Optogenetic interrogation and control of cell signaling

Hongdusit, Akarawin; Liechty, Evan T; Fox, Jerome M.

doi:10.1016/j.copbio.2020.07.007

Cited by 15 publications

(9 citation statements)

References 95 publications

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“…5 Cell signaling networks rigorously regulate numerous intracellular signaling pathways to precisely control the progression of cellular activities. 6 When these important signaling pathways are disrupted, abnormal cellular changes may occur, leading to tumorigenesis. 7 Therefore, the search for key factors involved in the intracellular regulatory networks of OC might proffer a theoretical basis for individualized diagnosis and treatment of OC.…”

Section: Introductionmentioning

confidence: 99%

Identification of Prognostic Biomarkers Among FAM83 Family Genes in Human Ovarian Cancer Through Bioinformatic Analysis and Experimental Verification

Lin¹,

Du²,

Hao³

et al. 2021

CMAR

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Section: Introductionmentioning

confidence: 99%

Identification of Prognostic Biomarkers Among FAM83 Family Genes in Human Ovarian Cancer Through Bioinformatic Analysis and Experimental Verification

Lin¹,

Du²,

Hao³

et al. 2021

CMAR

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“…In practice, this can limit the utility of powerful classical nonlinear control methods that identify inputs that can globally or locally control a system, such as control Lyapunov methods 19 , 25 , but which assume the ability to carefully engineer input signals. Despite the biotechnological challenge of implementing finely tuned control strategies, there have been notable successes in applying optogenetic methods to study and control cardiac processes 26 , neurological signaling 27 , molecular signaling pathways 28 , and gene expression 29 .…”

Section: Challenges Of Network Controlmentioning

confidence: 99%

“…Despite the biotechnological challenge of implementing finely tuned control strategies, there have been notable successes in applying optogenetic methods to study and control cardiac processes 26 , neurological signaling 27 , molecular signaling pathways 28 , and gene expression 29 .…”

Section: Uncertainty In Dynamic Specificationmentioning

confidence: 99%

Leveraging network structure in nonlinear control

Rozum

Albert

2022

npj Syst Biol Appl

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Over the last twenty years, dynamic modeling of biomolecular networks has exploded in popularity. Many of the classical tools for understanding dynamical systems are unwieldy in the highly nonlinear, poorly constrained, high-dimensional systems that often arise from these modeling efforts. Understanding complex biological systems is greatly facilitated by purpose-built methods that leverage common features of such models, such as local monotonicity, interaction graph sparsity, and sigmoidal kinetics. Here, we review methods for controlling the systems of ordinary differential equations used to model biomolecular networks. We focus on methods that make use of the structure of the network of interactions to help inform, which variables to target for control, and highlight the computational and experimental advantages of such approaches. We also discuss the importance of nonperturbative methods in biomedical and experimental molecular biology applications, where finely tuned interventions can be difficult to implement. It is well known that feedback loops, and positive feedback loops in particular, play a major determining role in the dynamics of biomolecular networks. In many of the methods we cover here, control over system trajectories is realized by overriding the behavior of key feedback loops.

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“…Multichromatic approaches enable the control of two signaling pathways independently by using light of different wavelengths [ 5 ]. The unprecedented spatiotemporal resolution allows researchers to activate signaling in single cell resolution or even subcellular resolution dynamically [ 6 , 7 ].…”

Section: Introductionmentioning

confidence: 99%

Optogenetic Approaches for the Spatiotemporal Control of Signal Transduction Pathways

Kramer

Lataster

Weber

et al. 2021

IJMS

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Biological signals are sensed by their respective receptors and are transduced and processed by a sophisticated intracellular signaling network leading to a signal-specific cellular response. Thereby, the response to the signal depends on the strength, the frequency, and the duration of the stimulus as well as on the subcellular signal progression. Optogenetic tools are based on genetically encoded light-sensing proteins facilitating the precise spatiotemporal control of signal transduction pathways and cell fate decisions in the absence of natural ligands. In this review, we provide an overview of optogenetic approaches connecting light-regulated protein-protein interaction or caging/uncaging events with steering the function of signaling proteins. We briefly discuss the most common optogenetic switches and their mode of action. The main part deals with the engineering and application of optogenetic tools for the control of transmembrane receptors including receptor tyrosine kinases, the T cell receptor and integrins, and their effector proteins. We also address the hallmarks of optogenetics, the spatial and temporal control of signaling events.

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Optogenetic interrogation and control of cell signaling

Cited by 15 publications

References 95 publications

Identification of Prognostic Biomarkers Among FAM83 Family Genes in Human Ovarian Cancer Through Bioinformatic Analysis and Experimental Verification

Identification of Prognostic Biomarkers Among FAM83 Family Genes in Human Ovarian Cancer Through Bioinformatic Analysis and Experimental Verification

Leveraging network structure in nonlinear control

Optogenetic Approaches for the Spatiotemporal Control of Signal Transduction Pathways

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