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Frades I, Foguet C, Cascante M, Araúzo-Bravo MJ. Genome Scale Modeling to Study the Metabolic Competition between Cells in the Tumor Microenvironment. Cancers (Basel) 2021; 13:4609. [PMID: 34572839 PMCID: PMC8470216 DOI: 10.3390/cancers13184609] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2021] [Revised: 09/06/2021] [Accepted: 09/09/2021] [Indexed: 12/31/2022] Open
Abstract
The tumor's physiology emerges from the dynamic interplay of numerous cell types, such as cancer cells, immune cells and stromal cells, within the tumor microenvironment. Immune and cancer cells compete for nutrients within the tumor microenvironment, leading to a metabolic battle between these cell populations. Tumor cells can reprogram their metabolism to meet the high demand of building blocks and ATP for proliferation, and to gain an advantage over the action of immune cells. The study of the metabolic reprogramming mechanisms underlying cancer requires the quantification of metabolic fluxes which can be estimated at the genome-scale with constraint-based or kinetic modeling. Constraint-based models use a set of linear constraints to simulate steady-state metabolic fluxes, whereas kinetic models can simulate both the transient behavior and steady-state values of cellular fluxes and concentrations. The integration of cell- or tissue-specific data enables the construction of context-specific models that reflect cell-type- or tissue-specific metabolic properties. While the available modeling frameworks enable limited modeling of the metabolic crosstalk between tumor and immune cells in the tumor stroma, future developments will likely involve new hybrid kinetic/stoichiometric formulations.
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Affiliation(s)
- Itziar Frades
- Computational Biology and Systems Biomedicine Group, Biodonostia Health Research Institute, 20009 San Sebastian, Spain;
| | - Carles Foguet
- Department of Biochemistry and Molecular Biomedicine, Institute of Biomedicine of University of Barcelona, Faculty of Biology, Universitat de Barcelona, Av. Diagonal 643, 08028 Barcelona, Spain; (C.F.); (M.C.)
- Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBEREHD) (CB17/04/00023) and Metabolomics Node at Spanish National Bioinformatics Institute (INB-ISCIII-ES-ELIXIR), Instituto de Salud Carlos III (ISCIII), 28020 Madrid, Spain
| | - Marta Cascante
- Department of Biochemistry and Molecular Biomedicine, Institute of Biomedicine of University of Barcelona, Faculty of Biology, Universitat de Barcelona, Av. Diagonal 643, 08028 Barcelona, Spain; (C.F.); (M.C.)
- Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBEREHD) (CB17/04/00023) and Metabolomics Node at Spanish National Bioinformatics Institute (INB-ISCIII-ES-ELIXIR), Instituto de Salud Carlos III (ISCIII), 28020 Madrid, Spain
| | - Marcos J. Araúzo-Bravo
- Computational Biology and Systems Biomedicine Group, Biodonostia Health Research Institute, 20009 San Sebastian, Spain;
- Max Planck Institute of Molecular Biomedicine, 48167 Münster, Germany
- Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBERfes), 28015 Madrid, Spain
- Translational Bioinformatics Network (TransBioNet), 8001 Barcelona, Spain
- Ikerbasque, Basque Foundation for Science, 48012 Bilbao, Spain
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Di Narzo A, Frades I, Crane HM, Crane PK, Hulot JS, Kasarskis A, Hart A, Argmann C, Dubinsky M, Peter I, Hao K. Meta-analysis of sample-level dbGaP data reveals novel shared genetic link between body height and Crohn's disease. Hum Genet 2021; 140:865-877. [PMID: 33452914 DOI: 10.1007/s00439-020-02250-3] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2020] [Accepted: 12/19/2020] [Indexed: 12/29/2022]
Abstract
To further explore genetic links between complex traits, we developed a comprehensive framework to harmonize and integrate extensive genotype and phenotype data from the four well-characterized cohorts with the focus on cardiometabolic diseases deposited to the database of Genotypes and Phenotypes (dbGaP). We generated a series of polygenic risk scores (PRS) to investigate pleiotropic effects of loci that confer genetic risk for 19 common diseases and traits on body height, type 2 diabetes (T2D), and myocardial infarction (MI). In a meta-analysis of 20,021 subjects, we identified shared genetic determinants of Crohn's Disease (CD), a type of inflammatory bowel disease, and body height (p = 5.5 × 10-5). The association of PRS-CD with height was replicated in UK Biobank (p = 1.1 × 10-5) and an independent cohort of 510 CD cases and controls (1.57 cm shorter height per PRS-CD interquartile increase, p = 5.0 × 10-3 and a 28% reduction in CD risk per interquartile increase in PRS-height, p = 1.1 × 10-3, with the effect independent of CD diagnosis). A pathway analysis of the variants overlapping between PRS-height and PRS-CD detected significant enrichment of genes from the inflammatory, immune-mediated and growth factor regulation pathways. This finding supports the clinical observation of growth failure in patients with childhood-onset CD and demonstrates the value of using individual-level data from dbGaP in searching for shared genetic determinants. This information can help provide a refined insight into disease pathogenesis and may have major implications for novel therapies and drug repurposing.
