Diagnosis of Invasive Mold Infections: History
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Subjects: Microbiology
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Invasive mold infections are increasingly recognized in immunocompromised hosts. Current diagnostic techniques are limited by low sensitivity and prolonged turnaround times.

  • fungal diagnostics
  • mycoses
  • invasive candidiasis
  • invasive mold infections
  • invasive aspergillosis
  • mucormycosis
  • transplant
  • immunocompromised host
  • non-culture diagnostics
  • culture independent

1. Introduction

In recent years, the incidence of invasive mold infections (IMI) has increased in parallel with advances in chemotherapies, immunosuppression in solid organ and hematopoietic cell transplantation, and critical care technologies. Invasive mold infections (IMI) are a major cause of morbidity and mortality in immunocompromised patients. The diagnosis of IMI has traditionally relied on culture, direct microscopy, and histopathology demonstrating hyphal invasion[1]. Conventional culture techniques are frequently insensitive, have prolonged turnaround times (TAT) on the order of days to weeks, and may require invasive sampling. Colony morphology and microscopic identification from culture and histopathology are laborious, require skilled mycologists, and are not practical for the identification of rare species[2]. An increase in the diversity of pathogenic species makes phenotypic identification challenging, particularly as the number of clinical mycologists declines. Precise species identification is needed given the variability of anti-fungal drug susceptibility profiles even between closely related organisms. Thus, non-culture-based techniques have gained interest, particularly those with rapid turnaround times to allow for early clinical detection and decision making[3].

2. Diagnosis of Invasive Mold Infections

Aspergillus is the most common opportunistic mold, though Mucorales, FusariumScedosporium/Lomentospora/Pseudallescheria, and Paecilomyces/Purpureocillium are increasingly seen in clinical settings, especially in patients receiving mold-active anti-fungal prophylaxis[4]. In the absence of microbiologic data, the diagnosis is typically made clinically, with consideration of host factors (e.g., solid organ or hematopoietic cell transplantation (HCT), prolonged steroid use or exposure to immunosuppressants that impair T-lymphocyte function), radiographic appearance, and mycological evidence (e.g., antigen detection)[1]. In practice, patients are frequently treated with empiric anti-fungal therapies without a definitive diagnosis, which can result in unnecessary exposure to toxic and costly medications or inadequate treatment in the setting of drug resistance.

Ribosomal sequencing for tissue diagnosis is frequently performed on clinical samples, though sensitivity is variable. Immunohistochemistry may be applied to tissue samples to help distinguish between Aspergillus and Mucorales based on morphological features, without waiting for positive cultures[5]. Proteomic techniques such as matrix-assisted laser desorption/ionization time of flight mass spectrometry (MALDI-TOF) are increasingly being adapted to rapidly make a species diagnosis from prepared cultures in culture-positive cases, which comprise the minority of invasive mold infections overall[6][7]. In the absence of culture data, fungal markers such as BDG and galactomannan, while non-invasive, are limited by poor sensitivity and specificity and do not apply to all species of mold.

Development and clinical validation of diagnostic tests to detect mold infections is often hindered by the relatively low frequency of cases seen at any single institution and the need for an array of different specimens (blood, serum, plasma, BAL fluid, urine, etc.) for validation[8]. Unlike bacteria, working with mold specimens can be technically challenging. They may be unevenly distributed in samples, exist in different forms at various stage of growth, and have hardy cell wall structures that can make nucleic acid extraction difficult[9]. Debate over nomenclature of mold phylogenies also hinders streamlined standardization. In addition to the need for rapid techniques to identify mold species from cultures, rapid non-invasive diagnostic tests are needed to detect IMI and ideally, antifungal resistance, to better guide antifungal therapy.

Here we will discuss the current  and emerging diagnostic techniques applied to diagnosing invasive mold infections, including pan-fungal diagnostic strategies as well as specific techniques emerging for Aspergillus, Mucorales, and other less common molds.

3. Pan-fungal diangostics

3.1 Ribosomal Sequencing

Clinical specimens, including tissue, blood, BAL fluid, and CSF, can be sent to reference laboratories for ribosomal sequencing for species-level identification. Amplification of highly conserved regions of fungal ribosomal RNA including the internal transcribed spacers 1 and 2 (ITS1 and ITS2) and the D1/D2 regions of the 28S rRNA gene, followed by sequencing, can allow for identification of a broad array of fungal species including rare organisms[10]. The sensitivity and specificity of pan-fungal sequencing techniques vary widely depending on the method of DNA extraction, the type and preparation of clinical sample, and whether hyphal forms are visible on histopathology [11][12][13]. Formalin fixation can reduce assay sensitivity due to DNA degradation (e.g., from 100% to 90% in one study [11]). Samples collected from non-sterile sites may reveal non-pathogenic commensal organisms of uncertain clinical significance[14]. The method of sampling is also important, where open resection provides a better diagnostic yield than FNA or core needle biopsy[11]. Most importantly, sensitivity is highest (>90%)[11] if fungal forms are visualized on histopathology[11][15]. Because of this, the EORTC/MSG recommends sequencing from tissue samples only if fungal elements are present[15]. Use of pan-fungal PCR in samples where fungal forms are not visualized on a clinical sample may help to augment a diagnosis if positive, but must fit clinically and cannot be used to exclude disease, particularly in patients receiving anti-mold therapies where assay sensitivity may be further limited[10]. Lack of technical standardization has been addressed by recent attempts to protocolize PCR methods from tissue samples (https://fpcri.eu/, accessed on 1 December 2020).

3.2 Next-Generation Sequencing

Next-generation sequencing (NGS), also called high-throughput/massively parallel sequencing, is a non-culture-based technique that allows for the application of both targeted and whole-genome sequencing (WGS). There are a number of available sequencing technologies and data analytic software packages[16]. All human and microbial DNA is extracted from clinical samples (including blood, CSF, BAL fluid, etc.), without a priori knowledge of a particular target. Sequencing is performed using a “shotgun approach,” human DNA is removed, and results are compared to existing nucleotide sequences from in pre-formed databases. This can allow for identification of esoteric species, as well as potential resistance mutations, provided the sequences exist in a reference database. TAT is typically 12–24 h once it has been received by the reference laboratory[17].

NGS techniques enable evolutionary tracing and were used to identify outbreaks of various fungal infections including cases of Exserohilum rostratum meningitis related to contaminated injections[18]Sarocladium kiliense bloodstream infections from contaminated anti-emetic medication[19], and invasive wound mucormycosis [20]. There are a few commercially available NGS platforms that detect cell-free DNA (mcf-DNA-seq) from plasma (Karius, Redwood, CA, USA), DNA and RNA from cerebrospinal fluid (University of California, USA) and respiratory secretions (IDbyDNA, Salt Lake City, UT, USA) to diagnose fungal pathogens (in addition to bacterial and viral pathogens)[16]. A small number of studies have been performed to address the diagnostic utility of this technique in IMI.

