High-throughput single-molecule analysis of DNA-protein interactions by tethered particle motion

Tethered particle motion (TPM) monitors the variations in the effective length of a single DNA molecule by tracking the Brownian motion of a bead tethered to a support by the DNA molecule. Providing information about DNA conformations in real time, this technique enables a refined characterization of DNA-protein interactions. To increase the output of this powerful but time-consuming single-molecule assay, we have developed a biochip for the simultaneous acquisition of data from more than 500 single DNA molecules. The controlled positioning of individual DNA molecules is achieved by self-assembly on nanoscale arrays fabricated through a standard microcontact printing method. We demonstrate the capacity of our biochip to study biological processes by applying our method to explore the enzymatic activity of the T7 bacteriophage exonuclease. Our single molecule observations shed new light on its behaviour that had only been examined in bulk assays previously and, more specifically, on its processivity.     

High-throughput single-molecule imaging system using nanofabricated trenches and fluorescent DNA-binding proteins

DNA curtain is a high-throughput system, integrating a lipid bilayer, fluorescence imaging, and microfluidics to probe protein–DNA interactions in real-time and has provided in-depth understanding of DNA metabolism. Especially, the microfluidic platform of a DNA curtain is highly suitable for a biochip. In the DNA curtain, DNA molecules are aligned along chromium nanobarriers, which are fabricated on a slide surface, and visualized using an intercalating dye, YOYO-1. Although the chromium barriers confer precise geometric alignment of DNA, reuse of the slides is limited by wear of the barriers during cleaning. YOYO-1 is rapidly photobleached and causes photocleavage of DNA under continuous laser illumination, restricting DNA observation to a brief time window. To address these challenges, we developed a new nanopatterned slide, upon which carved nanotrenches serve as diffusion barriers. The nanotrenches were robust under harsh cleaning conditions, facilitating the maintenance of surface cleanliness that is essential to slide reuse. We also stained DNA with a fluorescent protein with a DNA-binding motif, fluorescent protein–DNA binding peptide (FP–DBP). FP–DBP was slowly photobleached and did not cause DNA photocleavage. This new DNA curtain system enables a more stable and repeatable investigation of real-time protein–DNA interactions and will serve as a good platform for lab-on-a-chip.     

High-throughput analysis of peptide-binding modules

Modular protein interaction domains (PIDs) that recognize linear peptide motifs are found in hundreds of proteins within the human genome. Some PIDs such as SH2, 14-3-3, Chromo, and Bromo domains serve to recognize posttranslational modification (PTM) of amino acids (such as phosphorylation, acetylation, methylation, etc.) and translate these into discrete cellular responses. Other modules such as SH3 and PSD-95/Discs-large/ZO-1 (PDZ) domains recognize linear peptide epitopes and serve to organize protein complexes based on localization and regions of elevated concentration. In both cases, the ability to nucleate-specific signaling complexes is in large part dependent on the selectivity of a given protein module for its cognate peptide ligand. High-throughput (HTP) analysis of peptide-binding domains by peptide or protein arrays, phage display, mass spectrometry, or other HTP techniques provides new insight into the potential protein-protein interactions prescribed by individual or even whole families of modules. Systems level analyses have also promoted a deeper understanding of the underlying principles that govern selective protein-protein interactions and how selectivity evolves. Lastly, there is a growing appreciation for the limitations and potential pitfalls associated with HTP analysis of protein-peptide interactomes. This review will examine some of the common approaches utilized for large-scale studies of PIDs and suggest a set of standards for the analysis and validation of datasets from large-scale studies of peptide-binding modules. We will also highlight how data from large-scale studies of modular interaction domain families can provide insight into systems level properties such as the linguistics of selective interactions.     

