Protein Localization Data Research Articles

Mapping the Multiscale Proteomic Organization of Cellular and Disease Phenotypes.

While the primary sequences of human proteins have been cataloged for over a decade, determining how these are organized into a dynamic collection of multiprotein assemblies, with structures and functions spanning biological scales, is an ongoing venture. Systematic and data-driven analyses of these higher-order structures are emerging, facilitating the discovery and understanding of cellular phenotypes. At present, knowledge of protein localization and function has been primarily derived from manual annotation and curation in resources such as the Gene Ontology, which are biased toward richly annotated genes in the literature. Here, we envision a future powered by data-driven mapping of protein assemblies. These maps can capture and decode cellular functions through the integration of protein expression, localization, and interaction data across length scales and timescales. In this review, we focus on progress toward constructing integrated cell maps that accelerate the life sciences and translational research.

Peripheral thickening of the sarcomeres and pointed end elongation of the thin filaments are both promoted by SALS and its formin interaction partners.

During striated muscle development the first periodically repeated units appear in the premyofibrils, consisting of immature sarcomeres that must undergo a substantial growth both in length and width, to reach their final size. Here we report that, beyond its well established role in sarcomere elongation, the Sarcomere length short (SALS) protein is involved in Z-disc formation and peripheral growth of the sarcomeres. Our protein localization data and loss-of-function studies in the Drosophila indirect flight muscle strongly suggest that radial growth of the sarcomeres is initiated at the Z-disc. As to thin filament elongation, we used a powerful nanoscopy approach to reveal that SALS is subject to a major conformational change during sarcomere development, which might be critical to stop pointed end elongation in the adult muscles. In addition, we demonstrate that the roles of SALS in sarcomere elongation and radial growth are both dependent on formin type of actin assembly factors. Unexpectedly, when SALS is present in excess amounts, it promotes the formation of actin aggregates highly resembling the ones described in nemaline myopathy patients. Collectively, these findings helped to shed light on the complex mechanisms of SALS during the coordinated elongation and thickening of the sarcomeres, and resulted in the discovery of a potential nemaline myopathy model, suitable for the identification of genetic and small molecule inhibitors.

The Lipid Droplet Knowledge Portal: A resource for systematic analyses of lipid droplet biology.

Lipid droplets (LDs) are organelles of cellular lipid storage with fundamental roles in energy metabolism and cell membrane homeostasis. There has been an explosion of research into the biology of LDs, in part due to their relevance in diseases of lipid storage, such as atherosclerosis, obesity, type 2 diabetes, and hepatic steatosis. Consequently, there is an increasing need for a resource that combines datasets from systematic analyses of LD biology. Here, we integrate high-confidence, systematically generated human, mouse, and fly data from studies on LDs in the framework of an online platform named the "Lipid Droplet Knowledge Portal" (https://lipiddroplet.org/). This scalable and interactive portal includes comprehensive datasets, across a variety of cell types, for LD biology, including transcriptional profiles of induced lipid storage, organellar proteomics, genome-wide screen phenotypes, and ties to human genetics. This resource is a powerful platform that can be utilized to identify determinants of lipid storage.

Comparison of ethylenediaminetetraacetic acid and rapid decalcificier solution for studying human temporal bones by immunofluorescence.

ObjectivesThe pervasiveness of hearing loss and the development of new potential therapeutic approaches have led to increased animal studies of the inner ear. However, translational relevance of such studies depends upon verification of protein localization data in human samples. Cadavers used for anatomical education provide a potential research resource, but are limiting due to difficulties in accessing sensory tissues from the dense temporal bones. This study seeks to reduce the often months‐long process of decalcification and improve immunofluorescent staining of human cadaveric temporal bones for research use.MethodsTemporal bones were decalcified in either (a) hydrochloric acid‐containing RDO solution for 2 days followed by 0.5 M ethylenediaminetetraacetic acid (EDTA) for 3 to 5 additional days, or (b) 0.5 M EDTA alone for 2 to 4 weeks. Image‐iT FX signal enhancer (ISE) was used to improve immunofluorescent signal‐to‐noise ratios.ResultsThe data indicate that both methods speed decalcification and allow for immunolabeling of the extranuclear proteins neurofilament (heavy chain), myosin VIIa, oncomodulin and prestin. However, RDO decalcification was more likely to alter structural morphology of sensory tissues and hindered effective labeling of the nuclear proteins SRY‐box transcription factor 2 and GATA binding protein 3.ConclusionsAlthough both approaches allow for rapid decalcification, EDTA appears superior to RDO for preserving cytoarchitecture and immunogenicity.Level of evidenceNA.