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Affiliation(s)
- Antonio Di Narzo
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, 1425 Madison Ave, New York, NY, 10029, USA.,Icahn School of Medicine At Mount Sinai, Icahn Institute for Data Science and Genomic Technology, New York, NY, USA
| | - Itziar Frades
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, 1425 Madison Ave, New York, NY, 10029, USA.,Computational Biology and Systems Biomedicine Research Group, Biodonostia Health Research Institute, San Sebastián, Spain
| | - Heidi M Crane
- Department of Medicine, University of Washington, Seattle, WA, USA.,Center for AIDS Research, University of Washington, Seattle, WA, USA
| | - Paul K Crane
- Department of Medicine, University of Washington, Seattle, WA, USA
| | - Jean-Sebastian Hulot
- Université de Paris, INSERM, PARCC, CIC1418, F-75015, Paris, France.,Cardiovascular Research Center, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Andrew Kasarskis
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, 1425 Madison Ave, New York, NY, 10029, USA.,Icahn School of Medicine At Mount Sinai, Icahn Institute for Data Science and Genomic Technology, New York, NY, USA.,Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Amy Hart
- Janssen R&D, LLC, 1400 McKean Road, Spring House, PA, USA
| | - Carmen Argmann
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, 1425 Madison Ave, New York, NY, 10029, USA.,Icahn School of Medicine At Mount Sinai, Icahn Institute for Data Science and Genomic Technology, New York, NY, USA
| | - Marla Dubinsky
- Department of Pediatric Gastroenterology and Nutrition, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Inga Peter
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, 1425 Madison Ave, New York, NY, 10029, USA.,Icahn School of Medicine At Mount Sinai, Icahn Institute for Data Science and Genomic Technology, New York, NY, USA
| | - Ke Hao
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, 1425 Madison Ave, New York, NY, 10029, USA. .,Icahn School of Medicine At Mount Sinai, Icahn Institute for Data Science and Genomic Technology, New York, NY, USA.
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3
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Frades I, Readhead B, Amadori L, Koplev S, Talukdar HA, Crane HM, Crane PK, Kovacic JC, Dudley JT, Giannarelli C, Björkegren JLM, Peter I. Systems Pharmacology Identifies an Arterial Wall Regulatory Gene Network Mediating Coronary Artery Disease Side Effects of Antiretroviral Therapy. Circ Genom Precis Med 2019; 12:e002390. [PMID: 31059280 DOI: 10.1161/circgen.118.002390] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
BACKGROUND Antiretroviral therapy (ART) for HIV infection increases risk for coronary artery disease (CAD), presumably by causing dyslipidemia and increased atherosclerosis. We applied systems pharmacology to identify and validate specific regulatory gene networks through which ART drugs may promote CAD. METHODS Transcriptional responses of human cell lines to 15 ART drugs retrieved from the Library of Integrated Cellular Signatures (overall 1127 experiments) were used to establish consensus ART gene/transcriptional signatures. Next, enrichments of differentially expressed genes and gene-gene connectivity within these ART-consensus signatures were sought in 30 regulatory gene networks associated with CAD and CAD-related phenotypes in the Stockholm Atherosclerosis Gene Expression study. RESULTS Ten of 15 ART signatures were significantly enriched both for differential expression and connectivity in a specific atherosclerotic arterial wall regulatory gene network (AR-RGN) causal for CAD involving RNA processing genes. An atherosclerosis in vitro model of cholestryl ester-loaded foam cells was then used for experimental validation. Treatments of these foam cells with ritonavir, nelfinavir, and saquinavir at least doubled cholestryl ester accumulation ( P=0.02, 0.0009, and 0.02, respectively), whereas RNA silencing of the AR-RGN top key driver, PQBP1 (polyglutamine binding protein 1), significantly curbed cholestryl ester accumulation following treatment with any of these ART drugs by >37% ( P<0.05). CONCLUSIONS By applying a novel systems pharmacology data analysis framework, 3 commonly used ARTs (ritonavir, nelfinavir, and saquinavir) were found altering the activity of AR-RGN, a regulatory gene network promoting foam cell formation and risk of CAD. Targeting AR-RGN or its top key driver PQBP1 may help reduce CAD side effects of these ART drugs.
