Search

Your search keyword '"Barrio-Hernandez, Inigo"' showing total 154 results
Start Over Author "Barrio-Hernandez, Inigo"
154 results on '"Barrio-Hernandez, Inigo"'

3. The effects of pathogenic and likely pathogenic variants for inherited hemostasis disorders in 140 214 UK Biobank participants

Author

Stefanucci, Luca, Collins, Janine, Sims, Matthew C., Barrio-Hernandez, Inigo, Sun, Luanluan, Burren, Oliver S., Perfetto, Livia, Bender, Isobel, Callahan, Tiffany J., Fleming, Kathryn, Guerrero, Jose A., Hermjakob, Henning, Martin, Maria J., Stephenson, James, Paneerselvam, Kalpana, Petrovski, Slavé, Porras, Pablo, Robinson, Peter N., Wang, Quanli, Watkins, Xavier, Frontini, Mattia, Laskowski, Roman A., Beltrao, Pedro, Di Angelantonio, Emanuele, Gomez, Keith, Laffan, Mike, Ouwehand, Willem H., Mumford, Andrew D., Freson, Kathleen, Carss, Keren, Downes, Kate, Gleadall, Nick, Megy, Karyn, Bruford, Elspeth, and Vuckovic, Dragana

Published
2023
Full Text
View/download PDF

5. Comparative host-coronavirus protein interaction networks reveal pan-viral disease mechanisms

Author

Gordon, David E, Hiatt, Joseph, Bouhaddou, Mehdi, Rezelj, Veronica V, Ulferts, Svenja, Braberg, Hannes, Jureka, Alexander S, Obernier, Kirsten, Guo, Jeffrey Z, Batra, Jyoti, Kaake, Robyn M, Weckstein, Andrew R, Owens, Tristan W, Gupta, Meghna, Pourmal, Sergei, Titus, Erron W, Cakir, Merve, Soucheray, Margaret, McGregor, Michael, Cakir, Zeynep, Jang, Gwendolyn, O’Meara, Matthew J, Tummino, Tia A, Zhang, Ziyang, Foussard, Helene, Rojc, Ajda, Zhou, Yuan, Kuchenov, Dmitry, Hüttenhain, Ruth, Xu, Jiewei, Eckhardt, Manon, Swaney, Danielle L, Fabius, Jacqueline M, Ummadi, Manisha, Tutuncuoglu, Beril, Rathore, Ujjwal, Modak, Maya, Haas, Paige, Haas, Kelsey M, Naing, Zun Zar Chi, Pulido, Ernst H, Shi, Ying, Barrio-Hernandez, Inigo, Memon, Danish, Petsalaki, Eirini, Dunham, Alistair, Marrero, Miguel Correa, Burke, David, Koh, Cassandra, Vallet, Thomas, Silvas, Jesus A, Azumaya, Caleigh M, Billesbølle, Christian, Brilot, Axel F, Campbell, Melody G, Diallo, Amy, Dickinson, Miles Sasha, Diwanji, Devan, Herrera, Nadia, Hoppe, Nick, Kratochvil, Huong T, Liu, Yanxin, Merz, Gregory E, Moritz, Michelle, Nguyen, Henry C, Nowotny, Carlos, Puchades, Cristina, Rizo, Alexandrea N, Schulze-Gahmen, Ursula, Smith, Amber M, Sun, Ming, Young, Iris D, Zhao, Jianhua, Asarnow, Daniel, Biel, Justin, Bowen, Alisa, Braxton, Julian R, Chen, Jen, Chio, Cynthia M, Chio, Un Seng, Deshpande, Ishan, Doan, Loan, Faust, Bryan, Flores, Sebastian, Jin, Mingliang, Kim, Kate, Lam, Victor L, Li, Fei, Li, Junrui, Li, Yen-Li, Li, Yang, Liu, Xi, Lo, Megan, Lopez, Kyle E, Melo, Arthur A, Moss, Frank R, Nguyen, Phuong, Paulino, Joana, Pawar, Komal Ishwar, and Peters, Jessica K

Subjects
Biological Sciences, Bioinformatics and Computational Biology, Lung, Pneumonia & Influenza, Coronaviruses, Biodefense, Emerging Infectious Diseases, Genetics, Pneumonia, Coronaviruses Therapeutics and Interventions, Infectious Diseases, 2.1 Biological and endogenous factors, 2.2 Factors relating to the physical environment, Infection, Generic health relevance, Good Health and Well Being, COVID-19, Conserved Sequence, Coronavirus Nucleocapsid Proteins, Cryoelectron Microscopy, Host Microbial Interactions, Humans, Mitochondrial Membrane Transport Proteins, Mitochondrial Precursor Protein Import Complex Proteins, Phosphoproteins, Protein Conformation, Protein Interaction Maps, Severe acute respiratory syndrome-related coronavirus, SARS-CoV-2, Severe Acute Respiratory Syndrome, QCRG Structural Biology Consortium, Zoonomia Consortium, General Science & Technology
Abstract

The COVID-19 pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is a grave threat to public health and the global economy. SARS-CoV-2 is closely related to the more lethal but less transmissible coronaviruses SARS-CoV-1 and Middle East respiratory syndrome coronavirus (MERS-CoV). Here, we have carried out comparative viral-human protein-protein interaction and viral protein localization analyses for all three viruses. Subsequent functional genetic screening identified host factors that functionally impinge on coronavirus proliferation, including Tom70, a mitochondrial chaperone protein that interacts with both SARS-CoV-1 and SARS-CoV-2 ORF9b, an interaction we structurally characterized using cryo-electron microscopy. Combining genetically validated host factors with both COVID-19 patient genetic data and medical billing records identified molecular mechanisms and potential drug treatments that merit further molecular and clinical study.

Published
2020

6. A SARS-CoV-2 protein interaction map reveals targets for drug repurposing

Author

Gordon, David E, Jang, Gwendolyn M, Bouhaddou, Mehdi, Xu, Jiewei, Obernier, Kirsten, White, Kris M, O’Meara, Matthew J, Rezelj, Veronica V, Guo, Jeffrey Z, Swaney, Danielle L, Tummino, Tia A, Hüttenhain, Ruth, Kaake, Robyn M, Richards, Alicia L, Tutuncuoglu, Beril, Foussard, Helene, Batra, Jyoti, Haas, Kelsey, Modak, Maya, Kim, Minkyu, Haas, Paige, Polacco, Benjamin J, Braberg, Hannes, Fabius, Jacqueline M, Eckhardt, Manon, Soucheray, Margaret, Bennett, Melanie J, Cakir, Merve, McGregor, Michael J, Li, Qiongyu, Meyer, Bjoern, Roesch, Ferdinand, Vallet, Thomas, Mac Kain, Alice, Miorin, Lisa, Moreno, Elena, Naing, Zun Zar Chi, Zhou, Yuan, Peng, Shiming, Shi, Ying, Zhang, Ziyang, Shen, Wenqi, Kirby, Ilsa T, Melnyk, James E, Chorba, John S, Lou, Kevin, Dai, Shizhong A, Barrio-Hernandez, Inigo, Memon, Danish, Hernandez-Armenta, Claudia, Lyu, Jiankun, Mathy, Christopher JP, Perica, Tina, Pilla, Kala Bharath, Ganesan, Sai J, Saltzberg, Daniel J, Rakesh, Ramachandran, Liu, Xi, Rosenthal, Sara B, Calviello, Lorenzo, Venkataramanan, Srivats, Liboy-Lugo, Jose, Lin, Yizhu, Huang, Xi-Ping, Liu, YongFeng, Wankowicz, Stephanie A, Bohn, Markus, Safari, Maliheh, Ugur, Fatima S, Koh, Cassandra, Savar, Nastaran Sadat, Tran, Quang Dinh, Shengjuler, Djoshkun, Fletcher, Sabrina J, O’Neal, Michael C, Cai, Yiming, Chang, Jason CJ, Broadhurst, David J, Klippsten, Saker, Sharp, Phillip P, Wenzell, Nicole A, Kuzuoglu-Ozturk, Duygu, Wang, Hao-Yuan, Trenker, Raphael, Young, Janet M, Cavero, Devin A, Hiatt, Joseph, Roth, Theodore L, Rathore, Ujjwal, Subramanian, Advait, Noack, Julia, Hubert, Mathieu, Stroud, Robert M, Frankel, Alan D, Rosenberg, Oren S, Verba, Kliment A, Agard, David A, Ott, Melanie, Emerman, Michael, and Jura, Natalia

