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30 results on '"Singh, Vidisha"'

1. Brain microglia serve as a persistent HIV reservoir despite durable antiretroviral therapy

Author

Tang, Yuyang, Chaillon, Antoine, Gianella, Sara, Wong, Lilly M, Li, Dajiang, Simermeyer, Theresa L, Porrachia, Magali, Ignacio, Caroline, Woodworth, Brendon, Zhong, Daniel, Du, Jiayi, de la Parra Polina, Eduardo, Kirchherr, Jennifer, Allard, Brigitte, Clohosey, Matthew L, Moeser, Matt, Sondgeroth, Amy L, Whitehill, Gregory D, Singh, Vidisha, Dashti, Amir, Smith, Davey M, Eron, Joseph J, Bar, Katherine J, Chahroudi, Ann, Joseph, Sarah B, Archin, Nancie M, Margolis, David M, and Jiang, Guochun

Subjects
Medical Microbiology, Biomedical and Clinical Sciences, Immunology, HIV/AIDS, Genetics, Sexually Transmitted Infections, Infectious Diseases, Neurosciences, Aetiology, 2.1 Biological and endogenous factors, 2.2 Factors relating to the physical environment, Infection, Good Health and Well Being, Animals, Humans, Microglia, HIV-1, Brain, Macrophages, Proviruses, HIV Infections, AIDS/HIV, Drug therapy, Medical and Health Sciences, Biological sciences, Biomedical and clinical sciences, Health sciences
Abstract

Brain microglia (MG) may serve as a human immunodeficiency virus 1 (HIV) reservoir and ignite rebound viremia following cessation of antiretroviral therapy (ART), but they have yet to be proven to harbor replication-competent HIV. Here, we isolated brain myeloid cells (BrMCs) from nonhuman primates and rapid autopsy of people with HIV (PWH) on ART and sought evidence of persistent viral infection. BrMCs predominantly displayed microglial markers, in which up to 99.9% of the BrMCs were TMEM119+ MG. Total and integrated SIV or HIV DNA was detectable in the MG, with low levels of cell-associated viral RNA. Provirus in MG was highly sensitive to epigenetic inhibition. Outgrowth virus from parietal cortex MG in an individual with HIV productively infected both MG and PBMCs. This inducible, replication-competent virus and virus from basal ganglia proviral DNA were closely related but highly divergent from variants in peripheral compartments. Phenotyping studies characterized brain-derived virus as macrophage tropic based on the ability of the virus to infect cells expressing low levels of CD4. The lack of genetic diversity in virus from the brain suggests that this macrophage-tropic lineage quickly colonized brain regions. These data demonstrate that MG harbor replication-competent HIV and serve as a persistent reservoir in the brain.

Published
2023

2. AZD5582 plus SIV-specific antibodies reduce lymph node viral reservoirs in antiretroviral therapy-suppressed macaques

Author

Dashti, Amir, Sukkestad, Sophia, Horner, Anna M., Neja, Margaret, Siddiqi, Zain, Waller, Chevaughn, Goldy, Jordan, Monroe, Dominique, Lin, Alice, Schoof, Nils, Singh, Vidisha, Mavigner, Maud, Lifson, Jeffrey D., Deleage, Claire, Tuyishime, Marina, Falcinelli, Shane D., King, Hannah A. D., Ke, Ruian, Mason, Rosemarie D., Archin, Nancie M., Dunham, Richard M., Safrit, Jeffrey T., Jean, Sherrie, Perelson, Alan S., Margolis, David M., Ferrari, Guido, Roederer, Mario, Silvestri, Guido, and Chahroudi, Ann

Published
2023
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4. Transgender Women Have Higher Human Papillomavirus Prevalence Than Men Who Have Sex With Men-Two U.S. Cities, 2012-2014.

Author

Singh, Vidisha, Gratzer, Beau, Gorbach, Pamina M, Crosby, Richard A, Panicker, Gitika, Steinau, Martin, Amiling, Raiza, Unger, Elizabeth R, Markowitz, Lauri E, and Meites, Elissa

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Vaccine Related, Infectious Diseases, Sexually Transmitted Infections, Sexual and Gender Minorities (SGM/LGBT*), Prevention, Cancer, HIV/AIDS, Clinical Research, Immunization, 3.4 Vaccines, Prevention of disease and conditions, and promotion of well-being, Infection, Good Health and Well Being, Adolescent, Adult, Chicago, Cities, Female, Homosexuality, Male, Humans, Los Angeles, Male, Papillomavirus Infections, Papillomavirus Vaccines, Prevalence, Sex Factors, Sexual Behavior, Transgender Persons, Young Adult, Biological Sciences, Medical and Health Sciences, Public Health, Clinical sciences, Epidemiology, Public health
Abstract

BackgroundHuman papillomavirus (HPV) prevalence is high among men who have sex with men (MSM), yet little is known about HPV among transgender women (TGW). We assessed HPV prevalence and knowledge among TGW compared with MSM.MethodsWe enrolled TGW and MSM aged 18 to 26 years from clinics in Chicago and Los Angeles during 2012 to 2014. Participants self-reported gender identity, HIV status, HPV knowledge, and vaccination status. Self-collected anal and oral specimens were tested for HPV DNA (37 types); serum was tested for HPV antibodies (4 vaccine types). Prevalence among unvaccinated TGW and MSM was compared using prevalence ratios (PRs) and 95% confidence intervals (CIs). Participants without DNA or serologic evidence of HPV were considered naïve.ResultsAmong 1033 participants, 49 were TGW. Among 44 TGW and 855 MSM who were unvaccinated, any HPV DNA was detected in anal specimens from 39 (88.6%) TGW and 606 (70.9%) MSM (PR, 1.3; 95% CI, 1.1-1.4), and oral specimens from 4 (9.1%) TGW and 81 (9.5%) MSM (PR, 1.0; 95% CI, 0.4-2.5). Antibodies were detected among 37 (84.1%) TGW and 467 (54.6%) MSM (PR, 1.5; 95% CI, 1.3-1.8). Most participants were naïve to 1 or more HPV vaccine type/s, including 29 (65.9%) TGW and 775 (90.6%) MSM (PR, 0.7; 95% CI, 0.6-0.9). Most TGW (55.1%) had never heard of HPV vaccine.ConclusionsAmong TGW, HPV prevalence was high and knowledge was low. Most were still naïve to 1 or more HPV vaccine type. Although vaccination ideally occurs prior to exposure, findings support existing national recommendations to vaccinate TGW and MSM, and suggest additional outreach might increase vaccination.