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Affiliation(s)
- Itziar Frades
- Department of Genetics and Genomic Sciences (I.F., B.R., L.A., S.K., J.T.D., C.G., J.L.M.B., I.P.), Icahn School of Medicine at Mount Sinai, New York, NY
| | - Ben Readhead
- Department of Genetics and Genomic Sciences (I.F., B.R., L.A., S.K., J.T.D., C.G., J.L.M.B., I.P.), Icahn School of Medicine at Mount Sinai, New York, NY.,Icahn Institute for Data Science and Genomic Technology (B.R., J.T.D., J.L.M.B., I.P.), Icahn School of Medicine at Mount Sinai, New York, NY.,Institute for Next Generation Healthcare (B.R., J.T.D.), Icahn School of Medicine at Mount Sinai, New York, NY.,ASU-Banner Neurodegenerative Disease Research Center, Arizona State University, Tempe (B.R.)
| | - Letizia Amadori
- Department of Genetics and Genomic Sciences (I.F., B.R., L.A., S.K., J.T.D., C.G., J.L.M.B., I.P.), Icahn School of Medicine at Mount Sinai, New York, NY
| | - Simon Koplev
- Department of Genetics and Genomic Sciences (I.F., B.R., L.A., S.K., J.T.D., C.G., J.L.M.B., I.P.), Icahn School of Medicine at Mount Sinai, New York, NY
| | - Husain A Talukdar
- Department of Medicine, Integrated Cardio Metabolic Centre, Karolinska Institutet, Karolinska Universitetssjukhuset, Huddinge, Sweden (H.A.T., J.L.M.B.)
| | - Heidi M Crane
- Department of Medicine, University of Washington, Seattle (H.M.C., P.K.C.)
| | - Paul K Crane
- Department of Medicine, University of Washington, Seattle (H.M.C., P.K.C.)
| | - Jason C Kovacic
- Department of Medicine (J.C.K.), Icahn School of Medicine at Mount Sinai, New York, NY.,Cardiovascular Research Center (J.C.K., C.G.), Icahn School of Medicine at Mount Sinai, New York, NY
| | - Joel T Dudley
- Department of Genetics and Genomic Sciences (I.F., B.R., L.A., S.K., J.T.D., C.G., J.L.M.B., I.P.), Icahn School of Medicine at Mount Sinai, New York, NY.,Icahn Institute for Data Science and Genomic Technology (B.R., J.T.D., J.L.M.B., I.P.), Icahn School of Medicine at Mount Sinai, New York, NY.,Institute for Next Generation Healthcare (B.R., J.T.D.), Icahn School of Medicine at Mount Sinai, New York, NY
| | - Chiara Giannarelli
- Department of Genetics and Genomic Sciences (I.F., B.R., L.A., S.K., J.T.D., C.G., J.L.M.B., I.P.), Icahn School of Medicine at Mount Sinai, New York, NY.,Cardiovascular Research Center (J.C.K., C.G.), Icahn School of Medicine at Mount Sinai, New York, NY.,Precision Immunology Institute (C.G.), Icahn School of Medicine at Mount Sinai, New York, NY
| | - Johan L M Björkegren
- Department of Genetics and Genomic Sciences (I.F., B.R., L.A., S.K., J.T.D., C.G., J.L.M.B., I.P.), Icahn School of Medicine at Mount Sinai, New York, NY.,Icahn Institute for Data Science and Genomic Technology (B.R., J.T.D., J.L.M.B., I.P.), Icahn School of Medicine at Mount Sinai, New York, NY.,Department of Medicine, Integrated Cardio Metabolic Centre, Karolinska Institutet, Karolinska Universitetssjukhuset, Huddinge, Sweden (H.A.T., J.L.M.B.)
