Main Page - Revision history

Murray: /* Modeling and Specifications */

2025-09-13T04:51:01Z

Modeling and Specifications

← Older revision		Revision as of 21:51, 12 September 2025
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	Throughout this wiki, Python-based simulation models will be used to illustrate the dynamic characteristics of the subsystems and to build computational representations of interconnected subsystems. We will make use of the BioCRNpyler package<ref name="biocrnpyler">https://biocrnpyler.readthedocs.org. Retrieved 13 Sep 2025</ref>, a software framework and library designed to aid in the rapid construction of models from common motifs, such as molecular components, biochemical mechanisms and parameter sets. These parts can be reused and recombined to rapidly generate chemical reaction network (CRN) models in diverse chemical contexts at varying levels of model complexity.		Throughout this wiki, Python-based simulation models will be used to illustrate the dynamic characteristics of the subsystems and to build computational representations of interconnected subsystems. We will make use of the BioCRNpyler package<ref name="biocrnpyler">https://biocrnpyler.readthedocs.org. Retrieved 13 Sep 2025</ref>, a software framework and library designed to aid in the rapid construction of models from common motifs, such as molecular components, biochemical mechanisms and parameter sets. These parts can be reused and recombined to rapidly generate chemical reaction network (CRN) models in diverse chemical contexts at varying levels of model complexity.

	BioCRNpyler compiles high-level specifications into detailed CRN models saved as SBML. Specifications may include: biomolecular ~~Components~~, modeling assumptions (~~Mechanisms~~), biochemical context (~~Mixtures~~), and ~~Parameters~~. BioCRNpyler is written in Python with a flexible object-oriented design, extensive documentation, and detailed examples to allow for easy model construction by modelers as well as customization and extension by developers. BioCRNpyler make use of the following abstractions (see the BioCRNpyler<ref name=biocrnpyler/> documentation for more details):		BioCRNpyler compiles high-level specifications into detailed CRN models saved as SBML. Specifications may include: biomolecular components, modeling assumptions (mechanisms), biochemical context (mixtures), and parameters. BioCRNpyler is written in Python with a flexible object-oriented design, extensive documentation, and detailed examples to allow for easy model construction by modelers as well as customization and extension by developers. BioCRNpyler make use of the following abstractions (see the BioCRNpyler<ref name=biocrnpyler/> documentation for more details):

	* '''Species''' and '''Reactions''' make up a CRN and are the output of BioCRNpyler compilation. Many sub-classes exist, such as ComplexSpecies and reactions with different kinds of rate function (e.g. mass-action, Hill functions, etc).		* '''Species''' and '''Reactions''' make up a CRN and are the output of BioCRNpyler compilation. Many sub-classes exist, such as ComplexSpecies and reactions with different kinds of rate function (e.g. mass-action, Hill functions, etc).

Murray: /* Modeling and Specifications */

2025-09-13T04:40:04Z

Modeling and Specifications

← Older revision		Revision as of 21:40, 12 September 2025
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	[[Image:BioCRNpyler_Overview.png\|thumb\|400px\|The hierarchical organization of classes in the BioCRNpyler framework. Arrows represent compilation. From https://biocrnpyler.readthedocs.org]]		[[Image:BioCRNpyler_Overview.png\|thumb\|400px\|The hierarchical organization of classes in the BioCRNpyler framework. Arrows represent compilation. From https://biocrnpyler.readthedocs.org]]

	Throughout this wiki, Python-based simulation models will be used to illustrate the dynamic characteristics of the subsystems and to build computational representations of interconnected subsystems. We will make use of the BioCRNpyler package<ref name="biocrnpyler"> https://~~buildacell~~.~~github~~.~~com/biocrnpyler~~. Retrieved ~~19 Jul~~ 2025</ref>, a software framework and library designed to aid in the rapid construction of models from common motifs, such as molecular components, biochemical mechanisms and parameter sets. These parts can be reused and recombined to rapidly generate chemical reaction network (CRN) models in diverse chemical contexts at varying levels of model complexity.		Throughout this wiki, Python-based simulation models will be used to illustrate the dynamic characteristics of the subsystems and to build computational representations of interconnected subsystems. We will make use of the BioCRNpyler package<ref name="biocrnpyler">https://biocrnpyler.readthedocs.org. Retrieved 13 Sep 2025</ref>, a software framework and library designed to aid in the rapid construction of models from common motifs, such as molecular components, biochemical mechanisms and parameter sets. These parts can be reused and recombined to rapidly generate chemical reaction network (CRN) models in diverse chemical contexts at varying levels of model complexity.

