Phosphorylation alters the mechanical stiffness of a model fragment of the dystrophin homologue utrophin.

Duchenne muscular dystrophy is a lethal muscle wasting disease caused by the absence of the protein dystrophin. Utrophin is a dystrophin homologue currently under investigation as a protein replacement therapy for Duchenne muscular dystrophy. Dystrophin is hypothesized to function as a molecular shock absorber that mechanically stabilizes the sarcolemma. While utrophin is homologous with dystrophin from a molecular and biochemical perspective, we have recently shown that full-length utrophin expressed in eukaryotic cells is stiffer than what has been reported for dystrophin fragments expressed in bacteria. In this study, we show that differences in expression system impact the mechanical stiffness of a model utrophin fragment encoding the N terminus through spectrin repeat 3 (UtrN-R3). We also demonstrate that UtrN-R3 expressed in eukaryotic cells was phosphorylated while bacterial UtrN-R3 was not detectably phosphorylated. Using atomic force microscopy, we show that phosphorylated UtrN-R3 exhibited significantly higher unfolding forces compared to unphosphorylated UtrN-R3 without altering its actin-binding activity. Consistent with the effect of phosphorylation on mechanical stiffness, mutating the phosphorylated serine residues on insect eukaryotic protein to alanine decreased its stiffness to levels not different from unphosphorylated bacterial protein. Taken together, our data suggest that the mechanical properties of utrophin may be tuned by phosphorylation, with the potential to improve its efficacy as a protein replacement therapy for dystrophinopathies.

Multimodal regulation of myosin VI ensemble transport by cargo adaptor protein GIPC.

A range of cargo adaptor proteins are known to recruit cytoskeletal motors to distinct subcellular compartments. However, the structural impact of cargo recruitment on motor function is poorly understood. Here, we dissect the multimodal regulation of myosin VI activity through the cargo adaptor GAIP-interacting protein, C terminus (GIPC), whose overexpression with this motor in cancer enhances cell migration. Using a range of biophysical techniques, including motility assays, FRET-based conformational sensors, optical trapping, and DNA origami-based cargo scaffolds to probe the individual and ensemble properties of GIPC-myosin VI motility, we report that the GIPC myosin-interacting region (MIR) releases an autoinhibitory interaction within myosin VI. We show that the resulting conformational changes in the myosin lever arm, including the proximal tail domain, increase the flexibility of the adaptor-motor linkage, and that increased flexibility correlates with faster actomyosin association and dissociation rates. Taken together, the GIPC MIR-myosin VI interaction stimulates a twofold to threefold increase in ensemble cargo speed. Furthermore, the GIPC MIR-myosin VI ensembles yield similar cargo run lengths as forced processive myosin VI dimers. We conclude that the emergent behavior from these individual aspects of myosin regulation is the fast, processive, and smooth cargo transport on cellular actin networks. Our study delineates the multimodal regulation of myosin VI by the cargo adaptor GIPC, while highlighting linkage flexibility as a novel biophysical mechanism for modulating cellular cargo motility.

Stiffness of Cargo-Motor Linkage Tunes Myosin VI Motility and Response to Load.

We examine the effect of cargo-motor linkage stiffness on the mechanobiological properties of the molecular motor myosin VI. We use the programmability of DNA nanostructures to modulate cargo-motor linkage stiffness and combine it with high-precision optical trapping measurements to measure the effect of linkage stiffness on the motile properties of myosin VI. Our results reveal that a stiff cargo-motor linkage leads to shorter step sizes and load-induced anchoring of myosin VI, while a flexible linkage results in longer steps with frequent detachments from the actin filament under load. Our findings suggest a novel regulatory mechanism for tuning the dual cellular roles of the anchor and transporter ascribed to myosin VI.

Single Molecule Studies Enabled by Model-Based Controller Design.

Optical tweezers have enabled important insights into intracellular transport through the investigation of motor proteins, with their ability to manipulate particles at the microscale, affording femto newton force resolution. Its use to realize a constant force clamp has enabled vital insights into the behavior of motor proteins under different load conditions. However, the varying nature of disturbances and the effect of thermal noise pose key challenges to force regulation. Furthermore, often the main aim of many studies is to determine the motion of the motor and the statistics related to the motion, which can be at odds with the force regulation objective. In this article, we propose a mixed objective H 2 /H ∞ optimization framework using a model-based design, that achieves the dual goals of force regulation and real time motion estimation with quantifiable guarantees. Here, we minimize the H ∞ norm for the force regulation and error in step estimation while maintaining the H 2 norm of the noise on step estimate within user specified bounds. We demonstrate the efficacy of the framework through extensive simulations and an experimental implementation using an optical tweezer setup with live samples of the motor protein 'kinesin'; where regulation of forces below 1 piconewton with errors below 10% is obtained while simultaneously providing real time estimates of motor motion.

