Membrane dynamics of resting and internalin B-bound MET receptor tyrosine kinase studied by single-molecule tracking

Quantitative live imaging reveals a direct interaction between CD44v6 and MET in membrane domains upon activation with both MET ligands, HGF and internalin B

Deregulation of the receptor tyrosine kinase MET/hepatocyte growth factor (HGF) pathway results in several pathological processes involved in tumor progression and metastasis. In a different context, MET can serve as an entry point for the bacterium Listeria monocytogenes, when activated by the internalin B (InlB) protein during infection of non-phagocytic cells. We have previously demonstrated that MET requires CD44v6 for its ligand-induced activation. However, the stoichiometry and the steps required for the formation of this complex, are still unknown. In this work, we studied the dynamics of the ligand-induced interaction of CD44v6 with MET at the plasma membrane. Using Förster resonance energy transfer-based fluorescence lifetime imaging microscopy in T-47D cells, we evidenced a direct interaction between MET and CD44v6 promoted by HGF and InlB in live cells. In the absence of MET, fluorescence correlation spectroscopy experiments further showed the dimerization of CD44v6 and the increase of its diffusion induced by HGF and InlB. In the presence of MET, stimulation of the cells by HGF or InlB significantly decreased the diffusion of CD44v6, in line with the formation of a ternary complex of MET with CD44v6 and HGF/InlB. Finally, similarly to HGF/InlB, disruption of liquid-ordered domains (Lo) by methyl-β-cyclodextrin increased CD44v6 mobility suggesting that these factors induce the exit of CD44v6 from the Lo domains. Our data led us to propose a model for MET activation, where CD44v6 dimerizes and diffuses rapidly out of Lo domains to form an oligomeric MET/ligand/CD44v6 complex that is instrumental for MET activation.

Biased activation of the receptor tyrosine kinase HER2

HER2 belongs to the ErbB sub-family of receptor tyrosine kinases and regulates cellular proliferation and growth. Different from other ErbB receptors, HER2 has no known ligand. Activation occurs through heterodimerization with other ErbB receptors and their cognate ligands. This suggests several possible activation paths of HER2 with ligand-specific, differential response, which has so far remained unexplored. Using single-molecule tracking and the diffusion profile of HER2 as a proxy for activity, we measured the activation strength and temporal profile in live cells. We found that HER2 is strongly activated by EGFR-targeting ligands EGF and TGFα, yet with a distinguishable temporal fingerprint. The HER4-targeting ligands EREG and NRGβ1 showed weaker activation of HER2, a preference for EREG, and a delayed response to NRGβ1. Our results indicate a selective ligand response of HER2 that may serve as a regulatory element. Our experimental approach is easily transferable to other membrane receptors targeted by multiple ligands.

A recurring packing contact in crystals of InlB pinpoints functional binding sites in the internalin domain and the B repeat

InlB, a bacterial agonist of the human receptor tyrosine kinase MET, consists of an N-terminal internalin domain, a central B repeat and three C-terminal GW domains. In all previous structures of full-length InlB or an InlB construct lacking the GW domains (InlB392), there was no interpretable electron density for the B repeat. Here, three InlB392 crystal structures in which the B repeat is resolved are described. These are the first structures to reveal the relative orientation of the internalin domain and the B repeat. A wild-type structure and two structures of the T332E variant together contain five crystallographically independent molecules. Surprisingly, the threonine-to-glutamate substitution in the B repeat substantially improved the crystallization propensity and crystal quality of the T332E variant. The internalin domain and B repeat are quite rigid internally, but are flexibly linked to each other. The new structures show that inter-domain flexibility is the most likely cause of the missing electron density for the B repeat in previous InlB structures. A potential binding groove between B-repeat strand β2 and an adjacent loop forms an important crystal contact in all five crystallographically independent chains. This region may represent a hydrophobic `sticky patch' that supports protein–protein interactions. This assumption agrees with the previous finding that all known inactivating point mutations in the B repeat lie within strand β2. The groove formed by strand β2 and the adjacent loop may thus represent a functionally important protein–protein interaction site in the B repeat.

