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1.
ACS Synth Biol ; 10(1): 183-191, 2021 01 15.
Artículo en Inglés | MEDLINE | ID: mdl-33382586

RESUMEN

Characterization is fundamental to the design, build, test, learn (DBTL) cycle for engineering synthetic genetic circuits. Components must be described in such a way as to account for their behavior in a range of contexts. Measurements and associated metadata, including part composition, constitute the test phase of the DBTL cycle. These data may consist of measurements of thousands of circuits, measured in hundreds of conditions, in multiple assays potentially performed in different laboratories and using different techniques. In order to inform the learn phase this large volume of data must be filtered, collated, and analyzed. Characterization consists of using this data to parametrize models of component function in different contexts, and combining them to predict behaviors of novel circuits. Tools to store, organize, share, and analyze large volumes of measurement and metadata are therefore essential to linking the test phase to the build and learn phases, closing the loop of the DBTL cycle. Here we present such a system, implemented as a web app with a backend data registry and analysis engine. An interactive frontend provides powerful querying, plotting, and analysis tools, and we provide a REST API and Python package for full integration with external build and learn software. All measurements are associated with circuit part composition via SBOL (Synthetic Biology Open Language). We demonstrate our tool by characterizing a range of genetic components and circuits according to composition and context.


Asunto(s)
Redes Reguladoras de Genes/genética , Interfaz Usuario-Computador , Biología Sintética/métodos
2.
ACS Synth Biol ; 6(2): 256-265, 2017 02 17.
Artículo en Inglés | MEDLINE | ID: mdl-27794593

RESUMEN

Morphogenetic engineering is an emerging field that explores the design and implementation of self-organized patterns, morphologies, and architectures in systems composed of multiple agents such as cells and swarm robots. Synthetic biology, on the other hand, aims to develop tools and formalisms that increase reproducibility, tractability, and efficiency in the engineering of biological systems. We seek to apply synthetic biology approaches to the engineering of morphologies in multicellular systems. Here, we describe the engineering of two mechanisms, symmetry-breaking and domain-specific cell regulation, as elementary functions for the prototyping of morphogenetic instructions in bacterial colonies. The former represents an artificial patterning mechanism based on plasmid segregation while the latter plays the role of artificial cell differentiation by spatial colocalization of ubiquitous and segregated components. This separation of patterning from actuation facilitates the design-build-test-improve engineering cycle. We created computational modules for CellModeller representing these basic functions and used it to guide the design process and explore the design space in silico. We applied these tools to encode spatially structured functions such as metabolic complementation, RNAPT7 gene expression, and CRISPRi/Cas9 regulation. Finally, as a proof of concept, we used CRISPRi/Cas technology to regulate cell growth by controlling methionine synthesis. These mechanisms start from single cells enabling the study of morphogenetic principles and the engineering of novel population scale structures from the bottom up.


Asunto(s)
Bacterias/genética , Sistemas CRISPR-Cas/genética , Simulación por Computador , Expresión Génica/genética , Ingeniería Genética/métodos , Metionina/genética , ARN/genética , Reproducibilidad de los Resultados , Biología Sintética/métodos
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