INTRODUCTION CONCLUSIONS METHODS RESULTS
Nail Raman spectroscopy: a promising method for the diagnosis of onychomycosis. An ex vivo pilot study Nikolaos Kourkoumelis1, Georgios Gaitanis2, Aristea Velegraki3,4, Ioannis D. Bassukas2 1 Department of Medical Physics, School of Health Sciences, 2Department of Skin and Venereal Diseases, University of Ioannina, Greece, 3Mycology Research Laboratory, Department of Microbiology, Medical School, National and Kapodistrian University of Athens, Greece,4 Biomedicine SA, Athens, Greece
INTRODUCTION
Onychomycosis is a common infection of the nails, especially the toenails, with an estimated mean prevalence of 4.3% in the general population in Europe and North America with the dermatophyte Trichophyton rubrum identified in 44.9% of the cases (95% CI: 33.8–56.0), followed by yeasts (predominantly Candida species) in 21.1% (95% CI: 11.0–31.3).
RESULTS
Tentative assignment of the Raman bands for normal and infected nail samples.
Ex vivo, mean Raman spectra with standard deviations (SDev, cyan area) of normal nails (N=26) and infected nails: T. rubrum (N=12), Candida spp. (N=14). The spectra (solid lines) are artificially offset for clarity. The strong Raman band at 500-520 cm-1 is attributed to the disulfide stretching bond of cystine and cysteine residues. Samples infected with Candida species feature a “shoulder” at 519 cm-1 which is typical of the less stable gauche-gauche-trans conformation indicating heterogeneity among the S-S bonds conformation. Samples with T. rubrum are the only ones which show two weak, but distinct, Raman bands at 619 cm-1 and 648 cm-1 which correspond to the C-S stretching vibration. A striking difference in Raman scattering also occurs at 1550 cm-1; this peak which is attributed to amide II (60% N–H bend and 40% C–N stretch) and tryptophan (Trp), is absent from the samples of nails infected by Candida species. Strong bands found in common across all three groups of samples include the symmetric ring breathing mode and the C–H in-plane bending mode of phenylalanine (Phe) as well as the amide I, II and III bands.
The gold standard of diagnosis remains the microscopic investigation of nail clippings coupled with inoculation of the infected nails in appropriate culture media. Direct microscopy is inexpensive and easy to perform, yet its sensitivity is operator dependent. Culture is the mainstay of clinical mycology and holds high predictive value when a dermatophyte is grown after 3-4 weeks of incubation; yet, it has lower sensitivity compared to microscopy. Raman spectroscopy is able to detect subtle biochemical changes in biological samples providing chemical and compositional information. In principle, it is suitable for biological specimens because it does not interfere with water molecules, it is non-invasive and it requires minimal sample preparation; however, it typically suffers from auto-fluorescence and low signal-to-noise ratio.
PCA Scores plot with Hotelling T2 (0.95) ellipse, partitioning 52 nail samples within the area defined by the two first PCs; (sl: sensu lato).
The purpose of this study was to evaluate the discriminative power of Raman spectroscopy in the ex vivo differentiation of nail clinical samples with confirmed infection by the dermatophyte T. rubrum or Candida species from healthy (normal) nails. Moreover, to our knowledge, this is the first study that predictive classification modelling is applied for the diagnosis of onychomycosis in clinical nail samples, addressing the potential of Raman spectroscopy in the clinic.
METHODS
Predicted values with estimated uncertainties for the test set (14 samples) calibrated by PLS-DA (C: Candida spp., T: T.rubrum, N: Normal).
Samples
Institutional Ethical Review Committee permission was granted and Raman measurements were performed on nail clippings (N=52) that had both direct KOH examination and positive culture for either Trichophyton rubrum (N=12) or Candida species, including species of the Candida parapsilosis complex (N=11), Candida glabrata (N=1), and Candida albicans (N=2). The negative controls (N=26) were clippings of healthy nails from volunteers. Spectra were collected at 30 mW output power, with 785 nm diode laser at ~4.5 cm-1 resolution and 5 s accumulation time, in the 200–3200 cm-1 spectral range. For each nail clipping, four Raman spectra were measured on different spots to ensure statistical variability (208 spectra in total).
CONCLUSIONS
Raman spectroscopy efficiently differentiated 3 classes of nails: healthy, T. rubrum and Candida infected; Raman characterization of clinical data of untreated nails has the obvious advantages of providing real time results and can be easily integrated in the clinical setting. The principal difference in the acquired Raman spectra between healthy nails and infected ones was observed in the regions of disulfide bonds, Phe vibration, amide I, II, and III. The difference in Raman spectra between Candida and T. rubrum nails can be attributed to the variable nail-invading mechanisms of these pathogens. Difference in keratinolytic ability may have resulted in the differentiation of the Raman peaks that correspond to the disulfide moiety.
Data analysis Signal processing and multivariate statistical analysis were performed using the Unscrambler X (CAMO Software AS, Oslo, Norway) software package. Data processing of the Raman spectra was carried out in the fingerprint region (400-2000 cm-1). Spectra were smoothed, baseline corrected and normalized. Data reduction of the 827 variables (wavenumbers) was accomplished by Principal Component Analysis (PCA) with full cross validation. To classify an unknown, future clinical sample, discrimination enhancement and class modeling was performed using Partial least squares discriminant analysis (PLS-DA).
