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  • Articles  (148)
  • Oxford University Press  (148)
  • American Institute of Physics (AIP)
  • Medicine  (148)
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  • Articles  (148)
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  • 1
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    INstruct: a database of high-quality 3D structurally resolved protein interactome networks (2013)
    Oxford University Press
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    Publication Date: 2013-06-06
    Description: : INstruct is a database of high-quality, 3D, structurally resolved protein interactome networks in human and six model organisms. INstruct combines the scale of available high-quality binary protein interaction data with the specificity of atomic-resolution structural information derived from co-crystal evidence using a tested interaction interface inference method. Its web interface is designed to allow for flexible search based on standard and organism-specific protein and gene-naming conventions, visualization of protein architecture highlighting interaction interfaces and viewing and downloading custom 3D structurally resolved interactome datasets. Availability: INstruct is freely available on the web at http://instruct.yulab.org with all major browsers supported. Contact: haiyuan.yu@cornell.edu Supplementary information: Supplementary data are available at Bioinformatics online.
    Print ISSN: 1367-4803
    Electronic ISSN: 1460-2059
    Topics: Biology , Computer Science , Medicine
    Published by Oxford University Press
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  • 2
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    Molecular mechanism of CHRDL1-mediated X-linked megalocornea in humans and in Xenopus model (2015)
    Oxford University Press
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    Publication Date: 2015-05-09
    Description: Chordin-Like 1 ( CHRDL1 ) mutations cause non-syndromic X-linked megalocornea (XMC) characterized by enlarged anterior eye segments. Mosaic corneal degeneration, presenile cataract and secondary glaucoma are associated with XMC. Beside that CHRDL1 encodes Ventroptin, a secreted bone morphogenetic protein (BMP) antagonist, the molecular mechanism of XMC is not well understood yet. In a family with broad phenotypic variability of XMC, we identified the novel CHRDL1 frameshift mutation c.807_808delTC [p.H270Wfs*22] presumably causing CHRDL1 loss of function. Using Xenopus laevis as model organism, we demonstrate that chrdl1 is specifically expressed in the ocular tissue at late developmental stages. The chrdl1 knockdown directly resembles the human XMC phenotype and confirms CHRDL1 deficiency to cause XMC. Interestingly, secondary to this bmp4 is down-regulated in the Xenopus eyes. Moreover, phospho-SMAD1/5 is altered and BMP receptor 1A is reduced in a XMC patient. Together, we classify these observations as negative-feedback regulation due to the deficient BMP antagonism in XMC. As CHRDL1 is preferentially expressed in the limbal stem cell niche of adult human cornea, we assume that CHRDL1 plays a key role in cornea homeostasis. In conclusion, we provide novel insights into the molecular mechanism of XMC as well as into the specific role of CHRDL1 during cornea organogenesis, among others by the establishment of the first XMC in vivo model. We show that unravelling monogenic cornea disorders like XMC—with presumably disturbed cornea growth and differentiation—contribute to the identification of potential limbal stem cell niche factors that are promising targets for regenerative therapies of corneal injuries.
    Print ISSN: 0964-6906
    Electronic ISSN: 1460-2083
    Topics: Biology , Medicine
    Published by Oxford University Press
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  • 3
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    Loss of MITF expression during human embryonic stem cell differentiation disrupts retinal pigment epithelium development and optic vesicle cell proliferation (2014)
    Oxford University Press
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    Publication Date: 2014-11-07
    Description: Microphthalmia-associated transcription factor ( MITF ) is a master regulator of pigmented cell survival and differentiation with direct transcriptional links to cell cycle, apoptosis and pigmentation. In mouse, Mitf is expressed early and uniformly in optic vesicle (OV) cells as they evaginate from the developing neural tube, and null Mitf mutations result in microphthalmia and pigmentation defects. However, homozygous mutations in MITF have not been identified in humans; therefore, little is known about its role in human retinogenesis. We used a human embryonic stem cell (hESC) model that recapitulates numerous aspects of retinal development, including OV specification and formation of retinal pigment epithelium (RPE) and neural retina progenitor cells (NRPCs), to investigate the earliest roles of MITF. During hESC differentiation toward a retinal lineage, a subset of MITF isoforms was expressed in a sequence and tissue distribution similar to that observed in mice. In addition, we found that promoters for the MITF-A , -D and -H isoforms were directly targeted by Visual Systems Homeobox 2 (VSX2), a transcription factor involved in patterning the OV toward a NRPC fate. We then manipulated MITF RNA and protein levels at early developmental stages and observed decreased expression of eye field transcription factors, reduced early OV cell proliferation and disrupted RPE maturation. This work provides a foundation for investigating MITF and other highly complex, multi-purposed transcription factors in a dynamic human developmental model system.
