Dynamic allocation of orthogonal ribosomes facilitates uncoupling of co-expressed genes

AbstractIntroduction of synthetic circuits into host microbes creates competition between circuit and host genes for shared cellular resources, such as RNA polymerases and ribosomes. This can lead to the emergence of unwanted coupling between the expression of different genes, complicating circuit design and potentially leading to circuit failure. Here we demonstrate the ability of orthogonal ribosomes to alleviate the effects of this resource competition. We partition the ribosome pool by expressing an engineered 16S RNA with altered specificity, and use this division of specificity to build simple resource allocators which reduce the level of ribosome-mediated gene coupling. We then design and implement a dynamic resource allocation controller, which acts to increase orthogonal ribosome production as the demand for translational resources by a synthetic circuit increases. Our results highlight the potential of dynamic translational resource allocation as a means of minimising the impact of cellular limitations on the function of synthetic circuitry.

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Information and Memory in Dynamic Resource Allocation

Operations Research ◽

10.1287/opre.2019.1940 ◽

2020 ◽

Vol 68 (6) ◽

pp. 1698-1715

Author(s):

Kuang Xu ◽

Yuan Zhong

Keyword(s):

Resource Allocation ◽

Imperfect Information ◽

Dynamic Resource Allocation ◽

Noisy Channel ◽

Capacity Region ◽

Allocation Policy ◽

Stochastic Processing ◽

Dynamic Resource ◽

Information Constraints ◽

The Impact

We propose a general framework, dubbed stochastic processing under imperfect information (SPII), to study the impact of information constraints and memories on dynamic resource allocation. The framework involves a stochastic processing network (SPN) scheduling problem in which the scheduler may access the system state only through a noisy channel, and resource allocation decisions must be carried out through the interaction between an encoding policy (that observes the state) and an allocation policy (that chooses the allocation). Applications in the management of large-scale data centers and human-in-the-loop service systems are among our chief motivations. We quantify the degree to which information constraints reduce the size of the capacity region in general SPNs and how such reduction depends on the amount of memories available to the encoding and allocation policies. Using a novel metric, capacity factor, our main theorem characterizes the reduction in capacity region (under “optimal” policies) for all nondegenerate channels and across almost all combinations of memory sizes. Notably, the theorem demonstrates, in substantial generality, that (1) the presence of a noisy channel always reduces capacity, (2) more memory for the allocation policy always improves capacity, and (3) more memory for the encoding policy has little to no effect on capacity. Finally, all of our positive (achievability) results are established through constructive, implementable policies.

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Developing a pathway-independent and full-autonomous global resource allocation strategy to dynamically switching phenotypic states

Nature Communications ◽

10.1038/s41467-020-19432-2 ◽

2020 ◽

Vol 11 (1) ◽

Author(s):

Junjun Wu ◽

Meijiao Bao ◽

Xuguo Duan ◽

Peng Zhou ◽

Caiwen Chen ◽

...

Keyword(s):

Resource Allocation ◽

Metabolic Flux ◽

Dynamic Resource Allocation ◽

Grand Challenge ◽

Allocation Strategy ◽

Chemical Production ◽

Resource Allocation Strategy ◽

Dynamic Resource ◽

Cell Phenotypes ◽

Host Genes

Abstract A grand challenge of biological chemical production is the competition between synthetic circuits and host genes for limited cellular resources. Quorum sensing (QS)-based dynamic pathway regulations provide a pathway-independent way to rebalance metabolic flux over the course of the fermentation. Most cases, however, these pathway-independent strategies only have capacity for a single QS circuit functional in one cell. Furthermore, current dynamic regulations mainly provide localized control of metabolic flux. Here, with the aid of engineering synthetic orthogonal quorum-related circuits and global mRNA decay, we report a pathway-independent dynamic resource allocation strategy, which allows us to independently controlling two different phenotypic states to globally redistribute cellular resources toward synthetic circuits. The strategy which could pathway-independently and globally self-regulate two desired cell phenotypes including growth and production phenotypes could totally eliminate the need for human supervision of the entire fermentation.

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