Application of metagenomic next-generation sequencing in the diagnosis of pulmonary invasive fungal disease

Diagnostic value of metagenomic next-generation sequencing in patients with osteoarticular infections: a prospective study

Due to the limits of traditional microbiological methods and the complexity of osteoarthritis pathogens, only a few pathogens can be detected. We evaluated metagenomic next-generation sequencing (mNGS) for detecting pathogens in osteoarthritis infection samples. We prospectively included 150 patients with osteoarthritis infection who visited the Orthopedics Department of Shandong Provincial Public Health Center from 2023 to 2024, including 124 cases of primary osteoarthritis (POI) and 26 cases of invasive osteoarthritis (IOI). The most common pathogenic bacteria were Mycobacterium tuberculosis complex, Staphylococcus aureus, and Brucella melitensis. mNGS (75.33%) significantly improved the detection of pathogens in osteoarticular infections compared to conventional tests (CT) methods (36.67%). mNGS could detect a wider spectrum of pathogens compared to CT methods, especially for mixed and rare pathogens. The treatment strategies for patients with osteoarthritis infection could be adjusted based on the results obtained from mNGS testing. Furthermore, the abundance of M. tuberculosis complex, B. melitensis, and Staphylococcus epidermidis was significantly correlated with clinical indicators.IMPORTANCEIdentifying the microorganisms responsible for osteoarthritis infection could help with early diagnosis and treatment. In this study, we compared the pathogen detection rate of metagenomic next-generation sequencing (mNGS) and CT methods in patients with osteoarthritis infection and found that mNGS had a higher microbial detection rate and a broader spectrum of pathogens (especially for mixed pathogens). This study demonstrates that mNGS is an ideal tool for detecting pathogens in patients with osteoarticular infections.

New Diagnostics for Fungal Infections in Transplant Infectious Disease: A Systematic Review

Fungal infections are common in highly immunosuppressed, solid organ transplant recipients. They can be quite difficult to diagnose in a timely manner; thus, we present a review of current studies focusing on broad categories of molecular diagnostics, i.e., metagenomic sequencing, magnetic resonance, and gas chromatography mass spectrometry. We further discuss their syndrome-specific utilization in the diagnosis of fungemia and disseminated disease, pneumonia, and central nervous system infections. We assess the level of evidence of their utility as fungal diagnostics particularly in solid organ transplant recipients using the STARD criteria. In addition, we provide future research directions to substantiate and appropriately utilize these platforms in clinical practice. Directed polymerase chain reaction testing and targeted metagenomic sequencing are being used clinically and show the most promise, though only in conjunction with conventional methods at this time. The majority of these platforms contain limited data, and thus further larger studies are needed in order to properly implement their use.

Diagnosis and management of invasive fungal diseases by next-generation sequencing: are we there yet?

INTRODUCTION

Invasive fungal diseases (IFDs) are a serious threat to immunocompromised patients. Routine diagnostic methods have limited performance in identifying IFDs. Next-generation sequencing (NGS), including metagenomic NGS (mNGS) and whole-genome sequencing (WGS), recently emerged as diagnostic methods that could provide more accurate and timely diagnoses and management of IFDs.

AREAS COVERED

This article describes the emergence of NGS as a diagnostic tool to address the limitations of current tests. The literature regarding its application and clinical utility in the diagnosis of IFDs is reviewed. Practical considerations, challenges, and opportunities as they relate to the development and implementation of mNGS and WGS for fungal pathogens are discussed.

EXPERT OPINION

NGS emerged over a decade ago with the potential to solve many of the challenges in diagnosing infectious diseases, including IFDs. However, published literature has yielded conflicting data about its clinical utility. The increased clinical adoption of NGS is improving our understanding of how to interpret and use its results to guide actionable decisions. Still, several gaps remain. As the cost, effort, and expertise involved in performing NGS decrease and the reporting of its results becomes standardized, NGS is poised to fill current gaps in the diagnosis of IFDs.

Study on the application of microfluidic-based in vitro diagnostic technology in pathogenic detection of respiratory tract infections

OBJECTIVE

To investigate the clinical application value of microfluidic-based in vitro diagnostic (IVD) technology in pathogenic detection of respiratory tract infections.

METHODS

A total of 300 clinical samples, including blood, bronchoalveolar lavage fluid, and pleural effusion, were collected from patients with respiratory tract infections. The samples were randomly divided into three groups: A, B, and C, with 100 cases in each group. Group A used traditional microbiological detection methods, Group B used metagenomic next-generation sequencing (mNGS) technology, and Group C used both microfluidic-based IVD technology and traditional microbiological detection methods to detect pathogenic microorganisms in the clinical samples. The positive detection rate, detection time, and detection cost were compared among the groups. The diagnostic performance of each group was compared using the Receiver Operating Characteristic (ROC) curve.

RESULTS

Traditional microbiological detection identified 38 positive samples (38%), including 45 pathogens; mNGS technology identified 95 positive samples (95%), including 210 pathogens; microfluidic-based IVD technology identified 96 positive samples (96%), including 158 pathogens. Microfluidic-based IVD technology had a significantly higher positive detection rate for pathogenic microorganisms compared to traditional culture techniques (96% vs 38%, χ2 = 122.0, P < 0.01), and it was also faster and cheaper than mNGS technology. ROC analysis showed that compared to traditional microbiological culture results, microfluidic-based IVD technology had significantly increased sensitivity and specificity, similar to mNGS technology.