High-throughput analysis of HGF-stimulated cell scattering

Historically, only relatively low-throughput or expensive methods have been available to measure cell migration. Hepatocyte growth factor (HGF) is a ligand for the tyrosine kinase receptor Met that, in addition to mediating proliferation and survival, increases cell motility and metastasis. The authors have developed a high-throughput imaging assay for measuring inhibition of HGF-induced scattering in human HPAF-II pancreatic adenocarcinoma cells. Following treatment with test compounds and HGF for 24 h, cells are labeled with a nuclear stain and imaged at 10x magnification. The proximity of neighboring nuclei is measured, and the distribution of internuclear distances across each field of view is used to calculate the fraction of scattered cells. This method of analysis can be extended to other cell types and signaling pathways and, compared with other membrane-based migration assays currently available, the assay is significantly lower in cost, is less labor intensive, and provides higher throughput.     

High-throughput analysis of concentration-dependent antibody self-association

Monoclonal antibodies are typically monomeric and nonviscous at low concentrations, yet they display highly variable associative and viscous behavior at elevated concentrations. Although measurements of antibody self-association are critical for understanding this complex behavior, traditional biophysical methods are not capable of characterizing such concentration-dependent self-association in a high-throughput manner. Here we describe a nanoparticle-based method, termed self-interaction nanoparticle spectroscopy, that is capable of rapidly measuring concentration-dependent self-interactions for three human monoclonal antibodies with unique solution behaviors. We demonstrate that gold nanoparticles conjugated with antibodies at low protein concentrations (<40 μg/mL) display self-association behavior (as measured by the interparticle distance-dependent plasmon wavelength) that is well correlated with static light-scattering measurements obtained at three orders of magnitude higher antibody concentrations. Using this methodology, we find that the antibodies display a complex pH-dependent self-association behavior that is strongly influenced by the solution ionic strength. Importantly, we find that a polyclonal human antibody is nonassociative for all solution conditions evaluated in this work, suggesting that antibody self-association is more specific than previously realized. We expect that our findings will guide rational manipulation of antibody phase behavior, and enable studies that elucidate sequence and structural determinants of antibody self-association.     

High-throughput human metabolism and toxicity analysis

Poor drug candidate safety profiles are often identified late in the drug development process, manifesting themselves in the preclinical and clinical phases and significantly contributing to the high cost and low yield of drug discovery. As a result, new tools are needed to accelerate the assessment of drug candidate toxicity and human metabolism earlier in the drug development process, from primary drug candidate screening to lead optimization. Although high-throughput screens exist for much of the discovery phase of drug development, translating such screening techniques into platforms that can accurately mimic the human in vivo response and predict the impact of drug candidates on human toxicology has proven difficult. Nevertheless, some success has been achieved in recent years, which may ultimately yield widespread acceptance in the pharmaceutical industry.     

High-throughput analysis of immunoglobulin G glycosylation

Introduction: Glycosylation of immunoglobulin G (IgG) is important for its effector functions and was shown to be related to age, sex and disease status of an individual. Adding glycomic information to genome-wide association studies (GWAS) and large clinical trials is enabling insight into the functional relevance of changes in glycosylation, as well as molecular mechanisms behind these changes. Large-scale studies require sensitive, robust and affordable high-throughput methodologies for glycosylation analysis, which are currently available in only a limited number of laboratories.

Areas covered: This review focuses on currently used high-throughput approaches for N-glycosylation analysis of IgG, as well as some recent advances in the areas of deglycosylation, trypsin digestion, labeling, purification, derivatization and automation of current workflows. Relevant literature was searched using the PubMed database.

Expert commentary: Development, optimization and validation of robust, affordable and simple high-throughput glycosylation analysis methods is essential for discovery and validation of diagnostic and prognostic glycan biomarkers. Although significant advances in glycosylation analysis have been made in recent years, currently used protocols will have to be further optimized to enable subsequent analysis of glycosylation on all levels with the limited initial sample and in the minimal amount of time, which is still a challenging task.     