Analysis of Heat Dissipation and Reliability in Information Erasure: A Gaussian Mixture Approach.

This article analyzes the effect of imperfections in physically realizable memory. Motivated by the realization of a bit as a Brownian particle within a double well potential, we investigate the energetics of an erasure protocol under a Gaussian mixture model. We obtain sharp quantitative entropy bounds that not only give rigorous justification for heuristics utilized in prior works, but also provide a guide toward the minimal scale at which an erasure protocol can be performed. We also compare the results obtained with the mean escape times from double wells to ensure reliability of the memory. The article quantifies the effect of overlap of two Gaussians on the the loss of interpretability of the state of a one bit memory, the required heat dissipated in partially successful erasures and reliability of information stored in a memory bit.

Interrogating Emergent Transport Properties for Molecular Motor Ensembles: A Semi-analytical Approach.

Intracellular transport is an essential function in eucaryotic cells, facilitated by motor proteins-proteins converting chemical energy into kinetic energy. It is understood that motor proteins work in teams enabling unidirectional and bidirectional transport of intracellular cargo over long distances. Disruptions of the underlying transport mechanisms, often caused by mutations that alter single motor characteristics, are known to cause neurodegenerative diseases. For example, phosphorylation of kinesin motor domain at the serine residue is implicated in Huntington's disease, with a recent study of phosphorylated and phosphomimetic serine residues indicating lowered single motor stalling forces. In this article we report the effects of mutations of this nature on transport properties of cargo carried by multiple wild-type and mutant motors. Results indicate that mutants with altered stall forces might determine the average velocity and run-length even when they are outnumbered by wild type motors in the ensemble. It is shown that mutants gain a competitive advantage and lead to an increase in the expected run-length when the load on the cargo is in the vicinity of the mutant's stalling force or a multiple of its stalling force. A separate contribution of this article is the development of a semi-analytic method to analyze transport of cargo by multiple motors of multiple types. The technique determines transition rates between various relative configurations of motors carrying the cargo using the transition rates between various absolute configurations. This enables a computation of biologically relevant quantities like average velocity and run-length without resorting to Monte Carlo simulations. It can also be used to introduce alterations of various single motor parameters to model a mutation and to deduce effects of such alterations on the transport of a common cargo by multiple motors. Our method is easily implementable and we provide a software package for general use.

Toward quantitative estimation of material properties with dynamic mode atomic force microscopy: a comparative study.

In this article, we explore methods that enable estimation of material properties with the dynamic mode atomic force microscopy suitable for soft matter investigation. The article presents the viewpoint of casting the system, comprising of a flexure probe interacting with the sample, as an equivalent cantilever system and compares a steady-state analysis based method with a recursive estimation technique for determining the parameters of the equivalent cantilever system in real time. The steady-state analysis of the equivalent cantilever model, which has been implicitly assumed in studies on material property determination, is validated analytically and experimentally. We show that the steady-state based technique yields results that quantitatively agree with the recursive method in the domain of its validity. The steady-state technique is considerably simpler to implement, however, slower compared to the recursive technique. The parameters of the equivalent system are utilized to interpret storage and dissipative properties of the sample. Finally, the article identifies key pitfalls that need to be avoided toward the quantitative estimation of material properties.

Two operational modes of atomic force microscopy reveal similar mechanical properties for homologous regions of dystrophin and utrophin.

Duchenne muscular dystrophy (DMD) is a lethal muscle disease caused by the absence of the protein dystrophin. Dystrophin is hypothesized to work as a molecular shock absorber that limits myofiber membrane damage when undergoing reversible unfolding upon muscle stretching and contraction. Utrophin is a dystrophin homologue that is under investigation as a protein replacement therapy for DMD. However, it remains uncertain whether utrophin can mechanically substitute for dystrophin. Here, we compared the mechanical properties of homologous utrophin and dystrophin fragments encoding the N terminus through spectrin repeat 3 (UtrN-R3, DysN-R3) using two operational modes of atomic force microscopy (AFM), constant speed and constant force. Our comprehensive data, including the statistics of force magnitude at which the folded domains unfold in constant speed mode and the time of unfolding statistics in constant force mode, show consistent results. We recover parameters of the energy landscape of the domains and conducted Monte Carlo simulations which corroborate the conclusions drawn from experimental data. Our results confirm that UtrN-R3 expressed in bacteria exhibits significantly lower mechanical stiffness compared to insect UtrN-R3, while the mechanical stiffness of the homologous region of dystrophin (DysN-R3) is intermediate between bacterial and insect UtrN-R3, showing greater similarity to bacterial UtrN-R3.

