TY - JOUR T1 - Drug-target identification in COVID-19 disease mechanisms using computational systems biology approaches. JF - Front Immunol Y1 - 2024 A1 - Niarakis, Anna A1 - Ostaszewski, Marek A1 - Mazein, Alexander A1 - Kuperstein, Inna A1 - Kutmon, Martina A1 - Gillespie, Marc E A1 - Funahashi, Akira A1 - Acencio, Marcio Luis A1 - Hemedan, Ahmed A1 - Aichem, Michael A1 - Klein, Karsten A1 - Czauderna, Tobias A1 - Burtscher, Felicia A1 - Yamada, Takahiro G A1 - Hiki, Yusuke A1 - Hiroi, Noriko F A1 - Hu, Finterly A1 - Pham, Nhung A1 - Ehrhart, Friederike A1 - Willighagen, Egon L A1 - Valdeolivas, Alberto A1 - Dugourd, Aurélien A1 - Messina, Francesco A1 - Esteban-Medina, Marina A1 - Peña-Chilet, Maria A1 - Rian, Kinza A1 - Soliman, Sylvain A1 - Aghamiri, Sara Sadat A1 - Puniya, Bhanwar Lal A1 - Naldi, Aurélien A1 - Helikar, Tomáš A1 - Singh, Vidisha A1 - Fernández, Marco Fariñas A1 - Bermudez, Viviam A1 - Tsirvouli, Eirini A1 - Montagud, Arnau A1 - Noël, Vincent A1 - Ponce-de-Leon, Miguel A1 - Maier, Dieter A1 - Bauch, Angela A1 - Gyori, Benjamin M A1 - Bachman, John A A1 - Luna, Augustin A1 - Piñero, Janet A1 - Furlong, Laura I A1 - Balaur, Irina A1 - Rougny, Adrien A1 - Jarosz, Yohan A1 - Overall, Rupert W A1 - Phair, Robert A1 - Perfetto, Livia A1 - Matthews, Lisa A1 - Rex, Devasahayam Arokia Balaya A1 - Orlic-Milacic, Marija A1 - Gomez, Luis Cristobal Monraz A1 - De Meulder, Bertrand A1 - Ravel, Jean Marie A1 - Jassal, Bijay A1 - Satagopam, Venkata A1 - Wu, Guanming A1 - Golebiewski, Martin A1 - Gawron, Piotr A1 - Calzone, Laurence A1 - Beckmann, Jacques S A1 - Evelo, Chris T A1 - D'Eustachio, Peter A1 - Schreiber, Falk A1 - Saez-Rodriguez, Julio A1 - Dopazo, Joaquin A1 - Kuiper, Martin A1 - Valencia, Alfonso A1 - Wolkenhauer, Olaf A1 - Kitano, Hiroaki A1 - Barillot, Emmanuel A1 - Auffray, Charles A1 - Balling, Rudi A1 - Schneider, Reinhard KW - Computer Simulation KW - COVID-19 KW - drug repositioning KW - Humans KW - SARS-CoV-2 KW - Systems biology AB -

INTRODUCTION: The COVID-19 Disease Map project is a large-scale community effort uniting 277 scientists from 130 Institutions around the globe. We use high-quality, mechanistic content describing SARS-CoV-2-host interactions and develop interoperable bioinformatic pipelines for novel target identification and drug repurposing.

METHODS: Extensive community work allowed an impressive step forward in building interfaces between Systems Biology tools and platforms. Our framework can link biomolecules from omics data analysis and computational modelling to dysregulated pathways in a cell-, tissue- or patient-specific manner. Drug repurposing using text mining and AI-assisted analysis identified potential drugs, chemicals and microRNAs that could target the identified key factors.

RESULTS: Results revealed drugs already tested for anti-COVID-19 efficacy, providing a mechanistic context for their mode of action, and drugs already in clinical trials for treating other diseases, never tested against COVID-19.

DISCUSSION: The key advance is that the proposed framework is versatile and expandable, offering a significant upgrade in the arsenal for virus-host interactions and other complex pathologies.

VL - 14 ER - TY - JOUR T1 - Metabolic reprogramming by Acly inhibition using SB-204990 alters glucoregulation and modulates molecular mechanisms associated with aging. JF - Commun Biol Y1 - 2023 A1 - Sola-García, Alejandro A1 - Cáliz-Molina, María Ángeles A1 - Espadas, Isabel A1 - Petr, Michael A1 - Panadero-Morón, Concepción A1 - González-Morán, Daniel A1 - Martín-Vázquez, María Eugenia A1 - Narbona-Pérez, Álvaro Jesús A1 - López-Noriega, Livia A1 - Martínez-Corrales, Guillermo A1 - López-Fernández-Sobrino, Raúl A1 - Carmona-Marin, Lina M A1 - Martínez-Force, Enrique A1 - Yanes, Oscar A1 - Vinaixa, Maria A1 - López-López, Daniel A1 - Reyes, José Carlos A1 - Dopazo, Joaquin A1 - Martín, Franz A1 - Gauthier, Benoit R A1 - Scheibye-Knudsen, Morten A1 - Capilla-González, Vivian A1 - Martín-Montalvo, Alejandro AB -

ATP-citrate lyase is a central integrator of cellular metabolism in the interface of protein, carbohydrate, and lipid metabolism. The physiological consequences as well as the molecular mechanisms orchestrating the response to long-term pharmacologically induced Acly inhibition are unknown. We report here that the Acly inhibitor SB-204990 improves metabolic health and physical strength in wild-type mice when fed with a high-fat diet, while in mice fed with healthy diet results in metabolic imbalance and moderated insulin resistance. By applying a multiomic approach using untargeted metabolomics, transcriptomics, and proteomics, we determined that, in vivo, SB-204990 plays a role in the regulation of molecular mechanisms associated with aging, such as energy metabolism, mitochondrial function, mTOR signaling, and folate cycle, while global alterations on histone acetylation are absent. Our findings indicate a mechanism for regulating molecular pathways of aging that prevents the development of metabolic abnormalities associated with unhealthy dieting. This strategy might be explored for devising therapeutic approaches to prevent metabolic diseases.