	BioCRNpyler compiles high-level specifications into detailed CRN models saved as SBML. Specifications may include: biomolecular Components, modeling assumptions (Mechanisms), biochemical context (Mixtures), and Parameters. BioCRNpyler is written in Python with a flexible object-oriented design, extensive documentation, and detailed examples to allow for easy model construction by modelers as well as customization and extension by developers. BioCRNpyler make use of the following abstractions (see the BioCRNpyler<ref name=biocrnpyler/> documentation for more details):		BioCRNpyler compiles high-level specifications into detailed CRN models saved as SBML. Specifications may include: biomolecular Components, modeling assumptions (Mechanisms), biochemical context (Mixtures), and Parameters. BioCRNpyler is written in Python with a flexible object-oriented design, extensive documentation, and detailed examples to allow for easy model construction by modelers as well as customization and extension by developers. BioCRNpyler make use of the following abstractions (see the BioCRNpyler<ref name=biocrnpyler/> documentation for more details):

Murray: /* More Achievable Starting Points (MVPs) */

2025-08-30T12:00:44Z

More Achievable Starting Points (MVPs)

← Older revision		Revision as of 05:00, 30 August 2025
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	* '''Synthetic Cells as Replacements for EMERs'''. Engineered Microbes for Environmental Release (EMERs) are an emerging application area in synthetic biology with applications in agriculture, remediation, biomining, and therapeutics (animals or humans). EMERs can be challenging to use due to regulations governing the release of genetically modified organisms, in particular because they are often intended for open release, and so conventional containments strategies for genetically engineered organisms are not applicable. Replacing EMERs with (non-replicating) synthetic cells could provide a safer and more predictable method for carrying out existing biological functions such as nitrogen fixation, phenol degradation, or waste processing.		* '''Synthetic Cells as Replacements for EMERs'''. Engineered Microbes for Environmental Release (EMERs) are an emerging application area in synthetic biology with applications in agriculture, remediation, biomining, and therapeutics (animals or humans). EMERs can be challenging to use due to regulations governing the release of genetically modified organisms, in particular because they are often intended for open release, and so conventional containments strategies for genetically engineered organisms are not applicable. Replacing EMERs with (non-replicating) synthetic cells could provide a safer and more predictable method for carrying out existing biological functions such as nitrogen fixation, phenol degradation, or waste processing.

			[[Synthetic cell demonstrations\|Current demonstrations]] of synthetic cells are primarily oriented at demonstrating basic capabilities.

	=== What About Recreating Life? ===		=== What About Recreating Life? ===

Murray: /* Why Are Synthetic Cells a Good Way to Get There? */

2025-08-30T11:17:01Z

Why Are Synthetic Cells a Good Way to Get There?

← Older revision		Revision as of 04:17, 30 August 2025
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	=== Why Are Synthetic Cells a Good Way to Get There? ===		=== Why Are Synthetic Cells a Good Way to Get There? ===

			[[Image:syncell_whitespace.png\|400px\|thumb\|alt=DARPA white space chart\|"White space" chart, showing a possible path to engineering biology at scale using synthetic cells. Figure courtesy Richard Murray, 2025 (CC BY).]]