Small studies have shown good concordance of NGS with biopsy proven IFI[21][22] One retrospective cohort study of 82 Karius tests ordered for suspected infection (representing 66 patents) in a varied patient population reported a positive impact only 6/82 cases (7.3%), a negative impact in 3 cases (3.7%), no impact in 71 cases (86.6%), and was indeterminate in 2 (2.4%)[23]. Thus far, the majority of studies are limited by small sample size, the inclusion of patients with suspected IFI from varied anatomic sites (e.g., lung, skin, sinuses) and lack of a control group. In one recent retrospective case–control study of 114 HCT recipients, overall sensitivity of NGS for proven/probable IFD was 51%, 31% for Aspergillus and 79% for non-Aspergillus IFD. There were two proven IFD cases where Karius testing was positive and both serum and BAL galactomannans were negative, and only one case of Aspergillus detected in a patient with possible IFD. Only one patient with possible IFD had a pathogen detected. Specificity was reported at 95%. Thus, this diagnostic modality has low to moderate sensitivity but high specificity in patients with proven or probably pulmonary IFD. Sensitivity was improved when combined with GM or when samples were taken within 3 days of a clinical diagnosis. This assay is potentially useful as an adjunctive diagnostic technique in patients with a very high likelihood of proven or probable pulmonary IFD, with slightly better performance in non-Aspergillus IFD, although the assay cost and need for specimen shipping to a central laboratory may be barriers to adoption[24].

There are significant limitations to unbiased NGS techniques. Commercially available assays are typically expensive and though results are typically available within 24 h, TATs may be delayed due to the need to ship samples to specialized laboratories. Capital equipment costs, the need for highly trained laboratory staff, and comprehensive reference databases have been major limitations to adoption of this technique outside highly specialized reference laboratories. Positive results may represent contamination or identify non-pathogenic commensal organisms. Validation for rare species due to need for positive controls can be challenging[10][17]. Overall, low sensitivity precludes the use of NGS for stand-alone testing or to rule out infection. NGS may be useful as an adjunctive test in cases where invasive biopsy is contraindicated[25]. With decreasing costs and expanding databases, this technique is likely to be implemented more broadly[10][17]. The clinical application and stewardship of NGS sequencing technologies for diagnosing infection still requires clarification.

3.3 MALDI-TOF MS

Species-level identification of molds grown in culture is frequently desired in order to guide antifungal choice. MALDI-TOF MS platforms are widely used in clinical microbiology laboratories to identify bacteria, yeast, and have recently been applied for the detection of mold. A sample colony from a culture plate is placed onto a MALDI-TOF MS target plate and placed in an ionization chamber, generating a mass spectrum based on the mass-to-charge ratios of highly conserved ribosomal proteins, generating signature peaks that are then compared to reference samples within a database. This technique requires no prior knowledge of the organism and can be performed on multiple samples simultaneously, giving results in <10 min. MALDI-TOF MS has the advantage of being able to identify a wide spectrum of species from commercial and in-house databases[26].

Application of MALDI-TOF MS to filamentous fungi has evolved over the past ten years, but time-consuming sample preparation techniques, which can vary between manufacturers, and limitations of spectral databases and available isolate challenge sets have delayed its widespread use. The mechanism of culturing mold isolates and the stage of fungal growth may impact the identification, as different levels of mycelia and spores are present in liquid versus solid media, which have different proteomic fingerprints[2][6]. A number of studies have reported identification rates of filamentous fungi ranging between 15% and 97%, depending on the platform and database used. There was a notable trend towards using lower species-level cut offs, a log(score) that refers to the level of similarity between an unknown tested specimen and reference sample[27], to achieve higher detection rates with only marginal increases in false positivity. A score of ≥1.7 rather than the manufacturer recommended cut off of ≥2 has been widely adopted for fungal isolates[2][27] There are a number of commercially available platforms and significant differences between their curated databases, including the range of species included and the nomenclature used for species identification, which can make generalization somewhat challenging[2].

MALDI-TOF MS is a reasonable alternative to conventional microbiological and molecular methods for species identification from positive cultures, though lack of standardized processing techniques and incomplete database spectra are still limiting factors. Additional molecular diagnostic techniques are needed in cases that cannot be identified.

3.4 Other Spectroscopy Techniques

A variety of other spectroscopy techniques have been applied to fungal diagnostics in the research setting and have the potential for both accurate yeast and mold identification, particularly for use on direct clinical samples (rather than subcultured isolates).

Rapid evaporative ionization mass spectrometry (REIMS) performs MS analysis of the metabolites produced by heating up cells to a gas-phase and identifies microbes based on their lipid content. This technique demonstrated 98–100% accuracy in identifying Candida isolates[28][29]. REIMS has been coupled with electrosurgery and is used for immediate intraoperative tissue identification for malignant tumors[30]. Based on these proof of concept studies, its application in fungal identification is a potential area of future exploration. For example, intra-operative identification of invasive mold infections could allow for immediate therapeutic decisions.

Fourier transform infrared (FT-IR) spectroscopy and Raman spectroscopy (RS)[31] use vibrational spectroscopy-based biochemical profiling to detect pathogen species at extremely high resolution. Raman spectroscopy has extremely high specificity for pathogen detection, though enhancement techniques, such as surface-enhanced Raman spectroscopy (SERS) are required to achieve good sensitivity. SERS uses metallic nano-structures to enhance scattering and could be a potentially useful tool for sensitive biomarker detection and can be applied directly to clinical specimens. SERS has been coupled with PCR techniques (e.g., used in the commercially available RenDx Fungiplex®, Renishaw Diagnostics assay, Glasgow, UK) for the detection of Candida and Aspergillus, but its clinical utility is not yet well defined[32][33] Interference-enhanced Raman spectroscopy is a slightly less sensitive but more economically feasible technique (easily fabricated substrates and long-term stability of substrates). It has been applied to the diagnosis of aspergillosis via detection of TAFC fungal siderophore (see Section 4.4) from urine samples with a <3 h TAT[34].

PCR coupled with electrospray-ionization mass spectrometry (PCR/ESI-MS) is a promising technique for identification of species-specific sequences in specimens containing visible hyphae and has been successfully applied to the detection of Mucorales in one study, though could theoretically be applied to other species. TAT is about 6h, although implementation is limited by the significant expense and limited availability of this technique[35].

3. Diagnosis of Aspergillus

Aspergillus is a ubiquitous airborne environmental mold that can cause invasive aspergillosis (IA) in immunosuppressed patients. Patients at risk for Aspergillus infection include those with prolonged neutropenia, solid organ transplantation, HCT, or exposure to steroids or T-lymphocyte immunosuppressants. For pulmonary aspergillosis, the most common manifestation of Aspergillus infection, respiratory cultures, bronchoalveolar lavage (BAL) and lung biopsy are typically performed to obtain cultures. BAL yield is reduced in patients on anti-fungal therapy or those that have peripheral lesions. Culture is insensitive, can reveal colonization rather than infection, and can sometimes take days to weeks to yield a result[36]. Identification is often further delayed due to the need for sporulation in order to make a phenotypic identification. Fungal elements may be seen with calcofluor white staining. On histopathology, Gomori methenamine silver or periodic acid-Schiff staining are frequently used, though these stains are not specific for Aspergillus[37].