Subjects
Biological Sciences, Bioinformatics and Computational Biology, Biomedical and Clinical Sciences, Coronaviruses Therapeutics and Interventions, Emerging Infectious Diseases, Infectious Diseases, Coronaviruses, 5.1 Pharmaceuticals, Infection, Good Health and Well Being, Animals, Antiviral Agents, Betacoronavirus, COVID-19, Chlorocebus aethiops, Cloning, Molecular, Coronavirus Infections, Drug Evaluation, Preclinical, Drug Repositioning, HEK293 Cells, Host-Pathogen Interactions, Humans, Immunity, Innate, Mass Spectrometry, Molecular Targeted Therapy, Pandemics, Pneumonia, Viral, Protein Binding, Protein Biosynthesis, Protein Domains, Protein Interaction Mapping, Protein Interaction Maps, Receptors, sigma, SARS-CoV-2, SKP Cullin F-Box Protein Ligases, Vero Cells, Viral Proteins, COVID-19 Drug Treatment, General Science & Technology
Abstract

A newly described coronavirus named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which is the causative agent of coronavirus disease 2019 (COVID-19), has infected over 2.3 million people, led to the death of more than 160,000 individuals and caused worldwide social and economic disruption1,2. There are no antiviral drugs with proven clinical efficacy for the treatment of COVID-19, nor are there any vaccines that prevent infection with SARS-CoV-2, and efforts to develop drugs and vaccines are hampered by the limited knowledge of the molecular details of how SARS-CoV-2 infects cells. Here we cloned, tagged and expressed 26 of the 29 SARS-CoV-2 proteins in human cells and identified the human proteins that physically associated with each of the SARS-CoV-2 proteins using affinity-purification mass spectrometry, identifying 332 high-confidence protein-protein interactions between SARS-CoV-2 and human proteins. Among these, we identify 66 druggable human proteins or host factors targeted by 69 compounds (of which, 29 drugs are approved by the US Food and Drug Administration, 12 are in clinical trials and 28 are preclinical compounds). We screened a subset of these in multiple viral assays and found two sets of pharmacological agents that displayed antiviral activity: inhibitors of mRNA translation and predicted regulators of the sigma-1 and sigma-2 receptors. Further studies of these host-factor-targeting agents, including their combination with drugs that directly target viral enzymes, could lead to a therapeutic regimen to treat COVID-19.

Published
2020

9. A SARS-CoV-2-Human Protein-Protein Interaction Map Reveals Drug Targets and Potential Drug-Repurposing.

Author

Gordon, David E, Jang, Gwendolyn M, Bouhaddou, Mehdi, Xu, Jiewei, Obernier, Kirsten, O'Meara, Matthew J, Guo, Jeffrey Z, Swaney, Danielle L, Tummino, Tia A, Hüttenhain, Ruth, Kaake, Robyn M, Richards, Alicia L, Tutuncuoglu, Beril, Foussard, Helene, Batra, Jyoti, Haas, Kelsey, Modak, Maya, Kim, Minkyu, Haas, Paige, Polacco, Benjamin J, Braberg, Hannes, Fabius, Jacqueline M, Eckhardt, Manon, Soucheray, Margaret, Bennett, Melanie J, Cakir, Merve, McGregor, Michael J, Li, Qiongyu, Naing, Zun Zar Chi, Zhou, Yuan, Peng, Shiming, Kirby, Ilsa T, Melnyk, James E, Chorba, John S, Lou, Kevin, Dai, Shizhong A, Shen, Wenqi, Shi, Ying, Zhang, Ziyang, Barrio-Hernandez, Inigo, Memon, Danish, Hernandez-Armenta, Claudia, Mathy, Christopher JP, Perica, Tina, Pilla, Kala B, Ganesan, Sai J, Saltzberg, Daniel J, Ramachandran, Rakesh, Liu, Xi, Rosenthal, Sara B, Calviello, Lorenzo, Venkataramanan, Srivats, Lin, Yizhu, Wankowicz, Stephanie A, Bohn, Markus, Trenker, Raphael, Young, Janet M, Cavero, Devin, Hiatt, Joe, Roth, Theo, Rathore, Ujjwal, Subramanian, Advait, Noack, Julia, Hubert, Mathieu, Roesch, Ferdinand, Vallet, Thomas, Meyer, Björn, White, Kris M, Miorin, Lisa, Agard, David, Emerman, Michael, Ruggero, Davide, García-Sastre, Adolfo, Jura, Natalia, von Zastrow, Mark, Taunton, Jack, Schwartz, Olivier, Vignuzzi, Marco, d'Enfert, Christophe, Mukherjee, Shaeri, Jacobson, Matt, Malik, Harmit S, Fujimori, Danica G, Ideker, Trey, Craik, Charles S, Floor, Stephen, Fraser, James S, Gross, John, Sali, Andrej, Kortemme, Tanja, Beltrao, Pedro, Shokat, Kevan, Shoichet, Brian K, and Krogan, Nevan J

Subjects
Prevention, Vaccine Related, Biodefense, Infectious Diseases, Rare Diseases, Pneumonia & Influenza, Emerging Infectious Diseases, Lung, Pneumonia, 5.1 Pharmaceuticals, 2.2 Factors relating to the physical environment, Infection
Abstract

An outbreak of the novel coronavirus SARS-CoV-2, the causative agent of COVID-19 respiratory disease, has infected over 290,000 people since the end of 2019, killed over 12,000, and caused worldwide social and economic disruption1,2. There are currently no antiviral drugs with proven efficacy nor are there vaccines for its prevention. Unfortunately, the scientific community has little knowledge of the molecular details of SARS-CoV-2 infection. To illuminate this, we cloned, tagged and expressed 26 of the 29 viral proteins in human cells and identified the human proteins physically associated with each using affinity- purification mass spectrometry (AP-MS), which identified 332 high confidence SARS-CoV-2-human protein-protein interactions (PPIs). Among these, we identify 66 druggable human proteins or host factors targeted by 69 existing FDA-approved drugs, drugs in clinical trials and/or preclinical compounds, that we are currently evaluating for efficacy in live SARS-CoV-2 infection assays. The identification of host dependency factors mediating virus infection may provide key insights into effective molecular targets for developing broadly acting antiviral therapeutics against SARS-CoV-2 and other deadly coronavirus strains.

