usually have lower bacterial abundance and higher host DNA, confounding antibiotic sensitivity prediction; an additional host depletion step will likely be required during the processing of these, and other types of samples with high levels of host cell contamination. In summary, our pipeline represents an important step towards the design of individually tailored veterinary treatment plans on the same day as presentation, facilitating the effective use of antibiotics and promoting better antimicrobial stewardship.

16S rRNA nanopore sequencing for rapid diagnosis of causative bacteria in bovine mastitis

The rapid identification of specific bacterial pathogens in bovine mastitis is crucial for appropriate antimicrobial treatment. Sequencing of 16S rRNA gene amplicons is a proven, useful strategy for diagnosing bacterial infections. In this study, the use of 16S rRNA analysis with nanopore sequencer for the rapid identification of causative bacteria in bovine mastitis, was evaluated. DNA was extracted from 122 milk samples from cattle with suspected mastitis based on clinical symptoms. 16S rRNA gene amplicon sequencing was conducted using a nanopore sequencer. The efficacy of bacterial identification was verified by comparison with conventional culture methods. Nanopore sequencing identified the causative bacteria with high accuracy within approximately 6 h from the time of sample collection. When the major causative bacteria of bovine mastitis (Escherichia coli, Streptcoccus uberis, Klebsiella pneumoniae, and Staphylococcus aureus) were detected by nanopore sequencing, 98.3% of the results were consistent with identification through conventional culturing methods. 16S rRNA gene analysis using a nanopore sequencer enabled the rapid and accurate identification of bacterial species in bovine mastitis.

Detection of Biological Molecules Using Nanopore Sensing Techniques

Modern biomedical sensing techniques have significantly increased in precision and accuracy due to new technologies that enable speed and that can be tailored to be highly specific for markers of a particular disease. Diagnosing early-stage conditions is paramount to treating serious diseases. Usually, in the early stages of the disease, the number of specific biomarkers is very low and sometimes difficult to detect using classical diagnostic methods. Among detection methods, biosensors are currently attracting significant interest in medicine, for advantages such as easy operation, speed, and portability, with additional benefits of low costs and repeated reliable results. Single-molecule sensors such as nanopores that can detect biomolecules at low concentrations have the potential to become clinically relevant. As such, several applications have been introduced in this field for the detection of blood markers, nucleic acids, or proteins. The use of nanopores has yet to reach maturity for standardization as diagnostic techniques, however, they promise enormous potential, as progress is made into stabilizing nanopore structures, enhancing chemistries, and improving data collection and bioinformatic analysis. This review offers a new perspective on current biomolecule sensing techniques, based on various types of nanopores, challenges, and approaches toward implementation in clinical settings.

Metagenomic next generation sequencing for studying antibiotic resistance genes in the environment

Bacterial antimicrobial resistance (AMR) is a persisting and growing threat to human health. Characterization of antibiotic resistance genes (ARGs) in the environment is important to understand and control ARG-associated microbial risks. Numerous challenges exist in monitoring ARGs in the environment, due to the extraordinary diversity of ARGs, low abundance of ARGs with respect to the complex environmental microbiomes, difficulties in linking ARGs with bacterial hosts by molecular methods, difficulties in achieving quantification and high throughput simultaneously, difficulties in assessing mobility potential of ARGs, and difficulties in determining the specific AMR determinant genes. Advances in the next generation sequencing (NGS) technologies and related computational and bioinformatic tools are facilitating rapid identification and characterization ARGs in genomes and metagenomes from environmental samples. This chapter discusses NGS-based strategies, including amplicon-based sequencing, whole genome sequencing, bacterial population-targeted metagenome sequencing, metagenomic NGS, quantitative metagenomic sequencing, and functional/phenotypic metagenomic sequencing. Current bioinformatic tools for analyzing sequencing data for studying environmental ARGs are also discussed.