Receptor tyrosine kinase MET ligand-interaction classified via machine learning from single-particle tracking data

Internalin B–mediated activation of the membrane-bound receptor tyrosine kinase MET is accompanied by a change in receptor mobility. Conversely, it should be possible to infer from receptor mobility whether a cell has been treated with internalin B. Here, we propose a method based on hidden Markov modeling and explainable artificial intelligence that machine-learns the key differences in MET mobility between internalin B–treated and –untreated cells from single-particle tracking data. Our method assigns receptor mobility to three diffusion modes (immobile, slow, and fast). It discriminates between internalin B–treated and –untreated cells with a balanced accuracy of >99% and identifies three parameters that are most affected by internalin B treatment: a decrease in the mobility of slow molecules (1) and a depopulation of the fast mode (2) caused by an increased transition of fast molecules to the slow mode (3). Our approach is based entirely on free software and is readily applicable to the analysis of other membrane receptors.

Diffusion State Transitions in Single-Particle Trajectories of MET Receptor Tyrosine Kinase Measured in Live Cells

Single-particle tracking enables the analysis of the dynamics of biomolecules in living cells with nanometer spatial and millisecond temporal resolution. This technique reports on the mobility of membrane proteins and is sensitive to the molecular state of a biomolecule and to interactions with other biomolecules. Trajectories describe the mobility of single particles over time and provide information such as the diffusion coefficient and diffusion state. Changes in particle dynamics within single trajectories lead to segmentation, which allows to extract information on transitions of functional states of a biomolecule. Here, mean-squared displacement analysis is developed to classify trajectory segments into immobile, confined diffusing, and freely diffusing states, and to extract the occurrence of transitions between these modes. We applied this analysis to single-particle tracking data of the membrane receptor MET in live cells and analyzed state transitions in single trajectories of the un-activated receptor and the receptor bound to the ligand internalin B. We found that internalin B-bound MET shows an enhancement of transitions from freely and confined diffusing states into the immobile state as compared to un-activated MET. Confined diffusion acts as an intermediate state between immobile and free, as this state is most likely to change the diffusion state in the following segment. This analysis can be readily applied to single-particle tracking data of other membrane receptors and intracellular proteins under various conditions and contribute to the understanding of molecular states and signaling pathways.

Maximum likelihood estimates of diffusion coefficients from single-particle tracking experiments

Single-molecule localization microscopy allows practitioners to locate and track labeled molecules in biological systems. When extracting diffusion coefficients from the resulting trajectories, it is common practice to perform a linear fit on mean-squared-displacement curves. However, this strategy is suboptimal and prone to errors. Recently, it was shown that the increments between the observed positions provide a good estimate for the diffusion coefficient, and their statistics are well-suited for likelihood-based analysis methods. Here, we revisit the problem of extracting diffusion coefficients from single-particle tracking experiments subject to static noise and dynamic motion blur using the principle of maximum likelihood. Taking advantage of an efficient real-space formulation, we extend the model to mixtures of subpopulations differing in their diffusion coefficients, which we estimate with the help of the expectation-maximization algorithm. This formulation naturally leads to a probabilistic assignment of trajectories to subpopulations. We employ the theory to analyze experimental tracking data that cannot be explained with a single diffusion coefficient. We test how well a dataset conforms to the assumptions of a diffusion model and determine the optimal number of subpopulations with the help of a quality factor of known analytical distribution. To facilitate use by practitioners, we provide a fast open-source implementation of the theory for the efficient analysis of multiple trajectories in arbitrary dimensions simultaneously.

CRISPR/Cas12a-mediated labeling of MET receptor enables quantitative single-molecule imaging of endogenous protein organization and dynamics

Single-molecule localization microscopy (SMLM) reports on protein organization in cells with near-molecular resolution and in combination with stoichiometric labeling enables protein counting. Fluorescent proteins allow stoichiometric labeling of cellular proteins; however, most methods either lead to overexpression or are complex and time demanding. We introduce CRISPR/Cas12a for simple and efficient tagging of endogenous proteins with a photoactivatable protein for quantitative SMLM and single-particle tracking. We constructed a HEK293T cell line with the receptor tyrosine kinase MET tagged with mEos4b and demonstrate full functionality. We determine the oligomeric state of MET with quantitative SMLM and find a reorganization from monomeric to dimeric MET upon ligand stimulation. In addition, we measured the mobility of single MET receptors in vivo in resting and ligand-treated cells. The combination of CRISPR/Cas12a-assisted endogenous protein labeling and super-resolution microscopy represents a powerful tool for cell biological research with molecular resolution.

