Panfungal Polymerase Chain Reaction for Identification of Fungal Pathogens in Formalin-Fixed Animal Tissues

Abstract

Identification of fungal organisms often poses a problem for pathologists because the histomorphology of some fungal organisms is not specific, fresh tissues may not be available, and isolation and identification in culture may take a long time. The purpose of this study was to validate the use of panfungal polymerase chain reaction (PCR) to identify fungal organisms from formalin-fixed paraffin-embedded (FFPE) tissues. Formalin-fixed paraffin-embedded curls were tested from 128 blocks containing canine, feline, equine, and bovine tissues with cutaneous, nasal, pulmonary, and systemic fungal infections, identified by the presence of fungi in histologic sections. Quantitative scoring of histologic sections identified rare (11.9%), occasional (17.5%), moderate (17.5%), or abundant (53.1%) fungal organisms. DNA was isolated from FFPE tissues and PCR was performed targeting the internal transcribed spacer 2 (ITS-2) region, a segment of noncoding DNA found in all eukaryotes. Polymerase chain reaction products were sequenced and identified at ≥97% identity match using the Basic Local Alignment Search Tool and the NCBI database of ITS sequences. Of the 128 blocks, 117 (91.4%) yielded PCR products and high-quality sequences were derived from 89 (69.5%). Sequence and histologic identifications matched in 79 blocks (61.7%). This assay was capable of providing genus- and species-level identification when histopathology could not and, thus, is a beneficial complementary tool for diagnosis of fungal diseases.

Keywords

DNA isolation formal-fixed paraffin-embedded fungi internal transcribed spacer lyticase mycology mycoses panfungal polymerase chain reaction pathology

An exponential growth in molecular diagnostics for infectious diseases has produced opportunities for confirming culture results and can be combined with other methods, such as histopathology, to confirm a diagnosis when culture is not possible.^1,5,14 DNA-based assays have been particularly helpful in diagnosis of fungal infections due to the speed of these tests compared to fungal culture, which can take 2 to 4 weeks.¹⁰ Many fungi are not readily cultivable in the laboratory and others require biosafety level 3 precautions. In addition to culture, fungal identification has relied on histopathology and cytology, although inherent challenges exist due to the subtle nuances in distinguishing fungal morphology.⁴¹

Polymerase chain reaction (PCR) assays have been developed to target and quantify specific genera and species of fungi from clinical samples.^11,13 These assays, however, require prior suspicion of the etiologic agent and are not available for every fungal organism, including emerging pathogens. The greatest utility has come from panfungal PCR, which amplifies conserved genes that are present in all fungi such as the ribosomal RNA (rRNA) region, including the large (28S) and small (18S) subunits, 5.8S, and internal transcribed spacer (ITS-1 and -2) and intergenic spacer (IGS) regions. Primers targeting these conserved rRNA sequences were originally developed for phylogenetic studies.⁴⁵ The resulting PCR products have regions that are hypervariable among fungi, allowing for identification by comparison of their sequences to a reference fungal database. The ITS regions are currently considered the superior regions for species resolution.⁴² Panfungal PCR can potentially identify any fungal agent without prior knowledge of its suspected identity, which can greatly reduce the time and cost spent on other molecular diagnostics.

Panfungal PCR on formalin-fixed paraffin-embedded (FFPE) tissues is useful when fresh tissue was not or could not be collected. It has been successfully applied in different human tissues and for a variety of fungal infections^30,36,39; however, less work has been performed in veterinary cases. Two of the human studies^30,36 have included small subsets of animal tissues (6 and 19, respectively) but were lacking in breadth of animal species and tissue types. Recently, there have been more extensive applications of this assay in cats,^3,8 but there is still a need for validation in other animals. Furthermore, there does not appear to be a general consensus on DNA extraction methods for FFPE tissues,^36,40 and many of the recommended kits are expensive or the protocols are time intensive.

Improving fungal diagnostics in veterinary medicine has the potential to not only improve animal healthcare but also enable proper selection of antifungal therapeutics, thereby reducing the development of resistance that has already been documented in poultry,⁷ dogs,³⁷ and other animals.¹² In addition, improvement in the accuracy and specificity of identifying fungi to the genus and species level would allow for better epidemiologic studies of current and emerging fungal pathogens. The purpose of this study was to validate the use of panfungal PCR on FFPE specimens in a variety of veterinary cases from birds, cats, camels, cattle, dogs, horses, and sheep. Furthermore, we aimed to test and optimize a cost-effective DNA extraction kit for amplification of fungal DNA from FFPE animal tissues.

Materials and Methods

Case Selection

From the pathology archives at the Texas A&M University College of Veterinary Medicine and Biomedical Sciences, the Dermatopathology Specialty Service, and the Texas A&M Veterinary Medical Diagnostic Laboratory, an exhaustive query was performed, and 128 paraffin blocks from 96 animals were selected for inclusion in this study. The initial selection criteria included the presence of fungi observed histologically (Supplemental Fig. 1), a diagnosis of primary fungal infection, and an attempt to select representative numbers of animal species, tissue types, and fungal etiologic agents. Once the blocks were selected, a single pathologist reviewed all archived slides to confirm the histologic diagnosis and to categorize the cases based on the amount of fungal organisms. Separate guidelines were used for yeast and hyphal morphologies since hyphae are generally more prolific, and cases were classified according to the number of organisms seen in 20 fields at 200× magnification as either rare (<3 yeast or <8 hyphae), occasional (3-10 yeast or 8-20 hyphae), moderate (10-15 yeast or 20-50 hyphae), or abundant (>15 yeast or >50 hyphae). The cases included tissues of dogs (66), cats (25), horses (19), cattle (7), birds (6), camels (3), sheep (1), or wild cats (1). The tissue types included oral cavity, respiratory tract, gastrointestinal tract, urinary tract, skin, brain, heart, lymph node, and bone. Previous ancillary testing included 69 cases with special stains, 26 with culture, 4 with cytology, 3 with PCR performed at other institutions, and 1 with immunohistochemistry. Most cases without ancillary testing showed strong fungal identification based on histopathology, and additional tests were deemed unnecessary due to costs or unavailability of fresh samples.