VL - 6 IS - 1 ER - TY - JOUR T1 - Novel genes and sex differences in COVID-19 severity. JF - Hum Mol Genet Y1 - 2022 A1 - Cruz, Raquel A1 - Almeida, Silvia Diz-de A1 - Heredia, Miguel López A1 - Quintela, Inés A1 - Ceballos, Francisco C A1 - Pita, Guillermo A1 - Lorenzo-Salazar, José M A1 - González-Montelongo, Rafaela A1 - Gago-Domínguez, Manuela A1 - Porras, Marta Sevilla A1 - Castaño, Jair Antonio Tenorio A1 - Nevado, Julián A1 - Aguado, Jose María A1 - Aguilar, Carlos A1 - Aguilera-Albesa, Sergio A1 - Almadana, Virginia A1 - Almoguera, Berta A1 - Alvarez, Nuria A1 - Andreu-Bernabeu, Álvaro A1 - Arana-Arri, Eunate A1 - Arango, Celso A1 - Arranz, María J A1 - Artiga, Maria-Jesus A1 - Baptista-Rosas, Raúl C A1 - Barreda-Sánchez, María A1 - Belhassen-Garcia, Moncef A1 - Bezerra, Joao F A1 - Bezerra, Marcos A C A1 - Boix-Palop, Lucía A1 - Brión, Maria A1 - Brugada, Ramón A1 - Bustos, Matilde A1 - Calderón, Enrique J A1 - Carbonell, Cristina A1 - Castano, Luis A1 - Castelao, Jose E A1 - Conde-Vicente, Rosa A1 - Cordero-Lorenzana, M Lourdes A1 - Cortes-Sanchez, Jose L A1 - Corton, Marta A1 - Darnaude, M Teresa A1 - De Martino-Rodríguez, Alba A1 - Campo-Pérez, Victor A1 - Bustamante, Aranzazu Diaz A1 - Domínguez-Garrido, Elena A1 - Luchessi, André D A1 - Eirós, Rocío A1 - Sanabria, Gladys Mercedes Estigarribia A1 - Fariñas, María Carmen A1 - Fernández-Robelo, Uxía A1 - Fernández-Rodríguez, Amanda A1 - Fernández-Villa, Tania A1 - Gil-Fournier, Belén A1 - Gómez-Arrue, Javier A1 - Álvarez, Beatriz González A1 - Quirós, Fernan Gonzalez Bernaldo A1 - González-Peñas, Javier A1 - Gutiérrez-Bautista, Juan F A1 - Herrero, María José A1 - Herrero-Gonzalez, Antonio A1 - Jimenez-Sousa, María A A1 - Lattig, María Claudia A1 - Borja, Anabel Liger A1 - Lopez-Rodriguez, Rosario A1 - Mancebo, Esther A1 - Martín-López, Caridad A1 - Martín, Vicente A1 - Martinez-Nieto, Oscar A1 - Martinez-Lopez, Iciar A1 - Martinez-Resendez, Michel F A1 - Martinez-Perez, Ángel A1 - Mazzeu, Juliana A A1 - Macías, Eleuterio Merayo A1 - Minguez, Pablo A1 - Cuerda, Victor Moreno A1 - Silbiger, Vivian N A1 - Oliveira, Silviene F A1 - Ortega-Paino, Eva A1 - Parellada, Mara A1 - Paz-Artal, Estela A1 - Santos, Ney P C A1 - Pérez-Matute, Patricia A1 - Perez, Patricia A1 - Pérez-Tomás, M Elena A1 - Perucho, Teresa A1 - Pinsach-Abuin, Mel Lina A1 - Pompa-Mera, Ericka N A1 - Porras-Hurtado, Gloria L A1 - Pujol, Aurora A1 - León, Soraya Ramiro A1 - Resino, Salvador A1 - Fernandes, Marianne R A1 - Rodríguez-Ruiz, Emilio A1 - Rodriguez-Artalejo, Fernando A1 - Rodriguez-Garcia, José A A1 - Ruiz-Cabello, Francisco A1 - Ruiz-Hornillos, Javier A1 - Ryan, Pablo A1 - Soria, José Manuel A1 - Souto, Juan Carlos A1 - Tamayo, Eduardo A1 - Tamayo-Velasco, Alvaro A1 - Taracido-Fernandez, Juan Carlos A1 - Teper, Alejandro A1 - Torres-Tobar, Lilian A1 - Urioste, Miguel A1 - Valencia-Ramos, Juan A1 - Yáñez, Zuleima A1 - Zarate, Ruth A1 - Nakanishi, Tomoko A1 - Pigazzini, Sara A1 - Degenhardt, Frauke A1 - Butler-Laporte, Guillaume A1 - Maya-Miles, Douglas A1 - Bujanda, Luis A1 - Bouysran, Youssef A1 - Palom, Adriana A1 - Ellinghaus, David A1 - Martínez-Bueno, Manuel A1 - Rolker, Selina A1 - Amitrano, Sara A1 - Roade, Luisa A1 - Fava, Francesca A1 - Spinner, Christoph D A1 - Prati, Daniele A1 - Bernardo, David A1 - García, Federico A1 - Darcis, Gilles A1 - Fernández-Cadenas, Israel A1 - Holter, Jan Cato A1 - Banales, Jesus M A1 - Frithiof, Robert A1 - Duga, Stefano A1 - Asselta, Rosanna A1 - Pereira, Alexandre C A1 - Romero-Gómez, Manuel A1 - Nafría-Jiménez, Beatriz A1 - Hov, Johannes R A1 - Migeotte, Isabelle A1 - Renieri, Alessandra A1 - Planas, Anna M A1 - Ludwig, Kerstin U A1 - Buti, Maria A1 - Rahmouni, Souad A1 - Alarcón-Riquelme, Marta E A1 - Schulte, Eva C A1 - Franke, Andre A1 - Karlsen, Tom H A1 - Valenti, Luca A1 - Zeberg, Hugo A1 - Richards, Brent A1 - Ganna, Andrea A1 - Boada, Mercè A1 - Rojas, Itziar A1 - Ruiz, Agustín A1 - Sánchez, Pascual A1 - Real, Luis Miguel A1 - Guillén-Navarro, Encarna A1 - Ayuso, Carmen A1 - González-Neira, Anna A1 - Riancho, José A A1 - Rojas-Martinez, Augusto A1 - Flores, Carlos A1 - Lapunzina, Pablo A1 - Carracedo, Ángel AB -

Here we describe the results of a genome-wide study conducted in 11 939 COVID-19 positive cases with an extensive clinical information that were recruited from 34 hospitals across Spain (SCOURGE consortium). In sex-disaggregated genome-wide association studies for COVID-19 hospitalization, genome-wide significance (p < 5x10-8) was crossed for variants in 3p21.31 and 21q22.11 loci only among males (p = 1.3x10-22 and p = 8.1x10-12, respectively), and for variants in 9q21.32 near TLE1 only among females (p = 4.4x10-8). In a second phase, results were combined with an independent Spanish cohort (1598 COVID-19 cases and 1068 population controls), revealing in the overall analysis two novel risk loci in 9p13.3 and 19q13.12, with fine-mapping prioritized variants functionally associated with AQP3 (p = 2.7x10-8) and ARHGAP33 (p = 1.3x10-8), respectively. The meta-analysis of both phases with four European studies stratified by sex from the Host Genetics Initiative confirmed the association of the 3p21.31 and 21q22.11 loci predominantly in males and replicated a recently reported variant in 11p13 (ELF5, p = 4.1x10-8). Six of the COVID-19 HGI discovered loci were replicated and an HGI-based genetic risk score predicted the severity strata in SCOURGE. We also found more SNP-heritability and larger heritability differences by age (<60 or ≥ 60 years) among males than among females. Parallel genome-wide screening of inbreeding depression in SCOURGE also showed an effect of homozygosity in COVID-19 hospitalization and severity and this effect was stronger among older males. In summary, new candidate genes for COVID-19 severity and evidence supporting genetic disparities among sexes are provided.