Sequence-independent recognition of the amyloid structural motif by GFP protein family

Cnidarian fluorescent protein (FP) derivatives such as GFP, mCherry, and mEOS2 have been widely used to monitor gene expression and protein localization through biological imaging because they are considered functionally inert. We demonstrate that FPs specifically bind amyloid fibrils formed from many natural peptides and proteins. FPs do not bind other nonamyloid fibrillar structures such as microtubules or actin filaments and do not bind to amorphous aggregates. FPs can also bind small aggregates formed during the lag phase and early elongation phase of fibril formation and can inhibit amyloid fibril formation in a dose-dependent manner. These findings suggest caution should be taken in interpreting FP-fusion protein localization data when amyloid structures may be present. Given the pathological significance of amyloid-related species in some diseases, detection and inhibition of amyloid fibril formation using FPs can provide insights on developing diagnostic tools.

A method for identifying protein complexes with the features of joint co-localization and joint co-expression in static PPI networks

Identifying protein complexes in static protein-protein interaction (PPI) networks is essential for understanding the underlying mechanism of biological processes. Proteins in a complex are co-localized at the same place and co-expressed at the same time. We propose a novel method to identify protein complexes with the features of joint co-localization and joint co-expression in static PPI networks. To achieve this goal, we define a joint localization vector to construct a joint co-localization criterion of a protein group, and define a joint gene expression to construct a joint co-expression criterion of a gene group. Moreover, the functional similarity of proteins in a complex is an important characteristic. Thus, we use the CC-based, MF-based, and BP-based protein similarities to devise functional similarity criterion to determine whether a protein is functionally similar to a protein cluster. Based on the core-attachment structure and following to seed expanding strategy, we use four types of biological data including PPI data with reliability score, protein localization data, gene expression data, and gene ontology annotations, to identify protein complexes. The experimental results on yeast data show that comparing with existing methods our proposed method can efficiently and exactly identify more protein complexes, especially more protein complexes of sizes from 2 to 6. Furthermore, the enrichment analysis demonstrates that the protein complexes identified by our method have significant biological meaning.

Multiple marker abundance profiling: combining selected reaction monitoring and data‐dependent acquisition for rapid estimation of organelle abundance in subcellular samples

SummaryMeasuring changes in protein or organelle abundance in the cell is an essential, but challenging aspect of cell biology. Frequently‐used methods for determining organelle abundance typically rely on detection of a very few marker proteins, so are unsatisfactory. In silico estimates of protein abundances from publicly available protein spectra can provide useful standard abundance values but contain only data from tissue proteomes, and are not coupled to organelle localization data. A new protein abundance score, the normalized protein abundance scale (NPAS), expands on the number of scored proteins and the scoring accuracy of lower‐abundance proteins in Arabidopsis. NPAS was combined with subcellular protein localization data, facilitating quantitative estimations of organelle abundance during routine experimental procedures. A suite of targeted proteomics markers for subcellular compartment markers was developed, enabling independent verification of in silico estimates for relative organelle abundance. Estimation of relative organelle abundance was found to be reproducible and consistent over a range of tissues and growth conditions. In silico abundance estimations and localization data have been combined into an online tool, multiple marker abundance profiling, available in the SUBA4 toolbox (http://suba.live).

Loss-of-Function Analysis Elucidates Essential Roles of eIF4E Isoforms in Drosophila Spermatogenesis

Background: Through transcriptional and post-transcriptional regulation, eukaryotic cells can control gene expression to moderate vital cell processes and induce morphological changes. In developmental biology, translation initiation is emerging as a key player in gene expression regulation. Translation initiation begins when eukaryotic initiation factor 4E (eIF4E) binds the 5’ mRNA cap to recruit other initiation factors. Eight eIF4E isoforms are present in Drosophila melanogaster. The canonical eIF4E-1 is involved in the translation of all genes and is a common target for translational regulation mechanisms. The activity of testis-specific eIF4Es in Drosophila are largely unclear, but recent evidence on eIF4E-3 suggests that the other isoforms may also possess distinct, essential functions in spermatogenesis.
 Methods: Here we provide protein localization data and loss-of-function analysis to characterize eIF4E-4, eIF4E-5, and eIF4E-7.
 Results: Single KD showed few phenotypes, while eIF4E-4/eIF4E-5 double knockdown males had severe de- fects in spermatogenesis. In eIF4E-5/eIF4E-7 double knockdowns, mutations manifested in multiple stages of severity.
 Conclusions: The unique expression patterns and differential mutant phenotypes observed suggest that the testis-specific isoforms contain varying levels of functional redundancy. eIF4E-4 and eIF4E-5, which share close homology, appear to have overlapping roles in regulating germ cell division during early spermato- genesis. However, during spermatid individualization they seem to assume different functions. eIF4E-7 also appears to be involved in germ cell differentiation, but most likely in a separate mechanism due to the inability of other isoforms to compensate for its knockdown.