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    Electronic ISSN: 1460-2083
    Topics: Biology , Medicine
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  • 4
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    Diabetogenic milieus induce specific changes in mitochondrial transcriptome and differentiation of human pancreatic islets (2015)
    Oxford University Press
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    Publication Date: 2015-08-27
    Description: In pancreatic β-cells, mitochondria play a central role in coupling glucose metabolism to insulin secretion. Chronic exposure of β-cells to metabolic stresses impairs their function and potentially induces apoptosis. Little is known on mitochondrial adaptation to metabolic stresses, i.e. high glucose, fatty acids or oxidative stress; being all highlighted in the pathogenesis of type 2 diabetes. Here, human islets were exposed for 3 days to 25 m m glucose, 0.4 m m palmitate, 0.4 m m oleate and transiently to H 2 O 2 . Culture at physiological 5.6 m m glucose served as no-stress control. Expression of mitochondrion-associated genes was quantified, including the transcriptome of mitochondrial inner membrane carriers. Targets of interest were further evaluated at the protein level. Three days after acute oxidative stress, no significant alteration in β-cell function or apoptosis was detected in human islets. Palmitate specifically increased expression of the pyruvate carriers MPC1 and MPC2, whereas the glutamate carrier GC1 and the aspartate/glutamate carrier AGC1 were down-regulated by palmitate and oleate, respectively. High glucose decreased mRNA levels of key transcription factors (HNF4A, IPF1, PPARA and TFAM) and energy-sensor SIRT1. High glucose also reduced expression of 11 mtDNA-encoded respiratory chain subunits. Interestingly, transcript levels of the carriers for aspartate/glutamate AGC2, malate DIC and malate/oxaloacetate/aspartate UCP2 were increased by high glucose, a profile suggesting important mitochondrial anaplerotic/cataplerotic activities and NADPH-generating shuttles. Chronic exposure to high glucose impaired glucose-stimulated insulin secretion, decreased insulin content, promoted caspase-3 cleavage and cell death, revealing glucotoxicity. Overall, expression profile of mitochondrion-associated genes was selectively modified by glucose, delineating a glucotoxic-specific signature.
    Print ISSN: 0964-6906
    Electronic ISSN: 1460-2083
    Topics: Biology , Medicine
    Published by Oxford University Press
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  • 5
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    Predicting protein phosphorylation from gene expression: top methods from the IMPROVER Species Translation Challenge (2015)
    Oxford University Press
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    Publication Date: 2015-02-13
    Description: Motivation : Using gene expression to infer changes in protein phosphorylation levels induced in cells by various stimuli is an outstanding problem. The intra-species protein phosphorylation challenge organized by the IMPROVER consortium provided the framework to identify the best approaches to address this issue. Results : Rat lung epithelial cells were treated with 52 stimuli, and gene expression and phosphorylation levels were measured. Competing teams used gene expression data from 26 stimuli to develop protein phosphorylation prediction models and were ranked based on prediction performance for the remaining 26 stimuli. Three teams were tied in first place in this challenge achieving a balanced accuracy of about 70%, indicating that gene expression is only moderately predictive of protein phosphorylation. In spite of the similar performance, the approaches used by these three teams, described in detail in this article, were different, with the average number of predictor genes per phosphoprotein used by the teams ranging from 3 to 124. However, a significant overlap of gene signatures between teams was observed for the majority of the proteins considered, while Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were enriched in the union of the predictor genes of the three teams for multiple proteins. Availability and implementation : Gene expression and protein phosphorylation data are available from ArrayExpress (E-MTAB-2091). Software implementation of the approach of Teams 49 and 75 are available at http://bioinformaticsprb.med.wayne.edu and http://people.cs.clemson.edu/~luofeng/sbv.rar , respectively. Contact : gyanbhanot@gmail.com or luofeng@clemson.edu or atarca@med.wayne.edu Supplementary information: Supplementary data are available at Bioinformatics online.
