Fungal Diagnostics - CSHL Pperspectivesinmedicine.cshlp.org/content/4/4/a019299.full.pdfFungal Diagnostics Thomas R. Kozel1 and Brian Wickes2 1Department of Microbiologyand Immunology,

Fungal Diagnostics

Thomas R. Kozel1 and Brian Wickes2

1Department of Microbiology and Immunology, University of Nevada School of Medicine, Reno,Nevada 89557

2Department of Microbiology and Immunology, The University of Texas Health Science Centerat San Antonio, San Antonio, Texas 78229

Correspondence: [email protected]

Early diagnosis of fungal infection is critical to effective treatment. There are many imped-iments to diagnosis such as a diminishing number of clinical mycologists, cost, time to result,and requirements for sensitivity and specificity. In addition, fungal diagnostics must meet thecontrasting needs presented by the increasing diversity of fungi found in association with theuse of immunosuppressive agents in countries with high levels of medical care and the needfor diagnostics in resource-limited countries where large numbers of opportunistic infectionsoccur in patients with AIDS. Traditional approaches to diagnosis include direct microscopicexamination of clinical samples, histopathology, culture, and serology. Emerging technolo-gies include molecular diagnostics and antigen detection in clinical samples. Innovative newtechnologies that use molecular and immunoassay platforms have the potential to meet theneeds of both resource-rich and resource-limited clinical environments.

There has been an enormous increase in thefrequency and severity of fungal infection in

recent years. This increase has been driven ina large part by two factors. First, the globalAIDS epidemic has fostered the emergence oflife-threatening infections by the opportunisticfungi Cryptococcus neoformans and Pneumocys-tis jiroveci and by regional endemic fungi suchas Histoplasma capsulatum and Penicilliummarneffei. These infections occur most oftenin resource-limited countries in Africa, SouthAmerica, and Southeast Asia. Second, advancesin medical care and treatment have led to in-creases in the number of opportunistic infec-tions in patients who are immunocompromisedby way of treatment with immunosuppressivedrugs or chemotherapy, or who are infected

in the course of extended critical care. Theseinfections occur most often in the setting ofadvanced medical care. The result is patientswith infections that are difficult to diagnoseand difficult to treat.

Diagnosis of invasive fungal disease (IFD) ischallenging because current diagnostic meth-ods lack sensitivity and specificity, or take toolong to yield a result to be clinically useful. Suchlimitations have consequences; delayed diagno-sis leads to delayed treatment. Speed to diagno-sis is a key risk factor in patient outcomes(Barnes 2008). Diagnosis of fungal infection isfurther complicated by problematic develop-ments in the field of medical mycology. Firstand foremost is the loss of senior mycology ex-perts in the field who were trained in classical

Editors: Arturo Casadevall, Aaron P. Mitchell, Judith Berman, Kyung J. Kwon-Chung, John R. Perfect, and Joseph Heitman

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mycology, which has created crises-level prob-lems in clinical mycology (Steinbach et al. 2003).This problem has been compounded over thelast 30 years as the spectrum of fungi-causinginfections has exploded owing to AIDS and theuse of highly immunosuppressive agents fortreatment of a variety of diseases. These patientsare susceptible to infections from fungi rarelyseen, or never reported as a human pathogen,which can cause identification problems foreven the most experienced mycologists. Where-as mycologists in the past needed to be ableto identify �50 commonly encountered fungi,and �300 total fungi that were pathogenic forhumans, the number of potential fungal path-ogens is likely many times what is described intextbooks, and will continue to grow as the se-verely immunosuppressed patient populationcontinues to grow (Ajello and Hay 1998; Collieret al. 1998; Andrew et al. 2009).

Diagnosis of fungal infection has relied pri-marily on methods such as direct microscopicexamination of clinical samples, histopathol-ogy, and culture. Such approaches are depen-dent on personnel with relatively high levels ofspecific mycology training. The growth in thenumber of fungi that clinical mycologists mustidentify has forced investigators to develop andapply new methods for fungal identificationthat go beyond classical phenotypic methods.As a consequence, there is an increased empha-sis on the use of molecular methods and antigendetection as surrogates for culture in diagnosisof fungal diseases.

CULTURE, DIRECT MICROSCOPY,AND HISTOPATHOLOGY

Culture, direct microscopy, and histopathologyhave been the foundation for diagnosis of fungalinfection for many decades. Microscopy, histo-pathology, and use of fungal-specific stains playimportant roles in diagnosis of infection byC. neoformans, P. jirovecci, Candida spp., Asper-gillus spp., H. capsulatum, Blastomyces dermati-tidis, Coccidioides immitis, Sporothrix schenckii,Paracoccidioides brasiliensis, and the Mucorales.Sensitivity of microscopy for diagnosis of fungalinfection varies with the individual agent, the

source and quality of the specimen, and theskills and experience of the laboratorian. Final-ly, diagnosis of invasive fungal infection by di-rect microscopy and histopathology may re-quire the use of biopsies of deep tissues, whichposes a risk to those patients who are most sus-ceptible to invasive disease.

