Journals / Journal of Health Sciences and Medicine / 2026 / Volume: 9 Issue: 4

Preliminary evaluation of a SYBR Green-based screening approach for selected fungal targets in simulated cerebrospinal fluid samples

Pages
—
Publication Date
2026-07-20
🏛️Bibliographic metadata and full text access for this article are provided via DergiPark.
DergiPark Record ↗
✨

AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Further validation with clinically positive CSF samples is required before clinical implementation.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Aims: Most commercial multiplex polymerase chain reaction (PCR) panels primarily detect bacterial and viral pathogens and usually include only Cryptococcus among fungal targets.
📊
Key Findings & Data:The assay was initially designed as a SYBR Green-based screening method; however, because overlapping melting temperatures limited reliable target discrimination, a three-target probe-based confirmation step was subsequently incorporated for Candida spp., Aspergillus spp., and Fusarium spp.
💡
Conclusion & Impact:Further validation with clinically positive CSF samples is required before clinical implementation.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:CNS infection · fungal diagnosis · real-time PCR

Abstract

Aims: Most commercial multiplex polymerase chain reaction (PCR) panels primarily detect bacterial and viral pathogens and usually include only Cryptococcus among fungal targets. However, other fungi such as Candida and Aspergillus are increasingly recognized as important causes of central nervous system (CNS) infections, especially in immunocompromised patients. This study aimed to preliminarily develop a multiplex real-time PCR approach for the detection of selected fungal targets in cerebrospinal fluid (CSF)-based samples. The assay was initially designed as a SYBR Green-based screening method; however, because overlapping melting temperatures limited reliable target discrimination, a three-target probe-based confirmation step was subsequently incorporated for Candida spp., Aspergillus spp., and Fusarium spp. Methods: Target-specific primers were used for Candida spp., Aspergillus spp., Fusarium spp., Mucor spp., Rhizopus spp., and Trichosporon spp. in the SYBR Green-based screening step. In addition, probe-based primer/probe sets were evaluated for Candida spp., Aspergillus spp., and Fusarium spp. to improve target-specific discrimination. The assay was evaluated using CSF-based simulated samples and tested against selected bacterial backgrounds. Results: The SYBR Green-based screening step produced amplification signals for the selected fungal targets, but melting curve analysis alone was insufficient for reliable discrimination because of overlapping Tm values. In the probe-based format, Candida spp., Aspergillus spp., and Fusarium spp. generated target-specific signals in their assigned fluorescence channels, with no off-target amplification in the tested bacterial background. These findings support the added value of probe-based confirmation while highlighting the preliminary nature of the assay. Conclusion: This preliminary study suggests that an in-house multiplex real-time PCR approach may provide a feasible framework for detecting selected fungal targets in CSF-based simulated samples. While SYBR Green-based amplification enabled initial screening, overlapping melting temperatures limited reliable target discrimination. Probe-based testing in a limited subset suggested a potential role in reducing interpretive ambiguity. Further validation with clinically positive CSF samples is required before clinical implementation.

🔖

Cite This Article

Şahin, E. A., Kalkancı, A., Çeltikçi, E., Şahin, M. Ç., Fidan, I., Çağlar, K. (2026). Preliminary evaluation of a SYBR Green-based screening approach for selected fungal targets in simulated cerebrospinal fluid samples. Journal of Health Sciences and Medicine, Volume: 9 Issue: 4. https://doi.org/10.32322/jhsm.1937982

📄 Full Text PDF Viewer

📄

PDF görüntüleyici hazırlanıyor...

References (25)