Published
2020

10. A draft genome sequence of the elusive giant squid, Architeuthis dux

Author

da Fonseca, Rute R, Couto, Alvarina, Machado, Andre M, Brejova, Brona, Albertin, Carolin B, Silva, Filipe, Gardner, Paul, Baril, Tobias, Hayward, Alex, Campos, Alexandre, Ribeiro, Ângela M, Barrio-Hernandez, Inigo, Hoving, Henk-Jan, Tafur-Jimenez, Ricardo, Chu, Chong, Frazão, Barbara, Petersen, Bent, Peñaloza, Fernando, Musacchia, Francesco, Alexander, Graham C, Osório, Hugo, Winkelmann, Inger, Simakov, Oleg, Rasmussen, Simon, Rahman, M Ziaur, Pisani, Davide, Vinther, Jakob, Jarvis, Erich, Zhang, Guojie, Strugnell, Jan M, Castro, L Filipe C, Fedrigo, Olivier, Patricio, Mateus, Li, Qiye, Rocha, Sara, Antunes, Agostinho, Wu, Yufeng, Ma, Bin, Sanges, Remo, Vinar, Tomas, Blagoev, Blagoy, Sicheritz-Ponten, Thomas, Nielsen, Rasmus, and Gilbert, M Thomas P

Subjects
Microbiology, Biological Sciences, Bioinformatics and Computational Biology, Genetics, Human Genome, Biotechnology, Life Below Water, Animals, Biological Evolution, Chromatography, Liquid, Computational Biology, DNA Transposable Elements, Decapodiformes, Gene Expression Profiling, Genome, Genomics, Molecular Sequence Annotation, Multigene Family, RNA, Untranslated, Tandem Mass Spectrometry, Transcriptome, Whole Genome Sequencing, cephalopod, invertebrate, genome assembly
Abstract

BackgroundThe giant squid (Architeuthis dux; Steenstrup, 1857) is an enigmatic giant mollusc with a circumglobal distribution in the deep ocean, except in the high Arctic and Antarctic waters. The elusiveness of the species makes it difficult to study. Thus, having a genome assembled for this deep-sea-dwelling species will allow several pending evolutionary questions to be unlocked.FindingsWe present a draft genome assembly that includes 200 Gb of Illumina reads, 4 Gb of Moleculo synthetic long reads, and 108 Gb of Chicago libraries, with a final size matching the estimated genome size of 2.7 Gb, and a scaffold N50 of 4.8 Mb. We also present an alternative assembly including 27 Gb raw reads generated using the Pacific Biosciences platform. In addition, we sequenced the proteome of the same individual and RNA from 3 different tissue types from 3 other species of squid (Onychoteuthis banksii, Dosidicus gigas, and Sthenoteuthis oualaniensis) to assist genome annotation. We annotated 33,406 protein-coding genes supported by evidence, and the genome completeness estimated by BUSCO reached 92%. Repetitive regions cover 49.17% of the genome.ConclusionsThis annotated draft genome of A. dux provides a critical resource to investigate the unique traits of this species, including its gigantism and key adaptations to deep-sea environments.

Published
2020

12. Elucidation of time-dependent systems biology cell response patterns with time course network enrichment

Author

Wiwie, Christian, Rauch, Alexander, Haakonsson, Anders, Barrio-Hernandez, Inigo, Blagoev, Blagoy, Mandrup, Susanne, Röttger, Richard, and Baumbach, Jan

Subjects
Quantitative Biology - Quantitative Methods
Abstract

Advances in OMICS technologies emerged both massive expression data sets and huge networks modelling the molecular interplay of genes, RNAs, proteins and metabolites. Network enrichment methods combine these two data types to extract subnetwork responses from case/control setups. However, no methods exist to integrate time series data with networks, thus preventing the identification of time-dependent systems biology responses. We close this gap with Time Course Network Enrichment (TiCoNE). It combines a new kind of human-augmented clustering with a novel approach to network enrichment. It finds temporal expression prototypes that are mapped to a network and investigated for enriched prototype pairs interacting more often than expected by chance. Such patterns of temporal subnetwork co-enrichment can be compared between different conditions. With TiCoNE, we identified the first distinguishing temporal systems biology profiles in time series gene expression data of human lung cells after infection with Influenza and Rhino virus. TiCoNE is available online (https://ticone.compbio.sdu.dk) and as Cytoscape app in the Cytoscape App Store (http://apps.cytoscape.org/).

Published
2017

14. Actionable druggable genome-wide Mendelian randomization identifies repurposing opportunities for COVID-19

Author

Gaziano, Liam, Giambartolomei, Claudia, Pereira, Alexandre C., Gaulton, Anna, Posner, Daniel C., Swanson, Sonja A., Ho, Yuk-Lam, Iyengar, Sudha K., Kosik, Nicole M., Vujkovic, Marijana, Gagnon, David R., Bento, A. Patrícia, Barrio-Hernandez, Inigo, Rönnblom, Lars, Hagberg, Niklas, Lundtoft, Christian, Langenberg, Claudia, Pietzner, Maik, Valentine, Dennis, Gustincich, Stefano, Tartaglia, Gian Gaetano, Allara, Elias, Surendran, Praveen, Burgess, Stephen, Zhao, Jing Hua, Peters, James E., Prins, Bram P., Angelantonio, Emanuele Di, Devineni, Poornima, Shi, Yunling, Lynch, Kristine E., DuVall, Scott L., Garcon, Helene, Thomann, Lauren O., Zhou, Jin J., Gorman, Bryan R., Huffman, Jennifer E., O’Donnell, Christopher J., Tsao, Philip S., Beckham, Jean C., Pyarajan, Saiju, Muralidhar, Sumitra, Huang, Grant D., Ramoni, Rachel, Beltrao, Pedro, Danesh, John, Hung, Adriana M., Chang, Kyong-Mi, Sun, Yan V., Joseph, Jacob, Leach, Andrew R., Edwards, Todd L., Cho, Kelly, Gaziano, J. Michael, Butterworth, Adam S., and Casas, Juan P.

Published
2021
Full Text
View/download PDF

16. Systematic identification of structure-specific protein–protein interactions

Author

Holfeld, Aleš; https://orcid.org/0000-0003-0775-8634, Schuster, Dina; https://orcid.org/0000-0001-6611-8237, Sesterhenn, Fabian; https://orcid.org/0000-0001-8331-4344, Gillingham, Alison K; https://orcid.org/0009-0000-3835-2333, Stalder, Patrick; https://orcid.org/0000-0003-4005-8488, Haenseler, Walther; https://orcid.org/0000-0003-4868-3704, Barrio-Hernandez, Inigo; https://orcid.org/0000-0002-5686-0451, Ghosh, Dhiman; https://orcid.org/0000-0003-2087-8075, Vowles, Jane; https://orcid.org/0000-0002-7000-1581, Cowley, Sally A; https://orcid.org/0000-0003-0297-6675, Nagel, Luise; https://orcid.org/0000-0001-8844-7234, Khanppnavar, Basavraj; https://orcid.org/0000-0002-6637-3550, Serdiuk, Tetiana, Beltrao, Pedro; https://orcid.org/0000-0002-2724-7703, Korkhov, Volodymyr M; https://orcid.org/0000-0002-0962-9433, Munro, Sean; https://orcid.org/0000-0001-6160-5773, Riek, Roland; https://orcid.org/0000-0002-6333-066X, de Souza, Natalie; https://orcid.org/0000-0003-4286-8951, Picotti, Paola; https://orcid.org/0000-0002-4109-3552, Holfeld, Aleš; https://orcid.org/0000-0003-0775-8634, Schuster, Dina; https://orcid.org/0000-0001-6611-8237, Sesterhenn, Fabian; https://orcid.org/0000-0001-8331-4344, Gillingham, Alison K; https://orcid.org/0009-0000-3835-2333, Stalder, Patrick; https://orcid.org/0000-0003-4005-8488, Haenseler, Walther; https://orcid.org/0000-0003-4868-3704, Barrio-Hernandez, Inigo; https://orcid.org/0000-0002-5686-0451, Ghosh, Dhiman; https://orcid.org/0000-0003-2087-8075, Vowles, Jane; https://orcid.org/0000-0002-7000-1581, Cowley, Sally A; https://orcid.org/0000-0003-0297-6675, Nagel, Luise; https://orcid.org/0000-0001-8844-7234, Khanppnavar, Basavraj; https://orcid.org/0000-0002-6637-3550, Serdiuk, Tetiana, Beltrao, Pedro; https://orcid.org/0000-0002-2724-7703, Korkhov, Volodymyr M; https://orcid.org/0000-0002-0962-9433, Munro, Sean; https://orcid.org/0000-0001-6160-5773, Riek, Roland; https://orcid.org/0000-0002-6333-066X, de Souza, Natalie; https://orcid.org/0000-0003-4286-8951, and Picotti, Paola; https://orcid.org/0000-0002-4109-3552

Abstract

The physical interactome of a protein can be altered upon perturbation, modulating cell physiology and contributing to disease. Identifying interactome differences of normal and disease states of proteins could help understand disease mechanisms, but current methods do not pinpoint structure-specific PPIs and interaction interfaces proteome-wide. We used limited proteolysis–mass spectrometry (LiP–MS) to screen for structure-specific PPIs by probing for protease susceptibility changes of proteins in cellular extracts upon treatment with specific structural states of a protein. We first demonstrated that LiP–MS detects well-characterized PPIs, including antibody–target protein interactions and interactions with membrane proteins, and that it pinpoints interfaces, including epitopes. We then applied the approach to study conformation-specific interactors of the Parkinson’s disease hallmark protein alpha-synuclein (aSyn). We identified known interactors of aSyn monomer and amyloid fibrils and provide a resource of novel putative conformation-specific aSyn interactors for validation in further studies. We also used our approach on GDP- and GTP-bound forms of two Rab GTPases, showing detection of differential candidate interactors of conformationally similar proteins. This approach is applicable to screen for structure-specific interactomes of any protein, including posttranslationally modified and unmodified, or metabolite-bound and unbound protein states.