Culture from a clinical sample is the goldstandard for diagnosis of fungal infection. Cul-ture has the advantage of yielding the specificetiological agent if positive. Moreover, cultureallows for susceptibility testing. However, use ofculture for diagnosis of IFD has significant lim-itations. Culture may take many days to a resultwith several of the filamentous fungi. In the caseof disseminated candidiasis, blood culture (1)may miss �50% of patients with documenteddisease (Fraser et al. 1992; Ostrosky-Zeichnerand Pappas 2006; Ostrosky-Zeichner 2012),(2) may only become positive late in infection(Ellepola and Morrison 2005), and (3) typicallytakes 24–72 h for identification of Candida in aclinical sample—too long for early treatment.Positive blood culture is rare in invasive asper-gillosis and is most often owing to environmen-tal contamination (Kontoyiannis et al. 2000).Recovery of H. capsulatum from sputum of pa-tients with acute pulmonary histoplasmosisranges from 10% to 15%; however, in cavitaryhistoplasmosis, sputum cultures are positive inup to 60% of patients (Deepe 2010). In patientswith pulmonary blastomycosis, sputum cultureor culture of specimens obtained by broncho-scopy has a high yield (86% per patient for spu-tum culture and 92% for broncoscopy) (Chap-man and Sullivan 2010). Culture of Coccidioidesspp. is complicated by the biosafety hazard as-sociated with culture of the mycelial form. Fi-nally, identification of less common fungi thatmay cause opportunistic infections requires ahigh level of expertise on the part of laboratorypersonnel.

SEROLOGY

Serologic tests for patient antibodies have beenuseful for non-culture-based diagnosis of fun-gal infection since the middle of the last century.Serology is of greatest value in diagnosis of

T.R. Kozel and B. Wickes

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endemic mycoses. Available technologies in-clude immunodiffusion (ID), complement fix-ation (CF), and enzyme immunoassay (EIA).

CF and immunodiffusion are the mostcommon serologic tests for diagnosis of histo-plasmosis. The ID test detects precipitating an-tibodies to Histoplasma H and M antigens. Se-rologic testing for histoplasmosis is most usefulif an increase in CF titer is observed betweenacute and convalescent sera in acute histoplas-mosis (Deepe 2010). High titers may be ob-served with chronic pulmonary or disseminatedhistoplasmosis (Lindsley et al. 2006).

Serological testing plays an important rolein diagnosis of coccidioidomycosis, particularlyin patients who may not be able to produce asputum sample, for example, primary infection,or when samples are often negative, for exam-ple, coccidioidal meningitis (Galgiani 2010).Depending on the antigen used in the test, thequalitative ID test will determine the presence ofcoccidioidal IgM with a result that is similar to atube precipitin test (IDTP) or coccidioidal IgGthat detects antibody recognized by the CF test(IDCF). Detection of IgM is useful in diagnosisof acute primary coccidioidomycosis in whichthe sensitivity may be .80% (Saubolle et al.2007). CF detects IgG antibodies. IgG antibod-ies are produced during the convalescent phaseof disease or during chronic infection. CF ismore sensitive than IDCF and provides quanti-tative results. A commercially available EIA canbe used to detect IgM or IgG antibodies.

There are many advantages to the use ofserology for diagnosis of invasive fungal infec-tion. First, results may be positive when cultureresults are negative or samples are difficult toobtain. Second, if positive, serological resultsmay reduce the need for culture of potentiallyhazardous fungi, for example, Coccidioides spp.Finally, serology is a minimally invasive sample,which lowers barriers to testing. Disadvantagesof serology include sometimes low levels of sen-sitivity and specificity. A negative serologic testshould not exclude the presence of fungal infec-tion. Some tests, particularly CF, are time con-suming and require trained personnel. Immu-nocompromised patients may show a reducedantibody response, which would dramatically

reduce the value of serologic assays (Tobon etal. 2005). Interpretation of serological resultsmay be confounded by the inability of serologythat measures IgG to distinguish between cur-rent or previous infection. False positives mayoccur with some tests in the setting of otherendemic fungal infections. Finally, sensitivityis dependent on the type of disease and thetiming of testing relative to the disease process,for example, early versus late.

MOLECULAR DIAGNOSTICS

In the field of clinical mycology, no area is ad-vancing faster than the application of modernmolecular tools for the identification of fungi.The advancement of this area has been driven inlarge part by the rapid accumulation of proteinand DNA sequence data, which continues un-abated and accelerates with each new advance intechnology, and the growing need to identify abroader range of fungi. Importantly, molecularmethods for fungal diagnosis and identificationdirectly address the declining numbers of clin-ical mycologists because they are not dependenton classical phenotyping methods. Similarly,molecular methods have the power to identifythe increasing numbers of fungi found to pro-duce disease in humans and animals.

Non-Culture-Based Molecular DiagnosticMethods

Molecular identification methods form a sub-set of diagnostic methods that do not necessari-ly need live fungal cells for success. Molecularmethods for fungal identification generally workbest when pure cultures are available. However,because polymerase chain reaction (PCR) playsa role in many molecular identification meth-ods, molecular identification can work in theabsence of live cells if template nucleic acid isavailable in patient specimens, including fixedtissue.

PCR is a central component for many mo-lecular methods, either as the main diagnosticstrategy or as one of the preliminary steps in thediagnostic assay. Consequently, diagnostic PCRencompasses a number of different approaches.

