Literature DB >> 21625306

Update on the laboratory diagnosis of invasive fungal infections.

Brunella Posteraro1, Riccardo Torelli, Elena De Carolis, Patrizia Posteraro, Maurizio Sanguinetti.   

Abstract

Recent advances in the management of patients with haematological malignancies and transplant recipients have paralleled an increase in the incidence of fungal diseases due to pathogenic genera such as Candida and Aspergillus and the emergence of less common genera including Fusarium and Zygomycetes. Despite availability of new antifungal agents these opportunistic infections have high mortality. Rapid and reliable species identification is essential for antifungal treatment, but detection of the increasing diversity of fungal pathogens by conventional phenotypic methods remains difficult and time-consuming, and the results may sometimes be inconclusive, especially for unusual species. New diagnostic techniques (e.g., 1,3-beta-d-glucan detection) could improve this scenario, although further studies are necessary to confirm their usefulness in clinical practice.

Entities:  

Year:  2011        PMID: 21625306      PMCID: PMC3103235          DOI: 10.4084/MJHID.2011.002

Source DB:  PubMed          Journal:  Mediterr J Hematol Infect Dis        ISSN: 2035-3006            Impact factor:   2.576


Introduction

Despite the development of new techniques and new antifungal agents, diagnosis of invasive fungal infection (IFI), which still relies upon a combination of clinical observation and laboratory investigation, remains a challenge especially for immunocompromised patients with haematological disease.1 This has important clinical repercussions since delayed diagnosis and therapy contribute significantly to the high mortality rates associated with IFIs,2 whereas early intervention with antifungal drugs may result in more effective management of high-risk patients.3 While superficial and subcutaneous fungal infections often produce characteristic lesions that suggest the diagnosis, a thorough knowledge of potential causative organisms is yet required to aid the diagnostic process, mainly in situations where systemic fungal infection is suspected but the clinical presentation is nonspecific and then ascribable to a wide range of infections, underlying illnesses, or complication of treatments.4 The exact identification of the infecting organism is became essential in light of the increased use of prophylactic schedules that predispose the patient not just to fungal infection, but also to the selection of fungal species such as non-albicans Candida (e.g., C. glabrata and C. krusei), Aspergillus terreus, Scedosporium species, and Zygomycetes, many of which are intrinsically resistant to the available antifungal agents.5,6

Culture-based detection methods

Laboratory diagnosis of IFI remains based on conventional approaches, such as the direct microscopically detection of the etiologic agent in clinical specimen and the isolation and identification of the pathogen in culture, and non-culture based methods involving detection of a serologic response to the pathogen or other marker of its presence such as fungal antigens or metabolites.4 Visual examination of fungi in tissue samples allows presumptive identification based on cellular morphology and staining properties, but it should be appreciated that invasive procedures necessary to obtain biopsies may be precluded in haematological patients. It should be noted that microbiological cultures are often insensitive or of limited use, since even with modern blood cultures systems candidaemia can be transient and not detected, or Aspergillus cannot be cultured from a significant proportion of sputum or bronchoalveolar lavage samples from patients with invasive aspergillosis (IA).7 Although a variety of culture media and incubation conditions may be required for recovery of fungal agents, chromogenic primary isolation media (e.g., CHROMagar Candida medium) can be employed for the presumptive identification of the most medically important Candida species, including C. albicans, C. tropicalis, C. glabrata, and C. parapsilosis. Most yeasts isolated from clinical samples can be identified using one of the numerous commercial identification systems, such as API 20C AUX, VITEK 2, and RapID Yeast Plus.4,8 Although the kits are relatively easy to use, it should be remembered that additional morphologic-based tests are often required to avoid confusion between organisms with identical biochemical profiles. Unlike pathogenic yeasts, filamentous fungi can be identified only by visualization of macroscopic (colonial form, surface colour, and pigmentation) or microscopic (spore-bearing structures) morphologic characteristics, following to sub-cultivation of a mould isolate to encourage sporulation,4 a process that takes days to weeks. In addition to the use of genetic probes for the culture confirmation of dimorphic systemic fungal pathogens (e.g., Histoplasma capsulatum), an alternative and useful approach to the detection and identification of fungi in clinical specimens involves a broad-range polymerase chain reaction (PCR) followed by nucleic acid sequencing, after which the nucleic acid sequence is compared with known sequence database and identification is based on DNA homology.9 However, these methods are expensive and time-consuming, and they are not currently suitable for routine identification. By contrast, matrix-assisted laser-desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) is becoming a reliable method for identification of microorganisms. The remarkable reproducibility of the methodology is based on the measurement of constantly expressed and highly abundant proteins such as ribosomal molecules.10,11 Some recent studies have shown the potential of the MALDI-TOF technique to identify fungal clinical species such as Aspergillus and Fusarium. Recently, the MALDI-TOF technology provided a fast and accurate identification of common and unusual species of Aspergillus when tested on 124 clinical and 16 environmental isolates.12 With regard to Fusarium species, a recent case report supported the usefulness of MALDI-TOF analysis in diagnosing an infection due to Fusarium proliferatum, which is a very infrequent pathogen within this genus.13

