Genetically Encoded Fluorescent Biosensors Illuminate the Spatiotemporal Regulation of Signaling Networks.

Cellular signaling networks are the foundation which determines the fate and function of cells as they respond to various cues and stimuli. The discovery of fluorescent proteins over 25 years ago enabled the development of a diverse array of genetically encodable fluorescent biosensors that are capable of measuring the spatiotemporal dynamics of signal transduction pathways in live cells. In an effort to encapsulate the breadth over which fluorescent biosensors have expanded, we endeavored to assemble a comprehensive list of published engineered biosensors, and we discuss many of the molecular designs utilized in their development. Then, we review how the high temporal and spatial resolution afforded by fluorescent biosensors has aided our understanding of the spatiotemporal regulation of signaling networks at the cellular and subcellular level. Finally, we highlight some emerging areas of research in both biosensor design and applications that are on the forefront of biosensor development.

Scaffold state switching amplifies, accelerates, and insulates protein kinase C signaling.

Scaffold proteins localize two or more signaling enzymes in close proximity to their downstream effectors. A-kinase-anchoring proteins (AKAPs) are a canonical family of scaffold proteins known to bind protein kinase A (PKA) and other enzymes. Several AKAPs have been shown to accelerate, amplify, and specify signal transduction to dynamically regulate numerous cellular processes. However, there is little theory available to mechanistically explain how signaling on protein scaffolds differs from solution biochemistry. In our present study, we propose a novel kinetic mechanism for enzymatic reactions on protein scaffolds to explain these phenomena, wherein the enzyme-substrate-scaffold complex undergoes stochastic state switching to reach an active state. This model predicted anchored enzymatic reactions to be accelerated, amplified, and insulated from inhibition compared with those occurring in solution. We exploited a direct interaction between protein kinase C (PKC) and AKAP7α as a model to validate these predictions experimentally. Using a genetically encoded PKC activity reporter, we found that both the strength and speed of substrate phosphorylation were enhanced by AKAP7α. PKC tethered to AKAP7α was less susceptible to inhibition from the ATP-competitive inhibitor Gö6976 and the substrate-competitive inhibitor PKC 20-28, but not the activation-competitive inhibitor calphostin C. Model predictions and experimental validation demonstrated that insulation is a general property of scaffold tethering. Sensitivity analysis indicated that these findings may be applicable to many other scaffolds as well. Collectively, our findings provide theoretical and experimental evidence that scaffold proteins can amplify, accelerate, and insulate signal transduction.

Discovery of a highly potent, selective, orally bioavailable inhibitor of KAT6A/B histone acetyltransferases with efficacy against KAT6A-high ER+ breast cancer.

KAT6A, and its paralog KAT6B, are histone lysine acetyltransferases (HAT) that acetylate histone H3K23 and exert an oncogenic role in several tumor types including breast cancer where KAT6A is frequently amplified/overexpressed. However, pharmacologic targeting of KAT6A to achieve therapeutic benefit has been a challenge. Here we describe identification of a highly potent, selective, and orally bioavailable KAT6A/KAT6B inhibitor CTx-648 (PF-9363), derived from a benzisoxazole series, which demonstrates anti-tumor activity in correlation with H3K23Ac inhibition in KAT6A over-expressing breast cancer. Transcriptional and epigenetic profiling studies show reduced RNA Pol II binding and downregulation of genes involved in estrogen signaling, cell cycle, Myc and stem cell pathways associated with CTx-648 anti-tumor activity in ER-positive (ER+) breast cancer. CTx-648 treatment leads to potent tumor growth inhibition in ER+ breast cancer in vivo models, including models refractory to endocrine therapy, highlighting the potential for targeting KAT6A in ER+ breast cancer.

Bigger, better, faster: principles and models of AKAP anchoring protein signaling.

A kinase anchoring proteins (AKAPs) bind multiple signaling proteins and have subcellular targeting domains that allow them to greatly impact cellular signaling. AKAPs localize, specify, amplify, and accelerate signal transduction within the cell by bringing signaling proteins together in space and time. AKAPs also organize higher-order network motifs such as feed forward and feedback loops that may create complex network responses, including adaptation, oscillation, and ultrasensitivity. Computational models have begun to provide an insight into how AKAPs regulate signaling dynamics and cardiovascular pathophysiology. Models of mitogen-activated protein kinase and epidermal growth factor receptor scaffolds have revealed additional design principles and new methods for representing signaling scaffolds mathematically. Coupling computational modeling with quantitative experimental approaches will be increasingly necessary for dissecting the diverse information processing functions performed by AKAP signaling complexes.

