A framework for querying a database for structural information on 3D images of macromolecules: A web-based query-by-content prototype on the BioImage macromolecular server

Nowadays we are experiencing a remarkable growth in the number of databases that have become accessible over the Web. However, in a certain number of cases, for example, in the case of BioImage, this information is not of a textual nature, thus posing new challenges in the design of tools to handle these data. In this work, we concentrate on the development of new mechanisms aimed at "querying" these databases of complex data sets by their intrinsic content, rather than by their textual annotations only. We concentrate our efforts on a subset of BioImage containing 3D images (volumes) of biological macromolecules, implementing a first prototype of a "query-by-content" system. In the context of databases of complex data types the term query-by-content makes reference to those data modeling techniques in which user-defined functions aim at "understanding" (to some extent) the informational content of the data sets. In these systems the matching criteria introduced by the user are related to intrinsic features concerning the 3D images themselves, hence, complementing traditional queries by textual key words only. Efficient computational algorithms are required in order to "extract" structural information of the 3D images prior to storing them in the database. Also, easy-to-use interfaces should be implemented in order to obtain feedback from the expert. Our query-by-content prototype is used to construct a concrete query, making use of basic structural features, which are then evaluated over a set of three-dimensional images of biological macromolecules. This experimental implementation can be accessed via the Web at the BioImage server in Madrid, at http://www.bioimage.org/qbc/index.html.     

Video on the Internet: An introduction to the digital encoding, compression, and transmission of moving image data

In this paper, we seek to provide an introduction to the fast-moving field of digital video on the Internet, from the viewpoint of the biological microscopist who might wish to store or access videos, for instance in image databases such as the BioImage Database (http://www.bioimage.org). We describe and evaluate the principal methods used for encoding and compressing moving image data for digital storage and transmission over the Internet, which involve compromises between compression efficiency and retention of image fidelity, and describe the existing alternate software technologies for downloading or streaming compressed digitized videos using a Web browser. We report the results of experiments on video microscopy recordings and three-dimensional confocal animations of biological specimens to evaluate the compression efficiencies of the principal video compression-decompression algorithms (codecs) and to document the artefacts associated with each of them. Because MPEG-1 gives very high compression while yet retaining reasonable image quality, these studies lead us to recommend that video databases should store both a high-resolution original version of each video, ideally either uncompressed or losslessly compressed, and a separate edited and highly compressed MPEG-1 preview version that can be rapidly downloaded for interactive viewing by the database user.     

The need for a shared database infrastructure: combining X-ray crystallography and electron microscopy

Advances in structural biology are opening greater opportunities for understanding biological structures from the cellular to the atomic level. Particularly promising are the links that can be established between the information provided by electron microscopy and the atomic structures derived from X-ray crystallography and nuclear magnetic resonance spectroscopy. Combining such different kinds of structural data can result in novel biological information on the interaction of biomolecules in large supramolecular assemblies. As a consequence, the need to develop new databases in the field of structural biology that allow for an integrated access to data from all the experimental techniques is becoming critical. Pilot studies performed in recent years have already established a solid background as far as the basic information that an integrated macromolecular structure database should contain, as well as the basic principles for integration. These efforts started in the context of the BioImage project, and resulted in a first complete database prototype that provided a versatile platform for the linking of atomic models or X-ray diffraction data with electron microscopy information. Analysis of the requirements needed to combine data at different levels of resolution have resulted in sets of specifications that make possible the integration of all these different types in the context of a web environment. The case of a structural study linking electron microscopy and X-ray data, which is already contained within the BioImage data base and in the Protein Data Bank, is used here to illustrate the current approach, while a general discussion highlights the urgent need for integrated databases. Received: 26 January 2000 / Revised version: 15 May 2000 / Accepted: 15 May 2000     