| | - Inga Peter
- Department of Genetics and Genomic Sciences (I.F., B.R., L.A., S.K., J.T.D., C.G., J.L.M.B., I.P.), Icahn School of Medicine at Mount Sinai, New York, NY.,Icahn Institute for Data Science and Genomic Technology (B.R., J.T.D., J.L.M.B., I.P.), Icahn School of Medicine at Mount Sinai, New York, NY
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Frades I, Andreasson E. Phytophthora infestans specific phosphorylation patterns and new putative control targets. Fungal Biol 2016; 120:631-644. [PMID: 27020162 DOI: 10.1016/j.funbio.2016.01.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2015] [Revised: 12/16/2015] [Accepted: 01/06/2016] [Indexed: 11/15/2022]
Abstract
In this study we applied biomathematical searches of gene regulatory mechanisms to learn more about oomycete biology and to identify new putative targets for pesticides or biological control against Phytophthora infestans. First, oomycete phylum-specific phosphorylation motifs were found by discriminative n-gram analysis. We found 11.600 P. infestans specific n-grams, mapping 642 phosphoproteins. The most abundant group among these related to phosphatidylinositol metabolism. Due to the large number of possible targets found and our hypothesis that multi-level control is a sign of usefulness as targets for intervention, we identified overlapping targets with a second screen. This was performed to identify proteins dually regulated by small RNA and phosphorylation. We found 164 proteins to be regulated by both sRNA and phosphorylation and the dominating functions where phosphatidylinositol signalling/metabolism, endocytosis, and autophagy. Furthermore we performed a similar regulatory study and discriminative n-gram analysis of proteins with no clear orthologs in other species and proteins that are known to be unique to P. infestans such as the RxLR effectors, Crinkler (CRN) proteins and elicitins. We identified CRN proteins with specific phospho-motifs present in all life stages. PITG_12626, PITG_14042 and PITG_23175 are CRN proteins that have species-specific phosphorylation motifs and are subject to dual regulation.
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Affiliation(s)
- Itziar Frades
- Department of Plant Protection Biology, Swedish University of Agricultural Sciences, Alnarp, SE-230 53, Sweden.
| | - Erik Andreasson
- Department of Plant Protection Biology, Swedish University of Agricultural Sciences, Alnarp, SE-230 53, Sweden
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5
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Frades I, Abreha KB, Proux-Wéra E, Lankinen Å, Andreasson E, Alexandersson E. A novel workflow correlating RNA-seq data to Phythophthora infestans resistance levels in wild Solanum species and potato clones. Front Plant Sci 2015; 6:718. [PMID: 26442032 PMCID: PMC4585127 DOI: 10.3389/fpls.2015.00718] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/13/2015] [Accepted: 08/27/2015] [Indexed: 05/18/2023]
Abstract
Comparative transcriptomics between species can provide valuable understanding of plant-pathogen interactions. Here, we focus on wild Solanum species and potato clones with varying degree of resistance against Phytophthora infestans, which causes the devastating late blight disease in potato. The transcriptomes of three wild Solanum species native to Southern Sweden, Solanum dulcamara, Solanum nigrum, and Solanum physalifolium were compared to three potato clones, Desiree (cv.), SW93-1015 and Sarpo Mira. Desiree and S. physalifolium are susceptible to P. infestans whereas the other four have different degrees of resistance. By building transcript families based on de novo assembled RNA-seq across species and clones and correlating these to resistance phenotypes, we created a novel workflow to identify families with expanded or depleted number of transcripts in relation to the P. infestans resistance level. Analysis was facilitated by inferring functional annotations based on the family structure and semantic clustering. More transcript families were expanded in the resistant clones and species and the enriched functions of these were associated to expected gene ontology (GO) terms for resistance mechanisms such as hypersensitive response, host programmed cell death and endopeptidase activity. However, a number of unexpected functions and transcripts were also identified, for example transmembrane transport and protein acylation expanded in the susceptible group and a cluster of Zinc knuckle family proteins expanded in the resistant group. Over 400 expressed putative resistance (R-)genes were identified and resistant clones Sarpo Mira and SW93-1015 had ca 25% more expressed putative R-genes than susceptible cultivar Desiree. However, no differences in numbers of susceptibility (S-)gene homologs were seen between species and clones. In addition, we identified P. infestans transcripts including effectors in the early stages of P. infestans-Solanum interactions.