Published
2024

17. Genetic interaction library screening with a next-generation dual guide CRISPR system

Author

Burgold, Thomas, primary, Karakoc, Emre, additional, Goncalves, Emanuel, additional, Dwane, Lisa, additional, Barrio-Hernandez, Inigo, additional, Silva, Romina Oliveira, additional, Souster, Emily, additional, Sharma, Mamta, additional, Beck, Alexandra, additional, Koh, Gene, additional, Zalmas, Lykourgos-Panagiotis, additional, Garnett, Mathew, additional, and Bassett, Andrew R, additional

Published
2024
Full Text
View/download PDF

19. SARS‐CoV‐2 infection remodels the host protein thermal stability landscape

Author

Selkrig, Joel, Stanifer, Megan, Mateus, André, Mitosch, Karin, Barrio‐Hernandez, Inigo, Rettel, Mandy, Kim, Heeyoung, Voogdt, Carlos G P, Walch, Philipp, Kee, Carmon, Kurzawa, Nils, Stein, Frank, Potel, Clément, Jarzab, Anna, Kuster, Bernhard, Bartenschlager, Ralf, Boulant, Steeve, Beltrao, Pedro, Typas, Athanasios, and Savitski, Mikhail M

Published
2021
Full Text
View/download PDF

23. Towards a structurally resolved human protein interaction network

Author

Burke, David F, Bryant, Patrick, Barrio-Hernandez, Inigo, Memon, Danish, Pozzati, Gabriele, Shenoy, Aditi, Zhu, Wensi, Dunham, Alistair S, Albanese, Pascal, Keller, Andrew, Scheltema, Richard A, Bruce, James E, Leitner, Alexander, Kundrotas, Petras, Beltrao, Pedro, Elofsson, Arne, Burke, David F, Bryant, Patrick, Barrio-Hernandez, Inigo, Memon, Danish, Pozzati, Gabriele, Shenoy, Aditi, Zhu, Wensi, Dunham, Alistair S, Albanese, Pascal, Keller, Andrew, Scheltema, Richard A, Bruce, James E, Leitner, Alexander, Kundrotas, Petras, Beltrao, Pedro, and Elofsson, Arne

Abstract

Cellular functions are governed by molecular machines that assemble through protein-protein interactions. Their atomic details are critical to studying their molecular mechanisms. However, fewer than 5% of hundreds of thousands of human protein interactions have been structurally characterized. Here we test the potential and limitations of recent progress in deep-learning methods using AlphaFold2 to predict structures for 65,484 human protein interactions. We show that experiments can orthogonally confirm higher-confidence models. We identify 3,137 high-confidence models, of which 1,371 have no homology to a known structure. We identify interface residues harboring disease mutations, suggesting potential mechanisms for pathogenic variants. Groups of interface phosphorylation sites show patterns of co-regulation across conditions, suggestive of coordinated tuning of multiple protein interactions as signaling responses. Finally, we provide examples of how the predicted binary complexes can be used to build larger assemblies helping to expand our understanding of human cell biology.

Published
2023

24. Towards a structurally resolved human protein interaction network

Author

Afd Biomol.Mass Spect. and Proteomics, Biomolecular Mass Spectrometry and Proteomics, Burke, David F, Bryant, Patrick, Barrio-Hernandez, Inigo, Memon, Danish, Pozzati, Gabriele, Shenoy, Aditi, Zhu, Wensi, Dunham, Alistair S, Albanese, Pascal, Keller, Andrew, Scheltema, Richard A, Bruce, James E, Leitner, Alexander, Kundrotas, Petras, Beltrao, Pedro, Elofsson, Arne, Afd Biomol.Mass Spect. and Proteomics, Biomolecular Mass Spectrometry and Proteomics, Burke, David F, Bryant, Patrick, Barrio-Hernandez, Inigo, Memon, Danish, Pozzati, Gabriele, Shenoy, Aditi, Zhu, Wensi, Dunham, Alistair S, Albanese, Pascal, Keller, Andrew, Scheltema, Richard A, Bruce, James E, Leitner, Alexander, Kundrotas, Petras, Beltrao, Pedro, and Elofsson, Arne

Published
2023

25. Systematic identification of structure-specific protein–protein interactions

Author

Holfeld, Aleš; https://orcid.org/0000-0003-0775-8634, Schuster, Dina; https://orcid.org/0000-0001-6611-8237, Sesterhenn, Fabian; https://orcid.org/0000-0001-8331-4344, Stalder, Patrick; https://orcid.org/0000-0003-4005-8488, Haenseler, Walther; https://orcid.org/0000-0003-4868-3704, Barrio-Hernandez, Inigo; https://orcid.org/0000-0002-5686-0451, Ghosh, Dhiman, Vowles, Jane; https://orcid.org/0000-0002-7000-1581, Cowley, Sally A; https://orcid.org/0000-0003-0297-6675, Nagel, Luise; https://orcid.org/0000-0001-8844-7234, Khanppnavar, Basavraj; https://orcid.org/0000-0002-6637-3550, Beltrao, Pedro; https://orcid.org/0000-0002-2724-7703, Korkhov, Volodymyr M; https://orcid.org/0000-0002-0962-9433, Riek, Roland; https://orcid.org/0000-0002-6333-066X, de Souza, Natalie; https://orcid.org/0000-0003-4286-8951, Picotti, Paola; https://orcid.org/0000-0002-4109-3552, Holfeld, Aleš; https://orcid.org/0000-0003-0775-8634, Schuster, Dina; https://orcid.org/0000-0001-6611-8237, Sesterhenn, Fabian; https://orcid.org/0000-0001-8331-4344, Stalder, Patrick; https://orcid.org/0000-0003-4005-8488, Haenseler, Walther; https://orcid.org/0000-0003-4868-3704, Barrio-Hernandez, Inigo; https://orcid.org/0000-0002-5686-0451, Ghosh, Dhiman, Vowles, Jane; https://orcid.org/0000-0002-7000-1581, Cowley, Sally A; https://orcid.org/0000-0003-0297-6675, Nagel, Luise; https://orcid.org/0000-0001-8844-7234, Khanppnavar, Basavraj; https://orcid.org/0000-0002-6637-3550, Beltrao, Pedro; https://orcid.org/0000-0002-2724-7703, Korkhov, Volodymyr M; https://orcid.org/0000-0002-0962-9433, Riek, Roland; https://orcid.org/0000-0002-6333-066X, de Souza, Natalie; https://orcid.org/0000-0003-4286-8951, and Picotti, Paola; https://orcid.org/0000-0002-4109-3552

Abstract

Protein–protein interactions (PPIs) mediate numerous essential functions and regulatory events in living organisms. The physical interactome of a protein can be abnormally altered in response to external and internal cues, thus modulating cell physiology and contributing to human disease. In particular, neurodegenerative diseases due to the accumulation of aberrantly folded and aggregated proteins may lead to alterations in protein interactomes. Identifying changes in the interactomes of normal and disease states of proteins could help to understand molecular disease mechanisms, but current interactomics methods are limited in the ability to pinpoint structure-specific PPIs and their interaction interfaces on a proteome-wide scale. Here, we adapted limited proteolysis–mass spectrometry (LiP–MS) to systematically identify putative structure-specific PPIs by probing protein structural alterations within cellular extracts upon treatment with specific structural states of a given protein. We demonstrate the feasibility of our method to detect well-characterized PPIs, including antibody–target protein interactions and interactions with membrane proteins, and show that it pinpoints PPI interfaces. We then applied the LiP–MS approach to study the structure-specific interactors of the Parkinson’s disease hallmark protein alpha-synuclein (aSyn). We identified several previously known interactors of both aSyn monomer and amyloid fibrils and provide a resource of novel putative structure-specific interactors for further studies. This approach is applicable to identify structure-specific interactomes of any protein, including posttranslationally modified and unmodified, or metabolite-bound and unbound structural states of proteins.