3.1. Serologies and Biomarkers

Clinicians currently heavily rely on serum fungal markers including the BDG and galactomannan (GM) to help establish or provide supporting evidence for the diagnosis of invasive aspergillosis in the absence of culture data. BDG and galactomannan are often ordered in parallel in patients with suspected aspergillosis. 

The 1,3-B-D-glucan (BDG) assay (Fungitell, East Falmouth, MA, USA), which was FDA cleared in 2004, is the most commonly used fungal antigen assay in clinical laboratories. BDG is a chromogenic quantitative enzyme-linked immunosorbent assay (EIA), designed to detect (1-3)-β-d-glucan polysaccharide cell wall component of pathogenic fungi including Aspergillus, Pneumocystis jiroveci, and Candida. BDG, has a relatively high negative predictive value for excluding IFI, but is neither sensitive nor specific for Aspergillus. Sensitivity and specificity vary widely in reported literature (33-100%, 36-94%, respectively) (144). 

The galactomannan Platelia Aspergillus EIA/Ag (Bio-Rad, Redmond, WA, USA) assay is a monoclonal Ab immunoassay that detects branched β-1,5-linked galactofuranose side chains of the α-linked mannosyl backbone of the large GM polysaccharide, a component of the Aspergillus cell wall[38]. At an optical density index (ODI) of 0.5 the pooled sensitivity and specificity for proven or probable IA in serum samples is approximately 78% and 85%, respectively. Sensitivity decreases and specificity increases at higher ODIs. The GM assay is fairly specific for Aspergillus, can be used in serial monitoring to assess treatment response [39][40], and is FDA-cleared for detection in serum and BAL fluid, though it can be found in other bodily fluids (CSF, pleural fluid). Cross-reactivity in patients with histoplasmosis, fusariosis, and talaromycosis can occur[41]. The diagnostic performance of GM is dependent on the optical density cut off used to interpret positivity, the net state of immunosuppression of the host (higher sensitivity in neutropenic patients), and the presence of anti-fungal therapy[37]. Batch testing and use of reference laboratories can delay TAT to days, which can limit its use in early clinical decision making. There are a number of alternative biomarker detection kits that have come onto the market but still need proper validation.

Antibody testing for Aspergillus is available, though its application for the diagnosis of IPA is limited, given the weak and variable immune response elicited in neutropenic or immunosuppressed patients. Antibody testing is available for patients with suspected allergic or chronic cavitary aspergillosis, but will not be reviewed here[42][43].

3.2 Lateral Flow Devices

Immunochromatographic lateral flow assays for IPA have been developed for POC (TAT ~ 15–30 min), rapid testing. The AspLFD (OLM Diagnostics, Newcastle upon Tyne, UK,) and the Aspergillus galactomannan LFA (IMMY) are two such assays, currently available in Europe. The LFD assay uses a JF5 antibody to detect a mannoprotein antigen released in serum and BAL during active fungal growth[44][45]. Like the GM-EIA, the LFA assay targets galactomannan but uses two mABs which may provide greater sensitivity[46]. It has demonstrated good qualitative agreement with GM-EIA[47]. Both assays show better performance in BAL fluid than serum, and among hematology patients as compared to other patient subgroups[46]. Cross-reactivity with other fungal infections, including histoplasmosis (similarly to standard GM–EIA testing), has been observed, and is a potential limitation[48]. Anti-mold agents reduce sensitivity[46], thus use in patients on antifungal prophylaxis or treatment may be constrained. LFDs are inexpensive to produce and can provide rapid easy-to-interpret results without the need for specialized equipment or training. Further clinical studies are needed for broader application.

3.3. Aspergillus PCR-Based Testing

An array of PCR-based assays have been developed for the clinical diagnosis of IA. The updated 2019 Cochrane review including 29 studies of PCR from whole blood, serum, or plasma, showed a pooled sensitivity of 79.2% and specificity of 79.6% for PCR-based testing. For two or more consecutive positive results, sensitivity was lower at 59.6% and specificity improved to 95.1%[49]. Based on a 2012 systematic review, BAL-PCR had a reported sensitivity and specificity of 77% and 94%, respectively[50].

The implementation of PCR testing on serum, whole blood, and BAL fluid into clinical practice was previously limited by lack of standardization of techniques, with notable variability in the methods of DNA extraction, primer use, and differences in reference criteria to define a positive result. The European Aspergillus PCR Initiative (EAPCRI) group was formed in 2006 to develop methodological guidelines for technique standardization[51]. White et al. 2015 showed that when comparing EAPRCI non-compliant protocols with compliant ones, sensitivity increased from 85% to 98% and specificity from 82% to 87%[51]. Based on the performance of these assays and improved standardization, EORTC/MSG incorporated the use of Aspergillus PCR into the diagnosis of probable invasive aspergillosis in September 2020. To meet mycological criteria, patients must have blood (serum, whole blood, or plasma) PCR positivity on two consecutive tests, BAL PCR positivity on two or more tests, or at least one positive test from blood and one from BAL testing[15].

The majority of assays described in the literature were developed in-house, but there are a number of commercial assays now available in a multiplex format that detect Aspergillus sp. and resistance mutations[10], including the most prevalent cyp51A gene mutations associated with azole resistance (R34/L98H and TR46/Y121F/T289A mutations) [10][36]. In addition to rapid diagnosis of resistance mutations, PCR amplification allows for the potential to diagnose mixed strains of Aspergillus with both azole-susceptible and resistant isolates that would not be detected by conventional phenotypical susceptibility testing[52]. Expansion of commercial tests to include probes for additional resistance mutations is needed. Roth et al. reviews the diagnostic performance of commercially available Aspergillus PCR tests, Including the MycAssay Aspergillus® (Myconostica Ltd., Cambridge UK), AsperGenius® (Pathonostics, Maastricht, The Netherlands), among others[32].

PCR allows for direct detection of Aspergillus DNA in blood, serum, or BAL fluid and has moderate accuracy for screening high risk patients with suspected IA. It has an excellent negative predictive value (~95% with either single or serial testing) and improved positive predictive value with serial performance and/or in combination with other biomarkers[49]. Compared to GM, PCR is more sensitive but slightly less specific, while serial positive PCR is less sensitive but more specific. Unlike GM and BDG which are released during active disease, Aspergillus DNA may be detected in the absence of active angio-invasive disease. Though this assay does not distinguish between active disease and colonization, it does provide a potential opportunity for early initiation of either pre-emptive therapy in those with high clinical suspicion but inconsistent radiographic findings, or antifungal prophylaxis in at-risk individuals [49][53]. PCR could be incorporated as part of a screening strategy for ruling out disease, rather than initiating empiric antifungal therapy in high-risk groups[49].

There are still a number of limitations with the use of PCR. The impact of antifungal therapy on test sensitivity is not well defined. False positivity (up to 12% [54]) due to cross reactivity with other mold species or environmental contamination remains a concern. Though the meta-analyses described include a spectrum of patients, the majority of PCR-based studies have been applied to patients with hematologic malignancies, thus limiting some extrapolation to solid organ transplant patients or other hosts where the burden of disease may be less, and assays potentially less sensitive[44].