Signaling and Gene Regulatory Networks Governing Definitive Endoderm Derivation From Pluripotent Stem Cells.

The generation of definitive endoderm (DE) from pluripotent stem cells (PSCs) is a fundamental stage in the formation of highly organized visceral organs, such as the liver and pancreas. Currently, there is a need for a comprehensive study that illustrates the involvement of different signaling pathways and their interactions in the derivation of DE cells from PSCs. This study aimed to identify signaling pathways that have the greatest influence on DE formation using analyses of transcriptional profiles, protein-protein interactions, protein-DNA interactions, and protein localization data. Using this approach, signaling networks involved in DE formation were constructed using systems biology and data mining tools, and the validity of the predicted networks was confirmed experimentally by measuring the mRNA levels of hub genes in several PSCs-derived DE cell lines. Based on our analyses, seven signaling pathways, including the BMP, ERK1-ERK2, FGF, TGF-beta, MAPK, Wnt, and PIP signaling pathways and their interactions, were found to play a role in the derivation of DE cells from PSCs. Lastly, the core gene regulatory network governing this differentiation process was constructed. The results of this study could improve our understanding surrounding the efficient generation of DE cells for the regeneration of visceral organs. J. Cell. Physiol. 231: 1994-2006, 2016. © 2016 Wiley Periodicals, Inc.

Genetic organization of interphase chromosome bands and interbands in Drosophila melanogaster.

Drosophila melanogaster polytene chromosomes display specific banding pattern; the underlying genetic organization of this pattern has remained elusive for many years. In the present paper, we analyze 32 cytology-mapped polytene chromosome interbands. We estimated molecular locations of these interbands, described their molecular and genetic organization and demonstrate that polytene chromosome interbands contain the 5′ ends of housekeeping genes. As a rule, interbands display preferential “head-to-head” orientation of genes. They are enriched for “broad” class promoters characteristic of housekeeping genes and associate with open chromatin proteins and Origin Recognition Complex (ORC) components. In two regions, 10A and 100B, coding sequences of genes whose 5′-ends reside in interbands map to constantly loosely compacted, early-replicating, so-called “grey” bands. Comparison of expression patterns of genes mapping to late-replicating dense bands vs genes whose promoter regions map to interbands shows that the former are generally tissue-specific, whereas the latter are represented by ubiquitously active genes. Analysis of RNA-seq data (modENCODE-FlyBase) indicates that transcripts from interband-mapping genes are present in most tissues and cell lines studied, across most developmental stages and upon various treatment conditions. We developed a special algorithm to computationally process protein localization data generated by the modENCODE project and show that Drosophila genome has about 5700 sites that demonstrate all the features shared by the interbands cytologically mapped to date.

Predicting Yeast Protein Localization Sites by a New Clustering Algorithm Based on Weighted Feature Ensemble

The analysis of protein localization sites is an important task in bioinformatics. Predicting the yeast protein localization sites is a promising domain among numerous research methods based on the yeast protein measurement data which have multiple indexes/features. In order to reflect the different contributions of those features to predicting tasks, a clustering algorithm based on weighted feature ensemble (WFE) is proposed to predict yeast protein localization sites on the basis of the gathered yeast protein localization data. WFE process firstly assigns different weights to features, and then the results are computed and presented to obtain the best outcome. Experimental results on our algorithm based on WFE and other several clustering algorithms based on the ideas of weighted features have shown that our new algorithm outperformed the other feature weighting type algorithms in accuracy and stability.