Twenty-four blocks were used to compare 2 commercially available kits for extraction of fungal DNA from FFPE tissues, another 52 blocks were used to further optimize the superior kit’s protocol, and the remaining 52 blocks were processed following the optimized protocol (Supplemental Fig. 1). From each block, sections totaling 50 μm in depth were cut in 5-μm scrolls with a microtome, and the blade was cleaned with absolute alcohol between blocks. The initial scroll for each block was discarded to minimize environmental and carry-over contamination. The scrolls were stored in DNase-, DNA-, and RNA-free microcentrifuge tubes until DNA was extracted.

ITS-2 and IRBP Polymerase Chain Reactions and Sequence Analysis

Fungal DNA was amplified by PCR targeting the internal transcribed spacer-2 (ITS-2) region, located between the coding regions for the 5.8S and small ribosomal RNA subunits, using the following panfungal primers: ITS3-F (5’-GCATCGATGAAGAACGCAGC-3’) and ITS4-R (5’-TCCTCCGCTTATTGATATGC-3’).⁴⁵ To evaluate quality of host DNA in each sample, a PCR targeting the Canis familiaris interphotoreceptor retinoid-binding protein (IRBP) gene, which is highly conserved in a large number of mammalian species, was performed using the following primers: IRBP-F (5’-TCCAACACCACCACTGAGATCTGGAC-3’) and IRBP-R (5’-GTGAGGAAGAAATCGGACTGGCC-3’).¹⁷ For both PCRs, the total reaction volume was 25 µl containing 1 μl of DNA extract, 0.5 µl 10uM forward primer, 0.5 µl 10uM reverse primer, 10.5 µl Ultrapure nuclease-free water (Invitrogen, Carlsbad, CA), and 12.5 µl Accustart II Toughmix (hot-start Taq polymerase; Quanta Biosciences, Gaithersburg, MD). Thermal cycler conditions were identical for both PCRs and consisted of 5 minutes at 95°C; 40 cycles of 95°C for 30 seconds, 57°C for 30 seconds, and 68°C for 30 seconds; and a final extension step at 68°C for 5 minutes. The amplification positive control included with every group of ITS-2 reactions was 1 μl of purified genomic DNA from Cryptococcus neoformans (ATTC 208821, strain H99). The positive control included with IRBP reactions was 1 μl of DNA extracted from a block containing an assortment of animal skin biopsies that were unremarkable. A negative control was included with both PCRs by adding 1 μl of UltraPure water (Invitrogen) instead of DNA. Samples that tested negative for ITS-2 and IRBP were repeated and spiked with 1 μl of positive control DNA to determine if false negative results were due to PCR inhibitors, likely from the formalin fixation.

All PCR products were separated on a 2% agarose gel made with 1× Tris boric acid ethylenediaminetetraacetic acid (TBE) buffer and GelRed^® (Biotium, Inc., Hayward, CA). The sample was separated by electrophoresis for 1 hour at 120 V and visualized with a UV transilluminator (GelDoc EZ™ system; Bio-rad Laboratories, Inc., Hercules, CA). Every ITS-2 band was excised from the gel, and the DNA was isolated using the E.Z.N.A.^® gel extraction kit (Omega Bio-Tek, Inc., Norcross, GA). This purified DNA was then submitted for sequencing (Eton Bioscience, Inc., San Diego, CA) using the ITS3-F and ITS4-R primers. Sequences were trimmed for quality by removal of the beginning and end of sequences, joined as contigs using Sequencher^® 4.8 (Gene Codes Corporation, Ann Arbor, MI) and then queried against the GenBank database using the Basic Local Alignment Search Tool (BLAST, NCBI).² Published GenBank accession matches were given precedence over unpublished ones. Sequences were assessed both quantitatively with the quality score given in Sequencher and qualitatively by visual inspection of the electropherogram. Sequences were identified as poor quality for the remaining analyses when the overall quality score was less than 70%, where no or little sequence was detected, and when a majority of peaks overlapped for each base. A fungal identification was made when a sequence matched the reference at ≥97% identity (for genus and species levels). When the sequence matched to more than 1 taxon at ≥97%, the one with the highest identity score was chosen. When there were multiple matches at the highest identity score, all matches were reported. Also, when there were multiple matches from different bands, all matches were reported. Interphotoreceptor retinoid-binding protein bands were considered positive or negative based on the presence or absence of a band at the same level as positive controls and were not submitted for sequencing.