Antigen-based detection methods

To facilitate early diagnosis of IFI, important advances have been made in the development of laboratory markers (e.g., galactomannan [GM] and 1,3-beta-d-glucan [BG] assays), which have led to the potential for newer paradigms regarding prevention and early treatment of IFIs.14 Among fungal markers, GM, a component of fungal cell wall that can be detected by a sandwich-type enzyme-linked immunosorbent assay (ELISA) in serum or plasma,15 bronchoalveolar lavage (BAL) fluid,16,17 and cerebrospinal fluid,18 has recently been approved by the US Food and Drug Administration at a serum cut-off of 0.5, as a diagnostic adjunct for IA.14 Together with clinical criteria, a positive serum or BAL fluid GM would strongly suggest probable IA, as defined by authoritative consensus criteria.19 However, this technique has shown contradictory results, in terms of sensitivity and specificity, due to several factors, including the impact of prior antifungal therapy on the levels of circulating fungal components,20 the occurrence of false-positive results in association with some antibiotic treatments,21,22 and the different cutoffs of positivity among studies.14 Thus, a recently published meta-analysis of 27 studies showed an overall sensitivity of 71% and specificity of 89% for proven cases of IA when used for surveillance.23 In addition, GM also correlates well with outcome.24 In contrast to GM, BG is a cell wall constituent of several fungi, including Aspergillus, Candida, and Fusarium, a spectrum of pathogens that encompasses the majority of those emerging in neutropenic patients with either prolonged neutropenia or chemotherapy-induced mucositis, with some notable exceptions such as Zygomycetes, a rare but emerging cause of invasive mycosis.25,26 Measurement of serum BG has been shown to be an aid in the diagnosis of fungaemia and deep-seated mycoses, including IA.27,28 Among commercially available assays, the Fungitell, which is also an ELISA technique, is widely used to detect serum BG concentrations as low as 1 pg/mL.27 The cutoff for a positive result is >80 pg/ml. As with GM, variable results have been reported for BG assay, with a slightly higher sensitivity and specificity, ranging from 70% to 90%.28,29 When performances of both GM and BD tests were compared to determine their diagnostic usefulness for high-risk haematological malignancy patients, GM assay was significantly better for detecting non-fumigatus Aspergillus species, whereas BG was shown to have a higher sensitivity in detecting IA and other mould infections.30 Non-culture based methods for diagnosis of candidiasis are of limited value because the levels of circulating antigens are low and the transient nature of the antigenaemia requires sensitive assays and frequent sampling of at-risk patients.1,31 However, the use of Platelia Candida, an ELISA that combines the detection of mannan antigen and anti-mannan antibodies in serum, led to earlier diagnosis of Candida infection when compared with blood cultures.31 In haematological patients with hepatosplenic lesions, assessing mannan/anti-mannan antibodies shortened significantly the median time of diagnosis of candidiasis when compared with imaging.32

Molecular-based detection methods

A range of polymerase chain reaction (PCR)-based methods have been developed with the prospect of give highly specific, highly sensitive, and rapid means for fungal detection and identification.33 Most of them have focused on Aspergillus and Candida species, using different specimens types (e.g., serum, plasma, or BAL fluid), even though pan-fungal PCR amplification technology may be able to detect a broad range of fungal targets.33 Although PCR has been studied for years, the lack of standardization and clinical validation has led to its exclusion from consensus criteria for defining IFI.19 Nevertheless, a recent prospective evaluation of serial PCR assays against34 or along with GM and computed tomography35 was carried out in haematological patients, thus showing acceptable sensitivity and specificity. In such one study, the combination of serial PCR and GM detected 100% of aspergillosis cases, with a positive predictive value of 75.1%.35 Of note, in a systematic review and meta-analysis of Aspergillus PCR tests for diagnosis of IA,36 the authors proposed that a single PCR-negative test is sufficient to exclude IA, whereas two PCR-positive results are required to confirm disease. Compared with Aspergillus PCR, only a few Candida PCR methods have received major clinical evaluation.37 As confirmed by a national consensus evaluation,38 performance of these tests is generally good, with sensitivities and specificities consistently >90%.33 Although addressed to critically ill patients, a prospective clinical trial published in 2008 reported positive predictive values and negative predictive values of >90% for a PCR method that detects several species of Candida.39