Enhancing a Pathway-Genome Database (PGDB) to capture subcellular localization of metabolites and enzymes: the nucleotide-sugar biosynthetic pathways of Populus trichocarpa

Understanding how cellular metabolism works and is regulated requires that the underlying biochemical pathways be adequately represented and integrated with large metabolomic data sets to establish a robust network model. Genetically engineering energy crops to be less recalcitrant to saccharification requires detailed knowledge of plant polysaccharide structures and a thorough understanding of the metabolic pathways involved in forming and regulating cell-wall synthesis. Nucleotide-sugars are building blocks for synthesis of cell wall polysaccharides. The biosynthesis of nucleotide-sugars is catalyzed by a multitude of enzymes that reside in different subcellular organelles, and precise representation of these pathways requires accurate capture of this biological compartmentalization. The lack of simple localization cues in genomic sequence data and annotations however leads to missing compartmentalization information for eukaryotes in automatically generated databases, such as the Pathway-Genome Databases (PGDBs) of the SRI Pathway Tools software that drives much biochemical knowledge representation on the internet. In this report, we provide an informal mechanism using the existing Pathway Tools framework to integrate protein and metabolite sub-cellular localization data with the existing representation of the nucleotide-sugar metabolic pathways in a prototype PGDB for Populus trichocarpa. The enhanced pathway representations have been successfully used to map SNP abundance data to individual nucleotide-sugar biosynthetic genes in the PGDB. The manually curated pathway representations are more conducive to the construction of a computational platform that will allow the simulation of natural and engineered nucleotide-sugar precursor fluxes into specific recalcitrant polysaccharide(s).Database URL: The curated Populus PGDB is available in the BESC public portal at http://cricket.ornl.gov/cgi-bin/beocyc_home.cgi and the nucleotide-sugar biosynthetic pathways can be directly accessed at http://cricket.ornl.gov:1555/PTR/new-image?object=SUGAR-NUCLEOTIDES.

The development and geometry of shape change in Arabidopsis thaliana cotyledon pavement cells.

BackgroundThe leaf epidermis is an important architectural control element that influences the growth properties of underlying tissues and the overall form of the organ. In dicots, interdigitated pavement cells are the building blocks of the tissue, and their morphogenesis includes the assembly of specialized cell walls that surround the apical, basal, and lateral (anticlinal) cell surfaces. The microtubule and actin cytoskeletons are highly polarized along the cortex of the anticlinal wall; however, the relationships between these arrays and cell morphogenesis are unclear.ResultsWe developed new quantitative tools to compare population-level growth statistics with time-lapse imaging of cotyledon pavement cells in an intact tissue. The analysis revealed alternating waves of lobe initiation and a phase of lateral isotropic expansion that persisted for days. During lateral isotropic diffuse growth, microtubule organization varied greatly between cell surfaces. Parallel microtubule bundles were distributed unevenly along the anticlinal surface, with subsets marking stable cortical domains at cell indentations and others clearly populating the cortex within convex cell protrusions.ConclusionsPavement cell morphogenesis is discontinuous, and includes punctuated phases of lobe initiation and lateral isotropic expansion. In the epidermis, lateral isotropic growth is independent of pavement cell size and shape. Cortical microtubules along the upper cell surface and stable cortical patches of anticlinal microtubules may coordinate the growth behaviors of orthogonal cell walls. This work illustrates the importance of directly linking protein localization data to the growth behavior of leaf epidermal cells.

Layered Functional Network Analysis of Gene Expression in Human Heart Failure

BackgroundAlthough dilated cardiomyopathy (DCM) is a leading cause of heart failure (HF), the mechanism underlying DCM is not well understood. Previously, it has been demonstrated that an integrative analysis of gene expression and protein-protein interaction (PPI) networks can provide insights into the molecular mechanisms of various diseases. In this study we develop a systems approach by linking public available gene expression data on ischemic dilated cardiomyopathy (ICM), a main pathological form of DCM, with data from a layered PPI network. We propose that the use of a layered PPI network, as opposed to a traditional PPI network, provides unique insights into the mechanism of DCM.MethodsFour Cytoscape plugins including BionetBuilder, NetworkAnalyzer, Cerebral and GenePro were used to establish the layered PPI network, which was based upon validated subcellular protein localization data retrieved from the HRPD and Entrez Gene databases. The DAVID function annotation clustering tool was used for gene ontology (GO) analysis.ResultsThe assembled layered PPI network was divided into four layers: extracellular, plasma membrane, cytoplasm and nucleus. The characteristics of the gene expression pattern of the four layers were compared. In the extracellular and plasma membrane layers, there were more proteins encoded by down-regulated genes than by up-regulated genes, but in the other two layers, the opposite trend was found. GO analysis established that proteins encoded by up-regulated genes, reflecting significantly over-represented biological processes, were mainly located in the nucleus and cytoplasm layers, while proteins encoded by down-regulated genes were mainly located in the extracellular and plasma membrane layers. The PPI network analysis revealed that the Janus family tyrosine kinase-signal transducer and activator of transcription (Jak-STAT) signaling pathway might play an important role in the development of ICM and could be exploited as a therapeutic target of ICM. In addition, glycogen synthase kinase 3 beta (GSK3B) may also be a potential candidate target, but more evidence is required.ConclusionThis study illustrated that by incorporating subcellular localization information into a PPI network based analysis, one can derive greater insights into the mechanisms underlying ICM.