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The simplest consists of conventional PCR inwhich species-specific primers that have beendesigned based on existing sequence or data,are used to amplify fungal DNA from clinicalspecimens. The readout generally consists ofthe presence or absence of a band, with thesize of the band often being a secondary factorin identification. This type of PCR is not FDAapproved and although simple and inexpen-sive, can be subject to wide intra- and interla-boratory variation. There also must be someprior suspicion about the identity of the isolate,which the PCR reaction will confirm. Nonethe-less, it is still used in research laboratories thatoccasionally may need to perform diagnosticstudies on select organisms and can be suitablefor minimally equipped laboratories if there is astable power supply to run the thermocycler.

Further discriminatory power can be addedto conventional PCR techniques by using re-striction enzymes to digest the PCR products,which are resolved on a gel and visualized as thefinal step in the assay. The presence or absenceof a fragment and their various sizes can thenbe used to make an identification. This methodwas used extensively in early fungal taxonomy(de Hoog et al. 2000). Unfortunately, owing tothe great variability of PCR and the confir-matory nature of the technology (results arepositive or negative, depending on the suspect-ed organism), it is not widely used in the clini-cal laboratory. Importantly, conventional PCRserves as a confirmatory assay in which a posi-tive reaction simply confirms the identity ofthe suspected fungus. The confirmatory natureof the assay is derived from the need to designprimers that anneal to specific target sequencespreviously identified from a known organism.However, degenerate primers can expand thisidentification to genus or higher taxonomic lev-els, and if the product is to be sequenced, specialstrategies are used in primer design and targetselection to greatly expand the number of fungithat can be amplified.

In contrast to conventional PCR, which re-quires gel electrophoresis of ethidium bromidestained PCR products as the final readout,real-time PCR uses fluorescent dyes to enhancespecificity through either a nonspecific DNA-

binding dye, that is, SYBR green, or a specificfluorescently labeled probe directed to a targetsequence lying within the amplicon. Thereare various chemistries for probe labeling andfluorescent detection (i.e., Taqman, MolecularBeacons, etc.), as well as numerous thermocy-cler platforms (i.e., LightCycler, GeneAmp,etc.), which, depending on the combination,can have various levels of throughput. The ap-plication of fluorescent probes to PCR has madethis technology suitable for the clinical labora-tory and even has nanolevel applications thatenable the identification of multiple organismsusing different matrices.

A number of assays have been FDA approvedfor nonfungal identification (i.e., influenza,methicillin-resistant Staphylococcus aureus),whereas only a few have been approved for fun-gal identification, such as the FilmArray BloodCulture Identification (BioFire Diagnostics,Inc.), which is a PCR-based reaction performedon positive blood cultures and detects mainlyCandida spp. Because PCR-based assays includean amplification step of a specific nucleic acidtarget, they can be performed on specimens thatare potentially contaminated with human tissueor fluids, which is a tremendous advantage ofPCR because a time-consuming outgrowth pe-riod is not needed and the assay can often becompleted in a few hours. Furthermore, PCRcan be performed on fixed tissue with somesuccess, although these templates come withspecial challenges (Dannaoui et al. 2010). Likeconventional PCR, real-time PCR generally isconfirmatory in that a suspicion of the organ-ism identity is established before performingthe PCR reaction. Additionally, although mul-tiplexable, a problem with probe-based diag-nostic assays is that each assay must contain allprobes for the organisms it can detect, whichcan entail substantial reagent costs, even whenperformed on a nanoscale.

Culture-Based Molecular DiagnosticMethods

Establishing a pure culture of a suspected mi-crobial sample isolated from a clinical specimenhas always been the gold standard of diagnostic



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microbiology, regardless of the downstream di-agnostic assay that is applied for the ultimateidentity of the organism. Although in many in-stances it is not possible to obtain a pure, viableculture, virtually all diagnostic assays work bestif the assay initiates from a pure culture. Purecultures ensure there is enough material to per-form the assay, enable repeat assays in the caseof failure, allow for sending the isolate to alter-nate sites where the assay can be performed,and/or allow additional unrelated assays to beperformed if confirmation or a more discrim-inatory strategy is needed. Culture-based meth-ods historically have been phenotype driven,in which yeasts were identified biochemicallyand molds were identified based on morpho-logical features. These methods are still impor-tant, frontline diagnostic methods. However,with the application of molecular biology tofungal taxonomy and phylogeny, it has becomeclear that molecular biology needs to be part ofdiagnostic mycology. As a result, the major mo-lecular taxonomic tool, ribosomal sequencing,is now the major molecular tool for fungal iden-tification.

