Enhanced DNA and RNA pathogen detection via metagenomic sequencing in patients with pneumonia

Unified metagenomic method for rapid detection of microorganisms in clinical samples

BACKGROUND

Clinical metagenomics involves the genomic sequencing of all microorganisms in clinical samples ideally after depletion of human DNA to increase sensitivity and reduce turnaround times. Current human DNA depletion methods preferentially preserve either DNA or RNA containing microbes, but not both simultaneously. Here we describe and present data using a practical and rapid mechanical host-depletion method allowing simultaneous detection of RNA and DNA microorganisms linked with nanopore sequencing.

METHODS

The human cells from respiratory samples are lysed mechanically using 1.4 mm zirconium-silicate spheres and the human DNA is depleted using a nonspecific endonuclease. The RNA is converted to dsDNA to allow the simultaneous sequencing of DNA and RNA.

RESULTS

The method decreases human DNA concentration by a median of eight Ct values while detecting a broad range of RNA & DNA viruses, bacteria, including atypical pathogens (Legionella, Chlamydia, Mycoplasma) and fungi (Candida, Pneumocystis, Aspergillus). The first automated reports are generated after 30 min sequencing from a 7 h end-to-end workflow. Sensitivity and specificity for bacterial detection are 90% and 100%, respectively, and viral detection are 92% and 100% after 2 h of sequencing. Prospective validation on 33 consecutive lower respiratory tract samples from ventilated patients with suspected pneumonia shows 60% concordance with routine testing, detection of additional pathogens in 21% of samples and pathogen genomic assembly achieve for 42% of viruses and 33% of bacteria.

CONCLUSIONS

Although further workflow refinement and validation on samples containing a broader range of pathogens is required, it holds promise as a clinically deployable workflow suitable for evaluation in routine microbiology laboratories.

Metagenomic next-generation sequencing for diagnosing severe leptospirosis in a patient suspected COVID-19: A case report

Leptospirosis is a zoonotic and neglected waterborne disease caused by the pathogenic helical spirochetes. Early diagnosis of leptospirosis remains challenging due to non-specific symptoms and the limited availability of rapid point-of-care diagnostic tests. Herein, we present a case where a patient suspected of having COVID-19 was diagnosed with leptospirosis using metagenomic next-generation sequencing (mNGS). This case highlights the potential of mNGS to diagnose leptospirosis in the context of the COVID-19 pandemic.

A single-center, retrospective study of hospitalized patients with lower respiratory tract infections: clinical assessment of metagenomic next-generation sequencing and identification of risk factors in patients

INTRODUCTION

Lower respiratory tract infections(LRTIs) in adults are complicated by diverse pathogens that challenge traditional detection methods, which are often slow and insensitive. Metagenomic next-generation sequencing (mNGS) offers a comprehensive, high-throughput, and unbiased approach to pathogen identification. This retrospective study evaluates the diagnostic efficacy of mNGS compared to conventional microbiological testing (CMT) in LRTIs, aiming to enhance detection accuracy and enable early clinical prediction.

METHODS

In our retrospective single-center analysis, 451 patients with suspected LRTIs underwent mNGS testing from July 2020 to July 2023. We assessed the pathogen spectrum and compared the diagnostic efficacy of mNGS to CMT, with clinical comprehensive diagnosis serving as the reference standard. The study analyzed mNGS performance in lung tissue biopsies and bronchoalveolar lavage fluid (BALF) from cases suspected of lung infection. Patients were stratified into two groups based on clinical outcomes (improvement or mortality), and we compared clinical data and conventional laboratory indices between groups. A predictive model and nomogram for the prognosis of LRTIs were constructed using univariate followed by multivariate logistic regression, with model predictive accuracy evaluated by the area under the ROC curve (AUC).