ER - TY - JOUR T1 - COVID19 Disease Map, a computational knowledge repository of virus-host interaction mechanisms. JF - Mol Syst Biol Y1 - 2021 A1 - Ostaszewski, Marek A1 - Niarakis, Anna A1 - Mazein, Alexander A1 - Kuperstein, Inna A1 - Phair, Robert A1 - Orta-Resendiz, Aurelio A1 - Singh, Vidisha A1 - Aghamiri, Sara Sadat A1 - Acencio, Marcio Luis A1 - Glaab, Enrico A1 - Ruepp, Andreas A1 - Fobo, Gisela A1 - Montrone, Corinna A1 - Brauner, Barbara A1 - Frishman, Goar A1 - Monraz Gómez, Luis Cristóbal A1 - Somers, Julia A1 - Hoch, Matti A1 - Kumar Gupta, Shailendra A1 - Scheel, Julia A1 - Borlinghaus, Hanna A1 - Czauderna, Tobias A1 - Schreiber, Falk A1 - Montagud, Arnau A1 - Ponce de Leon, Miguel A1 - Funahashi, Akira A1 - Hiki, Yusuke A1 - Hiroi, Noriko A1 - Yamada, Takahiro G A1 - Dräger, Andreas A1 - Renz, Alina A1 - Naveez, Muhammad A1 - Bocskei, Zsolt A1 - Messina, Francesco A1 - Börnigen, Daniela A1 - Fergusson, Liam A1 - Conti, Marta A1 - Rameil, Marius A1 - Nakonecnij, Vanessa A1 - Vanhoefer, Jakob A1 - Schmiester, Leonard A1 - Wang, Muying A1 - Ackerman, Emily E A1 - Shoemaker, Jason E A1 - Zucker, Jeremy A1 - Oxford, Kristie A1 - Teuton, Jeremy A1 - Kocakaya, Ebru A1 - Summak, Gökçe Yağmur A1 - Hanspers, Kristina A1 - Kutmon, Martina A1 - Coort, Susan A1 - Eijssen, Lars A1 - Ehrhart, Friederike A1 - Rex, Devasahayam Arokia Balaya A1 - Slenter, Denise A1 - Martens, Marvin A1 - Pham, Nhung A1 - Haw, Robin A1 - Jassal, Bijay A1 - Matthews, Lisa A1 - Orlic-Milacic, Marija A1 - Senff Ribeiro, Andrea A1 - Rothfels, Karen A1 - Shamovsky, Veronica A1 - Stephan, Ralf A1 - Sevilla, Cristoffer A1 - Varusai, Thawfeek A1 - Ravel, Jean-Marie A1 - Fraser, Rupsha A1 - Ortseifen, Vera A1 - Marchesi, Silvia A1 - Gawron, Piotr A1 - Smula, Ewa A1 - Heirendt, Laurent A1 - Satagopam, Venkata A1 - Wu, Guanming A1 - Riutta, Anders A1 - Golebiewski, Martin A1 - Owen, Stuart A1 - Goble, Carole A1 - Hu, Xiaoming A1 - Overall, Rupert W A1 - Maier, Dieter A1 - Bauch, Angela A1 - Gyori, Benjamin M A1 - Bachman, John A A1 - Vega, Carlos A1 - Grouès, Valentin A1 - Vazquez, Miguel A1 - Porras, Pablo A1 - Licata, Luana A1 - Iannuccelli, Marta A1 - Sacco, Francesca A1 - Nesterova, Anastasia A1 - Yuryev, Anton A1 - de Waard, Anita A1 - Turei, Denes A1 - Luna, Augustin A1 - Babur, Ozgun A1 - Soliman, Sylvain A1 - Valdeolivas, Alberto A1 - Esteban-Medina, Marina A1 - Peña-Chilet, Maria A1 - Rian, Kinza A1 - Helikar, Tomáš A1 - Puniya, Bhanwar Lal A1 - Modos, Dezso A1 - Treveil, Agatha A1 - Olbei, Marton A1 - De Meulder, Bertrand A1 - Ballereau, Stephane A1 - Dugourd, Aurélien A1 - Naldi, Aurélien A1 - Noël, Vincent A1 - Calzone, Laurence A1 - Sander, Chris A1 - Demir, Emek A1 - Korcsmaros, Tamas A1 - Freeman, Tom C A1 - Augé, Franck A1 - Beckmann, Jacques S A1 - Hasenauer, Jan A1 - Wolkenhauer, Olaf A1 - Wilighagen, Egon L A1 - Pico, Alexander R A1 - Evelo, Chris T A1 - Gillespie, Marc E A1 - Stein, Lincoln D A1 - Hermjakob, Henning A1 - D'Eustachio, Peter A1 - Saez-Rodriguez, Julio A1 - Dopazo, Joaquin A1 - Valencia, Alfonso A1 - Kitano, Hiroaki A1 - Barillot, Emmanuel A1 - Auffray, Charles A1 - Balling, Rudi A1 - Schneider, Reinhard KW - Antiviral Agents KW - Computational Biology KW - Computer Graphics KW - COVID-19 KW - Cytokines KW - Data Mining KW - Databases, Factual KW - Gene Expression Regulation KW - Host Microbial Interactions KW - Humans KW - Immunity, Cellular KW - Immunity, Humoral KW - Immunity, Innate KW - Lymphocytes KW - Metabolic Networks and Pathways KW - Myeloid Cells KW - Protein Interaction Mapping KW - SARS-CoV-2 KW - Signal Transduction KW - Software KW - Transcription Factors KW - Viral Proteins AB -

We need to effectively combine the knowledge from surging literature with complex datasets to propose mechanistic models of SARS-CoV-2 infection, improving data interpretation and predicting key targets of intervention. Here, we describe a large-scale community effort to build an open access, interoperable and computable repository of COVID-19 molecular mechanisms. The COVID-19 Disease Map (C19DMap) is a graphical, interactive representation of disease-relevant molecular mechanisms linking many knowledge sources. Notably, it is a computational resource for graph-based analyses and disease modelling. To this end, we established a framework of tools, platforms and guidelines necessary for a multifaceted community of biocurators, domain experts, bioinformaticians and computational biologists. The diagrams of the C19DMap, curated from the literature, are integrated with relevant interaction and text mining databases. We demonstrate the application of network analysis and modelling approaches by concrete examples to highlight new testable hypotheses. This framework helps to find signatures of SARS-CoV-2 predisposition, treatment response or prioritisation of drug candidates. Such an approach may help deal with new waves of COVID-19 or similar pandemics in the long-term perspective.

VL - 17 IS - 10 U1 - https://www.ncbi.nlm.nih.gov/pubmed/34664389?dopt=Abstract ER - TY - JOUR T1 - The NCI Genomic Data Commons JF - Nature Genetics Y1 - 2021 A1 - Heath, Allison P. A1 - Ferretti, Vincent A1 - Agrawal, Stuti A1 - An, Maksim A1 - Angelakos, James C. A1 - Arya, Renuka A1 - Bajari, Rosita A1 - Baqar, Bilal A1 - Barnowski, Justin H. B. A1 - Burt, Jeffrey A1 - Catton, Ann A1 - Chan, Brandon F. A1 - Chu, Fay A1 - Cullion, Kim A1 - Davidsen, Tanja A1 - Do, Phuong-My A1 - Dompierre, Christian A1 - Ferguson, Martin L. A1 - Fitzsimons, Michael S. A1 - Ford, Michael A1 - Fukuma, Miyuki A1 - Gaheen, Sharon A1 - Ganji, Gajanan L. A1 - Garcia, Tzintzuni I. A1 - George, Sameera S. A1 - Gerhard, Daniela S. A1 - Gerthoffert, Francois A1 - Gomez, Fauzi A1 - Han, Kang A1 - Hernandez, Kyle M. A1 - Issac, Biju A1 - Jackson, Richard A1 - Jensen, Mark A. A1 - Joshi, Sid A1 - Kadam, Ajinkya A1 - Khurana, Aishmit A1 - Kim, Kyle M. J. A1 - Kraft, Victoria E. A1 - Li, Shenglai A1 - Lichtenberg, Tara M. A1 - Lodato, Janice A1 - Lolla, Laxmi A1 - Martinov, Plamen A1 - Mazzone, Jeffrey A. A1 - Miller, Daniel P. A1 - Miller, Ian A1 - Miller, Joshua S. A1 - Miyauchi, Koji A1 - Murphy, Mark W. A1 - Nullet, Thomas A1 - Ogwara, Rowland O. A1 - Ortuño, Francisco M. A1 - Pedrosa, Jesús A1 - Pham, Phuong L. A1 - Popov, Maxim Y. A1 - Porter, James J. A1 - Powell, Raymond A1 - Rademacher, Karl A1 - Reid, Colin P. A1 - Rich, Samantha A1 - Rogel, Bessie A1 - Sahni, Himanso A1 - Savage, Jeremiah H. A1 - Schmitt, Kyle A. A1 - Simmons, Trevar J. A1 - Sislow, Joseph A1 - Spring, Jonathan A1 - Stein, Lincoln A1 - Sullivan, Sean A1 - Tang, Yajing A1 - Thiagarajan, Mathangi A1 - Troyer, Heather D. A1 - Wang, Chang A1 - Wang, Zhining A1 - West, Bedford L. A1 - Wilmer, Alex A1 - Wilson, Shane A1 - Wu, Kaman A1 - Wysocki, William P. A1 - Xiang, Linda A1 - Yamada, Joseph T. A1 - Yang, Liming A1 - Yu, Christine A1 - Yung, Christina K. A1 - Zenklusen, Jean Claude A1 - Zhang, Junjun A1 - Zhang, Zhenyu A1 - Zhao, Yuanheng A1 - Zubair, Ariz A1 - Staudt, Louis M. A1 - Grossman, Robert L. UR - http://www.nature.com/articles/s41588-021-00791-5 JO - Nat Genet ER - TY - JOUR T1 - Orchestrating and sharing large multimodal data for transparent and reproducible research. JF - Nat Commun Y1 - 2021 A1 - Mammoliti, Anthony A1 - Smirnov, Petr A1 - Nakano, Minoru A1 - Safikhani, Zhaleh A1 - Eeles, Christopher A1 - Seo, Heewon A1 - Nair, Sisira Kadambat A1 - Mer, Arvind S A1 - Smith, Ian A1 - Ho, Chantal A1 - Beri, Gangesh A1 - Kusko, Rebecca A1 - Lin, Eva A1 - Yu, Yihong A1 - Martin, Scott A1 - Hafner, Marc A1 - Haibe-Kains, Benjamin AB -

Reproducibility is essential to open science, as there is limited relevance for findings that can not be reproduced by independent research groups, regardless of its validity. It is therefore crucial for scientists to describe their experiments in sufficient detail so they can be reproduced, scrutinized, challenged, and built upon. However, the intrinsic complexity and continuous growth of biomedical data makes it increasingly difficult to process, analyze, and share with the community in a FAIR (findable, accessible, interoperable, and reusable) manner. To overcome these issues, we created a cloud-based platform called ORCESTRA ( orcestra.ca ), which provides a flexible framework for the reproducible processing of multimodal biomedical data. It enables processing of clinical, genomic and perturbation profiles of cancer samples through automated processing pipelines that are user-customizable. ORCESTRA creates integrated and fully documented data objects with persistent identifiers (DOI) and manages multiple dataset versions, which can be shared for future studies.