CONCLUSION

In respiratory infectious diseases, microfluidic-based IVD technology had a higher detection rate for pathogenic microorganisms than traditional culture methods, and it had advantages in detection time and cost compared to mNGS technology. It could also detect critical drug-resistant genes of pathogens. Hence, microfluidic-based IVD technology can be a viable option for diagnosis and treatment of respiratory infectious diseases.

Bronchoalveolar lavage fluid and lung biopsy tissue metagenomic next-generation sequencing in the diagnosis of pulmonary cryptococcosis

Objective

To evaluate the diagnostic value of metagenomic next-generation sequencing (mNGS) in pulmonary cryptococcosis (PC) using bronchoalveolar lavage fluid (BALF) and lung biopsy tissue specimens.

Methods

In this retrospective study, 321 patients diagnosed with lower respiratory tract diseases who underwent mNGS using BALF and LBT samples, between January 2021 and December 2023 were included. Individuals were classified into PC and non-PC groups according to the diagnostic criteria for PC, and conventional fungal cultures were performed. A serum/BALF cryptococcal antigen (CrAg) test was performed in some patients with PC. The diagnostic efficiencies of three methods for PC (mNGS, conventional culture, and CrAg) were compared. Additionally, two mNGS methods were used in this study: original mNGS (OmNGS, testing time from January 2021 to December 2022) and modified mNGS (MmNGS, testing time from January to December 2023). The diagnostic efficiency of the two mNGS methods on PC was simultaneously compared.

Results

Among the 321 patients, 23 (7.2%) had PC and 298 (92.8%) did not. Compared with the composite reference standard for PC diagnosis, the sensitivity, specificity, and accuracy of mNGS for PC were 78.3% (95% confidence interval [CI], 55.8%-91.7%), 98.7% (95% CI, 96.4%-99.6%), and 97.2% (95% CI, 94.7%-98.7%), respectively. The sensitivity of mNGS was similar to that of CrAg (80.0%, 12/15) (P > 0.05). The diagnostic sensitivity of both mNGS and CrAg was higher than that of conventional culture (35.0%, 7/20) (P = 0.006, P = 0.016), and the combined detection of mNGS and CrAg further improved the diagnostic sensitivity of PC (93.3%, 14/15). The area under the receiver operating characteristic curve of mNGS was superior to that of conventional culture (0.885 vs. 0.675). In addition, the diagnostic sensitivity of PC was higher than that of OmNGS (P = 0.046).

Conclusion

The sensitivity of mNGS is better than that of conventional culture. The combination of mNGS and CrAg improves the testing sensitivity of Cryptococcus. MmNGS could further improve the detection of Cryptococcus. Conventional PC detection methods are indispensable and mNGS can be used as a rapid and accurate auxiliary diagnostic method for PC.

Risk factors for identifying pneumocystis pneumonia in pediatric patients

OBJECTIVES

This study aimed to identify the risk factors and construct the diagnostic model associated with pneumocystis pneumonia (PCP) in pediatric patients.

METHODS

This retrospective observational study analyzed 34 cases of PCP and 51 cases of other types of pneumonia treated at Children's Hospital Affiliated to Shandong University between January 2021 and August 2023. Multivariate binary logistic regression was used to identify the risk factors associated with PCP. Receiver operating characteristic curves and calibration plots were constructed to evaluate the diagnostic model.

RESULTS

Twenty clinical variables significantly differed between the PCP and non-PCP groups. Multivariate binary logistic regression analysis revealed that dyspnea, body temperature>36.5°C, and age<1.46 years old were risk factors for PCP. The area under the curve of the diagnostic model was 0.958, the P-value of Hosmer-Lemeshow calibration test was 0.346, the R2 of the calibration plot for the actual and predicted probability of PCP was 0.9555 (P<0.001), and the mean Brier score was 0.069. In addition, metagenomic next-generation sequencing revealed 79.41% (27/34) and 52.93% (28/53) mixed infections in the PCP and non-PCP groups, respectively. There was significantly more co-infection with cytomegalovirus and Streptococcus pneumoniae in the PCP group than that in the non-PCP group (p<0.05).

CONCLUSIONS

Dyspnea, body temperature>36.5°C, and age<1.46 years old were found to be independent risk factors for PCP in pediatric patients. The probability of co-infection with cytomegalovirus and S. pneumoniae in the PCP group was significantly higher than that in the non-PCP group.

Knowledge framework and emerging trends of invasive pulmonary fungal infection: A bibliometric analysis (2003-2023)

The rising number of immunocompromised people has increased concerns about fungal infections as a severe public health issue. Invasive pulmonary fungal infections (IPFIs) are prevalent and often fatal, particularly for those with weakened immune systems. Understanding IPFIs is crucial. The work aims to offer a concise overview of the field's characteristics, main research areas, development paths, and trends. This study searched the Web of Science Core Collection on June 5, 2024, collecting relevant academic works from 2003 to 2023. Analysis was conducted using CiteSpace, VOSviewer, Bibliometrix Package in R, Microsoft Excel 2019, and Scimago Graphica. The study indicated that the USA, the University of Manchester, and Denning DW led in productivity and impact, while the Journal of Fungi topped the list in terms of publication volume and citations. High-frequency terms include "fungal infection," "invasive," "diagnosis," and "epidemiology." Keyword and trend analysis identified "influenza," "COVID-19," "invasive pulmonary aspergillosis," and "metagenomic next-generation sequencing" as emerging research areas. Over the last 2 decades, research on IPFI has surged, with topics becoming more profound. These insights offer key guidance on current trends, gaps, and the trajectory of IPFI studies.