Published
2019

5. Disclosure of Sexual Behavior Is Significantly Associated With Receiving a Panel of Health Care Services Recommended for Men Who Have Sex With Men

Author

Singh, Vidisha, Crosby, Richard A, Gratzer, Beau, Gorbach, Pamina M, Markowitz, Lauri E, and Meites, Elissa

Subjects
Biomedical and Clinical Sciences, Public Health, Health Sciences, Clinical Sciences, Vaccine Related, Health Services, Infectious Diseases, Adolescent Sexual Activity, Sexually Transmitted Infections, Sexual and Gender Minorities (SGM/LGBT*), Prevention, HIV/AIDS, Clinical Research, Pediatric, Behavioral and Social Science, Immunization, Infection, Good Health and Well Being, Adolescent, Adult, Chicago, Community Health Services, Disclosure, Female, Gonorrhea, Homosexuality, Female, Homosexuality, Male, Humans, Los Angeles, Male, Mass Screening, Papillomavirus Infections, Risk-Taking, Sexual Behavior, Sexual Partners, Sexually Transmitted Diseases, Syphilis, Transgender Persons, Young Adult, Biological Sciences, Medical and Health Sciences, Clinical sciences, Epidemiology, Public health
Abstract

BackgroundMen who have sex with men (MSM) are at high risk for sexually transmitted infections (STIs). National guidelines recommend that MSM receive HIV, syphilis, gonorrhea, and chlamydia screening at least annually, and hepatitis A and B and human papillomavirus vaccinations. We investigated associations between disclosure of male-male sexual orientation/behavior and receipt of this panel of services.MethodsGay, bisexual, and other MSM aged 18 through 26 years were enrolled from health clinics serving lesbian, gay, bisexual, and transgender communities in Los Angeles and Chicago during 2012 to 2014. Participants completed a computer-assisted self-interview regarding health care services, disclosure of sexual orientation/behavior, and recent HIV test results. Proportions receiving recommended care, prevalence ratios (PRs), and 95% confidence intervals (CIs) were calculated using SAS 9.4.ResultsOverall, 817 participants visited a provider within the past year. Of these, 525 (64.3%) had disclosed, and 749 (91.7%) felt they could disclose if important to health. In total, 548 (67.1%) received all STI screenings, and 74 (9.1%) received all vaccinations. Only 105 (12.9%) received any human papillomavirus vaccination. More disclosing participants received all recommended screenings (adjusted PR [aPR],1.4; 95% CI, 1.3-1.6) and all recommended care components (aPR, 2.2; 95% CI, 1.4-4.3) than nondisclosing participants.ConclusionsDespite national recommendations, receipt of a complete panel of STI care services was low among young MSM. Vaccine uptake was lower than STI screening. However, most participants visited a health care provider in the past year and most disclosed, suggesting opportunities to improve services. Providers might encourage disclosure by improving sexual history taking and education, which could increase opportunities for MSM to receive recommended care.

Published
2018

6. Drug-target identification in COVID-19 disease mechanisms using computational systems biology approaches

Author

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

Abstract

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., Peer Reviewed

Published
2024

7. Erratum To: COVID‐19 Disease Map, a computational knowledge repository of virus‐host interaction mechanisms

Author

Ostaszewski, Marek, Niarakis, Anna, Mazein, Alexander, Kuperstein, Inna, Phair, Robert, Orta‐Resendiz, Aurelio, Singh, Vidisha, Aghamiri, Sara Sadat, Acencio, Marcio Luis, Glaab, Enrico, Ruepp, Andreas, Fobo, Gisela, Montrone, Corinna, Brauner, Barbara, Frishman, Goar, Monraz Gómez, Luis Cristóbal, Somers, Julia, Hoch, Matti, Kumar Gupta, Shailendra, Scheel, Julia, Borlinghaus, Hanna, Czauderna, Tobias, Schreiber, Falk, Montagud, Arnau, Ponce de Leon, Miguel, Funahashi, Akira, Hiki, Yusuke, Hiroi, Noriko, Yamada, Takahiro G, Dräger, Andreas, Renz, Alina, Naveez, Muhammad, Bocskei, Zsolt, Messina, Francesco, Börnigen, Daniela, Fergusson, Liam, Conti, Marta, Rameil, Marius, Nakonecnij, Vanessa, Vanhoefer, Jakob, Schmiester, Leonard, Wang, Muying, Ackerman, Emily E, Shoemaker, Jason E, Zucker, Jeremy, Oxford, Kristie, Teuton, Jeremy, Kocakaya, Ebru, Summak, Gökçe Yağmur, Hanspers, Kristina, Kutmon, Martina, Coort, Susan, Eijssen, Lars, Ehrhart, Friederike, Rex, D A B, Slenter, Denise, Martens, Marvin, Pham, Nhung, Haw, Robin, Jassal, Bijay, Matthews, Lisa, Orlic‐Milacic, Marija, Senff‐Ribeiro, Andrea, Rothfels, Karen, Shamovsky, Veronica, Stephan, Ralf, Sevilla, Cristoffer, Varusai, Thawfeek, Ravel, Jean‐Marie, Fraser, Rupsha, Ortseifen, Vera, Marchesi, Silvia, Gawron, Piotr, Smula, Ewa, Heirendt, Laurent, Satagopam, Venkata, Wu, Guanming, Riutta, Anders, Golebiewski, Martin, Owen, Stuart, Goble, Carole, Hu, Xiaoming, Overall, Rupert W, Maier, Dieter, Bauch, Angela, Gyori, Benjamin M, Bachman, John A, Vega, Carlos, Grouès, Valentin, Vazquez, Miguel, Porras, Pablo, Licata, Luana, Iannuccelli, Marta, Sacco, Francesca, Nesterova, Anastasia, Yuryev, Anton, de Waard, Anita, Turei, Denes, Luna, Augustin, Babur, Ozgun, Soliman, Sylvain, Valdeolivas, Alberto, Esteban‐Medina, Marina, Peña‐Chilet, Maria, Rian, Kinza, Helikar, Tomáš, Puniya, Bhanwar Lal, Modos, Dezso, Treveil, Agatha, Olbei, Marton, De Meulder, Bertrand, Ballereau, Stephane, Dugourd, Aurélien, Naldi, Aurélien, Noël, Vincent, Calzone, Laurence, Sander, Chris, Demir, Emek, Korcsmaros, Tamas, Freeman, Tom C, Augé, Franck, Beckmann, Jacques S, Hasenauer, Jan, Wolkenhauer, Olaf, Willighagen, Egon L, Pico, Alexander R, Evelo, Chris T, Gillespie, Marc E, Stein, Lincoln D, Hermjakob, Henning, D'Eustachio, Peter, Saez‐Rodriguez, Julio, Dopazo, Joaquin, Valencia, Alfonso, Kitano, Hiroaki, Barillot, Emmanuel, Auffray, Charles, Balling, Rudi, and Schneider, Reinhard

