Christian Stolte

COMPARTMENTS: unification and visualization of protein subcellular localization evidence.

Information on protein subcellular localization is important to understand the cellular functions of proteins. Currently, such information is manually curated from the literature, obtained from high-throughput microscopy-based screens and predicted from primary sequence. To get a comprehensive view of the localization of a protein, it is thus necessary to consult multiple databases and prediction tools. To address this, we present the COMPARTMENTS resource, which integrates all sources listed above as well as the results of automatic text mining. The resource is automatically kept up to date with source databases, and all localization evidence is mapped onto common protein identifiers and Gene Ontology terms. We further assign confidence scores to the localization evidence to facilitate comparison of different types and sources of evidence. To further improve the comparability, we assign confidence scores based on the type and source of the localization evidence. Finally, we visualize the unified localization evidence for a protein on a schematic cell to provide a simple overview. Database URL: http://compartments.jensenlab.org

Comprehensive comparison of large-scale tissue expression datasets

For tissues to carry out their functions, they rely on the right proteins to be present. Several high-throughput technologies have been used to map out which proteins are expressed in which tissues; however, the data have not previously been systematically compared and integrated. We present a comprehensive evaluation of tissue expression data from a variety of experimental techniques and show that these agree surprisingly well with each other and with results from literature curation and text mining. We further found that most datasets support the assumed but not demonstrated distinction between tissue-specific and ubiquitous expression. By developing comparable confidence scores for all types of evidence, we show that it is possible to improve both quality and coverage by combining the datasets. To facilitate use and visualization of our work, we have developed the TISSUES resource (http://tissues.jensenlab.org), which makes all the scored and integrated data available through a single user-friendly web interface.

Unexpected features of the dark proteome

Significance A key remaining frontier in our understanding of biological systems is the “dark proteome”—that is, the regions of proteins where molecular conformation is completely unknown. We systematically surveyed these regions, finding that nearly half of the proteome in eukaryotes is dark and that, surprisingly, most of the darkness cannot be accounted for. We also found that the dark proteome has unexpected features, including an association with secretory tissues, disulfide bonding, low evolutionary conservation, and very few known interactions with other proteins. This work will help future research shed light on the remaining dark proteome, thus revealing molecular processes of life that are currently unknown. We surveyed the “dark” proteome–that is, regions of proteins never observed by experimental structure determination and inaccessible to homology modeling. For 546,000 Swiss-Prot proteins, we found that 44–54% of the proteome in eukaryotes and viruses was dark, compared with only ∼14% in archaea and bacteria. Surprisingly, most of the dark proteome could not be accounted for by conventional explanations, such as intrinsic disorder or transmembrane regions. Nearly half of the dark proteome comprised dark proteins, in which the entire sequence lacked similarity to any known structure. Dark proteins fulfill a wide variety of functions, but a subset showed distinct and largely unexpected features, such as association with secretion, specific tissues, the endoplasmic reticulum, disulfide bonding, and proteolytic cleavage. Dark proteins also had short sequence length, low evolutionary reuse, and few known interactions with other proteins. These results suggest new research directions in structural and computational biology.

The Molecular Control Toolkit: Controlling 3D molecular graphics via gesture and voice

Three-dimensional (3D) molecular graphic systems are widely used in the life sciences, both for research and communication. These systems need to enable a rich set of 3D operations, including three-axis rotation and translation, selection of parts of macromolecules, and the ability to redefine the center of rotation. As a result, graphical interfaces for these systems typically require users to learn complex keyboard and mouse combinations. This can be a significant barrier for new or occasional users, and even for experts, precise control of 3D molecular structures can be challenging. To help address these challenges, we developed the Molecular Control Toolkit to support multiple consumer gesture and voice recognition devices, and provide an API that allows adaption to multiple molecular graphics systems. The toolkit allows intuitive control, almost as if users are directly manipulating 3D objects in their hands. We applied the toolkit to the Kinect and Leap Motion devices, and to the Aquaria molecular graphics system. We did a pilot user study with 18 life scientists to test the resulting system in different scenarios. Overall, users gave quite favorable ratings to using the Kinect and Leap Motion gesture devices to control molecular graphics, even though these devices initially proved less efficient for common 3D control tasks, compared to the more familiar mouse/keyboard. To our knowledge, this is the first toolkit for macromolecular graphics that supports multiple devices with a set of controls sufficiently rich to be useful in the day-to-day work of a broad range of life scientists. The Molecular Control Toolkit and Aquaria can be accessed at http://aquaria.ws.