Comparison of DNA Extraction From Paraffin Blocks Using 2 Commercially Available Kits

Two commercially available kits, the QIAGEN QIAamp^® DNA FFPE Tissue Kit and Deparaffinization Solution (QIAGEN, Valencia, CA) and MO BIO BiOstic^® FFPE Tissue DNA Isolation Kit (MO BIO, Carlsbad, CA), were compared through assessment of DNA extract quality (calculated as the number of IRBP-positive samples divided by the total number of samples),³⁶ PCR efficiency (calculated as the number of ITS-2 PCR-positive samples divided by the number of IRBP-positive samples),³⁶ and ITS-2 sequence quality (calculated as the number of high-quality sequences divided by the total number of samples). The 24 blocks included in this experiment included roughly equal numbers of blocks with either yeast or hyphae to evaluate the efficiency of DNA extraction from yeast capsules as well as hyphal mats and chitin-containing hyphae. The kit protocols (including an initial deparaffinization step) were followed according to the manufacturers’ directions, except the combined thickness of the scrolls included in the first step was standardized at 50 μm, and the incubation time with proteinase K was standardized at 2 hours for both protocols, the minimum recommended incubation time period. All extracted DNA was stored at –20°C prior to PCR amplification. For every block, fungal DNA was amplified through ITS-2 PCR and host DNA was amplified through IRBP PCR.

Optimization of the MO BIO BiOstic Kit Protocol

The MO BIO BiOstic kit protocol was further optimized to determine whether addition of lyticase would improve PCR efficiency. The DNA was extracted from scrolls of the 52 blocks following the manufacturer’s directions, except for a 2-hour incubation time with proteinase K. Following the proteinase K digestion, the lysate was equally divided into 2 microcentrifuge tubes. One of these tubes was then processed following the manufacturer’s directions, but 2U/100 μl of lyticase (L2524; Sigma-Aldrich, St Louis, MO) was added to the other tube and incubated at 37°C for 45 minutes.³⁶ After lyticase incubation, these samples were processed following the manufacturer’s directions. From each block, fungal DNA was amplified using the ITS-2 PCR and host DNA was amplified using the IRBP PCR. DNA quality, PCR efficiency, and sequence quality were calculated for all extractions.

Phylogenetic Analysis of Aspergillus spp

All Aspergillus spp sequences (n = 20) from this study were aligned with 8 reference sequences for A. flavus, A. fumigatus, A. niger, A. terreus, A. ustus, A. nidulans, A. felis, and Phialosimplex caninus (NCBI accession numbers: AF138287, AF138288, AF138904, AF138290, AF157507, AF138289,²⁴ KF558318.1,⁶ and GQ169311.1,²² respectively) using molecular evolutionary genetic analysis 7 (MEGA 7)⁴⁴ and multiple sequence comparison by log-expectation (MUSCLE) algorithm.¹⁶ The alignment was chopped at the 3’ end to exclude the ITS-1 region found in the reference sequences. The alignment was then imported into Geneious²⁷ and, using the Tamura-Nei model to calculate the distances, neighbor joining was performed, with F. solani (NCBI accession: HQ026747.1) selected as the outgroup. Bootstrap analysis was performed with 1000 replications and the consensus tree was reported, including the bootstrap support values at branching points.

Statistical Analysis

Contingency analysis was performed in JMP^® Pro 12 (SAS Institute, Inc., Cary, NC) to determine whether an association existed between the number of organisms observed histologically and ITS-2 PCR results, and with the quality of sequences derived from the PCR products. First, the correlation between variables was assessed with a chi-square test. When a significant correlation was identified for variables with multiple categories, the samples were then scored (yes/no) for the category in each variable that was suspected to contribute to the correlation. A second chi-square test was then performed between 1 category from each variable, and significant P values were reported.

Results

Comparison of 2 DNA Extraction Kits

DNA extraction using the QIAGEN QIAamp DNA FFPE Tissue Kit and MO BIO BiOstic FFPE Tissue DNA Isolation Kit was compared using 24 blocks of FFPE tissue from animals with suspected histoplasmosis (7), Malassezia infection (5), cryptococcosis (1), dermatophytosis (5), and phaeohyphomycosis (6) (Table 1). To assess the ability of the kit to remove inhibitors and preserve DNA quality, we calculated the number of IRBP-positive samples divided by the total number of samples tested (DNA quality) and found that the kits were equally successful at 100%. To test the ability of the kit to extract fungal DNA from the block, we calculated the number of ITS-2 PCR-positive samples divided by the number of IRBP-positive samples (PCR efficiency) and found that the kits were equally successful at 83%. The percentage of high-quality sequences derived from ITS-2 PCR products that yielded an identification (ITS-2 sequence quality) were the same for each kit at 71%. Based on DNA quality, PCR efficiency, and the quality of ITS-2 sequences for these 24 blocks, we determined that the MO BIO BiOstic kit was comparable to the QIAGEN QIAamp kit (with deparaffinization solution), but the MO BIO BiOstic kit had practicality advantages including a lower price and shorter protocol completion time. Therefore, we decided to further optimize the MO BIO BiOstic kit’s protocol for the extraction of fungal DNA from FFPE animal tissues.

Table 1.

Comparison of DNA Extraction Kits and Effect of Adding Lyticase, With Respect to DNA Quality, PCR Efficiency, and Sequence Quality.

	Kit Experiment		Lyticase Experiment^a
Measure	QIAGEN	MO BIO	MO BIO + Lyticase	MO BIO – Lyticase
Total no. of blocks	24	24	51	51
IRBP PCR positives, No.	24	24	49	49
ITS-2 PCR positives, No.	17	19	32	44
ITS-2 PCR faint bands, No.	3	1	11	2
ITS-2 sequence identification, No.	17	17	35	41
DNA quality,^b %	100	100	96.1	96.1
PCR efficiency,^c %	83.3	83.3	87.8	93.9
Sequence identification,^d %	70.8	70.8	68.6	80.4
Correlation with histology, %	70.8	70.8	57.7	68.6

Abbreviations: IRBP, interphotoreceptor retinoid-binding protein; ITS-2, internal transcribed spacer 2; MO BIO, MO BIO BiOstic^® FFPE Tissue DNA Isolation Kit; PCR, polymerase chain reaction; QIAGEN, QIAGEN QIAamp^® DNA FFPE Tissue Kit.