Metagenomic next-generation sequencing promotes pathogen detection over culture in joint infections with previous antibiotic exposure

Objective

To investigate the diagnostic value of metagenomic next-generation sequencing (mNGS) in detecting pathogens from joint infection (JI) synovial fluid (SF) samples with previous antibiotic exposure.

Methods

From January 2019 to January 2022, 59 cases with suspected JI were enrolled. All cases had antibiotic exposure within 2 weeks before sample collection. mNGS and conventional culture were performed on SF samples. JI was diagnosed based on history and clinical symptoms in conjunction with MSIS criteria. The diagnostic values, including sensitivity, specificity, positive/negative predictive values (PPV/NPV), and accuracy, were in comparison with mNGS and culture.

Results

There were 47 of the 59 cases diagnosed with JI, while the remaining 12 were diagnosed with non-infectious diseases. The sensitivity of mNGS was 68.1%, which was significantly higher than that of culture (25.5%, p<0.01). The accuracy of mNGS was significantly higher at 71.2% compared to the culture at 39.0% (p <0.01). Eleven pathogenic strains were detected by mNGS but not by microbiological culture, which included Staphylococcus lugdunensis, Staphylococcus cohnii, Finegoldia magna, Enterococcus faecalis, Staphylococcus saprophytics, Escherichia coli, Salmonella enterica, Pseudomonas aeruginosa, Acinetobacter pittii, Brucella ovis, andCoxiella burnetii. Antibiotic therapy was adjusted based on the mNGS results in 32 (68.1%) patients, including 12 (25.5%) and 20 (42.6%) patients, in whom treatment was upgraded and changed, respectively. All JI patients underwent surgery and received subsequent antibiotic therapy. They were followed up for an average of 23 months (20-27 months), and the success rate of treatment was 89.4%. Out of the 33 patients who had positive results for pathogens, reoperation was performed in 1 case (3.03%), while out of the 14 cases with negative results for both mNGS and cultures, reoperation was performed in 4 cases (28.6%).

Conclusions

mNGS has advantages over conventional culture in detecting pathogens in SF samples from JI patients previously treated with antibiotics, potentially improving clinical outcomes.

The diagnostic value of bronchoalveolar lavage fluid metagenomic next-generation sequencing in critically ill patients with respiratory tract infections

Metagenomic next-generation sequencing (mNGS) is an unbiased and rapid method for detecting pathogens. This study enrolled 145 suspected severe pneumonia patients who were admitted to the Affiliated Hospital of Jining Medical University. This study primarily aimed to determine the diagnostic performance of mNGS and conventional microbiological tests (CMTs) using bronchoalveolar lavage fluid samples for detecting pathogens. Our findings indicated that mNGS performed significantly higher sensitivity (97.54% vs 28.68%, P < 0.001), coincidence (90.34% vs 35.17%, P < 0.001), and negative predictive value (80.00% vs 13.21%, P < 0.001) but performed lower specificity than CMTs (52.17% vs 87.5%, P < 0.001). Streptococcus pneumoniae as the most common bacterial pathogen had the largest proportion (22.90%, 30/131) in this study. In addition to bacteria, fungi, and virus, mNGS can detect a variety of atypical pathogens such as Mycobacterium tuberculosis and non-tuberculous. Mixed infections were common in patients with severe pneumonia, and bacterial-fungal-viral-atypical pathogens were the most complicated infection. After adjustments of antibiotics based on mNGS and CMTs, the clinical manifestation improved in 139 (95.86%, 139/145) patients. Our data demonstrated that mNGS had significant advantage in diagnosing respiratory tract infections, especially atypical pathogens and fungal infections. Pathogens were detected timely and comprehensively, contributing to the adjustments of antibiotic treatments timely and accurately, improving patient prognosis and decreasing mortality potentially.IMPORTANCEMetagenomic next-generation sequencing using bronchoalveolar lavage fluid can provide more comprehensive and accurate pathogens for respiratory tract infections, especially when considering the previous usage of empirical antibiotics before admission or complicated clinical presentation. This technology is expected to play an important role in the precise application of antimicrobial drugs in the future.

The value of metagenomic next-generation sequencing with different nucleic acid extracting methods of cell-free DNA or whole-cell DNA in the diagnosis of non-neutropenic pulmonary aspergillosis

Purpose

Metagenomic next-generation sequencing(mNGS) is a novel molecular diagnostic technique. For nucleic acid extraction methods, both whole-cell DNA (wcDNA) and cell-free DNA (cfDNA) are widely applied with the sample of bronchoalveolar lavage fluid (BALF). We aim to evaluate the clinical value of mNGS with cfDNA and mNGS with wcDNA for the detection of BALF pathogens in non-neutropenic pulmonary aspergillosis.

Methods

mNGS with BALF-cfDNA, BALF-wcDNA and conventional microbiological tests (CMTs) were performed in suspected non-neutropenic pulmonary aspergillosis. The diagnostic value of different assays for pulmonary aspergillosis was compared.

Results

BALF-mNGS (cfDNA, wcDNA) outperformed CMTs in terms of microorganisms detection. Receiver operating characteristic (ROC) analysis indicated BALF-mNGS (cfDNA, wcDNA) was superior to culture and BALF-GM. Combination diagnosis of either positive for BALF-mNGS (cfDNA, wcDNA) or CMTs is more sensitive than CMTs alone in the diagnosis of pulmonary aspergillosis (BALF-cfDNA+CMTs/BALF-wcDNA+CMTs vs. CMTs: ROC analysis: 0.813 vs.0.66, P=0.0142/0.796 vs.0.66, P=0.0244; Sensitivity: 89.47% vs. 47.37%, P=0.008/84.21% vs. 47.37%, P=0.016). BALF-cfDNA showed a significantly greater reads per million (RPM) than BALF-wcDNA. The area under the ROC curve (AUC) for RPM of Aspergillus detected by BALF-cfDNA, used to predict "True positive" pulmonary aspergillosis patients, was 0.779, with a cut-off value greater than 4.5.