New transposons to generate GFP protein fusions in Candida albicans

Transposon elements are important tools for gene function analysis, for example they can be used to easily create genome-wide collections of insertion mutants. Transposons may also carry sequences coding for an epitope or fluorescent marker useful for protein expression and localization analysis. We have developed three new Tn5-based transposons that incorporate a GFP (green fluorescent protein) coding sequence to generate fusion proteins in the important fungal pathogen Candida albicans. Each transposon also contains the URA3 and Kan R genes for yeast and bacterial selection, respectively. After in vitro transposition, the insertional allele is transferred to the chromosomal locus by homologous recombination. Transposons Tn5-CaGFP and Tn5-CaGFP-URA3::FLIP can generate C-terminal truncated GFP fusions. A URA3 flipper recycling cassette was incorporated into the transposon Tn5-CaGFP-URA3::FLIP. After the induction of Flip recombinase to excise the marker, the heterozygous strain is transformed again in order to obtain a GFP-tagged homozygous strains. In the Tn5-CaGFP-FL transposon the markers are flanked by a rare-cutting enzyme. After in vitro transposition into a plasmid-borne target gene, the markers are eliminated by restriction digestion and religation, resulting in a construct coding for full-length GFP-fusion proteins. This transposon can generate plasmid libraries of GFP insertions in proteins where N- or C-terminal tagging may alter localization. We tested our transposon system by mutagenizing the essential septin CDC3 gene. The results indicate that the Cdc3 C-terminal extension is important for correct septin filament assembly. The transposons described here provide a new system to obtain global gene expression and protein localization data in C. albicans.

Connecting protein structure with predictions of regulatory sites

A common task posed by microarray experiments is to infer the binding site preferences for a known transcription factor from a collection of genes that it regulates and to ascertain whether the factor acts alone or in a complex. The converse problem can also be posed: Given a collection of binding sites, can the regulatory factor or complex of factors be inferred? Both tasks are substantially facilitated by using relatively simple homology models for protein-DNA interactions, as well as the rapidly expanding protein structure database. For budding yeast, we are able to construct reliable structural models for 67 transcription factors and with them redetermine factor binding sites by using a Bayesian Gibbs sampling algorithm and an extensive protein localization data set. For 49 factors in common with a prior analysis of this data set (based largely on phylogenetic conservation), we find that half of the previously predicted binding motifs are in need of some revision. We also solve the inverse problem of ascertaining the factors from the binding sites by assigning a correct protein fold to 25 of the 49 cases from a previous study. Our approach is easily extended to other organisms, including higher eukaryotes. Our study highlights the utility of enlarging current structural genomics projects that exhaustively sample fold structure space to include all factors with significantly different DNA-binding specificities.

Probabilistic Protein Function Prediction from Heterogeneous Genome-Wide Data

Dramatic improvements in high throughput sequencing technologies have led to a staggering growth in the number of predicted genes. However, a large fraction of these newly discovered genes do not have a functional assignment. Fortunately, a variety of novel high-throughput genome-wide functional screening technologies provide important clues that shed light on gene function. The integration of heterogeneous data to predict protein function has been shown to improve the accuracy of automated gene annotation systems. In this paper, we propose and evaluate a probabilistic approach for protein function prediction that integrates protein-protein interaction (PPI) data, gene expression data, protein motif information, mutant phenotype data, and protein localization data. First, functional linkage graphs are constructed from PPI data and gene expression data, in which an edge between nodes (proteins) represents evidence for functional similarity. The assumption here is that graph neighbors are more likely to share protein function, compared to proteins that are not neighbors. The functional linkage graph model is then used in concert with protein domain, mutant phenotype and protein localization data to produce a functional prediction. Our method is applied to the functional prediction of Saccharomyces cerevisiae genes, using Gene Ontology (GO) terms as the basis of our annotation. In a cross validation study we show that the integrated model increases recall by 18%, compared to using PPI data alone at the 50% precision. We also show that the integrated predictor is significantly better than each individual predictor. However, the observed improvement vs. PPI depends on both the new source of data and the functional category to be predicted. Surprisingly, in some contexts integration hurts overall prediction accuracy. Lastly, we provide a comprehensive assignment of putative GO terms to 463 proteins that currently have no assigned function.