Sequencing of fungal ribosomal targets isan attractive diagnostic method for a numberof reasons. First, fungal ribosomes and mosteukaryotic ribosomal genes are multicopy in na-ture, which increases detection sensitivity dur-

ing PCR amplification because there are moretarget sequences. Second, the organization ofthese loci in fungi places multiple conservedribosomal (18s, 5.8s, and 28s) subunit genesin close proximity, which offers conservedPCR primer sites that are positioned such thatmultiple target sites are close enough to yieldPCR products. In fact, the conserved nature ofthe subunits, and their primer annealing sites,makes PCR and sequence identification possi-ble, enabling virtually any unknown fungus tobe amplified with universal primers targeted tothese regions (White et al. 1990; Kurtzman andRobnett 1997). Third, the overall organizationof this region confers variability owing to thefact that variable regions separate the key ribo-somal units. These regions, called the internaltranscribed spacer (ITS) sequences, consist oftwo regions (ITS1 and ITS2) that are not partof the fungal ribosome and are spliced out aftertranscription (Fig. 1). Their presence confersthe sequence variability that makes rDNA se-quencing the most powerful nucleic acid–baseddiagnostic method available. In addition tothe variable ITS1 and ITS2 regions, a third var-iable region exists within the large 28s ribo-somal subunit called the D1/D2 region. Allthree regions are informative owing to theirvariable nature, which can yield genus-specif-ic and species-specific identifications. Finally,

ITS

D1/D2

ITS2 IGSITS1

18s 5.8s 28s 5s

Figure 1. Ribosomal subunit organization in eukaryotes with variable regions. Eukaryotic ribosomal subunitgenes are typically organized in repeats of the 18s rDNA (small subunit), ITS1 (internal transcribed spacer region1), 5.8s rDNA, ITS2 (internal transcribed spacer region 2), and the 28s rDNA (large subunit). Conservedpriming sites exist at the end of the 28s subunit and the beginning of the 28s subunit, and at the end of theD1/D2 region within the 28s subunit. Additional sites exist within the 5.8s subunit and throughout the large andsmall ribosomal subunits. The variable regions, which can provide information that can discriminate to thespecies level, depending on genus, include ITS1, ITS2, and D1/D2. The ITS region can be covered in a single PCRreaction and by double-stranded sequencing, and is roughly 450–750 bp in length, depending on species. TheD1/D2 region is in a similar size range.

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sequence data generated from an unknown fun-gus can be used to search the public databases,such as GenBank, using the web-based BLASTnalgorithm.

Database searches must be performed withextreme caution owing to the public nature ofthe database and high frequency of erroneousdeposits (Bidartondo 2008). Nevertheless, thereare hundreds of thousands of fungal sequencesdeposited within GenBank that can serve aspotential identification data. It is the wide arrayof different fungal species that makes GenBankso powerful. It is unlikely that any fungal iden-tification platform will be as broad in termsof the number of potential species that canbe identified using DNA sequences because ofthe public nature of GenBank, length of timesequences have been deposited into the data-base, and widespread use of sequencing as abasic molecular technique. In fact, most jour-nals that publish papers that include sequenceinformation require a GenBank deposit of thedata. Importantly, global access to GenBank en-sures that fungal sequences from all over theworld are regularly deposited, which serves toincrease the diversity of information in the da-tabase. Unfortunately, the unedited nature ofGenBank has always been problematic for fun-gal identification, which has resulted in the de-velopment of both commercial and publicly cu-rated, closed databases.

Although most of the taxonomically signifi-cant sequences are ribosomal in nature, forsome fungi, there is not enough specificity inthe ribosomal loci to discriminate different spe-cies. In this case, alternate sites based on con-served structural genes have been developed andin many cases are standard depending on thepresumed identity (Table 1) (Petti et al. 2008).However, to generate these sequences, specificprimers must be used, which requires some in-formation about the unknown fungus to guideprimer selection. Some genes such as tubulinhave primers that amplify across families (Glassand Donaldson 1995).

A requirement for sequence-based diag-nostics is the need for bioinformatics skills tomanipulate sequences and ultimately to searchdatabases and interpret the results. This require-

ment has led to the development of alternateDNA-based identification technologies. Oneof these technologies (Luminex xMAP) usescolor-coded microspheres that are specific foreach analyte in a sample. In the case of fungalidentification, this platform uses PCR of anunknown sample that can then be detected ina hybridization assay by binding to its corre-sponding bead in the assay. Detection and iden-tification using this methodology is similar tothe technology used in flow cytometry. Eachassay is capable of detecting up to 100 differentspecies in a single multiplex reaction (Preunerand Lion 2013). The advantage of this platformis that there are no downstream manipulationsof data after the assay is complete. The multi-plex capability also greatly exceeds a single PCRreaction; however, the true identity of the or-ganism must be one of the 100 components ofthe multiplex.

Proteomics Profiling/Fingerprinting

The most popular and fastest growing non-nu-cleic acid sequence based molecular diagnosticassay for fungi is MALDI-TOF (matrix-assistedlaser desorption/ionization time-of-flight). Thetechnique generates species-specific spectra thatprovide a unique signature characteristic ofthe species. MALDI-TOF instrumentation con-sists of an ion source that transfers sample mol-ecules into a gas phase, a mass analyzer thatresolves ions based on mass-to-charge ratio,and a component that detects the ions (Cro-xatto et al. 2012). Samples are mixed with amatrix of small acidic molecules that crystallizesthe specimen and facilitates ionization becausethe matrix absorbs energy in the range of thelaser used for sample excitation. The TOF com-ponent consists of a tube that the excited ionstravel through, with the transit time (time-of-flight) of individual ions providing the methodfor identification. The generated spectra arescreened against a library of reference spectra,which correspond to individual species. Thetechnology has already been commercializedfor microbial identification, with instrumentsbeing available from Bruker Daltronics (MALDIBiotyper), Shimazu (AXIMA@SARAMIS), An-



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dromas (Andromas), and bioMerieux (VitekMS) (Bader 2013).