Published
2021
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8. COVID19 Disease Map, a computational knowledge repository of virus–host interaction mechanisms

Author

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

Published
2021
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9. rVSVΔG-ZEBOV-GP (also designated V920) recombinant vesicular stomatitis virus pseudotyped with Ebola Zaire Glycoprotein: Standardized template with key considerations for a risk/benefit assessment

Author

Monath, Thomas P., Fast, Patricia E., Modjarrad, Kayvon, Clarke, David K., Martin, Brian K., Fusco, Joan, Nichols, Richard, Heppner, D. Gray, Simon, Jakub K., Dubey, Sheri, Troth, Sean P., Wolf, Jayanthi, Singh, Vidisha, Coller, Beth-Ann, and Robertson, James S.

Published
2019
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10. Drug-target identification in COVID-19 disease mechanisms using computational systems biology approaches

Author

Sanofi, Instituto de Salud Carlos III, Ministerio de Ciencia, Innovación y Universidades (España), Agencia Estatal de Investigación (España), German Research Foundation, Ministero della Salute, European Commission, Generalitat de Catalunya, National Institutes of Health (US), Klaus Tschira Foundation, National Library of Medicine (US), Niarakis, Anna, Ostaszewski, Marek, Mazein, Alexander, Kuperstein, Inna, Kutmon, Martina, Gillespie, Marc E., Funahashi, Akira, Acencio, Marcio Luis, Hemedan, Ahmed, Aichem, Michael, Klein, Karsten, Czauderna, Tobias, Burtscher, Felicia, Yamada, Takahiro G., Hiki, Yusuke, Hiroi, Noriko F., Hu, Finterly, Pham, Nhung, Ehrhart, Friederike, Willighagen, Egon L., Valdeolivas, Alberto, Dugourd, Aurelien, Messina, Francesco, Esteban-Medina, Marina, Peña-Chilet, María, Rian, Kinza, Soliman, Sylvain, Aghamiri, Sara Sadat, Lal Puniya, Bhanwar, Naldi, Aurelien, Helikar, Tomas, Singh, Vidisha, Fariñas Fernández, Marco, Bermudez, Viviam, Tsirvouli, Eirini, Montagud, Arnau, Noël, Vincent, Ponce de León, Miguel, Maier, Dieter, Bauch, Angela, Gyori, Benjamin M., Bachman, John A., Luna, Augustin, Piñero, Janet, Furlong, Laura I., Balaur, Irina BalaurIrina, Rougny, Adrien, Jarosz, Yohan, Overall, Rupert W., Phair, Robert, Perfetto, Livia, Matthews, Lisa, Balaya Rex, Devasahayam Arokia, Orlic-Milacic, Marija, Monraz Gómez, Luis Cristóbal, De Meulder, Bertrand, Ravel, Jean Marie, Jassal, Bijay, Satagopam, Venkata, Wu, Guanming, Golebiewski, Martin, Gawron, Piotr, Calzone, Laurence, Beckmann, Jacques S., Evelo, Chris T., D’Eustachio, Peter, Schreiber, Falk, Sáez-Rodríguez, Julio, Dopazo, Joaquín, Kuiper, Martin, Valencia, Alfonso, Wolkenhauer, Olaf, Kitano, Hiroaki, Barillot, Emmanuel, Auffray, Charles, Balling, Rudi, Schneider, Reinhard, COVID- Disease Map Community the COVID-19 Disease Map Community, Sanofi, Instituto de Salud Carlos III, Ministerio de Ciencia, Innovación y Universidades (España), Agencia Estatal de Investigación (España), German Research Foundation, Ministero della Salute, European Commission, Generalitat de Catalunya, National Institutes of Health (US), Klaus Tschira Foundation, National Library of Medicine (US), Niarakis, Anna, Ostaszewski, Marek, Mazein, Alexander, Kuperstein, Inna, Kutmon, Martina, Gillespie, Marc E., Funahashi, Akira, Acencio, Marcio Luis, Hemedan, Ahmed, Aichem, Michael, Klein, Karsten, Czauderna, Tobias, Burtscher, Felicia, Yamada, Takahiro G., Hiki, Yusuke, Hiroi, Noriko F., Hu, Finterly, Pham, Nhung, Ehrhart, Friederike, Willighagen, Egon L., Valdeolivas, Alberto, Dugourd, Aurelien, Messina, Francesco, Esteban-Medina, Marina, Peña-Chilet, María, Rian, Kinza, Soliman, Sylvain, Aghamiri, Sara Sadat, Lal Puniya, Bhanwar, Naldi, Aurelien, Helikar, Tomas, Singh, Vidisha, Fariñas Fernández, Marco, Bermudez, Viviam, Tsirvouli, Eirini, Montagud, Arnau, Noël, Vincent, Ponce de León, Miguel, Maier, Dieter, Bauch, Angela, Gyori, Benjamin M., Bachman, John A., Luna, Augustin, Piñero, Janet, Furlong, Laura I., Balaur, Irina BalaurIrina, Rougny, Adrien, Jarosz, Yohan, Overall, Rupert W., Phair, Robert, Perfetto, Livia, Matthews, Lisa, Balaya Rex, Devasahayam Arokia, Orlic-Milacic, Marija, Monraz Gómez, Luis Cristóbal, De Meulder, Bertrand, Ravel, Jean Marie, Jassal, Bijay, Satagopam, Venkata, Wu, Guanming, Golebiewski, Martin, Gawron, Piotr, Calzone, Laurence, Beckmann, Jacques S., Evelo, Chris T., D’Eustachio, Peter, Schreiber, Falk, Sáez-Rodríguez, Julio, Dopazo, Joaquín, Kuiper, Martin, Valencia, Alfonso, Wolkenhauer, Olaf, Kitano, Hiroaki, Barillot, Emmanuel, Auffray, Charles, Balling, Rudi, Schneider, Reinhard, and COVID- Disease Map Community the COVID-19 Disease Map Community

