Prevalence of Fungal and Bacterial Co-Infection in Pulmonary Fungal Infections: A Metagenomic Next Generation Sequencing-Based Study

Comparative Cross-Kingdom DDA- and DIA-PASEF Proteomic Profiling Reveals Novel Determinants of Fungal Virulence and a Putative Druggable Target

Accurate and reliable detection of fungal pathogens presents an important hurdle to manage infections, especially considering that fungal pathogens, including the globally important human pathogen, Cryptococcus neoformans, have adapted diverse mechanisms to survive the hostile host environment and moderate virulence determinant production during coinfections. These pathogen adaptations present an opportunity for improvements (e.g., technological and computational) to better understand the interplay between a host and a pathogen during disease to uncover new strategies to overcome infection. In this study, we performed comparative proteomic profiling of an in vitro coinfection model across a range of fungal and bacterial burden loads in macrophages. Comparing data-dependent acquisition and data-independent acquisition enabled with parallel accumulation serial fragmentation technology, we quantified changes in dual-perspective proteome remodeling. We report enhanced and novel detection of pathogen proteins with data-independent acquisition-parallel accumulation serial fragmentation (DIA-PASEF), especially for fungal proteins during single and dual infection of macrophages. Further characterization of a fungal protein detected only with DIA-PASEF uncovered a novel determinant of fungal virulence, including altered capsule and melanin production, thermotolerance, and macrophage infectivity, supporting proteomics advances for the discovery of a novel putative druggable target to suppress C. neoformans pathogenicity.

Real-time application of ITS and D1-D3 nanopore amplicon metagenomic sequencing in fungal infections: Enhancing fungal infection diagnostics

While fungal infections cause considerable morbidity and mortality, the performance of the current diagnostic tests for fungal infection is low. Even though fungal metagenomics or targeted next-generation sequencing have been investigated for various clinical samples, the real-time clinical utility of these methods still needs to be elucidated. In this study, we used internal transcribed spacer (ITS) and D1-D3 ribosomal DNA nanopore amplicon metagenomic sequencing to assess its utility in patients with fungal infections. Eighty-four samples from seventy-three patients were included and categorized into 'Fungal infection,' 'Fungal colonization,' and 'Fungal contamination' groups based on the judgement of infectious disease specialists. In the 'Fungal infection' group, forty-seven initial samples were obtained from forty-seven patients. Three fungal cases detected not by the sequencing but by conventional fungal assays were excluded from the analysis. In the remaining cases, the conventional fungal assay-negative/sequencing-positive group (n=11) and conventional fungal assay-positive/sequencing-positive group (n=33) were compared. Non-Candida and non-Aspergillus fungi infections were more frequent in the conventional-negative/sequencing-positive group (p-value = 0.031). We demonstrated the presence of rare human pathogens, such as Trichosporon asahii and Phycomyces blakesleeanus. In the 'Fungal infection' group and 'Fungal colonization' group, sequencing was faster than culturing (mean difference = 4.92 days, p-value < 0.001/ mean difference = 4.67, p-value <0.001). Compared to the conventional diagnostic methods including culture, nanopore amplicon sequencing showed a shorter turnaround time and a higher detection rate for uncommon fungal pathogens.

Value of bronchoalveolar lavage fluid metagenomic next-generation sequencing in acute exacerbation of fibrosing interstitial lung disease: an individualized treatment protocol based on microbiological evidence

BACKGROUND

Acute exacerbation of fibrosing interstitial lung diseases (AE-ILD) is a serious life-threatening event per year. Methylprednisolone and/or immunosuppressive agents (ISA) are a mainstay in any regimen, under the premise that pulmonary infection has been promptly identified and controlled. We investigated the value of bronchoalveolar lavage fluid (BALF) metagenomic next-generation sequencing (mNGS) on the treatment adjustment of AE-ILD.

METHODS

We conducted a cross-sectional observational study. All data were collected prospectively and retrospectively analyzed. We included fifty-six patients with AE-ILD and nineteen stable ILD who underwent BALF mNGS at the beginning of admission.

RESULTS

Patients with a variety of ILD classification were included. Connective-tissue disease related ILD (CTD-ILD) occupy the most common underlying non-idiopathic pulmonary fibrosis (non-IPF). The infection-triggered AE accounted for 39.29%, with the majority of cases being mixed infections. The microorganisms load in the AE-ILD group was significantly higher. After adjusted by mNGS, the therapy coverage number of pathogens was significantly higher compared to the initial treatment (p < 0.001). After treatment, the GGO score and the consolidation score were significantly lower during follow up in survivors (1.57 ± 0.53 vs. 2.38 ± 0.83 with p < 0.001, 1.11 ± 0.24 vs. 1.49 ± 0.47 with p < 0.001, respectively). Some detected microorganisms, such as Tropheryma whipplei, Mycobacterium, Aspergillus, and mixed infections were difficult to be fully covered by empirical medication. BALF mNGS was also very helpful for excluding infections and early administration of methylprednisolone and/or ISA.

CONCLUSIONS

mNGS has been shown to be a useful tool to determine pathogens in patients with AE-ILD, the results should be fully analyzed. The comprehensive treatment protocol based on mNGS has been shown crucial in AE-ILD patients.

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.

Prevalence of Co-infection of Culture-Proven Bacterial Pathogens in Microbiologically Confirmed Pulmonary Tuberculosis Patients From a Tertiary Care Center