Degradation improves tissue formation in (un)loaded chondrocyte-laden hydrogels.

BACKGROUND: Photopolymerizable poly(ethylene glycol) (PEG) hydrogels offer a platform to deliver cells in vivo and support three-dimensional cell culture but should be designed to degrade in sync with neotissue development and endure the physiologic environment. QUESTIONS/PURPOSES: We asked whether (1) incorporation of degradation into PEG hydrogels facilitates tissue development comprised of essential cartilage macromolecules; (2) with early loading before pericellular matrix formation, the duration of load affects matrix production; and (3) dynamic loading in general influences macroscopic tissue development. METHODS: Primary bovine chondrocytes were encapsulated in hydrogels (n = 3 for each condition). The independent variables were hydrogel degradation (nondegrading PEG and degrading oligo(lactic acid)-b-PEG-b-oligo(lactic acid) [PEG-LA]), culture condition (free swelling, unconfined dynamic compressive loading applied intermittently for 1 or 4 weeks), and time (up to 28 days). The dependent variables were neotissue deposition through biochemical contents, immunohistochemistry, and compressive modulus. RESULTS: Degradation led to 2.3- and 2.9-fold greater glycosaminoglycan and collagen contents, respectively; macroscopic cartilage-like tissue formation comprised of aggrecan, collagen II and VI, link protein, and decorin; but decreased moduli. Loading, applied early or throughout culture, did not affect neotissue content in either hydrogel but affected neotissue spatial distribution in degrading hydrogels where 4 weeks of loading appeared to enhance hydrogel degradation resulting in tissue defects. CONCLUSIONS: PEG-LA hydrogels led to macroscopic tissue development comprised of key cartilage macromolecules under loading, but hydrogel degradation requires further tuning. CLINICAL RELEVANCE: PEG-LA hydrogels have potential for delivering chondrocytes in vivo to replace damaged cartilage with a tissue-engineered native equivalent, overcoming many limitations associated with current clinical treatments.

AKAP95 Organizes a Nuclear Microdomain to Control Local cAMP for Regulating Nuclear PKA.

Contrary to the classic model of protein kinase A (PKA) residing outside of the nucleus, we identify a nuclear signaling complex that consists of AKAP95, PKA, and PDE4D5 and show that it forms a functional cyclic AMP (cAMP) signaling microdomain. Locally generated cAMP can accumulate within the vicinity of this complex; however, when cAMP is generated at the plasma membrane, PDE4 serves as a local sink and PDE3 as a barrier to prevent accumulation of cAMP within the microdomain as a means of controlling activation of tethered nuclear PKA.

Integrating fluorescent biosensor data using computational models.

This book chapter provides a tutorial on how to construct computational models of signaling networks for the integration and interpretation of FRET-based biosensor data. A model of cAMP production and PKA activation is presented to provide an example of the model building process. The computational model is defined using hypothesized signaling network structure and measured kinetic parameters and then simulated in Virtual Cell software. Experimental acquisition and processing of FRET biosensor data is discussed in the context of model validation. This data is then used to fit parameters of the computational model such that the model can more accurately predict experimental data. Finally, this model is used to show how computational experiments can interrogate signaling networks and provide testable hypotheses. This simple, yet detailed, tutorial on how to use computational models provides biologists that use biosensors a powerful tool to further probe and evaluate the underpinnings of a biological response.

Triphasic mixture model of cell-mediated enzymatic degradation of hydrogels.

One critical component of engineering living tissue equivalents is the design scaffolds (often made of hydrogels) whose degradation kinetics can match that of matrix production by cells. However, cell-mediated enzymatic degradation of a hydrogel is a highly complex and nonlinear process that is challenging to comprehend based solely on experimental observations. To address this issue, this study presents a triphasic mixture model of the enzyme-hydrogel system, which consists of a solid polymer network, water and enzyme. On the basis mixture theory, the rubber elasticity theory and the Michaelis-Menton kinetics for degradation, the model naturally incorporates a strong coupling between gel mechanical properties, the kinetics of degradation and the transport of enzyme through the gel. The model is then used to investigate the particular problem of a single spherical enzyme-producing cell, embedded in a spherical hydrogel domain, for which the governing equations can be cast within the cento-symmetric assumptions. The governing equations are subsequently solved using an implicit nonlinear finite element procedure to obtain the evolution of enzyme concentration and gel degradation through time and space. The model shows that two regimes of degradation behaviour exist, whereby degradation is dominated either by diffusion or dominated by reaction kinetics. Depending on the enzyme properties and the initial hydrogel design, the temporal and spatial changes in gel cross-linking are dramatically impacted, a feature that is likely to strongly affect new tissue development.