Automatic Analysis of Isothermal Amplification via Impedance Time-Constant-Domain Spectroscopy: A SARS-CoV-2 Case Study
Roberto G. Ramírez-Chavarría,
Elizabeth Castillo-Villanueva,
Bryan E. Alvarez-Serna,
Julián Carrillo-Reyes,
Lizeth Torres,
Rosa María Ramírez-Zamora,
Germán Buitrón,
Luis Alvarez-Icaza
Affiliations
Roberto G. Ramírez-Chavarría
Instituto de Ingeniería, Universidad Nacional Autónoma de México, Ciudad de México 04510, Mexico
Elizabeth Castillo-Villanueva
Instituto de Ingeniería, Universidad Nacional Autónoma de México, Ciudad de México 04510, Mexico
Bryan E. Alvarez-Serna
Instituto de Ingeniería, Universidad Nacional Autónoma de México, Ciudad de México 04510, Mexico
Julián Carrillo-Reyes
Laboratorio de Investigación en Procesos Avanzados de Tratamiento de Aguas, Unidad Académica Juriquilla, Instituto de Ingeniería, Universidad Nacional Autónoma de México, Querétaro 76230, Mexico
Lizeth Torres
Instituto de Ingeniería, Universidad Nacional Autónoma de México, Ciudad de México 04510, Mexico
Rosa María Ramírez-Zamora
Instituto de Ingeniería, Universidad Nacional Autónoma de México, Ciudad de México 04510, Mexico
Germán Buitrón
Laboratorio de Investigación en Procesos Avanzados de Tratamiento de Aguas, Unidad Académica Juriquilla, Instituto de Ingeniería, Universidad Nacional Autónoma de México, Querétaro 76230, Mexico
Luis Alvarez-Icaza
Instituto de Ingeniería, Universidad Nacional Autónoma de México, Ciudad de México 04510, Mexico
The development of sensitive and affordable testing devices for infectious diseases is essential to preserve public health, especially in pandemic scenarios. In this work, we have developed an attractive analytical method to monitor products of genetic amplification, particularly the loop-mediated isothermal amplification reaction (RT-LAMP). The method is based on electrochemical impedance measurements and the distribution of relaxation times model, to provide the so-called time-constant-domain spectroscopy (TCDS). The proposed method is tested for the SARS-CoV-2 genome, since it has been of worldwide interest due to the COVID-19 pandemic. Particularly, once the method is calibrated, its performance is demonstrated using real wastewater samples. Moreover, we propose a simple classification algorithm based on TCDS data to discriminate among positive and negative samples. Results show how a TCDS-based method provides an alternative mechanism for label-free and automated assays, exhibiting robustness and specificity for genetic detection.