Tuberculosis (TB) is a chronic condition that weakens the immune system, causes structural changes in the lungs, and can lead to infections by other bacterial pathogens. Very few studies have been done to understand the magnitude of co-infection with other bacterial pathogens, so this study was conducted to understand the co-infection pattern and burden. A total of 174 microbiologically confirmed pulmonary TB patients' samples, identified by cartridge-based nucleic acid amplification test, were further tested for other bacterial pathogens by culture over a period of five months from May 2023 to September 2023. The isolates' identification and drug susceptibility were performed using the VITEK 2 system (bioMérieux, Marcy-l'Étoile, France). Of the 174 pulmonary samples tested, 19 samples grew a significant amount of other bacterial pathogens, making the prevalence 10.91% (19/174). Among the pulmonary samples tested, 54.59% were sputum, 38.5% were bronchoalveolar lavage, and 6.89% were endotracheal aspirate. Additionally, 70.11% of the patients tested were in the age group of 19-60 years. Of the patients who had co-infection, 94.73% (18/19) were male. The most common bacterial infection was caused by Pseudomonas aeruginosa, which was identified in 36.84% of the co-infection cases (7/19). This was followed by Acinetobacter baumannii in 31.57% (6/19), Klebsiella pneumoniae in 26.31% (5/19), and Stenotrophomonas maltophilia in 5.28% (1/19). Acinetobacter baumannii and Klebsiella pneumoniae showed high drug resistance, ranging from 60% to 100% against various groups of drugs tested. None of the patient samples with co-infection showed rifampicin resistance. Among all the samples with co-infection, the majority (42.10%, or 8/19) had a high load of Mycobacterium tuberculosis complex detected by CBNAAT Ultra (Cepheid, Sunnyvale, California). Pseudomonas aeruginosa, Acinetobacter baumannii, and Klebsiella pneumoniae are unusual pathogens causing infection in community patients and are known to cause illness in hospitalized patients. These organisms' resistance was also similar to the resistance shown by hospital-acquired infections. This indicates that bacterial co-infection in pulmonary TB patients will be similar to the pattern of hospital-acquired infections. The high prevalence of bacterial co-infections (10.91%) in patients with pulmonary TB poses a significant challenge as these bacterial pathogens are not susceptible to anti-tubercular drugs. Therefore, comprehensive screening for other bacterial infections in all pulmonary TB patients is crucial for effective treatment and outcomes.

The gut-lung axis: the impact of the gut mycobiome on pulmonary diseases and infections

The gastrointestinal tract contains a diverse microbiome consisting of bacteria, fungi, viruses and archaea. Although these microbes usually reside as commensal organisms, it is now well established that higher abundance of specific bacterial or fungal species, or loss of diversity in the microbiome can significantly affect development, progression and outcomes in disease. Studies have mainly focused on the effects of bacteria, however, the impact of other microbes, such as fungi, has received increased attention in the last few years. Fungi only represent around 0.1% of the total gut microbial population. However, key fungal taxa such as Candida, Aspergillus and Wallemia have been shown to significantly impact health and disease. The composition of the gut mycobiome has been shown to affect immunity at distal sites, such as the heart, lung, brain, pancreas, and liver. In the case of the lung this phenomenon is referred to as the 'gut-lung axis'. Recent studies have begun to explore and unveil the relationship between gut fungi and lung immunity in diseases such as asthma and lung cancer, and lung infections caused by viruses, bacteria and fungi. In this review we will summarize the current, rapidly growing, literature describing the impact of the gut mycobiome on respiratory disease and infection.

Integrative analyses identify opportunistic pathogens of patients with lower respiratory tract infections based on metagenomic next-generation sequencing

Lower respiratory tract infections (LRTIs) represent some of the most globally prevalent and detrimental diseases. Metagenomic next-generation sequencing (mNGS) technology has effectively addressed the requirement for the diagnosis of clinical infectious diseases. This study aimed at identifying and classifying opportunistic pathogens from the respiratory tract-colonizing microflora in LRTI patients using data acquired from mNGS analyses. A retrospective study was performed employing the mNGS data pertaining to the respiratory samples derived from 394 LRTIs patients. Linear discriminant analysis effect size (LEfSe) analysis was conducted to discern the discriminant bacteria. Receiver operating characteristic curves (ROC) were established to demonstrate discriminant bacterial behavior to distinguish colonization from infection. A total of 443 discriminant bacteria were identified and segregated into three cohorts contingent upon their correlation profiles, detection frequency, and relative abundance in order to distinguish pathogens from colonizing microflora. Among them, 119 emerging opportunistic pathogens (cohort 2) occupied an average area under the curve (AUC) of 0.976 for exhibiting the most prominent predictability in distinguishing colonization from infection, 39 were colonizing bacteria (cohort 1, 0.961), and 285 were rare opportunistic pathogens (cohort 3, 0.887). The LTRIs patients appeared modular in the form of cohorts depicting complex microbial co-occurrence networks, reduced diversity, and a high degree of antagonistic interactions in the respiratory tract microbiome. The study findings indicate that therapeutic interventions should target interaction networks rather than individual microbes, providing an innovative perspective for comprehending and combating respiratory infections. Conclusively, this study reports a profile of LRTIs-associated bacterial colonization and opportunistic pathogens in a relatively large-scale cohort, which might serve as a reference panel for the interpretation of mNGS results in clinical practice.

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.

Assessment and clinical utility of metagenomic next-generation sequencing for suspected lower respiratory tract infections

OBJECTIVES

This study aims to compare the diagnostic efficacy of metagenomic next-generation sequencing (mNGS) to traditional diagnostic methods in patients with lower respiratory tract infections (LRTIs), elucidate the etiological spectrum of these infections, and explore the impact of mNGS on guiding antimicrobial therapy.

METHODS

We retrospectively analyzed data from 128 patients admitted to the Respiratory Department of Anqing 116 Hospital between July 2022 and July 2023. All patients had undergone both mNGS and conventional microbiological techniques (CMT) for LRTI diagnosis. We assessed the diagnostic performance of these methods and examined the influence of mNGS on antimicrobial decision-making.

RESULTS

Overall, mNGS demonstrated superior sensitivity (96.8%) and accuracy (96.8%) compared to CMT. For Mycobacterium tuberculosis detection, the accuracy and sensitivity of mNGS was 88.8% and 77.6%, which was lower than the 94.7% sensitivity of the T-spot test and the 79.6% sensitivity of CMT. In fungal pathogen detection, mNGS showed excellent sensitivity (90.5%), specificity (86.7%), and accuracy (88.0%). Bacteria were the predominant pathogens detected (75.34%), with Mycobacterium tuberculosis (41.74%), Streptococcus pneumoniae (21.74%), and Haemophilus influenzae (16.52%) being most prevalent. Bacterial infections were most common (62.10%), followed by fungal and mixed infections (17.74%). Of the 118 patients whose treatment regimens were adjusted based on mNGS results, 102 (86.5%) improved, 7 (5.9%) did not respond favorably, and follow-up was lost for 9 patients (7.6%).