Distinct mechanical properties in homologous spectrin-like repeats of utrophin.

Patients with Duchenne muscular dystrophy (DMD) lack the protein dystrophin, which is a critical molecular component of the dystrophin-glycoprotein complex (DGC). Dystrophin is hypothesized to function as a molecular shock absorber that mechanically stabilizes the sarcolemma of striated muscle through interaction with the cortical actin cytoskeleton via its N-terminal half and with the transmembrane protein ß-dystroglycan via its C-terminal region. Utrophin is a fetal homologue of dystrophin that can subserve many dystrophin functions and is therefore under active investigation as a dystrophin replacement therapy for DMD. Here, we report the first mechanical characterization of utrophin using atomic force microscopy (AFM). Our data indicate that the mechanical properties of spectrin-like repeats in utrophin are more in line with the PEVK and Ig-like repeats of titin rather than those reported for repeats in spectrin or dystrophin. Moreover, we measured markedly different unfolding characteristics for spectrin repeats within the N-terminal actin-binding half of utrophin compared to those in the C-terminal dystroglycan-binding half, even though they exhibit identical thermal denaturation profiles. Our results demonstrate dramatic differences in the mechanical properties of structurally homologous utrophin constructs and suggest that utrophin may function as a stiff elastic element in series with titin at the myotendinous junction.

Note: Design of FPGA based system identification module with application to atomic force microscopy.

The science of system identification is widely utilized in modeling input-output relationships of diverse systems. In this article, we report field programmable gate array (FPGA) based implementation of a real-time system identification algorithm which employs forgetting factors and bias compensation techniques. The FPGA module is employed to estimate the mechanical properties of surfaces of materials at the nano-scale with an atomic force microscope (AFM). The FPGA module is user friendly which can be interfaced with commercially available AFMs. Extensive simulation and experimental results validate the design.

Memory erasure using time-multiplexed potentials.

We study the thermodynamics of a Brownian particle under the influence of a time-multiplexed harmonic potential of finite width. The memory storage mechanism and the erasure protocol based on time-multiplexed potentials are utilized to experimentally realize erasure with work performed close to Landauer's bound. We quantify the work performed on the system with respect to the duty ratio of time multiplexing, which also provides a handle for approaching reversible erasures. A Langevin dynamics based simulation model is developed for the proposed memory bit and the erasure protocol, which guides the experimental realization. The study also provides insight into transport on the microscale.

An exact approach for studying cargo transport by an ensemble of molecular motors.

BACKGROUND: Intracellular transport is crucial for many cellular processes where a large fraction of the cargo is transferred by motor-proteins over a network of microtubules. Malfunctions in the transport mechanism underlie a number of medical maladies.Existing methods for studying how motor-proteins coordinate the transfer of a shared cargo over a microtubule are either analytical or are based on Monte-Carlo simulations. Approaches that yield analytical results, while providing unique insights into transport mechanism, make simplifying assumptions, where a detailed characterization of important transport modalities is difficult to reach. On the other hand, Monte-Carlo based simulations can incorporate detailed characteristics of the transport mechanism; however, the quality of the results depend on the number and quality of simulation runs used in arriving at results. Here, for example, it is difficult to simulate and study rare-events that can trigger abnormalities in transport. RESULTS: In this article, a semi-analytical methodology that determines the probability distribution function of motor-protein behavior in an exact manner is developed. The method utilizes a finite-dimensional projection of the underlying infinite-dimensional Markov model, which retains the Markov property, and enables the detailed and exact determination of motor configurations, from which meaningful inferences on transport characteristics of the original model can be derived. CONCLUSIONS: Under this novel probabilistic approach new insights about the mechanisms of action of these proteins are found, suggesting hypothesis about their behavior and driving the design and realization of new experiments.The advantages provided in accuracy and efficiency make it possible to detect rare events in the motor protein dynamics, that could otherwise pass undetected using standard simulation methods. In this respect, the model has allowed to provide a possible explanation for possible mechanisms under which motor proteins could coordinate their motion.

Detection of Steps in Single Molecule Data.