Conclusion

Molecular detection methods, combined with additional microbiological and clinical information, has the potential not only to accurately and rapidly identify fungal pathogens, but also to indicate whether the pathogen is likely to respond to conventional antifungal treatment.9 Inclusion of these methods in a diagnostic surveillance strategy to exclude IFI in high-risk patients with haematological malignancy40 should result in improved clinical management, thus allowing more rational use of antifungal drugs.
  38 in total

Review 1.  Use of PCR for diagnosis of invasive aspergillosis: systematic review and meta-analysis.

Authors:  Carlo Mengoli; Mario Cruciani; Rosemary A Barnes; Juergen Loeffler; J Peter Donnelly
Journal:  Lancet Infect Dis       Date:  2009-02       Impact factor: 25.071

2.  Fungal infections in recipients of hematopoietic stem cell transplants: results of the SEIFEM B-2004 study--Sorveglianza Epidemiologica Infezioni Fungine Nelle Emopatie Maligne.

Authors:  L Pagano; M Caira; A Nosari; M T Van Lint; A Candoni; M Offidani; T Aloisi; G Irrera; A Bonini; M Picardi; C Caramatti; R Invernizzi; D Mattei; L Melillo; C de Waure; G Reddiconto; L Fianchi; C G Valentini; C Girmenia; G Leone; F Aversa
Journal:  Clin Infect Dis       Date:  2007-09-26       Impact factor: 9.079

3.  Clinical impact of enhanced diagnosis of invasive fungal disease in high-risk haematology and stem cell transplant patients.

Authors:  R A Barnes; P L White; C Bygrave; N Evans; B Healy; J Kell
Journal:  J Clin Pathol       Date:  2009-01       Impact factor: 3.411

4.  Strong correlation between serum aspergillus galactomannan index and outcome of aspergillosis in patients with hematological cancer: clinical and research implications.

Authors:  Marisa H Miceli; Monica L Grazziutti; Gail Woods; Weizhi Zhao; Mehmet H Kocoglu; Bart Barlogie; Elias Anaissie
Journal:  Clin Infect Dis       Date:  2008-05-01       Impact factor: 9.079

5.  Detection of circulating Aspergillus fumigatus DNA by real-time PCR assay of large serum volumes improves early diagnosis of invasive aspergillosis in high-risk adult patients under hematologic surveillance.

Authors:  F Suarez; O Lortholary; S Buland; M T Rubio; D Ghez; V Mahé; G Quesne; S Poirée; A Buzyn; B Varet; P Berche; M E Bougnoux
Journal:  J Clin Microbiol       Date:  2008-09-24       Impact factor: 5.948

6.  The use of ITS DNA sequence analysis and MALDI-TOF mass spectrometry in diagnosing an infection with Fusarium proliferatum.

Authors:  Florian Seyfarth; Mirjana Ziemer; Herbert G Sayer; Anke Burmester; Marcel Erhard; Martin Welker; Sibylle Schliemann; Eberhard Straube; Uta-Christina Hipler
Journal:  Exp Dermatol       Date:  2008-06-10       Impact factor: 3.960

7.  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.

Authors:  Ben De Pauw; Thomas J Walsh; J Peter Donnelly; David A Stevens; John E Edwards; Thierry Calandra; Peter G Pappas; Johan Maertens; Olivier Lortholary; Carol A Kauffman; David W Denning; Thomas F Patterson; Georg Maschmeyer; Jacques Bille; William E Dismukes; Raoul Herbrecht; William W Hope; Christopher C Kibbler; Bart Jan Kullberg; Kieren A Marr; Patricia Muñoz; Frank C Odds; John R Perfect; Angela Restrepo; Markus Ruhnke; Brahm H Segal; Jack D Sobel; Tania C Sorrell; Claudio Viscoli; John R Wingard; Theoklis Zaoutis; John E Bennett
Journal:  Clin Infect Dis       Date:  2008-06-15       Impact factor: 9.079

Review 8.  Clinical relevance of resistance to antifungals.