Gut microbiome profiling of neonates using Nanopore MinION and Illumina MiSeq sequencing

This study aimed to evaluate the difference in gut microbiomes between preterm and term infants using third-generation long-read sequencing (Oxford Nanopore Technologies, ONT) compared with an established gold standard, Illumina (second-generation short-read sequencing). A total of 69 fecal samples from 51 term (T) and preterm (P) infants were collected at 7 and 28 days of life. Gut colonization profiling was performed by 16S rRNA gene sequencing using ONT. We used Illumina to validate and compare the patterns in 13 neonates. Using bioinformatic analysis, we identified features that differed between P and T. Both T1 and P1 microbiomes were dominated by Firmicutes (Staphylococcus and Enterococcus), whereas sequentially showed dominant transitions to Lactobacillus (p < 0.001) and Streptococcus in T2 (p = 0.001), and pathogenic bacteria (Klebsiella) in P2 (p = 0.001). The abundance of beneficial bacteria (Bifidobacterium and Lactobacillus) increased in T2 (p = 0.026 and p < 0.001, respectively). These assignments were correlated with the abundance at the species-level. Bacterial α-diversity increased in T (p = 0.005) but not in P (p = 0.156), and P2 showed distinct β-diversity clustering than T2 (p = 0.001). The ONT reliably identified pathogenic bacteria at the genus level, and taxonomic profiles were comparable to those identified by Illumina at the genus level. This study shows that ONT and Illumina are highly correlated. P and T had different microbiome profiles, and the α- and β-diversity varied. ONT sequencing has potential for pathogen detection in neonates in clinical settings.

Nanopore-Based Metagenomic Sequencing in Respiratory Tract Infection: A Developing Diagnostic Platform

Respiratory tract infection (RTI) remains a significant cause of morbidity and mortality across the globe. The optimal management of RTI relies upon timely pathogen identification via evaluation of respiratory samples, a process which utilises traditional culture-based methods to identify offending microorganisms. This process can be slow and often prolongs the use of broad-spectrum antimicrobial therapy, whilst also delaying the introduction of targeted therapy as a result. Nanopore sequencing (NPS) of respiratory samples has recently emerged as a potential diagnostic tool in RTI. NPS can identify pathogens and antimicrobial resistance profiles with greater speed and efficiency than traditional sputum culture-based methods. Increased speed to pathogen identification can improve antimicrobial stewardship by reducing the use of broad-spectrum antibiotic therapy, as well as improving overall clinical outcomes. This new technology is becoming more affordable and accessible, with some NPS platforms requiring minimal sample preparation and laboratory infrastructure. However, questions regarding clinical utility and how best to implement NPS technology within RTI diagnostic pathways remain unanswered. In this review, we introduce NPS as a technology and as a diagnostic tool in RTI in various settings, before discussing the advantages and limitations of NPS, and finally what the future might hold for NPS platforms in RTI diagnostics.

Novel and Efficient Method for Diagnosing Infective Endocarditis Using 16S Ribosomal RNA Gene Amplicon Sequence

We present 2 cases that both developed infective endocarditis and underwent mitral valve replacement. In addition to positive blood culture and echocardiographic findings, such as vegetation or mitral valve perforation, the 16S ribosomal RNA gene amplicon sequence approach used was helpful for disease diagnosis. (Level of Difficulty: Intermediate.).

Performance evaluation of whole genome metagenomics sequencing with the MinION nanopore sequencer: Microbial community analysis and antimicrobial resistance gene detection

Recently, the human gut microbiota has been implicated in various diseases such as immunological and neuropsychiatric disorders, and comprehensive gut microbiota analysis by metagenomic analysis using next-generation sequencers has been attracting attention. In this study, we compared microbial communities of 16S rDNA metagenome sequencing (16S-meta) and whole genome metagenome sequencing (WG-meta) using the nanopore sequencer MinION and 16S-meta using the Illumina Miseq sequencer with simulated and fecal samples, and evaluated the ability of WG-meta to detect antimicrobial resistance genes. We used the commercial Microbial Community DNA Standard as the DNA standard and a simulated sample comprising 17 strains of 15 bacterial species. In the detection of antimicrobial resistance genes, we used a simulated sample and spiked fecal samples containing Escherichia coli carrying bla_CTX-M-27, Klebsiella pneumoniae carrying bla_OXA-48, and Staphylococcus aureus carrying mecA. WG-meta using MinION was superior to 16S-meta and could accurately analyze the microbial communities at the species level, but it underestimated or misidentified the Bacillus subtilis group, Cryptococcus neoformans, Shigella sonnei, and Campylobacter jejuni. WG-meta using MinION could analyze the microbial communities in 5 min, and antimicrobial resistance gene detection using WG-meta could be performed in >30 min in the simulated sample with fewer bacterial counts.