A single-molecule assay for telomerase structure-function analysis

The activity of the telomerase ribonucleoprotein enzyme is essential for the maintenance of genome stability and normal cell development. Despite the biomedical importance of telomerase activity, detailed structural models for the enzyme remain to be established. Here we report a single-molecule assay for direct structural analysis of catalytically active telomerase enzymes. In this assay, oligonucleotide hybridization was used to probe the primer-extension activity of individual telomerase enzymes with single nucleotide sensitivity, allowing precise discrimination between inactive, active and processive enzyme binding events. FRET signals from enzyme molecules during the active and processive binding events were then used to determine the global organization of telomerase RNA within catalytically active holoenzymes. Using this assay, we have identified an active conformation of telomerase among a heterogeneous population of enzymes with distinct structures.     

High-throughput behavioral analysis in C. elegans

We designed a real-time computer vision system, the Multi-Worm Tracker (MWT), which can simultaneously quantify the behavior of dozens of Caenorhabditis elegans on a Petri plate at video rates. We examined three traditional behavioral paradigms using this system: spontaneous movement on food, where the behavior changes over tens of minutes; chemotaxis, where turning events must be detected accurately to determine strategy; and habituation of response to tap, where the response is stochastic and changes over time. In each case, manual analysis or automated single-worm tracking would be tedious and time-consuming, but the MWT system allowed rapid quantification of behavior with minimal human effort. Thus, this system will enable large-scale forward and reverse genetic screens for complex behaviors.     

High-throughput antibody microarrays for quantitative proteomic analysis

The antibody microarray is an intrinsically robust and quantitative system that delivers high-throughput and parallel measurements on particular sets of known proteins. It has become an important proteomics research tool, complementary to the conventional unbiased separation-based and mass spectrometry-based approaches. This review summarizes the technical aspects of production and the application for quantitative proteomic analysis with an emphasis on disease proteomics, especially the identification of biomarkers. Quality control, data analysis methods and the challenges for quantitative assays are also discussed.     

High-throughput antibody microarrays for quantitative proteomic analysis

The antibody microarray is an intrinsically robust and quantitative system that delivers high-throughput and parallel measurements on particular sets of known proteins. It has become an important proteomics research tool, complementary to the conventional unbiased separation-based and mass spectrometry-based approaches. This review summarizes the technical aspects of production and the application for quantitative proteomic analysis with an emphasis on disease proteomics, especially the identification of biomarkers. Quality control, data analysis methods and the challenges for quantitative assays are also discussed.     

High-throughput analysis of spatio-temporal dynamics in Dictyostelium

We demonstrate a time-lapse video approach that allows rapid examination of the spatio-temporal dynamics of Dictyostelium cell populations. Quantitative information was gathered by sampling life histories of more than 2,000 mutant clones from a large mutagenesis collection. Approximately 4% of the clonal lines showed a mutant phenotype at one stage. Many of these could be ordered by clustering into functional groups. The dataset allows one to search and retrieve movies on a gene-by-gene and phenotype-by-phenotype basis.     

Fluorescence-based analysis of enzymes at the single-molecule level

Enzymes, and proteins in general, consist of a dynamic ensemble of different conformations, which fluctuate around an average structure. Single-molecule experiments are a powerful tool to obtain information about these conformations and their contributions to the catalytic reaction. In contrast to classical ensemble measurements, which average over the whole population, singlemolecule experiments are able to detect conformational heterogeneities, to identify transient or rare conformations, to follow the time series of conformational changes and to reveal parallel reaction pathways. A number of single-molecule studies with enzymes have proven this potential showing that the activity of individual enzymes varies between different molecules and that the catalytic rate constants fluctuate over time. From a practical point of view this review focuses on fluorescence-based methods that have been used to study enzymes at the single-molecule level. Since the first proof-of-principle experiments a wide range of different methods have been developed over the last 10 years and the methodology now needs to be applied to answer questions of biological relevance, for example about conformational changes induced by allosteric effectors or mutations.     