	One of the hypothesis of the synthetic cell movement is that building from the "bottom up" is more "engineerable" (predictable, robust, scaleable) than other approaches to building complex biomachines. The most obvious alternative is genetically modifying living organisms, and this is where the majority of work in synthetic biology currently takes place. But our record in engineering complex biological circuits and pathways in living organisms is not great: the most complex systems we have been able to to engineer to date have at most dozens of individually engineered components (see, for example, Srinivasan and Smolke, ''Science'', 2020<ref>P. Srinivasan and C. D. Smolke. [https://www.nature.com/articles/s41586-020-2650-9 "Biosynthesis of medicinal tropane alkaloids in yeast"]. ''Nature'' 585(7826):614–19, 2020. DOI: 10.1038/s41586-020-2650-9.</ref>), versus the millions of engineered components that are part of a cell phone, an airplane, or the power grid. One reason this might be the case is that when we engineer living systems, we are fighting against billions of years of evolution that have fine-tuned the organism we are engineering to carry out its specific function in nature, and we don't yet have the understanding or insight to modify that function in a way that is predictable, robust, and scaleable.		One of the hypothesis of the synthetic cell movement is that building from the "bottom up" is more "engineerable" (predictable, robust, scaleable) than other approaches to building complex biomachines. The most obvious alternative is genetically modifying living organisms, and this is where the majority of work in synthetic biology currently takes place. But our record in engineering complex biological circuits and pathways in living organisms is not great: the most complex systems we have been able to to engineer to date have at most dozens of individually engineered components (see, for example, Srinivasan and Smolke, ''Science'', 2020<ref>P. Srinivasan and C. D. Smolke. [https://www.nature.com/articles/s41586-020-2650-9 "Biosynthesis of medicinal tropane alkaloids in yeast"]. ''Nature'' 585(7826):614–19, 2020. DOI: 10.1038/s41586-020-2650-9.</ref>), versus the millions of engineered components that are part of a cell phone, an airplane, or the power grid. One reason this might be the case is that when we engineer living systems, we are fighting against billions of years of evolution that have fine-tuned the organism we are engineering to carry out its specific function in nature, and we don't yet have the understanding or insight to modify that function in a way that is predictable, robust, and scaleable.

Murray: /* How Could Synthetic Cells Be Useful? */

2025-08-15T12:10:59Z

How Could Synthetic Cells Be Useful?

← Older revision		Revision as of 05:10, 15 August 2025
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	== How Could Synthetic Cells Be Useful? ==		== How Could Synthetic Cells Be Useful? ==

			This section summarizes some of the potential applications for synthetic cells. The [[Synthetic Cell Applications]] page has a more detailed analysis of current and future applications of synthetic cells.

	=== Long Term Vision: Building Biological Machines at Scale ===		=== Long Term Vision: Building Biological Machines at Scale ===

Murray: /* Why Are Synthetic Cells a Good Way to Get There? */

2025-07-19T14:58:26Z

Why Are Synthetic Cells a Good Way to Get There?

← Older revision		Revision as of 07:58, 19 July 2025
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	=== Why Are Synthetic Cells a Good Way to Get There? ===		=== Why Are Synthetic Cells a Good Way to Get There? ===

	One of the hypothesis of the synthetic cell movement is that building from the "bottom up" is more "engineerable" (predictable, robust, scaleable) than other approaches to building complex biomachines. The most obvious alternative is genetically modifying living organisms, and this is where the majority of work in synthetic biology currently takes place. But our record in engineering complex biological circuits and pathways in living organisms is not great: the most complex systems we have been able to to engineer to date have at most dozens of individually engineered components (see, for example, ~~X et al~~, Science, ~~2022~~<ref>P. Srinivasan and C. D. Smolke. "Biosynthesis of medicinal tropane alkaloids in yeast." ''Nature'' 585(7826):614–19, 2020. DOI: 10.1038/s41586-020-2650-9.</ref>), versus the millions of engineered components that are part of a cell phone, an airplane, or the power grid. One reason this might be the case is that when we engineer living systems, we are fighting against billions of years of evolution that have fine-tuned the organism we are engineering to carry out its specific function in nature, and we don't yet have the understanding or insight to modify that function in a way that is predictable, robust, and scaleable.		One of the hypothesis of the synthetic cell movement is that building from the "bottom up" is more "engineerable" (predictable, robust, scaleable) than other approaches to building complex biomachines. The most obvious alternative is genetically modifying living organisms, and this is where the majority of work in synthetic biology currently takes place. But our record in engineering complex biological circuits and pathways in living organisms is not great: the most complex systems we have been able to to engineer to date have at most dozens of individually engineered components (see, for example, Srinivasan and Smolke, ''Science'', 2020<ref>P. Srinivasan and C. D. Smolke. [https://www.nature.com/articles/s41586-020-2650-9 "Biosynthesis of medicinal tropane alkaloids in yeast"]. ''Nature'' 585(7826):614–19, 2020. DOI: 10.1038/s41586-020-2650-9.</ref>), versus the millions of engineered components that are part of a cell phone, an airplane, or the power grid. One reason this might be the case is that when we engineer living systems, we are fighting against billions of years of evolution that have fine-tuned the organism we are engineering to carry out its specific function in nature, and we don't yet have the understanding or insight to modify that function in a way that is predictable, robust, and scaleable.

