System for Measuring Planar Lipid Bilayer Properties

We present a system for measuring planar lipid bilayer properties. The system is composed of a control unit, an output stage, an LCR meter, pumps for filling reservoirs, a bath with temperature regulation and a measurement chamber with four electrodes. The planar lipid bilayer is automatically formed using a folding method on apertures of different sizes. The automatization is assured by two syringes, which are clamped in actuators. Actuators are driven and controlled by a control unit via RS-232 communication. The temperature of the planar lipid bilayer can be regulated between 15 and 55 °C. The regulation is assured by insertion of the measurement chamber into the temperature-regulated bath. Different shapes of voltage- or current-clamp signals can be applied to the planar lipid bilayer. By measuring the response of the planar lipid bilayer to the applied signal, the capacitance and breakdown voltage of the planar lipid bilayer can be determined. The cutoff frequencies of the system output stage for voltage- and current-clamp methods are 11 and 17 kHz, respectively.     

Single Molecule Detection in Microstructures

Abstract

Identification and manipulation of molecules on the single molecule level is best done in microstructures. The capability of observing single dye molecules in microstructures is demonstrated. Single molecules of DNA (106 bp) labelled with the intercalating dye TO-PRO-1 could also be observed.     

Bridging the Gap between Single Molecule and Ensemble Methods for Measuring Lateral Dynamics in the Plasma Membrane

The lateral dynamics of proteins and lipids in the mammalian plasma membrane are heterogeneous likely reflecting both a complex molecular organization and interactions with other macromolecules that reside outside the plane of the membrane. Several methods are commonly used for characterizing the lateral dynamics of lipids and proteins. These experimental and data analysis methods differ in equipment requirements, labeling complexities, and further oftentimes give different results. It would therefore be very convenient to have a single method that is flexible in the choice of fluorescent label and labeling densities from single molecules to ensemble measurements, that can be performed on a conventional wide-field microscope, and that is suitable for fast and accurate analysis. In this work we show that k-space image correlation spectroscopy (kICS) analysis, a technique which was originally developed for analyzing lateral dynamics in samples that are labeled at high densities, can also be used for fast and accurate analysis of single molecule density data of lipids and proteins labeled with quantum dots (QDs). We have further used kICS to investigate the effect of the label size and by comparing the results for a biotinylated lipid labeled at high densities with Atto647N-strepatvidin (sAv) or sparse densities with sAv-QDs. In this latter case, we see that the recovered diffusion rate is two-fold greater for the same lipid and in the same cell-type when labeled with Atto647N-sAv as compared to sAv-QDs. This data demonstrates that kICS can be used for analysis of single molecule data and furthermore can bridge between samples with a labeling densities ranging from single molecule to ensemble level measurements.     

A Single Molecule Scaffold for the Maize Genome

About 85% of the maize genome consists of highly repetitive sequences that are interspersed by low-copy, gene-coding sequences. The maize community has dealt with this genomic complexity by the construction of an integrated genetic and physical map (iMap), but this resource alone was not sufficient for ensuring the quality of the current sequence build. For this purpose, we constructed a genome-wide, high-resolution optical map of the maize inbred line B73 genome containing >91,000 restriction sites (averaging 1 site/∼23 kb) accrued from mapping genomic DNA molecules. Our optical map comprises 66 contigs, averaging 31.88 Mb in size and spanning 91.5% (2,103.93 Mb/∼2,300 Mb) of the maize genome. A new algorithm was created that considered both optical map and unfinished BAC sequence data for placing 60/66 (2,032.42 Mb) optical map contigs onto the maize iMap. The alignment of optical maps against numerous data sources yielded comprehensive results that proved revealing and productive. For example, gaps were uncovered and characterized within the iMap, the FPC (fingerprinted contigs) map, and the chromosome-wide pseudomolecules. Such alignments also suggested amended placements of FPC contigs on the maize genetic map and proactively guided the assembly of chromosome-wide pseudomolecules, especially within complex genomic regions. Lastly, we think that the full integration of B73 optical maps with the maize iMap would greatly facilitate maize sequence finishing efforts that would make it a valuable reference for comparative studies among cereals, or other maize inbred lines and cultivars.     

