Yunze Yang

Label-free measuring and mapping of binding kinetics of membrane proteins in single living cells

Membrane proteins mediate a variety of cellular responses to extracellular signals. Although membrane proteins are studied intensively for their values as disease biomarkers and therapeutic targets, in situ investigation of the binding kinetics of membrane proteins with their ligands has been a challenge. Traditional approaches isolate membrane proteins and then study them ex situ, which does not reflect accurately their native structures and functions. We present a label-free plasmonic microscopy method to map the local binding kinetics of membrane proteins in their native environment. This analytical method can perform simultaneous plasmonic and fluorescence imaging, and thus make it possible to combine the strengths of both label-based and label-free techniques in one system. Using this method, we determined the distribution of membrane proteins on the surface of single cells and the local binding kinetic constants of different membrane proteins. Furthermore, we studied the polarization of the membrane proteins on the cell surface during chemotaxis.

Quantification of epidermal growth factor receptor expression level and binding kinetics on cell surfaces by surface plasmon resonance imaging.

Epidermal growth factor receptor (EGFR, also known as ErbB-1 or HER-1) is a membrane bound protein that has been associated with a variety of solid tumors and the control of cell survival, proliferation, and metabolism. Quantification of the EGFR expression level in cell membranes and the interaction kinetics with drugs are thus important for cancer diagnosis and treatment. Here we report mapping of the distribution and interaction kinetics of EGFR in their native environment with the surface plasmon resonance imaging (SPRi) technique. The monoclonal anti-EGFR antibody was used as a model drug in this study. The binding of the antibody to EGFR overexpressed A431 cells was monitored in real time, which was found to follow the first-order kinetics with an association rate constant (ka) and dissociation rate constant (kd) of (2.7 ± 0.6) × 10(5) M(-1) s(-1) and (1.4 ± 0.5) × 10(-4) s(-1), respectively. The dissociation constant (KD) was determined to be 0.53 ± 0.26 nM with up to seven-fold variation among different individual A431 cells. In addition, the averaged A431 cell surface EGFR density was found to be 636/μm(2) with an estimation of 5 × 10(5) EGFR per cell. Additional measurement also revealed that different EGFR positive cell lines (A431, HeLa, and A549) show receptor density dependent anti-EGFR binding kinetics. The results demonstrate that SPRi is a valuable tool for direct quantification of membrane protein expression level and ligand binding kinetics at single cell resolution. Our findings show that the local environment affects the drug-receptor interactions, and in situ measurement of membrane protein binding kinetics is important.

Antimicrobial susceptibility test with plasmonic imaging and tracking of single bacterial motions on nanometer scale

Antimicrobial susceptibility tests (ASTs) are important for confirming susceptibility to empirical antibiotics and detecting resistance in bacterial isolates. Currently, most ASTs performed in clinical microbiology laboratories are based on bacterial culturing, which take days to complete for slowly growing microorganisms. A faster AST will reduce morbidity and mortality rates and help healthcare providers administer narrow spectrum antibiotics at the earliest possible treatment stage. We report the development of a nonculture-based AST using a plasmonic imaging and tracking (PIT) technology. We track the motion of individual bacterial cells tethered to a surface with nanometer (nm) precision and correlate the phenotypic motion with bacterial metabolism and antibiotic action. We show that antibiotic action significantly slows down bacterial motion, which can be quantified for development of a rapid phenotypic-based AST.

Label-Free Tracking of Single Organelle Transportation in Cells with Nanometer Precision Using a Plasmonic Imaging Technique.

Imaging and tracking of nano- and micrometer-sized organelles in cells with nanometer precision is crucial for understanding cellular behaviors at the molecular scale. Because of the fast intracellular dynamic processes, the imaging and tracking method must also be fast. In addition, to ensure that the observed dynamics is relevant to the native functions, it is critical to keep the cells under their native states. Here, a plasmonics-based imaging technique is demonstrated for studying the dynamics of organelles in 3D with high localization precision (5 nm) and temporal (10 ms) resolution. The technique is label-free and can track subcellular structures in the native state of the cells. Using the technique, nanometer steps of organelle (e.g., mitochondria) transportation are observed along neurite microtubules in primary neurons, and the 3D structure of neurite microtubule bundles is reconstructed at the nanometer scale from the tracks of the moving organelles.

Measuring Binding Kinetics of Antibody-Conjugated Gold Nanoparticles with Intact Cells

Antibody-conjugated nanomaterials have attracted much attention because of their applications in nanomedicine and nanotheranostics, and amplification of detection signals. For many of these applications, the nanoconjugates must bind with a cell membrane receptor (antigen) specifically before entering the cells and reaching the final target, which is thus important but not well understood. Here, a plasmonic imaging study of the binding kinetics of antibody-conjugated gold nanoparticles with antigen-expressing cells is presented, and the results are compared with that of the nanoparticle-free antibody. It is found that the nanoconjugates can significantly affect the binding kinetics compared with free antibody molecules, depending on the density of the antibody conjugated on the nanoparticles, and expressing level of the antigen on the cell membrane. The results are analyzed in terms of a transition from monovalent binding model to a bivalent binding model when the conjugation density and expressing level increase. These findings help optimize the design of functional nanomaterials for drug delivery and correct interpretation of data obtained with nanoparticle signal amplification.