VL - 12 IS - 1 U1 - https://www.ncbi.nlm.nih.gov/pubmed/34608132?dopt=Abstract ER - TY - JOUR T1 - Reporting guidelines for human microbiome research: the STORMS checklist. JF - Nat Med Y1 - 2021 A1 - Mirzayi, Chloe A1 - Renson, Audrey A1 - Zohra, Fatima A1 - Elsafoury, Shaimaa A1 - Geistlinger, Ludwig A1 - Kasselman, Lora J A1 - Eckenrode, Kelly A1 - van de Wijgert, Janneke A1 - Loughman, Amy A1 - Marques, Francine Z A1 - MacIntyre, David A A1 - Arumugam, Manimozhiyan A1 - Azhar, Rimsha A1 - Beghini, Francesco A1 - Bergstrom, Kirk A1 - Bhatt, Ami A1 - Bisanz, Jordan E A1 - Braun, Jonathan A1 - Bravo, Hector Corrada A1 - Buck, Gregory A A1 - Bushman, Frederic A1 - Casero, David A1 - Clarke, Gerard A1 - Collado, Maria Carmen A1 - Cotter, Paul D A1 - Cryan, John F A1 - Demmer, Ryan T A1 - Devkota, Suzanne A1 - Elinav, Eran A1 - Escobar, Juan S A1 - Fettweis, Jennifer A1 - Finn, Robert D A1 - Fodor, Anthony A A1 - Forslund, Sofia A1 - Franke, Andre A1 - Furlanello, Cesare A1 - Gilbert, Jack A1 - Grice, Elizabeth A1 - Haibe-Kains, Benjamin A1 - Handley, Scott A1 - Herd, Pamela A1 - Holmes, Susan A1 - Jacobs, Jonathan P A1 - Karstens, Lisa A1 - Knight, Rob A1 - Knights, Dan A1 - Koren, Omry A1 - Kwon, Douglas S A1 - Langille, Morgan A1 - Lindsay, Brianna A1 - McGovern, Dermot A1 - McHardy, Alice C A1 - McWeeney, Shannon A1 - Mueller, Noel T A1 - Nezi, Luigi A1 - Olm, Matthew A1 - Palm, Noah A1 - Pasolli, Edoardo A1 - Raes, Jeroen A1 - Redinbo, Matthew R A1 - Rühlemann, Malte A1 - Balfour Sartor, R A1 - Schloss, Patrick D A1 - Schriml, Lynn A1 - Segal, Eran A1 - Shardell, Michelle A1 - Sharpton, Thomas A1 - Smirnova, Ekaterina A1 - Sokol, Harry A1 - Sonnenburg, Justin L A1 - Srinivasan, Sujatha A1 - Thingholm, Louise B A1 - Turnbaugh, Peter J A1 - Upadhyay, Vaibhav A1 - Walls, Ramona L A1 - Wilmes, Paul A1 - Yamada, Takuji A1 - Zeller, Georg A1 - Zhang, Mingyu A1 - Zhao, Ni A1 - Zhao, Liping A1 - Bao, Wenjun A1 - Culhane, Aedin A1 - Devanarayan, Viswanath A1 - Dopazo, Joaquin A1 - Fan, Xiaohui A1 - Fischer, Matthias A1 - Jones, Wendell A1 - Kusko, Rebecca A1 - Mason, Christopher E A1 - Mercer, Tim R A1 - Sansone, Susanna-Assunta A1 - Scherer, Andreas A1 - Shi, Leming A1 - Thakkar, Shraddha A1 - Tong, Weida A1 - Wolfinger, Russ A1 - Hunter, Christopher A1 - Segata, Nicola A1 - Huttenhower, Curtis A1 - Dowd, Jennifer B A1 - Jones, Heidi E A1 - Waldron, Levi KW - Computational Biology KW - Dysbiosis KW - Humans KW - Microbiota KW - Observational Studies as Topic KW - Research Design KW - Translational Science, Biomedical AB -

The particularly interdisciplinary nature of human microbiome research makes the organization and reporting of results spanning epidemiology, biology, bioinformatics, translational medicine and statistics a challenge. Commonly used reporting guidelines for observational or genetic epidemiology studies lack key features specific to microbiome studies. Therefore, a multidisciplinary group of microbiome epidemiology researchers adapted guidelines for observational and genetic studies to culture-independent human microbiome studies, and also developed new reporting elements for laboratory, bioinformatics and statistical analyses tailored to microbiome studies. The resulting tool, called 'Strengthening The Organization and Reporting of Microbiome Studies' (STORMS), is composed of a 17-item checklist organized into six sections that correspond to the typical sections of a scientific publication, presented as an editable table for inclusion in supplementary materials. The STORMS checklist provides guidance for concise and complete reporting of microbiome studies that will facilitate manuscript preparation, peer review, and reader comprehension of publications and comparative analysis of published results.

VL - 27 IS - 11 U1 - https://www.ncbi.nlm.nih.gov/pubmed/34789871?dopt=Abstract ER - TY - JOUR T1 - Community Assessment of the Predictability of Cancer Protein and Phosphoprotein Levels from Genomics and Transcriptomics. JF - Cell Syst Y1 - 2020 A1 - Yang, Mi A1 - Petralia, Francesca A1 - Li, Zhi A1 - Li, Hongyang A1 - Ma, Weiping A1 - Song, Xiaoyu A1 - Kim, Sunkyu A1 - Lee, Heewon A1 - Yu, Han A1 - Lee, Bora A1 - Bae, Seohui A1 - Heo, Eunji A1 - Kaczmarczyk, Jan A1 - Stępniak, Piotr A1 - Warchoł, Michał A1 - Yu, Thomas A1 - Calinawan, Anna P A1 - Boutros, Paul C A1 - Payne, Samuel H A1 - Reva, Boris A1 - Boja, Emily A1 - Rodriguez, Henry A1 - Stolovitzky, Gustavo A1 - Guan, Yuanfang A1 - Kang, Jaewoo A1 - Wang, Pei A1 - Fenyö, David A1 - Saez-Rodriguez, Julio KW - Crowdsourcing KW - Female KW - Genomics KW - Humans KW - Machine Learning KW - Male KW - Neoplasms KW - Phosphoproteins KW - Proteins KW - Proteomics KW - Transcriptome AB -

Cancer is driven by genomic alterations, but the processes causing this disease are largely performed by proteins. However, proteins are harder and more expensive to measure than genes and transcripts. To catalyze developments of methods to infer protein levels from other omics measurements, we leveraged crowdsourcing via the NCI-CPTAC DREAM proteogenomic challenge. We asked for methods to predict protein and phosphorylation levels from genomic and transcriptomic data in cancer patients. The best performance was achieved by an ensemble of models, including as predictors transcript level of the corresponding genes, interaction between genes, conservation across tumor types, and phosphosite proximity for phosphorylation prediction. Proteins from metabolic pathways and complexes were the best and worst predicted, respectively. The performance of even the best-performing model was modest, suggesting that many proteins are strongly regulated through translational control and degradation. Our results set a reference for the limitations of computational inference in proteogenomics. A record of this paper's transparent peer review process is included in the Supplemental Information.

