Akt and 14-3-3 control a PACS-2 homeostatic switch that integrates membrane traffic with TRAIL-induced apoptosis.

TRAIL selectively kills diseased cells in vivo, spurring interest in this death ligand as a potential therapeutic. However, many cancer cells are resistant to TRAIL, suggesting the mechanism mediating TRAIL-induced apoptosis is complex. Here we identify PACS-2 as an essential TRAIL effector, required for killing tumor cells in vitro and virally infected hepatocytes in vivo. PACS-2 is phosphorylated at Ser437 in vivo, and pharmacologic and genetic studies demonstrate Akt is an in vivo Ser437 kinase. Akt cooperates with 14-3-3 to regulate the homeostatic and apoptotic properties of PACS-2 that mediate TRAIL action. Phosphorylated Ser437 binds 14-3-3 with high affinity, which represses PACS-2 apoptotic activity and is required for PACS-2 to mediate trafficking of membrane cargo. TRAIL triggers dephosphorylation of Ser437, reprogramming PACS-2 to promote apoptosis. Together, these studies identify the phosphorylation state of PACS-2 Ser437 as a molecular switch that integrates cellular homeostasis with TRAIL-induced apoptosis.

Generating Clinical-Grade Gene-Disease Validity Classifications Through the ClinGen Data Platforms.

Clinical genetic laboratories must have access to clinically validated biomedical data for precision medicine. A lack of accessibility, normalized structure, and consistency in evaluation complicates interpretation of disease causality, resulting in confusion in assessing the clinical validity of genes and genetic variants for diagnosis. A key goal of the Clinical Genome Resource (ClinGen) is to fill the knowledge gap concerning the strength of evidence supporting the role of a gene in a monogenic disease, which is achieved through a process known as Gene-Disease Validity curation. Here we review the work of ClinGen in developing a curation infrastructure that supports the standardization, harmonization, and dissemination of Gene-Disease Validity data through the creation of frameworks and the utilization of common data standards. This infrastructure is based on several applications, including the ClinGen GeneTracker, Gene Curation Interface, Data Exchange, GeneGraph, and website.

Association with endoplasmic reticulum promotes proteasomal degradation of GADD34 protein.

Stress-induced endogenous and ectopically expressed GADD34 proteins were present both in the cytoplasm and in membranes, with their membrane association showing similar biochemical properties. Deletion of N-terminal sequences in GADD34-GFP proteins highlighted an amphipathic helix, whose hydrophobic surface, specifically valine 25 and leucine 29, mediated endoplasmic reticulum (ER) localization. Substitution of leucines for three arginines on the polar surface indicated that the same helix also mediated the association of GADD34 with mitochondria. Fluorescence protease protection and chemical modification of cysteines substituted in the membrane-binding domain pointed to a monotopic insertion of GADD34 into the outer layer of the ER membrane. Fluorescence recovery after photobleaching showed that ER association retards the mobility of GADD34 in living cells. Both WT GADD34 and the mutant, V25R, effectively scaffolded the α-isoform of protein phosphatase-1 (PP1α) and enabled eIF2α dephosphorylation. However, the largely cytosolic V25R protein displayed a reduced rate of proteasomal degradation, and unlike WT GADD34, whose ectopic expression resulted in a dilated or distended ER, V25R did not modify ER morphology. These studies suggested that the association of with ER modulates intracellular trafficking and proteasomal degradation of GADD34, and in turn, its ability to modify ER morphology.

Standardization of assay representation in the Ontology for Biomedical Investigations.

The Ontology for Biomedical Investigations (OBI) underwent a focused review of assay term annotations, logic and hierarchy with a goal to improve and standardize these terms. As a result, inconsistencies in W3C Web Ontology Language (OWL) expressions were identified and corrected, and additionally, standardized design patterns and a formalized template to maintain them were developed. We describe here this informative and productive process to describe the specific benefits and obstacles for OBI and the universal lessons for similar projects.

GA4GH: International policies and standards for data sharing across genomic research and healthcare.