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Affiliation(s)
| | | | | | | | | | - Erik Alexandersson
- Department of Plant Protection Biology, Swedish University of Agricultural SciencesAlnarp, Sweden
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Amar D, Frades I, Diels T, Zaltzman D, Ghatan N, Hedley PE, Alexandersson E, Tzfadia O, Shamir R. The MORPH-R web server and software tool for predicting missing genes in biological pathways. Physiol Plant 2015; 155:12-20. [PMID: 25625434 DOI: 10.1111/ppl.12326] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/29/2014] [Accepted: 01/12/2015] [Indexed: 06/04/2023]
Abstract
A biological pathway is the set of molecular entities involved in a given biological process and the interrelations among them. Even though biological pathways have been studied extensively, discovering missing genes in pathways remains a fundamental challenge. Here, we present an easy-to-use tool that allows users to run MORPH (MOdule-guided Ranking of candidate PatHway genes), an algorithm for revealing missing genes in biological pathways, and demonstrate its capabilities. MORPH supports the analysis in tomato, Arabidopsis and the two new species: rice and the newly sequenced potato genome. The new tool, called MORPH-R, is available both as a web server (at http://bioinformatics.psb.ugent.be/webtools/morph/) and as standalone software that can be used locally. In the standalone version, the user can apply the tool to new organisms using any proprietary and public data sources.
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Affiliation(s)
- David Amar
- Blavatnik School of Computer Science, Tel Aviv University, Tel Aviv, Israel
| | - Itziar Frades
- Department of Plant Protection Biology, Swedish University of Agricultural Sciences, Alnarp, Sweden
| | - Tim Diels
- Department of Plant Systems Biology, VIB, Ghent, Belgium
- Department of Mathematics and Computer Science, University of Antwerp, Antwerp, Belgium
| | - David Zaltzman
- Department of Plant Science, The Weizmann Institute of Science, Rehovot, Israel
| | - Netanel Ghatan
- Department of Plant Science, The Weizmann Institute of Science, Rehovot, Israel
| | - Pete E Hedley
- Cell and Molecular Sciences, The James Hutton Institute, Dundee, United Kingdom
| | - Erik Alexandersson
- Department of Plant Protection Biology, Swedish University of Agricultural Sciences, Alnarp, Sweden
| | - Oren Tzfadia
- Department of Plant Systems Biology, VIB, Ghent, Belgium
- Department of Plant Science, The Weizmann Institute of Science, Rehovot, Israel
| | - Ron Shamir
- Blavatnik School of Computer Science, Tel Aviv University, Tel Aviv, Israel
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Abstract
Background How protein phosphorylation relates to kingdom/phylum divergence is largely unknown and the amino acid residues surrounding the phosphorylation site have profound importance on protein kinase–substrate interactions. Standard motif analysis is not adequate for large scale comparative analysis because each phophopeptide is assigned to a unique motif and perform poorly with the unbalanced nature of the input datasets. Results First the discriminative n-grams of five species from five different kingdom/phyla were identified. A signature with 5540 discriminative n-grams that could be found in other species from the same kingdoms/phyla was created. Using a test data set, the ability of the signature to classify species in their corresponding kingdom/phylum was confirmed using classification methods. Lastly, ortholog proteins among proteins with n-grams were identified in order to determine to what degree was the identity of the detected n-grams a property of phosphosites rather than a consequence of species-specific or kingdom/phylum-specific protein inventory. The motifs were grouped in clusters of equal physico-chemical nature and their distribution was similar between species in the same kingdom/phylum while clear differences were found among species of different kingdom/phylum. For example, the animal-specific top discriminative n-grams contained many basic amino acids and the plant-specific motifs were mainly acidic. Secondary structure prediction methods show that the discriminative n-grams in the majority of the cases lack from a regular secondary structure as on average they had 88 % of random coil compared to 66 % found in the phosphoproteins they were derived from. Conclusions The discriminative n-grams were able to classify organisms in their corresponding kingdom/phylum, they show different patterns among species of different kingdom/phylum and these regions can contribute to evolutionary divergence as they are in disordered regions that can evolve rapidly. The differences found possibly reflect group-specific differences in the kinomes of the different groups of species. Electronic supplementary material The online version of this article (doi:10.1186/s12859-015-0657-2) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Itziar Frades
- Department of Plant Protection Biology, Swedish University of Agricultural Sciences, Alnarp, SE-230 53, Sweden.