CONCLUSIONS

mNGS offers rapid and precise pathogen detection for patients with suspected LRTIs and shows considerable promise in diagnosing Mycobacterium tuberculosis and fungal infections. By broadening the pathogen spectrum and identifying polymicrobial infections, mNGS can significantly inform and refine antibiotic therapy.

Fungal coexistence in the skin mycobiome: a study involving Malassezia, Candida, and Rhodotorula

Evidence of fungal coexistence in humans points towards fungal adaptation to the host environment, like the skin. The human commensal Malassezia has evolved, especially residing in sebum-rich areas of the mammalian body where it can get the necessary nutrition for its survival. This fungus is primarily responsible for skin diseases like Pityriasis versicolor (PV), characterized by hypo or hyperpigmented skin discoloration and erythematous macules. In this manuscript, we report a 19-year-old healthy female who presented with a one-year history of reddish, hypopigmented, asymptomatic lesions over the chest and a raised erythematous lesion over the face. Upon clinical observation, the patient displayed multiple erythematous macules and erythematous papules over the bilateral malar area of the face, along with multiple hypopigmented scaly macules present on the chest and back. Based on the above clinical findings, a diagnosis of PV and Acne vulgaris (AV) was made. Interestingly, the patient was immunocompetent and didn't have any comorbidities. Upon isolation of skin scrapings and post-culturing, we found the existence of three fungal genera in the same region of the patient's body. We further went on to confirm the identity of the particular species and found it to represent Malassezia, Rhodotorula, and Candida. We report how Malassezia, the predominant microbial resident skin fungus, coexists with other fungal members of the skin mycobiome. This study on an applied aspect of microbiology also shows how important it is to identify the fungal organism associated with skin infections so that appropriate therapeutics can be advised to avoid cases of relapse.

Comparison of different criteria of metagenomic next-generation sequencing for the diagnosis of invasive pulmonary aspergillosis in critically ill patients

OBJECTIVE

To compare different criteria of Metagenomic Next-Generation Sequencing (mNGS) in bronchoalveolar lavage fluid (BALF) for diagnosing invasive pulmonary aspergillosis (IPA).

METHODS

We compared the diagnostic agreement and performances of six BALF mNGS-derived criteria (SDSMRN>1, SDSMRN≥3, SMRN≥10, SMRN≥50, RPM ratio≥10, and relative abundance of genus>30 %) in pneumonia patients.

RESULTS

A total of 115 patients were analyzed, with 28 identified with IPA. Diagnostic agreement among the six mNGS-derived criteria was moderate, with a Cohen's kappa of 0.577(P < 0.001). mNGS-derived criteria had low sensitivity ranging from 21.4 % to 57.1 % and high specificity from 88 % to 92 %. The optimal threshold of SDSMRN, SMRN, RPM ratio, and relative abundance of genus for diagnosing IPA were 5, 0.25, 8, and 20 %, respectively. Although using the optimal threshold, the sensitivity of mNGS is lower than 50 %.

CONCLUSIONS

All mNGS-derived criteria had low sensitivity for diagnosing IPA. A combination of mNGS and conventional mycological tests may be the best diagnostic strategy.

Synthesis and antimicrobial properties of guanidine-functionalized labdane type diterpenoids

The occurrence of increased antibiotic resistance has reduced the availability of drugs effective in the control of infectious diseases, especially those caused by various combinations of bacteria and/or fungi that are often associated with poorer patient outcomes. In the hunt for novel antibiotics of interest to treat polymicrobial diseases, molecules bearing guanidine moieties have recently come to the fore in designing and optimizing antimicrobial agents. Due to their remarkable antibacterial and antifungal activities, labdane diterpenes are also attracting increasing interest in antimicrobial drug discovery. In this study, six different guanidines prenylated with labdanic fragments were synthesized and evaluated for their antimicrobial properties. Assays were carried out against both non-resistant and antibiotic-resistant bacteria strains, while their possible antifungal activities have been tested on the yeast Candida albicans. Two of the synthesized compounds, namely labdan-8,13(R)-epoxy-15-oyl guanidine and labdan-8,13(S)-epoxy-15-oyl guanidine, were finally selected as the best candidates for further developments in drug discovery, due to their antimicrobial effects on both Gram-negative and Gram-positive bacterial strains, their fungicide action, and their moderate toxicity in vivo on zebrafish embryos. The study also provides insights into the structure-activity relationships of the guanidine-functionalized labdane-type diterpenoids.

Nanotechnology-based fungal detection and treatment: current status and future perspective

Fungal infections impose a significant impact on global health and encompass major expenditures in medical treatments. Human mycoses, a fungal co-infection associated with SARS-CoV-2, is caused by opportunistic fungal pathogens and is often overlooked or misdiagnosed. Recently, there is increasing threat about spread of antimicrobial resistance in fungus, mostly in hospitals and other healthcare facilities. The diagnosis and treatment of fungal infections are associated with several issues, including tedious and non-selective detection methods, the growth of drug-resistant bacteria, severe side effects, and ineffective drug delivery. Thus, a rapid and sensitive diagnostic method and a high-efficacy and low-toxicity therapeutic approach are needed. Nanomedicine has emerged as a viable option for overcoming these limitations. Due to the unique physicochemical and optical properties of nanomaterials and newer biosensing techniques, nanodiagnostics play an important role in the accurate and prompt differentiation and detection of fungal diseases. Additionally, nano-based drug delivery techniques can increase drug permeability, reduce adverse effects, and extend systemic circulation time and drug half-life. This review paper is aimed at highlighting recent, promising, and unique trends in nanotechnology to design and develop diagnostics and treatment methods for fungal diseases.

Distribution of Aspergillus species and risk factors for aspergillosis in mainland China: a systematic review

Background

Aspergillus, a widespread fungus in the natural environment, poses a significant threat to human health by entering the human body via the airways and causing a disease called aspergillosis. This study comprehensively analyzed data on aspergillosis in published articles from mainland China to investigate the prevalence of Aspergillus, and risk factors, mortality rate, and underlying condition associated with aspergillosis.

Methods

Published articles were retrieved from Google Scholar, PubMed, and Science Direct online search engines. In the 101 analyzed studies, 3558 Aspergillus isolates were meticulously collected and classified. GraphPad Prism 8 was used to statistically examine the epidemiology and clinical characteristics of aspergillosis.