Electronic light microscopy: present capabilities and future prospects

Electronic light microscopy involves the combination of microscopic techniques with electronic imaging and digital image processing, resulting in dramatic improvements in image quality and ease of quantitative analysis. In this review, after a brief definition of digital images and a discussion of the sampling requirements for the accurate digital recording of optical images, I discuss the three most important imaging modalities in electronic light microscopy-video-enhanced contrast microscopy, digital fluorescence microscopy and confocal scanning microscopy-considering their capabilities, their applications, and recent developments that will increase their potential. Video-enhanced contrast microscopy permits the clear visualisation and real-time dynamic recording of minute objects such as microtubules, vesicles and colloidal gold particles, an order of magnitude smaller than the resolution limit of the light microscope. It has revolutionised the study of cellular motility, and permits the quantitative tracking of organelles and gold-labelled membrane bound proteins. In combination with the technique of optical trapping (optical tweezers), it permits exquisitely sensitive force and distance measurements to be made on motor proteins. Digital fluorescence microscopy enables low-light-level imaging of fluorescently labelled specimens. Recent progress has involved improvements in cameras, fluorescent probes and fluorescent filter sets, particularly multiple bandpass dichroic mirrors, and developments in multiparameter imaging, which is becoming particularly important for in situ hybridisation studies and automated image cytometry, fluorescence ratio imaging, and time-resolved fluorescence. As software improves and small computers become more powerful, computational techniques for out-of-focus blur deconvolution and image restoration are becoming increasingly important. Confocal microscopy permits convenient, high-resolution, non-invasive, blur-free optical sectioning and 3D image acquisition, but suffers from a number of limitations. I discuss advances in confocal techniques that address the problems of temporal resolution, spherical and chromatic aberration, wavelength flexibility and cross-talk between fluorescent channels, and describe new optics to enhance axial resolution and the use of two-photon excitation to reduce photobleaching. Finally, I consider the desirability of establishing a digital image database, the BioImage database, which would permit the archival storage of, and public Internet access to, multidimensional image data from all forms of biological microscopy. Submission of images to the BioImage database would be made in coordination with the scientific publication of research results based upon these data. In the context of electronic light microscopy, this would be particularly useful for three-dimensional images of cellular structure and video sequences of dynamic cellular processes, which are otherwise hard to communicate. However, it has the wider significance of allowing correlative studies on data obtained from many different microscopies and from sequence and crystallographic investigations. It also opens the door to interactive hypermedia access to the multidimensional image data, and multimedia publishing ventures based upon this.Presented at the XXXVII Symposium of the Society for Histochemistry, 23 September 1995, Rigi Kaltbad, Switzerland     

BioJava: an open-source framework for bioinformatics

SUMMARY: BioJava is a mature open-source project that provides a framework for processing of biological data. BioJava contains powerful analysis and statistical routines, tools for parsing common file formats and packages for manipulating sequences and 3D structures. It enables rapid bioinformatics application development in the Java programming language. AVAILABILITY: BioJava is an open-source project distributed under the Lesser GPL (LGPL). BioJava can be downloaded from the BioJava website (http://www.biojava.org). BioJava requires Java 1.5 or higher. All queries should be directed to the BioJava mailing lists. Details are available at http://biojava.org/wiki/BioJava:MailingLists.     

Current state of the art for enhancing urine biomarker discovery

Introduction: Urine is a highly desirable biospecimen for biomarker analysis because it can be collected recurrently by non-invasive techniques, in relatively large volumes. Urine contains cellular elements, biochemicals, and proteins derived from glomerular filtration of plasma, renal tubule excretion, and urogenital tract secretions that reflect, at a given time point, an individual’s metabolic and pathophysiologic state.

Areas covered: High-resolution mass spectrometry, coupled with state of the art fractionation systems are revealing the plethora of diagnostic/prognostic proteomic information existing within urinary exosomes, glycoproteins, and proteins. Affinity capture pre-processing techniques such as combinatorial peptide ligand libraries and biomarker harvesting hydrogel nanoparticles are enabling measurement/identification of previously undetectable urinary proteins.

Expert commentary: Future challenges in the urinary proteomics field include a) defining either single or multiple, universally applicable data normalization methods for comparing results within and between individual patients/data sets, and b) defining expected urinary protein levels in healthy individuals.     