Conclusion

We propose that the incorporation of BALF-mNGS (cfDNA, wcDNA) with CMTs improves diagnostic precision in the identification of non-neutropenic pulmonary aspergillosis when compared to CMTs alone. BALF-cfDNA outperforms BALF-wcDNA in clinical value.

Clinical utility of metagenomic next-generation sequencing in the diagnosis of invasive pulmonary aspergillosis in acute exacerbation of chronic obstructive pulmonary disease patients in the intensive care unit

Objective

To explore the clinical utility of metagenomic next-generation sequencing (mNGS) in diagnosing invasive pulmonary aspergillosis (IPA) among patients with acute exacerbation of chronic obstructive pulmonary disease (AECOPD) in the intensive care unit (ICU).

Methods

A retrospective analysis was conducted on patients with AECOPD admitted to the ICU of Xinxiang Central Hospital in Henan Province, China, between March 2020 and September 2023, suspected of having IPA. Bronchoalveolar lavage fluid (BALF) samples were collected for fungal culture, the galactomannan (GM) test, and mNGS. Based on host factors, clinical features, and microbiological test results, patients were categorized into 62 cases of IPA and 64 cases of non-IPA. Statistical analysis was performed to compare the diagnostic efficacy of fungal culture, the serum and BALF GM test, and mNGS detection for IPA in patients with AECOPD.

Results

1. The sensitivity and specificity of mNGS in diagnosing IPA were 70.9% and 71.8% respectively, with the sensitivity of mNGS surpassing that of fungal culture (29.0%, P<0.01), serum GM test (35.4%, P<0.01), and BALF GM test (41.9%, P<0.05), albeit with slightly lower specificity compared to fungal culture (90.6%, P >0.05), serum GM test (87.5%, P >0.05), and BALF GM test (85.9%, P >0.05).Combining fungal culture with the GM test and mNGS resulted in a sensitivity of 80.6% and a specificity of 92.2%, underscoring a superior diagnostic rate compared to any single detection method. 2.mNGS accurately distinguished strains of the Aspergillus genus. 3.The area under the ROC curves of mNGS was 0.73, indicating good diagnostic performance. 4.The detection duration for mNGS is shorter than that of traditional fungal culture and GM testing.

Conclusion

mNGS presents a pragmatic and highly sensitive approach, serving as a valuable complementary tool to conventional microbiological tests (CMT). Our research demonstrated that, compared to fungal culture and GM testing, mNGS exhibits superior diagnostic capability for IPA among patients with AECOPD. Integration of mNGS with established conventional methods holds promise for improving the diagnosis rate of IPA.

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.

Clinical features of pediatric mucormycosis: role of metagenomic next generation sequencing in diagnosis

Background

Mucormycosis is an uncommon invasive fungal infection that has a high mortality rate in patients with severe underlying diseases, which leads to immunosuppression. Due to its rarity, determining the incidence and optimal treatment methods for mucormycosis in children is challenging. Metagenomic next-generation sequencing (mNGS) is a rapid, precise and sensitive method for pathogen detection, which helps in the early diagnosis and intervention of mucormycosis in children. In order to increase pediatricians' understanding of this disease, we conducted a study on the clinical features of mucormycosis in children and assessed the role of mNGS in its diagnosis.

Methods

We retrospectively summarized the clinical data of 14 children with mucormycosis treated at the First Affiliated Hospital of Zhengzhou University from January 2020 to September 2023.

Results

Of the 14 cases, 11 case of mucormycosis were classified as probable, and 3 cases were proven as mucormycosis. Most children (85.71%) had high-risk factors for mucormycosis. All 14 children had lung involvement, with 5 cases of extrapulmonary dissemination. Among the 14 cases, 4 cases underwent histopathological examination of mediastinum, lung tissue or kidney tissue, in which fungal pathogens were identified in 3 patients. Fungal hyphae was identified in 3 cases of mucormycosis, but only 1 case yielded a positive culture result. All patients underwent mNGS testing with samples from blood (8/14), bronchoalveolar lavage fluid (6/14), and tissue (1/14). mNGS detected fungi in all cases: 7 cases had Rhizomucor pusillus, 4 cases had Rhizopus oryzae, 3 cases had Rhizopus microsporus, 1 case had Lichtheimia ramosa, and 1 case had Rhizomucor miehei. Coinfections were found with Aspergillus in 3 cases, bacteria in 3 cases, and viruses in 5 cases.

Conclusion

Children with mucormycosis commonly exhibit non-specific symptoms like fever and cough during the initial stages. Early diagnosis based on clinical symptoms and imaging is crucial in children suspected of having mucormycosis. mNGS, as a supplementary diagnostic method, offers greater sensitivity and shorter detection time compared to traditional mucormycosis culture or histopathological testing. Additionally, mNGS enables simultaneous detection of bacteria and viruses, facilitating timely and appropriate administration of antibiotics and thereby enhancing patient outcomes.

Metagenomic next-generation sequencing could play a pivotal role in validating the diagnosis of invasive mold disease of the central nervous system

Background

Invasive mold diseases of the central nervous (CNS IMD) system are exceedingly rare disorders, characterized by nonspecific clinical symptoms. This results in significant diagnostic challenges, often leading to delayed diagnosis and the risk of misdiagnosis for patients. Metagenomic Next-Generation Sequencing (mNGS) holds significant importance for the diagnosis of infectious diseases, especially in the rapid and accurate identification of rare and difficult-to-culture pathogens. Therefore, this study aims to explore the clinical characteristics of invasive mold disease of CNS IMD in children and assess the effectiveness of mNGS technology in diagnosing CNS IMD.