Results

Aspergillus fumigatus was prominently reported (n = 2679, 75.14%), followed by A. flavus (n = 437, 12.25%), A. niger (n = 219, 6.14%), and A. terreus (n = 119, 3.33%). Of a total of 9810 patients, 7513 probable cases accounted for the highest number, followed by confirmed cases (n = 1956) and possible cases (n = 341). In patients, cough emerged as the most common complaint (n = 1819, 18.54%), followed by asthma (n = 1029, 10.48%) and fever (1024, 10.44%). Of total studies, invasive pulmonary aspergillosis (IPA) was reported in 47 (45.53%) studies, exhibiting an increased prevalence in Beijing (n = 12, 25.53%), Guangdong (n = 7, 14.89%), and Shanghai (n = 6, 12.76%). Chronic pulmonary aspergillosis (CPA) was reported in 14 (13.86%) studies. Among the total of 14 studies, the occurrence of CPA was 5 (35.71%) in Beijing and 3 (21.42%) in Shanghai. Allergic bronchopulmonary aspergillosis (ABPA), was reported at a lower frequency (n = 8, 7.92%), Guangdong recorded a relatively high number (n = 3, 37.5%), followed by Beijing (n = 2, 25.0%), and Shanghai (n = 1, 12.5%). Percentage of death reported: IPA had the highest rate (n = 447, 68.87%), followed by CPA (n = 181, 27.88%) and ABPA (n = 14, 2.15%). Among the aspergillosis patients, 6220 had underlying conditions, including chronic lung disease (n = 3765, 60.53%), previous tuberculosis (n = 416, 6.68%), and organ transplant or organ failure (n = 648, 10.41%). Aspergillosis was also found in patients using corticosteroid therapy (n = 622, 10.0%).

Conclusion

This review sheds light on the prevalence patterns of Aspergillus species, risk factors of aspergillosis, and gaps in surveillance that could be helpful for the control and treatment of aspergillosis and guide the researchers in future studies.

Registration

This systematic review was prospectively registered on PROSPERO: Registration ID CRD42023476870.

Blood metagenomics next-generation sequencing has advantages in detecting difficult-to-cultivate pathogens, and mixed infections: results from a real-world cohort

Background

Blood is a common sample source for metagenomics next-generation sequencing (mNGS) in clinical practice. In this study, we aimed to detect the diagnostic value of blood mNGS in a large real-world cohorts.

Methods

Blood mNGS results of 1,046 cases were collected and analyzed along with other laboratory tests. The capabilities and accuracy of blood mNGS were compared with other conventional approaches.

Results

Both the surgical department and the intensive care unit had a positive rate of over 80% in blood mNGS. The positive rate of mNGS was consistent with clinical manifestations. Among the 739 positive samples, 532 were detected as mixed infections. Compared to pathogen cultures, the negative predictive value of blood mNGS for bacteria and fungi detection was 98.9% [95%CI, 96.9%-100%], with an accuracy rate of 89.39%. When compared with polymer chain reaction, the consistency rates of blood mNGS for virus identification were remarkably high.

Conclusions

Blood mNGS have significant advantages in detecting difficult-to-cultivate bacteria or fungi, viruses, and mixed infections, which benefits patients of surgery department the most. Samples other than blood are recommended for mNGS test if a specific infection is suspected. The reporting threshold and reporting criteria of blood mNGS need to be optimized.

Invasive pulmonary aspergillosis in the intensive care unit: current challenges and best practices

The prevalence of invasive pulmonary aspergillosis (IPA) is growing in critically ill patients in the intensive care unit (ICU). It is increasingly recognized in immunocompetent hosts and immunocompromised ones. IPA frequently complicates both severe influenza and severe coronavirus disease 2019 (COVID-19) infection. It continues to represent both a diagnostic and therapeutic challenge and can be associated with significant morbidity and mortality. In this narrative review, we describe the epidemiology, risk factors and disease manifestations of IPA. We discuss the latest evidence and current published guidelines for the diagnosis and management of IPA in the context of the critically ill within the ICU. Finally, we review influenza-associated pulmonary aspergillosis (IAPA), COVID-19-associated pulmonary aspergillosis (CAPA) as well as ongoing and future areas of research.

The Clinical Impact of Metagenomic Next-Generation Sequencing for the Diagnosis of Periprosthetic Joint Infection

Background

Synovial fluid metagenomic next-generation sequencing was introduced into the diagnosis of periprosthetic joint infection (PJI) in recent years. However, the clinical impact of mNGS remains unknown. Therefore, we performed a prospective cohort study to evaluate the clinical impact of mNGS for PJI diagnosis.

Materials and Methods

Between April 2019 and April 2021, a total of 201 patients with suspected PJI were recruited in a high-volume PJI revision center. All patients underwent joint aspiration before surgeries and the obtained synovial fluids were sent to tests for the diagnosis of PJI. Based on the clinical evaluation of these patients, the patients were categorized into three groups: Group A: the mNGS reports were not acted upon. Group B: mNGS confirmed the standard diagnostic tests of PJI and generated identical clinical impact compared to standard diagnostic tests. Group C: mNGS results guided clinical therapy. Then, the concordance between synovial mNGS and cultures was analyzed. After that, multivariate regressions were performed to explore the "targeted populations" of mNGS tests.

Results

A total of 107 patients were diagnosed with PJI based on the 2014 MSIS criteria and there were 33, 123, 45 patients in the group A, B, C respectively. The predictive factors of mNGS inducing clinical impact compared to standard diagnostic tests were negative culture results (adjusted OR: 5.88), previous history of joint infection (adjusted OR: 5.97), polymicrobial PJI revealed by culture (adjusted OR: 4.39) and PJI identified by MSIS criteria (adjusted OR: 17.06).

Conclusion

When standard diagnostic tests for PJI were performed, about 22% of synovial fluid mNGS tests can change the treatment protocols built on standard diagnostic tests and affect the clinical practice. Thus, the use of synovial fluid mNGS in some "target" populations is more valuable compared to others such as patients with previous joint infection, polymicrobial PJI, and culture-negative PJI.

Evidence Level

Level I.

