Meeting report: SMART timing—principles of single molecule techniques course at the University of Michigan 2014

Four days after the announcement of the 2014 Nobel Prize in Chemistry for “the development of super‐resolved fluorescence microscopy” based on single molecule detection, the Single Molecule Analysis in Real‐Time (SMART) Center at the University of Michigan hosted a “Principles of Single Molecule Techniques 2014” course. Through a combination of plenary lectures and an Open House at the SMART Center, the course took a snapshot of a technology with an especially broad and rapidly expanding range of applications in the biomedical and materials sciences. Highlighting the continued rapid emergence of technical and scientific advances, the course underscored just how brightly the future of the single molecule field shines. © 2014 Wiley Periodicals, Inc. Biopolymers 103: 296–302, 2015.     

Sharing and archiving nucleic acid structure mapping data

Nucleic acids are particularly amenable to structural characterization using chemical and enzymatic probes. Each individual structure mapping experiment reveals specific information about the structure and/or dynamics of the nucleic acid. Currently, there is no simple approach for making these data publically available in a standardized format. We therefore developed a standard for reporting the results of single nucleotide resolution nucleic acid structure mapping experiments, or SNRNASMs. We propose a schema for sharing nucleic acid chemical probing data that uses generic public servers for storing, retrieving, and searching the data. We have also developed a consistent nomenclature (ontology) within the Ontology of Biomedical Investigations (OBI), which provides unique identifiers (termed persistent URLs, or PURLs) for classifying the data. Links to standardized data sets shared using our proposed format along with a tutorial and links to templates can be found at http://snrnasm.bio.unc.edu.     

High-Density 3D Single Molecular Analysis Based on Compressed Sensing

Single molecule fitting-based superresolution microscopy achieves sub-diffraction-limit image resolution but suffers from a need for long acquisition times to gather enough molecules. Several methods have recently been developed that analyze high molecule density images but most are only applicable to two dimensions. In this study, we implemented a high-density superresolution localization algorithm based on compressed sensing and a biplane approach that provides three-dimensional information about molecules, achieving super-resolution imaging at higher molecule densities than those achieved using the conventional single molecule fitting method.     

High-Density 3D Single Molecular Analysis Based on Compressed Sensing

Single molecule fitting-based superresolution microscopy achieves sub-diffraction-limit image resolution but suffers from a need for long acquisition times to gather enough molecules. Several methods have recently been developed that analyze high molecule density images but most are only applicable to two dimensions. In this study, we implemented a high-density superresolution localization algorithm based on compressed sensing and a biplane approach that provides three-dimensional information about molecules, achieving super-resolution imaging at higher molecule densities than those achieved using the conventional single molecule fitting method.     

Rapid quantitative analysis using a single molecule counting approach

Single molecule detection of target molecules specifically bound by paired fluorescently labeled probes has shown great potential for sensitive quantitation of biomolecules. To date, no reports have rigorously evaluated the analytical capabilities of a single molecule detection platform employing this dual-probe approach or the performance of its data analysis methodology. In this paper, we describe a rapid, automated, and sensitive multicolor single molecule detection apparatus and a novel extension of coincident event counting based on detection of fluorescent probes. The approach estimates the number of dual-labeled molecules of interest from the total number of coincident fluorescent events observed by correcting for unbound probes that randomly pass through the interrogation zone simultaneously. Event counting was evaluated on three combinations of distinct fluorescence channels and was demonstrated to outperform conventional spatial cross-correlation in generating a wider linear dynamic response to target molecules. Furthermore, this approach succeeded in detecting subpicomolar concentrations of a model RNA target to which fluorescently labeled oligonucleotide probes were hybridized in a complex background of RNA. These results illustrate that the fluorescent event counting approach described represents a general tool for rapid sensitive quantitative analysis of any sample analyte, including nucleic acids and proteins, for which pairs of specific probes can be developed.     

The InterPro Database, 2003 brings increased coverage and new features

InterPro, an integrated documentation resource of protein families, domains and functional sites, was created in 1999 as a means of amalgamating the major protein signature databases into one comprehensive resource. PROSITE, Pfam, PRINTS, ProDom, SMART and TIGRFAMs have been manually integrated and curated and are available in InterPro for text- and sequence-based searching. The results are provided in a single format that rationalises the results that would be obtained by searching the member databases individually. The latest release of InterPro contains 5629 entries describing 4280 families, 1239 domains, 95 repeats and 15 post-translational modifications. Currently, the combined signatures in InterPro cover more than 74% of all proteins in SWISS-PROT and TrEMBL, an increase of nearly 15% since the inception of InterPro. New features of the database include improved searching capabilities and enhanced graphical user interfaces for visualisation of the data. The database is available via a webserver (http://www.ebi.ac.uk/interpro) and anonymous FTP (ftp://ftp.ebi.ac.uk/pub/databases/interpro).     