Abstract

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.

Published
2023

11. Cross-Neutralizing and Protective Human Antibody Specificities to Poxvirus Infections

Author

Gilchuk, Iuliia, Gilchuk, Pavlo, Sapparapu, Gopal, Lampley, Rebecca, Singh, Vidisha, Kose, Nurgun, Blum, David L., Hughes, Laura J., Satheshkumar, Panayampalli S., Townsend, Michael B., Kondas, Ashley V., Reed, Zachary, Weiner, Zachary, Olson, Victoria A., Hammarlund, Erika, Raue, Hans-Peter, Slifka, Mark K., Slaughter, James C., Graham, Barney S., Edwards, Kathryn M., Eisenberg, Roselyn J., Cohen, Gary H., Joyce, Sebastian, and Crowe, James E., Jr.

Published
2016
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13. Redesigned HIV antibodies exhibit enhanced neutralizing potency and breadth

Author

Willis, Jordan R., Sapparapu, Gopal, Murrell, Sasha, Julien, Jean-Philippe, Singh, Vidisha, King, Hannah G., Xia, Yan, Pickens, Jennifer A., LaBranche, Celia C., Slaughter, James C., Montefiori, David C., Wilson, Ian A., Meiler, Jens, and Crowe, James E., Jr.

Subjects
HIV antibodies -- Health aspects -- Research, Health care industry
Abstract

Several HIV envelope-targeting (Env-targeting) antibodies with broad and potent neutralizing activity have been Identified and shown to have unusual features. Of these, the PG9 antibody has a long heavy chain complementarity determining region 3 (HCDR3) and possesses unique structural elements that interact with protein and glycan features of the HIV Env glycoprotein. Here, we used the Rosetta software suite to design variants of the PG9 antibody HCDR3 loop with the goal of identifying variants with increased potency and breadth of neutralization for diverse HIV strains. One variant, designated [PG9_N100.sub.F]Y, possessed increased potency and was able to neutralize a diverse set of PG9- resistant HIV strains, including those lacking the Env N160 glycan, which is critical for PG9 binding. An atomic resolution structure of the [PG9_N100.sub.F]Y fragment antigen binding (Fab) confirmed that the mutated residue retains the paratope surface when compared with WT PG9. Differential scanning calorimetry experiments revealed that the mutation caused a modest increase in thermodynamic stability of the Fab, a feature predicted by the computational model. Our findings suggest that thermodynamic stabilization of the long HCDR3 in its active conformation is responsible for the increased potency of [PG9_N100.sub.F]Y, and strategies aimed at stabilizing this region in other HIV antibodies could become an important approach to in silico optimization of antibodies., Introduction Recent studies have described the isolation of a number of human mAbs directed to the HIV envelope (Env) that exhibit broad and potent neutralizing activity, many of which exhibit [...]

Published
2015
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14. Limited induction of SARS-CoV-2–specific T cell responses in children with multisystem inflammatory syndrome compared with COVID-19

Author

Singh, Vidisha, primary, Obregon-Perko, Veronica, additional, Lapp, Stacey A., additional, Horner, Anna Marie, additional, Brooks, Alyssa, additional, Macoy, Lisa, additional, Hussaini, Laila, additional, Lu, Austin, additional, Gibson, Theda, additional, Silvestri, Guido, additional, Grifoni, Alba, additional, Weiskopf, Daniela, additional, Sette, Alessandro, additional, Anderson, Evan J., additional, Rostad, Christina A., additional, and Chahroudi, Ann, additional

Published
2022
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16. COVID19 Disease Map, a computational knowledge repository of virus-host interaction mechanisms.