Methods

Three pediatric patients diagnosed with Invasive mold disease brain abscess and treated in the Pediatric Intensive Care Unit (PICU) of the First Affiliated Hospital of Zhengzhou University from January 2020 to December 2023 were selected for this study.

Results

Case 1, a 6-year-old girl, was admitted to the hospital with "acute liver failure." During her hospital stay, she developed fever, irritability, and seizures. CSF mNGS testing resulted in a negative outcome. Multiple brain abscesses were drained, and Aspergillus fumigatus was detected in pus culture and mNGS. The condition gradually improved after treatment with voriconazole combined with caspofungin. Case 2, a 3-year-old girl, was admitted with "acute B-lymphoblastic leukemia." During induction chemotherapy, she developed fever and seizures. Aspergillus fumigatus was detected in the intracranial abscess fluid by mNGS, and the condition gradually improved after treatment with voriconazole combined with caspofungin, followed by "right-sided brain abscess drainage surgery." Case 3, a 7-year-old girl, showed lethargy, fever, and right-sided limb weakness during the pending chemotherapy period for acute B-lymphoblastic leukemia. Rhizomucor miehei and Rhizomucor pusillus was detected in the cerebrospinal fluid by mNGS. The condition gradually improved after treatment with amphotericin B combined with posaconazole. After a six-month follow-up post-discharge, the three patients improved without residual neurological sequelae, and the primary diseases were in complete remission.

Conclusion

The clinical manifestations of CNS IMD lack specificity. Early mNGS can assist in identifying the pathogen, providing a basis for definitive diagnosis. Combined surgical treatment when necessary can help improve prognosis.

Deciphering the microbial landscape of lower respiratory tract infections: insights from metagenomics and machine learning

Background

Lower respiratory tract infections represent prevalent ailments. Nonetheless, current comprehension of the microbial ecosystems within the lower respiratory tract remains incomplete and necessitates further comprehensive assessment. Leveraging the advancements in metagenomic next-generation sequencing (mNGS) technology alongside the emergence of machine learning, it is now viable to compare the attributes of lower respiratory tract microbial communities among patients across diverse age groups, diseases, and infection types.

Method

We collected bronchoalveolar lavage fluid samples from 138 patients diagnosed with lower respiratory tract infections and conducted mNGS to characterize the lung microbiota. Employing various machine learning algorithms, we investigated the correlation of key bacteria in patients with concurrent bronchiectasis and developed a predictive model for hospitalization duration based on these identified key bacteria.

Result

We observed variations in microbial communities across different age groups, diseases, and infection types. In the elderly group, Pseudomonas aeruginosa exhibited the highest relative abundance, followed by Corynebacterium striatum and Acinetobacter baumannii. Methylobacterium and Prevotella emerged as the dominant genera at the genus level in the younger group, while Mycobacterium tuberculosis and Haemophilus influenzae were prevalent species. Within the bronchiectasis group, dominant bacteria included Pseudomonas aeruginosa, Haemophilus influenzae, and Klebsiella pneumoniae. Significant differences in the presence of Pseudomonas phage JBD93 were noted between the bronchiectasis group and the control group. In the group with concomitant fungal infections, the most abundant genera were Acinetobacter and Pseudomonas, with Acinetobacter baumannii and Pseudomonas aeruginosa as the predominant species. Notable differences were observed in the presence of Human gammaherpesvirus 4, Human betaherpesvirus 5, Candida albicans, Aspergillus oryzae, and Aspergillus fumigatus between the group with concomitant fungal infections and the bacterial group. Machine learning algorithms were utilized to select bacteria and clinical indicators associated with hospitalization duration, confirming the excellent performance of bacteria in predicting hospitalization time.

Conclusion

Our study provided a comprehensive description of the microbial characteristics among patients with lower respiratory tract infections, offering insights from various perspectives. Additionally, we investigated the advanced predictive capability of microbial community features in determining the hospitalization duration of these patients.

Clinical performance of metagenomic next-generation sequencing for diagnosis of pulmonary Aspergillus infection and colonization

Background

Investigations assessing the value of metagenomic next-generation sequencing (mNGS) for distinguish Aspergillus infection from colonization are currently insufficient.

Methods

The performance of mNGS in distinguishing Aspergillus infection from colonization, along with the differences in patients' characteristics, antibiotic adjustment, and lung microbiota, were analyzed.

Results

The abundance of Aspergillus significantly differed between patients with Aspergillus infection (n=36) and colonization (n=32) (P < 0.0001). Receiver operating characteristic (ROC) curve result for bronchoalveolar lavage fluid (BALF) mNGS indicated an area under the curve of 0.894 (95%CI: 0.811-0.976), with an optimal threshold value of 23 for discriminating between Aspergillus infection and colonization. The infection group exhibited a higher proportion of antibiotic adjustments in comparison to the colonization group (50% vs. 12.5%, P = 0.001), with antibiotic escalation being more dominant. Age, length of hospital stay, hemoglobin, cough and chest distress were significantly positively correlated with Aspergillus infection. The abundance of A. fumigatus and Epstein-Barr virus (EBV) significantly increased in the infection group, whereas the colonization group exhibited higher abundance of A. niger.

Conclusion

BALF mNGS is a valuable tool for differentiating between colonization and infection of Aspergillus. Variations in patients' age, length of hospital stay, hemoglobin, cough and chest distress are observable between patients with Aspergillus infection and colonization.