	A major drawback of the synthetic cell approach versus more conventional approaches to engineering biology is that we have to re-invent all of the major subsystems from scratch. In particular, the need to "reinvent" metabolism is a major hurdle: natural cells come with the ability to metabolize carbon sources and turn them into energy and the other materials need for the cell to function. Synthetic cells must import the natural metabolic subsystem, reinvent metabolism, or find a different method for providing the power required to operate. The last approach seems to most plausible, but is an example of the significant challenges that must be overcome in order to make synthetic cells a viable alternative to genetically modified organisms.		A major drawback of the synthetic cell approach versus more conventional approaches to engineering biology is that we have to re-invent all of the major subsystems from scratch. In particular, the need to "reinvent" metabolism is a major hurdle: natural cells come with the ability to metabolize carbon sources and turn them into energy and the other materials need for the cell to function. Synthetic cells must import the natural metabolic subsystem, reinvent metabolism, or find a different method for providing the power required to operate. The last approach seems to most plausible, but is an example of the significant challenges that must be overcome in order to make synthetic cells a viable alternative to genetically modified organisms.

Murray: /* Why Are Synthetic Cells a Good Way to Get There? */

2025-07-19T14:57:09Z

Why Are Synthetic Cells a Good Way to Get There?

← Older revision		Revision as of 07:57, 19 July 2025
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	=== Why Are Synthetic Cells a Good Way to Get There? ===		=== Why Are Synthetic Cells a Good Way to Get There? ===

	One of the hypothesis of the synthetic cell movement is that building from the "bottom up" is more "engineerable" (predictable, robust, scaleable) than other approaches to building complex biomachines. The most obvious alternative is genetically modifying living organisms, and this is where the majority of work in synthetic biology currently takes place. But our record in engineering complex biological circuits and pathways in living organisms is not great: the most complex systems we have been able to to engineer to date have at most dozens of individually engineered ~~component~~, versus the millions of engineered components that are part of a cell phone, an airplane, or the power grid. One reason this might be the case is that when we engineer living systems, we are fighting against billions of years of evolution that have fine-tuned the organism we are engineering to carry out its specific function in nature, and we don't yet have the understanding or insight to modify that function in a way that is predictable, robust, and scaleable.		One of the hypothesis of the synthetic cell movement is that building from the "bottom up" is more "engineerable" (predictable, robust, scaleable) than other approaches to building complex biomachines. The most obvious alternative is genetically modifying living organisms, and this is where the majority of work in synthetic biology currently takes place. But our record in engineering complex biological circuits and pathways in living organisms is not great: the most complex systems we have been able to to engineer to date have at most dozens of individually engineered components (see, for example, X et al, Science, 2022<ref>P. Srinivasan and C. D. Smolke. "Biosynthesis of medicinal tropane alkaloids in yeast." ''Nature'' 585(7826):614–19, 2020. DOI: 10.1038/s41586-020-2650-9.</ref>), versus the millions of engineered components that are part of a cell phone, an airplane, or the power grid. One reason this might be the case is that when we engineer living systems, we are fighting against billions of years of evolution that have fine-tuned the organism we are engineering to carry out its specific function in nature, and we don't yet have the understanding or insight to modify that function in a way that is predictable, robust, and scaleable.

	A major drawback of the synthetic cell approach versus more conventional approaches to engineering biology is that we have to re-invent all of the major subsystems from scratch. In particular, the need to "reinvent" metabolism is a major hurdle: natural cells come with the ability to metabolize carbon sources and turn them into energy and the other materials need for the cell to function. Synthetic cells must import the natural metabolic subsystem, reinvent metabolism, or find a different method for providing the power required to operate. The last approach seems to most plausible, but is an example of the significant challenges that must be overcome in order to make synthetic cells a viable alternative to genetically modified organisms.		A major drawback of the synthetic cell approach versus more conventional approaches to engineering biology is that we have to re-invent all of the major subsystems from scratch. In particular, the need to "reinvent" metabolism is a major hurdle: natural cells come with the ability to metabolize carbon sources and turn them into energy and the other materials need for the cell to function. Synthetic cells must import the natural metabolic subsystem, reinvent metabolism, or find a different method for providing the power required to operate. The last approach seems to most plausible, but is an example of the significant challenges that must be overcome in order to make synthetic cells a viable alternative to genetically modified organisms.