^aLyticase was added or not added, prior to DNA extraction using the MO BIO BiOstic kit.

^bNo. of IRBP positive / total number.

^c(ITS-2 positive + ITS-2 faint) / IRBP positive.

^dSequence identification / total number.

Optimization of the MO BIO BiOstic FFPE Tissue DNA Isolation Kit

The addition of lyticase digestion to the QIAGEN QIAamp kit protocol has been shown to improve PCR efficiency,^3,36 so we wanted to test whether this would also be true for the MO BIO BiOstic kit. A set of 52 blocks of FFPE tissue (different from those mentioned above) were included in this experiment. The calculated PCR efficiency for samples digested with lyticase was 87.8%, and for samples without lyticase was 93.9%. Furthermore, only 68.6% of the samples digested with lyticase produced a high-quality sequence for which identification was possible (ITS-2 sequence quality), and only 30 of 51 (57.7%) of the samples yielded a sequence that correlated with the histologic diagnosis. In comparison, 80.4% of samples without lyticase produced high-quality sequences and 35 of 51 (68.6%) of the samples yielded a sequence that correlated with the histology. We found that lyticase did not improve amplification of fungal DNA extracted from FFPE blocks using the MO BIO BiOstic kit and, therefore, was not necessary to be included in the optimized protocol.

Sequence Analysis of Archived Case Material

An additional 52 blocks were processed with the MO BIO BiOstic kit according to the manufacturer’s directions, except that proteinase K incubation time was 2 hours. For all processed samples (n = 128; using the MO BIO BiOstic kit without lyticase; Supplemental Table S1), 117 of 128 (91.4%) were ITS-2 PCR positive, 9 of 128 (7.0%) were negative, and 2 of 128 (1.5%) were smeared on an agarose gel (Supplemental Table S1). Of the blocks that were ITS-2 PCR positive, 37 of 117 (31%) demonstrated multiple PCR product bands on electrophoresis, 17 of 117 (14.5%) had faint band(s), and the remaining 63 of 117 showed a single strongly positive band. Most PCR positives (89/117) yielded high-quality sequences, although 28 of 117 (23.9%) yielded a poor-quality sequence. Roughly equal numbers of the poor-quality sequences came from faint bands (13/28) as from strongly positive bands. None of the poor-quality sequences were queried against the database. In 6 samples, nonfungal eukaryotic DNA was amplified, including the ITS-2 sequences of plants and mites.

To calculate sensitivity relative to histologic examination, the number of cases for which genus-level identification of fungi was possible through both histology and the panfungal PCR (n = 66) was divided by the number of cases for which identification was possible through histology (n = 95). The diagnostic assay had a sensitivity of 69.5% relative to histologic examination (Table 2).

Table 2.

Number of Fungal Identifications Made Through Histopathology or Panfungal Polymerase Chain Reaction (PCR) for Calculation of Sensitivity.^a

	Histopathology
PCR	+	–	Total
+	66	18	84
–	29	15	44
Total	95	33	128

^a+ indicates that fungal identification was made to at least the genus level.

A fungal identification was made through ITS-2 PCR and sequencing for 83 of 128 (65%) blocks tested. The vast majority of these sequence-derived identities (79/83, 96%) corresponded to those made histologically and only a small number (4%) identified as an organism that did not match the histologic descriptions. A genus- or species-level identification was made by BLAST analysis of sequences in 48 of 83 (60%) cases, whereas histologic evaluation was unable to do so. This included 24 samples for which sequencing provided a genus-level resolution, and 24 samples a species-level resolution. Three representative cases were selected to demonstrate the benefit of using panfungal PCR where histologic fungal morphology could not provide a genus-level identification (Figs. 1–3).

Figures 1–4.

Various mycotic infections in domestic species that were classified using panfungal polymerase chain reaction. Figure 1. Abomasum, cow, case No. 118. Large, irregular-walled fungal hyphae identified as Rhizopus microsporus are within a thrombosed vessel. Hematoxylin and eosin (HE). Figure 2. Urinary bladder, dog, case No. 125. Hyphae form large fungal mats and were classified into the Scedosporium spp/Pseudallescheria spp family. HE. Inset: PAS. Figure 3. Dermis, dog, case No. 63. Curvularia spicifera showing varied fungal morphology including yeasts (arrowhead) and pseudohyphae (long arrows). HE. Inset: PAS with yeasts, pseudohyphae, and hyphae (short arrows). Figure 4. Subcutis, horse, case No. 48. Multinucleated giant cells contain large Coccidioides posadasii fungal spherules. HE. Inset: PAS.

Some of the cases that were included from the archives also had ancillary testing performed, which enabled further comparison with culture results. Fungal culture had been successfully performed on 25 cases. Panfungal PCR and sequencing results correlated with culture in 12 of 25 (48%) cases, whereas 7 of 25 (28%) did not. Aspergillus was sequenced from 3 of the blocks, and from the tissues contained within these blocks, an isolate of Mucor had been cultured. The histopathologic findings for 2 of the cases were consistent with aspergillosis, agreeing with the sequencing results, and in the third, the hyphae could not be further identified. Last, 6 of the cases that had positive fungal culture results were PCR positive, but the resultant sequences were of poor quality. To highlight the utility of this panfungal PCR assay when culture could pose a threat to the clinical microbiology personnel, several cases of dimorphic fungal infections were included in this study, and 1 of these cases of coccidioidomycosis with rare organisms is presented in Fig. 4.