Interkingdom interactions between Pseudomonas aeruginosa and Candida albicans affect clinical outcomes and antimicrobial responses

Infections that involve interkingdom microbial communities, such as those between bacteria and yeast pathogens, are difficult to treat, associated with worse patient outcomes, and may be a source of antimicrobial resistance. In this review, we address co-occurrence and co-infections of Candida albicans and Pseudomonas aeruginosa, two pathogens that occupy multiple infection niches in the human body, especially in immunocompromised patients. The interaction between the pathogen species influences microbe-host interactions, the effectiveness of antimicrobials and even infection outcomes, and may thus require adapted treatment strategies. However, the molecular details of bacteria-fungal interactions both inside and outside the infection sites, are insufficiently characterised. We argue that comprehensively understanding the P. aeruginosa-C. albicans interaction network through integrated systems biology approaches will capture the highly dynamic and complex nature of these polymicrobial infections and lead to a more comprehensive understanding of clinical observations such as reshaped immune defences and low antimicrobial treatment efficacy.

Investigating Metabolic and Molecular Ecological Evolution of Opportunistic Pulmonary Fungal Coinfections: Protocol for a Laboratory-Based Cross-Sectional Study

BACKGROUND

Fungal-bacterial cocolonization and coinfections pose an emerging challenge among patients suspected of having pulmonary tuberculosis (PTB); however, the underlying pathogenic mechanisms and microbiome interactions are poorly understood. Understanding how environmental microbes, such as fungi and bacteria, coevolve and develop traits to evade host immune responses and resist treatment is critical to controlling opportunistic pulmonary fungal coinfections. In this project, we propose to study the coexistence of fungal and bacterial microbial communities during chronic pulmonary diseases, with a keen interest in underpinning fungal etiological evolution and the predominating interactions that may exist between fungi and bacteria.

OBJECTIVE

This is a protocol for a study aimed at investigating the metabolic and molecular ecological evolution of opportunistic pulmonary fungal coinfections through determining and characterizing the burden, etiological profiles, microbial communities, and interactions established between fungi and bacteria as implicated among patients with presumptive PTB.

METHODS

This will be a laboratory-based cross-sectional study, with a sample size of 406 participants. From each participant, 2 sputa samples (one on-spot and one early morning) will be collected. These samples will then be analyzed for both fungal and bacterial etiology using conventional metabolic and molecular (intergenic transcribed spacer and 16S ribosomal DNA-based polymerase chain reaction) approaches. We will also attempt to design a genome-scale metabolic model for pulmonary microbial communities to analyze the composition of the entire microbiome (ie, fungi and bacteria) and investigate host-microbial interactions under different patient conditions. This analysis will be based on the interplays of genes (identified by metagenomics) and inferred from amplicon data and metabolites (identified by metabolomics) by analyzing the full data set and using specific computational tools. We will also collect baseline data, including demographic and clinical history, using a patient-reported questionnaire. Altogether, this approach will contribute to a diagnostic-based observational study. The primary outcome will be the overall fungal and bacterial diagnostic profile of the study participants. Other diagnostic factors associated with the etiological profile, such as incidence and prevalence, will also be analyzed using univariate and multivariate schemes. Odds ratios with 95% CIs will be presented with a statistical significance set at P<.05.

RESULTS

The study has been approved by the Mbarara University Research Ethic Committee (MUREC1/7-07/09/20) and the Uganda National Council of Science and Technology (HS1233ES). Following careful scrutiny, the protocol was designed to enable patient enrollment, which began in March 2022 at Mbarara University Teaching Hospital. Data collection is ongoing and is expected to be completed by August 2023, and manuscripts will be submitted for publication thereafter.

CONCLUSIONS

Through this protocol, we will explore the metabolic and molecular ecological evolution of opportunistic pulmonary fungal coinfections among patients with presumptive PTB. Establishing key fungal-bacterial cross-kingdom synergistic relationships is crucial for instituting fungal bacterial coinfecting etiology.

TRIAL REGISTRATION

ISRCTN Registry ISRCTN33572982; https://tinyurl.com/caa2nw69.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/48014.

Metagenomic next-generation sequencing for Mycobacterium tuberculosis complex detection: a meta-analysis

Objective

Metagenomic next-generation sequencing (mNGS) has been gradually applied to the diagnosis of tuberculosis (TB) due to its rapid and highly sensitive characteristics. Despite numerous studies on this subject, their results vary significantly. Thus, the current meta-analysis was performed to assess the performance of the mNGS on tuberculosis.

Methods

PubMed, Embase, Web of Science, and The Cochrane Library were searched up to June 21, 2023. Studies utilizing the mNGS for tuberculosis detection were included. The risk of bias was assessed by QUADAS-2, and a meta-analysis was performed with STATA14.0 software.

Results

Seventeen studies comprising 3,205 specimens were included. The combined sensitivity and specificity of mNGS for clinical specimens were 0.69[0.58-0.79] and 1.00[0.99-1.00], respectively. Subgroup analysis identified sequencing platform, diagnostic criteria, study type, sample size, and sample types as potential sources of heterogeneity. Cerebrospinal Fluid (CSF) has a lower sensitivity of 0.58 (0.39-0.75). In a population with a 10% prevalence rate, the accuracy of sensitivity reached 94%.

Conclusion

Metagenomic next-generation sequencing technology exhibits high sensitivity and speed in diagnosing Mycobacterium tuberculosis. Its application in mono and mixed infections peoples shows promise, and mNGS is likely to be increasingly used to address challenges posed by Mycobacterium tuberculosis complexes in the future.

Aspergillosis and pulmonary tuberculosis co-infection in a 9-year-old with B-cell acute lymphoblastic leukemia

This case report highlights the infrequent occurrence of coinfection involving invasive aspergillosis and Mycobacterium tuberculosis (MTB) in pediatric patients. We present the case of a 9-year-old Thai girl diagnosed with B-cell acute lymphoblastic leukemia, who experienced prolonged febrile neutropenia lasting 1 month during chemotherapy. Chest computed tomography (CT) revealed lung nodules with an air crescent sign, while CT angiography of the brain detected an infected ruptured brain aneurysm, which exhibited septate hyphae with acute angle branching, consistent with invasive aspergillosis. Despite voriconazole treatment, the patient's high-grade fever and dyspnea persisted. Further investigations revealed a lung abscess and wedge resection confirmed AFB 1+ and positive MTB detection via polymerase chain reaction, leading to the initiation of combined treatment for pulmonary tuberculosis and invasive aspergillosis. Considering drug-drug interactions was an essential aspect of the management. This case report highlights challenges of coinfection between invasive aspergillosis and MTB.

