Metagenomic next-generation sequencing (mNGS) for diagnosis of invasive fungal infectious diseases: a narrative review

Introduction

Invasive infections caused by opportunistic fungi have high morbidity and mortality, especially in immunocompromised patients. It is estimated that more than 1.6 million people die of fungal diseases annually (1). Therefore, accurate and timely identification of pathogenic fungi is essential for patient management and can significantly improve the prognosis. Conventional diagnostic tests include microscopy, culture (through biochemical phenotyping, matrix-assisted laser desorption/ionization (MALDI) time-of-flight mass spectrometry analysis, or nucleic acid probes), antigen and/or antibody immunology, and specific polymerase chain reaction (PCR) testing microbial nucleic acid (2,3). Among them, the molecular diagnostic analysis provides a fairly efficient and quick (usually less than 2 hours) way to diagnose the most common fungal infections (4,5). However, almost all traditional microbiological tests currently in use are able to detect only one or a limited number of pathogens at a time or require a successful culture of microorganisms from clinical specimens.

In recent years, metagenomic next-generation sequencing technology (mNGS) has been increasingly used by clinicians as a culture-independent and hypothesis-free method to diagnose pathogens (6,7). It can directly obtain the microbial nucleic acid from various samples, including sputum, bronchoalveolar lavage fluid (BALF), blood, cerebrospinal fluid (CSF), pleural fluid, ascites, pus, and tissue samples (5,8,9). All potential pathogens with known genomic sequences, such as bacteria, viruses, fungi, parasites, mycoplasma and leptospira, are unbiasedly detected in theory (6,10). At present, mNGS could release results on an average of 24 hours after sampling, generally no longer than 48 hours (11). The workflow of mNGS consists of two components including experimental operations (sample preprocessing, nucleic acid extraction, library preparation and sequencing) and bioinformatic analysis (database comparison, report generation and result interpretation), which demands a high level of the technical platform and personnel quality (7). Although this new technology greatly facilitates the clinical identification of pathogens, it remains a second-line option because of lengthy procedures and microbial contamination introduced during experimental operations. A recent advance has been achieved in mNGS, for example, shorter turnaround time, reduced exogenous contamination, improved workflow and sensitivity (12-15). The potency of the mNGS test using cell-free DNA from of 182 body fluids was evaluated using two sequencing platforms. The test sensitivity and specificity of identification were 91% and 89% for fungi, respectively, using Illumina sequencing assigned to the second-generation sequencing; and 91% and 100% for fungi, respectively, based on nanopore sequencing attributed to the third-generation sequencing (16). Moreover, an outstanding advantage of mNGS lies in that its detection rate is less likely to be affected by prior antimicrobial treatment than by traditional methods (17,18). Thus, it has a high potential value in accurately diagnosing and treating clinical infectious diseases. We present the following article in accordance with the Narrative Review reporting checklist (available at https://dx.doi.org/10.21037/jlpm-21-25).

Methods

To obtain information on mNGS testing for the diagnosis of fungal infections, we searched PubMed, Embase, CNKI and Wanfang, using the search terms (“fungi” OR “fungus” OR “fungal infection*” OR “fungal disease*”) AND (“mNGS” OR “metagenomic next-generation sequencing” OR “metagenomic NGS” OR (“cell free” AND (“NGS” OR “next-generation sequencing”))) without date (up to June 16, 2021). After carefully examining the title, abstract, and full text, we found a few articles related to this subject. Most evidence is primarily derived from case reports or small-scale retrospective studies (Table 1 and Table S1). In the diagnosis of IFDs, mNGS has been used for severe or difficult infections mainly caused by Pneumocystis jirovecii, Cryptococcus spp., Histoplasma capsulatum, Aspergillus spp. and Candida spp. Here, we reviewed the literature to explore the role of mNGS in the diagnosis of fungal infections by highlighting the species most commonly isolated in these studies.

mNGS for diagnosis of Pneumocystis jirovecii

Pneumocystis jirovecii is an opportunistic pathogen that can cause fatal pneumocystis pneumonia (PCP). The incidence of PCP in patients with organ transplantation, autoimmune diseases, tumors, etc. is on the rise (35). Therefore, to reduce mortality, there is an urgent need for timely diagnosis and prompt PCP-specific treatment (36). The traditional diagnostic method for PCP detection is based on microscopic identification of cysts or trophozoites of Pneumocystis jirovecii in stained samples collected from the respiratory tract of patients. This method has low sensitivity and is affected by many factors, such as staining protocol, specimen collection, and pathogen load (37,38). Meanwhile, although the serum 1,3-β-D-glucan (BDG) test has a certain sensitivity to Pneumocystis jirovecii, it lacks specificity (39).

