Cell-in-the-loop pattern formation with optogenetically emulated cell-to-cell signaling

Perkins, Melinda Liu; Benzinger, Dirk; Arcak, Murat; Khammash, Mustafa

doi:10.1038/s41467-020-15166-3

Cited by 36 publications

(34 citation statements)

References 63 publications

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“…Much work remains to characterize and exploit phenomena such as cardiac memory (Chakravarthy and Ghosh, 1997;Zoghi, 2004), and learning in bone (Turner et al, 2002;Spencer and Genever, 2003) and in gene-regulatory networks (Herrera-Delgado et al, 2018). Emerging technologies for real-time, closed-loop controls (Bugaj et al, 2017;Perkins et al, 2019) now enable interrogation of cellular cognition in a variety of somatic contexts ex vivo. We have previously suggested the use of behavior shaping and training paradigms as a strategy for synthetic morphology and regenerative medicine that complements bottom-up rewiring at the molecular level Levin, 2015, 2016;Mathews and Levin, 2017).…”

Section: Predictions and Research Programmentioning

confidence: 99%

The Computational Boundary of a “Self”: Developmental Bioelectricity Drives Multicellularity and Scale-Free Cognition

2019

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All epistemic agents physically consist of parts that must somehow comprise an integrated cognitive self. Biological individuals consist of subunits (organs, cells, and molecular networks) that are themselves complex and competent in their own native contexts. How do coherent biological Individuals result from the activity of smaller sub-agents? To understand the evolution and function of metazoan creatures' bodies and minds, it is essential to conceptually explore the origin of multicellularity and the scaling of the basal cognition of individual cells into a coherent larger organism. In this article, I synthesize ideas in cognitive science, evolutionary biology, and developmental physiology toward a hypothesis about the origin of Individuality: "Scale-Free Cognition." I propose a fundamental definition of an Individual based on the ability to pursue goals at an appropriate level of scale and organization and suggest a formalism for defining and comparing the cognitive capacities of highly diverse types of agents. Any Self is demarcated by a computational surface -the spatio-temporal boundary of events that it can measure, model, and try to affect. This surface sets a functional boundarya cognitive "light cone" which defines the scale and limits of its cognition. I hypothesize that higher level goal-directed activity and agency, resulting in larger cognitive boundaries, evolve from the primal homeostatic drive of living things to reduce stress -the difference between current conditions and life-optimal conditions. The mechanisms of developmental bioelectricity -the ability of all cells to form electrical networks that process informationsuggest a plausible set of gradual evolutionary steps that naturally lead from physiological homeostasis in single cells to memory, prediction, and ultimately complex cognitive agents, via scale-up of the basic drive of infotaxis. Recent data on the molecular mechanisms of pre-neural bioelectricity suggest a model of how increasingly sophisticated cognitive functions emerge smoothly from cell-cell communication used to guide embryogenesis and regeneration. This set of hypotheses provides a novel perspective on numerous phenomena, such as cancer, and makes several unique, testable predictions for interdisciplinary research that have implications not only for evolutionary developmental biology but also for biomedicine and perhaps artificial intelligence and exobiology.

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Section: Predictions and Research Programmentioning

confidence: 99%

The Computational Boundary of a “Self”: Developmental Bioelectricity Drives Multicellularity and Scale-Free Cognition

2019

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“…Blue (Zhao et al, 2019) CRY2/CIB1 Blue (Sweeney, Moreno Morales, Burmeister, Nimunkar, & McClean, 2019) AtLOV2 Blue (Scheffer, Hasenjäger, & Taxis, 2019) AsLOV2 (LINuS plus CRISPR-dCas9) Blue (Geller, Antwi, di Ventura, & McClean, 2019) CRY2/CIB1 (yOTK) Blue (An-Adirekkun et al, 2020) CRY2/CIB1 Blue (Rivera-Tarazona, Bhat, Kim, Campbell, & Ware, 2020) AuLOV Blue (Hepp et al, 2020) EL222 Blue (Perkins, Benzinger, Arcak, & Khammash, 2020) PYP Blue (Woloschuk, Reed, McDonald, Uppalapati, & Woolley, 2020) AsLOV2 (LINX) Blue (Meriesh, Lerner, Chandrasekharan, & Strahl, 2020) CrPHOT Blue (Suzuki et al, 2020) AsLOV2 (CLASP) Blue (Chen et al, 2020) AsLOV2 (LOV2GIVe) Blue (Garcia-Marcos et al, 2020)…”