Due to the high prevalence of Aspergillus cases in the present study, and the previously proposed ability of the ITS-2 region to provide speciation within the genus, additional phylogenetic analysis was performed on Aspergillus sequences to confirm BLAST results and further validate this assay. From the 20 Aspergillus sequences included, 19 of 20 (95%) demonstrated correlation between the BLAST result and the phylogenetic clusters into which it was placed using neighbor-joining analysis (Table 3). The 1 sequence that did not fall into a cluster, Equ1, matched to A. fumigatus using BLAST and fell into the A. fumigatus cluster without repeat bootstrapping. Upon increasing the bootstrap replicates to 1000, Equ1 fell out of the A. fumigatus cluster in the consensus tree. Bootstrap support values indicate high confidence (>90) for the separation of major clusters by species except for the branch points leading to the A. fumigatus (75) and A. felis (83) clusters (Supplemental Fig. 2). Furthermore, the majority (17/20) of culture results also correlated with the BLAST sequencing results and the phylogenetic clade placement. There were 3 samples from which Mucor sp was cultured, but the sequencing matched to either A. fumigatus or A. felis.

Table 3.

Aspergillus Sequences Comparing BLAST, Phylogenetic, and Ancillary Testing Results.^a

SeqID	Case	BLAST Results	Phylogenetic Clade	Ancillary Testing
Avi1	24	A. flavus, A. oryzae	A. flavus	Aspergillus
Avi2	31	A. flavus, A. oryzae	A. flavus	Aspergillus
Avi3	32	A. terreus	A. terreus	Aspergillus terreus
Avi4	33	A. terreus	A. terreus	Aspergillus terreus
Bov1	27	A. fumigatus	A. fumigatus	—
Bov2	28	A. fumigatus	A. fumigatus	—
Can1	23	P. caninus	P. caninus	Aspergillus
Can2	40	A. terreus	A. terreus	Aspergillus
Can3	25	A. flavus, A. oryzae	A. flavus	Aspergillus
Can4	34	A. terreus	A. terreus	Aspergillus
Can5	38	A. terreus	A. terreus	Aspergillus
Can6	35	A. terreus	A. terreus	—
Can7	37	A. terreus	A. terreus	Aspergillus terreus
Can8	36	A. terreus	A. terreus	Aspergillus
Can9	39	A. terreus	A. terreus	Aspergillus
Equ1	29	A. fumigatus	—^b	Mucor spp ^b
Equ2	30	A. nidulans, A. quadrilineata	A. nidulans	—
Equ3	26	A. flavus, A. oryzae	A. flavus	Aspergillus
Fel1	41	A. aureolus, N. fischeri, A. felis	A. felis	Mucor spp ^b
Fel2	42	A. aureoles, N. fischeri, A. felis	A. felis	Mucor spp ^b

Abbreviations: Avi, avian; BLAST, Basic Local Alignment Search Tool; Bov, bovine; Can, canine; Equ, equine; Fel, feline.

^aBlocks with no phylogenetic clade placement or no culture results are marked with an em-dash (—).

^bResults that do not correlate with other categories.

Statistical analysis revealed no influence of host, tissue, or fungal type on PCR results (positive/negative). Respiratory tract samples in this study were significantly associated with an increased likelihood of having more than 1 band on gel electrophoresis (P = .015), and skin samples were significantly associated with having poor-quality sequences (P = .002). Chi-square analysis further demonstrated that the abundance of fungal organisms observed histologically was correlated with the PCR result (positive/faint/negative), number of bands, and quality of sequence. Rare organisms observed histologically were associated with an increased likelihood of having faint bands (P = .0054) and poor-quality sequences (P = .0045). Tissues with abundant organisms were associated with an increased likelihood of having a strongly positive (P = .0367), single band (P = .0061). Overall, poor-quality sequences were more likely obtained from blocks that demonstrated multiple PCR product bands on electrophoresis (P = .0053) and from blocks with faint bands (P < .0001).

Discussion

The panfungal PCR diagnostic assay presented here had a sensitivity of 69.5%, calculated as the percentage of cases for which ITS-2 sequencing provided a fungal identification. This sensitivity correlates well with previous studies, which also amplified the ITS-2 region from DNA extracts of FFPE tissues and showed sensitivities of 53.8%⁴ and 64.3%.³⁰ These 2 studies with similar sensitivities both targeted the ITS-2 regions but used other methods of DNA extraction. Our work demonstrated that this assay was successful in a wide variety of animal hosts, tissues, and fungi and, thus, is a valuable test when used in conjunction with histopathology for identification of fungal infections in animals. The results presented here also show that the MO BIO BiOstic FFPE Tissue DNA Isolation Kit was successful at isolating high-quality fungal DNA from FFPE animal tissues without requiring the use of lyticase. The time required for assay completion is approximately 3 days. The assay has the ability to identify fungi in FFPE specimens regardless of their transport temperature and, thus, in some cases may be superior to culture, although culture remains the gold standard.

Many fungi have characteristic histologic features, which can be used to identify fungi in typical presentations and representative sections. However, there are cases of atypical morphology, stemming from genotypic variation.²³ For example, some Cryptococcus cases have varying amounts of polysaccharide capsule and thus resemble yeasts of similar size, such as Candida or Blastomyces or one of the smaller yeasts such as Histoplasma or Candida.²⁰ Also, Candida has the ability to produce pseudohyphae and may even appear to be branching and, thus, could be confused with hyphae.³³ The present assay enabled sequencing of a variety of yeast from FFPE tissues including Blastomyces (3), Coccidioides (7), Cryptococcus (8), Histoplasma (16), and Malassezia (1). For 1 of the yeast cases, the histologic diagnosis could not be identified further than “yeast with narrow-based budding,” but sequencing was able to confirm the etiologic agent as Histoplasma sp.