3.4. Radiotracers

The diagnosis of IPA requires chest imaging, though abnormalities on basic chest tomograms (CT) are often non-specific and difficult to distinguish from other forms of invasive mold infections. Combining CT and positron emission tomography (PET) with [18F]fluorodeoxyglucose ([18F]FDG), a marker of metabolic activity, helps to localize an area of abnormality but does not distinguish between malignancy, infection, or inflammation[55]. A number of radiotracers have been developed to better image IPA and could theoretically be useful as adjunctive diagnostic tools to visualize infected tissue and monitor clinical response to treatment but have not yet been applied in the clinical setting[56]. For example, in preclinical murine experiments with two 99mTc labeled Aspergillus-specific fungal rRNA-targeted Morpholino oligomers (MORF) probes, researchers observed that probe accumulation is two times higher in infected lungs than non-infected lungs on single-photon emission tomography (SPECT)/CT imaging[57]. Another imaging technique that has been developed combines microPET/CT with detection of iron-scavenging siderophores, specific iron-chelating molecules secreted by fungi, which act as virulence factors. A. fumigatus and A. nidulans produce the siderophores triacetylfusarinine C (TAFC) and ferricrocin (FC), which, when combined with 68Ga, a radionuclide with complexing properties similar to that of iron, can be visualized on microPET/CT[58][59]. The high specificity of mAbs for diagnosing IA makes antibody-guided imaging techniques another attractive and highly specific way to both detect and visualize IA. In a murine model of neutrophil depleted mice infected with Aspergillus, [64Cu]DOTA-labeled mAb mJF5, a monoclonal antibody specific to a mannoprotein antigen of Aspergillus sp. released during active fungal growth, was effective in localizing an area of the lung infection with PET/MRI while discriminating between active infection and colonization from other pathologies[55].  

3.5 Volatile Metabolite Profiles of Aspergillus

Another non-invasive method of Aspergillus detection utilizes exhaled air for detection of volatile organic compounds (VOCs) released in breath in the setting of IA[60][61]. A proof-of-concept study demonstrated distinct VOC signatures with 100% sensitivity and 83% specificity in high-risk hematologic malignancy patients using “electronic nose” technology[60]. In a prospective study of 64 patients with hematologic malignancies, detection of specific secondary metabolite volatile organic compounds using thermal desorption/gas chromatography/mass spectrometry (α-trans-bergamotene, β-trans-bergamotene, a β-vatirenene-like sesquiterpene, and trans-geranylacetone) had a sensitivity and specificity of 94% and 93%, respectively, for IA[61]. Volatile metabolite profiles could be useful biomarkers for rapid and inexpensive diagnosis of IFI, but are pending further clinical validation. The relationship between metabolite signature and nodule size, the kinetics of these metabolites with antifungal therapy, and distinguishing between colonization versus infection are all areas of potential exploration[61]. This technology could be applied for the detection of other pathogenic molds and endemic fungi[62].

4. Diagnosis of Mucorales

Invasive mucormycosis, caused by filamentous fungi of the order Mucorales, is the second most common invasive mold infection after invasive aspergillosis[63] Mucorales causes significant morbidity and mortality in immunocompromised hosts and in patients with poorly controlled diabetes mellitus and ketoacidosis. Diagnosis is usually made by culture and histopathology and is essential to guide mold active therapy, as several first-line antifungal agents lack therapeutic efficacy against Mucorales. Given the low yield of biopsy and culture, patients are often started on empiric therapy for suspected disease with broad spectrum antifungal therapy that covers both Aspergillus and Mucorales, as distinguishing between these two entities without definitive confirmation can be challenging. Molecular methods are typically employed for species identification and detection when cultures are negative and can detect potentially mixed infections[64]. There are no commercially available serological tests, though this is an area of active development.

4.1. Mucorales-Specific PCR

In addition to PCR from tissue biopsy samples, serum and BAL PCR assays have been used to detect Mucorales from clinical samples. BAL PCR may be a useful adjunctive test to allow for earlier initiation of antifungal therapy and detection in culture-negative BAL samples[65]. One study of BAL fluid from 374 immunosuppressed patients with pneumonia used a combined approach of three qPCR assays on BAL fluid. A total of 24 patients had a positive BALPCR; 23/24 met radiologic criteria for IMI, of which 7 had proven and 3 had probable mucormycosis, 5 had other fungal infections, and 8 had possible IFD. Sensitivity and specificity for probable or biopsy-proven pulmonary mucormycosis was 100% and 97%, respectively. Only 2/24 PCR positive samples had concordant positive cultures [65]. PCR combined with high-resolution melt analysis (PCR/HRMA) has also been described, and showed a sensitivity and specificity of 100% and 93% in one study of 99 BAL samples (9 of which were positive)[66]. MucorGenius (Pathonostics, Maastricht, The Netherlands), is a non-FDA approved semi-quantitative PCR assay that targets 28S rRNA in BAL and biopsy samples and can be run in parallel with AsperGenius, with a TAT of 3 h [67][68].

Non-invasive techniques to detect Mucorales PCR from plasma, serum, or urine are desired to avoid biopsy and even BAL in critically ill patients unable to tolerate these procedures. qPCR using genera-specific, broad-range, or multiplex PCR from serum has been described as successful in detecting infection as early as up to 28 days prior to mycological diagnosis[64][65][69][70] and up to 3 days earlier than classic radiographic findings[71]. Millon et al. reported a sensitivity between 81% and 92% when combining 3 genera-specific real-time qPCR assays, with notably higher sensitivities using larger sample volumes (1mL)[69]. Sensitivity of PCR is reduced in those receiving antifungal therapy, a notable limitation[69][71]. Persistent DNA detection despite antifungal initiation was associated with higher mortality, suggesting a possible application for serial sampling in prognostication or treatment monitoring [69]. PCR techniques could be considered for screening high risk patients[69] and efforts to standardize PCR techniques will allow for broader application in the future[64].

4.2. Other Biomarkers

The detection of mold-reactive CD154+ cells has been suggested as a non-invasive (TAT ~24h) way to detect invasive Mucorales. Mucorales-specific T cells were identified via enzyme-linked immunospot (ELISpot) and were found to be reactive only in patients with proven invasive mucormycosis (IM)[72][73].  Steinbach et al. quantified mold-reactive CD4/CD69/CD154+ lymphocytes with flow cytometry and found a sensitivity of 100% and a specificity of 81% for Mucorales infection in a cohort of 115 at risk patients (4 with proven, 3 with probable, and 44 with possible IMI), with a TAT of about 24h. Patients with T cell counts <4500 were excluded, thus limiting extrapolation to those with severe bone marrow suppression and T-cell dysfunction. Given the underlying immune deficiencies in patients at risk for mucormycosis, this is a significant limitation to this approach[74].