The Global Alliance for Genomics and Health (GA4GH) aims to accelerate biomedical advances by enabling the responsible sharing of clinical and genomic data through both harmonized data aggregation and federated approaches. The decreasing cost of genomic sequencing (along with other genome-wide molecular assays) and increasing evidence of its clinical utility will soon drive the generation of sequence data from tens of millions of humans, with increasing levels of diversity. In this perspective, we present the GA4GH strategies for addressing the major challenges of this data revolution. We describe the GA4GH organization, which is fueled by the development efforts of eight Work Streams and informed by the needs of 24 Driver Projects and other key stakeholders. We present the GA4GH suite of secure, interoperable technical standards and policy frameworks and review the current status of standards, their relevance to key domains of research and clinical care, and future plans of GA4GH. Broad international participation in building, adopting, and deploying GA4GH standards and frameworks will catalyze an unprecedented effort in data sharing that will be critical to advancing genomic medicine and ensuring that all populations can access its benefits.

Representing glycophenotypes: semantic unification of glycobiology resources for disease discovery.

While abnormalities related to carbohydrates (glycans) are frequent for patients with rare and undiagnosed diseases as well as in many common diseases, these glycan-related phenotypes (glycophenotypes) are not well represented in knowledge bases (KBs). If glycan-related diseases were more robustly represented and curated with glycophenotypes, these could be used for molecular phenotyping to help to realize the goals of precision medicine. Diagnosis of rare diseases by computational cross-species comparison of genotype-phenotype data has been facilitated by leveraging ontological representations of clinical phenotypes, using Human Phenotype Ontology (HPO), and model organism ontologies such as Mammalian Phenotype Ontology (MP) in the context of the Monarch Initiative. In this article, we discuss the importance and complexity of glycobiology and review the structure of glycan-related content from existing KBs and biological ontologies. We show how semantically structuring knowledge about the annotation of glycophenotypes could enhance disease diagnosis, and propose a solution to integrate glycophenotypes and related diseases into the Unified Phenotype Ontology (uPheno), HPO, Monarch and other KBs. We encourage the community to practice good identifier hygiene for glycans in support of semantic analysis, and clinicians to add glycomics to their diagnostic analyses of rare diseases.

Developing a vocabulary and ontology for modeling insect natural history data: example data, use cases, and competency questions.

Insects are possibly the most taxonomically and ecologically diverse class of multicellular organisms on Earth. Consequently, they provide nearly unlimited opportunities to develop and test ecological and evolutionary hypotheses. Currently, however, large-scale studies of insect ecology, behavior, and trait evolution are impeded by the difficulty in obtaining and analyzing data derived from natural history observations of insects. These data are typically highly heterogeneous and widely scattered among many sources, which makes developing robust information systems to aggregate and disseminate them a significant challenge. As a step towards this goal, we report initial results of a new effort to develop a standardized vocabulary and ontology for insect natural history data. In particular, we describe a new database of representative insect natural history data derived from multiple sources (but focused on data from specimens in biological collections), an analysis of the abstract conceptual areas required for a comprehensive ontology of insect natural history data, and a database of use cases and competency questions to guide the development of data systems for insect natural history data. We also discuss data modeling and technology-related challenges that must be overcome to implement robust integration of insect natural history data.

Growth arrest and DNA damage-inducible protein GADD34 targets protein phosphatase 1 alpha to the endoplasmic reticulum and promotes dephosphorylation of the alpha subunit of eukaryotic translation initiation factor 2.

The growth arrest and DNA damage-inducible protein, GADD34, associates with protein phosphatase 1 (PP1) and promotes in vitro dephosphorylation of the alpha subunit of eukaryotic translation initiation factor 2, (eIF-2 alpha). In this report, we show that the expression of human GADD34 in cultured cells reversed eIF-2 alpha phosphorylation induced by thapsigargin and tunicamycin, agents that promote protein unfolding in the endoplasmic reticulum (ER). GADD34 expression also reversed eIF-2 alpha phosphorylation induced by okadaic acid but not that induced by another phosphatase inhibitor, calyculin A (CA), which is a result consistent with PP1 being a component of the GADD34-assembled eIF-2 alpha phosphatase. Structure-function studies identified a bipartite C-terminal domain in GADD34 that encompassed a canonical PP1-binding motif, KVRF, and a novel RARA sequence, both of which were required for PP1 binding. N-terminal deletions of GADD34 established that while PP1 binding was necessary, it was not sufficient to promote eIF-2 alpha dephosphorylation in cells. Imaging of green fluorescent protein (GFP)-GADD34 proteins showed that the N-terminal 180 residues directed the localization of GADD34 at the ER and that GADD34 targeted the alpha isoform of PP1 to the ER. These data provide new insights into the mode of action of GADD34 in assembling an ER-associated eIF-2 alpha phosphatase that regulates protein translation in mammalian cells.