The strength of MALDI-TOF technologylies in the rapid sample analysis (minutes) andthe absence of any downstream data manipula-tion. For many fungi, particularly many yeasts,sample prep is minimal. For other fungi, a rap-id extraction with a solvent is all that is need-ed. These factors—the lack of downstream stepsand simple sample preparation—combinedwith the accuracy and speed of this systemmake MALDI-TOF one of the most intriguingdiagnostic options for fungal identification.Importantly, just as for sequencing, no priorsuspicion of the true identity of the isolate isneeded. If there is a reference spectrum in thelibrary, there is a high probability that a correctidentification can be made (Posteraro et al.2013). Weaknesses of this system include theneed for an existing spectral library to comparegenerated spectra to, and potential variability inresults of unknown fungi if they are not grownunder conditions similar to reference spectra

in the library. Libraries are proprietary and in-strument specific, although most are modifiableby users. There are capitalization costs for theinstrumentation, and user skills need to besomewhat advanced. Portability is also not anoption with this instrumentation.

Challenges to Molecular-Based DiagnosticMycology

There remain a number of challenges prevent-ing full implementation of a molecular-basedplatform as the main identification method inclinical microbiology laboratories. On the my-cology side, the spectrum of fungi that can causedisease continues to grow and likely will be al-most infinite as patient populations, dependingon illness or treatment, can be so profoundlyimmunosuppressed that species never beforeseen as pathogenic for humans regularly appearin the clinical microbiology laboratory. Identi-fying these fungi using classical phenotypicmethods is extremely difficult as laboratory staff

Table 1. Alternate non-rDNA loci used for molecular identification

Locus Genera/order References

b-Tubulin Aspergillus, Penicillium, Phoma,Pseudallescheria, Chaetomium,Phaeoacremonium, Sporothrix,Paecilomyces

Glass and Donaldson 1995

Preribosomal-processingprotein

Aspergillus, Penicillium Houbraken and Samson 2011

Minichromosomemaintenance protein

Aspergillus Sugui et al. 2012

Translation elongationfactor 1a

Fusarium, Mucorales, Beauveria,Cordyceps, Trichoderma, Alternaria,Cladosporium, Phomopsis

O’Donnell et al. 1998, 2001; Abe et al.2010

Cytochrome oxidase 1 Penicillium Lasker 2006Calmodulin Pseudallescheria, Sporothrix, Aspergillus O’Donnell et al. 2000; Hong et al. 2006;

Marimon et al. 2006Glyceraldehyde-3-phosphate

dehydrogenaseCochliobolus, Curvularia, Bipolaris Berbee et al. 1999

Endopolygalacturonase Alternaria Andrew et al. 2009RNA polymerase II Schizophyllum, Alternaria, Penicillium,

AspergillusLiu et al. 1999; Peterson 2008; Samson

et al. 2011; Yilmaz et al. 2012Actin Rhizopus, Stachybotrys, Trichophyton,

PhaeoacremoniumCarbone and Kohn 1999; Gao and

Takashima 2004Intergenic sequence Trichosporon Sugita et al. 2002

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generally do not have the necessary training orexperience to arrive at an identification basedon morphology for rare fungi. Biochemicalidentification is generally limited to commercialplatforms that have panels of standard com-pounds, which are directed toward identifyingcommon fungi found in a coded database de-pending on metabolism pattern of the panel.Furthermore, mycology is unique in that thereis a special nomenclature system that takes intoconsideration whether or not a given isolatehas a sexual state or not. Unfortunately, onlythe most experienced mycologists can navigatethis system, which has become so complex thatefforts are under way to reform it so that a sim-pler more stable naming system can be used(Hibbett and Taylor 2013). Beginning in 2013,consistent with the Amsterdam Declarationon Fungal Nomenclature, a unified effort willbe made to insure that the one-fungus–one-name rule is implemented so that fungal no-menclature can be simplified (Hawksworth etal. 2011).

On the technical side, one of the simplest,yet longest running challenges impeding mo-lecular diagnostics is a universal method forpreparing sample templates. For sequence-based assays, fungi vary depending on theirmorphology in their resistance to cell lysis andease of release of nucleic acid. There are count-less methods that have been successful, rangingfrom enzymatic to chemical to physical; howev-er, a “one-size-fits-all” method that could becommercialized has proven elusive. This prob-lem also hinders development of strategies thatcould meet FDA approval because lack of con-sistency and varying requirements for technicalinput are problematic for certified laboratories.Additionally, the sheer number of fungi that amicrobiology laboratory must be able to iden-tify can preclude the use of assays, such as PCR,that can only identify one or a few fungi in thegiven assay. More open-ended assays, whichtheoretically can identify any species within agiven platform’s reference libraries or databases,are more realistic because they could potentiallyreplace all culture-based assays in the clinicallaboratory, and can even be used across king-doms. However, these assays tend to require ex-

pensive, stationary equipment that requires spe-cialized skills to operate.

ANTIGEN DETECTION

Fungal polysaccharides or proteins may be shedinto body fluids during the course of infection.If an antibody can be raised against such a shedantigen, an immunoassay can be constructedfor antigen detection.