Coordinate-based colocalization analysis of single-molecule localization microscopy data

Colocalization of differently labeled biomolecules is a valuable tool in fluorescence microscopy and can provide information on biomolecular interactions. With the advent of super-resolution microscopy, colocalization analysis is getting closer to molecular resolution, bridging the gap to other technologies such as fluorescence resonance energy transfer. Among these novel microscopic techniques, single-molecule localization-based super-resolution methods offer the advantage of providing single-molecule coordinates that, rather than intensity information, can be used for colocalization analysis. This requires adapting the existing mathematical algorithms for localization microscopy data. Here, we introduce an algorithm for coordinate-based colocalization analysis which is suited for single-molecule super-resolution data. In addition, we present an experimental configuration for simultaneous dual-color imaging together with a robust approach to correct for optical aberrations with an accuracy of a few nanometers. We demonstrate the potential of our approach for cellular structures and for two proteins binding actin filaments.     

On chip optofluidic low-pressure monitoring device

We present an on chip optofluidic surface deformable liquid Dove prism (LDP) based low-fluid flow pressure monitoring device. The unique design of the device in combination with liquid and soft solid enabled by the total internal reflection of light makes the sensor highly sensitive and compatible with the integration of a microfluidic and/or Lab-on-a-chip device. A layer-by-layer soft lithographic (LSL) and 3D printing technique are exploited to make the device. We have used Polydimethylsiloxane (PDMS) as the layer material and two variety of liquids (a) immersion oil (IO) and (b) di-iodomethane (DI) as refracting medium to construct the LDP sensor. Optical ray tracing simulation is performed to optimize the sensor. The pressure sensor shows sensitivity as high as ±28.5 mV per 50 Pa pressure with an error ± 2.5 mV and repeatability of ~99.56% at full scale. We have shown the applicability of the sensor by capturing and analyzing respiratory pressure signals of some human subjects at numerous conditions.     

High-throughput analysis of hexosamine using a colorimetric method

A 96-well plate method was developed for analysis of total hexosamine content in biological samples. Four hexosamine monomer derivatives—glucosamine hydrochloride, glucosamine sulfate, galactosamine hydrochloride, and mannosamine hydrochloride—were examined for the linearity of their spectra in the concentration range specified in the assay. The hexosamine concentration analysis range was linear from 0.1 to 1 mM. The quantification of hexosamines from chitin and chitosan upon acid hydrolysis was also tested. Accurate quantification of glucosamine content in chitin and chitosan with different molecular sizes and degrees of acetylation was demonstrated using the new method.     

High-throughput FTIR-based bioprocess analysis of recombinant cyprosin production

To increase the knowledge of the recombinant cyprosin production process in Saccharomyces cerevisiae cultures, it is relevant to implement efficient bioprocess monitoring techniques. The present work focuses on the implementation of a mid-infrared (MIR) spectroscopy-based tool for monitoring the recombinant culture in a rapid, economic, and high-throughput (using a microplate system) mode. Multivariate data analysis on the MIR spectra of culture samples was conducted. Principal component analysis (PCA) enabled capturing the general metabolic status of the yeast cells, as replicated samples appear grouped together in the score plot and groups of culture samples according to the main growth phase can be clearly distinguished. The PCA-loading vectors also revealed spectral regions, and the corresponding chemical functional groups and biomolecules that mostly contributed for the cell biomolecular fingerprint associated with the culture growth phase. These data were corroborated by the analysis of the samples’ second derivative spectra. Partial least square (PLS) regression models built based on the MIR spectra showed high predictive ability for estimating the bioprocess critical variables: biomass (R ² = 0.99, RMSEP 2.8%); cyprosin activity (R ² = 0.98, RMSEP 3.9%); glucose (R ² = 0.93, RMSECV 7.2%); galactose (R ² = 0.97, RMSEP 4.6%); ethanol (R ² = 0.97, RMSEP 5.3%); and acetate (R ² = 0.95, RMSEP 7.0%). In conclusion, high-throughput MIR spectroscopy and multivariate data analysis were effective in identifying the main growth phases and specific cyprosin production phases along the yeast culture as well as in quantifying the critical variables of the process. This knowledge will promote future process optimization and control the recombinant cyprosin bioprocess according to Quality by Design framework.