Identification of cellular protein phosphatase-1 regulators.

Protein phosphatase-1 (PP1) is a major phosphoserine/phosphothreonine phosphatase that regulates multiple physiological events in all eukaryotic cells. Action of PP1 in cells is dictated by the association of PP1 catalytic subunit with one or more regulatory subunits that define both its catalytic function and subcellular localization. This chapter describes key methods used to identify PP1-binding proteins and assess their ability to modulate PP1 functions in mammalian cells. These methods include affinity isolation of cellular PP1 complexes, analysis of direct PP1 binding, modulation of PP (protein phosphatase) activity, and testing for the presence of the newly identified PP1 complex in cells and cellular compartments. Together these techniques set the foundation for further studies that can establish the physiological significance of this PP1 complex.

PDX-MI: Minimal Information for Patient-Derived Tumor Xenograft Models.

Patient-derived tumor xenograft (PDX) mouse models have emerged as an important oncology research platform to study tumor evolution, mechanisms of drug response and resistance, and tailoring chemotherapeutic approaches for individual patients. The lack of robust standards for reporting on PDX models has hampered the ability of researchers to find relevant PDX models and associated data. Here we present the PDX models minimal information standard (PDX-MI) for reporting on the generation, quality assurance, and use of PDX models. PDX-MI defines the minimal information for describing the clinical attributes of a patient's tumor, the processes of implantation and passaging of tumors in a host mouse strain, quality assurance methods, and the use of PDX models in cancer research. Adherence to PDX-MI standards will facilitate accurate search results for oncology models and their associated data across distributed repository databases and promote reproducibility in research studies using these models. Cancer Res; 77(21); e62-66. ©2017 AACR.

The Cell Ontology 2016: enhanced content, modularization, and ontology interoperability.

BACKGROUND: The Cell Ontology (CL) is an OBO Foundry candidate ontology covering the domain of canonical, natural biological cell types. Since its inception in 2005, the CL has undergone multiple rounds of revision and expansion, most notably in its representation of hematopoietic cells. For in vivo cells, the CL focuses on vertebrates but provides general classes that can be used for other metazoans, which can be subtyped in species-specific ontologies. CONSTRUCTION AND CONTENT: Recent work on the CL has focused on extending the representation of various cell types, and developing new modules in the CL itself, and in related ontologies in coordination with the CL. For example, the Kidney and Urinary Pathway Ontology was used as a template to populate the CL with additional cell types. In addition, subtypes of the class 'cell in vitro' have received improved definitions and labels to provide for modularity with the representation of cells in the Cell Line Ontology and Reagent Ontology. Recent changes in the ontology development methodology for CL include a switch from OBO to OWL for the primary encoding of the ontology, and an increasing reliance on logical definitions for improved reasoning. UTILITY AND DISCUSSION: The CL is now mandated as a metadata standard for large functional genomics and transcriptomics projects, and is used extensively for annotation, querying, and analyses of cell type specific data in sequencing consortia such as FANTOM5 and ENCODE, as well as for the NIAID ImmPort database and the Cell Image Library. The CL is also a vital component used in the modular construction of other biomedical ontologies-for example, the Gene Ontology and the cross-species anatomy ontology, Uberon, use CL to support the consistent representation of cell types across different levels of anatomical granularity, such as tissues and organs. CONCLUSIONS: The ongoing improvements to the CL make it a valuable resource to both the OBO Foundry community and the wider scientific community, and we continue to experience increased interest in the CL both among developers and within the user community.

The Ontology for Biomedical Investigations.