Author

Luxembourg Centre for Systems Biomedicine (LCSB): Bioinformatics Core (R. Schneider Group) [research center], Fonds National de la Recherche - FnR [sponsor], Ostaszewski, Marek, Niarakis, Anna, Mazein, Alexander, Kuperstein, Inna, Phair, Robert, Orta-Resendiz, Aurelio, Singh, Vidisha, Aghamiri, Sara Sadat, Acencio, Marcio Luis, Glaab, Enrico, Ruepp, Andreas, Fobo, Gisela, Montrone, Corinna, Brauner, Barbara, Frishman, Goar, Monraz Gómez, Luis Cristóbal, Somers, Julia, Hoch, Matti, Kumar Gupta, Shailendra, Scheel, Julia, Borlinghaus, Hanna, Czauderna, Tobias, Schreiber, Falk, Montagud, Arnau, Ponce de Leon, Miguel, Funahashi, Akira, Hiki, Yusuke, Hiroi, Noriko, Yamada, Takahiro G., Dräger, Andreas, Renz, Alina, Naveez, Muhammad, Bocskei, Zsolt, Messina, Francesco, Börnigen, Daniela, Fergusson, Liam, Conti, Marta, Rameil, Marius, Nakonecnij, Vanessa, Vanhoefer, Jakob, Schmiester, Leonard, Wang, Muying, Ackerman, Emily E., Shoemaker, Jason E., Zucker, Jeremy, Oxford, Kristie, Teuton, Jeremy, Kocakaya, Ebru, Summak, Gökçe Yağmur, Hanspers, Kristina, Kutmon, Martina, Coort, Susan, Eijssen, Lars, Ehrhart, Friederike, Rex, Devasahayam Arokia Balaya, Slenter, Denise, Martens, Marvin, Pham, Nhung, Haw, Robin, Jassal, Bijay, Matthews, Lisa, Orlic-Milacic, Marija, Senff Ribeiro, Andrea, Rothfels, Karen, Shamovsky, Veronica, Stephan, Ralf, Sevilla, Cristoffer, Varusai, Thawfeek, Ravel, Jean-Marie, Fraser, Rupsha, Ortseifen, Vera, Marchesi, Silvia, Gawron, Piotr, Smula, Ewa, Heirendt, Laurent, Satagopam, Venkata, Wu, Guanming, Riutta, Anders, Golebiewski, Martin, Owen, Stuart, Goble, Carole, Hu, Xiaoming, Overall, Rupert W., Maier, Dieter, Bauch, Angela, Gyori, Benjamin M., Bachman, John A., Vega, Carlos, Groues, Valentin, Vazquez, Miguel, Porras, Pablo, Licata, Luana, Iannuccelli, Marta, Sacco, Francesca, Nesterova, Anastasia, Yuryev, Anton, de Waard, Anita, Turei, Denes, Luna, Augustin, Babur, Ozgun, Soliman, Sylvain, Valdeolivas, Alberto, Esteban-Medina, Marina, Peña-Chilet, Maria, Rian, Kinza, Helikar, Tomáš, Puniya, Bhanwar Lal, Modos, Dezso, Treveil, Agatha, Olbei, Marton, De Meulder, Bertrand, Ballereau, Stephane, Dugourd, Aurélien, Naldi, Aurélien, Noël, Vincent, Calzone, Laurence, Sander, Chris, Demir, Emek, Korcsmaros, Tamas, Freeman, Tom C., Augé, Franck, Beckmann, Jacques S., Hasenauer, Jan, Wolkenhauer, Olaf, Wilighagen, Egon L., Pico, Alexander R., Evelo, Chris T., Gillespie, Marc E., Stein, Lincoln D., Hermjakob, Henning, D'Eustachio, Peter, Saez-Rodriguez, Julio, Dopazo, Joaquin, Valencia, Alfonso, Kitano, Hiroaki, Barillot, Emmanuel, Auffray, Charles, Balling, Rudi, Schneider, Reinhard, Luxembourg Centre for Systems Biomedicine (LCSB): Bioinformatics Core (R. Schneider Group) [research center], Fonds National de la Recherche - FnR [sponsor], Ostaszewski, Marek, Niarakis, Anna, Mazein, Alexander, Kuperstein, Inna, Phair, Robert, Orta-Resendiz, Aurelio, Singh, Vidisha, Aghamiri, Sara Sadat, Acencio, Marcio Luis, Glaab, Enrico, Ruepp, Andreas, Fobo, Gisela, Montrone, Corinna, Brauner, Barbara, Frishman, Goar, Monraz Gómez, Luis Cristóbal, Somers, Julia, Hoch, Matti, Kumar Gupta, Shailendra, Scheel, Julia, Borlinghaus, Hanna, Czauderna, Tobias, Schreiber, Falk, Montagud, Arnau, Ponce de Leon, Miguel, Funahashi, Akira, Hiki, Yusuke, Hiroi, Noriko, Yamada, Takahiro G., Dräger, Andreas, Renz, Alina, Naveez, Muhammad, Bocskei, Zsolt, Messina, Francesco, Börnigen, Daniela, Fergusson, Liam, Conti, Marta, Rameil, Marius, Nakonecnij, Vanessa, Vanhoefer, Jakob, Schmiester, Leonard, Wang, Muying, Ackerman, Emily E., Shoemaker, Jason E., Zucker, Jeremy, Oxford, Kristie, Teuton, Jeremy, Kocakaya, Ebru, Summak, Gökçe Yağmur, Hanspers, Kristina, Kutmon, Martina, Coort, Susan, Eijssen, Lars, Ehrhart, Friederike, Rex, Devasahayam Arokia Balaya, Slenter, Denise, Martens, Marvin, Pham, Nhung, Haw, Robin, Jassal, Bijay, Matthews, Lisa, Orlic-Milacic, Marija, Senff Ribeiro, Andrea, Rothfels, Karen, Shamovsky, Veronica, Stephan, Ralf, Sevilla, Cristoffer, Varusai, Thawfeek, Ravel, Jean-Marie, Fraser, Rupsha, Ortseifen, Vera, Marchesi, Silvia, Gawron, Piotr, Smula, Ewa, Heirendt, Laurent, Satagopam, Venkata, Wu, Guanming, Riutta, Anders, Golebiewski, Martin, Owen, Stuart, Goble, Carole, Hu, Xiaoming, Overall, Rupert W., Maier, Dieter, Bauch, Angela, Gyori, Benjamin M., Bachman, John A., Vega, Carlos, Groues, Valentin, Vazquez, Miguel, Porras, Pablo, Licata, Luana, Iannuccelli, Marta, Sacco, Francesca, Nesterova, Anastasia, Yuryev, Anton, de Waard, Anita, Turei, Denes, Luna, Augustin, Babur, Ozgun, Soliman, Sylvain, Valdeolivas, Alberto, Esteban-Medina, Marina, Peña-Chilet, Maria, Rian, Kinza, Helikar, Tomáš, Puniya, Bhanwar Lal, Modos, Dezso, Treveil, Agatha, Olbei, Marton, De Meulder, Bertrand, Ballereau, Stephane, Dugourd, Aurélien, Naldi, Aurélien, Noël, Vincent, Calzone, Laurence, Sander, Chris, Demir, Emek, Korcsmaros, Tamas, Freeman, Tom C., Augé, Franck, Beckmann, Jacques S., Hasenauer, Jan, Wolkenhauer, Olaf, Wilighagen, Egon L., Pico, Alexander R., Evelo, Chris T., Gillespie, Marc E., Stein, Lincoln D., Hermjakob, Henning, D'Eustachio, Peter, Saez-Rodriguez, Julio, Dopazo, Joaquin, Valencia, Alfonso, Kitano, Hiroaki, Barillot, Emmanuel, Auffray, Charles, Balling, Rudi, and Schneider, Reinhard

Abstract

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.