Predictive Power of Long-Read Whole-Genome Sequencing for Rapid Diagnostics of Multidrug-Resistant Brachyspira hyodysenteriae Strains

Infections with Brachyspira hyodysenteriae, the etiological agent of swine dysentery, result in major economic losses in the pig industry worldwide. Even though microbial differentiation of various Brachyspira species can be obtained via PCR, no quick diagnostics for antimicrobial susceptibility testing are in place, which is mainly due to the time-consuming (4 to 7 days) anaerobic growth requirements of these organisms. Veterinarians often rely on a clinical diagnosis for initiating antimicrobial treatment. These treatments are not always effective, which may be due to high levels of acquired resistance in B. hyodysenteriae field isolates. By using long-read-only whole-genome sequencing and a custom-trained Bonito base-calling model, 81 complete B. hyodysenteriae genomes with median Q51 scores and 99% completeness were obtained from 86 field strains. This allowed the assessment of the predictive potential of genetic markers in relation to the observed acquired resistance phenotypes obtained via agar dilution susceptibility testing. Multidrug resistance was observed in 77% and 21% of the tested strains based on epidemiological cutoff and clinical breakpoint values, respectively. The predictive power of genetic hallmarks (genes and/or gene mutations) for antimicrobial susceptibility testing was promising. Sensitivity and specificity for tiamulin [tva(A) and 50SL3^N148S, 99% and 67%], valnemulin [tva(A), 97% and 92%), lincomycin (23S^A2153T/G and lnuC, 94% and 100%), tylvalosin (23S^A2153T/G, 99% and 93%), and doxycycline (16S^G1026C, 93% and 87%) were determined. The predictive power of these genetic hallmarks is promising for use in sequencing-based workflows to speed up swine dysentery diagnostics in veterinary medicine and determine proper antimicrobial use. IMPORTANCE Diagnostics for swine dysentery rely on the identification of Brachyspira species using molecular techniques. Nevertheless, no quick diagnostic tools are available for antimicrobial susceptibility testing due to extended growth requirements (7 to 14 days). To enable practitioners to tailor antimicrobial treatment to specific strains, long-read sequencing-based methods are expected to lead to rapid methods in the future. Nevertheless, their potential implementation should be validated extensively. This mainly implies assessing sequencing accuracy and the predictive power of genetic hallmarks in relation to their observed (multi)resistance phenotypes.

Development of an Amplicon Nanopore Sequencing Strategy for Detection of Mutations Conferring Intermediate Resistance to Vancomycin in Staphylococcus aureus Strains