Paramacrobiotus lachowskae,a new species of Tardigrada from Colombia (Eutardigrada: Parachela: Macrobiotidae)

In this article we describe a new Paramacrobiotus species of the areolatus group by means of integrative taxonomy. Together with the detailed morphological and morphometric data (obtained from light and scanning electron microscopy) we also provide DNA sequences of four universal molecular markers used in tardigrade taxonomy (three nDNA fragments: 18S rRNA, 28S rRNA, ITS-2, and one mtDNA fragment: COI). The animals of Paramacrobiotus lachowskae sp. nov. are similar to several species of the areolatus complex and the eggshell ornamentation is similar to that of two species of the richtersi group. Therefore, the new species can be easily distinguished from the areolatus group species by egg morphology (dome-like, wrinkled processes with long flexible spines/filaments covered by fine short hairs) and from species of the richtersi complex by the absence of the microplacoid. Paramacrobiotus lachowskae sp. nov. is the 43rd species reported from Colombia and fifth Paramacrobiotus species from this South American country.

http://zoobank.org/urn:lsid:zoobank.org:pub:FEDC11D3-DCCF-4699-A704-CE6DEA1CDED4     

Automated detection and segmentation of synaptic contacts in nearly isotropic serial electron microscopy images

We describe a protocol for fully automated detection and segmentation of asymmetric, presumed excitatory, synapses in serial electron microscopy images of the adult mammalian cerebral cortex, taken with the focused ion beam, scanning electron microscope (FIB/SEM). The procedure is based on interactive machine learning and only requires a few labeled synapses for training. The statistical learning is performed on geometrical features of 3D neighborhoods of each voxel and can fully exploit the high z-resolution of the data. On a quantitative validation dataset of 111 synapses in 409 images of 1948×1342 pixels with manual annotations by three independent experts the error rate of the algorithm was found to be comparable to that of the experts (0.92 recall at 0.89 precision). Our software offers a convenient interface for labeling the training data and the possibility to visualize and proofread the results in 3D. The source code, the test dataset and the ground truth annotation are freely available on the website http://www.ilastik.org/synapse-detection.     

The discriminative bilateral filter: an enhanced denoising filter for electron microscopy data

Advances in three-dimensional (3D) electron microscopy (EM) and image processing are providing considerable improvements in the resolution of subcellular volumes, macromolecular assemblies and individual proteins. However, the recovery of high-frequency information from biological samples is hindered by specimen sensitivity to beam damage. Low dose electron cryo-microscopy conditions afford reduced beam damage but typically yield images with reduced contrast and low signal-to-noise ratios (SNRs). Here, we describe the properties of a new discriminative bilateral (DBL) filter that is based upon the bilateral filter implementation of Jiang et al. (Jiang, W., Baker, M.L., Wu, Q., Bajaj, C., Chiu, W., 2003. Applications of a bilateral denoising filter in biological electron microscopy. J. Struc. Biol. 128, 82-97.). In contrast to the latter, the DBL filter can distinguish between object edges and high-frequency noise pixels through the use of an additional photometric exclusion function. As a result, high frequency noise pixels are smoothed, yet object edge detail is preserved. In the present study, we show that the DBL filter effectively reduces noise in low SNR single particle data as well as cellular tomograms of stained plastic sections. The properties of the DBL filter are discussed in terms of its usefulness for single particle analysis and for pre-processing cellular tomograms ahead of image segmentation.     

Searching the literature for proteins facilitates the identification of biological processes,if advanced methods of analysis are linked: a case study on microgravity-caused changes in cells

Background: More than one hundred reports were published about the characterization of cells from malignant and healthy tissues, as well as of endothelial cells and stem cells exposed to microgravity conditions.

Methods: We retrieved publications about microgravity related studies on each type of cells, extracted the proteins mentioned therein and analyzed them aiming to identify biological processes affected by microgravity culture conditions.

Results: The analysis revealed 66 different biological processes, 19 of them were always detected when papers about the four types of cells were analyzed.

Conclusion: Since a response to the removal of gravity is common to the different cell types, some of the 19 biological processes could play a role in cellular adaption to microgravity. Applying computer programs, to extract and analyze proteins and genes mentioned in publications becomes essential for scientists interested to get an overview of the rapidly growing fields of gravitational biology and space medicine.     

The progress and potential of proteomic biomarkers for type 1 diabetes in children

Introduction: Although it is possible to identify the genetic risk for type 1 diabetes (T1D), it is not possible to predict who will develop the disease. New biomarkers are needed that would help understand the mechanisms of disease onset and when to administer targeted therapies and interventions.

