Fungi have increasingly been shown to cause various serious infections owing to the growing number of immunocompromised patients receiving chemotherapy, immunosuppressive agents, or medical intervention [
1-
3].
Candida species are the most common invasive fungal infection-causing pathogens; however, filamentous fungi, such as
Aspergillus species, also increasingly cause severe fungal infections with fatal outcomes [
1-
3]. Although immediate and accurate identification of the pathogen is critical for the treatment and management of fungal infections, conventional morphological examination has some limitations such as difficult differentiation of less common species, relatively complex identification training, and new emerging pathogens [
4,
5]. Molecular identification is used as the reference method for fungal identification; however, it requires expertise in interpretation, thus hindering its routine use in clinical laboratories [
4]. In contrast, the recently introduced matrix-assisted laser desorption ionization-time-of-flight mass spectrometry (MALDI-TOF MS) method is less labor intensive and can provide rapid identification results [
4,
5].
MALDI-TOF MS VITEK MS (bioMérieux, Marcy-l’Étoile, France) recently introduced an update of its knowledge base version 3.0 (v3.0) database, version 3.2 (v3.2). To date, only three studies have evaluated the performance of VITEK MS v3.0 system for the identification of filamentous fungi, showing that it may be influenced by the examined species distribution [
6-
8]. Furthermore, in contrast to the study by Rychert,
et al. [
7], few dermatophytes were evaluated in the other two studies [
6,
8]. In addition, the performance may vary depending on the instrument and database [
9,
10]. This study evaluated the performance of VITEK MS v3.0 system to identify 105 clinical filamentous fungi isolates using a Korean collection, representing 33 species from 14 genera, including various dermatophyte isolates. Owing to a database upgrade, strains that were added to the v3.2 database were additionally identified by the VITEK MS v3.2 system. This study was conducted with approval of the Institutional Review Board of Chonnam National University Hwasun Hospital, Hwasun, Korea (IRB CNUHH-2017-098).
All 105 filamentous fungi isolates were obtained from 12 Korean hospitals from 2016 to 2019, and duplicate isolates were excluded. Isolates were recovered from skin/tissue (N = 48), wound/pus (N = 22), respiratory specimens (N = 21), body fluids (N = 4), and other non-sterile specimens (N = 10). After sequencing the internal transcribed spacer or D1/D2 region of the 28S ribosomal DNA with additive sequencing of β-tubulin or calmodulin genes for
Aspergillus species [
10,
11], 37, 41, and 27 isolates were molecularly identified as
Aspergillus (nine species), dermatophytes (seven species), and other molds (17 species), respectively. The isolates were cultured on potato dextrose agar (PDA) or Sabouraud dextrose agar (SDA) and incubated for 2-23 days to acquire colonies at least 1 cm in diameter. Further, the isolates were prepared using the VITEK MS MOULD KIT (bioMérieux) and tested using the VITEK MS v3.0 system according to the manufacturer’s protocol. Additionally, only the species included in the v3.2 database were identified using the VITEK MS v3.2 system which was installed during the revision of this study. All isolates showing “no identification” or “multiple species identification” (two or more species were proposed) results at the initial VITEK MS testing were subcultured onto the initial culture media except two isolates (
Aspergillus fumigatus and
Trichophyton interdigitale), which were cultured on PDA for the initial testing and on SDA for the retesting. All isolates were retested following the same method using the VITEK MS MOULD KIT. The final additive testing results included the retesting results of the isolates initially showing “no identification” or “multiple species identification,” as well as the initial results of the other isolates showing acceptable identifications other than “no identification” or “multiple species identification.”
The VITEK MS results were compared with the sequence-based identification results and assigned to one of the four categories: (i) correct identification (identical to sequence-based identification), (ii) incomplete identification (either only the genus level was correctly identified or two or more species were proposed and one was correct), (iii) misidentification (none of the proposed species were correct), or (iv) no identification. As VITEK MS only displays species-complex-level identifications for some species, these were considered as the correct identification. McNemar’s, chi-square, and Fisher’s exact tests were performed to compare the correct identification rates. IBM SPSS Statistics for Windows version 25.0 (IBM Corp., Armonk, NY, USA) was used, and P < 0.05 was considered statistically significant.