Staphylococcus aureus is a major cause of bacteremia and other hospital-acquired infections. The cell-wall active antibiotic vancomycin is commonly used to treat both methicillin-resistant (MRSA) and sensitive (MSSA) infections. Vancomycin intermediate S. aureus (VISA) variants can arise through de novo mutations. Here, we performed pilot experiments to develop a combined PCR/long-read sequencing-based method for detection of previously known VISA-causing mutations. Primers were designed to generate 10 amplicons covering 16 genes associated with the VISA phenotype. We sequenced amplicon pools as long reads with Oxford Nanopore adapter ligation on Flongle flow cells. We then detected mutations by mapping reads against a parental consensus or known reference sequence and comparing called variants against a database of known VISA mutations from laboratory selection. Each amplicon in the pool was sequenced to high (>1,000×) coverage, and no relationship was found between amplicon length and coverage. We also were able to detect the causative mutation (walK 646C>G) in a VISA mutant derived from the USA300 strain (N384-3 from parental strain N384). Mixing mutant (N384-3) and parental (N384) DNA at various ratios from 0 to 1 mutant suggested a mutation detection threshold of the average minor allele frequency (6.5%) at 95% confidence (two standard errors above mean mutation frequency). The study lays the groundwork for direct S. aureus antibiotic resistance genotype inference using rapid nanopore sequencing from clinical samples. IMPORTANCE Bacteremia mortality is known to increase rapidly with time after infection, making rapid diagnostics and treatment necessary. Successful treatment depends on correct administration of antibiotics based on knowledge of strain antibiotic susceptibility. Staphylococcus aureus is a major causative agent of bacteremia that is also commonly antibiotic resistant. In this work, we develop a method to accelerate detection of a complex, polygenic antibiotic resistance phenotype in S. aureus, vancomycin-intermediate resistance (VISA), through long-read genomic sequencing of amplicons representing genes most commonly mutated in VISA selection. This method both rapidly identifies VISA genotypes and incorporates the most comprehensive database of VISA genetic determinants known to date.

Portable nanopore-sequencing technology: Trends in development and applications

Sequencing technology is the most commonly used technology in molecular biology research and an essential pillar for the development and applications of molecular biology. Since 1977, when the first generation of sequencing technology opened the door to interpreting the genetic code, sequencing technology has been developing for three generations. It has applications in all aspects of life and scientific research, such as disease diagnosis, drug target discovery, pathological research, species protection, and SARS-CoV-2 detection. However, the first- and second-generation sequencing technology relied on fluorescence detection systems and DNA polymerization enzyme systems, which increased the cost of sequencing technology and limited its scope of applications. The third-generation sequencing technology performs PCR-free and single-molecule sequencing, but it still depends on the fluorescence detection device. To break through these limitations, researchers have made arduous efforts to develop a new advanced portable sequencing technology represented by nanopore sequencing. Nanopore technology has the advantages of small size and convenient portability, independent of biochemical reagents, and direct reading using physical methods. This paper reviews the research and development process of nanopore sequencing technology (NST) from the laboratory to commercially viable tools; discusses the main types of nanopore sequencing technologies and their various applications in solving a wide range of real-world problems. In addition, the paper collates the analysis tools necessary for performing different processing tasks in nanopore sequencing. Finally, we highlight the challenges of NST and its future research and application directions.

Validation and Application of Long-Read Whole-Genome Sequencing for Antimicrobial Resistance Gene Detection and Antimicrobial Susceptibility Testing

Next-generation sequencing applications are increasingly used for detection and characterization of antimicrobial-resistant pathogens in clinical settings. Oxford Nanopore Technologies (ONT) sequencing offers advantages for clinical use compared with other sequencing methodologies because it enables real-time basecalling, produces long sequencing reads that increase the ability to correctly assemble DNA fragments, provides short turnaround times, and requires relatively uncomplicated sample preparation. A drawback of ONT sequencing, however, is its lower per-read accuracy than short-read sequencing. We sought to identify best practices in ONT sequencing protocols. As some variability in sequencing results may be introduced by the DNA extraction methodology, we tested three DNA extraction kits across three independent laboratories using a representative set of six bacterial isolates to investigate accuracy and reproducibility of ONT technology. All DNA extraction techniques showed comparable performance; however, the DNeasy PowerSoil Pro kit had the highest sequencing yield. This kit was subsequently applied to 42 sequentially collected bacterial isolates from blood cultures to assess Ares Genetics's pipelines for predictive whole-genome sequencing antimicrobial susceptibility testing (WGS-AST) performance compared to phenotypic triplicate broth microdilution results. WGS-AST results ranged across the organisms and resulted in an overall categorical agreement of 95% for penicillins, 82.4% for cephalosporins, 76.7% for carbapenems, 86.9% for fluoroquinolones, and 96.2% for aminoglycosides. Very major errors/major errors were 0%/16.7% (penicillins), 11.7%/3.6% (cephalosporins), 0%/24.4% (carbapenems), 2.5%/7.7% (fluoroquinolones), and 0%/4.1% (aminoglycosides), respectively. This work showed that, although additional refinements are necessary, ONT sequencing demonstrates potential as a method to perform WGS-AST on cultured isolates for patient care.