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    Topics: Biology , Computer Science , Medicine
    Published by Oxford University Press
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  • 6
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    Where are we at regarding species translation? A review of the sbv IMPROVER challenge (2015)
    Oxford University Press
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    Publication Date: 2015-02-13
    Description: Contact: Julia.Hoeng@pmi.com
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    Topics: Biology , Computer Science , Medicine
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  • 7
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    Inter-species prediction of protein phosphorylation in the sbv IMPROVER species translation challenge (2015)
    Oxford University Press
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    Publication Date: 2015-02-13
    Description: Motivation : Animal models are widely used in biomedical research for reasons ranging from practical to ethical. An important issue is whether rodent models are predictive of human biology. This has been addressed recently in the framework of a series of challenges designed by the systems biology verification for Industrial Methodology for Process Verification in Research (sbv IMPROVER) initiative. In particular, one of the sub-challenges was devoted to the prediction of protein phosphorylation responses in human bronchial epithelial cells, exposed to a number of different chemical stimuli, given the responses in rat bronchial epithelial cells. Participating teams were asked to make inter-species predictions on the basis of available training examples, comprising transcriptomics and phosphoproteomics data. Results: Here, the two best performing teams present their data-driven approaches and computational methods. In addition, post hoc analyses of the datasets and challenge results were performed by the participants and challenge organizers. The challenge outcome indicates that successful prediction of protein phosphorylation status in human based on rat phosphorylation levels is feasible. However, within the limitations of the computational tools used, the inclusion of gene expression data does not improve the prediction quality. The post hoc analysis of time-specific measurements sheds light on the signaling pathways in both species. Availability and implementation: A detailed description of the dataset, challenge design and outcome is available at www.sbvimprover.com . The code used by team IGB is provided under http://github.com/uci-igb/improver2013 . Implementations of the algorithms applied by team AMG are available at http://bhanot.biomaps.rutgers.edu/wiki/AMG-sc2-code.zip . Contact: meikelbiehl@gmail.com
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    Topics: Biology , Computer Science , Medicine
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  • 8
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    Inter-species inference of gene set enrichment in lung epithelial cells from proteomic and large transcriptomic datasets (2015)
    Oxford University Press
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    Publication Date: 2015-02-13
    Description: Motivation: Translating findings in rodent models to human models has been a cornerstone of modern biology and drug development. However, in many cases, a naive ‘extrapolation’ between the two species has not succeeded. As a result, clinical trials of new drugs sometimes fail even after considerable success in the mouse or rat stage of development. In addition to in vitro studies, inter-species translation requires analytical tools that can predict the enriched gene sets in human cells under various stimuli from corresponding measurements in animals. Such tools can improve our understanding of the underlying biology and optimize the allocation of resources for drug development. Results: We developed an algorithm to predict differential gene set enrichment as part of the sbv IMPROVER (systems biology verification in Industrial Methodology for Process Verification in Research) Species Translation Challenge, which focused on phosphoproteomic and transcriptomic measurements of normal human bronchial epithelial (NHBE) primary cells under various stimuli and corresponding measurements in rat (NRBE) primary cells. We find that gene sets exhibit a higher inter-species correlation compared with individual genes, and are potentially more suited for direct prediction. Furthermore, in contrast to a similar cross-species response in protein phosphorylation states 5 and 25 min after exposure to stimuli, gene set enrichment 6 h after exposure is significantly different in NHBE cells compared with NRBE cells. In spite of this difference, we were able to develop a robust algorithm to predict gene set activation in NHBE with high accuracy using simple analytical methods. Availability and implementation: Implementation of all algorithms is available as source code (in Matlab) at http://bhanot.biomaps.rutgers.edu/wiki/codes_SC3_Predicting_GeneSets.zip , along with the relevant data used in the analysis. Gene sets, gene expression and protein phosphorylation data are available on request. Contact: hormoz@kitp.ucsb.edu