Table 1 shows the results of 105 clinical filamentous fungi isolates identified using VITEK MS. At the initial testing, VITEK MS correctly identified 67.6% of
Aspergillus, 56.1% of dermatophytes, 48.1% of other molds, and 58.1% of the total mold isolates. Of the 105 isolates, 43 (41.0%) isolates had “no identification” (41 isolates) or “multiple species identification” (two isolates) results. These 43 isolates were retested using the same method; the correct identification rates for
Aspergillus, dermatophytes, other molds, and total mold isolates were 94.6%, 78.0%, 55.6%, and 78.1%, respectively, yielding a statistically significant increase for Aspergillus, dermatophytes, and total mold isolates compared with the initial testing (
P < 0.05). Two isolates (
Trichophyton verrucosum and
Alternaria astragali) showed “incomplete identification” (genus-level identification), and only two dermatophytes (
Trichophyton rubrum and
Microsporum gypseum) showed “misidentification.” The “no identification” rate was 5.4%, 14.6%, 40.7%, and 18.1% for
Aspergillus, dermatophytes, other molds, and total mold isolates, respectively.
Table 1
Clinical filamentous fungi isolates identified using the VITEK MS v3.0 system in comparison with sequence-based identification
Sequence-based identification (N of isolates) |
N (%) of isolates at initial testing |
N (%) of isolates at additive testing†
|
Correct ID |
Incomplete ID |
Mis-ID |
No ID |
Correct ID |
Incomplete ID |
Mis-ID |
No ID |
Aspergillus species (37)
|
|
|
|
|
|
|
|
|
|
|
Aspergillus flavus/oryzae (9) |
7 (77.8) |
0 |
0 |
2 (22.2)†
|
9 (100) |
0 |
0 |
0 |
|
Aspergillus fumigatus (8) |
6 (75.0) |
0 |
0 |
2 (25.0)†
|
7 (87.5) |
0 |
0 |
1 (12.5) |
|
Aspergillus niger (6) |
3 (50.0) |
1 (16.7)†
|
0 |
2 (33.3)†
|
5 (83.3) |
0 |
0 |
1 (16.7) |
|
Aspergillus terreus (4) |
4 (100) |
0 |
0 |
0 |
4 (100) |
0 |
0 |
0 |
|
Aspergillus sydowii (3) |
2 (66.7) |
0 |
0 |
1 (33.3)†
|
3 (100) |
0 |
0 |
0 |
|
Aspergillus tubingensis (3)*
|
1 (33.3) |
0 |
0 |
2 (66.7)†
|
3 (100) |
0 |
0 |
0 |
|
Aspergillus nidulans (2) |
1 (50.0) |
0 |
0 |
1 (50.0)†
|
2 (100) |
0 |
0 |
0 |
|
Aspergillus lentulus (1) |
0 |
0 |
0 |
1 (100)†
|
1 (100) |
0 |
0 |
0 |
|
Aspergillus westerdijkiae (1)*
|
1 (100) |
0 |
0 |
0 |
1 (100) |
0 |
0 |
0 |
|
Subtotal (37) |
25 (67.6) |
1 (2.7) |
0 |
11 (29.7) |
35 (94.6) |
0 |
0 |
2 (5.4) |
Dermatophytes (41) |
|
|
|
|
|
|
|
|
|
|
Trichophyton rubrum (12) |
8 (66.7) |
1 (8.3)†
|
0 |
3 (25.0)†
|
10 (83.3) |
0 |
1 (8.3) |
1 (8.3) |
|
Trichophyton interdigitale (11) |
7 (63.6) |
0 |
0 |
4 (36.4)†
|
9 (81.8) |
0 |
0 |
2 (18.2) |
|
Trichophyton tonsurans (3) |
0 |
0 |
0 |
3 (100)†
|
3 (100) |
0 |
0 |
0 |
|
Trichophyton verrucosum (3) |
1 (33.3) |
0 |
0 |
2 (66.7)†
|
1 (33.3) |
1 (33.3) |
0 |
1 (33.3) |
|
Microsporum canis (5) |
4 (80.0) |