Published
2021

17. COVID19 Disease Map, a computational knowledge repository of virus–host interaction mechanisms

Author

Fonds National de la Recherche Luxembourg, European Commission, Federal Ministry of Education and Research (Germany), Ministry of Science, Research and Art Baden-Württemberg, German Center for Infection Research, Netherlands Organisation for Health Research and Development, National Institutes of Health (US), European Molecular Biology Laboratory, Ostaszewski, Marek, Niarakis, Anna, Mazein, Alexander, Kuperstein, Inna, Phair, Robert, Orta-Resendiz, Aurelio, Singh, Vidisha, Aghamiri, Sara Sadat, Acencio, Marcio Luis, Glaab, Enrico, Ruepp, Andreas, Schreiber, Falk, Montagud, Arnau, Ponce de León, Miguel, Funahashi, Akira, Hiki, Yusuke, Hiroi, Noriko, Yamada, Takahiro G., Dräger, Andreas, Renz, Alina, Naveez, Muhammad, Orlic-Milacic, Marija, Bocskei, Zsolt, Messina, Francesco, Börnigen, Daniela, Fergusson, Liam, Conti, Marta, Rameil, Marius, Nakonecnij, Vanessa, Vanhoefer, Jakob, Schmiester, Leonard, Wang, Muying, Senff Ribeiro, Andrea, Ackerman, Emily E., Shoemaker, Jason E., Zucker, Jeremy, Oxford, Kristie, Teuton, Jeremy, Kocakaya, Ebru, Summak, Gökçe Yagmu, Hanspers, Kristina, Kutmon, Martina, Coort, Susan, Rothfels, Karen, Eijssen, Lars, Ehrhart, Friederike, Arokia Balaya Rex, Devasahayam, Slenter, Denise, Martens, Marvin, Pham, Nhung, Haw, Robin, Jassal, Bijay, Matthews, Lisa, Shamovsky, Veronic, Stephan, Ralf, Sevilla, Cristoffer, Varusai, Thawfeek, Ravel, Jean-Marie, Fraser, Rupsha, Ortseifen, Vera, Soliman, Sylvain, Marchesi, Silvia, Gawron, Piotr, Smula, Ewa, Heirendt, Laurent, Satagopam, Venkata, Wu, Guanming, Riutta, Anders, Golebiewski, Martin, Owen, Stuart, Goble, Carole, Valdeolivas, Alberto, Hu, Xiaoming, Overall, Rupert W., Maier, Dieter, Bauch, Angela, Gyori, Benjamin M., Bachman, John A., Vega, Carlos, Groues, Valentin, Vázquez, Miguel, Porras, Pablo, Esteban-Medina, Marina, Licata, Luana, Iannuccelli, Marta, Sacco, Francesca, Nesterova, Anastasia, Yuryev, Anton, Waard, Anita de, Turei, Denes, Luna, Augustín, Babur, Ozgun, Peña-Chilet, María, Rian, Kinza, Helikar, Tomas, Lal Puniya, Bhanwar, Modos, Dezso, Treveil, Agatha, Olbe, Marton, Fobo, Gisela, De Meulder, Bertrand, Ballereau, Stephane, Dugourd, Aurelien, Naldi, Aurelien, Noël, Vincent, Calzone, Laurence, Sander, Chris, Demir, Emek, Korcsmaros, Tamas, Freeman, Tom C., Montrone, Corinna, Auge, Franck, Beckmann, Jacques S., Hasenauer, Jan, Wolkenhauer, Olaf, Wilighagen, Egon L ., Pico, Alexander R., Evelo, Chris T., Gillespie, Marc E., Stein, Lincoln D., Hermjakob, Henning, Brauner, Barbara, D’Eustachio, Peter, Sáez-Rodríguez, Julio, Dopazo, Joaquín, Valencia, Alfonso, Kitano, Hiroaki, Barillot, Emmanuel, Auffray, Charles, Balling, Rudi, Schneider, Reinhard, Frishman, Goar, Monraz Gómez, Luis Cristóbal, Somers, Julia, Hoch, Matti, Gupta, Shailendra Kumar, Scheel, Julia, Borlinghaus, Hanna, Czauderna, Tobias, Fonds National de la Recherche Luxembourg, European Commission, Federal Ministry of Education and Research (Germany), Ministry of Science, Research and Art Baden-Württemberg, German Center for Infection Research, Netherlands Organisation for Health Research and Development, National Institutes of Health (US), European Molecular Biology Laboratory, Ostaszewski, Marek, Niarakis, Anna, Mazein, Alexander, Kuperstein, Inna, Phair, Robert, Orta-Resendiz, Aurelio, Singh, Vidisha, Aghamiri, Sara Sadat, Acencio, Marcio Luis, Glaab, Enrico, Ruepp, Andreas, Schreiber, Falk, Montagud, Arnau, Ponce de León, Miguel, Funahashi, Akira, Hiki, Yusuke, Hiroi, Noriko, Yamada, Takahiro G., Dräger, Andreas, Renz, Alina, Naveez, Muhammad, Orlic-Milacic, Marija, Bocskei, Zsolt, Messina, Francesco, Börnigen, Daniela, Fergusson, Liam, Conti, Marta, Rameil, Marius, Nakonecnij, Vanessa, Vanhoefer, Jakob, Schmiester, Leonard, Wang, Muying, Senff Ribeiro, Andrea, Ackerman, Emily E., Shoemaker, Jason E., Zucker, Jeremy, Oxford, Kristie, Teuton, Jeremy, Kocakaya, Ebru, Summak, Gökçe Yagmu, Hanspers, Kristina, Kutmon, Martina, Coort, Susan, Rothfels, Karen, Eijssen, Lars, Ehrhart, Friederike, Arokia Balaya Rex, Devasahayam, Slenter, Denise, Martens, Marvin, Pham, Nhung, Haw, Robin, Jassal, Bijay, Matthews, Lisa, Shamovsky, Veronic, Stephan, Ralf, Sevilla, Cristoffer, Varusai, Thawfeek, Ravel, Jean-Marie, Fraser, Rupsha, Ortseifen, Vera, Soliman, Sylvain, Marchesi, Silvia, Gawron, Piotr, Smula, Ewa, Heirendt, Laurent, Satagopam, Venkata, Wu, Guanming, Riutta, Anders, Golebiewski, Martin, Owen, Stuart, Goble, Carole, Valdeolivas, Alberto, Hu, Xiaoming, Overall, Rupert W., Maier, Dieter, Bauch, Angela, Gyori, Benjamin M., Bachman, John A., Vega, Carlos, Groues, Valentin, Vázquez, Miguel, Porras, Pablo, Esteban-Medina, Marina, Licata, Luana, Iannuccelli, Marta, Sacco, Francesca, Nesterova, Anastasia, Yuryev, Anton, Waard, Anita de, Turei, Denes, Luna, Augustín, Babur, Ozgun, Peña-Chilet, María, Rian, Kinza, Helikar, Tomas, Lal Puniya, Bhanwar, Modos, Dezso, Treveil, Agatha, Olbe, Marton, Fobo, Gisela, De Meulder, Bertrand, Ballereau, Stephane, Dugourd, Aurelien, Naldi, Aurelien, Noël, Vincent, Calzone, Laurence, Sander, Chris, Demir, Emek, Korcsmaros, Tamas, Freeman, Tom C., Montrone, Corinna, Auge, Franck, Beckmann, Jacques S., Hasenauer, Jan, Wolkenhauer, Olaf, Wilighagen, Egon L ., Pico, Alexander R., Evelo, Chris T., Gillespie, Marc E., Stein, Lincoln D., Hermjakob, Henning, Brauner, Barbara, D’Eustachio, Peter, Sáez-Rodríguez, Julio, Dopazo, Joaquín, Valencia, Alfonso, Kitano, Hiroaki, Barillot, Emmanuel, Auffray, Charles, Balling, Rudi, Schneider, Reinhard, Frishman, Goar, Monraz Gómez, Luis Cristóbal, Somers, Julia, Hoch, Matti, Gupta, Shailendra Kumar, Scheel, Julia, Borlinghaus, Hanna, and Czauderna, Tobias