There are studies taking advantage of mNGS to find Pneumocystis jirovecii in samples obtained from the respiratory tract (19,40-42). However, as Pneumocystis jirovecii colonizes the surface of human type I alveolar cells, it is difficult for mNGS to determine an appropriate threshold between infection and colonization when confronted with samples from the respiratory tract (40,43). Excitingly, Zhang et al. combined the sequencing order of Pneumocystis jirovecii (ranking top 15) with the relative sequencing proportion in fungi (higher than 85%) and speculated a promising cutoff value for mNGS in the diagnosis of PCP (20). More samples need to be collected to verify the validity and clinical significance of this value.

In addition, mNGS was used to detect Pneumocystis jirovecii in the peripheral blood samples of patients with renal disease receiving immunosuppressive therapy, associated with the clinical manifestations and radiological features to determine the final diagnosis of PCP (21). Although studies have shown that blood mNGS is less sensitive than BALF mNGS in the detection of bacteria and fungi, it has unique advantages in certain circumstances (44,45). It is not only non-invasive, simple, and fast, but also free from the influence of Pneumocystis jirovecii colonizing the respiratory tract. Sensitivity and specificity are higher than those of the fungal G test in combination with the detection of lactate dehydrogenase detection (94.59% vs. 89.19% and 100% vs. 56.0%) (21). Interestingly, of two mild PCP patients whose peripheral blood samples were initially negative, one became positive after a week, which indicated that Pneumocystis jirovecii could penetrate the local infection site into the peripheral blood when the immune system is damaged (20,21). This suggests that for seriously ill patients who cannot tolerate invasive procedures, future high-throughput sequencing of peripheral blood samples may be an alternative and, to some degree, a marker for disease severity (22,23,46). Apart from simply identifying fungi, the application of mNGS also revealed mixed pulmonary infections in a single assay, and co-pathogens, such as the new coronavirus SARS-CoV-2, Mycobacterium tuberculosis, and Human cytomegalovirus were previously detected with one or more fungal species by mNGS (24,25,47,48). Mover, the Human Cytomegalovirus is the most common co-infected pathogens of Pneumocystis jirovecii infections (19,24). Therefore, mNGS is a promising technology to detect co-pathogens of mixed infection and provides information to improve culture conditions and develop a reasonable antifungal plan.

mNGS for diagnosis of Cryptococcus spp.

Cryptococcal meningitis (CM) occurs primarily in immunocompromised individuals, particularly those infected with HIV. There are over one million new cases of CM every year globally, among which about 600,000 people die within three months of infection (49). The Cryptococcus neoformans/Cryptococcus gattii species complexes dominate, leading to over 90% of human cryptococcosis cases. However, significant differences between the two are found in epidemiology, clinical manifestations, progression, and treatment strategies. In HIV-negative patients, C. gattii s.l. has a higher proportion of neurological complications, low response to antifungals, long-term therapies, and more surgical interventions (50,51). At present, traditional laboratory diagnostic methods, including India ink staining and cryptococcal antigen (CrAg) detection in CSF, cannot distinguish the two. Although l-Canavanine glycine bromothymol blue (CGB) agar and MALDI-TOF-MS can be used to differentiate C. neoformans and C. gattii, they must be based on a successful culture (52). The mNGS has been confirmed to be effective in identifying C. neoformans and C. gattii, which could reduce the misdiagnosis of CM in immunocompetent patients, promote the accurate treatment of central nervous system (CNS) infections, and considerably reduce the abuse of antifungal agents and resistance to fungi (26,53).

Cryptococcal osteomyelitis is very rare. Since X-rays are not specific and serum CrAg show low sensitivity, the diagnosis usually depends on culture or biopsy histopathology. However, negative culture results are not uncommon in clinical practice (54). Zhang et al. reported that an HIV-negative patient with an intact immune system, initially wrongly diagnosed as a soft tissue tumor of ribs, was eventually identified as a case of cryptococcal osteomyelitis via mNGS (55). Given that mNGS is based on the unknown to the known screening process, it often provides significant diagnostic information when faced with an atypical clinical presentation. Yet, it is simply used as an auxiliary means for traditional pathogenic diagnosis at present, due to limited reporting of mNGS applications in cryptococcosis and small sample sizes (27,28,53,56).

mNGS for diagnosis of Histoplasma capsulatum

Histoplasmosis is an endemic disease that mainly occurs in North America (especially the Midwest and Southeastern United States). It is generally asymptomatic or self-limiting, but may also cause severe symptomatic disease. For example, disseminated histoplasmosis is a progressive extrapulmonary disease that can be life-threatening if not treated. Therefore, a rapid diagnosis will make it possible to detect and curb infectious outbreaks at an earlier stage, saving lives and reducing medical costs (57). However, when the disease occurs in non-endemic areas, clinicians are often unaware of it, leaving them neglected and misdiagnosed (58).