A Theoretical Justification for Single Molecule Peptide Sequencing

The proteomes of cells, tissues, and organisms reflect active cellular processes and change continuously in response to intracellular and extracellular cues. Deep, quantitative profiling of the proteome, especially if combined with mRNA and metabolite measurements, should provide an unprecedented view of cell state, better revealing functions and interactions of cell components. Molecular diagnostics and biomarker discovery should benefit particularly from the accurate quantification of proteomes, since complex diseases like cancer change protein abundances and modifications. Currently, shotgun mass spectrometry is the primary technology for high-throughput protein identification and quantification; while powerful, it lacks high sensitivity and coverage. We draw parallels with next-generation DNA sequencing and propose a strategy, termed fluorosequencing, for sequencing peptides in a complex protein sample at the level of single molecules. In the proposed approach, millions of individual fluorescently labeled peptides are visualized in parallel, monitoring changing patterns of fluorescence intensity as N-terminal amino acids are sequentially removed, and using the resulting fluorescence signatures (fluorosequences) to uniquely identify individual peptides. We introduce a theoretical foundation for fluorosequencing and, by using Monte Carlo computer simulations, we explore its feasibility, anticipate the most likely experimental errors, quantify their potential impact, and discuss the broad potential utility offered by a high-throughput peptide sequencing technology.     

Light Sheet Microscopy for Single Molecule Tracking in Living Tissue

Single molecule observation in cells and tissue allows the analysis of physiological processes with molecular detail, but it still represents a major methodological challenge. Here we introduce a microscopic technique that combines light sheet optical sectioning microscopy and ultra sensitive high-speed imaging. By this approach it is possible to observe single fluorescent biomolecules in solution, living cells and even tissue with an unprecedented speed and signal-to-noise ratio deep within the sample. Thereby we could directly observe and track small and large tracer molecules in aqueous solution. Furthermore, we demonstrated the feasibility to visualize the dynamics of single tracer molecules and native messenger ribonucleoprotein particles (mRNPs) in salivary gland cell nuclei of Chironomus tentans larvae up to 200 µm within the specimen with an excellent signal quality. Thus single molecule light sheet based fluorescence microscopy allows analyzing molecular diffusion and interactions in complex biological systems.     

Automated System for Single Molecule Fluorescence Measurements of Surface-immobilized Biomolecules

Fluorescence Resonance Energy Transfer (FRET) microscopy has been widely used to study the structure and dynamics of molecules of biological interest, such as nucleic acids and proteins. Single molecule FRET (sm-FRET) measurements on immobilized molecules permit long observations of the system -effectively until both dyes photobleach- resulting in time-traces that report on biomolecular dynamics with a broad range of timescales from milliseconds to minutes. To facilitate the acquisition of large number of traces for statistical analyses, the process must be automated and the sample environment should be tightly controlled over the entire measurement time (~12 hours). This is accomplished using an automated scanning confocal microscope that allows the interrogation of thousands of single molecules overnight, and a microfluidic cell that permits the controlled exchange of buffer, with restricted oxygen content and maintains a constant temperature throughout the entire measuring period. Here we show how to assemble the microfluidic device and how to activate its surface for DNA immobilization. Then we explain how to prepare a buffer to maximize the photostability and lifetime of the fluorophores. Finally, we show the steps involved in preparing the setup for the automated acquisition of time-resolved single molecule FRET traces of DNA molecules.     

Sensitivity Analysis of Gold Nanorod Biosensors for Single Molecule Detection

Single protein molecule detection is important for investigating molecular behavior and diagnosing diseases at an early stage. Gold nanorod (GNR) biosensors have shown promise for label-free detection of single protein molecules. However, for widespread applications of GNR biosensors with high sensitivity, detail studies are needed to understand the effects of the sensing environment and the molecular binding dynamics on the sensitivity. In this work, a comprehensive theoretical analysis with variable substrate, buffer, ligand, and binding position of the target molecules shows that GNR biosensors are highly sensitive for single molecule detection of biological samples including critical pathogens such as cancer marker thyroglobulin and human immunodeficiency virus (HIV) marker glycoprotein. We also propose and show that a GNR biosensor with a dielectric cladding layer on the body increases the sensitivity by orders of magnitude compared to other state-of-the-art biosensors.

     

Lucky Imaging: Improved Localization Accuracy for Single Molecule Imaging

We apply the astronomical data-analysis technique, Lucky imaging, to improve resolution in single molecule fluorescence microscopy. We show that by selectively discarding data points from individual single-molecule trajectories, imaging resolution can be improved by a factor of 1.6 for individual fluorophores and up to 5.6 for more complex images. The method is illustrated using images of fluorescent dye molecules and quantum dots, and the in vivo imaging of fluorescently labeled linker for activation of T cells.     

Using Amino-Labeled Nucleotide Probes for Simultaneous Single Molecule RNA-DNA FISH

Using amino-labeled oligonucleotide probes, we established a simple, robust and low-noise method for simultaneous detection of RNA and DNA by fluorescence in situ hybridization, a highly useful tool to study the large pool of long non-coding RNAs being identified in the current research. With probes either chemically or biologically synthesized, we demonstrate that the method can be applied to study a wide range of RNA and DNA targets at the single-cell and single-molecule level in cellular contexts.     