Areas covered: An overview is presented of international study efforts towards understanding the cause of T1D, including the collection of several extensive temporal sample series that follow the development of T1D in at risk children. The results of the proteomics analysis of these materials are presented, which have included bodily fluids, such as serum or plasma and urine, as well as tissue samples from the pancreas.

Expert commentary: Promising recent reports have indicated detection of early proteomic changes in the serum of patients prior to diagnosis, potentially providing new measures for risk assessment. Similarly, there has been evidence that post-translational modification (PTM) may result in the recognition of islet cell proteins as autoantigens; modified proteins could thus be used as targets for immunomodulation to overcome the threat of the autoimmune response.     

A new species of entomopathogenic nematode Oscheius safricana n. sp. (Nematoda: Rhabditidae) from South Africa

In a recent entomopathogenic nematode (EPN) survey in the North West province of South Africa, Oscheius safricana was isolated from soil samples using the Galleria mellonella bait method. Morphological studies using light microscopy and scanning electron microscopy, molecular analysis of the internal transcribed spacer region (ITS), D2\D3 expansion segments of the large subunit rDNA gene (LSU) and concise small subunit rDNA gene (SSU), revealed that it was a new species, described herein as Oscheius safricana n. sp. Oscheius safricana n. sp. was characterised by unique ribosomal DNA sequences, amphidelphic reproduction, six separate lips each two bristle-like sensillae, narrow pharynx, valvated basal bulb, lateral field with four lines, leptoderan and closed bursa and fused spicules. This EPN belongs to the group Insectivorus and is morphologically closest to O. necromenus, O. chongmingensis and O. carolinensis. Oscheius safricana n. sp. is symbiotically associated with Serratia marcescens strain MCB.

http://www.zoobank.org/urn:lsid:zoobank.org:pub:642E1B7E-B88F-4CE0-9D06-4FA9ECA48847     

UniDrug-target: a computational tool to identify unique drug targets in pathogenic bacteria

Background

Targeting conserved proteins of bacteria through antibacterial medications has resulted in both the development of resistant strains and changes to human health by destroying beneficial microbes which eventually become breeding grounds for the evolution of resistances. Despite the availability of more than 800 genomes sequences, 430 pathways, 4743 enzymes, 9257 metabolic reactions and protein (three-dimensional) 3D structures in bacteria, no pathogen-specific computational drug target identification tool has been developed.

Methods

A web server, UniDrug-Target, which combines bacterial biological information and computational methods to stringently identify pathogen-specific proteins as drug targets, has been designed. Besides predicting pathogen-specific proteins essentiality, chokepoint property, etc., three new algorithms were developed and implemented by using protein sequences, domains, structures, and metabolic reactions for construction of partial metabolic networks (PMNs), determination of conservation in critical residues, and variation analysis of residues forming similar cavities in proteins sequences. First, PMNs are constructed to determine the extent of disturbances in metabolite production by targeting a protein as drug target. Conservation of pathogen-specific protein''s critical residues involved in cavity formation and biological function determined at domain-level with low-matching sequences. Last, variation analysis of residues forming similar cavities in proteins sequences from pathogenic versus non-pathogenic bacteria and humans is performed.

Results

The server is capable of predicting drug targets for any sequenced pathogenic bacteria having fasta sequences and annotated information. The utility of UniDrug-Target server was demonstrated for Mycobacterium tuberculosis (H37Rv). The UniDrug-Target identified 265 mycobacteria pathogen-specific proteins, including 17 essential proteins which can be potential drug targets.

Conclusions/Significance

UniDrug-Target is expected to accelerate pathogen-specific drug targets identification which will increase their success and durability as drugs developed against them have less chance to develop resistances and adverse impact on environment. The server is freely available at http://117.211.115.67/UDT/main.html. The standalone application (source codes) is available at http://www.bioinformatics.org/ftp/pub/bioinfojuit/UDT.rar.     

Mechanisms involved in the development of diabetic retinopathy induced by oxidative stress

Background: Diabetic retinopathy (DR) is one of the main complications in patients with diabetes and has been the leading cause of visual loss since 1990. Oxidative stress is a biological process resulting from excessive production of reactive oxygen species (ROS). This process contributes to the development of many diseases and disease complications. ROS interact with various cellular components to induce cell injury. Fortunately, there is an antioxidan t system that protects organisms against ROS. Indeed, when ROS exceed antioxidant capacity, the resulting cell injury can cause diverse physiological and pathological changes that could lead to a disease like DR.