0 |
0 |
1 (20.0)†
|
5 (100) |
0 |
0 |
0 |
|
Microsporum gypseum (4) |
1 (25.0) |
0 |
1 (25.0)‡
|
2 (50.0)†
|
1 (25.0) |
0 |
1 (25.0)‡
|
2 (50.0) |
|
Epidermophyton floccosum (3) |
2 (66.7) |
0 |
0 |
1 (33.3)†
|
3 (100) |
0 |
0 |
0 |
|
Subtotal (41) |
23 (56.1) |
1 (2.4) |
1 (2.4) |
16 (39.0) |
32 (78.0) |
1 (2.4) |
2 (4.9) |
6 (14.6) |
Other molds (27) |
|
|
|
|
|
|
|
|
|
|
Penicillium citrinum (5) |
1 (20.0) |
0 |
0 |
4 (80.0)†
|
1 (20.0) |
0 |
0 |
4 (80.0) |
|
Penicillium camemberti (1) |
0 |
0 |
0 |
1 (100)†
|
0 |
0 |
0 |
1 (100) |
|
Penicillium chrysogenum (1) |
1 (100) |
0 |
0 |
0 |
1 (100) |
0 |
0 |
0 |
|
Penicillium expansum (1) |
0 |
0 |
0 |
1 (100)†
|
0 |
0 |
0 |
1 (100) |
|
Fusarium solani (4) |
3 (75.0) |
0 |
0 |
1 (25.0)†
|
4 (100) |
0 |
0 |
0 |
|
Fusarium proliferatum (1) |
1 (100) |
0 |
0 |
0 |
1 (100) |
0 |
0 |
0 |
|
Alternaria alternata (3) |
3 (100) |
0 |
0 |
0 |
3 (100) |
0 |
0 |
0 |
|
Alternaria astragali (1)*
|
0 |
0 |
0 |
1 (100)†
|
0 |
1 (100) |
0 |
0 |
|
Scedosporium apiospermum (2) |
1 (50.0) |
0 |
0 |
1 (50.0)†
|
2 (100) |
0 |
0 |
0 |
|
Scedosporium boydii (1) |
0 |
0 |
0 |
1 (100)†
|
0 |
0 |
0 |
1 (100) |
|
Cladosporium cladosporioides (1) |
0 |
0 |
0 |
1 (100)†
|
0 |
0 |
0 |
1 (100) |
|
Cladosporium sphaerospermum (1)*
|
0 |
0 |
0 |
1 (100)†
|
0 |
0 |
0 |
1 (100) |
|
Acremonium sclerotigenum (1) |
1 (100) |
0 |
0 |
0 |
1 (100) |
0 |
0 |
0 |
|
Cunninghamella bertholletiae (1)*
|
0 |
0 |
0 |
1 (100)†
|
0 |
0 |
0 |
1 (100) |
|
Lichtheimia corymbifera (1) |
0 |
0 |
0 |
1 (100)†
|
0 |
0 |
0 |
1 (100) |
|
Paecilomyces variotii (1) |
1 (100) |
0 |
0 |
0 |
1 (100) |
0 |
0 |
0 |
|
Purpureocillium lilacinum (1) |
1 (100) |
0 |
0 |
0 |
1 (100) |
0 |
0 |
0 |
|
Subtotal |
|
|
|
|
|
|
|
|
|
Only database (25) |
13 (52.0) |
0 |
0 |
12 (48.0) |
15 (60.0) |
0 |
0 |
10 (40.0) |
|
All species (27) |
13 (48.1) |
0 |
0 |
14 (51.9) |
15 (55.6) |
1 (3.7) |
0 |
11 (40.7) |
Total molds (105) |
|
|
|
|
|
|
|
|
|
|
Only database (103) |
61 (59.2) |
2 (1.9) |
1 (1.0) |
39 (37.9) |
82 (79.6) |
1 (1.0) |
2 (1.9) |
18 (17.5) |
|
All species (105) |
61 (58.1) |
2 (1.9) |
1 (1.0) |
41 (39.0) |
82 (78.1) |
2 (1.9) |
2 (1.9) |
19 (18.1) |

Of the 33 species tested in this study,
Aspergillus tubingensis,
Aspergillus westerdijkiae, and
Cladosporium sphaerospermum were not included in the v3.0 database, but were included in the v3.2 database, whereas
Alternaria astragali and
Cunninghamella bertholletiae were not included in either database. All these isolates were not correctly identified using the VITEK MS v3.0 system; however,
A. tubingensis and
A. westerdijkiae were correctly identified using the VITEK MS v3.2 system. Nevertheless, the database needs continuous update and inclusion of additional species because it represents only a minor fraction of the filamentous fungi [
12].