| | - Svante Resjö
- Department of Plant Protection Biology, Swedish University of Agricultural Sciences, Alnarp, SE-230 53, Sweden.
| | - Erik Andreasson
- Department of Plant Protection Biology, Swedish University of Agricultural Sciences, Alnarp, SE-230 53, Sweden.
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Frades I, Andreasson E, Mato JM, Alexandersson E, Matthiesen R, Martínez-Chantar ML. Integrative genomic signatures of hepatocellular carcinoma derived from nonalcoholic Fatty liver disease. PLoS One 2015; 10:e0124544. [PMID: 25993042 PMCID: PMC4439034 DOI: 10.1371/journal.pone.0124544] [Citation(s) in RCA: 50] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2015] [Accepted: 03/05/2015] [Indexed: 12/11/2022] Open
Abstract
Nonalcoholic fatty liver disease (NAFLD) is a risk factor for Hepatocellular carcinoma (HCC), but he transition from NAFLD to HCC is poorly understood. Feature selection algorithms in human and genetically modified mice NAFLD and HCC microarray data were applied to generate signatures of NAFLD progression and HCC differential survival. These signatures were used to study the pathogenesis of NAFLD derived HCC and explore which subtypes of cancers that can be investigated using mouse models. Our findings show that: (I) HNF4 is a common potential transcription factor mediating the transcription of NAFLD progression genes (II) mice HCC derived from NAFLD co-cluster with a less aggressive human HCC subtype of differential prognosis and mixed etiology (III) the HCC survival signature is able to correctly classify 95% of the samples and gives Fgf20 and Tgfb1i1 as the most robust genes for prediction (IV) the expression values of genes composing the signature in an independent human HCC dataset revealed different HCC subtypes showing differences in survival time by a Logrank test. In summary, we present marker signatures for NAFLD derived HCC molecular pathogenesis both at the gene and pathway level.