Published
2023

28. Systematic identification of structure-specific protein–protein interactions

Author

Holfeld, Aleš, primary, Schuster, Dina, additional, Sesterhenn, Fabian, additional, Stalder, Patrick, additional, Haenseler, Walther, additional, Barrio-Hernandez, Inigo, additional, Ghosh, Dhiman, additional, Vowles, Jane, additional, Cowley, Sally A., additional, Nagel, Luise, additional, Khanppnavar, Basavraj, additional, Beltrao, Pedro, additional, Korkhov, Volodymyr M., additional, Riek, Roland, additional, Souza, Natalie de, additional, and Picotti, Paola, additional

Published
2023
Full Text
View/download PDF

30. Towards a structurally resolved human protein interaction network

Author

Elofsson, Arne, primary, Burke, David, additional, Bryant, Patrick, additional, Barrio-Hernandez, Inigo, additional, Memon, Danish, additional, Pozzati, Gabriele, additional, Shenoy, Aditi, additional, Zhu, Wensi, additional, Dunham, Alistair, additional, Albanese, Pascal, additional, Keller, Andrew, additional, Scheltema, Richard, additional, Bruce, James, additional, Leitner, Alexander, additional, Kundrotas, Petras, additional, and Beltrao, Pedro, additional

Published
2021
Full Text
View/download PDF

31. Towards a structurally resolved human protein interaction network

Author

Burke, David F., primary, Bryant, Patrick, additional, Barrio-Hernandez, Inigo, additional, Memon, Danish, additional, Pozzati, Gabriele, additional, Shenoy, Aditi, additional, Zhu, Wensi, additional, Dunham, Alistair S, additional, Albanese, Pascal, additional, Keller, Andrew, additional, Scheltema, Richard A., additional, Bruce, James E., additional, Leitner, Alexander, additional, Kundrotas, Petras, additional, Beltrao, Pedro, additional, and Elofsson, Arne, additional

Published
2021
Full Text
View/download PDF

32. Towards a structurally resolved human protein interaction network

Author

Burke, David F., Bryant, Patrick, Barrio-Hernandez, Inigo, Memon, Danish, Pozzati, Gabriele, Shenoy, Aditi, Zhu, Wensi, Dunham, Alistair S., Albanese, Pascal, Keller, Andrew, Scheltema, Richard A., Bruce, James E., Leitner, Alexander, Kundrotas, Petras, Beltrao, Pedro, and Elofsson, Arne

Abstract

All cellular functions are governed by complex molecular machines that assemble through protein-protein interactions. Their atomic details are critical to the study of their molecular mechanisms but fewer than 5% of hundreds of thousands of human interactions have been structurally characterized. Here, we test the potential and limitations of recent progress in deep-learning methods using AlphaFold2 to predict structures for 65,484 human interactions. We show that higher confidence models are enriched in interactions supported by affinity or structure based methods and can be orthogonally confirmed by spatial constraints defined by cross-link data. We identify 3,137 high confidence models, of which 1,371 have no homology to a known structure, from which we identify interface residues harbouring disease mutations, suggesting potential mechanisms for pathogenic variants. We find groups of interface phosphorylation sites that show patterns of co-regulation across conditions, suggestive of coordinated tuning of multiple interactions as signalling responses. Finally, we provide examples of how the predicted binary complexes can be used to build larger assemblies. Accurate prediction of protein complexes promises to greatly expand our understanding of the atomic details of human cell biology in health and disease., bioRxiv

Published
2021
Full Text
View/download PDF

33. Network expansion of genetic associations defines a pleiotropy map of human cell biology

Author

Barrio-Hernandez, Inigo, Schwartzentruber, Jeremy, Shrivastava, Anjali, del Toro, Noemi, Zhang, Qian, Bradley, Glyn, Hermjakob, Henning, Orchard, Sandra, Dunham, Ian, Anderson, Carl A., Porras, Pablo, and Beltrao, Pedro

Abstract

Proteins that interact within molecular networks tend to have similar functions and when perturbed influence the same organismal traits. Interaction networks can be used to expand the list of likely trait associated genes from genome-wide association studies (GWAS). Here, we used improvements in SNP-to-gene mapping to perform network based expansion of trait associated genes for 1,002 human traits showing that this recovers known disease genes or drug targets. The similarity of network expansion scores identifies groups of traits likely to share a common genetic basis as well as the biological processes underlying this. We identified 73 pleiotropic gene modules linked to multiple traits that are enriched in genes involved in processes such as protein ubiquitination and RNA processing. We show examples of modules linked to human diseases enriched in genes with pathogenic variants found in patients or relevant mouse knock-out phenotypes and can be used to map targets of approved drugs for repurposing opportunities. Finally, we illustrate the use of the network expansion scores to study genes at inflammatory bowel disease (IBD) GWAS loci, and implicate IBD-relevant genes with strong functional and genetic support., bioRxiv

Published
2021

34. Network expansion of genetic associations defines a pleiotropy map of human cell biology

Author

Barrio-Hernandez, Inigo, primary, Schwartzentruber, Jeremy, additional, Shrivastava, Anjali, additional, del-Toro, Noemi, additional, Zhang, Qian, additional, Bradley, Glyn, additional, Hermjakob, Henning, additional, Orchard, Sandra, additional, Dunham, Ian, additional, Anderson, Carl A., additional, Porras, Pablo, additional, and Beltrao, Pedro, additional

Published
2021
Full Text
View/download PDF

36. Actionable druggable genome-wide Mendelian randomization identifies repurposing opportunities for COVID-19

Author

Gaziano, Liam, primary, Giambartolomei, Claudia, additional, Pereira, Alexandre C, additional, Gaulton, Anna, additional, Posner, Daniel C, additional, Swanson, Sonja A, additional, Ho, Yuk-Lam, additional, Iyengar, Sudha K, additional, Kosik, Nicole M, additional, Vujkovic, Marijana, additional, Gagnon, David R, additional, Bento, A Patrícia, additional, Beltrao, Pedro, additional, Barrio-Hernandez, Inigo, additional, Rönnblom, Lars, additional, Hagberg, Niklas, additional, Lundtoft, Christian, additional, Langenberg, Claudia, additional, Pietzner, Maik, additional, Valentine, Dennis, additional, Allara, Elias, additional, Surendran, Praveen, additional, Burgess, Stephen, additional, Zhao, Jing Hua, additional, Peters, James E, additional, Prins, Bram P, additional, Danesh, John, additional, Devineni, Poornima, additional, Shi, Yunling, additional, Lynch, Kristine E, additional, DuVall, Scott L, additional, Garcon, Helene, additional, Thomann, Lauren O, additional, Zhou, Jin J, additional, Gorman, Bryan R, additional, Huffman, Jennifer E, additional, O’Donnell, Christopher J, additional, Tsao, Philip S, additional, Beckham, Jean C, additional, Pyarajan, Saiju, additional, Muralidhar, Sumitra, additional, Huang, Grant D, additional, Ramoni, Rachel, additional, Hung, Adriana M, additional, Chang, Kyong-Mi, additional, Sun, Yan V, additional, Joseph, Jacob, additional, Leach, Andrew R, additional, Edwards, Todd L, additional, Cho, Kelly, additional, Gaziano, J Michael, additional, Butterworth, Adam S, additional, and Casas, Juan P, additional