According to three recent studies on the performance evaluation of VITEK MS v3.0 system for identification of filamentous fungi, the correct identification rate varied, ranging from 51.0% to 91.3%, most likely owing to the different composition of the tested isolates in each study [
6-
8]. In the present study, for all 105 filamentous fungi isolates representing commonly isolated species from Korean hospitals, the correct identification rate was 58.1% at the initial testing and 78.1% with retesting using VITEK MS v3.0 and v3.2 systems. The correct identification rate of dermatophytes was 78.0%, like the previous finding (84.5%) [
7]. In line with previous studies [
7,
8], retesting filamentous fungi isolates improved the correct identification rate, indicating the necessity for retesting. The reasons for the improvement following retesting are poorly understood; however, they may be attributed to the characteristics of the filamentous fungi. In contrast to bacteria, it can be difficult to obtain uniform conidia for testing from filamentous fungi colonies on solid media, depending on culture conditions. However, given the fact that misidentification rate was only 1.9%, filamentous fungi isolates that remain unidentified after repeated VITEK MS testing can be further evaluated by sequence analysis or other morphological evaluation without the risk of misidentification.
The detailed VITEK MS retesting results for the 43 isolates, including 12
Aspergillus, 17 dermatophyte, and 14 other molds, are shown in
Table 2. Of the 43 isolates, 10 (83.3%)
Aspergillus, nine (52.9%) dermatophyte, and two (14.3%) other molds were correctly identified. Other molds, including
Penicillium,
Cladosporium,
Cunninghamella, and
Lichtheimia species, were not identified despite retesting. The correct identification rate after retesting was significantly higher for isolates cultured on SDA (
P = 0.012) but were similar irrespective of increased or decreased incubation time. This difference might be due to species selection bias, as other mold isolates were mostly cultured on PDA.
Table 2
Clinical filamentous fungi isolates that were retested using the VITEK MS v3.0 system
Sequence-based identification (N of isolates) |
Initial testing |
Retesting†
|
|
|
Culture medium |
Incubation time (days) |
ID results |
Culture medium |
Incubation time (days) |
Aspergillus species (12) |
|
|
|
|
|
|
|
Aspergillus flavus/oryzae
|
SDA |
5 |
Aspergillus flavus
|
SDA |
6 |
|
Aspergillus flavus/oryzae
|
SDA |
7 |
Aspergillus flavus
|
SDA |
3 |
|
Aspergillus fumigatus
|
PDA |
13 |
Aspergillus fumigatus
|
SDA |
3 |
|
Aspergillus fumigatus
|
PDA |
2 |
No ID |
PDA |
4 |
|
Aspergillus niger‡
|
SDA |
14 |
Aspergillus niger complex
|
SDA |
4 |
|
Aspergillus niger
|
SDA |
5 |
Aspergillus niger complex
|
SDA |
2 |
|
Aspergillus niger
|
PDA |
2 |
No ID |
PDA |
4 |
|
Aspergillus sydowii
|
PDA |
7 |
Aspergillus sydowii
|
PDA |
18 |
|
Aspergillus tubingensis*
|
PDA |
5 |
Aspergillus niger complex
|
PDA |
5 |
|
Aspergillus tubingensis*
|
PDA |
7 |
Aspergillus niger complex
|
PDA |
5 |
|
Aspergillus nidulans
|
PDA |
3 |
Aspergillus nidulans
|
PDA |
4 |
|
Aspergillus lentulus
|
PDA |
8 |
Aspergillus lentulus
|
PDA |
6 |
Dermatophytes (17) |
|
|
|
|
|
|
|
Trichophyton rubrum‡
|
SDA |
9 |
No ID |
SDA |
13 |
|
Trichophyton rubrum
|
PDA |
13 |
Trichophyton rubrum
|
PDA |
17 |
|
Trichophyton rubrum
|
PDA |
16 |
Trichophyton rubrum
|
PDA |
12 |
|
Trichophyton rubrum
|
SDA |
9 |
Fusarium proliferatum
|
SDA |
13 |
|
Trichophyton interdigitale
|
PDA |
10 |
Trichophyton interdigitale
|
PDA |
6 |
|
Trichophyton interdigitale
|
PDA |
20 |
Trichophyton interdigitale
|
SDA |
12 |
|
Trichophyton interdigitale
|
PDA |
16 |
No ID |
PDA |
12 |
|
Trichophyton interdigitale
|
PDA |
17 |
No ID |
PDA |
12 |
|
Trichophyton tonsurans
|
SDA |
9 |
Trichophyton tonsurans
|
SDA |