PCA loading plot for the first two PCs. Specific regions of interest are indicated in grey colour.
ACKNOWLEDGEMENTS
The authors wish to express their appreciation to A. Milioni and S. Kritikou for expert technical assistance.
INTRODUCTION
Onychomycosis is a common infection of the nails, especially the toenails, with an estimated mean prevalence of 4.3% in the general population in Europe and North America with the dermatophyte Trichophyton rubrum identified in 44.9% of the cases (95% CI: 33.8–56.0), followed by yeasts (predominantly Candida species) in 21.1% (95% CI: 11.0–31.3).
RESULTS
Tentative assignment of the Raman bands for normal and infected nail samples.
Ex vivo, mean Raman spectra with standard deviations (SDev, cyan area) of normal nails (N=26) and infected nails: T. rubrum (N=12), Candida spp. (N=14). The spectra (solid lines) are artificially offset for clarity. The strong Raman band at 500-520 cm-1 is attributed to the disulfide stretching bond of cystine and cysteine residues. Samples infected with Candida species feature a “shoulder” at 519 cm-1 which is typical of the less stable gauche-gauche-trans conformation indicating heterogeneity among the S-S bonds conformation. Samples with T. rubrum are the only ones which show two weak, but distinct, Raman bands at 619 cm-1 and 648 cm-1 which correspond to the C-S stretching vibration. A striking difference in Raman scattering also occurs at 1550 cm-1; this peak which is attributed to amide II (60% N–H bend and 40% C–N stretch) and tryptophan (Trp), is absent from the samples of nails infected by Candida species. Strong bands found in common across all three groups of samples include the symmetric ring breathing mode and the C–H in-plane bending mode of phenylalanine (Phe) as well as the amide I, II and III bands.
The gold standard of diagnosis remains the microscopic investigation of nail clippings coupled with inoculation of the infected nails in appropriate culture media. Direct microscopy is inexpensive and easy to perform, yet its sensitivity is operator dependent. Culture is the mainstay of clinical mycology and holds high predictive value when a dermatophyte is grown after 3-4 weeks of incubation; yet, it has lower sensitivity compared to microscopy. Raman spectroscopy is able to detect subtle biochemical changes in biological samples providing chemical and compositional information. In principle, it is suitable for biological specimens because it does not interfere with water molecules, it is non-invasive and it requires minimal sample preparation; however, it typically suffers from auto-fluorescence and low signal-to-noise ratio.
PCA Scores plot with Hotelling T2 (0.95) ellipse, partitioning 52 nail samples within the area defined by the two first PCs; (sl: sensu lato).
The purpose of this study was to evaluate the discriminative power of Raman spectroscopy in the ex vivo differentiation of nail clinical samples with confirmed infection by the dermatophyte T. rubrum or Candida species from healthy (normal) nails. Moreover, to our knowledge, this is the first study that predictive classification modelling is applied for the diagnosis of onychomycosis in clinical nail samples, addressing the potential of Raman spectroscopy in the clinic.
METHODS
Predicted values with estimated uncertainties for the test set (14 samples) calibrated by PLS-DA (C: Candida spp., T: T.rubrum, N: Normal).
Samples
Institutional Ethical Review Committee permission was granted and Raman measurements were performed on nail clippings (N=52) that had both direct KOH examination and positive culture for either Trichophyton rubrum (N=12) or Candida species, including species of the Candida parapsilosis complex (N=11), Candida glabrata (N=1), and Candida albicans (N=2). The negative controls (N=26) were clippings of healthy nails from volunteers. Spectra were collected at 30 mW output power, with 785 nm diode laser at ~4.5 cm-1 resolution and 5 s accumulation time, in the 200–3200 cm-1 spectral range. For each nail clipping, four Raman spectra were measured on different spots to ensure statistical variability (208 spectra in total).
CONCLUSIONS
Raman spectroscopy efficiently differentiated 3 classes of nails: healthy, T. rubrum and Candida infected; Raman characterization of clinical data of untreated nails has the obvious advantages of providing real time results and can be easily integrated in the clinical setting. The principal difference in the acquired Raman spectra between healthy nails and infected ones was observed in the regions of disulfide bonds, Phe vibration, amide I, II, and III. The difference in Raman spectra between Candida and T. rubrum nails can be attributed to the variable nail-invading mechanisms of these pathogens. Difference in keratinolytic ability may have resulted in the differentiation of the Raman peaks that correspond to the disulfide moiety.
Data analysis Signal processing and multivariate statistical analysis were performed using the Unscrambler X (CAMO Software AS, Oslo, Norway) software package. Data processing of the Raman spectra was carried out in the fingerprint region (400-2000 cm-1). Spectra were smoothed, baseline corrected and normalized. Data reduction of the 827 variables (wavenumbers) was accomplished by Principal Component Analysis (PCA) with full cross validation. To classify an unknown, future clinical sample, discrimination enhancement and class modeling was performed using Partial least squares discriminant analysis (PLS-DA).
PCA loading plot for the first two PCs. Specific regions of interest are indicated in grey colour.
ACKNOWLEDGEMENTS
The authors wish to express their appreciation to A. Milioni and S. Kritikou for expert technical assistance.