Aquaria: simplifying discovery and insight from protein structures

To the Editor: Since the discovery of the DNA double helix, biologists have been aware that atomic-scale three-dimensional (3D) structures can provide significant insight. The Protein Data Bank1 (PDB) contains a wealth of structural information, but few biologists take full advantage of it2. Thus, we developed Aquaria (http://aquaria. ws), a publicly available web resource that streamlines and simplifies the process of gleaning insight from protein structures. In contrast to most molecular graphics tools (for example, Astex3 or Chimera4), the user interface of Aquaria is organized primarily by protein sequence, not structure (Fig. 1). A user starts by specifying a protein of interest by name and organism (Supplementary Fig. 1), by identifier or by URL (for example, http://aquaria.ws/ P04637); Aquaria then generates a concise visual summary of all related PDB structures (Fig. 1 and Supplementary Methods), using a precalculated all-against-all comparison of Swiss-Prot5 and PDB1 sequences (updated monthly). The related structures are grouped first by alignment to the specified sequence and second by oligomeric state. Structures are then ranked—in both groupings—by sequence similarity to the specified protein. Users can quickly review all known structural information for a protein and find the structures most relevant to them (Supplementary Video 1). Initially, 3D structures are colored to highlight amino acid differences from the specified protein sequence, with bright, saturated colors indicating identical residues and with slightly dark and very dark coloring indicating conserved and nonconserved substitutions, respectively (Fig. 1). Aquaria also allows mapping of InterPro6 and UniProt5 sequence features (for example, domains, single-nucleotide polymorphisms or posttranslational modifications) onto 3D structures: a simple yet effective way to gain insight into molecular function2 (Supplementary Figs. 2 and 3). Aquaria is designed for biologists; its user interface creates clear and useful default views that show only the most relevant structural information tightly integrated with sequence, features and text that provide biological context. Aquaria uses a minimal set of mouse-based controls that are intuitive yet powerful7. For example, its “Autofocus” feature allows exploration of large complexes by focusing on one molecule at a time. Aquaria can also be controlled via hand gestures using the Leap Motion8. Currently, Aquaria contains 46 million precalculated sequenceto-structure alignments, resulting in at least one matching structure for 87% of Swiss-Prot proteins and a median of 35 structures per protein; this provides a depth of sequence-to-structure information currently not available from other resources.

SnapShot: Insulin/IGF1 Signaling

The insulin/IGF1signaling pathway (ISP) plays an essential role in long-term health. Some perturbations in this pathway are associated with diseases such as type 2 diabetes; other perturbations extend lifespan in worms, flies, and mice. The ISP regulates many biological processes, including energy storage, apoptosis, transcription, and cellular homeostasis. Such regulation involves precise rewiring of temporal events in protein phosphorylation networks. For an animated version of this Enhanced SnapShot, please visit http://www.cell.com/cell/enhanced/odonoghue.

TISSUES 2.0: an integrative web resource on mammalian tissue expression

Abstract Physiological and molecular similarities between organisms make it possible to translate findings from simpler experimental systems—model organisms—into more complex ones, such as human. This translation facilitates the understanding of biological processes under normal or disease conditions. Researchers aiming to identify the similarities and differences between organisms at the molecular level need resources collecting multi-organism tissue expression data. We have developed a database of gene–tissue associations in human, mouse, rat and pig by integrating multiple sources of evidence: transcriptomics covering all four species and proteomics (human only), manually curated and mined from the scientific literature. Through a scoring scheme, these associations are made comparable across all sources of evidence and across organisms. Furthermore, the scoring produces a confidence score assigned to each of the associations. The TISSUES database (version 2.0) is publicly accessible through a user-friendly web interface and as part of the STRING app for Cytoscape. In addition, we analyzed the agreement between datasets, across and within organisms, and identified that the agreement is mainly affected by the quality of the datasets rather than by the technologies used or organisms compared. Database URL: http://tissues.jensenlab.org/

Integrated visual analysis of protein structures, sequences, and feature data

BackgroundTo understand the molecular mechanisms that give rise to a proteins function, biologists often need to (i) find and access all related atomic-resolution 3D structures, and (ii) map sequence-based features (e.g., domains, single-nucleotide polymorphisms, post-translational modifications) onto these structures.ResultsTo streamline these processes we recently developed Aquaria, a resource offering unprecedented access to protein structure information based on an all-against-all comparison of SwissProt and PDB sequences. In this work, we provide a requirements analysis for several frequently occuring tasks in molecular biology and describe how design choices in Aquaria meet these requirements. Finally, we show how the interface can be used to explore features of a protein and gain biologically meaningful insights in two case studies conducted by domain experts.ConclusionsThe user interface design of Aquaria enables biologists to gain unprecedented access to molecular structures and simplifies the generation of insight. The tasks involved in mapping sequence features onto structures can be conducted easier and faster using Aquaria.

Visual analytics of signalling pathways using time profiles.

Data visualisation is usually a crucial first step in analysing and exploring large-scale complex data. The visualisation of proteomics time-course data on post-translational modifications presents a particular challenge that is largely unmet by existing tools and methods. To this end, we present Minardo, a novel visualisation strategy tailored for such proteomics data, in which data layout is driven by both cellular topology and temporal order. In this work, we utilised the Minardo strategy to visualise a dataset showing phosphorylation events in response to insulin. We evaluated the visualisation together with experts in diabetes and obesity, which led to new insights into the insulin response pathway. Based on this success, we outline how this layout strategy could be automated into a web-based tool for visualising a broad range of proteomics time-course data. We also discuss how the approach could be extended to include protein 3D structure information, as well as higher dimensional data, such as a range of experimental conditions. We also discuss our entry of Minardo in the international DREAM8 competition.