Comparison of quality/quantity mNGS and usual mNGS for pathogen detection in suspected pulmonary infections

Improved metagenomic next-generation sequencing (mNGS), for example, quality/quantity mNGS (QmNGS), is being used in the diagnosis of pulmonary pathogens. There are differences between QmNGS and the usual mNGS (UmNGS), but reports that compare their detection performances are rare. In this prospective study of patients enrolled between December 2021 and March 2022, the bronchoalveolar lavage fluid of thirty-six patients with suspected pulmonary infection was assessed using UmNGS and QmNGS. The sensitivity of QmNGS was similar to that of UmNGS. The specificity of QmNGS was higher than that of UmNGS; however, the difference was not statistically significant. The positive likelihood ratios (+LR) of QmNGS and UmNGS were 3.956 and 1.394, respectively, and the negative likelihood ratios (-LR) were 0.342 and 0.527, respectively. For the co-detection of pathogens, the depth and coverage of the QmNGS sequencing were lower than those of UmNGS, while for the detection of pathogens isolated from patients with pulmonary infection, the concordance rate was 77.2%. In the eleven patients with nonpulmonary infection, only viruses were detected using QmNGS, while UmNGS detected not only viruses but also bacteria and fungi. This study provides a basis for the selection of mNGS for the diagnosis of suspected pulmonary infection.

The Fungal and Bacterial Interface in the Respiratory Mycobiome with a Focus on Aspergillus spp

The heterogeneity of the lung microbiome and its alteration are prevalently seen among chronic lung diseases patients. However, studies to date have primarily focused on the bacterial microbiome in the lung rather than fungal composition, which might play an essential role in the mechanisms of several chronic lung diseases. It is now well established that Aspergillus spp. colonies may induce various unfavorable inflammatory responses. Furthermore, bacterial microbiomes such as Pseudomonas aeruginosa provide several mechanisms that inhibit or stimulate Aspergillus spp. life cycles. In this review, we highlighted fungal and bacterial microbiome interactions in the respiratory tract, with a focus on Aspergillus spp.

Advancing Microbe Detection for Lower Respiratory Tract Infection Diagnosis and Management with Metagenomic Next-Generation Sequencing

Background

Due to limitations of traditional microbiological methods and the presence of the oropharyngeal normal flora, there are still many pathogens that cause lower respiratory tract infections (LRTIs) cannot be detected. Metagenomic next-generation sequencing (mNGS) has the potential capacity to solve this problem.

Methods

This retrospective study successively reviewed 77 patients with LRTI and 29 patients without LRTI admitted to Tianjin Medical University General Hospital, China from August 2020 to June 2021. Pathogens in bronchoalveolar lavage fluid (BALF) specimens were detected adopting mNGS and traditional microbiological assays. The diagnostic performance of pathogens was compared between mNGS and BALF culture. The value of mNGS for aetiological and clinical impact investigation in LRTI was also evaluated.

Results

Among 77 patients with LRTI, 22.1%, 40.3%, and 65.0% of cases were detected as definite or probable pathogens by culture, all conventional microbiological tests, and mNGS, respectively. Using the final diagnosis as a gold standard, mNGS exhibited a sensitivity of 76.6% (95% confidence interval [CI], 65.6-85.5%), which was considerably superior to that of BALF culture (76.6% vs 18.2%; P < 0.01); specificity of 79.3% (95% CI, 60.3-92.0%), which was similar (79.3% vs 89.7%; P = 0.38); positive-predictive value of 90.8% (95% CI, 81.0-96.5%), and negative-predictive value of 56.1% (95% CI, 39.7-71.5%). According to our data, mNGS identified potential microorganisms in 66.7% (42/63) of culture-negative samples. Among 59 patients with pathogens identified by mNGS, conventional microbiological methods confirmed pathogenic infections in less than half (28/59) cases. Within the 77 patients, 34 (44.2%) patients received pathogen-directed therapy, 7 (9.1%) patients underwent antibiotic adjustment, and 3 (3.9%) patients stopped using antibiotics due to mNGS results.

Conclusion

mNGS exhibits high accuracy in diagnosing LRTI, and combine with traditional microbiological tests, causative pathogens can be detected in approximately 70.0% of cases, thus yields a positive effect on antibiotic application.

Aspergillus infection in chronic obstructive pulmonary diseases

Chronic obstructive pulmonary disease (COPD) is a chronic airway non-specific inflammatory disease characterised by airway obstruction and alveolar destruction. In recent years, due to the extensive use of antibiotics, glucocorticoids, immunosuppressants and other drugs, pulmonary fungal infection in patients with AECOPD, especially aspergillus infection, has gradually increased. The forms of aspergillus infection present in COPD patients include sensitisation, chronic pulmonary aspergillosis (CPA) and invasive pulmonary aspergillosis (IPA). This review will summarise diagnostic and treatment of aspergillus in COPD patients.

The performance of metagenomic next-generation sequencing in diagnosing pulmonary infectious diseases using authentic clinical specimens: The Illumina platform versus the Beijing Genomics Institute platform

Introduction: Metagenomic next-generation sequencing (mNGS) has been increasingly used to detect infectious organisms and is rapidly moving from research to clinical laboratories. Presently, mNGS platforms mainly include those from Illumina and the Beijing Genomics Institute (BGI). Previous studies have reported that various sequencing platforms have similar sensitivity in detecting the reference panel that mimics clinical specimens. However, whether the Illumina and BGI platforms provide the same diagnostic performance using authentic clinical samples remains unclear. Methods: In this prospective study, we compared the performance of the Illumina and BGI platforms in detecting pulmonary pathogens. Forty-six patients with suspected pulmonary infection were enrolled in the final analysis. All patients received bronchoscopy, and the specimens collected were sent for mNGS on the two different sequencing platforms. Results: The diagnostic sensitivity of the Illumina and BGI platforms was notably higher than that of conventional examination (76.9% vs. 38.5%, p < 0.001; 82.1% vs. 38.5%, p < 0.001; respectively). The sensitivity and specificity for pulmonary infection diagnosis were not significantly different between the Illumina and BGI platforms. Furthermore, the pathogenic detection rate of the two platforms were not significantly different. Conclusion: The Illumina and BGI platforms exhibited similar diagnostic performance for pulmonary infectious diseases using clinical specimens, and both are superior to conventional examinations.