RESULTS

(1) Comparative Analysis of mNGS versus CMT: In a comprehensive analysis of 510 specimens, where 59 cases were concurrently collected from lung tissue biopsies and BALF, the study highlights the diagnostic superiority of mNGS over CMT. Specifically, mNGS demonstrated significantly higher sensitivity and specificity in BALF samples (82.86% vs. 44.42% and 52.00% vs. 21.05%, respectively, p < 0.001) alongside greater positive and negative predictive values (96.71% vs. 79.55% and 15.12% vs. 5.19%, respectively, p < 0.01). Additionally, when comparing simultaneous testing of lung tissue biopsies and BALF, mNGS showed enhanced sensitivity in BALF (84.21% vs. 57.41%), whereas lung tissues offered higher specificity (80.00% vs. 50.00%). (2) Analysis of Infectious Species in Patients from This Study: The study also notes a concerning incidence of lung abscesses and identifies Epstein-Barr virus (EBV), Fusobacterium nucleatum, Mycoplasma pneumoniae, Chlamydia psittaci, and Haemophilus influenzae as the most common pathogens, with Klebsiella pneumoniae emerging as the predominant bacterial culprit. Among herpes viruses, EBV and herpes virus 7 (HHV-7) were most frequently detected, with HHV-7 more prevalent in immunocompromised individuals. (3) Risk Factors for Adverse Prognosis and a Mortality Risk Prediction Model in Patients with LRTIs: We identified key risk factors for poor prognosis in lower respiratory tract infection patients, with significant findings including delayed time to mNGS testing, low lymphocyte percentage, presence of chronic lung disease, multiple comorbidities, false-negative CMT results, and positive herpesvirus affecting patient outcomes. We also developed a nomogram model with good consistency and high accuracy (AUC of 0.825) for predicting mortality risk in these patients, offering a valuable clinical tool for assessing prognosis.

CONCLUSION

The study underscores mNGS as a superior tool for lower respiratory tract infection diagnosis, exhibiting higher sensitivity and specificity than traditional methods.

Association between Clinical Characteristics and Microbiota in Bronchiectasis Patients Based on Metagenomic Next-Generation Sequencing Technology

This study aimed to investigate the disparities between metagenomic next-generation sequencing (mNGS) and conventional culture results in patients with bronchiectasis. Additionally, we sought to investigate the correlation between the clinical characteristics of patients and their microbiome profiles. The overarching goal was to enhance the effective management and treatment of bronchiectasis patients, providing a theoretical foundation for healthcare professionals. A retrospective survey was conducted on 67 bronchiectasis patients admitted to The First Hospital of Jiaxing from October 2019 to March 2023. Clinical baseline information, inflammatory indicators, and pathogen detection reports, including mNGS, conventional blood culture, bronchoalveolar lavage fluid (BALF) culture, and sputum culture results, were collected. By comparing the results of mNGS and conventional culture, the differences in pathogen detection rate and pathogen types were explored, and the diagnostic performance of mNGS compared to conventional culture was evaluated. Based on the various pathogens detected by mNGS, the association between clinical characteristics of bronchiectasis patients and mNGS microbiota results was analyzed. The number and types of pathogens detected by mNGS were significantly larger than those detected by conventional culture. The diagnostic efficacy of mNGS was significantly superior to conventional culture for all types of pathogens, particularly in viral detection (p < 0.01). Regarding pathogen detection rate, the bacteria with the highest detection rate were Pseudomonas aeruginosa (17/58) and Haemophilus influenzae (11/58); the fungus with the highest detection rate was Aspergillus fumigatus (10/21), and the virus with the highest detection rate was human herpes virus 4 (4/11). Differences were observed between the positive and negative groups for P. aeruginosa in terms of common scoring systems for bronchiectasis and whether the main symptom of bronchiectasis manifested as thick sputum (p < 0.05). Significant distinctions were also noted between the positive and negative groups for A. fumigatus regarding Reiff score, neutrophil percentage, bronchiectasis etiology, and alterations in treatment plans following mNGS results reporting (p < 0.05). Notably, 70% of patients with positive A. fumigatus infection opted to change their treatment plans. The correlation study between clinical characteristics of bronchiectasis patients and mNGS microbiological results revealed that bacteria, such as P. aeruginosa, and fungi, such as A. fumigatus, were associated with specific clinical features of patients. This underscored the significance of mNGS in guiding personalized treatment approaches. mNGS could identify multiple pathogens in different types of bronchiectasis samples and was a rapid and effective diagnostic tool for pathogen identification. Its use was recommended for diagnosing the causes of infections in bronchiectasis patients.

Clinical application of amplification-based versus amplification-free metagenomic next-generation sequencing test in infectious diseases

Background

Recently, metagenomic next-generation sequencing (mNGS) has been used in the diagnosis of infectious diseases (IDs) as an emerging and powerful tool. However, whether the complicated methodological variation in mNGS detections makes a difference in their clinical performance is still unknown. Here we conducted a method study on the clinical application of mNGS tests in the DNA detection of IDs.

Methods

We analyzed the effect of several potential factors in the whole process of mNGS for DNA detection on microorganism identification in 98 samples of suspected ID patients by amplification-based mNGS. The amplification-based and amplification-free mNGS tests were successfully performed in 41 samples. Then we compared the clinical application of the two mNGS methods in the DNA detection of IDs.