Murray: /* Long Term Vision: Building Biological Machines at Scale */

2025-07-19T14:46:58Z

Long Term Vision: Building Biological Machines at Scale

← Older revision		Revision as of 07:46, 19 July 2025
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	[[Image:syncell-ant.png\|right\|240px\|thumb\|alt={Synthetic ants}\|Carpenter ant, showing some of the different subsystems. CC BY-SA, [https://commons.wikimedia.org/wiki/File:Muurahainen.svg Jpant via Wikimedia Commons], 2006]]		[[Image:syncell-ant.png\|right\|240px\|thumb\|alt={Synthetic ants}\|Carpenter ant, showing some of the different subsystems. CC BY-SA, [https://commons.wikimedia.org/wiki/File:Muurahainen.svg Jpant via Wikimedia Commons], 2006]]
	A long term goal for synthetic cells is to enable predictable engineering of complex "biomachines", where a biomachine is ~~a biomachine is complex~~ system that makes use of biomolecules to carry out a useful function. For example, imagine a world in which engineers can design and build a device that is 1-2 mm long, operates for 24 hours, and can be programmed to explore small spaces and retrieve objects and substances with well-defined chemical, mechanical, or optical properties. In nature, this is called a carpenter ant, and it consists of ~20M cells that allow the ant to explore its environment, find food or building materials for its nest, and communicate with other ants. The various cells in the ant carry out different ~~function~~ (muscles, energy conversion, sensing, decision making, etc) and are assembled together in a fashion that allows the system to operate, much like a self-driving car is able navigate on city streets. While engineers are able to build self-driving cars, we have not yet developed and mastered the engineering processes and workflows needed to engineer a system at the millimeter scale that can carry out similarly useful functions.		A long term goal for synthetic cells is to enable predictable engineering of complex "biomachines", where a biomachine is an engineered system that makes use of biomolecules to carry out a useful function. For example, imagine a world in which engineers can design and build a device that is 1-2 mm long, operates for 24 hours, and can be programmed to explore small spaces and retrieve objects and substances with well-defined chemical, mechanical, or optical properties. In nature, this is called a carpenter ant, and it consists of ~20M cells that allow the ant to explore its environment, find food or building materials for its nest, and communicate with other ants. The various cells in the ant carry out different functions (muscles, energy conversion, sensing, decision making, etc.) and are assembled together in a fashion that allows the system to operate autonomously, much like a self-driving car is able navigate on city streets. While engineers are able to build self-driving cars, we have not yet developed and mastered the engineering processes and workflows needed to engineer a system at the millimeter scale that can carry out similarly useful functions.

	[[Image:syncell-plant.png\|left\|240px\|thumb\|alt={Synthetic plants}\|Conceptual synthetic plant, growing multiple fruits. Original figure courtesy LSU Ag Center, 2021]]		[[Image:syncell-plant.png\|left\|240px\|thumb\|alt={Synthetic plants}\|Conceptual synthetic plant, growing multiple fruits. Original figure courtesy LSU Ag Center, 2021]]
	As a second example, imagine a biological machine that can extract chemicals (and energy) from the environment around it, transport ~~them~~ to processing centers where it combines and converts ~~the chemicals~~ into new ~~ones~~, and then transports them to packaging centers where its assembles them into useful form. In nature, this is called an orange tree. The chemical engineering discipline can build machines that have these same high level functions (perhaps to produce [https://en.wikipedia.org/wiki/Terry%27s_Chocolate_Orange ~~chocolate oranges]~~ [invented in 1932!]), but we don't know how to build a biological machine at this level of complexity and function. If we could, we might even be able to engineer it so that it made different types of fruits on different branche (apples, oranges, and plums?) s, or build different variants of the machine that were tuned to operate in different types of climate (from rainforests to semi-arid plains).		As a second example, imagine a biological machine that can extract chemicals and energy from the environment around it, transport the chemicals to processing centers where it combines and converts them into new molecules, and then transports them to packaging centers where its assembles them into a useful form. In nature, this is called an orange tree. The chemical engineering discipline can build machines that have these same high level functions (perhaps to produce chocolate oranges<ref>https://en.wikipedia.org/wiki/Terry%27s_Chocolate_Orange. Retrieved 19 Jul 2025.</ref> [invented in 1932!]), but we don't know how to build a biological machine at this level of complexity and function. If we could, we might even be able to engineer it so that it made different types of fruits on different branche (apples, oranges, and plums?), or build different variants of the machine that were tuned to operate in different types of climate (from rainforests to semi-arid plains, depending on the model that you choose).