P-Body Components, microRNA Regulation, and Synaptic Plasticity

What is the protein apparatus required for microRNA (miRNA) function and translational repression in neurons? This article reviews our recent work on Me31B, a conserved P-body protein present on Staufen-containing neuronal and maternal ribonucleoprotein (RNP) particles, which is required for dendrite morphogenesis and miRNA function in vivo. In addition, it provides new data to show that Me31B is present on and regulates formation of P-bodies in the Drosophila wing disc, where it has a general role in the regulation of miRNA function. While illuminating the function of this important RNA regulatory molecule, it also brings into focus a hypothesis of potentially broad significance. Namely, that P-body proteins may play important roles in regulation of dendrite-localized mRNAs and, thereby, in synaptic plasticity. A wide range of protein localization and early functional data support this hypothesis. We also discuss current knowledge of RNP particles that mediate translational repression and the implications of these findings for understanding translational control in neurons.

The Plant Structure Ontology, a Unified Vocabulary of Anatomy and Morphology of a Flowering Plant

Formal description of plant phenotypes and standardized annotation of gene expression and protein localization data require uniform terminology that accurately describes plant anatomy and morphology. This facilitates cross species comparative studies and quantitative comparison of phenotypes and expression patterns. A major drawback is variable terminology that is used to describe plant anatomy and morphology in publications and genomic databases for different species. The same terms are sometimes applied to different plant structures in different taxonomic groups. Conversely, similar structures are named by their species-specific terms. To address this problem, we created the Plant Structure Ontology (PSO), the first generic ontological representation of anatomy and morphology of a flowering plant. The PSO is intended for a broad plant research community, including bench scientists, curators in genomic databases, and bioinformaticians. The initial releases of the PSO integrated existing ontologies for Arabidopsis (Arabidopsis thaliana), maize (Zea mays), and rice (Oryza sativa); more recent versions of the ontology encompass terms relevant to Fabaceae, Solanaceae, additional cereal crops, and poplar (Populus spp.). Databases such as The Arabidopsis Information Resource, Nottingham Arabidopsis Stock Centre, Gramene, MaizeGDB, and SOL Genomics Network are using the PSO to describe expression patterns of genes and phenotypes of mutants and natural variants and are regularly contributing new annotations to the Plant Ontology database. The PSO is also used in specialized public databases, such as BRENDA, GENEVESTIGATOR, NASCArrays, and others. Over 10,000 gene annotations and phenotype descriptions from participating databases can be queried and retrieved using the Plant Ontology browser. The PSO, as well as contributed gene associations, can be obtained at www.plantontology.org.

Organelle DB: an updated resource of eukaryotic protein localization and function

Organelle DB () is a web-accessible relational database presenting a supplemented catalog of organelle-localized proteins and major protein complexes. Since its release in 2004, Organelle DB has grown by 20% to encompass over 30 000 proteins from 138 eukaryotic organisms. Each protein in Organelle DB is presented with its subcellular localization, primary sequence and a detailed description of its function, as available. All records in Organelle DB have been annotated using controlled vocabulary from the Gene Ontology consortium. Protein localization data are inherently visual, and Organelle DB is a significant repository of biological images, housing 1500 micrographs of yeast cells carrying stained proteins. Furthermore, we report here the development of Organelle View, an extension of Organelle DB for the interactive visualization of organelles and subcellular structures in the budding yeast Saccharomyces cerevisiae. Organelle View offers a dimensional representation of a yeast cell; users can search Organelle View for proteins of interest, and the organelles housing these proteins will be highlighted in the cell image. Among other applications, Organelle View may serve as an educational aid engaging introductory biology students through a visually ‘fun’ interface. Organelle View can be accessed from the Organelle DB home page or directly at .