Quantifying the Kinetics of Signaling and Arrestin Recruitment by Nervous System G-Protein Coupled Receptors

Neurons integrate inputs over different time and space scales. Fast excitatory synapses at boutons (ms and μm), and slow modulation over entire dendritic arbors (seconds and mm) are all ultimately combined to produce behavior. Understanding the timing of signaling events mediated by G-protein-coupled receptors is necessary to elucidate the mechanism of action of therapeutics targeting the nervous system. Measuring signaling kinetics in live cells has been transformed by the adoption of fluorescent biosensors and dyes that convert biological signals into optical signals that are conveniently recorded by microscopic imaging or by fluorescence plate readers. Quantifying the timing of signaling has now become routine with the application of equations in familiar curve fitting software to estimate the rates of signaling from the waveform. Here we describe examples of the application of these methods, including (1) Kinetic analysis of opioid signaling dynamics and partial agonism measured using cAMP and arrestin biosensors; (2) Quantifying the signaling activity of illicit synthetic cannabinoid receptor agonists measured using a fluorescent membrane potential dye; (3) Demonstration of multiplicity of arrestin functions from analysis of biosensor waveforms and quantification of the rates of these processes. These examples show how temporal analysis provides additional dimensions to enhance the understanding of GPCR signaling and therapeutic mechanisms in the nervous system.

Dynamic configurations of meiotic DNA-break hotspot determinant proteins

Appropriate DNA double-strand-break (DSB) and crossover distributions are required for proper meiotic chromosome segregation. Schizosaccharomyces pombe linear element proteins (LinEs) determine DSB hotspots; LinE-bound hotspots form 3D clusters over ∼200 kb chromosomal regions. Here, we investigated LinE configurations and distributions in live cells using super-resolution fluorescence microscopy. We found LinEs form two chromosomal structures, dot-like and linear structures, in both zygotic and azygotic meiosis. Dot-like LinE structures appeared around the time of meiotic DNA replication, underwent dotty-to-linear-to-dotty configurational transitions, and disassembled before the first meiotic division. DSB formation and repair did not detectably influence LinE structure formation, but failure of DSB formation delayed disassembly. Recombination-deficient LinE missense mutants formed dot-like but not linear LinE structures. Our quantitative study reveals a transient form of LinE structures and suggests a novel role for LinE proteins in regulating meiotic events, such as DSB repair. We discuss the relation of LinEs and the synaptonemal complex in other species.

Generative adversarial network enables rapid and robust fluorescence lifetime image analysis in live cells

Fluorescence lifetime imaging microscopy (FLIM) is a powerful tool to quantify molecular compositions and study molecular states in complex cellular environment as the lifetime readings are not biased by fluorophore concentration or excitation power. However, the current methods to generate FLIM images are either computationally intensive or unreliable when the number of photons acquired at each pixel is low. Here we introduce a new deep learning-based method termed flimGANE (fluorescence lifetime imaging based on Generative Adversarial Network Estimation) that can rapidly generate accurate and high-quality FLIM images even in the photon-starved conditions. We demonstrated our model is up to 2,800 times faster than the gold standard time-domain maximum likelihood estimation (TD_MLE) and that flimGANE provides a more accurate analysis of low-photon-count histograms in barcode identification, cellular structure visualization, Förster resonance energy transfer characterization, and metabolic state analysis in live cells. With its advantages in speed and reliability, flimGANE is particularly useful in fundamental biological research and clinical applications, where high-speed analysis is critical.

Hypocrates is a genetically encoded fluorescent biosensor for (pseudo)hypohalous acids and their derivatives

The lack of tools to monitor the dynamics of (pseudo)hypohalous acids in live cells and tissues hinders a better understanding of inflammatory processes. Here we present a fluorescent genetically encoded biosensor, Hypocrates, for the visualization of (pseudo)hypohalous acids and their derivatives. Hypocrates consists of a circularly permuted yellow fluorescent protein integrated into the structure of the transcription repressor NemR from Escherichia coli. We show that Hypocrates is ratiometric, reversible, and responds to its analytes in the 106 M−1s−1 range. Solving the Hypocrates X-ray structure provided insights into its sensing mechanism, allowing determination of the spatial organization in this circularly permuted fluorescent protein-based redox probe. We exemplify its applicability by imaging hypohalous stress in bacteria phagocytosed by primary neutrophils. Finally, we demonstrate that Hypocrates can be utilized in combination with HyPerRed for the simultaneous visualization of (pseudo)hypohalous acids and hydrogen peroxide dynamics in a zebrafish tail fin injury model.