Abstract

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.

Published
2021

19. A Mechanistic Cellular Atlas of the Rheumatic Joint.

Author

Zerrouk, Naouel, Aghakhani, Sahar, Singh, Vidisha, Augé, Franck, and Niarakis, Anna

Subjects
GENE mapping, TH1 cells, RHEUMATOID arthritis, MOLECULAR interactions, METABOLIC regulation
Abstract

Rheumatoid Arthritis (RA) is an autoimmune disease of unknown aetiology involving complex interactions between environmental and genetic factors. Its pathogenesis is suspected to arise from intricate interplays between signalling, gene regulation and metabolism, leading to synovial inflammation, bone erosion and cartilage destruction in the patients' joints. In addition, the resident synoviocytes of macrophage and fibroblast types can interact with innate and adaptive immune cells and contribute to the disease's debilitating symptoms. Therefore, a detailed, mechanistic mapping of the molecular pathways and cellular crosstalks is essential to understand the complex biological processes and different disease manifestations. In this regard, we present the RA-Atlas, an SBGN-standardized, interactive, manually curated representation of existing knowledge related to the onset and progression of RA. This state-of-the-art RA-Atlas includes an updated version of the global RA-map covering relevant metabolic pathways and cell-specific molecular interaction maps for CD4+ Th1 cells, fibroblasts, and M1 and M2 macrophages. The molecular interaction maps were built using information extracted from published literature and pathway databases and enriched using omic data. The RA-Atlas is freely accessible on the webserver MINERVA (https://ramap.uni.lu/minerva/), allowing easy navigation using semantic zoom, cell-specific or experimental data overlay, gene set enrichment analysis, pathway export or drug query. [ABSTRACT FROM AUTHOR]

Published
2022
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20. Automated inference of Boolean models from molecular interaction maps using CaSQ

Author

Aghamiri, Sara Sadat, Singh, Vidisha, Naldi, Aurélien, Helikar, Tomáš, Soliman, Sylvain, Niarakis, Anna, Laboratoire de recherche européen pour la polyarthrite rhumatoïde (GenHotel), Université d'Évry-Val-d'Essonne (UEVE)-Université Paris-Saclay, Institut de biologie de l'ENS Paris (IBENS), Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Département de Biologie - ENS Paris, École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), University of Nebraska [Lincoln], University of Nebraska System, Computational systems biology and optimization (Lifeware), Inria Saclay - Ile de France, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Département de Biologie - ENS Paris, École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), University of Nebraska–Lincoln, ANR-16-CE18-0029,BIOPSY,Système de programmation à base de réseaux biochimiques(2016), Institut de biologie de l'ENS Paris (UMR 8197/1024) (IBENS), Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Département de Biologie - ENS Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM), and Soliman, Sylvain

Subjects
[INFO.INFO-PL]Computer Science [cs]/Programming Languages [cs.PL], AcademicSubjects/SCI01060, [SDV.GEN.GH]Life Sciences [q-bio]/Genetics/Human genetics, Systems Biology, Original Papers, Models, Biological, [SDV.BIBS]Life Sciences [q-bio]/Quantitative Methods [q-bio.QM], Software, ComputingMilieux_MISCELLANEOUS, [INFO.INFO-PL] Computer Science [cs]/Programming Languages [cs.PL]
Abstract

Motivation Molecular interaction maps have emerged as a meaningful way of representing biological mechanisms in a comprehensive and systematic manner. However, their static nature provides limited insights to the emerging behaviour of the described biological system under different conditions. Computational modelling provides the means to study dynamic properties through in silico simulations and perturbations. We aim to bridge the gap between static and dynamic representations of biological systems with CaSQ, a software tool that infers Boolean rules based on the topology and semantics of molecular interaction maps built with CellDesigner. Results We developed CaSQ by defining conversion rules and logical formulas for inferred Boolean models according to the topology and the annotations of the starting molecular interaction maps. We used CaSQ to produce executable files of existing molecular maps that differ in size, complexity and the use of Systems Biology Graphical Notation (SBGN) standards. We also compared, where possible, the manually built logical models corresponding to a molecular map to the ones inferred by CaSQ. The tool is able to process large and complex maps built with CellDesigner (either following SBGN standards or not) and produce Boolean models in a standard output format, Systems Biology Marked Up Language-qualitative (SBML-qual), that can be further analyzed using popular modelling tools. References, annotations and layout of the CellDesigner molecular map are retained in the obtained model, facilitating interoperability and model reusability. Availability and implementation The present tool is available online: https://lifeware.inria.fr/∼soliman/post/casq/ and distributed as a Python package under the GNU GPLv3 license. The code can be accessed here: https://gitlab.inria.fr/soliman/casq. Supplementary information Supplementary data are available at Bioinformatics online.