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Affiliation(s)
- Itziar Frades
- Metabolomics Unit, CIC bioGUNE, Centro de Investigación Cooperativa en Biociencias, Bizkaia Technology Park, Derio, Bizkaia, Spain
- Department of Plant Protection Biology, Swedish University of Agricultural Sciences, Alnarp, Sweden
| | - Erik Andreasson
- Department of Plant Protection Biology, Swedish University of Agricultural Sciences, Alnarp, Sweden
| | - Jose Maria Mato
- Metabolomics Unit, CIC bioGUNE, Centro de Investigación Cooperativa en Biociencias, Bizkaia Technology Park, Derio, Bizkaia, Spain
| | - Erik Alexandersson
- Department of Plant Protection Biology, Swedish University of Agricultural Sciences, Alnarp, Sweden
| | - Rune Matthiesen
- Department of Human genetics, National Health Institute Doutor Ricardo Jorge, Lisboa, Portugal
| | - Mª Luz Martínez-Chantar
- Metabolomics Unit, CIC bioGUNE, Centro de Investigación Cooperativa en Biociencias, Bizkaia Technology Park, Derio, Bizkaia, Spain
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9
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Amar D, Frades I, Danek A, Goldberg T, Sharma SK, Hedley PE, Proux-Wera E, Andreasson E, Shamir R, Tzfadia O, Alexandersson E. Evaluation and integration of functional annotation pipelines for newly sequenced organisms: the potato genome as a test case. BMC Plant Biol 2014; 14:329. [PMID: 25476999 PMCID: PMC4274702 DOI: 10.1186/s12870-014-0329-9] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/12/2014] [Accepted: 11/10/2014] [Indexed: 05/08/2023]
Abstract
BACKGROUND For most organisms, even if their genome sequence is available, little functional information about individual genes or proteins exists. Several annotation pipelines have been developed for functional analysis based on sequence, 'omics', and literature data. However, researchers encounter little guidance on how well they perform. Here, we used the recently sequenced potato genome as a case study. The potato genome was selected since its genome is newly sequenced and it is a non-model plant even if there is relatively ample information on individual potato genes, and multiple gene expression profiles are available. RESULTS We show that the automatic gene annotations of potato have low accuracy when compared to a "gold standard" based on experimentally validated potato genes. Furthermore, we evaluate six state-of-the-art annotation pipelines and show that their predictions are markedly dissimilar (Jaccard similarity coefficient of 0.27 between pipelines on average). To overcome this discrepancy, we introduce a simple GO structure-based algorithm that reconciles the predictions of the different pipelines. We show that the integrated annotation covers more genes, increases by over 50% the number of highly co-expressed GO processes, and obtains much higher agreement with the gold standard. CONCLUSIONS We find that different annotation pipelines produce different results, and show how to integrate them into a unified annotation that is of higher quality than each single pipeline. We offer an improved functional annotation of both PGSC and ITAG potato gene models, as well as tools that can be applied to additional pipelines and improve annotation in other organisms. This will greatly aid future functional analysis of '-omics' datasets from potato and other organisms with newly sequenced genomes. The new potato annotations are available with this paper.
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Affiliation(s)
- David Amar
- Blavatnik School of Computer Science, Tel Aviv University, Tel Aviv, Israel.
| | - Itziar Frades
- Deptartment of Plant Protection Biology, Swedish University of Agricultural Sciences, Alnarp, Sweden.
| | - Agnieszka Danek
- Institute of Informatics, Silesian University of Technology, Akademicka 2A, 44-100, Gliwice, Poland.
| | - Tatyana Goldberg
- Department for Bioinformatics and Computational Biology, Technical University of Munich, Arcisstraße 21, 80333, Munich, Germany.
| | - Sanjeev K Sharma
- Cell and Molecular Sciences, The James Hutton Institute, Aberdeen, Scotland, UK.
| | - Pete E Hedley
- Cell and Molecular Sciences, The James Hutton Institute, Aberdeen, Scotland, UK.
| | - Estelle Proux-Wera
- Deptartment of Plant Protection Biology, Swedish University of Agricultural Sciences, Alnarp, Sweden.
- Current affiliation: SciLifeLab, Stockholm University, Universitetsvägen 10, 114 18, Stockholm, Sweden.
| | - Erik Andreasson
- Deptartment of Plant Protection Biology, Swedish University of Agricultural Sciences, Alnarp, Sweden.
| | - Ron Shamir
- Blavatnik School of Computer Science, Tel Aviv University, Tel Aviv, Israel.
| | - Oren Tzfadia
- Department of Plant Science, The Weizmann Institute of Science, Rehovot, Israel.
| | - Erik Alexandersson
- Deptartment of Plant Protection Biology, Swedish University of Agricultural Sciences, Alnarp, Sweden.
