The First Step of Amyloidogenic Aggregation

The structural and dynamic characterization of the on-pathway intermediates involved in the mechanism of amyloid fibril formation is one of the major remaining biomedical challenges of our time. In addition to mature fibrils, various oligomeric structures are implicated in both the rate-limiting step of the nucleation process and the neuronal toxicity of amyloid deposition. Single-molecule fluorescence spectroscopy (SMFS) is an excellent tool for extracting most of the relevant information on these molecular systems, especially advanced multiparameter approaches, such as pulsed interleaved excitation (PIE). In our investigations of an amyloidogenic SH3 domain of α-spectrin, we have found dynamic oligomerization, even prior to incubation. Our single-molecule PIE experiments revealed that these species are small, mostly dimeric, and exhibit a loose and dynamic molecular organization. Furthermore, these experiments have allowed us to obtain quantitative information regarding the oligomer stability. These pre-amyloidogenic oligomers may potentially serve as the first target for fibrillization-prevention strategies.

SOLVING ION CHANNEL KINETICS WITH THE QuB SOFTWARE

The ability to record the currents from single ion channels led to the need to extract the underlying kinetic model from such data. This inverse hidden Markov problem is difficult but led to the creation of a software suite called QuB utilizing likelihood optimization. This review presents the software. The software is open source and, in addition to solving kinetic models, has many generic database operations including report generation with publishable graphics, function fitting and scripting for new and repeated processing and AD/DA I/O. The core algorithms allow for constraints such as fixed rates or maintaining detailed balance in the model. All rate constants can be driven by a stimulus and the system can analyze nonstationary data. QuB also can analyze the kinetics of multichannel data where individual events cannot be discriminated, but the fitting algorithms utilize the signal variance as well as the mean to fit models. QuB can be applied to any data appropriately modeled with Markov kinetics and has been utilized to solve ion channels but also the movement of motor proteins, the sleep cycles in mice, and physics processes.

[Formula: see text]Special Issue Comment: This is a review about the software QuB that can extract a model from the trajectory. It is connected with the review about treatments when solving single molecules,60 and the reviews about enzymes.61,62

NEURONAL MULTIFUNCTIONAL ATPase

Here, we review the properties of a suggested mechanism for a neural ATPase complex based on our recent experimental findings. The mechanism represents a multifunctional ATPase: an enzyme that is a chloride pump and a GABA receptor. This enables new views on the ways Cl - channel transports anions and its regulation by the intra- and extracellular ions and molecules (in particular by glucose, ATP, [Formula: see text]). The hydrolytic activity of this GABA A-coupled ATPase provides the [Formula: see text] transport process the energy and determines a certain direction of ions flux across neuronal membrane. This can help with the research regarding several diseases such as epilepsy.

[Formula: see text]Special Issue Comment: This project is about a multifunctional ATPase complex. Experiments involving measuring & solving individual ATPases are related with the Special Issue about FRET experiments,1 about enzymes,2 and about treatments when solving single molecules.3,4 The model suggested here is simply tested with these experimental and mathematical methods.

INSIGHTS IN ENZYME FUNCTIONAL DYNAMICS AND ACTIVITY REGULATION BY SINGLE MOLECULE STUDIES

The advent of advanced single molecule measurements heralded the arrival of a wealth of dynamic information revolutionizing our understanding of protein dynamics and behavior in ways not deducible by conventional bulk assays. They offered the direct observation and quantification of the abundance and life time of multiple states and transient intermediates in the energy landscape that are typically averaged out in non-synchronized ensemble measurements, thus providing unprecedented insights into complex biological processes. Here we survey the current state of the art in single-molecule fluorescence microscopy methodology for studying the mechanism of enzymatic activity and the insights on protein functional dynamics. We will initially discuss the strategies employed to date, their limitations and possible ways to overcome them, and finally how single enzyme kinetics can advance our understanding on mechanisms underlying function and regulation of proteins.

[Formula: see text]Special Issue Comment: This review focuses on functional dynamics of individual enzymes and is related to the review on ion channels by Lu,44 the reviews on mathematical treatment of Flomenbom45 and Sach et al.,46 and review on FRET by Ruedas-Rama et al.41

EGF RECEPTOR DYNAMICS IN EGF-RESPONDING CELLS REVEALED BY FUNCTIONAL IMAGING DURING SINGLE PARTICLE TRACKING

The epidermal growth factor (EGF) receptor transduces the extracellular EGF signal into the cells. The distribution of these EGF receptors in the plasma membrane is heterogeneous and dynamic, which is proposed to be important for the regulation of cell signaling. The response of the cells to a physiological concentration of EGF is not homogeneous, which makes it difficult to analyze the dynamics related to the response. Here we developed a system to perform functional imaging during single particle tracking (SPT) analysis. This system made it possible to observe the cytosolic Ca 2+ concentration to monitor the cell response while tracking individual EGF molecules and found that about half of the cells responded to the stimulation with 1.6 nM EGF. In the responding cells, the EGF receptor showed 3 modes of movement: fast (the diffusion coefficient of 0.081 ± 0.009 μm2/sec, 29 ± 9%), slow (0.020 ± 0.005 μm2/sec, 22 ± 6%), and stationary (49 ± 13%). The diffusion coefficient of the fast mode movement in the responding cells was significantly larger than that in the nonresponding cells (0.069 ± 0.009 μm2/sec, p < 0.05). The diffusion coefficient of the fast mode movement is thought to reflect the monomer–dimer equilibrium of the EGF receptor. We assumed that the feedback regulation via the Ca 2+ signaling pathway slightly shifts the equilibrium from dimer to monomer in the responding cells.

[Formula: see text]Special Issue Comment: This research paper is about the diffusion of EGF receptors in the membrane. It is therefore related with various projects in this Special Issue: the reviews about FRET41 and enzymes,42 and the projects about solving single molecules trajectories.43

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