	[[Image:syncell-slime.png\|right\|240px\|thumb\|alt={Synthetic slimes (biofilms)}\|Depiction of a biofilm. ARL CCDC, 2019.]]As a final, and perhaps the most achievable in the near term, consider the idea of embedding synthetic cells into artificial and/or hybrid materials, similar to biofilms or perhaps slime molds. In this instantiation of synthetic, multicellular biomachines, the individual synthetic cells embedded in a material could sense conditions in their local environment and change the properties of the material in response to those conditions. For example, a material might adjust its mechanical or optical properties based on changes in temperature or chemical cues. Synthetic cells embedded in materials could also export chemicals to interact with the environment, perhaps degrading toxins or killing harmful organisms on the surface.		[[Image:syncell-slime.png\|right\|240px\|thumb\|alt={Synthetic slimes (biofilms)}\|Depiction of a biofilm. ARL CCDC, 2019.]]As a final example, and perhaps the most achievable in the near term, consider the idea of embedding synthetic cells into artificial and/or hybrid materials, similar to biofilms or perhaps slime molds. In this instantiation of synthetic, multicellular biomachines, the individual synthetic cells embedded in a material could sense conditions in their local environment and change the properties of the material in response to those conditions. For example, a material might adjust its mechanical or optical properties based on changes in temperature or chemical cues. Synthetic cells embedded in materials could also export chemicals to interact with the environment, perhaps degrading toxins or killing harmful organisms on the surface.

	For all three of these cases (ants, plants, and slimes), synthetic cells are a possible starting point for many of the nanoscale and microscale functions that would need to be combined to produce these (multicellular) complex biomachines. Of course, there is no reason that these would need to mimic their natural counterparts completely. For example, rather than figuring out how to have cells grow, divide, and differentiate, we could instead assemble the cells using additive manufacturing techniques. And rather than building into each cell the ability to synthesize the energy it requires, we could simply feed energy into the system from an external source, much as we power a cell phone from a rechargeable battery or plug a computer into a wall outlet (via a power supply). Furthermore, we ~~wouldn't~~ have to restrict ourselves to complete biological materials: it would be fine to 3D print some portions of the biomachine using conventional materials (e.g., plastics) and other parts using biomaterials (encapsulated as synthetic cells).		For all three of these cases (ants, plants, and slimes), synthetic cells are a possible starting point for many of the nanoscale and microscale functions that would need to be combined to produce these (multicellular) complex biomachines. Of course, there is no reason that these would need to mimic their natural counterparts completely. For example, rather than figuring out how to have cells grow, divide, and differentiate, we could instead assemble the cells using additive manufacturing techniques. And rather than building into each cell the ability to synthesize the energy it requires, we could simply feed energy into the system from an external source, much as we power a cell phone from a rechargeable battery or plug a computer into a wall outlet (via a power supply). Furthermore, we would not have to restrict ourselves to complete biological materials: it would be fine to 3D print some portions of the biomachine using conventional materials (e.g., plastics) and other parts using biomaterials (encapsulated as synthetic cells).