Authors:  Juan Luis Rodriguez-Tudela; Laura Alcazar-Fuoli; Isabel Cuesta; Ana Alastruey-Izquierdo; Araceli Monzon; Emilia Mellado; Manuel Cuenca-Estrella
Journal:  Int J Antimicrob Agents       Date:  2008-11       Impact factor: 5.283

9.  Bronchoalveolar lavage galactomannan in diagnosis of invasive pulmonary aspergillosis among solid-organ transplant recipients.

Authors:  Cornelius J Clancy; Reia A Jaber; Helen L Leather; John R Wingard; Benjamin Staley; L Joseph Wheat; Christina L Cline; Kenneth H Rand; Denise Schain; Maher Baz; M Hong Nguyen
Journal:  J Clin Microbiol       Date:  2007-04-11       Impact factor: 5.948

10.  Utility of galactomannan enzyme immunoassay and (1,3) beta-D-glucan in diagnosis of invasive fungal infections: low sensitivity for Aspergillus fumigatus infection in hematologic malignancy patients.

Authors:  R Y Hachem; D P Kontoyiannis; R F Chemaly; Y Jiang; R Reitzel; I Raad
Journal:  J Clin Microbiol       Date:  2008-11-12       Impact factor: 5.948

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  8 in total

1.  Comparative evaluation of BD Phoenix and vitek 2 systems for species identification of common and uncommon pathogenic yeasts.

Authors:  Brunella Posteraro; Alberto Ruggeri; Elena De Carolis; Riccardo Torelli; Antonietta Vella; Flavio De Maio; Walter Ricciardi; Patrizia Posteraro; Maurizio Sanguinetti
Journal:  J Clin Microbiol       Date:  2013-08-21       Impact factor: 5.948

Review 2.  MALDI-TOF mass spectrometry: any use for Aspergilli?

Authors:  Maurizio Sanguinetti; Brunella Posteraro
Journal:  Mycopathologia       Date:  2014-07-08       Impact factor: 2.574

Review 3.  Novel Antifungal Agents and Their Activity against Aspergillus Species.

Authors:  Roya Vahedi-Shahandashti; Cornelia Lass-Flörl
Journal:  J Fungi (Basel)       Date:  2020-10-09

4.  Detection of (1, 3)-β-D-glucan in bronchoalveolar lavage and serum samples collected from immunocompromised hosts.

Authors:  Elitza S Theel; Deborah J Jespersen; Seher Iqbal; Jean E Bestrom; Leonard O Rollins; Lori J Misner; Barbara J Markley; Jayawant Mandrekar; Larry M Baddour; Andrew H Limper; Nancy L Wengenack; Matthew J Binnicker
Journal:  Mycopathologia       Date:  2012-09-01       Impact factor: 2.574

5.  Diagnostic performance of 1→3-β-d-glucan in neonatal and pediatric patients with Candidemia.

Authors:  Maria Teresa Montagna; Caterina Coretti; Grazia Lovero; Osvalda De Giglio; Osvaldo Montagna; Nicola Laforgia; Nicola Santoro; Giuseppina Caggiano
Journal:  Int J Mol Sci       Date:  2011-09-14       Impact factor: 5.923

6.  Phenotypic typing and epidemiological survey of antifungal resistance of Candida species detected in clinical samples of Italian patients in a 17 months' period.

Authors:  Margherita Scapaticci; Andrea Bartolini; Federica Del Chierico; Cristel Accardi; Francesco Di Girolamo; Andrea Masotti; Maurizio Muraca; Lorenza Putignani
Journal:  Germs       Date:  2018-06-04

Review 7.  Antifungal susceptibility testing: current role from the clinical laboratory perspective.

Authors:  Brunella Posteraro; Riccardo Torelli; Elena De Carolis; Patrizia Posteraro; Maurizio Sanguinetti
Journal:  Mediterr J Hematol Infect Dis       Date:  2014-04-07       Impact factor: 2.576

8.  Shedding light on Aspergillus niger volatile exometabolome.

Authors:  Carina Pedrosa Costa; Diogo Gonçalves Silva; Alisa Rudnitskaya; Adelaide Almeida; Sílvia M Rocha
Journal:  Sci Rep       Date:  2016-06-06       Impact factor: 4.379

  8 in total

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