Over the past few decades, single molecule investigations employing optical tweezers, AFM and TIRF microscopy have revealed that molecular behaviors are typically characterized by discrete steps or events that follow changes in protein conformation. These events, that manifest as steps or jumps, are short-lived transitions between otherwise more stable molecular states. A major limiting factor in determining the size and timing of the steps is the noise introduced by the measurement system. To address this impediment to the analysis of single molecule behaviors, step detection algorithms incorporate large records of data and provide objective analysis. However, existing algorithms are mostly based on heuristics that are not reliable and lack objectivity. Most of these step detection methods require the user to supply parameters that inform the search for steps. They work well, only when the signal to noise ratio (SNR) is high and stepping speed is low. In this report, we have developed a novel step detection method that performs an objective analysis on the data without input parameters, and based only on the noise statistics. The noise levels and characteristics can be estimated from the data providing reliable results for much smaller SNR and higher stepping speeds. An iterative learning process drives the optimization of step-size distributions for data that has unimodal step-size distribution, and produces extremely low false positive outcomes and high accuracy in finding true steps. Our novel methodology, also uniquely incorporates compensation for the smoothing affects of probe dynamics. A mechanical measurement probe typically takes a finite time to respond to step changes, and when steps occur faster than the probe response time, the sharp step transitions are smoothed out and can obscure the step events. To address probe dynamics we accept a model for the dynamic behavior of the probe and invert it to reveal the steps. No other existing method addresses the impact of probe dynamics on step detection. Importantly, we have also developed a comprehensive set of tools to evaluate various existing step detection techniques. We quantify the performance and limitations of various step detection methods using novel evaluation scales. We show that under these scales, our method provides much better overall performance. The method is validated on different simulated test cases, as well as experimental data.

Robust control approach to force estimation in a constant position optical tweezers.

Feedback enhanced optical tweezers with position regulation capability enable detection and estimation of forces in the pico-Newton regime. In this article we delineate the fundamental limitations and challenges of existing approaches for regulating position and force estimation in an optical tweezer. A modern control systems approach is shown to improve the bandwidth of force estimation by three to four times which is corroborated experimentally.

Real-time nonlinear correction of back-focal-plane detection in optical tweezers.

Photodiode based detection of laser trapped beads using forward scattered light is a frequently employed technique for position measurement. There is a nonlinear relationship between photodiode outputs and bead position but for small displacements linear approximation holds well. Traditionally, the nonlinearity is compensated by normalizing the photodiode's position signal with the intensity signal and then using a polynomial fit in the range where voltage to position mapping is one to one. In this article, this range is extended by using the intensity signal as an independent input along with the two position signals. A map from the input signals to the actual position values is obtained. This mapping is one-to-one for a larger range that results in an increased detection range. An artificial neural network that facilitates implementation is employed for this purpose. This scheme is implemented on a Field Programmable Gate Array based data acquisition and control hardware with closed loop bandwidth of 50 kHz. Detection of the order of 350 nm from the center of detection laser is demonstrated for a 500 nm diameter bead compared to 180 nm achieved by a polynomial fit.

Immobilization method of yeast cells for intermittent contact mode imaging using the atomic force microscope.

The atomic force microscope (AFM) is widely used for studying the surface morphology and growth of live cells. There are relatively fewer reports on the AFM imaging of yeast cells [1] (Kasas and Ikai, 1995), [2] (Gad and Ikai, 1995). Yeasts have thick and mechanically strong cell walls and are therefore difficult to attach to a solid substrate. In this report, a new immobilization technique for the height mode imaging of living yeast cells in solid media using AFM is presented. The proposed technique allows the cell surface to be almost completely exposed to the environment and studied using AFM. Apart from the new immobilization protocol, for the first time, height mode imaging of live yeast cell surface in intermittent contact mode is presented in this report. Stable and reproducible imaging over a 10-h time span is observed. A significant improvement in operational stability will facilitate the investigation of growth patterns and surface patterns of yeast cells.

Real time reduction of probe-loss using switching gain controller for high speed atomic force microscopy.

In this article, a switching gain proportional-integral-differential controller is used to reduce probe-loss affected regions in an image, obtained during tapping mode operation. Switching signal is derived from the "reliability index" signal, which demarcates regions where the tip has lost contact with the sample (probe-loss), within couple of cantilever oscillation cycles, thereby facilitating use of higher than optimal controller gain without deteriorating on-sample performance. Efficacy of the approach is demonstrated by imaging calibration sample at tip velocity close to 240 microm/s and plasmid DNA at tip velocity of 60 microm/s indicating significant reduction of probe-loss areas and recovery of lost sample features.