Cryptococcosis

Diagnosis of cryptococcal meningitis was thefirst application of antigen detection for diag-nosis of fungal infection that received wide-spread clinical use (Bloomfield et al. 1963). An-tibodies were raised in rabbits against wholecryptococcal cells and passively coated onto la-tex beads. Termed latex agglutination, the assaydetected glucuronoxylomannan (GXM), themajor capsular polysaccharide of C. neofor-mans. GXM is shed in large amounts into bloodand cerebrospinal fluid (CSF) during the courseof cryptococcal meningitis.

GXM occurs in four major serotypes: A, B,C, and D and a hybrid serotype AD. Before theuse of molecular methods for classification ofcryptococcal species, serotypes A, D, and A/Dwere C. neoformans; serotypes B and C were C.gattii (Bennett et al. 1977; Kwon-Chung andBennett 1984b). With further study, C. neofor-mans var. grubii was identified to correspond toserotype A. C. neoformans var. neoformans cor-responds to serotype D.

There is considerable variability in the geo-graphic distribution of the cryptococcal speciesand their corresponding serotypes. Serotype Ahas a global distribution, and initial studies ofcryptococcosis in patients with AIDS found apredominance of serotype A isolates, suggestingthat serotype A was selectively infecting AIDSpatients. However, there are several recent re-ports of serotype C in AIDS patients in sub-Saharan Africa where the frequency of serotypeC has been reported to be as high as 14% (Kar-staedt et al. 2002; Litvintseva et al. 2005; Thakuret al. 2009). C. neoformans var. neoformans (se-rotype D) has a global distribution, but clinical



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cases are concentrated in Europe (Kwon-Chungand Bennett 1984a; Dromer et al. 1996). Finally,C. gattii has gained recent prominence as thecause of an ongoing outbreak that began in Van-couver Island, British Columbia. Althoughthere has not been an extensive serological char-acterization of isolates from the outbreak, mo-lecular typing has found that almost all isolatesare genetic variants of the VGII class on the basisof PCR fingerprinting; isolates of VGII producecapsules of serotype B (Litvintseva et al. 2011).Geographic variability in occurrence of crypto-coccosis of different serotypes has consequencesfor diagnostic testing that targets cryptococcalantigen; assays for antigen must be able to detectGXM of all major serotypes.

A significant advance in testing for crypto-coccal antigen was the development of an assayin lateral flow immunoassay (dipstick) format.Termed CrAg LFA, the assay is constructed froma cocktail of monoclonal antibodies that wereformulated to be reactive with all GXM sero-types (Gates-Hollingsworth and Kozel 2013).The CrAg LFA is particularly well suited foruse in resource-limited settings. The LFA re-quires no power or clean water, is inexpensive,requires no refrigeration, and can be performedby personnel with limited training. The LFAworks well with serum or a drop of blood andprovides a result in �10 min. As a consequence,patients can be treated at the time of an initialvisit to clinic. The ease of use of the CrAg LFAalso makes the test valuable for use in settingswith advanced medical care.

Recent studies have found that CrAg testingcan be used for prospective testing in asymp-tomatic patients at high risk for cryptococcosis.CrAg is present in serum for weeks to monthsbefore the onset of symptoms of cryptococcosis(Jarvis et al. 2009). As a consequence, a targetedscreening program could identify subclinical in-fection in patients at greatest risk for crypto-coccal meningitis. Specifically, HIV-infectedpatients can be screened for CrAg at the timeof initial diagnosis of HIV/AIDS before startingantiretroviral therapy (World Health Organi-zation Cryptococcal Working Group 2011).If a patient tests positive in this prospectivescreen, the patient can be preemptively treated

to prevent infection from progressing to men-ingitis.

Galactomannan

In 1978, Lehmann and Reiss identified an anti-gen in serum from immunosuppressed rabbitsinfected with Aspergillus fumigatus (Lehmannand Reiss 1978). The investigators later foundthat the same antigen is released from growinghyphae (Reiss and Lehmann 1979). This anti-gen is galactomannan (GM), a polysaccharidepresent in the cell wall of most Aspergillus spp. Atest for serum GM is now in widespread use fordiagnosis of invasive aspergillosis (Platelia As-pergillus, Bio-Rad Laboratories). The test is anenzyme immunoassay that uses a rat monoclo-nal antibody that recognizes b (1!5)-linkedgalactofuranose (Stynen et al. 1992, 1995). Mul-tiple studies have found the GM enzyme immu-noassay (EIA) to be useful in diagnosis of inva-sive aspergillosis in neutropenic patients withcancer and recipients of stem cell transplants(Machetti et al. 1998; Maertens et al. 1999,2001; Sulahian et al. 2001).

There are limitations to the GM immuno-assay for diagnosis of invasive aspergillosis.First, there is considerable variability in reportsof sensitivity and specificity (Machetti et al.1998; Maertens et al. 1999, 2001; Pinel et al.2003). Second, false positive reactions may oc-cur owing to a variety of factors, including ad-ministration of b lactam antibiotics (Pinel et al.2003) or infusion of gluconate-containing Plas-ma-Lyte (Petraitiene et al. 2011). Third, there isconsiderable cross-reactivity with other fungiproducing disseminated infection (Huanget al. 2007; Wheat et al. 2007; Xavier et al. 2009).