The Ontology for Biomedical Investigations (OBI) is an ontology that provides terms with precisely defined meanings to describe all aspects of how investigations in the biological and medical domains are conducted. OBI re-uses ontologies that provide a representation of biomedical knowledge from the Open Biological and Biomedical Ontologies (OBO) project and adds the ability to describe how this knowledge was derived. We here describe the state of OBI and several applications that are using it, such as adding semantic expressivity to existing databases, building data entry forms, and enabling interoperability between knowledge resources. OBI covers all phases of the investigation process, such as planning, execution and reporting. It represents information and material entities that participate in these processes, as well as roles and functions. Prior to OBI, it was not possible to use a single internally consistent resource that could be applied to multiple types of experiments for these applications. OBI has made this possible by creating terms for entities involved in biological and medical investigations and by importing parts of other biomedical ontologies such as GO, Chemical Entities of Biological Interest (ChEBI) and Phenotype Attribute and Trait Ontology (PATO) without altering their meaning. OBI is being used in a wide range of projects covering genomics, multi-omics, immunology, and catalogs of services. OBI has also spawned other ontologies (Information Artifact Ontology) and methods for importing parts of ontologies (Minimum information to reference an external ontology term (MIREOT)). The OBI project is an open cross-disciplinary collaborative effort, encompassing multiple research communities from around the globe. To date, OBI has created 2366 classes and 40 relations along with textual and formal definitions. The OBI Consortium maintains a web resource (http://obi-ontology.org) providing details on the people, policies, and issues being addressed in association with OBI. The current release of OBI is available at http://purl.obolibrary.org/obo/obi.owl.

CLO: The cell line ontology.

BACKGROUND: Cell lines have been widely used in biomedical research. The community-based Cell Line Ontology (CLO) is a member of the OBO Foundry library that covers the domain of cell lines. Since its publication two years ago, significant updates have been made, including new groups joining the CLO consortium, new cell line cells, upper level alignment with the Cell Ontology (CL) and the Ontology for Biomedical Investigation, and logical extensions. CONSTRUCTION AND CONTENT: Collaboration among the CLO, CL, and OBI has established consensus definitions of cell line-specific terms such as 'cell line', 'cell line cell', 'cell line culturing', and 'mortal' vs. 'immortal cell line cell'. A cell line is a genetically stable cultured cell population that contains individual cell line cells. The hierarchical structure of the CLO is built based on the hierarchy of the in vivo cell types defined in CL and tissue types (from which cell line cells are derived) defined in the UBERON cross-species anatomy ontology. The new hierarchical structure makes it easier to browse, query, and perform automated classification. We have recently added classes representing more than 2,000 cell line cells from the RIKEN BRC Cell Bank to CLO. Overall, the CLO now contains ~38,000 classes of specific cell line cells derived from over 200 in vivo cell types from various organisms. UTILITY AND DISCUSSION: The CLO has been applied to different biomedical research studies. Example case studies include annotation and analysis of EBI ArrayExpress data, bioassays, and host-vaccine/pathogen interaction. CLO's utility goes beyond a catalogue of cell line types. The alignment of the CLO with related ontologies combined with the use of ontological reasoners will support sophisticated inferencing to advance translational informatics development.

On the reproducibility of science: unique identification of research resources in the biomedical literature.

Scientific reproducibility has been at the forefront of many news stories and there exist numerous initiatives to help address this problem. We posit that a contributor is simply a lack of specificity that is required to enable adequate research reproducibility. In particular, the inability to uniquely identify research resources, such as antibodies and model organisms, makes it difficult or impossible to reproduce experiments even where the science is otherwise sound. In order to better understand the magnitude of this problem, we designed an experiment to ascertain the "identifiability" of research resources in the biomedical literature. We evaluated recent journal articles in the fields of Neuroscience, Developmental Biology, Immunology, Cell and Molecular Biology and General Biology, selected randomly based on a diversity of impact factors for the journals, publishers, and experimental method reporting guidelines. We attempted to uniquely identify model organisms (mouse, rat, zebrafish, worm, fly and yeast), antibodies, knockdown reagents (morpholinos or RNAi), constructs, and cell lines. Specific criteria were developed to determine if a resource was uniquely identifiable, and included examining relevant repositories (such as model organism databases, and the Antibody Registry), as well as vendor sites. The results of this experiment show that 54% of resources are not uniquely identifiable in publications, regardless of domain, journal impact factor, or reporting requirements. For example, in many cases the organism strain in which the experiment was performed or antibody that was used could not be identified. Our results show that identifiability is a serious problem for reproducibility. Based on these results, we provide recommendations to authors, reviewers, journal editors, vendors, and publishers. Scientific efficiency and reproducibility depend upon a research-wide improvement of this substantial problem in science today.

Control of cellular GADD34 levels by the 26S proteasome.