There appears to be greater challenges in identifying hyphae compared to yeast, especially the hyaline septate molds that are indistinguishable from one another morphologically, including Fusarium and Scedosporium.²³ Even for Aspergillus species that have a characteristic branching angle, reports of misidentification include 1 study with 122 cases of Aspergillus identified based on histologic morphology, where only 83% had positive culture results for Aspergillus and the remaining culture results were positive for Scedosporium, Fusarium, Pseudallescheria, Phialophora, and Trichophyton.³¹ Although pigmented fungi may appear to be a straightforward identification on hematoxylin and eosin–stained sections, there exists variability in the amount of melanin produced by a genotypic variant, and thus, they could be confused with other hyaline hyphae, and these fungi cannot be identified to the genus level.^23,28 The present assay was able to sequence a variety of hyphae including Arthroderma (3), Aspergillus (20), Chaetomium (1), Curvularia (4), Curvularia/Bipolaris (8), Penicillium (1), Pythium (1), Rhizopus (3), and Scedosporium/Pseudallescheria (2). Eleven of these could not be identified further than hyphae based on histopathology alone. Overall, there were 3 cases in this study where the fungi observed histologically were not pigmented, but the fungal sequence identified a phaeohyphomycoses, further supporting the variability in melanin production in these pigmented fungi (Fig. 3).

Statistical analyses demonstrated that this assay is equally successful for both yeast and hyphae. There was not any influence of the type of tissue from which the DNA was isolated on PCR results (positive/negative); however, lung samples were more likely to have multiple PCR product bands, and skin samples were more likely to yield poor-quality sequences. The skin and respiratory tracts are known to have resident microbiota, which might influence PCR performed on these samples. It is also possible that the method of sample collection, or postmortem handling of the tissues prior to embedding, could have introduced contamination. Another limitation of this assay is that sensitivity decreases when organisms are rarely observed. More sensitive sequencing techniques, such as next-generation sequencing, might have greater success in amplifying fungal DNA when there are rare organisms in the embedded tissue. However, these techniques are costly and not yet suitable for diagnostics.

There was variable ability of the assay to derive genus- and species-level resolution. The sequence analysis provided genus- and species-level resolution in 36% of all cases where they could not be distinguished based only on histologic morphology. For some genera, such as those belonging to the phaeohyphomycoses, the ITS-2 region was unable to distinguish between genera such as Curvularia, Bipolaris, and Alternaria. On the contrary, the ITS-2 sequence was sufficient to derive a genus-level identification for fungi such as Coccidioides, Cryptococcus, Penicillium, Rhizopus, Scedosporium, and the fungal-like Pythium. In other cases, species-level resolution was possible for Aspergillus, Blastomyces, Histoplasma, and Microsporum species. The ability to distinguish between as many as 6 different Aspergillus species prompted further phylogenetic analysis to confirm these results derived through BLAST. Bioinformatics literature discusses the limitations of BLAST to distinguish between taxa and promotes the superior ability of neighbor-joining analysis to do so.³⁴ Agreement of the BLAST results, neighbor-joining analysis, and culture (Table 3) demonstrates that this assay is indeed capable of reliably speciating Aspergillus. The ability to differentiate between species of fungal organisms has clinical relevance due to the documented differences in susceptibility to antifungal agents between fungal genera, species,^21,29 and even subspecies.⁴³ Taken in conjunction with the documented rise of fungal resistance to antifungal agents specifically in Aspergillus,⁷ this tool may be extremely valuable for pathologists and clinicians treating these systemic mycoses.

It is interesting that 28 of 128 (21.9%) of all FFPE blocks returned sequences that were of poor quality, in spite of being purified from a strong band on the gel. Similar reports of ambiguous or poor-quality sequences were given in 1 of the original applications of this assay,³⁰ but this was not described in another more recent work.³⁶ Studies have shown through cloning that ITS sequence heterogeneity exists in some fungal genera including Fusarium ³⁸ and even in strains of Rhizopus microsporus.⁴⁶ Most likely, there has not been an exhaustive investigation into which fungal genera, species, or strains possess this ITS sequence heterogeneity. We hypothesize that at least some of the “poor-quality” sequences in this study were the result of ITS sequence heterogeneity present in the genomes of fungi infecting those animal tissues. Statistical analysis revealed that poor-quality sequences were more common when there were rare organisms on the slide, multiple bands were present, or the bands were faint. These findings elucidate some of the limitations of this assay, and further molecular work such as cloning and sequencing and/or high-throughput sequencing might be used to identify fungi observed histologically when panfungal PCR with second-generation sequencing fails to identify an etiologic agent.

Another rarely reported finding³⁰ that was encountered in the present study was the presence of multiple bands in a sample identified with gel electrophoresis. Use of the IRBP PCR enabled confirmation of high-quality extracted DNA for these samples, and thus the presence of multiple bands is not likely due to fragmentation of the DNA. It is possible that these additional sequences were amplified from commensal or contaminating fungi present in the tissues. At least for the skin,³⁵ gastrointestinal tract,¹⁸ and respiratory tract¹⁵ tissues, recent next-generation sequencing studies have identified an enormous diversity of commensal fungi inhabiting these tissues. Although these commensal fungi are rarely seen histologically, their DNA could still be present in the tissues and amplified with this assay, possibly producing a false positive result. An additional possibility that could explain the presence of multiple bands is variation in the copy number of the ITS coding region,^9,32 which is present as tandem repeats in some species of fungi.^25,26 Another recent application of this assay on tropical mycoses¹⁹ found that some of the amplified fungal ITS-2 sequences were not consistent with the histologic findings on those blocks. That study suggested that the amplified fungal DNA came from environmental contamination of the blocks. Although this is possible, it is also possible that commensal fungal DNA was amplified, as hypothesized here. This limitation indicates that the PCR and sequencing results provided by this assay need to be interpreted in the context of fungal morphology observed histologically.