Published
2020
Full Text
View/download PDF

37. SARS-CoV-2 infection remodels the host protein thermal stability landscape

Author

Selkrig, Joel, primary, Stanifer, Megan, additional, Mateus, André, additional, Mitosch, Karin, additional, Barrio-Hernandez, Inigo, additional, Rettel, Mandy, additional, Kim, Heeyoung, additional, Voogdt, Carlos, additional, Walch, Philipp, additional, Kee, Carmon, additional, Kurzawa, Nils, additional, Stein, Frank, additional, Potel, Clement, additional, Jarzab, Anna, additional, Kuster, Bernhard, additional, Bartenschlager, Ralf, additional, Boulant, Steeve, additional, Beltrao, Pedro, additional, Typas, Athanasios, additional, and Savitski, Mikhail, additional

Published
2020
Full Text
View/download PDF

38. Comparative host-coronavirus protein interaction networks reveal pan-viral disease mechanisms

Author

Gordon, David E., Hiatt, Joseph, Bouhaddou, Mehdi, Rezelj, Veronica V., Ulferts, Svenja, Braberg, Hannes, Jureka, Alexander S., Obernier, Kirsten, Guo, Jeffrey Z., Batra, Jyoti, Kaake, Robyn M., Weckstein, Andrew R., Owens, Tristan W., Gupta, Meghna, Pourmal, Sergei, Titus, Erron W., Cakir, Merve, Soucheray, Margaret, McGregor, Michael, Cakir, Zeynep, Jang, Gwendolyn, O’Meara, Matthew J., Zhang, Ziyang, Foussard, Helene, Rojc, Ajda, Zhou, Yuan, Kuchenov, Dmitry, Hüttenhain, Ruth, Xu, Jiewei, Eckhardt, Manon, Swaney, Danielle L., Fabius, Jacqueline M., Ummadi, Manisha, Tutuncuoglu, Beril, Rathore, Ujjwal, Modak, Maya, Haas, Paige, Haas, Kelsey M., Naing, Zun Zar Chi, Pulido, Ernst H., Shi, Ying, Barrio-Hernandez, Inigo, Memon, Danish, Petsalaki, Eirini, Dunham, Alistair, Correa Marrero, Miguel, Burke, David, Koh, Cassandra, Vallet, Thomas, Silvas, Jesus A., Azumaya, Caleigh M., Billesbølle, Christian, Brilot, Axel F., Campbell, Melody G., Diallo, Amy, Dickinson, Miles Sasha, Diwanji, Devan, Herrera, Nadia, Hoppe, Nick, Kratochvil, Huong T., Liu, Yanxin, Merz, Gregory E., Moritz, Michelle, Nguyen, Henry C., Nowotny, Carlos, Puchades, Cristina, Rizo, Alexandrea N., Schulze-Gahmen, Ursula, Smith, Amber M., Sun, Ming, Young, Iris D., Zhao, Jianhua, Asarnow, Daniel, Biel, Justin, Braxton, Julian R., Chen, Jen, Chio, Cynthia M., Chio, Un Seng, Deshpande, Ishan, Doan, Loan, Faust, Bryan, Flores, Sebastian, Jin, Mingliang, Kim, Kate, Lam, Victor L., Li, Fei, Li, Junrui, Li, Yen-Li, Li, Yang, Liu, Xi, Lo, Megan, Lopez, Kyle E., Melo, Arthur A., Nguyen, Phuong, Paulino, Joana, Pawar, Komal Ishwar, Peters, Jessica K., Pospiech, Thomas H., Safari, Maliheh, Sangwan, Smriti, Schaefer, Kaitlin, Thomas, Paul V., Thwin, Aye C., Trenker, Raphael, Tse, Eric, Tsui, Tsz Kin Martin, Wang, Feng, Whitis, Natalie, Yu, Zanlin, Zhang, Kaihua, Zhang, Yang, Zhou, Fengbo, Saltzberg, Daniel, QCRG Structural Biology Consortium, Hodder, Anthony J., Williams, Daniel M., White, Kris M., Rosales, Romel, Kehrer, Thomas, Miorin, Lisa, Moreno, Elena, Patel, Arvind H., Rihn, Suzannah, Khalid, Mir M., Vallejo-Gracia, Albert, Fozouni, Parinaz, Simoneau, Camille R., Roth, Theodore L., Wu, David, Karim, Mohd Anisul, Ghoussaini, Maya, Dunham, Ian, Berardi, Francesco, Weigang, Sebastian, Chazal, Maxime, Park, Jisoo, Logue, James, McGrath, Marisa, Weston, Stuart, Hastie, C. James, Elliott, Matthew, Brown, Fiona, Burness, Kerry A., Reid, Elaine, Dorward, Mark, Johnson, Clare, Wilkinson, Stuart G., Geyer, Anna, Giesel, Daniel M., Baillie, Carla, Raggett, Samantha, Leech, Hannah, Goodman, Nicola, Keough, Kathleen C., Lind, Abigail L., Zoonomia Consortium, Klesh, Reyna J., Hemphill, Kafi R., Carlson-Stevermer, Jared, Oki, Jennifer, Holden, Kevin, Maures, Travis, Pollard, Katherine S., Sali, Andrej, Agard, David A., Cheng, Yifan, Fraser, James S., Frost, Adam, Jura, Natalia, Kortemme, Tanja, Manglik, Aashish, Southworth, Daniel R., Stroud, Robert M., Alessi, Dario R., Davies, Paul, Frieman, Matthew B., Ideker, Trey, Abate, Carmen, Jouvenet, Nolwenn, Kochs, Georg, Shoichet, Brian, Ott, Melanie, Palmarini, Massimo, Shokat, Kevan M., García-Sastre, Adolfo, Rassen, Jeremy A., Grosse, Robert, Rosenberg, Oren S., Verba, Kliment A., Basler, Christopher F., Vignuzzi, Marco, Peden, Andrew A., Beltrao, Pedro, and Krogan, Nevan J.

Subjects
viruses, virus diseases
Abstract

Introduction The emergence of three lethal coronaviruses in, Science, 370 (6521), ISSN:0036-8075, ISSN:1095-9203

