Clinical evaluation of aT. rubrum-specific polymerase chain reaction and pandermatophyte polymerase chain reaction in the diagnosis of suspected onychomycosis in 183 Serbian patients

Host-Pathogen Interaction and Resistance Mechanisms in Dermatophytes

Dermatophytes are widely distributed in the environment, with an estimated prevalence of 20-25% of the the global population yearly. These fungi are keratinophilic and keratinolytic and cause the infection of keratin-rich structures such as skin, hair, and nails. The pattern of this infectious disease covers a wide spectrum from exposed individuals without symptoms to those with acutely inflammatory or non-inflammatory, chronic to invasive, and even life-threatening symptoms. This review summarizes current information on the pathogenicity, virulence factors, and drug resistance mechanisms associated with dermatophytes. A greater number of virulence factors of these fungi are important for the occurrence of infection and the changes that occur, including those regarding adhesins, the sulfite efflux pump, and proteolytic enzymes. Other virulence factors include mechanisms of evading the host defense, while the development of resistance to antifungal drugs is increasing, resulting in treatment failure. The investigation of host-pathogen interactions is essential for developing a more complete understanding of the mechanisms underlying dermatophyte pathogenesis and host response to inform the use of diagnostics methods and antifungal therapeutics to minimize the high fungal burden caused by dermatophytes and to control the spread of resistance.

Correlation of clinical characteristics, by calculation of SCIO index, with the laboratory diagnosis of onychomycosis

INTRODUCTION

Onychomycosis is a chronic fungal infection with increasing incidence and the global prevalence is estimated to be 5.5%. The aim of our study was to perceive objectively severity of onychomycosis by calculating Scoring Clinical Index for Onychomycosis and to correlate this index with accurate laboratory diagnosis in our patients.

MATERIALS AND METHODS

The study population comprised of 417 patients with laboratory confirmed onychomycosis. For each patient, we recorded basic demographic information, site of infection, the most affected nail with onychomycosis, clinical presentation, and type of onychomycosis. The evaluation of the disease severity was based on Scoring Clinical Index for Onychomycosis which was calculated for every patient separately. Mycological identification was done by microscopy and fungal culture.

RESULTS

The majority of patients had distal and lateral subungual onychomycosis (95.44%) that was localized on big toe (62.59%), with female to male ratio 1.24:1. Male patients had significantly more nails affected with onychomycosis compared with female patients (p = 0.011), while female had significantly more often onychomycosis on fingernails 2-5 (p < 0.05), and they reported significantly more often pain (p < 0.05) and esthetic problems (p < 0.05). Mean Scoring Clinical Index for Onychomycosis was 16.76. Dermatophytes were most frequently isolated (91.85%). In patients with onychomycosis caused by dermatophytes, Scoring Clinical Index for Onychomycosis had significantly higher values (p = 0.032).

CONCLUSION

Comprehensive understanding of disease characteristics will allow introduction of individualized treatment plan for each patient, based on proper fungal identification and standardized method of evaluating disease severity, which could help the patient achieve a complete cure.

Optimization of multiplex quantitative polymerase chain reaction based on response surface methodology and an artificial neural network-genetic algorithm approach

Multiplex quantitative polymerase chain reaction (qPCR) has found an increasing range of applications. The construction of a reliable and dynamic mathematical model for multiplex qPCR that analyzes the effects of interactions between variables is therefore especially important. This work aimed to analyze the effects of interactions between variables through response surface method (RSM) for uni- and multiplex qPCR, and further optimize the parameters by constructing two mathematical models via RSM and back-propagation neural network-genetic algorithm (BPNN-GA) respectively. The statistical analysis showed that Mg2+ was the most important factor for both uni- and multiplex qPCR. Dynamic models of uni- and multiplex qPCR could be constructed using both RSM and BPNN-GA methods. But RSM was better than BPNN-GA on prediction performance in terms of the mean absolute error (MAE), the mean square error (MSE) and the Coefficient of Determination (R2). Ultimately, optimal parameters of uni- and multiplex qPCR were determined by RSM.

Evaluation of multiplex real-time PCR for identifying dermatophytes in clinical samples-A multicentre study

The gold-standard method for dermatophyte identification involves direct microscopy and culture, which have inherent shortcomings. Only few molecular methods have been standardised for routine clinical work. This study aimed to develop and test a platform for identifying the most common dermatophytes in Israel using multiplex real-time polymerase chain reaction (RT-PCR). Specific primers were designed for the multiplex system (LightCycler 480) according to known cultures and validated by reference isolates. The dermatophyte detection rate was compared to smear and culture in 223 clinical samples obtained from a tertiary medical centre. Inconsistencies between methods were evaluated by sequencing. The RT-PCR was further evaluated in 200 community-based samples obtained from a health maintenance organisation and 103 military-personnel-based samples analysed at a central laboratory. In hospital-based clinical samples, complete concordance between methods was observed in 190 samples (85%; Kappa = 0.69). In most cases of non-concordance, sequencing was consistent with RT-PCR results. RT-PCR correctly identified all smear- and culture-positive cases in community and military-personnel samples. The results were available within 4 hours. The multiplex RT-PCR platform is a rapid and efficient method for identifying dermatophyte species in clinical samples and may serve as a first step in the diagnostic algorithm of superficial fungal infections.

Development and Evaluation of a Novel Real-Time PCR for Pan-Dermatophyte Detection in Nail Specimens

An accurate diagnosis of tinea unguium is necessary for the selection of antimycotics and successful treatment. To rapidly and accurately identify the aetiological agents causing tinea unguium, we improved upon the conventional boiling method for DNA extraction and developed a novel real-time PCR detection system that includes two assays. The two assays, based on the amplification of ribosomal internal transcribed spacer regions and 28S rDNA, were designed to detect pan-dermatophyte and Trichophyton rubrum, respectively. The analytical sensitivities of both assays permitted the detection of ten copies of plasmid DNA template. The analytical specificity of the detection system was confirmed using 11 dermatophyte strains and 25 non-dermatophyte strains. In total, 165 nail specimens were examined by microscopy, culture, conventional PCR, and the novel real-time PCR method. Real-time PCR gave positive results in 47.3 % of the specimens (78), a rate exceeding those obtained using microscopy (72, 43.6 %), conventional PCR (69, 41.8 %), and culture (49, 29.7 %). All conventional PCR-positive specimens were detected by real-time PCR, and real-time PCR detected nine specimens that were missed by conventional PCR. The results from latent class analysis, and further calculations, showed that real-time PCR was the most sensitive method, but the diagnostic specificity of the four approaches was equivalent. In particular, molecular approaches may be more effective than microscopy and culture when the clinical symptoms of tinea unguium are not evident.