Burnham-Marusich et al. developed a pan-fungal monoclonal antibody, 2DA6, that reacts with purified mannans of different fungi, including Rhizopus, Mucor, and Aspergillus and can be detected using enzyme-linked immunosorbent assay (ELISA). A lateral flow format for this test has been developed. Such an assay may be useful in addition to the BDG assay, which is typically negative in Rhizopus and Mucor infections[75]. Human validation studies are still needed.

5. Conclusions

With the growing threat of invasive fungal infections and concurrent rise in anti-fungal resistance, new technologies are emerging for rapid species identification and earlier detection of IFD. Advancements in proteomics and molecular techniques have allowed for highly discriminatory species identification. Non-culture-based methods including enhanced imaging modalities, multiplex panels, NGS metagenomic sequencing, volatile metabolites, and new immunologic biomarkers could overcome the prolonged turnaround times and limited sensitivity of traditional techniques, while potentially obviating the need for invasive sampling.

This entry is adapted from the peer-reviewed paper 10.3390/jof7020127

References

  1. De Pauw, B.; Walsh, T.J.; Donnelly, J.P.; Stevens, D.A.; Edwards, J.E.; Calandra, T.; Pappas, P.G.; Maertens, J.; Lortholary, O.; Kauffman, C.A.; et al. Revised Definitions of Invasive Fungal Disease from the European Organization for Research and Treatment of Cancer/Invasive Fungal Infections Cooperative Group and the National Institute of Allergy and Infectious Diseases Mycoses Study Group (Eortc/Msg) Consensus Group. Clin. Infect. Dis. 2008, 46, 1813–1821.
  2. Patel, R. A Moldy Application of Maldi: Maldi-Tof Mass Spectrometry for Fungal Identification. J. Fungi 2019, 5, 4.
  3. Kozel, T.R.; Wickes, B. Fungal Diagnostics. Cold Spring Harb. Perspect. Med. 2014, 4, a019299.
  4. Lass-Flörl, C.; Cuenca-Estrella, M. Changes in the epidemiological landscape of invasive mould infections and disease. J. Antimicrob. Chemother. 2017, 72, i5–i11.
  5. Son, H.J.; Song, J.S.; Choi, S.; Jung, J.; Kim, M.J.; Chong, Y.P.; Lee, S.O.; Choi, S.H.; Kim, Y.S.; Woo, J.H.; et al. A Comparison of Histomorphologic Diagnosis with Culture- and Immunohistochemistry-Based Diagnosis of Invasive Aspergillosis and Mucormycosis. Infect. Dis. 2020, 52, 279–283.
  6. Li, Y.; Wang, H.; Zhao, Y.-P.; Xu, Y.-C.; Hsueh, P.-R. Evaluation of the Bruker Biotyper Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry System for Identification of Aspergillus Species Directly from Growth on Solid Agar Media. Front. Microbiol. 2017, 8, 1209.
  7. Li, Y.; Wang, H.; Hou, X.; Huang, J.-J.; Wang, P.-C.; Xu, Y.-C. Identification by Matrix-Assisted Laser Desorption Ionization–Time of Flight Mass Spectrometry and Antifungal Susceptibility Testing of Non-Aspergillus Molds. Front. Microbiol. 2020, 11, 922.
  8. Arvanitis, M.; Anagnostou, T.; Fuchs, B.B.; Caliendo, A.M.; Mylonakis, E. Molecular and Nonmolecular Diagnostic Methods for Invasive Fungal Infections. Clin. Microbiol. Rev. 2014, 27, 490–526.
  9. Klimek-Ochab, M.; Brzezińska-Rodak, M.; Żymańczyk-Duda, E.; Lejczak, B.; Kafarski, P. Comparative study of fungal cell disruption—Scope and limitations of the methods. Folia Microbiol. 2011, 56, 469–475.
  10. Kidd, S.E.; Sharon, C.A.; Chen, W.M.; Catriona, L.H. A New Age in Molecular Diagnostics for Invasive Fungal Disease: Are We Ready? Front. Microbiol. 2020, 10, 2903.
  11. Gomez, C.A.; Budvytiene, I.; Zemek, A.J.; Banaei, N. Performance of Targeted Fungal Sequencing for Culture-Independent Diagnosis of Invasive Fungal Disease. Clin. Infect. Dis. 2017, 65, 2035–2041.
  12. Trubiano, J.A.; Dennison, A.M.; Morrissey, C.O.; Chua, K.Y.; Halliday, C.L.; Chen, S.C.-A.; Spelman, D. Clinical utility of panfungal polymerase chain reaction for the diagnosis of invasive fungal disease: A single center experience. Med. Mycol. 2015, 54, 138–146.
  13. Rickerts, V.; Khot, P.D.; Myerson, D.; Ko, D.L.; Lambrecht, E.; Fredricks, D. Comparison of quantitative real time PCR with Sequencing and ribosomal RNA-FISH for the identification of fungi in Formalin fixed, paraffin-embedded tissue specimens. Bmc Infect. Dis. 2011, 11, 202.
  14. Zeller, I.; Schabereiter-Gurtner, C.; Mihalits, V.; Selitsch, B.; Barousch, W.; Hirschl, A.M.; Makristathis, A.; Willinger, B. Detection of fungal pathogens by a new broad range real-time PCR assay targeting the fungal ITS2 region. J. Med. Microbiol. 2017, 66, 1383–1392.
  15. Donnelly, J.P.; Chen, S.C.; Kauffman, C.A.; Steinbach, W.J.; Baddley, J.W.; Verweij, P.E.; Clancy, C.J.; Wingard, J.R.; Lockhart, S.R.; Groll, A.H.; et al. Revision and Update of the Consensus Definitions of Invasive Fungal Disease from the European Organization for Research and Treatment of Cancer and the Mycoses Study Group Education and Research Consortium. Clin. Infect. Dis. 2020, 71, 1367–1376.
  16. Deurenberg, R.H.; Bathoorn, E.; Chlebowicz, M.A.; Couto, N.; Ferdous, M.; García-Cobos, S.; Kooistra-Smid, A.M.D.; Raangs, E.C.; Rosema, S.; Veloo, A.C.M.; et al. Application of next generation sequencing in clinical microbiology and infection prevention. J. Biotechnol. 2017, 243, 16–24.
  17. Gu, W.; Miller, S.; Chiu, C.Y. Clinical Metagenomic Next-Generation Sequencing for Pathogen Detection. Annu. Rev. Pathol. Mech. Dis. 2019, 14, 319–338.