Detection of H. capsulatum polysaccharideantigen in body fluids, especially urine, hasbeen useful in presumptive diagnosis of histo-plasmosis in patients with disseminated disease(Wheat et al. 1986). The antigen is a galacto-mannan (Connolly et al. 2007). Antigen can bedetected in urine of �90% of patients with dis-seminated infection (Williams et al. 1994; Dur-kin et al. 1997). The sensitivity of antigen de-tection is greater in urine than in serum (Wheatet al. 2002). This is an antigen-capture ELISA in

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which polyclonal rabbit antibodies are used inboth the solid-phase capture and fluid-phaseindicator modes. Galactomannan recognizedby immunoassay of urine in histoplasmosis pa-tients is cross-reactive with polysaccharide an-tigen produced by several endemic mycoses(B. dermatitidis, P. brasiliensis, H. capsulatumvar. duboisii, and P. marneffei) (Azuma et al.1974; Wheat et al. 1997).

Immunoassays have been recently devel-oped for detection of galactomannan fromB. dermatitidis and C. immitis in urine and oth-er body fluids. For B. dermatitidis antigen de-tection, antigenuria was detected in 90% of pa-tients with culture- or histopathology-provenblastomycosis (Connolly et al. 2012). Specificitywas 99% in healthy subjects and patients withnonfungal disease, but cross-reactions occurredin 96% of patients with histoplasmosis. ForC. immitis antigen detection, antigenuria wasdetected in 71% of patients with more severeforms of coccidioidomycosis (Durkin et al.2008). Additional studies are needed to assessthe usefulness of galactomannan testing in oth-er clinical forms of coccidioidomycosis.

Pan-Fungal Detection of b-Glucan

(1!3)-b-D-glucan (BG) is a polysaccharidecomponent of most fungal cell walls. The poly-saccharide may be released into blood in thecourse of IFD, including infection by speciesof Aspergillus, Candida, Fusarium, Trichosporin,Saccharomyces, Acremonium, and P. jiroveci. BGdoes not appear in blood from patients withinfection by Cryptococcus spp. or the Mucorales.The assay for BG is not an immunoassay. Rath-er, assay for BG is based on the ability of thepolysaccharide to activate factor G of the horse-shoe crab coagulation cascade. With use of achromogenic substrate, the test can detect BGlevels as low as 1 pg/mL (Obayashi et al. 1995).

Assay for BG has value as a screen for pre-sumptive diagnosis of invasive fungal infection(IFI). Early diagnosis allows for earlier initiationof antifungal therapy. Clinical studies havefound BG testing to have a high sensitivity fordiagnosis of IFI. The test has a strong negativepredictive value, allowing the test to be used to

exclude IFI. There are a number of limitations inthe use of BG assay for diagnosis of IFI. First, BGis ubiquitous in the environment, which mayproduce false positive reactions. All testing ma-terials must be glucan-free. Second, BG testingis typically performed at reference laboratories,which reduces time to result and discouragesroutine, potentially prospective, testing by cli-nicians. Finally, BG testing cannot be used todetect mucormycosis or cryptococcosis.

Strengths and Weaknessesof Antigen Testing

A particular advantage of testing for antigen isthe possibility that antigen can be shed from alocal site of infection to a body fluid such asblood or urine. As a consequence, it is possibleto avoid highly invasive sample collection. Cir-culating or urinary antigen functions as a sur-rogate for the actual presence of the microbe.Second, it is possible to use antigen-detectionplatforms that can be inexpensive, rapid, andcapable of use by personnel with limited train-ing. This is the case with the CrAg LFA for diag-nosis of cryptococcosis. Third, by judicious se-lection of antibodies, it is possible to produce atest with a broad or a very limited specificity,depending on the clinical needs for testing. Amajor limitation for antigen testing is the needto identify antigen surrogates for infection.CrAg is a well-characterized surrogate for infec-tion; however, identification of similar surro-gates for other infections is needed.

CONCLUDING REMARKS

Desirable properties of a diagnostic test are list-ed in Table 2. It is likely that several diagnosticplatforms will be needed to meet the diverserequirements of different fungal infections andthe resources available for testing. The ideal testwould detect infection early in the course ofdisease, perhaps before the advent of symptoms.Early diagnosis would enable administration ofantifungals at a time when treatment is mostlikely to be effective. For example, there is a20% increase in mortality of invasive candidia-sis if therapy is delayed by .12 h (Morrell et al.



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2005). An example of a diagnostic test that canidentify subacute infection is detection of cryp-tococcal polysaccharide in sera of patients whoenter antiretroviral therapy who do not havesymptoms of cryptococcal meningitis (Jarviset al. 2009). Second, a test with strong negativepredictive value would be of great value in man-aging patients at high risk for IFD. The neutro-penic patient with fever of unknown origin thatis unresponsive to broad-spectrum antibioticsis often treated empirically with antifungalagents. A test with a high negative predictivevalue could identify patients who should notbe given antifungal therapy. This would reducethe cost of patient care and reduce developmentof antibiotic resistance.

