The dependence of EGFR oligomerization on environment and structure: A camera-based N&B study

Transmembrane signaling through single-spanning receptors modulated by phase separation at the cell surface

A wide variety of transmembrane signals are transduced by cell-surface receptors that activate intracellular signaling molecules. In particular, receptor clustering in the plasma membrane plays a critical role in these processes. Single-spanning or single-pass transmembrane proteins are among the most significant types of membrane receptors, which include adhesion receptors, such as integrins, CD44, cadherins, and receptor tyrosine kinases. Elucidating the molecular mechanisms underlying the regulation of the activity of these receptors is of great significance. Liquid-liquid phase separation (LLPS) is a recently emerging paradigm in cellular physiology for the ubiquitous regulation of the spatiotemporal dynamics of various signaling pathways. This study describes the emerging features of transmembrane signaling through single-spanning receptors from the perspective of phase separation. Possible physicochemical modulations of LLPS-based transmembrane signaling are also discussed.

Deep learning reduces data requirements and allows real-time measurements in imaging FCS

Imaging fluorescence correlation spectroscopy (FCS) is a powerful tool to extract information on molecular mobilities, actions, and interactions in live cells, tissues, and organisms. Nevertheless, several limitations restrict its applicability. First, FCS is data hungry, requiring 50,000 frames at 1-ms time resolution to obtain accurate parameter estimates. Second, the data size makes evaluation slow. Third, as FCS evaluation is model dependent, data evaluation is significantly slowed unless analytic models are available. Here, we introduce two convolutional neural networks-FCSNet and ImFCSNet-for correlation and intensity trace analysis, respectively. FCSNet robustly predicts parameters in 2D and 3D live samples. ImFCSNet reduces the amount of data required for accurate parameter retrieval by at least one order of magnitude and makes correct estimates even in moderately defocused samples. Both convolutional neural networks are trained on simulated data, are model agnostic, and allow autonomous, real-time evaluation of imaging FCS measurements.

Distinct interactions stabilize EGFR dimers and higher-order oligomers in cell membranes

The epidermal growth factor receptor (EGFR) is a receptor tyrosine kinase with important roles in many cellular processes as well as in cancer and other diseases. EGF binding promotes EGFR dimerization and autophosphorylation through interactions that are well understood structurally. How these dimers relate to higher-order EGFR oligomers seen in cell membranes, however, remains unclear. Here, we used single-particle tracking (SPT) and Förster resonance energy transfer imaging to examine how each domain of EGFR contributes to receptor oligomerization and the rate of receptor diffusion in the cell membrane. Although the extracellular region of EGFR is sufficient to drive receptor dimerization, we find that the EGF-induced EGFR slowdown seen by SPT requires higher-order oligomerization-mediated in part by the intracellular tyrosine kinase domain when it adopts an active conformation. Our data thus provide important insight into the interactions required for higher-order EGFR assemblies involved in EGF signaling.

Absolute quantification of protein number and dynamics in single cells

Quantitative characterization of protein abundance and interactions in live cells is necessary to understand and predict cellular behavior. The accurate determination of copy number for individual proteins and heterologous complexes in individual cells is critical because small changes in protein dosage, often less than two-fold, can have strong phenotypic consequences. Here, we review the merits and pitfalls of different quantitative fluorescence imaging methods for single-cell determination of protein abundance, localization, interactions, and dynamics. In particular, we discuss how scanning number and brightness (sN&B) and its variation, Raster scanning image correlation spectroscopy (RICS), exploit stochastic noise in small measurement volumes to quantify protein abundance, stoichiometry, and dynamics with high accuracy.

Benchmarking of novel green fluorescent proteins for the quantification of protein oligomerization in living cells

Protein-protein-interactions play an important role in many cellular functions. Quantitative non-invasive techniques are applied in living cells to evaluate such interactions, thereby providing a broader understanding of complex biological processes. Fluorescence fluctuation spectroscopy describes a group of quantitative microscopy approaches for the characterization of molecular interactions at single cell resolution. Through the obtained molecular brightness, it is possible to determine the oligomeric state of proteins. This is usually achieved by fusing fluorescent proteins (FPs) to the protein of interest. Recently, the number of novel green FPs has increased, with consequent improvements to the quality of fluctuation-based measurements. The photophysical behavior of FPs is influenced by multiple factors (including photobleaching, protonation-induced "blinking" and long-lived dark states). Assessing these factors is critical for selecting the appropriate fluorescent tag for live cell imaging applications. In this work, we focus on novel green FPs that are extensively used in live cell imaging. A systematic performance comparison of several green FPs in living cells under different pH conditions using Number & Brightness (N&B) analysis and scanning fluorescence correlation spectroscopy was performed. Our results show that the new FP Gamillus exhibits higher brightness at the cost of lower photostability and fluorescence probability (pf), especially at lower pH. mGreenLantern, on the other hand, thanks to a very high pf, is best suited for multimerization quantification at neutral pH. At lower pH, mEGFP remains apparently the best choice for multimerization investigation. These guidelines provide the information needed to plan quantitative fluorescence microscopy involving these FPs, both for general imaging or for protein-protein-interactions quantification via fluorescence fluctuation-based methods.

Determining the Functional Oligomeric State of Membrane-Associated Protein Oligomers Forming Membrane Pores on Giant Lipid Vesicles

Several peripheral membrane proteins are known to form membrane pores through multimerization. In many cases, in biochemical reconstitution experiments, a complex distribution of oligomeric states has been observed that may, in part, be irrelevant to their physiological functions. This phenomenon makes it difficult to identify the functional oligomeric states of membrane lipid interacting proteins, for example, during the formation of transient membrane pores. Using fibroblast growth factor 2 (FGF2) as an example, we present a methodology applicable to giant lipid vesicles by which functional oligomers can be distinguished from nonspecifically aggregated proteins without functionality. Two distinct populations of fibroblast growth factor 2 were identified with (i) dimers to hexamers and (ii) a broad population of higher oligomeric states of membrane-associated FGF2 oligomers significantly distorting the original unfiltered histogram of all detectable oligomeric species of FGF2. The presented statistical approach is relevant for various techniques for characterizing membrane-dependent protein oligomerization.

Distinct interactions stabilize EGFR dimers and higher-order oligomers in cell membranes

The epidermal growth factor receptor (EGFR) is a receptor tyrosine kinase (RTK) with important roles in many cellular processes as well as cancer and other diseases. EGF binding promotes EGFR dimerization and autophosphorylation through interactions that are well understood structurally. However, it is not clear how these dimers relate to higher-order EGFR oligomers detected at the cell surface. We used single-particle tracking (SPT) and Förster resonance energy transfer (FRET) imaging to examine how each domain within EGFR contributes to receptor dimerization and the rate of its diffusion in the cell membrane. We show that the EGFR extracellular region is sufficient to drive receptor dimerization, but that the EGF-induced EGFR slow-down seen by SPT requires formation of higher order oligomers, mediated in part by the intracellular tyrosine kinase domain - but only when in its active conformation. Our data thus provide important insight into higher-order EGFR interactions required for EGF signaling.