COVID-19 in pulmonary critically ill patients: metagenomic identification of fungi and characterization of pathogenic microorganisms

Background

Fungal co-infection is prevalent in critically ill patients with COVID-19. The conventional approach applied to fungal identification has relatively low sensitivity and is time-consuming. The metagenomic next-generation sequencing (mNGS) technology can simultaneously detect a variety of microorganisms, and is increasingly being used for the rapid detection and diagnosis of pathogens.

Methods

In this single-center retrospective study, we described the clinical presentation and outcomes of COVID-19 and mNGS positive for fungi in pulmonary critically ill patients during the outbreak of Omicron infection from December 2022 to January 2023.

Results

Among 43 COVID-19 patients with acute respiratory distress syndrome (ARDS) on a single intensive care unit (ICU), 10 were reported to be fungal positive using the mNGS test. The number of pathogenic microorganisms detected by mNGS was significantly higher than that via traditional methods, especially in the detection of fungi and viruses. Aspergillus infection was dominant, and most of these patients also had concurrent bacterial or viral infections. Probable or possible COVID-19-associated pulmonary aspergillosis (CAPA) was diagnosed in all 10 patients, and the prognosis was poor.

Conclusion

Patients with COVID-19 may be at increased risk of developing fungal infections as well as concurrent bacterial or viral infections, and mNGS can be a powerful tool in identifying these infections. Clinicians should be aware of the increased risk of fungal infections in COVID-19 patients, particularly those who have underlying immunocompromising conditions, and should monitor for early signs of infection.

The Clinical Value of Metagenomic Next-Generation Sequencing in Pneumocystis jirovecii Pneumonia

Background

The incidence of Pneumocystis jirovecii pneumonia (PJP) is increasing.

Methods

108 patients were analysed retrospectively at the Wuhan Union Hospital. The patients were classified into the PJP group or the P. jirovecii colonisation (PJC) group based on clinical diagnosis. Clinical data included demographics, laboratory examinations, treatment, and outcomes.

Results

A notable difference in the fungal load was seen between two groups, with median reads of 3215.79 vs. 5.61 in two groups, respectively (P<0.001). The optimal threshold value for discriminating P. jirovecii infection between colonisation for mNGS was six, and serum (1,3)-β-D-glucan (BDG) was 47.6 pg/mL. Besides, the positive detection rate of mNGS for co-pathogens in PJP patients was significantly higher than that of culture (88.16% vs. 22.37%, P<0.0001). Epstein-Barr virus and cytomegalovirus were the most common pathogens of co-infection in PJP patients. The antibiotic therapy in PJP patients was adjusted according to the mNGS results, of which seventeen (22.37%) were downgraded, 38 (50.0%) patients were upgraded, and 21 (27.63%) were unchanged. And almost all patients showed significant improvement in C-reactive protein.

Conclusion

mNGS is a promising and valuable technique with good performance for differentiating P. jirovecii infection and colonisation, the detection of pathogens, and antibiotic treatment.

Microbiome Alteration in Lung Tissues of Tuberculosis Patients Revealed by Metagenomic Next-Generation Sequencing and Immune-Related Transcriptional Profile Identified by Transcriptome Sequencing

This study explored alterations in the respiratory microbiome and transcriptome after Mycobacterium tuberculosis infection in tuberculosis (TB) patients. Metagenomic next-generation sequencing (mNGS) was adopted to reveal the microbiome in lung tissues from 110 TB and 25 nontuberculous (NonTB) patients. Transcriptome sequencing was performed in TB tissues (n = 3), tissues adjacent to TB (ParaTB, n = 3), and NonTB tissues (n = 3) to analyze differentially expressed genes (DEGs) and functional pathways. The microbial β diversity (p = 0.01325) in TB patients differed from that in the NonTB group, with 17 microbial species distinctively distributed. Eighty-three co-up-regulated DEGs were identified in the TB versus NonTB and the TB versus ParaTB comparison groups, and six were associated with immune response to Mtb. These DEGs were significantly enriched in the signaling pathways such as immune response, NF-κB, and B cell receptor. Data in the lung tissue microbiome and transcriptome in TB patients offer a sufficient understanding of the pathogenesis of TB.

Etiologic characteristics revealed by mNGS-mediated ultra-early and early microbiological identification in airway secretions from lung transplant recipients

Background

Post-operative etiological studies are critical for infection prevention in lung transplant recipients within the first year. In this study, mNGS combined with microbial culture was applied to reveal the etiological characteristics within one week (ultra-early) and one month (early) in lung transplant recipients, and the epidemiology of infection occurred within one month.

Methods

In 38 lung transplant recipients, deep airway secretions were collected through bronchofiberscope within two hours after the operation and were subjected to microbial identification by mNGS and microbial culture. The etiologic characteristics of lung transplant recipients were explored. Within one month, the infection status of recipients was monitored. The microbial species detected by mNGS were compared with the etiological agents causing infection within one month.

Results

The detection rate of mNGS in the 38 airway secretions specimens was significantly higher than that of the microbial culture (P<0.0001). MNGS identified 143 kinds of pathogenic microorganisms; bacterial pathogens account for more than half (72.73%), with gram-positive and -negative bacteria occupying large proportions. Fungi such as Candida are also frequently detected. 5 (50%) microbial species identified by microbial culture had multiple drug resistance (MDR). Within one month, 26 (68.42%) recipients got infected (with a median time of 9 days), among which 10 (38.46%) cases were infected within one week. In the infected recipients, causative agents were detected in advance by mNGS in 9 (34.62%) cases, and most of them (6, 66.67%) were infected within one week (ultra-early). In the infection that occurred after one week, the consistency between mNGS results and the etiological agents was decreased.

