Autophosphorylation of EGFR at Y954 Facilitated Homodimerization and Enhanced Downstream Signals

Asymmetric dimer formation of epidermal growth factor receptor (EGFR) is crucial for EGF-induced receptor activation. Even though autophosphorylation is important for activation, its role remains elusive in the context of regulating dimers. In this study, employing overlapping time series analysis to raster image correlation spectroscopy (RICS), we observed time-dependent transient dynamics of EGFR dimerization and found EGFR kinase activity to be essential for dimerization. As a result of which, we hypothesized that phosphorylation could influence dimerization. Evaluating this point, we observed that one of the tyrosine residues (Y954) located in the C-terminal lobe of the activator kinase domain was important to potentiate dimerization. Functional imaging to monitor Ca²⁺ and ERK signals revealed a significant role of Y954 in influencing downstream signaling cascade. Crucial for stabilization of EGFR asymmetric dimer is a "latch" formed between kinase domains of the binding partners. Because Y954 is positioned adjacent to the latch binding region on the kinase domain, we propose that phosphorylation strengthened the latch interaction. On the contrary, we identified that threonine phosphorylation (T669) in the latch domain negatively regulated EGFR dimerization and the downstream signals. Overall, we have delineated the previously anonymous role of phosphorylation at the latch interface of kinase domains in regulating EGFR dimerization.

Inhibition of Receptor Dimerization as a Novel Negative Feedback Mechanism of EGFR Signaling

Dimerization of the epidermal growth factor receptor (EGFR) is crucial for initiating signal transduction. We employed raster image correlation spectroscopy to continuously monitor the EGFR monomer-dimer equilibrium in living cells. EGFR dimer formation upon addition of EGF showed oscillatory behavior with a periodicity of about 2.5 min, suggesting the presence of a negative feedback loop to monomerize the receptor. We demonstrated that monomerization of EGFR relies on phospholipase Cγ, protein kinase C, and protein kinase D (PKD), while being independent of Ca2+ signaling and endocytosis. Phosphorylation of the juxtamembrane threonine residues of EGFR (T654/T669) by PKD was identified as the factor that shifts the monomer-dimer equilibrium of ligand bound EGFR towards the monomeric state. The dimerization state of the receptor correlated with the activity of an extracellular signal-regulated kinase, downstream of the EGFR. Based on these observations, we propose a novel, negative feedback mechanism that regulates EGFR signaling via receptor monomerization.

MATHEMATICAL TREATMENTS THAT SOLVE SINGLE MOLECULES

In this article, we talk about the ways that scientists can solve single molecule trajectories. Solving single molecules, that is, finding the model from the data, is complicated at least as much as measuring single molecules. We must filter the noise and take care of every step in the analysis when constructing the most accurate model from the data. Here, we present valuable solutions. Ways that solve clean discrete data are first presented. We review here our reduced dimensions forms (RDFs): unique models that are canonical forms of discrete data, and the statistical and numerical toolbox that builds a RDF from finite, clean, two-state data. We then review our most recent filter that "tackles" the noise when measuring two state noisy photon trajectories. The filter is a numerical algorithm with various special statistical treatments that is based on a general likelihood function that we have developed recently. We show the strengths of the filter (also over other approaches) and talk about its various new variants. This filter (with minor adjustments) can solve the noise in any discrete state trajectories, yet, extensions are needed in "tackling" the noise from other data, e.g. continuous data. Only the combined procedures enable creating the most accurate model from noisy discrete trajectories from single molecules. These concepts and methods (with adjustments) are valuable also when solving continuous trajectories and fluorescence resonance energy transfer trajectories. We also present a set of simple methods that can help any scientist with treating the trajectory perhaps encouraging applying the involved methods. The involved methods will appear in software that we are developing now, helping therefore the experimentalists utilizing these methods on real data. Comparisons with other known methods in this field are made.

[Formula: see text]Special Issue Comment: This article about mathematical treatments when solving single molecules is related to the reviews in this Special Issue about measuring enzymes67 and about FRET experiments2 and about the software QUB.6

SOLVING SINGLE BIOMOLECULES BY ADVANCED FRET-BASED SINGLE-MOLECULE FLUORESCENCE TECHNIQUES

The use of Förster resonance energy transfer (FRET) has undergone a renaissance in the last two decades, especially in the study of structure of biomolecules, biomolecular interactions, and dynamics. Thanks to powerful advances in single-molecule fluorescence (SMF) techniques, seeing molecules at work is a reality, which has helped to build up the mindset of molecular machines. In the last few years, many technical developments have broadened the applications of SMF-FRET, expanding the amount of information that can be recovered from individual molecules. Here, we focus on the non-standard SMF-FRET techniques, such as two-color coincidence detection (TCCD), alternating laser excitation (ALEX), multiparameter fluorescence detection (MFD); the addition of fluorescence lifetime as an orthogonal dimension in single-molecule experiments; or the development of novel and improved methods of analysis constituting to a set of advanced methodologies that may become routine tools in a close future.

[Formula: see text]Special Issue Comment: This review about advanced single-molecule FRET techniques is specially related to the review by Jørgensen and Hatzakis,6 who detail experimetal strategies to solve the activity of single enzymes. The advanced techniques described in our paper may serve as interesting alternatives when applied to enzyme studies. Our manuscript is also related to the reviews in this Special Issue that deal with model solving.22,130