Published
2020
Full Text
View/download PDF

39. A draft genome sequence of the elusive giant squid, Architeuthis dux

Author

da Fonseca, Rute R., Couto, Alvarina, Machado, Andre M., Brejova, Brona, Albertin, Carolin B., Silva, Filipe, Gardner, Paul, Baril, Tobias, Hayward, Alex, Campos, Alexandre, Ribeiro, Ângela M., Barrio-Hernandez, Inigo, Hoving, Henk-Jan, Tafur-Jimenez, Ricardo, Chu, Chong, Frazão, Barbara, Petersen, Bent, Peñaloza, Fernando, Musacchia, Francesco, Alexander, Graham C., Jr., Osório, Hugo, Winkelmann, Inger, Simakov, Oleg, Rasmussen, Simon, Rahman, M. Ziaur, Pisani, Davide, Vinther, Jakob, Jarvis, Erich, Zhang, Guojie, Strugnell, Jan M., Castro, L. Filipe C., Fedrigo, Olivier, Patricio, Mateus, Li, Qiye, Rocha, Sara, Antunes, Agostinho, Wu, Yufeng, Ma, Bin, Sanges, Remo, Vinar, Tomas, Blagoev, Blagoy, Sicheritz-Ponten, Thomas, Nielsen, Rasmus, Gilbert, M. Thomas P., da Fonseca, Rute R., Couto, Alvarina, Machado, Andre M., Brejova, Brona, Albertin, Carolin B., Silva, Filipe, Gardner, Paul, Baril, Tobias, Hayward, Alex, Campos, Alexandre, Ribeiro, Ângela M., Barrio-Hernandez, Inigo, Hoving, Henk-Jan, Tafur-Jimenez, Ricardo, Chu, Chong, Frazão, Barbara, Petersen, Bent, Peñaloza, Fernando, Musacchia, Francesco, Alexander, Graham C., Jr., Osório, Hugo, Winkelmann, Inger, Simakov, Oleg, Rasmussen, Simon, Rahman, M. Ziaur, Pisani, Davide, Vinther, Jakob, Jarvis, Erich, Zhang, Guojie, Strugnell, Jan M., Castro, L. Filipe C., Fedrigo, Olivier, Patricio, Mateus, Li, Qiye, Rocha, Sara, Antunes, Agostinho, Wu, Yufeng, Ma, Bin, Sanges, Remo, Vinar, Tomas, Blagoev, Blagoy, Sicheritz-Ponten, Thomas, Nielsen, Rasmus, and Gilbert, M. Thomas P.

Abstract

© The Author(s), 2020. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in da Fonseca, R. R., Couto, A., Machado, A. M., Brejova, B., Albertin, C. B., Silva, F., Gardner, P., Baril, T., Hayward, A., Campos, A., Ribeiro, A. M., Barrio-Hernandez, I., Hoving, H. J., Tafur-Jimenez, R., Chu, C., Frazao, B., Petersen, B., Penaloza, F., Musacchia, F., Alexander, G. C., Osorio, H., Winkelmann, I., Simakov, O., Rasmussen, S., Rahman, M. Z., Pisani, D., Vinther, J., Jarvis, E., Zhang, G., Strugnell, J. M., Castro, L. F. C., Fedrigo, O., Patricio, M., Li, Q., Rocha, S., Antunes, A., Wu, Y., Ma, B., Sanges, R., Vinar, T., Blagoev, B., Sicheritz-Ponten, T., Nielsen, R., & Gilbert, M. T. P. A draft genome sequence of the elusive giant squid, Architeuthis dux. Gigascience, 9(1), (2020): giz152. doi: 10.1093/gigascience/giz152., Background: The giant squid (Architeuthis dux; Steenstrup, 1857) is an enigmatic giant mollusc with a circumglobal distribution in the deep ocean, except in the high Arctic and Antarctic waters. The elusiveness of the species makes it difficult to study. Thus, having a genome assembled for this deep-sea–dwelling species will allow several pending evolutionary questions to be unlocked. Findings: We present a draft genome assembly that includes 200 Gb of Illumina reads, 4 Gb of Moleculo synthetic long reads, and 108 Gb of Chicago libraries, with a final size matching the estimated genome size of 2.7 Gb, and a scaffold N50 of 4.8 Mb. We also present an alternative assembly including 27 Gb raw reads generated using the Pacific Biosciences platform. In addition, we sequenced the proteome of the same individual and RNA from 3 different tissue types from 3 other species of squid (Onychoteuthis banksii, Dosidicus gigas, and Sthenoteuthis oualaniensis) to assist genome annotation. We annotated 33,406 protein-coding genes supported by evidence, and the genome completeness estimated by BUSCO reached 92%. Repetitive regions cover 49.17% of the genome. Conclusions: This annotated draft genome of A. dux provides a critical resource to investigate the unique traits of this species, including its gigantism and key adaptations to deep-sea environments., R.R.F. thanks the Villum Fonden for grant VKR023446 (Villum Fonden Young Investigator Grant), the Portuguese Science Foundation (FCT) for grant PTDC/MAR/115347/2009; COMPETE-FCOMP-01-012; FEDER-015453, Marie Curie Actions (FP7-PEOPLE-2010-IEF, Proposal 272927), and the Danish National Research Foundation (DNRF96) for its funding of the Center for Macroecology, Evolution, and Climate. H.O. thanks the Rede Nacional de Espectrometria de Massa, ROTEIRO/0028/2013, ref. LISBOA-01-0145-FEDER-022125, supported by COMPETE and North Portugal Regional Operational Programme (Norte2020), under the PORTUGAL 2020 Partnership Agreement, through the European Regional Development Fund (ERDF). A.C. thanks FCT for project UID/Multi/04423/2019. M.P. acknowledges the support from the Wellcome Trust (grant number WT108749/Z/15/Z) and the European Molecular Biology Laboratory. M.P.T.G. thanks the Danish National Research Foundation for its funding of the Center for GeoGenetics (grant DNRF94) and Lundbeck Foundation for grant R52–5062 on Pathogen Palaeogenomics. S.R. was supported by the Novo Nordisk Foundation grant NNF14CC0001. A.H. is supported by a Biotechnology and Biological Sciences Research Council David Phillips Fellowship (fellowship reference: BB/N020146/1). T.B. is supported by the Biotechnology and Biological Sciences Research Council-funded South West Biosciences Doctoral Training Partnership (training grant reference BB/M009122/1). This work was partially funded by the Lundbeck Foundation (R52-A4895 to B.B.). H.J.T.H. was supported by the David and Lucile Packard Foundation, the Netherlands Organization for Scientific Research (#825.09.016), and currently by the Deutsche Forschungsgemeinschaft (DFG) under grant HO 5569/2-1 (Emmy Noether Junior Research Group). T.V. and B. Brejova were supported by grants from the Slovak grant agency VEGA (1/0684/16, 1/0458/18). F.S. was supported by a PhD grant (SFRH/BD/126560/2016) from FCT. A.A. was partly supported by the FCT project PTDC

Published
2020

40. Phosphoproteomic profiling reveals a defined genetic program for osteoblastic lineage commitment of human bone marrow-derived stromal stem cells

Author

Barrio-Hernandez, Inigo, Jafari, Abbas, Rigbolt, Kristoffer T.G., Hallenborg, Philip, Sanchez-Quiles, Virginia, Skovrind, Ida, Akimov, Vyacheslav, Kratchmarova, Irina, Dengjel, Joern, Kassem, Moustapha, Blagoev, Blagoy, Barrio-Hernandez, Inigo, Jafari, Abbas, Rigbolt, Kristoffer T.G., Hallenborg, Philip, Sanchez-Quiles, Virginia, Skovrind, Ida, Akimov, Vyacheslav, Kratchmarova, Irina, Dengjel, Joern, Kassem, Moustapha, and Blagoev, Blagoy

Abstract

Bone marrow-derived mesenchymal stem cells (MSCs) differentiate into osteoblasts upon stimulation by signals present in their niche. Because the global signaling cascades involved in the early phases of MSCs osteoblast (OB) differentiation are not well-defined, we used quantitative mass spectrometry to delineate changes in human MSCs proteome and phosphoproteome during the first 24 h of their OB lineage commitment. The temporal profiles of 6252 proteins and 15,059 phosphorylation sites suggested at least two distinct signaling waves: one peaking within 30 to 60 min after stimulation and a second upsurge after 24 h. In addition to providing a comprehensive view of the proteome and phosphoproteome dynamics during early MSCs differentiation, our analyses identified a key role of serine/threonine protein kinase D1 (PRKD1) in OB commitment. At the onset of OB differentiation, PRKD1 initiates activation of the pro-osteogenic transcription factor RUNX2 by triggering phosphorylation and nuclear exclusion of the histone deacetylase HDAC7.