  1. Albuquerque RC, Moreno ACR, Santos SR, Ragazzi SLB, Martinez MB. Multiplex-PCR for diagnosis of bacterial meningitis. Braz J Microbiol. 2019;50(2):435-443. doi:10.1007/s42770-019-00055-9
  2. Parikh V, Tucci V, Galwankar S. Infections of the nervous system. Int J Crit Illn Inj Sci. 2012;2(2):82-97.
  3. Góralska K, Błaszkowska J, Dzikowiec M. Neuroinfections caused by fungi. Infection. 2018;46(4):443-459. doi:10.1007/s15010-018-1152-2
  4. Lino R, Guimarães AR, Sousa E, Azevedo M, Santos L. Emerging fungal infections of the central nervous system in the past decade: a literature review. Infect Dis Rep. 2024;16(5):952-976. doi:10.3390/idr16050076
  5. Zhang Z, Song Y, Kang J, et al. Epidemiology of patients with central nervous system infections, mainly neurosurgical patients: a retrospective study from 2012 to 2019 in a teaching hospital in China. BMC Infect Dis. 2021;21:826. doi:10.1186/s12879-021-06561-2
  6. Leber AL, Everhart K, Balada-Llasat JM, et al. Multicenter evaluation of BioFire FilmArray meningitis/encephalitis panel for detection of bacteria, viruses, and yeast in cerebrospinal fluid specimens. J Clin Microbiol. 2016;54(9):2251-2261.
  7. Chong B, Kennedy KJ. Comparison of a commercial real-time PCR panel to routine laboratory methods for the diagnosis of meningitis-encephalitis. Pathology. 2021;53(5):635-638. doi:10.1016/j.pathol.2020. 09.029
  8. Long F, Kong M, Wu S, et al. Development and validation of an advanced fragment analysis-based assay for the detection of 22 pathogens in the cerebrospinal fluid of patients with meningitis and encephalitis. J Clin Lab Anal. 2019;33(3):e22707. doi:10.1002/jcla.22707
  9. de Souza MB, de Carvalho E, Cergole-Novella MC, et al. Multiplex PCR to Streptococcus pneumoniae serotype identification directly in cerebrospinal fluid samples. Eur J Clin Microbiol Infect Dis. 2023;42(3):255-266. doi:10.1007/s10096-023-04547-3
  10. Sugita T, Nishikawa A, Ikeda R, Shinoda T. Identification of medically relevant Trichosporon species based on sequences of internal transcribed spacer regions and construction of a database for Trichosporon identification. J Clin Microbiol. 1999;37(6):1985-1993. doi:10.1128/JCM.37.6.1985-1993.1999
  11. Springer J, Lackner M, Ensinger C, et al. Development and application of two independent real-time PCR assays to detect clinically relevant Mucorales species. J Med Microbiol. 2016;65(3):227-234. doi:10.1099/jmm.0.000218
  12. Springer J, White PL, Hamilton S, et al. A comparison of Aspergillus and Mucorales PCR testing of different bronchoalveolar lavage fluid fractions from patients with suspected invasive pulmonary fungal disease. J Clin Microbiol. 2018;56(2):e01655-17. doi:10.1128/JCM.01655-17
  13. Karlsson I, Edel-Hermann V, Gautheron N, et al. Genus-specific primers for study of Fusarium communities in field samples. Appl Environ Microbiol. 2016;82(2):491-501. doi:10.1128/AEM.02748-15
  14. Ebihara M, Makimura K, Sato K, Abe S, Tsuboi R. Molecular detection of dermatophytes and nondermatophytes in onychomycosis by nested polymerase chain reaction based on 28S ribosomal RNA gene sequences. Br J Dermatol. 2009;161(5):1038-1044. doi:10.1111/j.1365-2133.2009. 09249.x
  15. He Z, Huo X, Piao J. Rapid preparation of Candida genomic DNA: combined use of enzymatic digestion and thermal disruption. AMB Express. 2023;13(1):1. doi:10.1186/s13568-022-01500-z
  16. Murthy JMK, Sundaram C. Fungal infections of the central nervous system. Handb Clin Neurol. 2014;121:1383-1401. doi:10.1016/B978-0-7020-4088-7.00095-X
  17. Köffer J, Frontzek A, Eigner U. Development and validation of a bacterial gastrointestinal multiplex RT-PCR assay for use on a fully automated molecular system. J Microbiol Methods. 2023;210:106754. doi:10.1016/j.mimet.2023.106754
  18. Zhuo X, Zhao J, Wang L, et al. Development and evaluation of a multiplex quantitative polymerase chain reaction assay for detecting bacteria associated with lower respiratory tract infection. Int J Infect Dis. 2022;122:202-211. doi:10.1016/j.ijid.2022.05.052
  19. He P, Wang H, Yan Y, Zhu G, Chen Z. Development and application of a multiplex fluorescent PCR for Shigella detection and species identification. J Fluoresc. 2022;32(2):707-713. doi:10.1007/s10895-021-02876-0
  20. Belem LRW, Ibemgbo SA, Gomgnimbou MK, et al. Development of multiplex molecular assays for simultaneous detection of dengue serotypes and chikungunya virus for arbovirus surveillance. Curr Issues Mol Biol. 2024;46(3):2093-2104. doi:10.3390/cimb46030134
  21. Gosiewski T, Jurkiewicz-Badacz D, Sroka A, Brzychczy-Włoch M, Bulanda M. A novel, nested, multiplex, real-time PCR for detection of bacteria and fungi in blood. BMC Microbiol. 2014;14:144. doi:10.1186/1471-2180-14-144
  22. Van de Groep K, Bos MP, Savelkoul PHM, et al. Development and first evaluation of a novel multiplex real-time PCR on whole blood samples for rapid pathogen identification in critically ill patients with sepsis. Eur J Clin Microbiol Infect Dis. 2018;37(7):1333-1344. doi:10.1007/s10096-018-3255-1
  23. Bernal-Martínez L, Buitrago MJ, Castelli MV, Rodríguez-Tudela JL, Cuenca-Estrella M. Development of a single-tube multiplex real-time PCR to detect the most clinically relevant Mucormycetes species. Clin Microbiol Infect. 2013;19(1):E1-E7. doi:10.1111/j.1469-0691.2012.03976.x
  24. Han H, Hu Z, Sun S, et al. Simultaneous detection and identification of bacteria and fungi in cerebrospinal fluid by TaqMan probe-based real-time PCR. Clin Lab. 2014;60(8):1287-1293. doi:10.7754/clin.lab.2013.130417
  25. KrishnanNair Geetha D, Sivaraman B, Rammohan R, Venkatapathy N, Solai Ramatchandirane P. A SYBR Green based multiplex real-time PCR assay for rapid detection and differentiation of ocular bacterial pathogens. J Microbiol Methods. 2020;171:105875. doi:10.1016/j.mimet.2020.105875