MAIRA: Protein-based Analysis of MinION Reads on a Laptop

Third-generation sequencing technologies are being increasingly used in microbiome research and this has given rise to new challenges in computational microbiome analysis. Oxford Nanopore's MinION is a portable sequencer that streams data that can be basecalled on-the-fly. Here we give an introduction to the MAIRA software, which is designed to analyze MinION sequencing reads from a microbiome sample, as they are produced in real-time, on a laptop. The software processes reads in batches and updates the presented analysis after each batch. There are two analysis steps: First, protein alignments are calculated to determine which genera might be present in a sample. When strong evidence for a genus is found, then, in a second step, a more detailed analysis is performed by aligning the reads against the proteins of all species in the detected genus. The program presents a detailed analysis of species, antibiotic resistance genes, and virulence factors.

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

Metagenomic sequencing analysis (mNGS) has been implemented as an alternative approach for pathogen diagnosis in recent years, which is independent of cultivation and is able to identify all potential antibiotic resistance genes (ARGs). However, current mNGS methods have to deal with low amounts of prokaryotic deoxyribonucleic acid (DNA) and high amounts of host DNA in clinical samples, which significantly decrease the overall microbial detection resolution. The recently released nanopore adaptive sampling (NAS) technology facilitates immediate mapping of individual nucleotides to a given reference as each molecule is sequenced. User-defined thresholds allow for the retention or rejection of specific molecules, informed by the real-time reference mapping results, as they are physically passing through a given sequencing nanopore. We developed a metagenomics workflow for ultra-sensitive diagnosis of bacterial pathogens and ARGs from clinical samples, which is based on the efficient selective 'human host depletion' NAS sequencing, real-time species identification and species-specific resistance gene prediction. Our method increased the microbial sequence yield at least 8-fold in all 21 sequenced clinical Bronchoalveolar Lavage Fluid (BALF) samples (4.5 h from sample to result) and accurately detected the ARGs at species level. The species-level positive percent agreement between metagenomic sequencing and laboratory culturing was 100% (16/16) and negative percent agreement was 100% (5/5) in our approach. Further work is required for a more robust validation of our approach with large sample size to allow its application to other infection types.

Deep Metagenomic Sequencing for Endophthalmitis Pathogen Detection Using a Nanopore Platform

PURPOSE

To evaluate the utility of nanopore sequencing for identifying potential causative pathogens in endophthalmitis, comparing culture results against full-length 16S rRNA nanopore sequencing (16S Nanopore), whole genome nanopore sequencing (Nanopore WGS), and Illumina (Illumina WGS).

DESIGN

Cross-sectional diagnostic comparison.

METHODS

Patients with clinically suspected endophthalmitis underwent intraocular vitreous biopsy as per standard care. Clinical samples were cultured by conventional methods, together with full-length 16S rRNA and WGS using nanopore and Illumina sequencing platforms.

RESULTS

Of 23 patients (median age 68.5 years [range 47-88]; 14 males [61%]), 18 cases were culture-positive. Nanopore sequencing identified the same cultured organism in all of the culture-positive cases and identified potential pathogens in two culture-negative cases (40%). Nanopore WGS was able to additionally detect the presence of bacteriophages in three samples. The agreements at genus level between culture and 16S Nanopore, Nanopore WGS, and Illumina WGS were 75%, 100%, and 78%, respectively.

CONCLUSIONS

Whole genome sequencing has higher sensitivity and provides a viable alternative to culture and 16S sequencing for detecting potential pathogens in endophthalmitis. Moreover, WGS has the ability to detect other potential pathogens in culture-negative cases. Whilst Nanopore and Illumina WGS provide comparable data, nanopore sequencing provides potential for cost-effective point-of-care diagnostics.