  18. Litvintseva, A.P.; Hurst, S.; Gade, L.; Frace, M.A.; Hilsabeck, R.; Schupp, J.M.; Gillece, J.D.; Roe, C.; Smith, D.; Keim, P.; et al. Whole-Genome Analysis of Exserohilum Rostratum from an Outbreak of Fungal Meningitis and Other Infections. J. Clin. Microbiol. 2014, 52, 3216–3222.
  19. Etienne, K.A.; Roe, C.C.; Smith, R.M.; Vallabhaneni, S.; Duarte, C.; Escandón, P.; Castañeda, E.; Gómez, B.L.; De Bedout, C.; López, L.F.; et al. Whole-Genome Sequencing to Determine Origin of Multinational Outbreak of Sarocladium kiliense Bloodstream Infections. Emerg. Infect. Dis. 2016, 22, 476–481.
  20. Garcia-Hermoso, D.; Criscuolo, A.; Lee, S.C.; Legrand, M.; Chaouat, M.; Denis, B.; Lafaurie, M.; Rouveau, M.; Soler, C.; Schaal, J.V.; et al. Outbreak of Invasive Wound Mucormycosis in a Burn Unit Due to Multiple Strains of Mucor Circinelloides, F. Circinelloides Resolved by Whole-Genome Sequencing. mBio 2018, 9, 2.
  21. Hong, D.K.; Blauwkamp, T.A.; Kertesz, M.; Bercovici, S.; Truong, C.; Banaei, N. Liquid biopsy for infectious diseases: Sequencing of cell-free plasma to detect pathogen DNA in patients with invasive fungal disease. Diagn. Microbiol. Infect. Dis. 2018, 92, 210–213.
  22. Armstrong, A.E.; Rossoff, J.; Hollemon, D.; Hong, D.K.; Muller, W.J.; Chaudhury, S. Cell-free DNA next-generation sequencing successfully detects infectious pathogens in pediatric oncology and hematopoietic stem cell transplant patients at risk for invasive fungal disease. Pediatr. Blood Cancer 2019, 66, e27734.
  23. Hogan, C.A.; Yang, S.; Garner, O.B.; Green, D.A.; Gomez, C.A.; Bard, J.D.; Pinsky, B.A.; Banaei, N. Clinical Impact of Metagenomic Next-Generation Sequencing of Plasma Cell-Free DNA for the Diagnosis of Infectious Diseases: A Multicenter Retrospective Cohort Study. Clin. Infect. Dis. 2020.
  24. Hill, J.A.; Dalai, S.C.; Hong, D.K.; Ahmed, A.A.; Ho, C.; Hollemon, D.; Blair, L.; Maalouf, J.; Keane-Candib, J.; Stevens-Ayers, T.; et al. Liquid Biopsy for Invasive Mold Infections in Hematopoietic Cell Transplant Recipients with Pneumonia Through Next-Generation Sequencing of Microbial Cell-Free DNA in Plasma. Clin. Infect. Dis. 2020.
  25. Blauwkamp, T.A.; Thair, S.; Rosen, M.J.; Blair, L.; Lindner, M.S.; Vilfan, I.D.; Kawli, T.; Christians, F.C.; Venkatasubrahmanyam, S.; Wall, G.D.; et al. Analytical and clinical validation of a microbial cell-free DNA sequencing test for infectious disease. Nat. Microbiol. 2019, 4, 663–674.
  26. De Carolis, E.; Posteraro, B.; Lass-Flörl, C.; Vella, A.; Florio, A.; Torelli, R.; Girmenia, C.; Colozza, C.; Tortorano, A.; Sanguinetti, M.; et al. Species identification of Aspergillus, Fusarium and Mucorales with direct surface analysis by matrix-assisted laser desorption ionization time-of-flight mass spectrometry. Clin. Microbiol. Infect. 2012, 18, 475–484.
  27. Normand, A.-C.; Cassagne, C.; Gautier, M.; Becker, P.; Ranque, S.; Hendrickx, M.; Piarroux, R. Decision criteria for MALDI-TOF MS-based identification of filamentous fungi using commercial and in-house reference databases. Bmc Microbiol. 2017, 17, 1–17.
  28. Cameron, S.J.S.; Bolt, F.; Perdones-Montero, A.; Rickards, T.; Hardiman, K.; Abdolrasouli, A.; Burke, A.; Bodai, Z.; Karancsi, T.; Simon, D.; et al. Rapid Evaporative Ionisation Mass Spectrometry (REIMS) Provides Accurate Direct from Culture Species Identification within the Genus Candida. Sci. Rep. 2016, 6, 36788.
  29. Strittmatter, N.; Rebec, M.; Jones, E.A.; Golf, O.; Abdolrasouli, A.; Balog, J.; Behrends, V.; Veselkov, K.; Takats, Z. Characterization and Identification of Clinically Relevant Microorganisms Using Rapid Evaporative Ionization Mass Spectrometry. Anal. Chem. 2014, 86, 6555–6562.
  30. Balog, J.; Sasi-Szabó, L.; Kinross, J.; Lewis, M.R.; Muirhead, L.J.; Veselkov, K.; Mirnezami, R.; Dezső, B.; Damjanovich, L.; Darzi, A.; et al. Intraoperative Tissue Identification Using Rapid Evaporative Ionization Mass Spectrometry. Sci. Transl. Med. 2013, 5, 194.
  31. OPATHY Consortium; Arastehfar, A.; Boekhout, T.; Butler, G.; De Cesare, G.B.; Dolk, E.; Gabaldóln, T.; Hafez, A.; Hube, B.; Hagen, F.; et al. Recent trends in molecular diagnostics of yeast infections: From PCR to NGS. Fems Microbiol. Rev. 2019, 43, 517–547.
  32. Rath, P.-M.; Steinmann, J. Overview of Commercially Available PCR Assays for the Detection of Aspergillus spp. DNA in Patient Samples. Front. Microbiol. 2018, 9, 740.
  33. White, P.L.; Hibbitts, S.J.; Perry, M.D.; Green, J.; Stirling, E.; Woodford, L.; McNay, G.; Stevenson, R.; Barnes, R.A. Evaluation of a Commercially Developed Semiautomated PCR-Surface-Enhanced Raman Scattering Assay for Diagnosis of Invasive Fungal Disease. J. Clin. Microbiol. 2014, 52, 3536–3543.
  34. Pahlow, S.; Orasch, T.; Žukovskaja, O.; Bocklitz, T.; Haas, H.; Weber, K. Rapid detection of the aspergillosis biomarker triacetylfusarinine C using interference-enhanced Raman spectroscopy. Anal. Bioanal. Chem. 2020, 412, 6351–6360.
  35. Alanio, A.; Garcia-Hermoso, D.; Mercier-Delarue, S.; Lanternier, F.; Gits-Muselli, M.; Menotti, J.; Denis, B.; Bergeron, A.; Legrand, M.; Lortholary, O.; et al. Molecular identification of Mucorales in human tissues: Contribution of PCR electrospray-ionization mass spectrometry. Clin. Microbiol. Infect. 2015, 21, e1–e5.