Results

We found that a higher concentration of extracted nucleic acid was more conducive to detecting microorganisms. Other potential factors, such as read depth and proportion of human reads, might not be attributed to microorganism identification. The concordance rate of amplification-based and amplification-free mNGS results was 80.5% (33/41) in the patients with suspected IDs. Amplification-based mNGS showed approximately 16.7% higher sensitivity than amplification-free mNGS. However, 4 cases with causative pathogens only detected by amplification-based mNGS were finally proved false-positive. In addition, empirical antibiotic treatments were adjusted in 18 patients following mNGS testing with unexpected pathogens.

Conclusions

Amplification-based and amplification-free mNGS tests showed their specific advantages and disadvantages in the diagnosis of IDs. The clinical application of mNGS still needs more exploration from a methodological perspective. With advanced technology and standardized procedure, mNGS will play a promising role in the diagnosis of IDs and help guide the use of antibiotics.

Diagnostic value of plasma and blood cells metagenomic next-generation sequencing in patients with sepsis

BACKGROUND

Several studies have investigated the detection of plasma cell-free DNA (cfDNA) using metagenomic next-generation sequencing (mNGS). However, to our knowledge, no study has evaluated the diagnostic value of mNGS detection using blood cells. In this study, we aimed to evaluate the performance of a whole blood mNGS assay which includes the results of plasma and blood cells mNGS detection.

METHODS

We selected a panel of seven microorganisms to validate both the plasma and blood cells assay for their limits of detection (LoD), linearity, precision, and robustness to interference. In a multicentered prospective study conducted from January 2021 to April 2022, we tested 253 septic patients with plasma and blood cells mNGS and compared it with blood cultures (BCs). The performance of pathogen detection was compared between mNGS and BCs.

RESULTS

The LoD for plasma and blood cells mNGS was 8.3-140 genome equivalents (GE)/mL and 26 to 534 colony-forming units (CFU) or copies/mL, respectively. The inter- and intra-assay reproducibility of both plasma and blood cells mNGS was 100%. Compared to plasma mNGS alone, the sensitivity of whole blood mNGS was increased by 18.04% when using BCs as the standard (67.21% vs 85.25%). Furthermore, the sensitivity of whole blood mNGS in diagnosing bloodstream infections (BSIs) was 85.21%, which was significantly higher than that of BCs (36.09%, P＜0.0001) and plasma mNGS (69.82%; P = 0.0007). Additional analysis showed that blood cells mNGS was able to detect bacteria missed by plasma mNGS, while plasma mNGS was effective at detecting viruses.

CONCLUSIONS

Our findings indicate that whole blood mNGS shows great potential as a promising diagnostic technique for BSIs owing to its ability to identify pathogens with higher sensitivity.

Saponin treatment for eukaryotic DNA depletion alters the microbial DNA profiles by reducing the abundance of Gram-negative bacteria in metagenomics analyses

Background: Recent advances in microbiome sequencing techniques have provided new insights into the role of the microbiome on human health with potential diagnostic implications. However, these developments are often hampered by the presence of a large amount of human DNA interfering with the analysis of the bacterial content. Nowadays, extensive scientific literature focuses on eukaryotic DNA depletion methods, which successfully remove host DNA in microbiome studies, even if a precise assessment of the impact on bacterial DNA is often missing. Methods: Here, we have investigated a saponin-based DNA isolation protocol commonly applied to different biological matrices to deplete the released host DNA. Results: The bacterial DNA obtained was used to assess the relative abundance of bacterial and human DNA, revealing that the inclusion of 2.5% wt/vol saponin allowed the depletion of most of the host's DNA in favor of bacterial DNA enrichment. However, shotgun metagenomic sequencing showed inaccurate microbial profiles of the DNA samples, highlighting an erroneous increase in Gram-positive DNA. Even the application of 0.0125% wt/vol saponin altered the bacterial profile by depleting Gram-negative bacteria, resulting in an overall increase of Gram-positive bacterial DNA. Conclusion: The application of the saponin-based protocol drastically changes the detection of the microbial composition of human-related biological specimens. In this context, we revealed that saponin targets not only host cells but also specific bacterial cells, thus inducing a drastic reduction in the profiling of Gram-negative bacterial DNA.

Clinical Efficiency of Metagenomic Next-Generation Sequencing in Sputum for Pathogen Detection of Patients with Pneumonia According to Disease Severity and Host Immune Status

Purpose

Severe pneumonia causes the highest mortality rate in immunocompromised patients. This study aimed to investigate the pathogen diagnostic efficacy of metagenomic next-generation sequencing (mNGS) using sputum sample in patients with pneumonia according to patients' disease severity and immune conditions.

