A streamlined integrated system integrating lysate release, freeze-dried reagents for multiplex polymerase chain reaction, and intelligent analysis for TORCHes pathogen identification

Introduction Current Toxoplasma gondii (TOX), Epstein–Barr virus (EBV), rubella virus, human cytomegalovirus (HCMV), and herpes simplex virus types I and II (HSV I and II) (TORCHes) diagnostic methods are limited by challenges, such as multi-step workflows and cold-chain dependency. This study aimed to develop an integrated “sample-in-result-out” system combining rapid nucleic acid release, room-temperature-stable multiplex polymerase chain reaction (PCR), and automated interpretation to improve diagnostic accuracy. Methods We utilized a self-prepared lysis buffer for fast nucleic acid extraction from diverse sample types. Primers, probes, and reaction components for six TORCHes pathogens were fabricated into freeze-dried microspheres via vacuum freeze-drying, enabling single-tube multicolor melting curve analysis (MMCA). The companion software, TORCHes-MCAv1.0, was used to automate pathogen typing and result reporting. Evaluation metrics encompassed sensitivity, specificity, precision, stability, and anti-interference ability. The system was validated using 210 clinical samples compared to commercial single-target qPCR, with Sanger sequencing resolving any discrepancies. Results Nucleic acid extraction and release were completed within 1 min. Freeze-dried microspheres demonstrated exceptional repeatability, with T m intra- and inter-batch CVs of 0.03–0.18%. Limits of detection (LoD) were 200 copies/mL for HSV-I/II, HCMV, and TOX, and 500 copies/mL for EBV and RV. Specificity analysis showed no cross-reactivity with non-target pathogens. Stability testing confirmed the microspheres could be stored stably at room temperature for 1 year. Clinical validation showed near-perfect agreement with qPCR (Kappa = 0.965–1.000), with all seven discrepant results confirmed correct via sequencing. The TORCHes-MCAv1.0 software achieved 100% concordance with manual interpretation. Conclusion We developed a robust, streamlined integrated TORCHes detection system. Its simplicity, stability, and high-throughput nature make it a valuable complementary tool for confirming active infection and differentiating pathogen subtypes in complex clinical scenarios.