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  • 9
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    Inter-species pathway perturbation prediction via data-driven detection of functional homology (2015)
    Oxford University Press
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    Publication Date: 2015-02-13
    Description: Motivation: Experiments in animal models are often conducted to infer how humans will respond to stimuli by assuming that the same biological pathways will be affected in both organisms. The limitations of this assumption were tested in the IMPROVER Species Translation Challenge, where 52 stimuli were applied to both human and rat cells and perturbed pathways were identified. In the Inter-species Pathway Perturbation Prediction sub-challenge, multiple teams proposed methods to use rat transcription data from 26 stimuli to predict human gene set and pathway activity under the same perturbations. Submissions were evaluated using three performance metrics on data from the remaining 26 stimuli. Results: We present two approaches, ranked second in this challenge, that do not rely on sequence-based orthology between rat and human genes to translate pathway perturbation state but instead identify transcriptional response orthologs across a set of training conditions. The translation from rat to human accomplished by these so-called direct methods is not dependent on the particular analysis method used to identify perturbed gene sets. In contrast, machine learning-based methods require performing a pathway analysis initially and then mapping the pathway activity between organisms. Unlike most machine learning approaches, direct methods can be used to predict the activation of a human pathway for a new (test) stimuli, even when that pathway was never activated by a training stimuli. Availability: Gene expression data are available from ArrayExpress (accession E-MTAB-2091), while software implementations are available from http://bioinformaticsprb.med.wayne.edu?p=50 and http://goo.gl/hJny3h . Contact: christoph.hafemeister@nyu.edu or atarca@med.wayne.edu . Supplementary information: Supplementary data are available at Bioinformatics online.
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    Topics: Biology , Computer Science , Medicine
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  • 10
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    A crowd-sourcing approach for the construction of species-specific cell signaling networks (2015)
    Oxford University Press
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    Publication Date: 2015-02-13
    Description: Motivation: Animal models are important tools in drug discovery and for understanding human biology in general. However, many drugs that initially show promising results in rodents fail in later stages of clinical trials. Understanding the commonalities and differences between human and rat cell signaling networks can lead to better experimental designs, improved allocation of resources and ultimately better drugs. Results: The sbv IMPROVER Species-Specific Network Inference challenge was designed to use the power of the crowds to build two species-specific cell signaling networks given phosphoproteomics, transcriptomics and cytokine data generated from NHBE and NRBE cells exposed to various stimuli. A common literature-inspired reference network with 220 nodes and 501 edges was also provided as prior knowledge from which challenge participants could add or remove edges but not nodes. Such a large network inference challenge not based on synthetic simulations but on real data presented unique difficulties in scoring and interpreting the results. Because any prior knowledge about the networks was already provided to the participants for reference, novel ways for scoring and aggregating the results were developed. Two human and rat consensus networks were obtained by combining all the inferred networks. Further analysis showed that major signaling pathways were conserved between the two species with only isolated components diverging, as in the case of ribosomal S6 kinase RPS6KA1. Overall, the consensus between inferred edges was relatively high with the exception of the downstream targets of transcription factors, which seemed more difficult to predict. Contact: ebilal@us.ibm.com or gustavo@us.ibm.com . Supplementary information: Supplementary data are available at Bioinformatics online.
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    Topics: Biology , Computer Science , Medicine
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