Skip to main content
Article thumbnail
Location of Repository

Trichophyton species: use of volatile fingerprints for rapid identification and discrimination.

By Natasha Sahgal, Barry Monk, Mohammad Wasil and Naresh Magan


Background: Fungal infection of the skin is a common clinical problem, and laboratory confirmation of the diagnosis is important to ensure appropriate treatment. The identification of the species of fungus is also important, because different fungal species have different modes of transmission, and this may be of importance both in preventing re-infection or in avoidance of infection of others. Objective: This study examined the potential of using volatile production patterns for the detection and discrimination between four Trichophyton species (T. mentagrophytes, T. rubrum, T. verrucosum and T. violaceum) in vitro on solid media and in broth culture. Methods: Two different sensor array systems (conducting polymer and metal oxide sensors) were examined for comparing the qualitative volatile fingerprints produced by these species over periods of 24-120 hrs in the headspace. The relative sensitivity of detection of two of the species (T. mentagrophytes, T. rubrum) was determined for log1 to log7 inoculum levels over the same time period. Results: The conducting polymer based system was unable to differentiate between species based on volatile fingerprints over the experimental period. However, metal oxide-based sensor arrays were found to be able to differentiate between the four species within 96 hrs of growth using PCA analysis which accounted for approximately 93% of the data in PC1 and 2 based on the qualitative volatile production patterns. This differentiation was confirmed by the Cluster analysis of the data using Euclidean distance and Ward’s linkage. Studies of the sensitivity of detection showed that for T. mentagrophytes and T. rubrum it was possible to differentiate between log3, log5 and log7 inoculum levels within 96 hrs. Conclusions: This is the first detailed study of the use of qualitative volatile fingerprints for identification and discrimination of dermatophytes. This approach could have potential for rapid identification of patient samples reducing significantly the time to treatment

Topics: Trichophyton species, early detection, electronic nose, volatile fingerprints
Publisher: Blackwell Publishing
Year: 2006
DOI identifier: 10.1111/j.1365-2133.2006.07549.x
OAI identifier:
Provided by: Cranfield CERES

Suggested articles


  1. (2003). Chemometrics: Data analysis for the laboratory and chemical plants. doi
  2. (2000). Detection and differentiation between mycotoxigenic and nonmycotoxigenic strains of Fusarium spp. using volatile production profiles and hydrolytic enzymes. doi
  3. (2004). Detection of Mycobacterium tunerculosis (TB) in vitro and in situ using electronic nose in combination with a neural netwrok system. Biosens Bioelectron doi
  4. (2005). Early detection and differentiation of spoilage of bakery products. Sens Actuators B doi
  5. (2002). Early detection of spoilage moulds in bread using volatile production patterns and quantitative enzyme assays. doi
  6. (2006). Electronic nose for quality and safety control. doi
  7. Electronic nose technology for the detection of microbial and chemical contamination of potable water. doi
  8. (2004). Electronic noses and disease diagnostics. doi
  9. (2001). Milk sense: a volatile sensory system for detection of microbial spoilage by bacteria and yeasts in milk. Sens Actuators B doi
  10. (2001). Rapid discrimination among dermatophytes, Scytalidium spp., and other fungi with a PCR-restriction fragment length polymorphism ribotyping method. doi
  11. (2003). Species identification and strain differentiation of dermatophyte fungi using polymerase chain reaction amplification and restriction enzyme analysis. doi
  12. (1995). The dermatophytes. Clin Microbiol Rev
  13. (1998). The how and why of electronic noses. doi
  14. (2002). Use of an electronic nose system for diganoses of urinary tract infections. Biosens Bioelectron
  15. (2000). Volatiles in grain as an indicator of fungal spoilage, odour descriptors for classifying spoiled grain and the potential for early detection using electronic nose technology: A review. doi

To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.