Scientific workflow management in proteomics

Data processing in proteomics can be a challenging endeavor, requiring extensive knowledge of many different software packages, all with different algorithms, data format requirements, and user interfaces. In this article we describe the integration of a number of existing programs and tools in Taverna Workbench, a scientific workflow manager currently being developed in the bioinformatics community. We demonstrate how a workflow manager provides a single, visually clear and intuitive interface to complex data analysis tasks in proteomics, from raw mass spectrometry data to protein identifications and beyond.     

Anvaya: a workflows environment for automated genome analysis

Anvaya is a workflow environment for automated genome analysis that provides an interface for several bioinformatics tools and databases, loosely coupled together in a coordinated system, enabling the execution of a set of analyses tools in series or in parallel. It is a client-server workflow environment that has an advantage over existing software as it enables extensive pre & post processing of biological data in an efficient manner. "Anvaya" offers the user, novel functionalities to carry out exhaustive comparative analysis via "custom tools," which are tools with new functionality not available in standard tools, and "built-in PERL parsers," which automate data-flow between tools that hitherto, required manual intervention. It also provides a set of 11 pre-defined workflows for frequently used pipelines in genome annotation and comparative genomics ranging from EST assembly and annotation to phylogenetic reconstruction and microarray analysis. It provides a platform that serves as a single-stop solution for biologists to carry out hassle-free and comprehensive analysis, without being bothered about the nuances involved in tool installation, command line parameters, format conversions required to connect tools and manage/process multiple data sets at a single instance.     

ProtaBank: A repository for protein design and engineering data

We present ProtaBank, a repository for storing, querying, analyzing, and sharing protein design and engineering data in an actively maintained and updated database. ProtaBank provides a format to describe and compare all types of protein mutational data, spanning a wide range of properties and techniques. It features a user‐friendly web interface and programming layer that streamlines data deposition and allows for batch input and queries. The database schema design incorporates a standard format for reporting protein sequences and experimental data that facilitates comparison of results across different data sets. A suite of analysis and visualization tools are provided to facilitate discovery, to guide future designs, and to benchmark and train new predictive tools and algorithms. ProtaBank will provide a valuable resource to the protein engineering community by storing and safeguarding newly generated data, allowing for fast searching and identification of relevant data from the existing literature, and exploring correlations between disparate data sets. ProtaBank invites researchers to contribute data to the database to make it accessible for search and analysis. ProtaBank is available at https://protabank.org .     

High-Throughput In Vivo Genotoxicity Testing: An Automated Readout System for the Somatic Mutation and Recombination Test (SMART)

Genotoxicity testing is an important component of toxicity assessment. As illustrated by the European registration, evaluation, authorization, and restriction of chemicals (REACH) directive, it concerns all the chemicals used in industry. The commonly used in vivo mammalian tests appear to be ill adapted to tackle the large compound sets involved, due to throughput, cost, and ethical issues. The somatic mutation and recombination test (SMART) represents a more scalable alternative, since it uses Drosophila, which develops faster and requires less infrastructure. Despite these advantages, the manual scoring of the hairs on Drosophila wings required for the SMART limits its usage. To overcome this limitation, we have developed an automated SMART readout. It consists of automated imaging, followed by an image analysis pipeline that measures individual wing genotoxicity scores. Finally, we have developed a wing score-based dose-dependency approach that can provide genotoxicity profiles. We have validated our method using 6 compounds, obtaining profiles almost identical to those obtained from manual measures, even for low-genotoxicity compounds such as urethane. The automated SMART, with its faster and more reliable readout, fulfills the need for a high-throughput in vivo test. The flexible imaging strategy we describe and the analysis tools we provide should facilitate the optimization and dissemination of our methods.     

GRAMA: genetic mapping analysis of temperature gradient capillary electrophoresis data

Temperature gradient capillary electrophoresis (TGCE) is a high-throughput method to detect segregating single nucleotide polymorphisms and InDel polymorphisms in genetic mapping populations. Existing software that analyzes TGCE data was, however, designed for mutation analysis rather than genetic mapping. Genetic recombinant analysis and mapping assistant (GRAMA) is a new tool that automates TGCE data analysis for the purpose of genetic mapping. Data from multiple TGCE runs are analyzed, integrated, and displayed in an intuitive visual format. GRAMA includes an algorithm to detect peaks in electropherograms and can automatically compare its peak calls with those produced by another software package. Consequently, GRAMA provides highly accurate results with a low false positive rate of 5.9% and an even lower false negative rate of 1.3%. Because of its accuracy and intuitive interface, GRAMA boosts user productivity more than twofold relative to previous manual methods of scoring TGCE data. GRAMA is written in Java and is freely available at .     

eL-DASionator: an LDAS upload file generator

Background  

The Distributed Annotation System (DAS) allows merging of DNA sequence annotations from multiple sources and provides a single annotation view. A straightforward way to establish a DAS annotation server is to use the "Lightweight DAS" server (LDAS). Onto this type of server, annotations can be uploaded as flat text files in a defined format. The popular Ensembl ContigView uses the same format for the transient upload and display of user data.     