Research on safety and compliance of imported microbial inoculants using high-throughput sequencing

Microbial inoculants are widely used in wastewater treatment, soil remediation, and biological control. Safety and compliance for active constituents are considered to be the most important measures of imported microbial inoculants. Microbial inoculants composition was commonly identified by phenotypic culture, which is time-consuming and labor intense with occasionally false negative results provided, and can only be tested for specific species. High-throughput sequencing (HTS), known for its non-targeted detection of unknown species composition in samples, is suitable for composition consistency identification and biosafety analysis of imported microbial inoculants. In this study, the application of HTS for microflora distribution and resistance gene was verified in microbial inoculants for environmental protection and then applicated in imported microbial inoculants. Both Illumina- and Nanopore-based HTS methods identified the same dominant bacterial species successfully in the imported microbial inoculants. The main component of bacterial species was Bacillus subtilis, Bacillus amyloliquefaciens, Bacillus licheniformis, and Enterococcus faecium, and further confirmed with traditional methods. The antibiotic resistance genes Bacillus subtilis mprF, bcrA, blt, lmrB, rphB, tet(L), tmrB, vmlR, ykkC, and ykkD were detected in all samples. Our results indicated that HTS processes the application potential to identify the active ingredients of microbial inoculants. Therefore, rapid and accurate identification of the microbial compositions in microbial formulation products is of high importance for port biosafety supervision.

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.

Antibiotic resistance in plant growth promoting bacteria: A comprehensive review and future perspectives to mitigate potential gene invasion risks

Plant growth-promoting bacteria (PGPB) are endowed with several attributes that can be beneficial for host plants. They opened myriad doors toward green technology approach to reduce the use of chemical inputs, improve soil fertility, and promote plants' health. However, many of these PGPB harbor antibiotic resistance genes (ARGs). Less attention has been given to multi-resistant bacterial bioinoculants which may transfer their ARGs to native soil microbial communities and other environmental reservoirs including animals, waters, and humans. Therefore, large-scale inoculation of crops by ARGs-harboring bacteria could worsen the evolution and dissemination of antibiotic resistance and aggravate the negative impacts on such ecosystem and ultimately public health. Their introduction into the soil could serve as ARGs invasion which may inter into the food chain. In this review, we underscore the antibiotic resistance of plant-associated bacteria, criticize the lack of consideration for this phenomenon in the screening and application processes, and provide some recommendations as well as a regulation framework relating to the development of bacteria-based biofertilizers to aid maximizing their value and applications in crop improvement while reducing the risks of ARGs invasion.

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.

Automated antimicrobial susceptibility testing and antimicrobial resistance genotyping using Illumina and Oxford Nanopore Technologies sequencing data among Enterobacteriaceae

Whole-genome sequencing (WGS) enables the molecular characterization of bacterial pathogens. We compared the accuracy of the Illumina and Oxford Nanopore Technologies (ONT) sequencing platforms for the determination of AMR classes and antimicrobial susceptibility testing (AST) among 181 clinical Enterobacteriaceae isolates. Sequencing reads for each isolate were uploaded to AREScloud (Ares Genetics) to determine the presence of AMR markers and the predicted WGS-AST profile. The profiles of both sequencing platforms were compared to broth microdilution (BMD) AST. Isolates were delineated by resistance to third-generation cephalosporins and carbapenems as well as the presence of AMR markers to determine clinically relevant AMR classes. The overall categorical agreement (CA) was 90% (Illumina) and 88% (ONT) across all antimicrobials, 96% for the prediction of resistance to third-generation cephalosporins for both platforms, and 94% (Illumina) and 91% (ONT) for the prediction of resistance to carbapenems. Carbapenem resistance was overestimated on ONT with a major error of 16%. Sensitivity for the detection of carbapenemases, extended-spectrum β-lactamases, and plasmid-mediated ampC genes was 98, 95, and 70% by ONT compared to the Illumina dataset as the reference. Our results highlight the potential of the ONT platform's use in clinical microbiology laboratories. When combined with robust bioinformatics methods, WGS-AST predictions may be a future approach to guide effective antimicrobial decision-making.