	=== Why Are Synthetic Cells a Good Way to Get There? ===		=== Why Are Synthetic Cells a Good Way to Get There? ===

Murray: /* Modeling and Specifications */

2025-07-19T14:39:11Z

Modeling and Specifications

← Older revision		Revision as of 07:39, 19 July 2025
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	[[Image:BioCRNpyler_Overview.png\|thumb\|400px\|The hierarchical organization of classes in the BioCRNpyler framework. Arrows represent compilation. From https://biocrnpyler.readthedocs.org]]		[[Image:BioCRNpyler_Overview.png\|thumb\|400px\|The hierarchical organization of classes in the BioCRNpyler framework. Arrows represent compilation. From https://biocrnpyler.readthedocs.org]]

	Throughout this wiki, Python-based simulation models will be used to illustrate the dynamic characteristics of the subsystems and to build computational representations of interconnected subsystems. We will make use of the [https://buildacell.github.com/biocrnpyler ~~BioCRNpyler] package~~, a software framework and library designed to aid in the rapid construction of models from common motifs, such as molecular components, biochemical mechanisms and parameter sets. These parts can be reused and recombined to rapidly generate chemical reaction network (CRN) models in diverse chemical contexts at varying levels of model complexity.		Throughout this wiki, Python-based simulation models will be used to illustrate the dynamic characteristics of the subsystems and to build computational representations of interconnected subsystems. We will make use of the BioCRNpyler package<ref name="biocrnpyler"> https://buildacell.github.com/biocrnpyler. Retrieved 19 Jul 2025</ref>, a software framework and library designed to aid in the rapid construction of models from common motifs, such as molecular components, biochemical mechanisms and parameter sets. These parts can be reused and recombined to rapidly generate chemical reaction network (CRN) models in diverse chemical contexts at varying levels of model complexity.

	BioCRNpyler compiles high-level specifications into detailed CRN models saved as SBML. Specifications may include: biomolecular Components, modeling assumptions (Mechanisms), biochemical context (Mixtures), and Parameters. BioCRNpyler is written in Python with a flexible object-oriented design, extensive documentation, and detailed examples to allow for easy model construction by modelers as well as customization and extension by developers. BioCRNpyler make use of the following abstractions (see the ~~[https:~~/~~/biocrnpyler.readthedocs.org BioCRNpyler documenation]~~ for more details):		BioCRNpyler compiles high-level specifications into detailed CRN models saved as SBML. Specifications may include: biomolecular Components, modeling assumptions (Mechanisms), biochemical context (Mixtures), and Parameters. BioCRNpyler is written in Python with a flexible object-oriented design, extensive documentation, and detailed examples to allow for easy model construction by modelers as well as customization and extension by developers. BioCRNpyler make use of the following abstractions (see the BioCRNpyler<ref name=biocrnpyler/> documentation for more details):

	* '''Species''' and '''Reactions''' make up a CRN and are the output of BioCRNpyler compilation. Many sub-classes exist, such as ComplexSpecies and reactions with different kinds of rate function (e.g. mass-action, Hill functions, etc).		* '''Species''' and '''Reactions''' make up a CRN and are the output of BioCRNpyler compilation. Many sub-classes exist, such as ComplexSpecies and reactions with different kinds of rate function (e.g. mass-action, Hill functions, etc).

Murray: /* What is a Synthetic Cell? */

2025-07-19T14:36:06Z

What is a Synthetic Cell?

← Older revision		Revision as of 07:36, 19 July 2025
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	* '''Encapsulated cell-free systems''': A system consisting of a container of some sort, with biomolecular machinery inside the contained region that carries out biomolecular functions (transcription, translation, sensing, chemical processing, motility, etc). Synthetic cells in this class can range from very simple artificial vesicles containing a few proteins to complex biomolecular machines that carry out complex functions. As a general rule, synthetic cells in this category are not self-replicating, though they may include mechanisms for assembly into more complex consortia or multi-cellular machines.		* '''Encapsulated cell-free systems''': A system consisting of a container of some sort, with biomolecular machinery inside the contained region that carries out biomolecular functions (transcription, translation, sensing, chemical processing, motility, etc). Synthetic cells in this class can range from very simple artificial vesicles containing a few proteins to complex biomolecular machines that carry out complex functions. As a general rule, synthetic cells in this category are not self-replicating, though they may include mechanisms for assembly into more complex consortia or multi-cellular machines.