Single cell analytics for nanobiology

Single cell analytics allows quantitative investigation of single biological cells from a structural, functional and proteomics point of view and opens possibilities to a novel unamplified cell analysis inherently insensitive to ensemble-averaging, cell-cycle or cell-population effects. We report on three different experimental methods and their application to cellular systems with single molecule sensitivity at the single cell level. Firstly, atomic force microscopy (AFM) can be used to elucidate the surface structure of living bacteria down to the nanometer scale where identification of irregular surface areas and 2D-arrays of regular protein s-layers is possible. Secondly, single cell manipulation and probing experiments with optical tweezers (OT) force spectroscopy allows quantitative identification of individual recognition events of membrane bound receptors. And thirdly, a novel, single cell analysis for protein fingerprinting in structured microfluidic device format will allow a future (label-free) on-chip electrophoretical protein separation of single cells without preamplification.     

Automating data manipulation for genetic analysis using a data base management system

Inefficient coding and manipulation of pedigree data have often hindered the progress of genetic studies. In this paper we present the methodology for interfacing a data base management system (DBMS) called MEGADATS with a linkage analysis program called LIPED. Two families that segregate a dominant trait and one test marker were used in a simulated exercise to demonstrate how a DBMS can be used to automate tedious clerical steps and improve the efficiency of a genetic analysis. The merits of this approach to data management are discussed. We conclude that a standardized format for genetic analysis programs would greatly facilitate data analysis.     

单分子实时测序及其在微生物表观遗传学中的应用

表观遗传学对于微生物的生命进程起着重要作用。由限制-修饰系统调控的DNA修饰参与微生物的免疫防御系统,无限制-修饰系统调控的DNA修饰通过调控基因表达影响表型。然而,表观遗传信息还没有被常规地作为DNA信息收集分析。基于对DNA合成反应的动力学分析,单分子实时测序技术可以在获得基本序列数据的同时实现对被修饰核苷酸的检测。这个技术为微生物中已知DNA修饰的研究提供了新的平台,也为新型DNA修饰的发现做好准备。本文综述了单分子实时测序技术及其在微生物表观遗传学中的应用。     

Macintosh graphics for the EPICS flow cytometer user

Graphic options for the EPICS flow cytometer user have been restricted in the past to software written specifically for the analysis and graphics of flow cytometric data. The software is limited to only a few graphic presentation styles. The technique described will allow the EPICS user to translate histogram files into text files that can be used in an alternative computer format.     

Inferring subunit stoichiometry from single molecule photobleaching

Single molecule photobleaching is a powerful tool for determining the stoichiometry of protein complexes. By attaching fluorophores to proteins of interest, the number of associated subunits in a complex can be deduced by imaging single molecules and counting fluorophore photobleaching steps. Because some bleaching steps might be unobserved, the ensemble of steps will be binomially distributed. In this work, it is shown that inferring the true composition of a complex from such data is nontrivial because binomially distributed observations present an ill-posed inference problem. That is, a unique and optimal estimate of the relevant parameters cannot be extracted from the observations. Because of this, a method has not been firmly established to quantify confidence when using this technique. This paper presents a general inference model for interpreting such data and provides methods for accurately estimating parameter confidence. The formalization and methods presented here provide a rigorous analytical basis for this pervasive experimental tool.     

Probing complexes with single fluorophores: factors contributing to dispersion of FRET in DNA/RNA duplexes

Single molecule fluorescent microscopy is a method for the analysis of the dynamics of biological macromolecules by detecting the fluorescence signal produced by fluorophores associated with the macromolecule. Two fluorophores located in a close proximity may result in Förster resonance energy transfer (FRET), which can be detected at the single molecule level and the efficiency of energy transfer calculated. In most cases, the experimentally observed distribution of FRET efficiency exhibits a significant width corresponding to 0.07–0.2 (on a scale of 0–1). Here, we present a general approach describing the analysis of experimental data for a DNA/RNA duplex. We have found that for a 15 bp duplex with Cy3 and Cy5 fluorophores attached to the opposite ends of the helix, the width of the energy transfer distribution is mainly determined by the photon shot noise and the orientation factor, whereas the variation of inter-dye distances plays a minor role.