Identification of rare <i>Candida</i> species isolated from various clinical specimens: Comparison of different methods


Kucukkaya İ., Turan D., KÜÇÜKKAYA S., Bilgi E. A., Caglar E., ERKÖSE GENÇ G., ...Daha Fazla

BRAZILIAN JOURNAL OF MICROBIOLOGY, cilt.56, sa.3, ss.1775-1785, 2025 (SCI-Expanded) identifier identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 56 Sayı: 3
  • Basım Tarihi: 2025
  • Doi Numarası: 10.1007/s42770-025-01725-7
  • Dergi Adı: BRAZILIAN JOURNAL OF MICROBIOLOGY
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Agricultural & Environmental Science Database, Aquatic Science & Fisheries Abstracts (ASFA), BIOSIS, CAB Abstracts, EMBASE, Food Science & Technology Abstracts, MEDLINE, Veterinary Science Database
  • Sayfa Sayıları: ss.1775-1785
  • Anahtar Kelimeler: Candida auris, Candida Non-albicans, Identification methods, Rare Candida species
  • İstanbul Üniversitesi Adresli: Evet

Özet

In recent years, there has been an increase in invasive infections caused by "'rare' Candida species". The intrinsic resistance characteristics of these species along with their higher antifungal MIC values reduce the success of antifungal treatment. Although molecular and other sophisticated tests are reliable for the identification of many rare and newly emerging Candida species. Their implementation in routine laboratories is limited due to trained personnel, high costs, and specialized laboratory equipments. As a result, conventional methods and automated systems such as VITEK-2 and MALDI-TOF MS are still widely used in routine laboratories. This study evaluates and compares the identification capabilities of these commonly used tests for rare Candida species and provides guidance for rapid identification. A total of 201 isolates consist of 16 rare Candida species from various clinical samples were analyzed. Identification was performed using VITEK MS (as a gold standard) and results compared with VITEK-2, API ID 32 C, CHROMagar Candida, CHROMagar Candida Plus, and cornmeal agar with 1% Tween 80. VITEK MS identified all isolates and among them, the three most common species were Candida inconspicua (n:34; 16.9%), Candida lusitaniae (n:33; 16.4%), and Candida kefyr (n:31; 15.4%). Among these, a total of 107 isolates (53.2%) were correctly identified at the species level using the VITEK-2 system, whereas only 51 isolates (25.37%) were accurately identified with the API ID 32C system. However, when additional conventional methods (colony morphology and colour on chromogenic agar medium, Dalmau plate method, esculin hydrolysis test, growth at different temperatures) were applied, these identification rates increased to 81.5% (n = 164) and 54.7% (n = 110), respectively. Notably, even when used alone, the VITEK-2 system demonstrated a high identification success rate for Candida auris (83.3%), Candida lipolytica (85.7%), Candida lusitaniae (78.7%), Candida guilliermondii (83.8%), and Candida dubliniensis (86.4%). One of the primary reasons for misidentification was the absence of these microorganisms in the databases of the identification systems used. Additionally, all C. auris strains were correctly identified using CHROMagar Candida Plus medium, with no false-positive results observed for other Candida species. None of the identification methods, when applied alone, were able to correctly identify all 201 rare Candida species. Both VITEK-2 and API ID 32 C demonstrated limited accuracy for some rare species. However, evaluating microscopic and colony morphology on cornmeal agar and chromogenic media improved the accuracy of identification, especially for C. auris. In laboratories with limited access to MALDI-TOF MS or molecular methods, these tests should be used in combination to improve identification accuracy and provide alternative approaches for species differentiation. Also laboratories should update regular databases of their systems constantly. These organisms may be considered "rare" because they remain unidentified due to limitations in current identification methods and databases.