VL - 11 IS - 2 U1 - https://www.ncbi.nlm.nih.gov/pubmed/32710834?dopt=Abstract ER - TY - JOUR T1 - The ELIXIR Human Copy Number Variations Community: building bioinformatics infrastructure for research. JF - F1000Res Y1 - 2020 A1 - Salgado, David A1 - Armean, Irina M A1 - Baudis, Michael A1 - Beltran, Sergi A1 - Capella-Gutíerrez, Salvador A1 - Carvalho-Silva, Denise A1 - Dominguez Del Angel, Victoria A1 - Dopazo, Joaquin A1 - Furlong, Laura I A1 - Gao, Bo A1 - Garcia, Leyla A1 - Gerloff, Dietlind A1 - Gut, Ivo A1 - Gyenesei, Attila A1 - Habermann, Nina A1 - Hancock, John M A1 - Hanauer, Marc A1 - Hovig, Eivind A1 - Johansson, Lennart F A1 - Keane, Thomas A1 - Korbel, Jan A1 - Lauer, Katharina B A1 - Laurie, Steve A1 - Leskošek, Brane A1 - Lloyd, David A1 - Marqués-Bonet, Tomás A1 - Mei, Hailiang A1 - Monostory, Katalin A1 - Piñero, Janet A1 - Poterlowicz, Krzysztof A1 - Rath, Ana A1 - Samarakoon, Pubudu A1 - Sanz, Ferran A1 - Saunders, Gary A1 - Sie, Daoud A1 - Swertz, Morris A A1 - Tsukanov, Kirill A1 - Valencia, Alfonso A1 - Vidak, Marko A1 - Yenyxe González, Cristina A1 - Ylstra, Bauke A1 - Béroud, Christophe KW - Computational Biology KW - DNA Copy Number Variations KW - High-Throughput Nucleotide Sequencing KW - Humans AB -

Copy number variations (CNVs) are major causative contributors both in the genesis of genetic diseases and human neoplasias. While "High-Throughput" sequencing technologies are increasingly becoming the primary choice for genomic screening analysis, their ability to efficiently detect CNVs is still heterogeneous and remains to be developed. The aim of this white paper is to provide a guiding framework for the future contributions of ELIXIR's recently established with implications beyond human disease diagnostics and population genomics. This white paper is the direct result of a strategy meeting that took place in September 2018 in Hinxton (UK) and involved representatives of 11 ELIXIR Nodes. The meeting led to the definition of priority objectives and tasks, to address a wide range of CNV-related challenges ranging from detection and interpretation to sharing and training. Here, we provide suggestions on how to align these tasks within the ELIXIR Platforms strategy, and on how to frame the activities of this new ELIXIR Community in the international context.

VL - 9 U1 - https://www.ncbi.nlm.nih.gov/pubmed/34367618?dopt=Abstract ER - TY - JOUR T1 - Community assessment to advance computational prediction of cancer drug combinations in a pharmacogenomic screen. JF - Nat Commun Y1 - 2019 A1 - Menden, Michael P A1 - Wang, Dennis A1 - Mason, Mike J A1 - Szalai, Bence A1 - Bulusu, Krishna C A1 - Guan, Yuanfang A1 - Yu, Thomas A1 - Kang, Jaewoo A1 - Jeon, Minji A1 - Wolfinger, Russ A1 - Nguyen, Tin A1 - Zaslavskiy, Mikhail A1 - Jang, In Sock A1 - Ghazoui, Zara A1 - Ahsen, Mehmet Eren A1 - Vogel, Robert A1 - Neto, Elias Chaibub A1 - Norman, Thea A1 - Tang, Eric K Y A1 - Garnett, Mathew J A1 - Veroli, Giovanni Y Di A1 - Fawell, Stephen A1 - Stolovitzky, Gustavo A1 - Guinney, Justin A1 - Dry, Jonathan R A1 - Saez-Rodriguez, Julio KW - ADAM17 Protein KW - Antineoplastic Combined Chemotherapy Protocols KW - Benchmarking KW - Biomarkers, Tumor KW - Cell Line, Tumor KW - Computational Biology KW - Datasets as Topic KW - Drug Antagonism KW - Drug Resistance, Neoplasm KW - Drug Synergism KW - Genomics KW - Humans KW - Molecular Targeted Therapy KW - mutation KW - Neoplasms KW - pharmacogenetics KW - Phosphatidylinositol 3-Kinases KW - Phosphoinositide-3 Kinase Inhibitors KW - Treatment Outcome AB -

The effectiveness of most cancer targeted therapies is short-lived. Tumors often develop resistance that might be overcome with drug combinations. However, the number of possible combinations is vast, necessitating data-driven approaches to find optimal patient-specific treatments. Here we report AstraZeneca's large drug combination dataset, consisting of 11,576 experiments from 910 combinations across 85 molecularly characterized cancer cell lines, and results of a DREAM Challenge to evaluate computational strategies for predicting synergistic drug pairs and biomarkers. 160 teams participated to provide a comprehensive methodological development and benchmarking. Winning methods incorporate prior knowledge of drug-target interactions. Synergy is predicted with an accuracy matching biological replicates for >60% of combinations. However, 20% of drug combinations are poorly predicted by all methods. Genomic rationale for synergy predictions are identified, including ADAM17 inhibitor antagonism when combined with PIK3CB/D inhibition contrasting to synergy when combined with other PI3K-pathway inhibitors in PIK3CA mutant cells.