Plasmonic‐Based Electrochemical Impedance Imaging of Electrical Activities in Single Cells

Studying electrical activities in cells, such as action potential and its propagation in neurons, requires a sensitive and non-invasive analytical tool that can image local electrical signals with high spatial and temporal resolutions. Here we report a plasmonic-based electrochemical impedance imaging technique to study transient electrical activities in single cells. The technique is based on the conversion of the electrical signal into a plasmonic signal, which is imaged optically without labels. We demonstrate imaging of the fast initiation and propagation of action potential within single neurons, and validate the imaging technique with the traditional patch clamp technique. We anticipate that the plasmonic imaging technique will contribute to the study of electrical activities in various cellular processes.

Imaging Action Potential in Single Mammalian Neurons by Tracking the Accompanying Sub-Nanometer Mechanical Motion

Action potentials in neurons have been studied traditionally by intracellular electrophysiological recordings and more recently by the fluorescence detection methods. Here we describe a label-free optical imaging method that can measure mechanical motion in single cells with a sub-nanometer detection limit. Using the method, we have observed sub-nanometer mechanical motion accompanying the action potential in single mammalian neurons by averaging the repeated action potential spikes. The shape and width of the transient displacement are similar to those of the electrically recorded action potential, but the amplitude varies from neuron to neuron, and from one region of a neuron to another, ranging from 0.2-0.4 nm. The work indicates that action potentials may be studied noninvasively in single mammalian neurons by label-free imaging of the accompanying sub-nanometer mechanical motion.

Rapid Antibiotic Susceptibility Testing of Uropathogenic E. coli by Tracking Submicron Scale Motion of Single Bacterial Cells

To combat antibiotic resistance, a rapid antibiotic susceptibility testing (AST) technology that can identify resistant infections at disease onset is required. Current clinical AST technologies take 1-3 days, which is often too slow for accurate treatment. Here we demonstrate a rapid AST method by tracking sub-μm scale bacterial motion with an optical imaging and tracking technique. We apply the method to clinically relevant bacterial pathogens, Escherichia coli O157: H7 and uropathogenic E. coli (UPEC) loosely tethered to a glass surface. By analyzing dose-dependent sub-μm motion changes in a population of bacterial cells, we obtain the minimum bactericidal concentration within 2 h using human urine samples spiked with UPEC. We validate the AST method using the standard culture-based AST methods. In addition to population studies, the method allows single cell analysis, which can identify subpopulations of resistance strains within a sample.

Tracking fast cellular membrane dynamics with sub-nm accuracy in the normal direction

Cellular membranes are important biomaterials with highly dynamic structures. Membrane dynamics plays an important role in numerous cellular processes, but precise tracking it is challenging due to the lack of tools with a highly sensitive and fast detection capability. Here we demonstrate a broad bandwidth optical imaging technique to measure cellular membrane displacements in the normal direction at sub-nm level detection limits and 20 μs temporal resolution (1 Hz-50 kHz). This capability allows us to study the intrinsic cellular membrane dynamics over a broad temporal and spatial spectrum. We measured the nanometer-scale stochastic fluctuations of the plasma membrane of HEK-293 cells, and found them to be highly dependent on the cytoskeletal structure of the cells. By analyzing the fluctuations, we further determine the mechanical properties of the cellular membranes. We anticipate that the method will contribute to the understanding of the basic cellular processes, and applications, such as mechanical phenotyping of cells at the single-cell level.

Phenotypic Antimicrobial Susceptibility Testing with Deep Learning Video Microscopy

Timely determination of antimicrobial susceptibility for a bacterial infection enables precision prescription, shortens treatment time, and helps minimize the spread of antibiotic resistant infections. Current antimicrobial susceptibility testing (AST) methods often take several days and thus impede these clinical and health benefits. Here, we present an AST method by imaging freely moving bacterial cells in urine in real time and analyzing the videos with a deep learning algorithm. The deep learning algorithm determines if an antibiotic inhibits a bacterial cell by learning multiple phenotypic features of the cell without the need for defining and quantifying each feature. We apply the method to urinary tract infection, a common infection that affects millions of people, to determine the minimum inhibitory concentration of pathogens from human urine specimens spiked with lab strain E. coli (ATCC 43888) and an E. coli strain isolated from a clinical urine sample for different antibiotics within 30 min and validate the results with the gold standard broth macrodilution method. The deep learning video microscopy-based AST holds great potential to contribute to the solution of increasing drug-resistant infections.