The clinical significance of in-house metagenomic next-generation sequencing for bronchoalveolar lavage fluid diagnostics in patients with lower respiratory tract infections

Objective

Metagenomic next-generation sequencing (mNGS) technology has the potential to detect a wide range of pathogenic microorganisms. However, reports on the diagnostic value and clinical significance of different platforms of mNGS for patients with lower respiratory tract infections (LRTIs) remain scarce.

Methods

A total of 306 patients with suspected LRTIs were enrolled from January 2019 to December 2021. The diagnostic performance of conventional methods and mNGS on bronchoalveolar lavage fluid (BALF) were compared. BALF mNGS was performed using a commercial and an in-house laboratory. The diagnostic value and the clinical implications of mNGS for LRTIs were analyzed for the different platforms.

Results

The positive rate of mNGS in the in-house group was higher than that in the commercial group (85.26% vs. 70.67%, p < 0.001). mNGS significantly increased the pathogen detection rate compared with conventional methods [from 70.67% vs. 22.67% (p < 0.001) to 85.26% vs. 30.77% (p < 0.001)]. The pathogens detected using mNGS included bacteria, fungi, viruses, and atypical pathogens. The in-house platform performed well on a wider spectrum of microbial distribution. Furthermore, it showed an advantage in detecting mixed pathogens in immunocompromised patients. Among the mNGS positive cases, 34 (32.0%) cases had their antibiotics adjusted in the commercial group, while 51 (38.3%) cases had a change of treatment in the in-house group. Moreover, the turnaround time of mNGS and the time from mNGS to discharge in the in-house group were significantly shorter than those in the commercial group.

Conclusion

In-house mNGS had a higher detection rate and can show a wider spectrum of pathogens, with potential benefits for the clinic by shortening the turnaround time and hospitalization, and it may be more suitable for clinical microbiology laboratories.

The diagnosis of leptospirosis complicated by pulmonary tuberculosis complemented by metagenomic next-generation sequencing: A case report

Leptospirosis is a zoonotic infection caused by the pathogenic Leptospira. Leptospirosis is transmitted mainly through contact with contaminated rivers, lakes, or animals carrying Leptospira. Human leptospirosis has a wide range of non-specific clinical manifestations ranging from fever, hypotension, and myalgia to multi-organ dysfunction, which severely hampers the timely clinical diagnosis and treatment of leptospirosis. Therefore, there is an urgent clinical need for an efficient strategy/method that can be used for the accurate diagnosis of leptospirosis, especially in critically ill patients. Here, we report a case of a 75-year-old male patient with clinical presentation of fever, cough, and diarrhea. Initial laboratory tests and a computed tomography (CT) scan of the chest suggested only tuberculosis. The patient was finally diagnosed with pulmonary tuberculosis (PTB) combined with leptospirosis by sputum Xpert MTB RIF, epidemiological investigations, and delayed serological testing. Furthermore, through metagenomic next-generation sequencing (mNGS) of clinical samples of cerebrospinal fluid (CSF), urine, plasma and sputum, the causative pathogens were identified as Mycobacterium tuberculosis complex and Leptospira spp. With specific treatment for both leptospirosis and tuberculosis, and associated supportive care (e.g., hemodialysis), the patient showed a good prognosis. This case report suggests that mNGS can generate a useful complement to conventional pathogenic diagnostic methods through more detailed etiological screening (i.e., at the level of species or species complex).

Application of metagenomic next-generation sequencing in cutaneous tuberculosis

Tuberculous infection in a skin wound is a rare but well-known condition. This study describes a child infected with tuberculosis after being wounded. Because of swelling and pain in his wrist tissue, he was admitted to the Affiliated Hospital of Jining Medical University of Shandong Province on 16 October 2021. His medical history only included a wound. He was discharged after debridement. The laboratory data were normal. Two months after surgery, his wound was still swollen and painful. Secretions from the wound were sent for metagenomic next-generation sequencing (mNGS), which revealed three reads related to the Mycobacterium tuberculosis complex group (MTBC). A diagnosis of cutaneous tuberculosis (TB) was made. The wound disappeared after anti-TB drugs were administered. This case demonstrates that, while TB presenting as a severe cutaneous wound is rare, it should be considered in the clinical diagnosis. Clinicians should also pay attention to extrapulmonary infection with MTBC in patients, particularly in some long-suffering patients, and identify the specific pathogen as soon as possible. mNGS could help to identify pathogens and facilitate early treatment, thereby improving the prognosis.

Metagenomic next-generation sequencing-guided antimicrobial treatment versus conventional antimicrobial treatment in early severe community-acquired pneumonia among immunocompromised patients (MATESHIP): A study protocol

Background

Severe community-acquired pneumonia (SCAP) is the main cause of mortality in immunocompromised patients. Compared with conventional microbiological tests (CMT), metagenomic next-generation sequencing (mNGS) can quickly and simultaneously detect a wide array of bacteria, viruses, and fungi in an unbiased manner. It is increasingly used for severe respiratory infectious diseases, especially for immunocompromised patients. However, the effects of mNGS-based antimicrobial treatment procedures on clinical outcomes in immunocompromised patients with SCAP have not been evaluated.