In summary, this assay has been improved through reduction in cost and time, and it has been validated for a variety of animal hosts and fungal pathogens that commonly infect animals. Although some limitations still exist for the assay, it could provide a diagnosis when morphology based on histologic examination alone could not, and when fresh tissues were not available for fungal culture. Having a quick and accurate diagnosis enables the correct selection of antifungal therapeutics. Accurate identification of fungal infections in animals will enhance epidemiologic studies of current and emerging fungal threats not only to animals but to humans as well. Further development of genus- and species-specific PCR could help to resolve fungal identification for instances when the ITS region possesses sequence heterogeneity within species or when the ITS region is homogeneous across genera.

Footnotes

Acknowledgements

We thank Dr Xiaorong Lin, Department of Biology, Texas A&M University, for providing purified fungal genomic DNA, and Anna Blick, Department of Veterinary Pathobiology, Texas A&M University, for assistance with phylogenetic analysis.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Supplemental material for this article is available on the Veterinary Pathology website at .

References

Alexander

Pfaller

. Contemporary tools for the diagnosis and management of invasive mycoses. Clin Infect Dis. 2006;43(suppl 1):S15–S27.

Altschul

Gish

Miller

. Basic local alignment search tool. J Mol Biol. 1990;215(3):403–410.

Arunmozhi Balajee

Hurst

Chang

. Multilocus sequence typing of Histoplasma capsulatum in formalin-fixed paraffin-embedded tissues from cats living in non-endemic regions reveals a new phylogenetic clade. Med Mycol. 2013;51(4):345–351.

Babouee Flury

Weisser

Prince

. Performances of two different panfungal PCRs to detect mould DNA in formalin-fixed paraffin-embedded tissue: what are the limiting factors? BMC Infect Dis. 2014;14:692.

Balajee

Sigler

Brandt

. DNA and the classical way: identification of medically important molds in the 21st century. Med Mycol. 2007;45(6):475–490.

Barrs

van Doorn

Houbraken

. Aspergillus felis sp. nov., an emerging agent of invasive aspergillosis in humans, cats, and dogs. PLoS One. 2013;8(6):e64871.

Beernaert

Pasmans

Van Waeyenberghe

. Avian Aspergillus fumigatus strains resistant to both itraconazole and voriconazole. Antimicrob Agents Chemother. 2009;53(5):2199–2201.

Bernhardt

von Bomhard

Antweiler

. Molecular identification of fungal pathogens in nodular skin lesions of cats. Med Mycol. 2015;53(2):132–144.

Black

Dean

Byfield

. Determining fungi rRNA copy number by PCR. J Biomol Tech. 2013;24(1):32–38.

10.

Bosshard

. Incubation of fungal cultures: how long is long enough? Mycoses. 2011;54(5):e539–e545.

11.

Boyle

Olsen

. Rapid quantitative detection of chytridiomycosis (Batrachochytrium dendrobatidis) in amphibian samples using real-time Taqman PCR assay. Dis Aquat Organ. 2004;60(2):141–148.

12.

Brilhante

de Jesus Santos Rodrigues

de Souza Collares Maia Castelo-Branco

. Antifungal susceptibility and virulence attributes of animal-derived isolates of Candida parapsilosis complex. J Med Microbiol. 2014;63(pt 11):1568–1572.

13.

Brinkman

Haugland

Wymer

. Evaluation of a rapid, quantitative real-time PCR method for enumeration of pathogenic Candida cells in water. Appl Environ Microbiol. 2003;69(3):1775–1782.

14.

Chen

Halliday

Meyer

. A review of nucleic acid-based diagnostic tests for systemic mycoses with an emphasis on polymerase chain reaction-based assays. Med Mycol. 2002;40(4):333–357.

15.

Delhaes

Monchy

Frealle

. The airway microbiota in cystic fibrosis: a complex fungal and bacterial community—implications for therapeutic management. PLoS One. 2012;7(4):e36313.

16.

Edgar

. MUSCLE: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res. 2004;32(5):1792–1797.

17.

Ferreira

Gontijo

Cruz

. Alternative PCR protocol using a single primer set for assessing DNA quality in several tissues from a large variety of mammalian species living in areas endemic for leishmaniasis. Mem Inst Oswaldo Cruz. 2010;105(7):895–898.

18.

Findley

Yang

. Topographic diversity of fungal and bacterial communities in human skin. Nature. 2013;498(7454):367–370.

19.

Frickmann

Loderstaedt

Racz

. Detection of tropical fungi in formalin-fixed, paraffin-embedded tissue: still an indication for microscopy in times of sequence-based diagnosis? Biomed Res Int. 2015;2015:938721.

20.

Gazzoni

Severo

Salles

. Histopathology, serology and cultures in the diagnosis of cryptococcosis. Rev Inst Med Trop Sao Paulo. 2009;51(5):255–259.

21.