Many laboratory tests for diagnosis of fun-gal infection are typically performed at refer-ence laboratories, for example, tests for galacto-mannan or BG. The time to result presents abarrier to routine use of such tests. Similarly,high cost presents barriers to routine use of ad-vanced testing for fungal infection. A majorbarrier to use of many diagnostic approachesis the need for invasive procedures for samplecollection, particularly for high-risk patients.The ideal test would use readily accessible sam-ples such as blood or urine. An example is theCrAg LFA, which has a high sensitivity for diag-nosis of cryptococcosis using serum. Thisavoids the need for the lumbar puncture, a ma-jor advantage in resource-limited settings (Jar-vis et al. 2013). Similarly, testing of urine forHistoplasma galactomannan enables diagnosisof disseminated histoplasmosis and is usefulin early diagnosis of acute pulmonary histoplas-

mosis and in treatment follow-up (Wheat2006). Finally, most diagnostic tests for IFI re-quire a high level of operator expertise. Onceagain, this need for a relatively advanced infra-structure reduces access and raises barriers totesting.

New generations of fungal diagnostics mustreconcile the diverse needs of patients in devel-oped countries with advanced levels of medicalcare and those of patients in resource-limitedsettings. Many of the IFIs in countries with ad-vanced medical care are a consequence of theability to provide long-term critical care to pa-tients or the use of highly immunosuppressiveagents. In contrast, most deaths owing to fungalinfection globally occur in patients with AIDS,most often in settings with little or no infra-structure. On a global level, fungal diagnosticsmust be able to function in a setting of limitedinfrastructure.

Is it possible to reconcile the needs of re-source-limited countries and those of patientsin settings of advanced medical care? Diagnostictests that meet the criteria outlined in Table 2may be able to do so. Clearly, low-cost testingthat can be performed at the point-of-patientcare is critical in resource-limited countries.However, these same tests may be able to dra-matically improve outcome for the critically illpatient in advanced medical settings. For exam-ple, if testing could be performed at low costwith a noninvasive sample and produce a rapidresult, such testing would enable prospectivemonitoring of those patients at high risk forIFD. Prospective monitoring would identify in-fection before the occurrence of overt symp-toms and enable early treatment when it ismost likely to be effective.

ACKNOWLEDGMENTS

This work is supported in part by National In-stitutes of Health (NIH) grants AI014209,AI085548, AI096945, and AI102311 to T.R.K.B.W. is supported by grant W81XWH-13-C-0103 from the U.S. Army Medical Research andMateriel Command, Office of CongressionallyDirected Medical Research Programs, JointWarfighter Medical Research Program.

Table 2. Properties of ideal next-generation fungaldiagnostics

Detects infection early in course of diseaseStrong negative predictive valueShort time to result; ideally near point of careLow cost; inexpensive equipment/instrumentationUse of noninvasive sampleSuitable for use by personnel with limited trainingMinimal number of stepsUncomplicated interpretation; no downstream

analysis required

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2014; doi: 10.1101/cshperspect.a019299Cold Spring Harb Perspect Med Thomas R. Kozel and Brian Wickes Fungal Diagnostics

Subject Collection Human Fungal Pathogens

PathogensEvolutionary Perspectives on Human Fungal

John W. Taylor Pathogenicity TraitPolyphyletic Pathogens with a Convergent

−−Thermally Dimorphic Human Fungal Pathogens

Anita Sil and Alex Andrianopoulos

HumansBlack Molds and Melanized Yeasts Pathogenic to

de HoogAnuradha Chowdhary, John Perfect and G. Sybren

Mechanisms of Antifungal Drug Resistance

Howard, et al.Leah E. Cowen, Dominique Sanglard, Susan J.

within MacrophagesFungal Pathogens: Survival and Replication

MayAndrew S. Gilbert, Robert T. Wheeler and Robin C.

Cryptococcus and CandidaTreatment Principles for

Laura C. Whitney and Tihana Bicanic

Innate Defense against Fungal Pathogens

Hise, et al.Rebecca A. Drummond, Sarah L. Gaffen, Amy G.

The Human MycobiomePatrick C. Seed

PharmacodynamicsAntifungal Pharmacokinetics and

Alexander J. Lepak and David R. AndesInfectionsTreatment Principles for the Management of Mold

Dimitrios P. Kontoyiannis and Russell E. Lewis

EntomophthoralesHuman Fungal Pathogens of Mucorales and

al.Leonel Mendoza, Raquel Vilela, Kerstin Voelz, et

Adaptive Immunity to Fungi

al.Akash Verma, Marcel Wüthrich, George Deepe, et

GenomesFunctional Profiling of Human Fungal Pathogen

Alexi I. Goranov and Hiten D. Madhani

Pathogenic Species ComplexCandidaThe Siobhán A. Turner and Geraldine Butler

and Related SpeciesAspergillus fumigatus

R. Juvvadi, et al.Janyce A. Sugui, Kyung J. Kwon-Chung, Praveen

Fungal Morphogenesis

al.Xiaorong Lin, J. Andrew Alspaugh, Haoping Liu, et

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Fungal Diagnostics - CSHL Pperspectivesinmedicine.cshlp.org/content/4/4/a019299.full.pdfFungal Diagnostics Thomas R. Kozel1 and Brian Wickes2 1Department of Microbiologyand Immunology,