Methods/Design

The MATESHIP study is a prospective, multicenter, parallel-group, open-label, randomized controlled trial from 20 ICUs in university hospitals and academic teaching hospitals across Shandong Province, China. We will enroll 342 immunocompromised patients with early onset SCAP who are admitted to an intensive care unit (ICU). Participants will be randomly allocated to an mNGS-guided treatment group or a conventional treatment group (guided by CMT), according to centrally computer-based block randomization stratified by participating centers. Participants will undergo CMT tests using appropriate lower respiratory tract (LRT) and other necessary specimens, with or without mNGS tests using LRT specimens. The primary outcomes will be: (1) The relative change in Sequential Organ Failure Assessment (SOFA) score from randomization to day 5, day 7, day 10, or the day of ICU discharge/death; and (2) the consumption of antimicrobial agents during ICU stay (expressed as defined daily doses). The secondary outcome measures will be: days from randomization to initiation of definitive antimicrobial treatment; overall antimicrobial agent use and cost; total cost of hospitalization; length of ICU stay; 28- and 90-day mortality; and clinical cure rate. This study hypothesizes that mNGS-guided treatment will decrease the degree of organ dysfunction/failure, the consumption of antimicrobial agents, and mortality, while the cure rate will be increased, and the time to initiation of appropriate therapy will be advanced.

Discussion

The MATESHIP study will evaluate for the first time whether mNGS-guided antimicrobial therapy improves the outcomes of SCAP in an immunocompromised population, and provide high-level evidence on the application of mNGS in the management of this population.

Clinical Trial Registration

[ClinicalTrials.gov], identifier [NCT05290454].

Metagenomic next-generation sequencing for accurate diagnosis and management of lower respiratory tract infections

OBJECTIVES

This study aimed to evaluate the clinical value of metagenomic next-generation sequencing (mNGS) in patients with suspected lower respiratory tract infections (LRTIs).

METHODS

This retrospective study reviewed patients with suspected LRTIs in Wuhan Union Hospital. Data including demographic, laboratory, and radiological profiles; treatment; and outcomes were recorded and analyzed.

RESULTS

mNGS identified pathogenic microbes in 100/140 (71.4%) patients, although 135 (96.4%) had received empiric antibiotic treatment before the mNGS tests. Single bacterial infection (35/100, 35%) was the most common type of infection in patients with positive mNGS results, followed by single fungal infection (14/100, 14%), bacterial-viral co-infection (14/100, 14%), single viral infection (12/100, 12%), bacterial-fungal co-infection (9/100, 9%), fungal-viral co-infection (9/100, 9%), and bacterial-fungal-viral co-infection (7/100, 7%). Moreover, compared with culture test, mNGS showed higher sensitivity (63/85, 74.1% vs. 22/85, 25.9% P=0.001) and lower processing time (24 h vs 48 h). Antibiotic treatment was adjusted or confirmed based on the mNGS results in 123 (87.9%) patients, including 5 (3.6%), 33 (23.6%) and 85 (60.7%) patients in whom treatment was downgraded, upgraded and unchanged, respectively, and almost all patients, regardless of escalation, de-escalation, or no change in treatment, showed significant improvement in clinical symptoms and inflammatory indicators. Additionally, 17 (12.1%) patients were referred to Wuhan Pulmonary Hospital for further treatment because of confirmed or suspected tuberculosis.

CONCLUSIONS

mNGS could be a promising technique for microbiological diagnosis and antibiotic management, potentially improving outcomes of patients.

Next-Generation Metagenome Sequencing Shows Superior Diagnostic Performance in Acid-Fast Staining Sputum Smear-Negative Pulmonary Tuberculosis and Non-tuberculous Mycobacterial Pulmonary Disease

In this study, we explored the clinical value of next-generation metagenome sequencing (mNGS) using bronchoalveolar lavage fluid (BALF) samples from patients with acid-fast staining (AFS) sputum smear-negative pulmonary tuberculosis (PTB) and non-tuberculous mycobacterial pulmonary disease (NTM-PD). Data corresponding to hospitalized patients with pulmonary infection admitted to the hospital between July 2018 and July 2021, who were finally diagnosed with AFS sputum smear-negative PTB and NTM-PD, were retrospectively analyzed. Bronchoscopy data as well as mNGS, Xpert, AFS (BALF analysis), and T-SPOT (blood) data, were extracted from medical records. Thereafter, the diagnostic performances of these methods with respect to PTB and NTM-PD were compared. Seventy-one patients with PTB and 23 with NTM-PD were included in the study. The sensitivities of mNGS, Xpert, T-SPOT, and AFS for the diagnosis of PTB were 94.4% (67/71), 85.9% (61/71), 64.8% (46/71), and 28.2% (20/71), respectively, and the diagnostic sensitivity of mNGS combined with Xpert was the highest (97.2%, 67/71). The specificity of Xpert was 100%, while those of AFS and T-SPOT were 73.9% (17/23) and 91.3% (21/23), respectively. Further, the 23 patients with NTM-PD could be identified using mNGS, and in the population with immunosuppression, the sensitivities of mNGS, Xpert, T-SPOT, and AFS were 93.5% (29/31), 80.6% (25/31), 48.4% (15/31), and 32.3% (10/31), respectively, and the diagnostic sensitivity of mNGS combined with Xpert was the highest (100%, 31/31). The specificities of Xpert and T-SPOT in this regard were both 100%, while that of AFS was 40% (2/5). Furthermore, using mNGS, all the NTM samples could be identified. Thus, the analysis of BALF samples using mNGS has a high accuracy in the differential diagnosis of MTB and NTM. Further, mNGS combined with Xpert can improve the detection of MTB, especially in AFS sputum smear-negative samples from patients with compromised immune states or poor responses to empirical antibiotics.

Application of metagenomic next-generation sequencing for bronchoalveolar lavage diagnostics in patients with lower respiratory tract infections

Objective

Metagenomic next-generation sequencing (mNGS) has the potential to overcome the shortcomings of traditional culture methods. This study aimed to assess the diagnostic value of mNGS in patients with lower respiratory tract infections (LRTIs).

Methods

This retrospective observational study sequentially enrolled 47 patients with LRTIs admitted to Shenzhen Hospital of Southern Medical University between February 2019 and November 2020. Pathogens in bronchoalveolar lavage fluid (BALF) samples were investigated to compare diagnoses by mNGS with culture methods.

Results

Compared with culture methods, mNGS had a diagnostic sensitivity of 80% and a specificity of 35.13% with an agreement rate of 44.68% between these two methods. mNGS significantly increased the pathogen detection rate.

Conclusions

mNGS may show some advantages in identifying a wide range of LRTI pathogens, improving the sensitivity for viruses and atypical pathogens. The clinical application of NGS technology is worth looking forward to.