Although the microscopy and culture are still recognized as the golden standards for the diagnosis of histoplasmosis, the morphology of H. capsulatum is similar to that of pathogens such as Talaromyces marneffei and Leishmania under a microscope, which frequently confuses inexperienced lab technicians (59). The detection of galactomannan antigen in body fluids provides a rapid and sensitive method for the diagnosis of histoplasmosis and was included in the second edition of the WHO Basic in Vitro Diagnostic List in 2019 (60). The rate of antigen detection in patients with progressive disseminated histoplasmosis or acute pulmonary histoplasmosis is as high as 80% to 95%, but cross-reactions occur most commonly in patients with blastomycosis (90%), penicilliosis marneffei (80%), coccidioidomycosis (60%), and aspergillosis (10%) (61).

The mNGS is a valuable tool for detecting pathogens in non-endemic areas of endemic diseases such as histoplasmosis, and reducing the misdiagnosis and missed cases, especially in cases where clinicians are not initially aware of the disease. For example, mNGS was applied to BALF specimens from an individual originally diagnosed with tuberculosis in China, and ultimately identified as H. capsulatum (62). Recently, Zhang et al. performed mNGS on blood and bone marrow specimens from five patients infected with H. capsulatum, Leishmania, or T. marneffei but presenting similar clinical symptoms. They found that mNGS had 100% diagnostic accuracy, remarkably higher than that of traditional methods including bone marrow smear, microscopy, and culture (29). As well, direct pathogen identification from blood samples makes mNGS a less invasive option for patients with contraindications to bone marrow puncture. Moreover, during the follow-up period, it was detected in three patients that the decrease in the abundance of sequencing reads was consistent with the clinical recovery stage. In other words, mNGS would be expected to monitor disease progression and assess therapeutic effectiveness, a common practice in clinical work, despite limited data and the need for a lot of time to confirm (18,63,64).

mNGS for diagnosis of Aspergillus spp.

Invasive pulmonary aspergillosis (IPA) is a potentially fatal opportunistic infection that usually occurs in patients with hematological malignancies. The 2016 American Society of Infectious Diseases Diagnostic and Management Practice Guidelines for Aspergillosis stated that for certain adults and children (hematological malignancies, HSCT) patients, it is recommended to detect galactomannan (GM) in serum and bronchoalveolar lavage (BAL), as an accurate marker for the diagnosis of IPA (65). Recently, the number of cases of IPA in non-neutropenia patients, especially those with chronic obstructive pulmonary disease (COPD), has been increasing (66). Unfortunately, for this group of people, the diagnosis of IPA is usually more difficult, because circulating biomarkers show a relatively low sensitivity (67). Three cases of severe pneumonia, two of which had a history of COPD and asthma, were reported and identified as Aspergillus fumigatus by mNGS in BALF samples, further emphasizing the diagnostic role of mNGS in non-neutropenic IPA (68). Interestingly, Ge et al. described a patient whose clinal and radiological characteristics overlapped with the IPA, serum β-D-glucan was positive, and sputum culture mimicked Aspergillus fumigatus, but who was eventually identified as Nocardia Gelsenkirchen in both the bronchoalveolar lavage culture and mNGS results (69). It has been shown that mNGS can sometimes assist in differentially diagnosing IPA when the results of traditional tools appear confusing (30,31,70).

In addition, mNGS has important advantages in identifying unknown, rare, and atypical pathogenic microorganisms, which facilitates the discovery of novel disease-causing fungi in humans. For the first time, mNGS helped Dai et al. to save a 36-year-old woman by the timely detection of Aspergillus flavus leading to a rare but lethal fungal endocarditis (71). Wilson and his colleagues successfully resolved seven cases with diagnostic challenges for chronic meningitis with the help of mNGS and reported the first case of CNS vasculitis resulting from Aspergillus oryzae (27). Furthermore, in thirty Bell’s palsy (BP) cases, Chang et al. discovered human herpesvirus 7 (HHV-7) and Aspergillus through analyzing the results generated by mNGS in samples obtained from the facial nerve epithelium, suggesting that more attention be paid to both pathogens in the pathogenesis of BP (32).

mNGS for diagnosis of Candida spp.