Goncalves

Stchigel

Cano

. In vitro antifungal susceptibility of clinically relevant species belonging to Aspergillus section Flavi. Antimicrob Agents Chemother. 2013;57(4):1944–1947.

22.

Greiner

Persoh

Weig

. Phialosimplex salinarum, a new species of Eurotiomycetes from a hypersaline habitat. IMA Fungus. 2014;5(2):161–172.

23.

Guarner

Brandt

. Histopathologic diagnosis of fungal infections in the 21st century. Clin Microbiol Rev. 2011;24(2):247–280.

24.

Henry

Iwen

Hinrichs

. Identification of Aspergillus species using internal transcribed spacer regions 1 and 2. J Clin Microbiol. 2000;38(4):1510–1515.

25.

Herrera

Vallor

Gelfond

. Strain-dependent variation in 18S ribosomal DNA copy numbers in Aspergillus fumigatus. J Clin Microbiol. 2009;47(5):1325–1332.

26.

Iwen

Hinrichs

Rupp

. Utilization of the internal transcribed spacer regions as molecular targets to detect and identify human fungal pathogens. Med Mycol. 2002;40(1):87–109.

27.

Kearse

Moir

Wilson

. Geneious Basic: an integrated and extendable desktop software platform for the organization and analysis of sequence data. Bioinformatics. 2012;28(12):1647–1649.

28.

Kimura

McGinnis

. Fontana-Masson–stained tissue from culture-proven mycoses. Arch Pathol Lab Med. 1998;122(12):1107–1111.

29.

Lass-Flörl

Alastruey-Izquierdo

Cuenca-Estrella

. In vitro activities of various antifungal drugs against Aspergillus terreus: global assessment using the methodology of the European Committee on Antimicrobial Susceptibility Testing. Antimicrob Agents Chemother. 2009;53(2):794–795.

30.

Lau

Chen

Sorrell

. Development and clinical application of a panfungal PCR assay to detect and identify fungal DNA in tissue specimens. J Clin Microbiol. 2007;45(2):380–385.

31.

Lee

Yun

Kim

. Discrepancy between histology and culture in filamentous fungal infections. Med Mycol. 2010;48(6):886–888.

32.

Longo

Rodriguez

da Silva Leite

. ITS1 copy number varies among Batrachochytrium dendrobatidis strains: implications for qPCR estimates of infection intensity from field-collected amphibian skin swabs. PLoS One. 2013;8(3):e59499.

33.

Luna

Candidiasis In: Connor

Chandler

, eds. Pathology of Infectious Diseases. Stanford, CT: Appleton and Lange; 1997:953–964.

34.

Matsen

Kodner

Armbrust

. pplacer: linear time maximum-likelihood and Bayesian phylogenetic placement of sequences onto a fixed reference tree. BMC Bioinformatics. 2010;11:538.

35.

Meason-Smith

Diesel

Patterson

. What is living on your dog’s skin? Characterization of the canine cutaneous mycobiota and fungal dysbiosis in canine allergic dermatitis. FEMS Microbiol Ecol. 2015;91(12). doi:10.1093/femsec/fiv139.

36.

Muñoz-Cadavid

Rudd

Zaki

. Improving molecular detection of fungal DNA in formalin-fixed paraffin-embedded tissues: comparison of five tissue DNA extraction methods using panfungal PCR. J Clin Microbiol. 2010;48(6):2147–2153.

37.

Nijima

Kano

Nagata

. An azole-resistant isolate of Malassezia pachydermatis. Vet Microbiol. 2011;149(1–2):288–290.

38.

O’Donnell

Cigelnik

. Two divergent intragenomic rDNA ITS2 types within a monophyletic lineage of the fungus Fusarium are nonorthologous. Mol Phylogenet Evol. 1997;7(1):103–116.

39.

Paterson

Seaton

McLaughlin

. Development of molecular methods for the identification of aspergillus and emerging moulds in paraffin wax embedded tissue sections. Mol Pathol. 2003;56(6):368–370.

40.

Rabelo-Goñalves

Roesler

Guardia

. Evaluation of five DNA extraction methods for detection of H. pylori in formalin-fixed paraffin-embedded (FFPE) liver tissue from patients with hepatocellular carcinoma. Pathol Res Pract. 2014;210(3):142–146.

41.

Sangoi

Rogers

Longacre

. Challenges and pitfalls of morphologic identification of fungal infections in histologic and cytologic specimens: a ten-year retrospective review at a single institution. Am J Clin Pathol. 2009;131(3):364–375.

42.

Schoch

Seifert

Huhndorf

. Nuclear ribosomal internal transcribed spacer (ITS) region as a universal DNA barcode marker for fungi. Proc Natl Acad Sci U S A. 2012;109(16):6241–6246.

43.

Singer

Meyer

Firacative

. Antifungal drug susceptibility and phylogenetic diversity among Cryptococcus isolates from dogs and cats in North America. J Clin Microbiol. 2014;52(6):2061–2070.

44.

Tamura

Stecher

Peterson

. MEGA6: Molecular Evolutionary Genetics Analysis version 6.0. Mol Biol Evol. 2013;30(12):2725–2729.

45.

White

TBT

Taylor

. Amplification and Direct Sequencing of Fungal Ribosomal RNA Genes for Phylogenetics. Cambridge, MA: Academic Press; 1990.

46.

Woo

Leung

. Internal transcribed spacer region sequence heterogeneity in Rhizopus microsporus: implications for molecular diagnosis in clinical microbiology laboratories. J Clin Microbiol. 2010;48(1):208–214.

Supplementary Material

Please find the following supplemental material available below.

For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.

For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.

0.00 MB

0.62 MB

0.02 MB