	* '''Biomimetic synthetic cells''': A system that carries the key functions of a living cell, typically including compartmentalization, replication, and metabolism. These systems do not yet exist, but significant progress has been made on each of the basic functions, often using encapusulated cell-free systems as a starting point. A recent review and roadmap for this class of systems has been written by members of the US Build-A-Cell<ref>https://buildacell.org</ref> consortium (Rosthschild et al, 2024<ref name="Ros+2024:ACSsynbio">L. J. Rothschild, N. J. H. Averesch, E. A. Strychalski, F. Moser, J. I. Glass, R. Cruz Perez, I. O. Yekinni, B. Rothschild-Mancinelli, G. A. Roberts Kingman, F. Wu, J. Waeterschoot, I. A. Ioannou, M. C. Jewett, A. P. Liu, V. Noireaux, C. Sorenson, and K. P. Adamala, [https://pubs.acs.org/doi/10.1021/acssynbio.3c00724 Building synthetic cells─From the technology infrastructure to cellular entities]. ''ACS Synthetic Biology'' 13(4):974-997, 2024. DOI: 10.1021/acssynbio.3c00724</ref>).		* '''Biomimetic synthetic cells''': A system that carries the key functions of a living cell, typically including compartmentalization, replication, and metabolism. These systems do not yet exist, but significant progress has been made on each of the basic functions, often using encapusulated cell-free systems as a starting point. A recent review and roadmap for this class of systems has been written by members of the US Build-A-Cell<ref>https://buildacell.org. Retrieved 19 Jul 2025.</ref> consortium (Rosthschild et al, 2024<ref name="Ros+2024:ACSsynbio">L. J. Rothschild, N. J. H. Averesch, E. A. Strychalski, F. Moser, J. I. Glass, R. Cruz Perez, I. O. Yekinni, B. Rothschild-Mancinelli, G. A. Roberts Kingman, F. Wu, J. Waeterschoot, I. A. Ioannou, M. C. Jewett, A. P. Liu, V. Noireaux, C. Sorenson, and K. P. Adamala, [https://pubs.acs.org/doi/10.1021/acssynbio.3c00724 Building synthetic cells─From the technology infrastructure to cellular entities]. ''ACS Synthetic Biology'' 13(4):974-997, 2024. DOI: 10.1021/acssynbio.3c00724</ref>).

	* '''Minimal cells''': A natural cell that has been heavily modified to utilize a minimized chromosome while still supporting life. The prototypical minimal cell is JCVI-syn3.0<ref>C. A. Hutchison III, R.-Y. Chuang, V. N. Noskov, N. Assad-Garcia, T. J. Deerinck, M. H. Ellisman, J. Gill, K. Kannan, B. J. Karas, L. Ma, J. F. Pelletier, Z.-Q. Qi, R. A. Richter, E. A. Strychalski, L. Sun, Y. Suzuki, B. Tsvetanova, K. S. Wise, H. O. Smith, J. I. Glass, C. Merryman, D. G. Gibson, and J. C. Venter, [https://www.science.org/doi/10.1126/science.aad6253 Design and synthesis of a minimal bacterial genome]. Science 351:aad6253, 2016. DOI:10.1126/science.aad6253</ref>, which consists of a modified ''Mycoplasma mycoides'' bacteria that has been modified to contain only 531,000 base pairs encoding 473 genes, making it the smallest genome of any self-replicating organism.		* '''Minimal cells''': A natural cell that has been heavily modified to utilize a minimized chromosome while still supporting life. The prototypical minimal cell is JCVI-syn3.0<ref>C. A. Hutchison III, R.-Y. Chuang, V. N. Noskov, N. Assad-Garcia, T. J. Deerinck, M. H. Ellisman, J. Gill, K. Kannan, B. J. Karas, L. Ma, J. F. Pelletier, Z.-Q. Qi, R. A. Richter, E. A. Strychalski, L. Sun, Y. Suzuki, B. Tsvetanova, K. S. Wise, H. O. Smith, J. I. Glass, C. Merryman, D. G. Gibson, and J. C. Venter, [https://www.science.org/doi/10.1126/science.aad6253 Design and synthesis of a minimal bacterial genome]. Science 351:aad6253, 2016. DOI:10.1126/science.aad6253</ref>, which consists of a modified ''Mycoplasma mycoides'' bacteria that has been modified to contain only 531,000 base pairs encoding 473 genes, making it the smallest genome of any self-replicating organism.