Published
2020

41. A SARS-CoV-2-Human Protein-Protein Interaction Map Reveals Drug Targets and Potential Drug-Repurposing

Author

Gordon, David E., primary, Jang, Gwendolyn M., additional, Bouhaddou, Mehdi, additional, Xu, Jiewei, additional, Obernier, Kirsten, additional, O’Meara, Matthew J., additional, Guo, Jeffrey Z., additional, Swaney, Danielle L., additional, Tummino, Tia A., additional, Hüttenhain, Ruth, additional, Kaake, Robyn M., additional, Richards, Alicia L., additional, Tutuncuoglu, Beril, additional, Foussard, Helene, additional, Batra, Jyoti, additional, Haas, Kelsey, additional, Modak, Maya, additional, Kim, Minkyu, additional, Haas, Paige, additional, Polacco, Benjamin J., additional, Braberg, Hannes, additional, Fabius, Jacqueline M., additional, Eckhardt, Manon, additional, Soucheray, Margaret, additional, Bennett, Melanie J., additional, Cakir, Merve, additional, McGregor, Michael J, additional, Li, Qiongyu, additional, Naing, Zun Zar Chi, additional, Zhou, Yuan, additional, Peng, Shiming, additional, Kirby, Ilsa T., additional, Melnyk, James E., additional, Chorba, John S., additional, Lou, Kevin, additional, Dai, Shizhong A., additional, Shen, Wenqi, additional, Shi, Ying, additional, Zhang, Ziyang, additional, Barrio-Hernandez, Inigo, additional, Memon, Danish, additional, Hernandez-Armenta, Claudia, additional, Mathy, Christopher J.P., additional, Perica, Tina, additional, Pilla, Kala B., additional, Ganesan, Sai J., additional, Saltzberg, Daniel J., additional, Ramachandran, Rakesh, additional, Liu, Xi, additional, Rosenthal, Sara B., additional, Calviello, Lorenzo, additional, Venkataramanan, Srivats, additional, Lin, Yizhu, additional, Wankowicz, Stephanie A., additional, Bohn, Markus, additional, Trenker, Raphael, additional, Young, Janet M., additional, Cavero, Devin, additional, Hiatt, Joe, additional, Roth, Theo, additional, Rathore, Ujjwal, additional, Subramanian, Advait, additional, Noack, Julia, additional, Hubert, Mathieu, additional, Roesch, Ferdinand, additional, Vallet, Thomas, additional, Meyer, Björn, additional, White, Kris M., additional, Miorin, Lisa, additional, Agard, David, additional, Emerman, Michael, additional, Ruggero, Davide, additional, García-Sastre, Adolfo, additional, Jura, Natalia, additional, Zastrow, Mark von, additional, Taunton, Jack, additional, Schwartz, Olivier, additional, Vignuzzi, Marco, additional, d’Enfert, Christophe, additional, Mukherjee, Shaeri, additional, Jacobson, Matt, additional, Malik, Harmit S., additional, Fujimori, Danica G., additional, Ideker, Trey, additional, Craik, Charles S., additional, Floor, Stephen, additional, Fraser, James S., additional, Gross, John, additional, Sali, Andrej, additional, Kortemme, Tanja, additional, Beltrao, Pedro, additional, Shokat, Kevan, additional, Shoichet, Brian K., additional, and Krogan, Nevan J., additional

Published
2020
Full Text
View/download PDF

43. Genome-wide meta-analysis, fine-mapping, and integrative prioritization identify new Alzheimer’s disease risk genes

Author

Schwartzentruber, Jeremy, primary, Cooper, Sarah, additional, Liu, Jimmy Z, additional, Barrio-Hernandez, Inigo, additional, Bello, Erica, additional, Kumasaka, Natsuhiko, additional, Johnson, Toby, additional, Estrada, Karol, additional, Gaffney, Daniel J., additional, Beltrao, Pedro, additional, and Bassett, Andrew, additional

Published
2020
Full Text
View/download PDF

44. Phosphoproteomic profiling reveals a defined genetic program for osteoblastic lineage commitment of human bone marrow–derived stromal stem cells

Author

Barrio-Hernandez, Inigo, primary, Jafari, Abbas, additional, Rigbolt, Kristoffer T.G., additional, Hallenborg, Philip, additional, Sanchez-Quiles, Virginia, additional, Skovrind, Ida, additional, Akimov, Vyacheslav, additional, Kratchmarova, Irina, additional, Dengjel, Joern, additional, Kassem, Moustapha, additional, and Blagoev, Blagoy, additional

Published
2019
Full Text
View/download PDF

45. Time-Resolved Systems Medicine Reveals Viral Infection-Modulating Host Targets

Author

Wiwie, Christian, primary, Kuznetsova, Irina, additional, Mostafa, Ahmed, additional, Rauch, Alexander, additional, Haakonsson, Anders, additional, Barrio-Hernandez, Inigo, additional, Blagoev, Blagoy, additional, Mandrup, Susanne, additional, Schmidt, Harald H.H.W., additional, Pleschka, Stephan, additional, Röttger, Richard, additional, and Baumbach, Jan, additional

Published
2019
Full Text
View/download PDF

49. StUbEx PLUSA Modified Stable Tagged Ubiquitin Exchange System for Peptide Level Purification and In-Depth Mapping of Ubiquitination Sites

Author

Akimov, Vyacheslav, Olsen, Louise C. B., Hansen, Sten V. F., Barrio-Hernandez, Inigo, Puglia, Michele, Jensen, Søren S., Solov’yov, Ilia A., Kratchmarova, Irina, and Blagoev, Blagoy

Abstract

Modulation of protein activities by reversible post-translational modifications (PTMs) is a major molecular mechanism involved in the control of virtually all cellular processes. One of these PTMs is ubiquitination, which regulates key processes including protein degradation, cell cycle, DNA damage repair, and signal transduction. Because of its importance for numerous cellular functions, ubiquitination has become an intense topic of research in recent years, and proteomics tools have greatly facilitated the identification of many ubiquitination targets. Taking advantage of the StUbEx strategy for exchanging the endogenous ubiquitin with an epitope-tagged version, we created a modified system, StUbEx PLUS, which allows precise mapping of ubiquitination sites by mass spectrometry. Application of StUbEx PLUS to U2OS cells treated with proteasomal inhibitors resulted in the identification of 41 589 sites on 7762 proteins, which thereby revealed the ubiquitous nature of this PTM and demonstrated the utility of the approach for comprehensive ubiquitination studies at site-specific resolution.

Published
2017
Full Text
View/download PDF

50. Genome-wide meta-analysis, fine-mapping and integrative prioritization implicate new Alzheimer's disease risk genes

Author

Schwartzentruber, Jeremy, Cooper, Sarah, Liu, Jimmy Z, Barrio-Hernandez, Inigo, Bello, Erica, Kumasaka, Natsuhiko, Young, Adam MH, Franklin, Robin JM, Johnson, Toby, Estrada, Karol, Gaffney, Daniel J, Beltrao, Pedro, and Bassett, Andrew

Subjects
Oncogene Proteins, Tetraspanins, Quantitative Trait Loci, Chromosome Mapping, Gene Expression, Polymorphism, Single Nucleotide, Linkage Disequilibrium, 3. Good health, Cytoskeletal Proteins, Alzheimer Disease, Risk Factors, Humans, Genetic Predisposition to Disease, Microglia, Protein Interaction Maps, Adaptor Proteins, Signal Transducing, Genome-Wide Association Study
Abstract

Genome-wide association studies have discovered numerous genomic loci associated with Alzheimer's disease (AD); yet the causal genes and variants are incompletely identified. We performed an updated genome-wide AD meta-analysis, which identified 37 risk loci, including new associations near CCDC6, TSPAN14, NCK2 and SPRED2. Using three SNP-level fine-mapping methods, we identified 21 SNPs with >50% probability each of being causally involved in AD risk and others strongly suggested by functional annotation. We followed this with colocalization analyses across 109 gene expression quantitative trait loci datasets and prioritization of genes by using protein interaction networks and tissue-specific expression. Combining this information into a quantitative score, we found that evidence converged on likely causal genes, including the above four genes, and those at previously discovered AD loci, including BIN1, APH1B, PTK2B, PILRA and CASS4.

Catalog

Books, media, physical & digital resources
See catalog results