Patients and Methods

A total of 180 patients suffering from pneumonia were recruited, and sputum samples were collected in duplicate for pathogen detection by both conventional microbiological tests (CMT) and mNGS. Then, the performance of pathogen identification was examined between two methods, according to disease severity and patients' immune status.

Results

In comparison to CMT, mNGS had higher positivity rates in all patients with pneumonia (85.0% vs 62.2%, P=9.445e-07). The most commonly detected microorganism in sputum of pneumonia patients was Acinetobacter baumannii (42/180, 23.3%) in bacterum level, Candida albicans in fungus level (44/180, 24.4%), and Human herpesvirus 1 (39/180, 27.5%) in virus level. However, for mNGS results, Candida albicans in 34.9% of positive patients, and Human herpesvirus 1 in 7.7% of positive cases were confirmed as pathogens causing pneumonia. Acinetobacter baumannii detected by mNGS in 75% of positive patients was diagnosed as pathogen of pneumonia. The microorganism profile of sputum mNGS differed according to disease severity and immune status of patients. Pneumocystis jirovecii was more likely to infect immunocompromised patients (P=0.002). Pseudomonas aeruginosa (14.8% vs 0.0%, P=0.008) and Human herpesvirus 1 (26.1% vs 5.3%, P=0.004) had higher infection rate in patients with severe pneumonia compared with non-severe cases. mNGS had overwhelming advantages over CMT in detecting a lot of microorganisms including Streptococcus pneumoniae, Enterococcus faecium, Pneumocystis jirovecii, and majority of viruses.

Conclusion

mNGS is a complementary tool of CMT for detecting suspected pathogens for patients with lower respiratory infections. The interpretation of opportunistic pathogens identified by mNGS is challenging, and needs comprehensive consideration of sequencing data and clinical factors.

Utilizing metagenomic next-generation sequencing for diagnosis and lung microbiome probing of pediatric pneumonia through bronchoalveolar lavage fluid in pediatric intensive care unit: results from a large real-world cohort

Background

Metagenomic next-generation sequencing (mNGS) is a powerful method for pathogen detection in various infections. In this study, we assessed the value of mNGS in the pathogen diagnosis and microbiome analysis of pneumonia in pediatric intensive care units (PICU) using bronchoalveolar lavage fluid (BALF) samples.

Methods

A total of 104 pediatric patients with pneumonia who were admitted into PICU between June 2018 and February 2020 were retrospectively enrolled. Among them, 101 subjects who had intact clinical information were subject to parallel comparison of mNGS and conventional microbiological tests (CMTs) for pathogen detection. The performance was also evaluated and compared between BALF-mNGS and BALF-culture methods. Moreover, the diversity and structure of all 104 patients' lung BALF microbiomes were explored using the mNGS data.

Results

Combining the findings of mNGS and CMTs, 94.06% (95/101) pneumonia cases showed evidence of causative pathogenic infections, including 79.21% (80/101) mixed and 14.85% (15/101) single infections. Regarding the pathogenesis of pneumonia in the PICU, the fungal detection rates were significantly higher in patients with immunodeficiency (55.56% vs. 25.30%, P =0.025) and comorbidities (40.30% vs. 11.76%, P=0.007). There were no significant differences in the α-diversity either between patients with CAP and HAP or between patients with and without immunodeficiency. Regarding the diagnostic performance, the detection rate of DNA-based BALF-mNGS was slightly higher than that of the BALF-culture although statistically insignificant (81.82% vs.77.92%, P=0.677) and was comparable to CMTs (81.82% vs. 89.61%, P=0.211). The overall sensitivity of DNA-based mNGS was 85.14% (95% confidence interval [CI]: 74.96%-92.34%). The detection rate of RNA-based BALF-mNGS was the same with CMTs (80.00% vs 80.00%, P>0.999) and higher than BALF-culture (80.00% vs 52.00%, P=0.045), with a sensitivity of 90.91% (95%CI: 70.84%-98.88%).

Conclusions

mNGS is valuable in the etiological diagnosis of pneumonia, especially in fungal infections, and can reveal pulmonary microecological characteristics. For pneumonia patients in PICU, the mNGS should be implemented early and complementary to CMTs.