Conclusion

Based on the mNGS-reported pathogens in airway secretions samples collected within two hours, the initial empirical anti-infection regimes covering the bacteria and fungi are reasonable. The existence of bacteria with MDR forecasts the high risk of infection within 48 hours after transplant, reminding us of the necessity to adjust the antimicrobial strategy. The predictive role of mNGS performed within two hours in etiological agents is time-limited, suggesting continuous pathogenic identification is needed after lung transplant.

The Diagnostic Accuracy of Metagenomic Next-Generation Sequencing in Diagnosing Pneumocystis Pneumonia: A Systemic Review and Meta-analysis

BACKGROUND

Pneumocystis pneumonia (PCP) is a growing concern as the immunocompromised population expands. Current laboratory approaches are limited. This systematic review aimed to evaluate metagenomic next-generation sequencing (MNGS) tests' performance in detecting PCP.

METHODS

Five databases were searched through December 19, 2022, to identify original studies comparing MNGS with clinically diagnosed PCP. To assess the accuracy, symmetric hierarchical summary receiver operating characteristic models were used.

RESULTS

Eleven observational studies reporting 1442 patients (424 with PCP) were included. Six studies focused exclusively on recipients of biologic immunosuppression (none with HIV-associated immunosuppression). Six were exclusively on bronchoalveolar lavage, while 1 was on blood samples. The sensitivity of MGNS was 0.96 (95% CI, 0.90-0.99), and specificity was 0.96 (95% CI, 0.92-0.98), with negative and positive likelihood ratios of 0.02 (95% CI, 0.01-0.05) and 19.31 (95% CI, 10.26-36.36), respectively. A subgroup analysis of studies exclusively including bronchoalveolar lavage (BAL) and blood samples demonstrated a sensitivity of 0.94 (95% CI, 0.78-0.99) and 0.93 (95% CI, 0.80-0.98) and a specificity of 0.96 (95% CI, 0.88-0.99) and 0.98 (95% CI, 0.76-1.00), respectively. The sensitivity analysis on recipients of biologic immunosuppression showed a sensitivity and specificity of 0.96 (95% CI, 0.90-0.98) and 0.94 (95% CI, 0.84-0.98), respectively. The overall confidence in the estimates was low.

CONCLUSIONS

Despite the low certainty of evidence, MNGS detects PCP with high sensitivity and specificity. This also applies to recipients of biologic immunosuppression and tests performed exclusively on blood samples without the need for BAL. Further studies are required in individuals with HIV-associated immunosuppression.

Microbiomes Detected by Bronchoalveolar Lavage Fluid Metagenomic Next-Generation Sequencing among HIV-Infected and Uninfected Patients with Pulmonary Infection

Comparison of lung microbiomes between HIV-infected and uninfected patients with pulmonary infection by metagenomic next-generation sequencing (mNGS) has not been described in China. The lung microbiomes detected in bronchoalveolar fluid (BALF) by mNGS among HIV-infected and uninfected patients with pulmonary infection were reviewed in the First Hospital of Changsha between January 2019 and June 2022. In total, 476 HIV-infected and 280 uninfected patients with pulmonary infection were enrolled. Compared with HIV-uninfected patients, the proportions of Mycobacterium (P = 0.011), fungi (P < 0.001), and viruses (P < 0.001) were significantly higher in HIV-infected patients. The higher positive rate of Mycobacterium tuberculosis (MTB; P = 0.018), higher positive rates of Pneumocystis jirovecii and Talaromyces marneffei (all P < 0.001), and higher positive rate of cytomegalovirus (P < 0.001) contributed to the increased proportions of Mycobacterium, fungi, and viruses among HIV-infected patients, respectively. The constituent ratios of Streptococcus pneumoniae (P = 0.007) and Tropheryma whipplei (P = 0.002) in the bacteria spectrum were significantly higher, while the constituent ratio of Klebsiella pneumoniae (P = 0.005) was significantly lower in HIV-infected patients than in HIV-uninfected patients. Compared with HIV-uninfected patients, the constituent ratios of P. jirovecii and T. marneffei (all P < 0.001) in the fungal spectrum were significantly higher, while the constituent ratios of Candida and Aspergillus (all P < 0.001) were significantly lower in HIV-infected patients. In comparison to HIV-infected patients without antiretroviral therapy (ART), the proportions of T. whipplei (P = 0.001), MTB (P = 0.024), P. jirovecii (P < 0.001), T. marneffei (P < 0.001), and cytomegalovirus (P = 0.008) were significantly lower in HIV-infected patients on ART. Significant differences in lung microbiomes exist between HIV-infected and uninfected patients with pulmonary infection, and ART influences the lung microbiomes among HIV-infected patients with pulmonary infection. IMPORTANCE A better understanding of lung microorganisms is conducive to early diagnosis and treatment and will improve the prognosis of HIV-infected patients with pulmonary infection. Currently, few studies have systematically described the spectrum of pulmonary infection among HIV-infected patients. This study is the first to provide comprehensive information on the lung microbiomes of HIV-infected patients with pulmonary infection (as assessed by more sensitive metagenomic next-generation sequencing of bronchoalveolar fluid) compared with those from HIV-uninfected patients, which could provide a reference for the etiology of pulmonary infection among HIV-infected patients.