Invasive candidiasis is the most common fungal disease in intensive care unit (ICU), accounting for 70–90% (72). Once considering fungal infections, they often use specific diagnostic methods to screen Candida species at first. Moreover, the rapid development of diagnostic technology based on the genetic sequence of known pathogens often works well. Consequently, the need for mNGS in candidiasis may be less urgent. Candida spp. are often reported as strains of colonization or mixed infection strains occurring in the preliminary report generated by mNGS, which requires further interpretation by clinicians. When conventional diagnostic tools fail to identify the pathogen, clinicians can turn to mNGS for help in diagnosis. For instance, when confronted with a negative culture result in a chronic disseminated candidiasis case, Jin et al. successfully identified the pathogen-Candida tropicalis via mNGS and it was further confirmed by calcofluor white staining (73). Additionally, Wilson et al. reported the fourth case of meningitis caused by Candida dubliniensis using mNGS technology, whereas the two 18S rRNA and 16S rRNA PCR tests in cerebrospinal fluid were negative (27). Importantly, mNGS is written into the Chinese consensus on the diagnosis and management of adult candidiasis, providing a basis for the etiological diagnosis of difficult or rare infectious diseases (74).

Challenges for mNGS in the diagnosis of IFDs

While many studies and case reports have confirmed that the success of mNGS in improving the diagnosis of IFDs, mNGS has not been included in the revised EORTC/MSG definitions (75,76) because of its limited standardization and validation. Several challenges remain in the routine implementation of mNGS technology in IFDs. Firstly, mNGS assays cost several hundreds to thousands of dollars per analytical sample, more than that for many other clinical tests, which is one of the main factors limiting their widespread use in the clinic (4). Secondly, although it has been reported that mNGS has superior fungal sensitivity and specificity to culture and histopathology (33,41,77), the sensitivity of mNGS depends heavily on the background and decreases in the high background, mostly from the human host or microbiome (4,67). In human samples, pathogen sequencing reads account for only a small portion of all mNGS results, while over 95% of sequencing results indicate human reads (11,78). As a result, removing human DNA sequences to enrich pathogen reads is a major direction in mNGS for microbial diagnosis (79). Ji et al. proposed an approach to effectively reduce host DNA contamination in CSF samples by collecting saponin-treated supernatant for DNA extraction, which has greatly improved the unique mNGS reads of Cryptococcus (P<0.01) (80). Meanwhile, the specificity of mNGS is commonly limited by contamination with DNA fragments from various microorganisms on the surfaces of reagents and consumables (10,12,48). A more stringent reporting threshold would be appropriate to increase specificity. Scoring algorithms such as Z-SCORE or SIQ-SCORE were designed in an attempt to separate sequences from the pathogen from those of environmental microbial sequences, which greatly simplifies the data interpretation (27,81,82). Thirdly, mNGS showed poor efficiency in extracting nucleic acid from pathogenic microorganisms with thicker cell walls, such as fungi (83). The efficient extraction method is a key step in achieving truly impartial sequencing of a sample because fungi need significant disruption of the cell walls to efficiently lyse the organisms for nucleic acid release. Some researchers have optimized the extraction conditions of Aspergillus RNA, while preserving the detection of bacterial and viral nucleic acid by mNGS (34). Lee et al. reported a simple and reproducible method extracting high molecular weight (∼20 kb) genomic DNA from filamentous fungi for use in next-generation sequencing (NGS) (84). Last but not least, detection of nucleic acids by the mNGS itself does not prove that an identified microorganism is responsible for the disease, and results should be interpreted in the clinical context (4,7,77). When using the mNGS test, it is best to consider the findings in conjunction with other diagnostic tests and clinical feature.

Summary

mNGS can be used for samples from multiple sources, identifying unknown, rare, and newly emerging pathogens, distinguishing mixed pathogenic microorganisms, and subsequently narrowing them down to a certain level of genus. It could help guide treatment decisions for a group of people who are intolerant to invasive operations, immunosuppressed, or critically ill. An ideal diagnostic method should include the following characteristics: the use of non-invasive biological specimens, high precision, good reproducibility, and short processing time. Furthermore, the related technology should be easily available and low-cost, thus it can be promoted in many places. However, mNGS has certain limitations in terms of the diagnosis of IFDs, so it is only used as an auxiliary diagnostic tool for traditional detection methods. In the near future, with the gradual determination of unified standard procedures or interpretation standards, improved nucleic acid extraction schemes, reduced turnaround time, and substantial cost reductions, mNGS is expected to become a routine diagnostic method of fungal infections.

Acknowledgments

We would like to thank Professor Dongmei Li (Georgetown University Medical Center, Washington, DC, USA) for kind assistance in editing our manuscript.

Funding: This work was supported by the National Science and Technology Major Project (No. 2018ZX10734404), the Chinese Academy of Medical Sciences Initiative for Innovative Medicine (No. 2016-I2M-3-021) and the National Natural Science Foundation of China (No. 82073455).

Footnote

Reporting Checklist: The authors have completed the Narrative Review reporting checklist. Available at https://dx.doi.org/10.21037/jlpm-21-25

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://dx.doi.org/10.21037/jlpm-21-25). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

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