Streamlining fungal diagnostics: Evaluation of a Direct-to-PCR extraction-free workflow for candida detection

Abstract:  Fungal infections are an escalating health threat, and delays from conventional nucleic acid extraction hinder timely diagnosis and treatment. This study evaluated the diagnostic performance of a novel extraction-free technology, Direct-to-PCR (D2P; Scienetix, Tyler, TX, USA), for the detection of clinically significant Candida species (C. albicans, C. glabrata, C. auris, C. parapsilosis, and C. tropicalis). D2P was compared against conventional silica column-based (Qiagen) and magnetic bead-based (KingFisher) extraction methods, using microbial reference isolates, residual clinical specimens, and limit-of-detection analyses. Diagnostic sensitivity and specificity of D2P were comparable to conventional approaches, with specificity ranging from 96.77 % to 100 %. Concordance between methods was high, with Cohen’s kappa coefficients (κ=0.93–1.00). Limit-of-detection analyses demonstrated strong analytical sensitivity, with excellent linearity (R²=0.924–0.999) and low replicate variability (coefficient of variation 0.2–6.3 %). Statistical comparison of cycle threshold values revealed no significant differences between methods (p > 0.05), supporting equivalent nucleic acid recovery without the need for time-intensive extraction steps. Despite these strengths, the study has limitations. The relatively small number of residual clinical specimens (n = 40) may restrict the generalizability of findings, and further validation across broader patient populations, specimen types, and clinical settings is warranted. Nevertheless, D2P offers a streamlined, rapid diagnostic workflow that reduces turnaround times and enhances accessibility, particularly in resource-limited environments. Wider adoption of extraction-free PCR platforms such as D2P could facilitate earlier detection of invasive candidiasis, improve clinical outcomes, and mitigate healthcare-associated morbidity and mortality attributable to fungal infections.