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CRISPR/Cas12a enables endogenous protein labeling for super-resolution microscopy

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HEK293T cells were generated with MET endogenously labeled with mEos4b

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Quantitative PALM microscopy reports efficient dimerization of MET receptor

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Single-particle tracking shows increased MET immobilization upon ligand treatment

Aptamers with Tunable Affinity Enable Single-Molecule Tracking and Localization of Membrane Receptors on Living Cancer Cells

Tumor cell-surface markers are usually overexpressed or mutated protein receptors for which spatiotemporal regulation differs between and within cancers. Single-molecule fluorescence imaging can profile individual markers in different cellular contexts with molecular precision. However, standard single-molecule imaging methods based on overexpressed genetically encoded tags or cumbersome probes can significantly alter the native state of receptors. We introduce a live-cell points accumulation for imaging in nanoscale topography (PAINT) method that exploits aptamers as minimally invasive affinity probes. Localization and tracking of individual receptors are based on stochastic and transient binding between aptamers and their targets. We demonstrated single-molecule imaging of a model tumor marker (EGFR) on a panel of living cancer cells. Affinity to EGFR was finely tuned by rational engineering of aptamer sequences to define receptor motion and/or native receptor density.

Single-Molecule Super-Resolution Microscopy Reveals Heteromeric Complexes of MET and EGFR upon Ligand Activation

Receptor tyrosine kinases (RTKs) orchestrate cell motility and differentiation. Deregulated RTKs may promote cancer and are prime targets for specific inhibitors. Increasing evidence indicates that resistance to inhibitor treatment involves receptor cross-interactions circumventing inhibition of one RTK by activating alternative signaling pathways. Here, we used single-molecule super-resolution microscopy to simultaneously visualize single MET and epidermal growth factor receptor (EGFR) clusters in two cancer cell lines, HeLa and BT-20, in fixed and living cells. We found heteromeric receptor clusters of EGFR and MET in both cell types, promoted by ligand activation. Single-protein tracking experiments in living cells revealed that both MET and EGFR respond to their cognate as well as non-cognate ligands by slower diffusion. In summary, for the first time, we present static as well as dynamic evidence of the presence of heteromeric clusters of MET and EGFR on the cell membrane that correlates with the relative surface expression levels of the two receptors.

Competitive Binding Study Revealing the Influence of Fluorophore Labels on Biomolecular Interactions

Fluorescence methods are important tools in modern biology. Direct labeling of biomolecules with a fluorophore might, however, change interaction surfaces. Here, we introduce a competitive binding assay in combination with fluorescence correlation spectroscopy that reports binding affinities of both labeled and unlabeled biomolecules to their binding target. We investigated how fluorophore labels at different positions of a DNA oligonucleotide affect hybridization to a complementary oligonucleotide and found dissociation constants varying within 2 orders of magnitude. We next demonstrated that placing a fluorophore label at position Leu280 in the protein ligand internalin B does not alter the binding affinity to the MET receptor tyrosine kinase, compared to unlabeled internalin B. Our approach is simple to implement and can be applied to investigate the influence of fluorophore labels in a large variety of biomolecular interactions.

SPT and Imaging FCS Provide Complementary Information on the Dynamics of Plasma Membrane Molecules

The dynamics of biomolecules in the plasma membrane is of fundamental importance to understanding cellular processes. Cellular signaling often starts with extracellular ligand binding to a membrane receptor, which then transduces an intracellular signal. Ligand binding and receptor-complex activation often involve a complex rearrangement of proteins in the membrane, which results in changes in diffusion properties. Two widely used methods to characterize biomolecular diffusion are single-particle tracking (SPT) and imaging total internal reflection fluorescence correlation spectroscopy (ITIR-FCS). Here, we compare the results of recovered diffusion coefficients and mean-square displacements of the two methods by simulations of free, domain-confined, or meshwork diffusion. We introduce, to our knowledge, a new method for the determination of confinement radii from ITIR-FCS data. We further establish and demonstrate simultaneous SPT/ITIR-FCS for direct comparison within living cells. Finally, we compare the results obtained by SPT and ITIR-FCS for the receptor tyrosine kinase MET. Our results show that SPT and ITIR-FCS yield complementary information on diffusion properties of biomolecules in cell membranes.