VL - 10 IS - 1 U1 - https://www.ncbi.nlm.nih.gov/pubmed/31209238?dopt=Abstract ER - TY - JOUR T1 - A crowdsourced analysis to identify ab initio molecular signatures predictive of susceptibility to viral infection JF - Nature Communications Y1 - 2018 A1 - Fourati, Slim A1 - Talla, Aarthi A1 - Mahmoudian, Mehrad A1 - Burkhart, Joshua G. A1 - Klén, Riku A1 - Henao, Ricardo A1 - Yu, Thomas A1 - Aydın, Zafer A1 - Yeung, Ka Yee A1 - Ahsen, Mehmet Eren A1 - Almugbel, Reem A1 - Jahandideh, Samad A1 - Liang, Xiao A1 - Nordling, Torbjörn E. M. A1 - Shiga, Motoki A1 - Stanescu, Ana A1 - Vogel, Robert A1 - Pandey, Gaurav A1 - Chiu, Christopher A1 - McClain, Micah T. A1 - Woods, Christopher W. A1 - Ginsburg, Geoffrey S. A1 - Elo, Laura L. A1 - Tsalik, Ephraim L. A1 - Mangravite, Lara M. A1 - Sieberts, Solveig K. VL - 9 UR - http://www.nature.com/articles/s41467-018-06735-8http://www.nature.com/articles/s41467-018-06735-8.pdfhttp://www.nature.com/articles/s41467-018-06735-8.pdfhttp://www.nature.com/articles/s41467-018-06735-8 IS - 1 JO - Nat Commun ER - TY - JOUR T1 - Combining tumor genome simulation with crowdsourcing to benchmark somatic single-nucleotide-variant detection. JF - Nature methods Y1 - 2015 A1 - Ewing, Adam D A1 - Houlahan, Kathleen E A1 - Hu, Yin A1 - Ellrott, Kyle A1 - Caloian, Cristian A1 - Yamaguchi, Takafumi N A1 - Bare, J Christopher A1 - P’ng, Christine A1 - Waggott, Daryl A1 - Sabelnykova, Veronica Y A1 - Kellen, Michael R A1 - Norman, Thea C A1 - Haussler, David A1 - Friend, Stephen H A1 - Stolovitzky, Gustavo A1 - Margolin, Adam A A1 - Stuart, Joshua M A1 - Boutros, Paul C ED - ICGC-TCGA DREAM Somatic Mutation Calling Challenge participants ED - Liu Xi ED - Ninad Dewal ED - Yu Fan ED - Wenyi Wang ED - David Wheeler ED - Andreas Wilm ED - Grace Hui Ting ED - Chenhao Li ED - Denis Bertrand ED - Niranjan Nagarajan ED - Qing-Rong Chen ED - Chih-Hao Hsu ED - Ying Hu ED - Chunhua Yan ED - Warren Kibbe ED - Daoud Meerzaman ED - Kristian Cibulskis ED - Mara Rosenberg ED - Louis Bergelson ED - Adam Kiezun ED - Amie Radenbaugh ED - Anne-Sophie Sertier ED - Anthony Ferrari ED - Laurie Tonton ED - Kunal Bhutani ED - Nancy F Hansen ED - Difei Wang ED - Lei Song ED - Zhongwu Lai ED - Liao, Yang ED - Shi, Wei ED - Carbonell-Caballero, José ED - Joaquín Dopazo ED - Cheryl C K Lau ED - Justin Guinney KW - cancer KW - NGS KW - variant calling AB - The detection of somatic mutations from cancer genome sequences is key to understanding the genetic basis of disease progression, patient survival and response to therapy. Benchmarking is needed for tool assessment and improvement but is complicated by a lack of gold standards, by extensive resource requirements and by difficulties in sharing personal genomic information. To resolve these issues, we launched the ICGC-TCGA DREAM Somatic Mutation Calling Challenge, a crowdsourced benchmark of somatic mutation detection algorithms. Here we report the BAMSurgeon tool for simulating cancer genomes and the results of 248 analyses of three in silico tumors created with it. Different algorithms exhibit characteristic error profiles, and, intriguingly, false positives show a trinucleotide profile very similar to one found in human tumors. Although the three simulated tumors differ in sequence contamination (deviation from normal cell sequence) and in subclonality, an ensemble of pipelines outperforms the best individual pipeline in all cases. BAMSurgeon is available at https://github.com/adamewing/bamsurgeon/. UR - http://www.nature.com/nmeth/journal/vaop/ncurrent/full/nmeth.3407.html ER - TY - JOUR T1 - Prediction of human population responses to toxic compounds by a collaborative competition. JF - Nature biotechnology Y1 - 2015 A1 - Eduati, Federica A1 - Mangravite, Lara M A1 - Wang, Tao A1 - Tang, Hao A1 - Bare, J Christopher A1 - Huang, Ruili A1 - Norman, Thea A1 - Kellen, Mike A1 - Menden, Michael P A1 - Yang, Jichen A1 - Zhan, Xiaowei A1 - Zhong, Rui A1 - Xiao, Guanghua A1 - Xia, Menghang A1 - Abdo, Nour A1 - Kosyk, Oksana AB - The ability to computationally predict the effects of toxic compounds on humans could help address the deficiencies of current chemical safety testing. Here, we report the results from a community-based DREAM challenge to predict toxicities of environmental compounds with potential adverse health effects for human populations. We measured the cytotoxicity of 156 compounds in 884 lymphoblastoid cell lines for which genotype and transcriptional data are available as part of the Tox21 1000 Genomes Project. The challenge participants developed algorithms to predict interindividual variability of toxic response from genomic profiles and population-level cytotoxicity data from structural attributes of the compounds. 179 submitted predictions were evaluated against an experimental data set to which participants were blinded. Individual cytotoxicity predictions were better than random, with modest correlations (Pearson’s r < 0.28), consistent with complex trait genomic prediction. In contrast, predictions of population-level response to different compounds were higher (r < 0.66). The results highlight the possibility of predicting health risks associated with unknown compounds, although risk estimation accuracy remains suboptimal. UR - http://www.nature.com/nbt/journal/vaop/ncurrent/full/nbt.3299.html ER - TY - JOUR T1 - Assessing technical performance in differential gene expression experiments with external spike-in RNA control ratio mixtures. JF - Nature communications Y1 - 2014 A1 - Munro, Sarah A A1 - Lund, Steven P A1 - Pine, P Scott A1 - Binder, Hans A1 - Clevert, Djork-Arné A1 - Ana Conesa A1 - Dopazo, Joaquin A1 - Fasold, Mario A1 - Hochreiter, Sepp A1 - Hong, Huixiao A1 - Jafari, Nadereh A1 - Kreil, David P A1 - Labaj, Paweł P A1 - Li, Sheng A1 - Liao, Yang A1 - Lin, Simon M A1 - Meehan, Joseph A1 - Mason, Christopher E A1 - Santoyo-López, Javier A1 - Setterquist, Robert A A1 - Shi, Leming A1 - Shi, Wei A1 - Smyth, Gordon K A1 - Stralis-Pavese, Nancy A1 - Su, Zhenqiang A1 - Tong, Weida A1 - Wang, Charles A1 - Wang, Jian A1 - Xu, Joshua A1 - Ye, Zhan A1 - Yang, Yong A1 - Yu, Ying A1 - Salit, Marc KW - RNA-seq AB - There is a critical need for standard approaches to assess, report and compare the technical performance of genome-scale differential gene expression experiments. Here we assess technical performance with a proposed standard ’dashboard’ of metrics derived from analysis of external spike-in RNA control ratio mixtures. These control ratio mixtures with defined abundance ratios enable assessment of diagnostic performance of differentially expressed transcript lists, limit of detection of ratio (LODR) estimates and expression ratio variability and measurement bias. The performance metrics suite is applicable to analysis of a typical experiment, and here we also apply these metrics to evaluate technical performance among laboratories. An interlaboratory study using identical samples shared among 12 laboratories with three different measurement processes demonstrates generally consistent diagnostic power across 11 laboratories. Ratio measurement variability and bias are also comparable among laboratories for the same measurement process. We observe different biases for measurement processes using different mRNA-enrichment protocols. VL - 5 UR - http://www.nature.com/ncomms/2014/140925/ncomms6125/full/ncomms6125.html ER - TY - JOUR T1 - Large-scale transcriptional profiling and functional assays reveal important roles for Rho-GTPase signalling and SCL during haematopoietic differentiation of human embryonic stem cells. JF - Hum Mol Genet Y1 - 2011 A1 - Yung, Sun A1 - Ledran, Maria A1 - Moreno-Gimeno, Inmaculada A1 - Conesa, Ana A1 - Montaner, David A1 - Dopazo, Joaquin A1 - Dimmick, Ian A1 - Slater, Nicholas J A1 - Marenah, Lamin A1 - Real, Pedro J A1 - Paraskevopoulou, Iliana A1 - Bisbal, Viviana A1 - Burks, Deborah A1 - Santibanez-Koref, Mauro A1 - Moreno, Ruben A1 - Mountford, Joanne A1 - Menendez, Pablo A1 - Armstrong, Lyle A1 - Lako, Majlinda KW - Acute Disease KW - Anemia, Hemolytic KW - Animals KW - Basic Helix-Loop-Helix Transcription Factors KW - Cell Differentiation KW - Cell Line KW - Cell Lineage KW - Cluster Analysis KW - Embryonic Stem Cells KW - Erythroid Cells KW - Flow Cytometry KW - Gene Expression Profiling KW - Hematopoietic Stem Cells KW - Humans KW - Mice KW - Myeloid Cells KW - Paracrine Communication KW - Proto-Oncogene Proteins KW - Reverse Transcriptase Polymerase Chain Reaction KW - rho GTP-Binding Proteins KW - Signal Transduction KW - Stem Cell Transplantation KW - T-Cell Acute Lymphocytic Leukemia Protein 1 KW - Transcriptome AB -

Understanding the transcriptional cues that direct differentiation of human embryonic stem cells (hESCs) and human-induced pluripotent stem cells to defined and functional cell types is essential for future clinical applications. In this study, we have compared transcriptional profiles of haematopoietic progenitors derived from hESCs at various developmental stages of a feeder- and serum-free differentiation method and show that the largest transcriptional changes occur during the first 4 days of differentiation. Data mining on the basis of molecular function revealed Rho-GTPase signalling as a key regulator of differentiation. Inhibition of this pathway resulted in a significant reduction in the numbers of emerging haematopoietic progenitors throughout the differentiation window, thereby uncovering a previously unappreciated role for Rho-GTPase signalling during human haematopoietic development. Our analysis indicated that SCL was the 11th most upregulated transcript during the first 4 days of the hESC differentiation process. Overexpression of SCL in hESCs promoted differentiation to meso-endodermal lineages, the emergence of haematopoietic and erythro-megakaryocytic progenitors and accelerated erythroid differentiation. Importantly, intrasplenic transplantation of SCL-overexpressing hESC-derived haematopoietic cells enhanced recovery from induced acute anaemia without significant cell engraftment, suggesting a paracrine-mediated effect.