Statistical Assessment of Change Point Detectors for Single Molecule Kinetic Analysis

Change point detectors (CPDs) are used to segment recordings of single molecules for the purpose of kinetic analysis. The assessment of the accuracy of CPD algorithms has usually been based on testing them with simulated data. However, there have not been methods to assess the output of CPDs from real data independent of simulation. Here we present one method to do this based on the assumption that the elementary kinetic unit is a stationary period (SP) with a normal distribution of samples, separated from other SPs by change points (CPs). Statistical metrics of normality can then be used to assess SPs detected by a CPD algorithm (detected SPs, DSPs). Two statistics in particular were found to be useful, the z-transformed skew (S _Z) and z-transformed kurtosis (K _Z). K _Z(S _Z) plots of DSP from noise, simulated data and single ion channel recordings showed that DSPs with false negative CP could be distinguished. Also they showed that filtering had a significant effect on the normality of data and so filtering should be taken into account when calculating statistics. This method should be useful for analyzing single molecule recordings where there is no simple model for the data.     

荧光单分子检测技术在生命科学中的应用

荧光单分子检测技术是用荧光标记来显示和追踪单个分子的构象变化、动力学,单分子之间的相互作用以及单分子操纵的研究。过去对于生命科学分子机制的研究,都是对分子群体进行研究,然后平均化来进行单分子估测。因此,单个分子的动态性和独立性也被平均化掉而无法表现出来。荧光单分子检测技术真正实现了对单个分子的实时观测,将过去被平均化并隐藏在群体测量中不能获得的信息显示出来。近几年来,荧光单分子检测技术的飞速发展,为生命科学的发展,开辟了全新的研究领域。现就荧光单分子检测技术在研究动力蛋白、DNA转录、酶反应、蛋白质动态性和细胞信号转导方面的应用进展作一综述。     

Classification of Dynamical Diffusion States in Single Molecule Tracking Microscopy

Single molecule tracking of membrane proteins by fluorescence microscopy is a promising method to investigate dynamic processes in live cells. Translating the trajectories of proteins to biological implications, such as protein interactions, requires the classification of protein motion within the trajectories. Spatial information of protein motion may reveal where the protein interacts with cellular structures, because binding of proteins to such structures often alters their diffusion speed. For dynamic diffusion systems, we provide an analytical framework to determine in which diffusion state a molecule is residing during the course of its trajectory. We compare different methods for the quantification of motion to utilize this framework for the classification of two diffusion states (two populations with different diffusion speed). We found that a gyration quantification method and a Bayesian statistics-based method are the most accurate in diffusion-state classification for realistic experimentally obtained datasets, of which the gyration method is much less computationally demanding. After classification of the diffusion, the lifetime of the states can be determined, and images of the diffusion states can be reconstructed at high resolution. Simulations validate these applications. We apply the classification and its applications to experimental data to demonstrate the potential of this approach to obtain further insights into the dynamics of cell membrane proteins.     

Classification of Dynamical Diffusion States in Single Molecule Tracking Microscopy

Single molecule tracking of membrane proteins by fluorescence microscopy is a promising method to investigate dynamic processes in live cells. Translating the trajectories of proteins to biological implications, such as protein interactions, requires the classification of protein motion within the trajectories. Spatial information of protein motion may reveal where the protein interacts with cellular structures, because binding of proteins to such structures often alters their diffusion speed. For dynamic diffusion systems, we provide an analytical framework to determine in which diffusion state a molecule is residing during the course of its trajectory. We compare different methods for the quantification of motion to utilize this framework for the classification of two diffusion states (two populations with different diffusion speed). We found that a gyration quantification method and a Bayesian statistics-based method are the most accurate in diffusion-state classification for realistic experimentally obtained datasets, of which the gyration method is much less computationally demanding. After classification of the diffusion, the lifetime of the states can be determined, and images of the diffusion states can be reconstructed at high resolution. Simulations validate these applications. We apply the classification and its applications to experimental data to demonstrate the potential of this approach to obtain further insights into the dynamics of cell membrane proteins.     