Iridium(III) solvent complex-based electrogenerated chemiluminescence and photoluminescence sensor array for the discrimination of bases in oligonucleotides

Development of rapid and sensitive method for the discrimination of bases in oligonucleotides is of great importance in clinical diagnosis. Here, we demonstrate the first case of single iridium(III) solvent complex-based electrogenerated chemiluminescence (ECL) and photoluminescence (PL) sensor array for the discrimination of bases in oligonucleotides. One iridium (III) solvent complex ([Ir(ppy)₂(DMSO)Cl], ppy = 2-phenylpyridine, probe 1) was designed as both ECL and PL probe while five bases (guanine, adenine, cytosine, thymine and uracil) were chosen as analytes. Two-element sensor array was built for the discrimination of five bases based on the fingerprint response of probe 1 to bases via coordination interactions. The combination of unique ECL and PL variations with principal component analysis was applied for the quantitative analysis of five bases in a linear range of 1.0 μM-10 μM and for the effective discrimination of individual base, the mixture of bases and oligonucleotides. Moreover, the sensor array was successfully applied to discriminate different mismatched ss-DNAs from HIV gene (a fully-matched ss-DNA), even at single-base difference. This work demonstrates that the sensor array using single iridium (III) solvent complex is a promising approach for the discrimination of bases with good sensitivity and simpleness in clinical diagnosis.

Deciphering Microbiota of Acute Upper Respiratory Infections: A Comparative Analysis of PCR and mNGS Methods for Lower Respiratory Trafficking Potential

Although it is clinically important for acute respiratory tract (co)infections to have a rapid and accurate diagnosis, it is critical that respiratory medicine understands the advantages of current laboratory methods. In this study, we tested nasopharyngeal samples (n = 29) with a commercially available PCR assay and compared the results with those of a hybridization-capture-based mNGS workflow. Detection criteria for positive PCR samples was Ct < 35 and for mNGS samples it was >40% target coverage, median depth of 1X and RPKM > 10. A high degree of concordance (98.33% PPA and 100% NPA) was recorded. However, mNGS yielded positively 29 additional microorganisms (23 bacteria, 4 viruses, and 2 fungi) beyond PCR. We then characterized the microorganisms of each method into three phenotypic categories using the IDbyDNA Explify^® Platform (Illumina^® Inc, San Diego, CA, USA) for consideration of infectivity and trafficking potential to the lower respiratory region. The findings are significant for providing a comprehensive yet clinically relevant microbiology profile of acute upper respiratory infection, especially important in immunocompromised or immunocompetent with comorbidity respiratory cases or where traditional syndromic approaches fail to identify pathogenicity. Accordingly, this technology can be used to supplement current syndrome-based tests, and data can quickly and effectively be phenotypically characterized for trafficking potential, clinical (co)infection, and comorbid consideration-with promise to reduce morbidity and mortality.

Prevention and treatment of ventilator-associated pneumonia in COVID-19

Ventilator-associated pneumonia (VAP) is the most common acquired infection in the intensive care unit. Recent studies showed that the critical COVID-19 patients with invasive mechanical ventilation have a high risk of developing VAP, which result in a worse outcome and an increasing economic burden. With the development of critical care medicine, the morbidity and mortality of VAP remains high. Especially since the outbreak of COVID-19, the healthcare system is facing unprecedented challenges. Therefore, many efforts have been made in effective prevention, early diagnosis, and early treatment of VAP. This review focuses on the treatment and prevention drugs of VAP in COVID-19 patients. In general, prevention is more important than treatment for VAP. Prevention of VAP is based on minimizing exposure to mechanical ventilation and encouraging early release. There is little difference in drug prophylaxis from non-COVID-19. In term of treatment of VAP, empirical antibiotics is the main treatment, special attention should be paid to the antimicrobial spectrum and duration of antibiotics because of the existence of drug-resistant bacteria. Further studies with well-designed and large sample size were needed to demonstrate the prevention and treatment of ventilator-associated pneumonia in COVID-19 based on the specificity of COVID-19.

Combination of Whole Genome Sequencing and Metagenomics for Microbiological Diagnostics

Whole genome sequencing (WGS) provides the highest resolution for genome-based species identification and can provide insight into the antimicrobial resistance and virulence potential of a single microbiological isolate during the diagnostic process. In contrast, metagenomic sequencing allows the analysis of DNA segments from multiple microorganisms within a community, either using an amplicon- or shotgun-based approach. However, WGS and shotgun metagenomic data are rarely combined, although such an approach may generate additive or synergistic information, critical for, e.g., patient management, infection control, and pathogen surveillance. To produce a combined workflow with actionable outputs, we need to understand the pre-to-post analytical process of both technologies. This will require specific databases storing interlinked sequencing and metadata, and also involves customized bioinformatic analytical pipelines. This review article will provide an overview of the critical steps and potential clinical application of combining WGS and metagenomics together for microbiological diagnosis.