VL - 20 IS - 24 U1 - https://www.ncbi.nlm.nih.gov/pubmed/21937587?dopt=Abstract ER - TY - JOUR T1 - Fine-scale evolution: genomic, phenotypic and ecological differentiation in two coexisting Salinibacter ruber strains. JF - The ISME journal Y1 - 2010 A1 - Peña, Arantxa A1 - Teeling, Hanno A1 - Huerta-Cepas, Jaime A1 - Santos, Fernando A1 - Yarza, Pablo A1 - Brito-Echeverría, Jocelyn A1 - Lucio, Marianna A1 - Schmitt-Kopplin, Philippe A1 - Meseguer, Inmaculada A1 - Schenowitz, Chantal A1 - Dossat, Carole A1 - Barbe, Valerie A1 - Joaquín Dopazo A1 - Rosselló-Mora, Ramon A1 - Schüler, Margarete A1 - Glöckner, Frank Oliver A1 - Amann, Rudolf A1 - Gabaldón, Toni A1 - Antón, Josefa AB -

Genomic and metagenomic data indicate a high degree of genomic variation within microbial populations, although the ecological and evolutive meaning of this microdiversity remains unknown. Microevolution analyses, including genomic and experimental approaches, are so far very scarce for non-pathogenic bacteria. In this study, we compare the genomes, metabolomes and selected ecological traits of the strains M8 and M31 of the hyperhalophilic bacterium Salinibacter ruber that contain ribosomal RNA (rRNA) gene and intergenic regions that are identical in sequence and were simultaneously isolated from a Mediterranean solar saltern. Comparative analyses indicate that S. ruber genomes present a mosaic structure with conserved and hypervariable regions (HVRs). The HVRs or genomic islands, are enriched in transposases, genes related to surface properties, strain-specific genes and highly divergent orthologous. However, the many indels outside the HVRs indicate that genome plasticity extends beyond them. Overall, 10% of the genes encoded in the M8 genome are absent from M31 and could stem from recent acquisitions. S. ruber genomes also harbor 34 genes located outside HVRs that are transcribed during standard growth and probably derive from lateral gene transfers with Archaea preceding the M8/M31 divergence. Metabolomic analyses, phage susceptibility and competition experiments indicate that these genomic differences cannot be considered neutral from an ecological perspective. The results point to the avoidance of competition by micro-niche adaptation and response to viral predation as putative major forces that drive microevolution within these Salinibacter strains. In addition, this work highlights the extent of bacterial functional diversity and environmental adaptation, beyond the resolution of the 16S rRNA and internal transcribed spacers regions.The ISME Journal advance online publication, 18 February 2010; doi:10.1038/ismej.2010.6.

ER - TY - JOUR T1 - The MicroArray Quality Control (MAQC)-II study of common practices for the development and validation of microarray-based predictive models. JF - Nature biotechnology Y1 - 2010 A1 - Shi, Leming A1 - Campbell, Gregory A1 - Jones, Wendell D A1 - Campagne, Fabien A1 - Wen, Zhining A1 - Walker, Stephen J A1 - Su, Zhenqiang A1 - Chu, Tzu-Ming A1 - Goodsaid, Federico M A1 - Pusztai, Lajos A1 - Shaughnessy, John D A1 - Oberthuer, André A1 - Thomas, Russell S A1 - Paules, Richard S A1 - Fielden, Mark A1 - Barlogie, Bart A1 - Chen, Weijie A1 - Du, Pan A1 - Fischer, Matthias A1 - Furlanello, Cesare A1 - Gallas, Brandon D A1 - Ge, Xijin A1 - Megherbi, Dalila B A1 - Symmans, W Fraser A1 - Wang, May D A1 - Zhang, John A1 - Bitter, Hans A1 - Brors, Benedikt A1 - Bushel, Pierre R A1 - Bylesjo, Max A1 - Chen, Minjun A1 - Cheng, Jie A1 - Cheng, Jing A1 - Chou, Jeff A1 - Davison, Timothy S A1 - Delorenzi, Mauro A1 - Deng, Youping A1 - Devanarayan, Viswanath A1 - Dix, David J A1 - Dopazo, Joaquin A1 - Dorff, Kevin C A1 - Elloumi, Fathi A1 - Fan, Jianqing A1 - Fan, Shicai A1 - Fan, Xiaohui A1 - Fang, Hong A1 - Gonzaludo, Nina A1 - Hess, Kenneth R A1 - Hong, Huixiao A1 - Huan, Jun A1 - Irizarry, Rafael A A1 - Judson, Richard A1 - Juraeva, Dilafruz A1 - Lababidi, Samir A1 - Lambert, Christophe G A1 - Li, Li A1 - Li, Yanen A1 - Li, Zhen A1 - Lin, Simon M A1 - Liu, Guozhen A1 - Lobenhofer, Edward K A1 - Luo, Jun A1 - Luo, Wen A1 - McCall, Matthew N A1 - Nikolsky, Yuri A1 - Pennello, Gene A A1 - Perkins, Roger G A1 - Philip, Reena A1 - Popovici, Vlad A1 - Price, Nathan D A1 - Qian, Feng A1 - Scherer, Andreas A1 - Shi, Tieliu A1 - Shi, Weiwei A1 - Sung, Jaeyun A1 - Thierry-Mieg, Danielle A1 - Thierry-Mieg, Jean A1 - Thodima, Venkata A1 - Trygg, Johan A1 - Vishnuvajjala, Lakshmi A1 - Wang, Sue Jane A1 - Wu, Jianping A1 - Wu, Yichao A1 - Xie, Qian A1 - Yousef, Waleed A A1 - Zhang, Liang A1 - Zhang, Xuegong A1 - Zhong, Sheng A1 - Zhou, Yiming A1 - Zhu, Sheng A1 - Arasappan, Dhivya A1 - Bao, Wenjun A1 - Lucas, Anne Bergstrom A1 - Berthold, Frank A1 - Brennan, Richard J A1 - Buness, Andreas A1 - Catalano, Jennifer G A1 - Chang, Chang A1 - Chen, Rong A1 - Cheng, Yiyu A1 - Cui, Jian A1 - Czika, Wendy A1 - Demichelis, Francesca A1 - Deng, Xutao A1 - Dosymbekov, Damir A1 - Eils, Roland A1 - Feng, Yang A1 - Fostel, Jennifer A1 - Fulmer-Smentek, Stephanie A1 - Fuscoe, James C A1 - Gatto, Laurent A1 - Ge, Weigong A1 - Goldstein, Darlene R A1 - Guo, Li A1 - Halbert, Donald N A1 - Han, Jing A1 - Harris, Stephen C A1 - Hatzis, Christos A1 - Herman, Damir A1 - Huang, Jianping A1 - Jensen, Roderick V A1 - Jiang, Rui A1 - Johnson, Charles D A1 - Jurman, Giuseppe A1 - Kahlert, Yvonne A1 - Khuder, Sadik A A1 - Kohl, Matthias A1 - Li, Jianying A1 - Li, Li A1 - Li, Menglong A1 - Li, Quan-Zhen A1 - Li, Shao A1 - Li, Zhiguang A1 - Liu, Jie A1 - Liu, Ying A1 - Liu, Zhichao A1 - Meng, Lu A1 - Madera, Manuel A1 - Martinez-Murillo, Francisco A1 - Medina, Ignacio A1 - Meehan, Joseph A1 - Miclaus, Kelci A1 - Moffitt, Richard A A1 - Montaner, David A1 - Mukherjee, Piali A1 - Mulligan, George J A1 - Neville, Padraic A1 - Nikolskaya, Tatiana A1 - Ning, Baitang A1 - Page, Grier P A1 - Parker, Joel A1 - Parry, R Mitchell A1 - Peng, Xuejun A1 - Peterson, Ron L A1 - Phan, John H A1 - Quanz, Brian A1 - Ren, Yi A1 - Riccadonna, Samantha A1 - Roter, Alan H A1 - Samuelson, Frank W A1 - Schumacher, Martin M A1 - Shambaugh, Joseph D A1 - Shi, Qiang A1 - Shippy, Richard A1 - Si, Shengzhu A1 - Smalter, Aaron A1 - Sotiriou, Christos A1 - Soukup, Mat A1 - Staedtler, Frank A1 - Steiner, Guido A1 - Stokes, Todd H A1 - Sun, Qinglan A1 - Tan, Pei-Yi A1 - Tang, Rong A1 - Tezak, Zivana A1 - Thorn, Brett A1 - Tsyganova, Marina A1 - Turpaz, Yaron A1 - Vega, Silvia C A1 - Visintainer, Roberto A1 - von Frese, Juergen A1 - Wang, Charles A1 - Wang, Eric A1 - Wang, Junwei A1 - Wang, Wei A1 - Westermann, Frank A1 - Willey, James C A1 - Woods, Matthew A1 - Wu, Shujian A1 - Xiao, Nianqing A1 - Xu, Joshua A1 - Xu, Lei A1 - Yang, Lun A1 - Zeng, Xiao A1 - Zhang, Jialu A1 - Zhang, Li A1 - Zhang, Min A1 - Zhao, Chen A1 - Puri, Raj K A1 - Scherf, Uwe A1 - Tong, Weida A1 - Wolfinger, Russell D AB -