GADD34, the product of a growth arrest and DNA damage-inducible gene, is expressed at low levels in unstressed cells. In response to stress, the cellular content of GADD34 protein increases and, on termination of stress, rapidly declines. We investigated the mechanisms that control GADD34 levels in human cells. GADD34 proteins containing either an internal FLAG or a C-terminal green fluorescent protein epitope were degraded at rates similar to endogenous GADD34. However, the addition of epitopes at the N terminus or deletion of N-terminal sequences stabilized GADD34. N-terminal peptides of GADD34, either alone or fused to heterologous proteins, exhibited rapid degradation similar to wild-type GADD34, thereby identifying an N-terminal degron. Deletion of internal PEST repeats had no impact on GADD34 stability but modulated the binding and activity of protein phosphatase 1. Proteasomal but not lysosomal inhibitors enhanced GADD34 stability and eukaryotic initiation factor 2alpha (eIF-2alpha) dephosphorylation, a finding consistent with GADD34's role in assembling an eIF-2alpha phosphatase. GADD34 was polyubiquitinated, and this modification enhanced its turnover in cells. A stabilized form of GADD34 promoted the accumulation and aggregation of the mutant cystic fibrosis transmembrane conductance regulator (CFTRDeltaF508), highlighting the physiological importance of GADD34 turnover in protein processing in the endoplasmic reticulum and the potential impact of prolonged GADD34 expression in human disease.

ROCK1 phosphorylates and activates zipper-interacting protein kinase.

Zipper-interacting protein kinase (ZIPK) regulates Ca(2+)-independent phosphorylation of both smooth muscle (to regulate contraction) and non-muscle myosin (to regulate non-apoptotic cell death) through either phosphorylation and inhibition of myosin phosphatase, the myosin phosphatase inhibitor CPI17, or direct phosphorylation of myosin light chain. ZIPK is regulated by multisite phosphorylation. Phosphorylation at least three sites Thr-180, Thr-225, and Thr-265 has been shown to be essential for full activity, whereas phosphorylation at Thr-299 regulates its intracellular localization. Herein we utilized an unbiased proteomics screen of smooth muscle extracts with synthetic peptides derived from the sequence of the regulatory phosphorylation sites of the enzyme to identify the protein kinases that might regulate ZIPK activity in vivo. Discrete kinase activities toward Thr-265 and Thr-299 were defined and identified by mass spectrometry as Rho kinase 1 (ROCK1). In vitro, ROCK1 showed a high degree of substrate specificity toward native ZIPK, both stoichiometrically phosphorylating the enzyme at Thr-265 and Thr-299 as well as bringing about activation. In HeLa cells, coexpression of ZIPK with ROCK1 altered the ROCK-induced phenotype of focused stress fiber pattern to a Rho-like phenotype of parallel stress fiber pattern. This effect was also dependent upon phosphorylation at Thr-265. Our findings provide a new regulatory pathway in smooth muscle and non-muscle cells whereby ROCK1 phosphorylates and regulates ZIP kinase.

Deactylase inhibitors disrupt cellular complexes containing protein phosphatases and deacetylases.

Affinity isolation of protein serine/threonine phosphatases on the immobilized phosphatase inhibitor microcystin-LR identified histone deacetylase 1(HDAC1), HDAC6, and HDAC10 as novel components of cellular phosphatase complexes. Other HDACs, specifically HDAC2, -3, -4, and -5, were excluded from such complexes. In vitro biochemical studies showed that recombinant HDAC6, but not HDAC4, bound directly to the protein phosphatase (PP)1 catalytic subunit. No association was observed between HDAC6 and PP2A, another major protein phosphatase. PP1 binding was mapped to the second catalytic domain and adjacent C-terminal sequences in HDAC6, and treatment of cells with trichostatin A (TSA) disrupted endogenous HDAC6.PP1 complexes. Consistent with the inhibition of tubulin deactylase activity of HDAC6, TSA enhanced cellular tubulin acetylation, and acetylated tubulin was present in the PP1 complexes from TSA-treated cells. Trapoxin B, a weak HDAC6 inhibitor, and calyculin A, a cell-permeable phosphatase inhibitor, had no effect on the stability of the HDAC6.PP1 complexes or on tubulin acetylation. Mutations that inactivated HDAC6 prevented its incorporation into cellular PP1 complexes and suggested that when bound together both enzymes were active. Interestingly, TSA disrupted all the cellular HDAC.phosphatase complexes analyzed. This study provided new insight into the mechanism by which HDAC inhibitors elicited coordinate changes in cellular protein phosphorylation and acetylation and suggested that changes in these protein modifications at multiple subcellular sites may contribute to the known ability of HDAC inhibitors to suppress cell growth and transformation.