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http://hdl.handle.net/2183/33739 Towards automation of the Design-Build-Test-Learn (DBTL) bioengineering cycle: Application to the testing and characterization of standard bioparts
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Pushkareva, Anna
Beltrán, Jaime
Díaz-Iza, Harold
Arboleda-García, Andrés
Boada, Yadira
Vignoni, Alejandro
Picó, Jesús
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Pushkareva, A., Beltran, J., Díaz-Iza, H., Arboleda-García, A., Boada, Y., Vignoni, A., Picó, J. 2023. Towards the automation of the Design-Build-Test-Learn (DBTL) bioengineering cycle. XLIV Jornadas de Automática, 453-458. https://doi.org/10.17979/spudc.9788497498609.453
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Abstract
[Resumen] El ciclo Diseño-Construcción-Prueba-Aprendizaje (DBTL) es un marco crucial en Biología Sintética para el desarrollo y optimización de sistemas biológicos. Sin embargo, la naturaleza manual del ciclo plantea limitaciones en términos de tiempo y mano de obra. Este artículo se centra en la aplicación de técnicas de automatización al ciclo DBTL, concretamente en el ensayo y caracterización de biopartes estándar, que son componentes esenciales de los circuitos genéticos. La automatización del proceso de ensayo puede mejorar significativamente el rendimiento, la fiabilidad y la reproducibilidad. En este artículo se analizan los retos asociados a los métodos de ensayo manuales y se exploran diversas estrategias y tecnologías de automatización que pueden resolverlos. Los métodos de cribado de alto rendimiento, la robótica de laboratorio y los algoritmos de análisis de datos son elementos clave en el proceso de automatización. Se examinan estudios de casos y avances recientes en la automatización del ciclo DBTL para pruebas de biopartes. La integración de la automatización en el ciclo DBTL ofrece numerosas ventajas, como una mayor eficacia, estandarización y control de calidad de las biopartes. También permite la exploración de espacios de diseño más amplios y la creación rápida de prototipos de sistemas genéticos complejos. Este artículo ofrece una revisión exhaustiva del estado actual de la técnica y las perspectivas de futuro en la automatización del ciclo DBTL para el ensayo y la caracterización de biopartes estándar.
[Abstract] The Design-Build-Test-Learn (DBTL) cycle is a crucial framework in Synthetic Biology for the development and optimization of biological systems. However, the manual nature of the cycle poses limitations in terms of time and labor. This paper focuses on the application of automation techniques to the DBTL cycle, specifically in the testing and characterization of standard bioparts, which are essential components of genetic circuits. By automating the testing process, throughput, reliability, and reproducibility can be significantly improved. This paper discusses the challenges associated with manual testing methods and explores various automation strategies and technologies that can address these challenges. High-throughput screening methods, laboratory robotics, and data analysis algorithms are key elements in the automation process. Case studies and recent advancements in automating the DBTL cycle for biopart testing are examined. The integration of automation in the DBTL cycle offers numerous advantages, including increased efficiency, standardization, and quality control of bioparts. It also enables the exploration of larger design spaces and rapid prototyping of complex genetic systems. This paper provides a comprehensive review of the current state-of-the-art and future prospects in automating the DBTL cycle for testing and characterizing standard bioparts.
[Abstract] The Design-Build-Test-Learn (DBTL) cycle is a crucial framework in Synthetic Biology for the development and optimization of biological systems. However, the manual nature of the cycle poses limitations in terms of time and labor. This paper focuses on the application of automation techniques to the DBTL cycle, specifically in the testing and characterization of standard bioparts, which are essential components of genetic circuits. By automating the testing process, throughput, reliability, and reproducibility can be significantly improved. This paper discusses the challenges associated with manual testing methods and explores various automation strategies and technologies that can address these challenges. High-throughput screening methods, laboratory robotics, and data analysis algorithms are key elements in the automation process. Case studies and recent advancements in automating the DBTL cycle for biopart testing are examined. The integration of automation in the DBTL cycle offers numerous advantages, including increased efficiency, standardization, and quality control of bioparts. It also enables the exploration of larger design spaces and rapid prototyping of complex genetic systems. This paper provides a comprehensive review of the current state-of-the-art and future prospects in automating the DBTL cycle for testing and characterizing standard bioparts.
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Attribution-NonCommercial-ShareAlike 4.0 lnternational (CC BY-NC-SA 4.0) https://creativecommons.org/licenses/by-ncsa/4.0/