Objective: This paper reviews the possible mechanisms of common and novel biomarkers involved in the development of DR and explores how these biomarkers could be used to monitor the damage induced by oxidative stress in DR, which is a significant complication in people with diabetes.

Conclusion: The poor control of glucemy in pacients with DB has been shown contribute to the development of complications in eyes as DR.     

Icy: an open bioimage informatics platform for extended reproducible research

Current research in biology uses evermore complex computational and imaging tools. Here we describe Icy, a collaborative bioimage informatics platform that combines a community website for contributing and sharing tools and material, and software with a high-end visual programming framework for seamless development of sophisticated imaging workflows. Icy extends the reproducible research principles, by encouraging and facilitating the reusability, modularity, standardization and management of algorithms and protocols. Icy is free, open-source and available at http://icy.bioimageanalysis.org/.     

Imaging three-dimensional tissue architectures by focused ion beam scanning electron microscopy

In this protocol, we describe a 3D imaging technique known as 'volume electron microscopy' or 'focused ion beam scanning electron microscopy (FIB/SEM)' applied to biological tissues. A scanning electron microscope equipped with a focused gallium ion beam, used to sequentially mill away the sample surface, and a backscattered electron (BSE) detector, used to image the milled surfaces, generates a large series of images that can be combined into a 3D rendered image of stained and embedded biological tissue. Structural information over volumes of tens of thousands of cubic micrometers is possible, revealing complex microanatomy with subcellular resolution. Methods are presented for tissue processing, for the enhancement of contrast with osmium tetroxide/potassium ferricyanide, for BSE imaging, for the preparation and platinum deposition over a selected site in the embedded tissue block, and for sequential data collection with ion beam milling; all this takes approximately 90 h. The imaging conditions, procedures for alternate milling and data acquisition and techniques for processing and partitioning the 3D data set are also described; these processes take approxiamtely 30 h. The protocol is illustrated by application to developing chick cornea, in which cells organize collagen fibril bundles into complex, multilamellar structures essential for transparency in the mature connective tissue matrix. The techniques described could have wide application in a range of fields, including pathology, developmental biology, microstructural anatomy and regenerative medicine.     

Cover Picture: Biotechnology Journal 2/2017

The cover of this regular issue of BTJ shows fluorescence microscopy images of bacteria along with their processed counterparts after CellShape analysis. While the former are simple raw images, the latter reveal important quantitative information e.g. intensity contours and spots. Altogether, they form a complete dataset from which we can accurately interpret cellular fluorescent signals. The cover is prepared by ρngel Goñi‐Moreno, Juhyun Kim and Víctor de Lorenzo authors of the article ”CellShape: A user‐friendly image analysis tool for quantitative visualization of bacterial cell factories inside“. ( http://dx.doi.org/10.1002/biot.201600323 ).     

Classification and 3D averaging with missing wedge correction in biological electron tomography

Strategies for the determination of 3D structures of biological macromolecules using electron crystallography and single-particle electron microscopy utilize powerful tools for the averaging of information obtained from 2D projection images of structurally homogeneous specimens. In contrast, electron tomographic approaches have often been used to study the 3D structures of heterogeneous, one-of-a-kind objects such as whole cells where image-averaging strategies are not applicable. Complex entities such as cells and viruses, nevertheless, contain multiple copies of numerous macromolecules that can individually be subjected to 3D averaging. Here we present a complete framework for alignment, classification, and averaging of volumes derived by electron tomography that is computationally efficient and effectively accounts for the missing wedge that is inherent to limited-angle electron tomography. Modeling the missing data as a multiplying mask in reciprocal space we show that the effect of the missing wedge can be accounted for seamlessly in all alignment and classification operations. We solve the alignment problem using the convolution theorem in harmonic analysis, thus eliminating the need for approaches that require exhaustive angular search, and adopt an iterative approach to alignment and classification that does not require the use of external references. We demonstrate that our method can be successfully applied for 3D classification and averaging of phantom volumes as well as experimentally obtained tomograms of GroEL where the outcomes of the analysis can be quantitatively compared against the expected results.