Negative tension controls stability and structure of intermediate filament networks

Networks, whose junctions are free to move along the edges, such as two-dimensional soap froths and membrane tubular networks of endoplasmic reticulum are intrinsically unstable. This instability is a result of a positive tension applied to the network elements. A paradigm of networks exhibiting stable polygonal configurations in spite of the junction mobility, are networks formed by bundles of Keratin Intermediate Filaments (KIFs) in live cells. A unique feature of KIF networks is a, hypothetically, negative tension generated in the network bundles due to an exchange of material between the network and an effective reservoir of unbundled filaments. Here we analyze the structure and stability of two-dimensional networks with mobile three-way junctions subject to negative tension. First, we analytically examine a simplified case of hexagonal networks with symmetric junctions and demonstrate that, indeed, a negative tension is mandatory for the network stability. Another factor contributing to the network stability is the junction elastic resistance to deviations from the symmetric state. We derive an equation for the optimal density of such networks resulting from an interplay between the tension and the junction energy. We describe a configurational degeneration of the optimal energy state of the network. Further, we analyze by numerical simulations the energy of randomly generated networks with, generally, asymmetric junctions, and demonstrate that the global minimum of the network energy corresponds to the irregular configurations.

Transbilayer Coupling of Lipids in Cells Investigated by Imaging Fluorescence Correlation Spectroscopy

Plasma membrane hosts numerous receptors, sensors, and ion channels involved in cellular signaling. Phase separation of the plasma membrane is emerging as a key biophysical regulator of signaling reactions in multiple physiological and pathological contexts. There is much evidence that plasma membrane composition supports the co-existence liquid-ordered (Lo) and liquid-disordered (Ld) phases or domains at physiological conditions. However, this phase/domain separation is nanoscopic and transient in live cells. It is recently proposed that transbilayer coupling between the inner and outer leaflets of the plasma membrane is driven by their asymmetric lipid distribution and by dynamic cytoskeleton-lipid composites that contribute to the formation and transience of Lo/Ld phase separation in live cells. In this Perspective, we highlight new approaches to investigate how transbilayer coupling may influence phase separation. For quantitative evaluation of the impact of these interactions, we introduce an experimental strategy centered around Imaging Fluorescence Correlation Spectroscopy (ImFCS), which measures membrane diffusion with very high precision. To demonstrate this strategy we choose two well-established model systems for transbilayer interactions: crosslinking by multivalent antigen of immunoglobulin E bound to receptor FcεRI, and crosslinking by cholera toxin B of GM1 gangliosides. We discuss emerging methods to systematically perturb membrane lipid composition, particularly exchange of outer leaflet lipids with exogenous lipids using methyl alpha cyclodextrin. These selective perturbations may be quantitatively evaluated with ImFCS and other high-resolution biophysical tools to discover novel principles of lipid-mediated phase separation in live cells in the context of their pathophysiological relevance.

Kinesin and Myosin Motors Compete to Drive Rich Multi-Phase Dynamics in Programmable Cytoskeletal Composites

The cytoskeleton of biological cells relies on a diverse population of motors, filaments, and binding proteins acting in concert to enable non-equilibrium processes ranging from mitosis to chemotaxis. The cytoskeleton’s versatile reconfigurability, programmed by interactions between its constituents, make it a foundational active matter platform. However, current active matter endeavors are limited largely to single force-generating components acting on a single substrate – far from the composite cytoskeleton in live cells. Here, we engineer actin-microtubule composites, driven by kinesin and myosin motors and tuned by crosslinkers, that restructure into diverse morphologies from interpenetrating filamentous networks to de-mixed amorphous clusters. Our Fourier analyses reveal that kinesin and myosin compete to delay kinesin-driven restructuring and suppress de-mixing and flow, while crosslinking accelerates reorganization and promotes actin-microtubule correlations. The phase space of non-equilibrium dynamics falls into three broad classes– slow reconfiguration, fast advective flow, and multi-mode ballistic dynamics – with structure-dynamics relations described by the relative contributions of elastic and dissipative responses to motor-generated forces.