Rapid Detection of Beta-Lactamases Genes among Enterobacterales in Urine Samples by Using Real-Time PCR

The objective of this study was to develop and evaluate newly improved, rapid, and reliable strategies based on real-time PCR to detect the most frequent beta-lactamase genes recorded in clinical Enterobacterales strains, particularly in Tunisia (bla_SHV12, bla_TEM, bla_CTX-M-15, bla_CTX-M-9, bla_CMY-2, bla_OXA-48, bla_NDM-1, and bla_IMP) directly from the urine. Following the design of primers for a specific gene pool and their validation, a series of real-time PCR reactions were performed to detect these genes in 78 urine samples showing high antibiotic resistance after culture and susceptibility testing. Assays were applied to DNA extracted from cultured bacteria and collected urine. qPCR results were compared for phenotypic sensitivity. qPCR results were similar regardless of whether cultures or urine were collected, with 100% sensitivity and specificity. Out of 78 multiresistant uropathogenic, strains of Enterobacterales (44 E. coli and 34 K. pneumoniae strains) show the presence of the genes of the bla group. In all, 44% E. coli and 36 of K. pneumoniae clinical strains harbored the bla group genes with 36.4%, 52.3%, 70.5%, 68.2%, 18.2%, and 4.5% of E. coli having bla_SHV-12, bla_TEM, bla_{CTX-M 15}, bla_CTX-M-9, bla_CMY-2, and bla_OXA-48 group genes, respectively, whereas 52.9%, 67.6%, 76.5%, 35.5%, 61.8, 14.7, and 1.28% of K. pneumoniae had bla_SHV-12, bla_TEM, bla_{CTX-M 15}, bla_CTX-M-9, bla_CMY-2, bla_OXA-48, and bla_NDM-1 group genes, respectively. The time required to have a result was 3 hours by real-time PCR and 2 to 3 days by the conventional method. Resistance genes of Gram-negative bacteria in urine, as well as cultured bacteria, were rapidly detected using qPCR techniques. These techniques will be used as rapid and cost-effective methods in the laboratory. Therefore, this test could be a good candidate to create real-time PCR kits for the detection of resistance genes directly from urine in clinical or epidemiological settings.

Comparison Analysis of Different DNA Extraction Methods on Suitability for Long-Read Metagenomic Nanopore Sequencing

Metagenomic next-generation sequencing (mNGS) is a novel useful strategy that is increasingly used for pathogens detection in clinic. Some emerging mNGS technologies with long-read ability are useful to decrease sequencing time and increase diagnosed accuracy, which is of great significance in rapid pathogen diagnosis. Reliable DNA extraction is considered critical for the success of sequencing; hence, there is thus an urgent need of gentle DNA extraction method to get unbiased and more integrate DNA from all kinds of pathogens. In this study, we systematically compared three DNA extraction methods (enzymatic cell lysis based on MetaPolyzyme, mechanical cell lysis based on bead beating, and the control method without pre-cell lysis, respectively) by assessing DNA yield, integrity, and the microbial diversity based on long-read nanopore sequencing of urine samples with microbial infections. Compared with the control method, the enzymatic-based method increased the average length of microbial reads by a median of 2.1-fold [Inter Quartile Range (IQR), 1.7-2.5; maximum, 4.8) in 18 of the 20 samples and the mapped reads proportion of specific species by a median of 11.8-fold (Inter Quartile Range (IQR), 6.9-32.2; maximum, 79.27]. Moreover, it provided fully (20 of 20) consistent diagnosed results to the clinical culture and more representative microbial profiles (P < 0.05), which all strongly proves the excellent performance of enzymatic-based method in long-read mNGS-based pathogen identification and potential diseases diagnosis of microbiome related.