13 |
|
Trichophyton tonsurans
|
SDA |
9 |
Trichophyton tonsurans
|
SDA |
13 |
|
Trichophyton tonsurans
|
SDA |
9 |
Trichophyton tonsurans
|
SDA |
20 |
|
Trichophyton verrucosum
|
PDA |
14 |
Trichophyton interdigitale
|
PDA |
8 |
|
Trichophyton verrucosum
|
PDA |
14 |
No ID |
PDA |
12 |
|
Microsporum canis
|
SDA |
9 |
Microsporum canis
|
SDA |
23 |
|
Microsporum gypseum
|
SDA |
9 |
No ID |
SDA |
13 |
|
Microsporum gypseum
|
SDA |
9 |
No ID |
SDA |
13 |
|
Epidermophyton floccosum
|
SDA |
13 |
Epidermophyton floccosum
|
SDA |
14 |
Other molds (14) |
|
|
|
|
|
|
|
Penicillium citrinum
|
PDA |
10 |
No ID |
PDA |
8 |
|
Penicillium citrinum
|
PDA |
10 |
No ID |
PDA |
8 |
|
Penicillium citrinum
|
PDA |
10 |
No ID |
PDA |
8 |
|
Penicillium citrinum
|
PDA |
13 |
No ID |
PDA |
8 |
|
Penicillium camemberti
|
PDA |
3 |
No ID |
PDA |
14 |
|
Penicillium expansum
|
PDA |
14 |
No ID |
PDA |
14 |
|
Fusarium solani
|
SDA |
5 |
Fusarium solani complex
|
SDA |
6 |
|
Alternaria astragali*
|
PDA |
4 |
Alternaria alternata
|
PDA |
4 |
|
Scedosporium apiospermum
|
SDA |
5 |
Scedosporium apiospermum
|
SDA |
6 |
|
Scedosporium boydii
|
PDA |
10 |
No ID |
PDA |
8 |
|
Cladosporium cladosporioides
|
PDA |
7 |
No ID |
PDA |
14 |
|
Cladosporium sphaerospermum*
|
PDA |
16 |
No ID |
PDA |
5 |
|
Cunninghamella bertholletiae*
|
PDA |
2 |
No ID |
PDA |
4 |
|
Lichtheimia corymbifera
|
PDA |
6 |
No ID |
PDA |
4 |
Total (43) |
|
|
|
|
|
|

VITEK MS correctly identified commonly isolated
Aspergillus species, as well as some clinically relevant species showing antifungal resistance such as
Aspergillus terreus and
Aspergillus lentulus [
13]. In the case of
Fusarium species, which are multiresistant organisms and the second most common filamentous fungi causing invasive fungal infections in immunocompromised patients [
14], VITEK MS correctly identified all five
Fusarium isolates, showing a higher rate of correct identification than that in previous studies (93.0% and 65.4%) [
7,
8].
T. rubrum is the most frequently isolated dermatophyte in Korea [
15]. Rychert,
et al. [
7] demonstrated that dermatophytes other than
T. rubrum are not always correctly identified at the species level using the VITEK MS v3.0 system. In the present study, the correct identification rate with retesting for
T. rubrum was 83.3%, while that for dermatophytes other than
T. rubrum was 75.9%. Furthermore, the correct identification rate for other molds was significantly lower than that for
Aspergillus and dermatophytes (
P < 0.05). However, the correct identification rate for other molds increased from 55.6% to 76.5%, excluding clinically insignificant species such as
Penicillium and
Cladosporium species, which are often regarded as contaminants [
16,
17]. VITEK MS correctly identified all
Alternaria alternata,
Acremonium sclerotigenum,
Paecilomyces variotii, and
Purpureocillium lilacinum isolates. VITEK MS seems to provide a correct identification for most clinically relevant filamentous fungi.
This study represents the first performance evaluation of the VITEK MS v3.0 system for the identification of clinically relevant filamentous fungi using the Korean collection, some of which were supplemented by the VITEK MS v3.2 system. VITEK MS provided 94.6% and 78.0% correct identification rates for Aspergillus and dermatophytes, respectively, which were commonly recovered in Korea, with only 1.9% rate of misidentification. In addition, it could differentiate clinically critical species exhibiting antifungal resistance such as A. terreus, A. lentulus, and Fusarium solani. Although VITEK MS has some limitations, such as its narrow-spectrum database and limited identification of rarely isolated species, it can help overcome the disadvantages of conventional methods, especially for Aspergillus species and dermatophytes.
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