  36. Husain, S.; Camargo, J.F. Invasive Aspergillosis in solid‐organ transplant recipients: Guidelines from the American Society of Transplantation Infectious Diseases Community of Practice. Transplant. 2019, 33, e13544.
  37. Ullmann, A.; Aguado, J.; Arikan-Akdagli, S.; Denning, D.; Groll, A.; Lagrou, K.; Lass-Flörl, C.; Lewis, R.; Munoz, P.; Verweij, P.; et al. Diagnosis and management of Aspergillus diseases: Executive summary of the 2017 ESCMID-ECMM-ERS guideline. Microbiol. Infect. 2018, 24, e1–e38.
  38. Marino, C.; Rinflerch, A.; De Lederkremer, R.M. Galactofuranose antigens, a target for diagnosis of fungal infections in humans. Sci. OA 2017, 3, 199.
  39. Kovanda, L.L.; Kolamunnage-Dona, R.; Neely, M.; Maertens, J.; Lee, M.; Hope, W.W. Pharmacodynamics of Isavuconazole for Invasive Mold Disease: Role of Galactomannan for Real-Time Monitoring of Therapeutic Response. Infect. Dis. 2017, 64, 1557–1563.
  40. Kovanda, L.L.; Desai, A.V.; Hope, W.W. Prognostic value of galactomannan: Current evidence for monitoring response to antifungal therapy in patients with invasive aspergillosis. Pharmacokinet. Pharmacodyn. 2017, 44, 143–151.
  41. Hoenigl, M.; Salzer, H.J.F.; Raggam, R.B.; Valentin, T.; Rohn, A.; Woelfler, A.; Seeber, K.; Linkesch, W.; Krause, R. Impact of galactomannan testing on the prevalence of invasive aspergillosis in patients with hematological malignancies. Mycol. 2012, 50, 266–269.
  42. Agarwal, R.; Chakrabarti, A.; Shah, A.; Gupta, D.; Meis, J.F.; Guleria, R.; Moss, R.; Denning, D.W.; ABPA complicating asthma ISHAM working group Allergic bronchopulmonary aspergillosis: Review of literature and proposal of new diagnostic and classification criteria. Exp. Allergy 2013, 43, 850–873
  43. Iain, D.P.; Malcolm Richardson, M.; Denning, D.W. Antibody Testing in Aspergillosis—Quo Vadis? Mycol. 2015, 53, 417–439.
  44. Villalobos, A.P.-C.; Husain, S. Aspergillus in Solid Organ and Stem Cell Transplant Patients: Emerging Options for Diagnosis and Management. Transpl. Infect. 2020, 1–32, doi:10.1007/978-3-030-01751-4_44.-1.
  45. Pan, Z.; Fu, M.; Zhang, J.; Zhou, H.; Fu, Y.; Zhou, J. Diagnostic Accuracy of a Novel Lateral-Flow Device in Invasive Aspergillosis: A Meta-Analysis. Med. Microbiol. 2015, 64, 702–707.
  46. Mercier, T.; Dunbar, A.; De Kort, E.A.; Schauwvlieghe, A.; Reynders, M.; Guldentops, E.; Blijlevens, N.M.A.; Vonk, A.G.; Rijnders, B.; Verweij, P.E.; et al. Lateral flow assays for diagnosing invasive pulmonary aspergillosis in adult hematology patients: A comparative multicenter study. Mycol. 2020, 58, 444–452.
  47. White, L.P.; Price, J.S.; Posso, R.; Cutlan-Vaughan, M.; Vale, L.; Backx, M. Evaluation of the Performance of the IMMY sona Aspergillus Galactomannan Lateral Flow Assay When Testing Serum to Aid in Diagnosis of Invasive Aspergillosis. Clin. Microbiol. 2020, 58, doi:10.1128/jcm.00053-20.
  48. Marr, K.A.; Datta, K.; Mehta, S.; Ostrander, D.B.; Rock, M.; Francis, J.; Feldmesser, M. Urine Antigen Detection as an Aid to Diagnose Invasive Aspergillosis. Infect. Dis. 2018, 67, 1705–1711.
  49. Cruciani, M.; Mengoli, C.; Barnes, R.; Donnelly, J.P.; Loeffler, J.; Jones, B.L.; Klingspor, L.; Maertens, J.; Morton, C.O.; White, L.P. Polymerase Chain Reaction Blood Tests for the Diagnosis of Invasive Aspergillosis in Immunocompromised People. Cochrane Database Rev. 2019, 9, .
  50. Avni, T.; Levy, I.; Sprecher, H.; Yahav, D.; Leibovici, L.; Paul, M. Diagnostic Accuracy of PCR Alone Compared to Galactomannan in Bronchoalveolar Lavage Fluid for Diagnosis of Invasive Pulmonary Aspergillosis: A Systematic Review. Clin. Microbiol. 2012, 50, 3652–3658.
  51. White, L.P.; Wingard, J.R.; Bretagne, S.; Löffler, J.; Patterson, T.F.; Slavin, M.A.; Barnes, R.A.; Pappas, P.G.; Donnelly, J.P. Aspergillus Polymerase Chain Reaction: Systematic Review of Evidence for Clinical Use in Comparison with Antigen Testing. Infect. Dis. 2015, 61, 1293–1303.
  52. Schauwvlieghe, A.F.A.D.; Vonk, A.G.; Buddingh, E.P.; Hoek, R.A.S.; Dalm, V.A.; Klaassen, C.H.W.; Rijnders, B.J.A. Detection of azole-susceptible and azole-resistant Aspergillus coinfection by cyp51A PCR amplicon melting curve analysis. Antimicrob. Chemother. 2017, 72, 3047–3050.
  53. White, P.L.; Wiederhold, N.P.; Loeffler, J.; Najvar, L.K.; Melchers, W.; Herrera, M.; Bretagne, S.; Wickes, B.; Kirkpatrick, W.R.; Barnes, R.A.; et al. Comparison of Nonculture Blood-Based Tests for Diagnosing Invasive Aspergillosis in an Animal Model. Clin. Microbiol. 2016, 54, 960–966.
  54. Luong, M.-L.; Clancy, C.J.; Vadnerkar, A.; Kwak, E.J.; Silveira, F.P.; Wissel, M.C.; Grantham, K.J.; Shields, R.K.; Crespo, M.; Pilewski, J.; et al. Comparison of an Aspergillus Real-time Polymerase Chain Reaction Assay with Galactomannan Testing of Bronchoalvelolar Lavage Fluid for the Diagnosis of Invasive Pulmonary Aspergillosis in Lung Transplant Recipients. Infect. Dis. 2011, 52, 1218–1226
  55. Rolle, A.-M.; Hasenberg, M.; Thornton, C.R.; Solouk-Saran, D.; Männ, L.; Weski, J.; Mäurer, A.; Fischer, E.; Spycher, P.R.; Schibli, R.; et al. ImmunoPET/MR imaging allows specific detection of Aspergillus fumigatus lung infection in vivo. Natl. Acad. Sci. USA 2016, 113, E1026–33.
  56. Thornton, C.R. Molecular Imaging of Invasive Pulmonary Aspergillosis Using ImmunoPET/MRI: The Future Looks Bright. Microbiol. 2018, 9, 691.