Gene expression data from microarrays are being applied to predict preclinical and clinical endpoints, but the reliability of these predictions has not been established. In the MAQC-II project, 36 independent teams analyzed six microarray data sets to generate predictive models for classifying a sample with respect to one of 13 endpoints indicative of lung or liver toxicity in rodents, or of breast cancer, multiple myeloma or neuroblastoma in humans. In total, >30,000 models were built using many combinations of analytical methods. The teams generated predictive models without knowing the biological meaning of some of the endpoints and, to mimic clinical reality, tested the models on data that had not been used for training. We found that model performance depended largely on the endpoint and team proficiency and that different approaches generated models of similar performance. The conclusions and recommendations from MAQC-II should be useful for regulatory agencies, study committees and independent investigators that evaluate methods for global gene expression analysis.

VL - 28 UR - http://www.nature.com/nbt/journal/v28/n8/full/nbt.1665.html ER - TY - JOUR T1 - GEPAS, an experiment-oriented pipeline for the analysis of microarray gene expression data JF - Nucleic Acids Res Y1 - 2005 A1 - Vaquerizas, J. M. A1 - L. Conde A1 - Yankilevich, P. A1 - Cabezon, A. A1 - Minguez, P. A1 - Diaz-Uriarte, R. A1 - Fatima Al-Shahrour A1 - Herrero, J. A1 - Dopazo, J. KW - gepas KW - microarray data analysis AB -

The Gene Expression Profile Analysis Suite, GEPAS, has been running for more than three years. With >76,000 experiments analysed during the last year and a daily average of almost 300 analyses, GEPAS can be considered a well-established and widely used platform for gene expression microarray data analysis. GEPAS is oriented to the analysis of whole series of experiments. Its design and development have been driven by the demands of the biomedical community, probably the most active collective in the field of microarray users. Although clustering methods have obviously been implemented in GEPAS, our interest has focused more on methods for finding genes differentially expressed among distinct classes of experiments or correlated to diverse clinical outcomes, as well as on building predictors. There is also a great interest in CGH-arrays which fostered the development of the corresponding tool in GEPAS: InSilicoCGH. Much effort has been invested in GEPAS for developing and implementing efficient methods for functional annotation of experiments in the proper statistical framework. Thus, the popular FatiGO has expanded to a suite of programs for functional annotation of experiments, including information on transcription factor binding sites, chromosomal location and tissues. The web-based pipeline for microarray gene expression data, GEPAS, is available at http://www.gepas.org.

VL - 33 UR - http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=15980548 N1 -

Vaquerizas, Juan M Conde, Lucia Yankilevich, Patricio Cabezon, Amaya Minguez, Pablo Diaz-Uriarte, Ramon Al-Shahrour, Fatima Herrero, Javier Dopazo, Joaquin Research Support, Non-U.S. Gov’t England Nucleic acids research Nucleic Acids Res. 2005 Jul 1;33(Web Server issue):W616-20.

ER - TY - JOUR T1 - Examining the role of glutamic acid 183 in chloroperoxidase catalysis JF - J Biol Chem Y1 - 2003 A1 - Yi, X. A1 - A. Conesa A1 - Punt, P. J. A1 - Hager, L. P. KW - Aspergillus niger/metabolism Catalase/metabolism Catalysis Chloride Peroxidase/*chemistry/*metabolism Chlorine/metabolism Chromatography KW - Ion Exchange Circular Dichroism Crystallography KW - Polyacrylamide Gel Fungi/enzymology Glutamic Acid/*chemistry Histidine/chemistry/metabolism Hydrogen-Ion Concentration Immunoblotting Isoelectric Focusing Mutation Oxidoreductases/metabolism Plasmids/metabolism KW - X-Ray Electrophoresis AB - Site-directed mutagenesis has been used to investigate the role of glutamic acid 183 in chloroperoxidase catalysis. Based on the x-ray crystallographic structure of chloroperoxidase, Glu-183 is postulated to function on distal side of the heme prosthetic group as an acid-base catalyst in facilitating the reaction between the peroxidase and hydrogen peroxide with the formation of Compound I. In contrast, the other members of the heme peroxidase family use a histidine residue in this role. Plasmids have now been constructed in which the codon for Glu-183 is replaced with a histidine codon. The mutant recombinant gene has been expressed in Aspergillus niger. An analysis of the produced mutant gene shows that the substitution of Glu-183 with a His residue is detrimental to the chlorination and dismutation activity of chloroperoxidase. The activity is reduced by 85 and 50% of wild type activity, respectively. However, quite unexpectedly, the epoxidation activity of the mutant enzyme is significantly enhanced approximately 2.5-fold. These results show that Glu-183 is important but not essential for the chlorination activity of chloroperoxidase. It is possible that the increased epoxidation of the mutant enzyme is based on an increase in the hydrophobicity of the active site. VL - 278 UR - http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=12576477 N1 - Yi, Xianwen Conesa, Ana Punt, Peter J Hager, Lowell P GM 07768/GM/NIGMS NIH HHS/United States Research Support, U.S. Gov’t, P.H.S. United States The Journal of biological chemistry J Biol Chem. 2003 Apr 18;278(16):13855-9. Epub 2003 Feb 7. ER - TY - JOUR T1 - Tools for comparative protein structure modeling and analysis JF - Nucleic Acids Res Y1 - 2003 A1 - Eswar, N. A1 - John, B. A1 - Mirkovic, N. A1 - Fiser, A. A1 - Ilyin, V. A. A1 - Pieper, U. A1 - Stuart, A. C. A1 - M. A. Marti-Renom A1 - Madhusudhan, M. S. A1 - Yerkovich, B. A1 - Sali, A. KW - Amino Acid *Software *Structural Homology KW - Internet Models KW - Molecular Protein Folding Proteins/chemistry Reproducibility of Results Sequence Alignment Sequence Homology KW - Protein Systems Integration AB - The following resources for comparative protein structure modeling and analysis are described (http://salilab.org): MODELLER, a program for comparative modeling by satisfaction of spatial restraints; MODWEB, a web server for automated comparative modeling that relies on PSI-BLAST, IMPALA and MODELLER; MODLOOP, a web server for automated loop modeling that relies on MODELLER; MOULDER, a CPU intensive protocol of MODWEB for building comparative models based on distant known structures; MODBASE, a comprehensive database of annotated comparative models for all sequences detectably related to a known structure; MODVIEW, a Netscape plugin for Linux that integrates viewing of multiple sequences and structures; and SNPWEB, a web server for structure-based prediction of the functional impact of a single amino acid substitution. VL - 31 UR - http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=12824331 N1 - Eswar, Narayanan John, Bino Mirkovic, Nebojsa Fiser, Andras Ilyin, Valentin A Pieper, Ursula Stuart, Ashley C Marti-Renom, Marc A Madhusudhan, M S Yerkovich, Bozidar Sali, Andrej P50 GM62529/GM/NIGMS NIH HHS/United States R01 GM 54762/GM/NIGMS NIH HHS/United States R33 CA84699/CA/NCI NIH HHS/United States Research Support, Non-U.S. Gov’t Research Support, U.S. Gov’t, P.H.S. England Nucleic acids research Nucleic Acids Res. 2003 Jul 1;31(13):3375-80. ER -