Section: Blue-light Optogenetic Systemsmentioning

confidence: 99%

“…Thereby, when the target gene is under the control of the GAL1 promoter, the (Zhao et al, 2018). Moreover, optogenetic switches based on EL222 have been used for the characterization of different biological processes in yeast, such as single-cell transcriptional regulation (Rullan et al, 2018), pulsatile behaviour of TFs , and cell-to-cell signalling (Perkins et al, 2020).…”

Section: Optogenetic Switches For Yeast Biotechnologymentioning

confidence: 99%

The rise and shine of yeast optogenetics

Figueroa

Rojas

Romero

et al. 2020

Yeast

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Optogenetics refers to the control of biological processes with light. The activation of cellular phenomena by defined wavelengths has several advantages compared with traditional chemically inducible systems, such as spatiotemporal resolution, dose-response regulation, low cost, and moderate toxic effects. Optogenetics has been successfully implemented in yeast, a remarkable biological platform that is not only a model organism for cellular and molecular biology studies, but also a microorganism with diverse biotechnological applications. In this review, we summarize the main optogenetic systems implemented in the budding yeast Saccharomyces cerevisiae, which allow orthogonal control (by light) of gene expression, protein subcellular localization, reconstitution of protein activity, and protein sequestration by oligomerization. Furthermore, we review the application of optogenetic systems in the control of metabolic pathways, heterologous protein production and flocculation. We then revise an example of a previously described yeast optogenetic switch, named FUN-LOV, which allows precise and strong activation of the target gene. Finally, we describe optogenetic systems that have not yet been implemented in yeast, which could therefore be used to expand the panel of available tools in this biological chassis. In conclusion, a wide repertoire of optogenetic systems can be used to address fundamental biological questions and broaden the biotechnological toolkit in yeast. Take Away The budding yeast Saccharomyces cerevisiae has become a powerful biological platform for optogenetics, allowing the use of light to control diverse phenotypes. In this review, we summarized the main optogenetic tools implemented in yeast and their applications in metabolic engineering and biotechnology. Finally, we propose different sources of building blocks to expand the current repertoire of optogenetic systems in yeast.

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“…These requirements varied depending on the element studied; for example, the phosphatase Msg5 had to be provided in pulses to recover wild-type function, whereas the negative regulator of G protein signaling Sst2 did not have any dynamic requirements, and a constant step input sufficed. Similar approaches have yielded insight into transcriptional dynamics using spatiotemporal delivery of inputs [41], spatiotemporal control of gene expression in multiple single cells [42] and virtual pattern formation [43]. developments in this area include an improved robust version of periodic forcing through integral feedback [45] and ratio control [46], where rather than keeping a toggle switch undecided, computer feedback controls the proportions of cells in each of the two states.…”

Section: External (Computer-aided) Controlmentioning

confidence: 99%

Autonomous and Assisted Control for Synthetic Microbiology

Banderas

Bec

Cordier

et al. 2020

IJMS

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The control of microbes and microbial consortia to achieve specific functions requires synthetic circuits that can reliably cope with internal and external perturbations. Circuits that naturally evolved to regulate biological functions are frequently robust to alterations in their parameters. As the complexity of synthetic circuits increases, synthetic biologists need to implement such robust control “by design”. This is especially true for intercellular signaling circuits for synthetic consortia, where robustness is highly desirable, but its mechanisms remain unclear. Cybergenetics, the interface between synthetic biology and control theory, offers two approaches to this challenge: external (computer-aided) and internal (autonomous) control. Here, we review natural and synthetic microbial systems with robustness, and outline experimental approaches to implement such robust control in microbial consortia through population-level cybergenetics. We propose that harnessing natural intercellular circuit topologies with robust evolved functions can help to achieve similar robust control in synthetic intercellular circuits. A “hybrid biology” approach, where robust synthetic microbes interact with natural consortia and—additionally—with external computers, could become a useful tool for health and environmental applications.

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Cell-in-the-loop pattern formation with optogenetically emulated cell-to-cell signaling

Cited by 36 publications

References 63 publications

The Computational Boundary of a “Self”: Developmental Bioelectricity Drives Multicellularity and Scale-Free Cognition

The Computational Boundary of a “Self”: Developmental Bioelectricity Drives Multicellularity and Scale-Free Cognition

The rise and shine of yeast optogenetics

Autonomous and Assisted Control for Synthetic Microbiology

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