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10
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Varela-Rey M, Martínez-López N, Fernández-Ramos D, Embade N, Calvisi DF, Woodhoo A, Rodríguez J, Fraga MF, Julve J, Rodríguez-Millán E, Frades I, Torres L, Luka Z, Wagner C, Esteller M, Lu SC, Martínez-Chantar ML, Mato JM. Fatty liver and fibrosis in glycine N-methyltransferase knockout mice is prevented by nicotinamide. Hepatology 2010; 52:105-14. [PMID: 20578266 PMCID: PMC2921576 DOI: 10.1002/hep.23639] [Citation(s) in RCA: 72] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/02/2023]
Abstract
UNLABELLED Deletion of glycine N-methyltransferase (GNMT), the main gene involved in liver S-adenosylmethionine (SAM) catabolism, leads to the hepatic accumulation of this molecule and the development of fatty liver and fibrosis in mice. To demonstrate that the excess of hepatic SAM is the main agent contributing to liver disease in GNMT knockout (KO) mice, we treated 1.5-month-old GNMT-KO mice for 6 weeks with nicotinamide (NAM), a substrate of the enzyme NAM N-methyltransferase. NAM administration markedly reduced hepatic SAM content, prevented DNA hypermethylation, and normalized the expression of critical genes involved in fatty acid metabolism, oxidative stress, inflammation, cell proliferation, and apoptosis. More importantly, NAM treatment prevented the development of fatty liver and fibrosis in GNMT-KO mice. Because GNMT expression is down-regulated in patients with cirrhosis, and because some subjects with GNMT mutations have spontaneous liver disease, the clinical implications of the present findings are obvious, at least with respect to these latter individuals. Because NAM has been used for many years to treat a broad spectrum of diseases (including pellagra and diabetes) without significant side effects, it should be considered in subjects with GNMT mutations. CONCLUSION The findings of this study indicate that the anomalous accumulation of SAM in GNMT-KO mice can be corrected by NAM treatment leading to the normalization of the expression of many genes involved in fatty acid metabolism, oxidative stress, inflammation, cell proliferation, and apoptosis, as well as reversion of the appearance of the pathologic phenotype.
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Affiliation(s)
- Marta Varela-Rey
- CIC bioGUNE, Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Dgestivas (CIBERehd), Bizkaia, Spain
| | - Nuria Martínez-López
- CIC bioGUNE, Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Dgestivas (CIBERehd), Bizkaia, Spain
| | - David Fernández-Ramos
- CIC bioGUNE, Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Dgestivas (CIBERehd), Bizkaia, Spain
| | - Nieves Embade
- CIC bioGUNE, Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Dgestivas (CIBERehd), Bizkaia, Spain
| | - Diego F. Calvisi
- Institute of Pathology, Ernst Moritz Arndt University of Greifswald, Greifswald, Germany
| | - Aswhin Woodhoo
- CIC bioGUNE, Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Dgestivas (CIBERehd), Bizkaia, Spain
| | - Juan Rodríguez
- CIC bioGUNE, Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Dgestivas (CIBERehd), Bizkaia, Spain
| | - Mario F Fraga
- Department of Immunology and Oncology, National Center of Biotechnology, CNB-CSIC, Cantoblanco, Madrid, Spain
| | - Josep Julve
- Institut de Recerca de l'Hospital de la Santa Creu I Sant Pau, Centro de Investigación Biomédica en Red de Diabetes y Enfermedades Metabólicas Asociadas (CIBERdem), Barcelona, Spain
| | - Elisabeth Rodríguez-Millán
- Institut de Recerca de l'Hospital de la Santa Creu I Sant Pau, Centro de Investigación Biomédica en Red de Diabetes y Enfermedades Metabólicas Asociadas (CIBERdem), Barcelona, Spain
| | - Itziar Frades
- CIC bioGUNE, Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Dgestivas (CIBERehd), Bizkaia, Spain
| | - Luís Torres
- Departmento de Bioquímica y Biología Molecular, Universidad de Valencia, Spain
| | - Zigmund Luka
- Vanderbilt University School of Medicine, Department of Biochemistry, Nashville, Tennessee, USA
| | - Conrad Wagner
- Vanderbilt University School of Medicine, Department of Biochemistry, Nashville, Tennessee, USA
| | - Manel Esteller
- Cancer Epigenetics and Biology Program, Belvitge Biomedical Research Institute, Barcelona, Catalonia, Spain
| | - Shelly C Lu
- Division of Gastroenterology and Liver Diseases, University of Southern California Research Center for Liver Diseases, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
| | - M Luz Martínez-Chantar
- CIC bioGUNE, Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Dgestivas (CIBERehd), Bizkaia, Spain
| | - José M Mato
- CIC bioGUNE, Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Dgestivas (CIBERehd), Bizkaia, Spain
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