Gramicidin-based Fluorescence Assay; for Determining Small Molecules Potential for Modifying Lipid Bilayer Properties

Many drugs and other small molecules used to modulate biological function are amphiphiles that adsorb at the bilayer/solution interface and thereby alter lipid bilayer properties. This is important because membrane proteins are energetically coupled to their host bilayer by hydrophobic interactions. Changes in bilayer properties thus alter membrane protein function, which provides an indirect way for amphiphiles to modulate protein function and a possible mechanism for "off-target" drug effects. We have previously developed an electrophysiological assay for detecting changes in lipid bilayer properties using linear gramicidin channels as probes ^3,12. Gramicidin channels are mini-proteins formed by the transbilayer dimerization of two non-conducting subunits. They are sensitive to changes in their membrane environment, which makes them powerful probes for monitoring changes in lipid bilayer properties as sensed by bilayer spanning proteins. We now demonstrate a fluorescence assay for detecting changes in bilayer properties using the same channels as probes. The assay is based on measuring the time-course of fluorescence quenching from fluorophore-loaded large unilamellar vesicles due to the entry of a quencher through the gramicidin channels. We use the fluorescence indicator/quencher pair 8-aminonaphthalene-1,3,6-trisulfonate (ANTS)/Tl⁺ that has been successfully used in other fluorescence quenching assays ^5,13. Tl⁺ permeates the lipid bilayer slowly ⁸ but passes readily through conducting gramicidin channels ^1,14. The method is scalable and suitable for both mechanistic studies and high-throughput screening of small molecules for bilayer-perturbing, and potential "off-target", effects. We find that results using this method are in good agreement with previous electrophysiological results ¹².Download video file.^{(69M, mov)}     

Controlling and Measuring Local Composition and Properties in Lipid Bilayer Membranes

Local composition, structure, morphology, and phase are interrelated in lipid bilayer membranes. This gives us the opportunity to control one or more of these properties by manipulating others. We investigate theserelationships with combinations of simultaneous two-color widefield fluorescence imaging, three-dimensional rendering of vesicle domains, andmanipulation of the vesicle morphology via optical trapping and micropipetteaspiration. We describe methods to modulate, to measure, and to probe thelocal structure of model membranes through control of membrane curvature inliposomes.     

Parameter Estimation Methods for Single Neuron Models

With the advancement in computer technology, it has become possible to fit complex models to neuronal data. In this work, we test how two methods can estimate parameters of simple neuron models (passive soma) to more complex ones (neuron with one dendritic cylinder and two active conductances). The first method uses classical voltage traces resulting from current pulses injection (time domain), while the second uses measures of the neuron's response to sinusoidal stimuli (frequency domain). Both methods estimate correctly the parameters in all cases studied. However, the time-domain method is slower and more prone to estimation errors in the cable parameters than the frequency-domain method. Because with noisy data the goodness of fit does not distinguish between different solutions, we suggest that running the estimation procedure a large number of times might help find a good solution and can provide information about the interactions between parameters. Also, because the formulation used for the model's response in the frequency domain is analytical, one can derive a local sensitivity analysis for each parameter. This analysis indicates how well a parameter is likely to be estimated and helps choose an optimal stimulation protocol. Finally, the tests suggest a strategy for fitting single-cell models using the two methods examined.     

Accounting for Limited Detection Efficiency and Localization Precision in Cluster Analysis in Single Molecule Localization Microscopy

Single Molecule Localization Microscopy techniques like PhotoActivated Localization Microscopy, with their sub-diffraction limit spatial resolution, have been popularly used to characterize the spatial organization of membrane proteins, by means of quantitative cluster analysis. However, such quantitative studies remain challenged by the techniques’ inherent sources of errors such as a limited detection efficiency of less than 60%, due to incomplete photo-conversion, and a limited localization precision in the range of 10 – 30nm, varying across the detected molecules, mainly depending on the number of photons collected from each. We provide analytical methods to estimate the effect of these errors in cluster analysis and to correct for them. These methods, based on the Ripley’s L(r) – r or Pair Correlation Function popularly used by the community, can facilitate potentially breakthrough results in quantitative biology by providing a more accurate and precise quantification of protein spatial organization.     

Single Molecule Imaging Reveals Differences in Microtubule Track Selection Between Kinesin Motors

Cells generate diverse microtubule populations by polymerization of a common α/β-tubulin building block. How microtubule associated proteins translate microtubule heterogeneity into specific cellular functions is not clear. We evaluated the ability of kinesin motors involved in vesicle transport to read microtubule heterogeneity by using single molecule imaging in live cells. We show that individual Kinesin-1 motors move preferentially on a subset of microtubules in COS cells, identified as the stable microtubules marked by post-translational modifications. In contrast, individual Kinesin-2 (KIF17) and Kinesin-3 (KIF1A) motors do not select subsets of microtubules. Surprisingly, KIF17 and KIF1A motors that overtake the plus ends of growing microtubules do not fall off but rather track with the growing tip. Selection of microtubule tracks restricts Kinesin-1 transport of VSVG vesicles to stable microtubules in COS cells whereas KIF17 transport of Kv1.5 vesicles is not restricted to specific microtubules in HL-1 myocytes. These results indicate that kinesin families can be distinguished by their ability to recognize microtubule heterogeneity. Furthermore, this property enables kinesin motors to segregate membrane trafficking events between stable and dynamic microtubule populations.