Affiliations: 1 Centro de Investigación y Asistencia en Tecnología y diseño del Estado de Jalisco, A.C., Biotecnología Médica y Farmacéutica, Av. Normalistas 800, Col. Colinas de la Normal, Guadalajara, Jalisco, Mexico, 44270.
Keywords:
tuberculosis, latent infection, diagnosis, proteomics, transcriptomics, point-of-care, immune response.
Corresponding Author(s):
Mario Alberto Flores-Valdez, Centro de Investigación y Asistencia en Tecnología y diseño del Estado de Jalisco, A.C., Biotecnología Médica y Farmacéutica, Av. Normalistas 800, Col. Colinas de la Normal, Guadalajara, Jalisco, Mexico, 44270; Tel.: +52 33 33 45 52 00 ext. 1301; floresv@ciatej.mx, floresvz91@gmail.com
Conflict of interest statement:
The author has no conflict of interest to disclose for this work.
Please cite this article as:
Mario Alberto Flores-Valdez (2017). Uncovering the hidden: complexity and strategies for diagnosing latent tuberculosis. Microbial Cell 4(11): 365-367. doi: 10.15698/mic2017.11.596
© 2017 Flores-Valdez. This is an open-access article released under the terms of the Creative Commons Attribution (CC BY) license, which allows the unrestricted use, distribution, and reproduction in any medium, provided the original author and source are acknowledged.
Uncovering the hidden: complexity and strategies for diagnosing latent tuberculosis
Authors:Mario Alberto Flores-Valdez
doi: 10.15698/mic2017.11.596
Volume 4, pp. 365 to 367, published 24/10/2017.
1 Centro de Investigación y Asistencia en Tecnología y diseño del Estado de Jalisco, A.C., Biotecnología Médica y Farmacéutica, Av. Normalistas 800, Col. Colinas de la Normal, Guadalajara, Jalisco, Mexico, 44270.
Keywords:
tuberculosis, latent infection, diagnosis, proteomics, transcriptomics, point-of-care, immune response.
Corresponding Author(s):
Conflict of interest statement:
The author has no conflict of interest to disclose for this work.
Please cite this article as:
Mario Alberto Flores-Valdez (2017). Uncovering the hidden: complexity and strategies for diagnosing latent tuberculosis. Microbial Cell 4(11): 365-367. doi: 10.15698/mic2017.11.596
© 2017 Flores-Valdez. This is an open-access article released under the terms of the Creative Commons Attribution (CC BY) license, which allows the unrestricted use, distribution, and reproduction in any medium, provided the original author and source are acknowledged.
Abstract:
Tuberculosis produces two clinical manifestations: active and latent (non-apparent) disease. The latter is estimated to affect one-third of the world population and constitutes a source of continued transmission should the disease emerge from its hidden state (reactivation). Methods to diagnose latent TB have been evolving and aim to detect the disease in people who are truly infected with M. tuberculosis, versus those where other mycobacteria, or even other pathologies not related to TB, are present. The current use of proteomic and transcriptomic approaches may lead to improved detection methods in the coming years.