  57. Wang, Y.; Chen, L.; Liu, X.; Cheng, D.; Liu, G.; Liu, Y.; Dou, S.; Hnatowich, D.J.; Rusckowski, M. Detection of Aspergillus fumigatus pulmonary fungal infections in mice with 99mTc-labeled MORF oligomers targeting ribosomal RNA. Med. Biol. 2013, 40, 89–96.
  58. Petřík, M.; Franssen, G.M.; Haas, H.; Laverman, P.; Hörtnagl, C.; Schrettl, M.; Helbok, A.; Lass-Flörl, C.; Decristoforo, C. Preclinical evaluation of two 68Ga-siderophores as potential radiopharmaceuticals for Aspergillus fumigatus infection imaging. J. Nucl. Med. Mol. Imaging 2012, 39, 1175–1183.
  59. Petřík, M.; Haas, H.; Dobrozemsky, G.; Lass-Flörl, C.; Helbok, A.; Blatzer, M.; Dietrich, H.; Decristoforo, C. 68 Ga-Siderophores for PET Imaging of Invasive Pulmonary Aspergillosis: Proof of Principle. Nucl. Med. 2010, 51, 639–645.
  60. De Heer, K.; Van Der Schee, M.P.; Zwinderman, K.; Berk, I.A.H.V.D.; Visser, C.E.; Van Oers, R.; Sterk, P.J. Electronic Nose Technology for Detection of Invasive Pulmonary Aspergillosis in Prolonged Chemotherapy-Induced Neutropenia: A Proof-of-Principle Study. Clin. Microbiol. 2013, 51, 1490–1495.
  61. Koo, S.; Thomas, H.R.; Daniels, S.D.; Lynch, R.C.; Fortier, S.M.; Shea, M.M.; Rearden, P.; Comolli, J.C.; Baden, L.R.; Marty, F.M. A Breath Fungal Secondary Metabolite Signature to Diagnose Invasive Aspergillosis. Infect. Dis. 2014, 59, 1733–1740.
  62. Koshy, S.; Ismail, N.; Astudillo, C.L.; Haeger, C.M.; Aloum, O.; Acharige, M.T.; Farmakiotis, D.; Baden, L.R.; Marty, F.M.; Kontoyiannis, D.P.; et al. Breath-Based Diagnosis of Invasive Mucormycosis (IM). Open Forum Infect. Dis. 2017, 4, S53–S54.
  63. Lewis, R.E.; Cahyame-Zuniga, L.; Leventakos, K.; Chamilos, G.; Ben-Ami, R.; Tamboli, P.; Tarrand, J.; Bodey, G.P.; Luna, M.; Kontoyiannis, D.P. Epidemiology and sites of involvement of invasive fungal infections in patients with haematological malignancies: A 20-year autopsy study. Mycoses 2013, 56, 638–645.
  64. Millon, L.; Scherer, E.; Rocchi, S.; Bellanger, A.-P. Molecular Strategies to Diagnose Mucormycosis. Fungi 2019, 5, 24.
  65. Scherer, E.E.; Iriart, X.; Bellanger, A.P.; Dupont, D.; Guitard, J.; Gabriel, F.; Cassaing, S.; Charpentier, E.; Guenounou, S.; Cornet, M.; et al. Quantitative PCR (qPCR) Detection of Mucorales DNA in Bronchoalveolar Lavage Fluid to Diagnose Pulmonary Mucormycosis. Clin. Microbiol. 2018, 56, doi:10.1128/jcm.00289-18.
  66. Lengerova, M.; Racil, Z.; Hrncirova, K.; Kocmanova, I.; Volfova, P.; Ricna, D.; Bejdak, P.; Moulis, M.; Pavlovsky, Z.; Weinbergerova, B.; et al. Rapid Detection and Identification of Mucormycetes in Bronchoalveolar Lavage Samples from Immunocompromised Patients with Pulmonary Infiltrates by Use of High-Resolution Melt Analysis. Clin. Microbiol. 2014, 52, 2824–2828.
  67. Mercier, T.; Reynders, M.; Beuselinck, K.; Guldentops, E.; Maertens, J.; Lagrou, K. Serial Detection of Circulating Mucorales DNA in Invasive Mucormycosis: A Retrospective Multicenter Evaluation. Fungi 2019, 5, 113.
  68. Guegan, H.; Iriart, X.; Bougnoux, M.E.; Berry, A.; Robert-Gangneux, F.; Gangneux, J.P. Evaluation of Mucorgenius(R) Mucorales Pcr Assay for the Diagnosis of Pulmonary Mucormycosis. J. Infect. 2020, 81, 311–317.
  69. Millon, L.; Herbrecht, R.; Grenouillet, F.; Morio, F.; Alanio, A.; Letscher-Bru, V.; Cassaing, S.; Chouaki, T.; Kauffmann-Lacroix, C.; Poirier, P.; et al. Early Diagnosis and Monitoring of Mucormycosis by Detection of Circulating DNA in Serum: Retrospective Analysis of 44 Cases Collected through the French Surveillance Network of Invasive Fungal Infections (Ressif). Microbiol. Infect. 2016, 22, e1–e8.
  70. Springer, J.; Lackner, M.; Ensinger, C.; Risslegger, B.; Morton, C.O.; Nachbaur, D.; Lass-Flörl, C.; Einsele, H.; Heinz, W.J.; Loeffler, J. Clinical evaluation of a Mucorales-specific real-time PCR assay in tissue and serum samples. Med. Microbiol. 2016, 65, 1414–1421.
  71. Caillot, D.; Valot, S.; Lafon, I.; Basmaciyan, L.; Chretien, M.L.; Sautour, M.; Million, L.; Legouge, C.; Payssot, A.; Dalle, F. Is It Time to Include Ct Reverse Halo Sign and Qpcr Targeting Mucorales in Serum to Eortc-Msg Criteria for the Diagnosis of Pulmonary Mucormycosis in Leukemia Patients Open Forum Infect. Dis. 2016, 3, ofw190.
  72. Potenza, L.; Vallerini, D.; Barozzi, P.; Riva, G.; Forghieri, F.; Zanetti, E.; Quadrelli, C.; Candoni, A.; Maertens, J.; Rossi, A.; et al. Mucorales-specific T cells emerge in the course of invasive mucormycosis and may be used as a surrogate diagnostic marker in high-risk patients. Blood 2011, 118, 5416–5419.
  73. Potenza, L.; Vallerini, D.; Barozzi, P.; Riva, G.; Gilioli, A.; Forghieri, F.; Candoni, A.; Cesaro, S.; Quadrelli, C.; Maertens, J.; et al. Mucorales-Specific T Cells in Patients with Hematologic Malignancies. PLoS ONE 2016, 11, e0149108.
  74. Steinbach, A.; Cornely, O.A.; Wisplinghoff, H.; Schauss, A.C.; Vehreschild, J.J.; Rybniker, J.; Hamprecht, A.; Richter, A.; Bacher, P.; Scheffold, A.; et al. Mould‐reactive T cells for the diagnosis of invasive mould infection—A prospective study. Mycoses 2019, 62, 562–569.
  75. Burnham-Marusich, A.R.; Hubbard, B.; Kvam, A.J.; Gates-Hollingsworth, M.; Green, H.R.; Soukup, E.; Limper, A.H.; Kozel, T.R. Conservation of Mannan Synthesis in Fungi of the Zygomycota and Ascomycota Reveals a Broad Diagnostic Target. mSphere 2018, 3, e00094–18.
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