Building a nomogram plot based on the nanopore targeted sequencing for predicting urinary tract pathogens and differentiating from colonizing bacteria

Background

The identification of uropathogens (UPBs) and urinary tract colonizing bacteria (UCB) conduces to guide the antimicrobial therapy to reduce resistant bacterial strains and study urinary microbiota. This study established a nomogram based on the nanopore-targeted sequencing (NTS) and other infectious risk factors to distinguish UPB from UCB.

Methods

Basic information, medical history, and multiple urine test results were continuously collected and analyzed by least absolute shrinkage and selection operator (LASSO) regression, and multivariate logistic regression was used to determine the independent predictors and construct nomogram. Receiver operating characteristics, area under the curve, decision curve analysis, and calibration curves were used to evaluate the performance of the nomogram.

Results

In this study, the UPB detected by NTS accounted for 74.1% (401/541) of all urinary tract microorganisms. The distribution of ln(reads) between UPB and UCB groups showed significant difference (OR = 1.39; 95% CI, 1.246-1.551, p < 0.001); the reads number in NTS reports could be used for the preliminary determination of UPB (AUC=0.668) with corresponding cutoff values being 7.042. Regression analysis was performed to determine independent predictors and construct a nomogram, with variables ranked by importance as ln(reads) and the number of microbial species in the urinary tract of NTS, urine culture, age, urological neoplasms, nitrite, and glycosuria. The calibration curve showed an agreement between the predicted and observed probabilities of the nomogram. The decision curve analysis represented that the nomogram would benefit clinical interventions. The performance of nomogram with ln(reads) (AUC = 0.767; 95% CI, 0.726-0.807) was significantly better (Z = 2.304, p-value = 0.021) than that without ln(reads) (AUC = 0.727; 95% CI, 0.681-0.772). The rate of UPB identification of nomogram was significantly higher than that of ln(reads) only (χ^2 = 7.36, p-value = 0.009).

Conclusions

NTS is conducive to distinguish uropathogens from colonizing bacteria, and the nomogram based on NTS and multiple independent predictors has better prediction performance of uropathogens.

Point-of-Care Testing for the Diagnosis of Fungal Infections

Invasive fungal infections are increasing worldwide due to factors such as climate change and immunomodulating therapies. Unfortunately, the detection of these infections is limited due to the low sensitivity and long periods required for laboratory testing. Point-of-care testing could lead to more rapid diagnosis of these often devasting infections. However, there are currently no true point-of-care tests on the market for the detection of fungi. In this article, the current state of fungal antigen and molecular testing is reviewed, with commentary on the potential for development and use in the point-of-care setting.

Metagenomic Next-Generation Sequencing Assists in the Diagnosis of Mediastinal Aspergillus fumigatus Abscess in an Immunocompetent Patient: A Case Report and Literature Review

Background

Aspergillus fumigatus is an opportunistic fungal pathogen, which is commonly found in lungs and rarely causes infections in mediastinum. Mediastinal Aspergillus abscess is a serious infectious condition, and is characterized by difficult diagnosis due to its clinical manifestations being nonspecific.

Case Presentation

Here, we report a case of a mediastinal Aspergillus fumigatus abscess in an immunocompetent patient. The patient was a 45-year-old woman who presented with a 20-day history of sore throat without any underlying diseases. Chest computed tomography (CT) showed a mass in the anterior superior mediastinum. Metagenomic next-generation sequencing (mNGS) identified Aspergillus fumigatus sequences in endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA) tissue, indicating the mediastinal Aspergillus fumigatus infection of this patient. The following mediastinal biopsy histological analysis and tissue fungi culture also suggested Aspergillus fumigatus infection, confirming the mNGS detection. The patient was diagnosed with mediastinal aspergillosis caused by Aspergillus fumigatus. After timely voriconazole treatment, the patient was discharged with good condition.

Conclusion

Our study presented a rare case with mediastinal Aspergillus fumigatus abscess in an immunocompetent patient. As a new clinical diagnostic method, mNGS could assist timely diagnosis and precise treatment of Aspergillus infection.

Metagenomic Next-Generation Sequencing for Diagnostically Challenging Mucormycosis in Patients with Hematological Malignancies

Background

Metagenomic next-generation sequencing (mNGS) is a fast, sensitive and accurate diagnostic method for pathogens detection. However, reports on the application of mNGS in mucormycosis remain scarce.

Methods

From January 2019 to December 2021, we recruited 13 patients with hematological malignancies who were suspected of mucormycosis and completed mNGS in D20. Then we retrospectively analyze the clinical data, diagnosis, therapeutic process, and outcomes. In order to evaluate the diagnostic value of mNGS in hematological malignancies patients with suspected mucormycosis.

Results

All patients had high risk factors of Invasive Fungal Disease, including hematopoietic stem cell transplantation, immunosuppression, glucocorticoids, etc. The clinical presentations were pulmonary (n=9), rhino-orbito-cerebral (n=4). But the manifestations were nonspecific. All enrolled patients completed mNGS. And most (8/13, 61.54%) of the samples were from blood. Fungi can be detected in all specimens, including Rhizopus (n=7), Rhizomucor (n=4) and Mucor (n=2). In addition, 7/13 (53.85%) specimens were detected bacteria at the same time and virus were detected in 5/13 (38.46%). Histopathological examination was completed in 5 patients, 3 of which were completely consistent with the results of mNGS. After treatment, 6 patients were cured, while the other 7 patients died.

Conclusion

mNGS may be a complementary method for early diagnosis, especially for patients who are not suitable for histopathology examination or unable to obtain culture specimen. mNGS can also help detect bacteria and viruses simultaneously, allowing for appropriate and timely antibiotic administration and thus improving patient outcomes.