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<p>Malaria significantly impacts public health in developing countries. Accurate identification of <i>Plasmodium</i> species, which can cause chronic infections lasting months or years, is crucial for reducing infection rates. Despite the global availability of various diagnostic methods, challenges remain compared to the microscopic slide detection method. Molecular techniques, while more sensitive, are generally more expensive than microscopy but offer greater accuracy and automation potential in clinical settings. This study aims to optimize the real-time PCR platform method using high-resolution melting (HRM) analysis technology and compare the results with sequencing and phylogenetic analyses to develop optimal malaria diagnostic methods. A total of 300 samples were collected from individuals with suspected malaria symptoms in various regions of Sistan and Baluchistan province, located in southeastern Iran. Peripheral blood slides were examined microscopically and analyzed using PCR HRM with the Light Cycler 96 Instrument (Roche). Subsequently, phylogenetic analysis was conducted to further analyze the sequencing, with the desired sequences submitted to GenBank. Out of the 300 suspected samples, the PCR method identified 9 cases (3%) of <i>Plasmodium falciparum</i> and 20 cases (6.66%) of <i>Plasmodium vivax</i>. In comparison, the HRM method detected 15 cases (5%) of <i>Plasmodium falciparum</i> and 14 cases (4.66%) of <i>Plasmodium vivax</i>. Sequencing results revealed 13 cases (4.33%) of <i>Plasmodium falciparum</i> and 16 cases (5.33%) of <i>Plasmodium vivax</i>. The HRM method targeted the 18S SSU rRNA region, achieving a significant differentiation of 2.73 degrees to distinguish between the two species. The results confirm that, with proper primer design and precise species separation, the HRM technique is a reliable and optimal method for diagnosing malaria species. Also, The HRM method showed high sensitivity and specificity in identifying <i>Plasmodium</i> species, with complete agreement observed with sequencing in the tested samples.</p>

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Optimization of the real-time PCR platform method using high-resolution melting analysis and comparison with sequencing and phylogenetic analysis for developing optimal malaria diagnostic methods

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年10月2日

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  • Omid Ahmadi,
  • Yousef Sharifi,
  • Michael Saeed,
  • Amirali Reihani,
  • Seyed Aliakbar Shamsian,
  • Elham Moghaddas,
  • Hadi Mirahmadi,
  • Soudabeh Etemadi,
  • Reza Fotouhi-Ardakani,
  • Mehdi Zarean

摘要

Malaria significantly impacts public health in developing countries. Accurate identification of Plasmodium species, which can cause chronic infections lasting months or years, is crucial for reducing infection rates. Despite the global availability of various diagnostic methods, challenges remain compared to the microscopic slide detection method. Molecular techniques, while more sensitive, are generally more expensive than microscopy but offer greater accuracy and automation potential in clinical settings. This study aims to optimize the real-time PCR platform method using high-resolution melting (HRM) analysis technology and compare the results with sequencing and phylogenetic analyses to develop optimal malaria diagnostic methods. A total of 300 samples were collected from individuals with suspected malaria symptoms in various regions of Sistan and Baluchistan province, located in southeastern Iran. Peripheral blood slides were examined microscopically and analyzed using PCR HRM with the Light Cycler 96 Instrument (Roche). Subsequently, phylogenetic analysis was conducted to further analyze the sequencing, with the desired sequences submitted to GenBank. Out of the 300 suspected samples, the PCR method identified 9 cases (3%) of Plasmodium falciparum and 20 cases (6.66%) of Plasmodium vivax. In comparison, the HRM method detected 15 cases (5%) of Plasmodium falciparum and 14 cases (4.66%) of Plasmodium vivax. Sequencing results revealed 13 cases (4.33%) of Plasmodium falciparum and 16 cases (5.33%) of Plasmodium vivax. The HRM method targeted the 18S SSU rRNA region, achieving a significant differentiation of 2.73 degrees to distinguish between the two species. The results confirm that, with proper primer design and precise species separation, the HRM technique is a reliable and optimal method for diagnosing malaria species. Also, The HRM method showed high sensitivity and specificity in identifying Plasmodium species, with complete agreement observed with sequencing in the tested samples.