Published
2020
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22. Increased breadth of HIV-1 neutralization achieved by diverse antibody clones each with limited neutralization breadth

Author

Chukwuma, Valentine U., primary, Kose, Nurgun, additional, Sather, D. Noah, additional, Sapparapu, Gopal, additional, Falk, Rachel, additional, King, Hannah, additional, Singh, Vidisha, additional, Lampley, Rebecca, additional, Malherbe, Delphine C., additional, Ditto, Noah T., additional, Sullivan, Jonathan T., additional, Barnes, Trevor, additional, Doranz, Benjamin J., additional, Labranche, Celia C., additional, Montefiori, David C., additional, Kalams, Spyros A., additional, Haigwood, Nancy L., additional, and Crowe, James E., additional

Published
2018
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23. Computational Systems Biology Approach for the Study of Rheumatoid Arthritis: From a Molecular Map to a Dynamical Model

Author

Singh, Vidisha, Ostaszewski, Marek, Kalliolias, George D., Chiocchia, Gilles, Olaso, Robert, Petit-Teixeira, Elisabeth, Helikar, Thomas, Niarakis, Anna, Singh, Vidisha, Ostaszewski, Marek, Kalliolias, George D., Chiocchia, Gilles, Olaso, Robert, Petit-Teixeira, Elisabeth, Helikar, Thomas, and Niarakis, Anna

Abstract

In this work we present a systematic effort to summarize current biological pathway knowledge concerning Rheumatoid Arthritis (RA). We are constructing a detailed molecular map based on exhaustive literature scanning, strict curation criteria, re-evaluation of previously published attempts and most importantly experts’ advice. The RA map will be web-published in the coming months in the form of an interactive map, using the MINERVA platform, allowing for easy access, navigation and search of all molecular pathways implicated in RA, serving thus, as an on line knowledgebase for the disease. Moreover the map could be used as a template for Omics data visualization offering a first insight about the pathways affected in different experimental datasets. The second goal of the project is a dynamical study focused on synovial fibroblasts’ behavior under different initial conditions specific to RA, as recent studies have shown that synovial fibroblasts play a crucial role in driving the persistent, destructive characteristics of the disease. Leaning on the RA knowledgebase and using the web platform Cell Collective, we are currently building a Boolean large scale dynamical model for the study of RA fibroblasts’ activation

Published
2017

24. Recognition of influenza H3N2 variant virus by human neutralizing antibodies

Author

Bangaru, Sandhya, primary, Nieusma, Travis, additional, Kose, Nurgun, additional, Thornburg, Natalie J., additional, Finn, Jessica A., additional, Kaplan, Bryan S., additional, King, Hannah G., additional, Singh, Vidisha, additional, Lampley, Rebecca M., additional, Sapparapu, Gopal, additional, Cisneros, Alberto, additional, Edwards, Kathryn M., additional, Slaughter, James C., additional, Edupuganti, Srilatha, additional, Lai, Lilin, additional, Richt, Juergen A., additional, Webby, Richard J., additional, Ward, Andrew B., additional, and Crowe, James E., additional

Published
2016
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25. COVID‐19 Disease Map, a computational knowledge repository of virus‐host interaction mechanisms.

Author

Ostaszewski, Marek, Niarakis, Anna, Mazein, Alexander, Kuperstein, Inna, Phair, Robert, Orta‐Resendiz, Aurelio, Singh, Vidisha, Aghamiri, Sara Sadat, Acencio, Marcio Luis, Glaab, Enrico, Ruepp, Andreas, Fobo, Gisela, Montrone, Corinna, Brauner, Barbara, Frishman, Goar, Monraz Gómez, Luis Cristóbal, Somers, Julia, Hoch, Matti, Kumar Gupta, Shailendra, and Scheel, Julia

Subjects
COVID-19, DISEASE mapping, BIOLOGICAL mathematical modeling, BIOLOGICAL systems, COMPUTATIONAL biology
Abstract

COVID-19 Disease Map, a computational knowledge repository of virus-host interaction mechanisms GLO:1CEJ/01dec21:msb202110851-toc-0001.jpg PHOTO (COLOR): . gl The authors requested to correct the spelling of Egon Willighagen and Andrea Senff-Ribeiro's names, as well as the following affiliations: Charles Auffray to: "European Institute for Systems Biology and Medicine (EISBM), Vourles, France"; Noriko Hiori to: "Graduate School of Media and Governance, Keio Research Institute at SFC, Keio University, Kanagawa, Japan"; and Leonard Schmeister to: "Center for Mathematics, Chair of Mathematical Modeling of Biological Systems, Technische Universität München, Garching, Germany and Helmholtz Zentrum München - German Research Center for Environmental Health, Institute of Computational Biology, Neuherberg, Germany". [Extracted from the article]

Published
2021
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26. Phase Evolution and Stability of Aluminum Titanate Prepared by Solid -State Route and Solution Combustion Route

Author

Singh, Vidisha and Singh, Vidisha

Abstract

Aluminum titanate (Al2TiO5) powder was synthesized using two different route, namely, solid-state route and solution combustion route. In solid-state route, two different types (micron and nano-size powder) of Al2O3 precursor powder was used. Phase evolution and powder morphology were investigated by X-ray diffraction method and Field emission scanning electron microscope (FESEM) respectively. In case of large particle Al2O3 precursor powder, Al2TiO5 (AT) phase was formed at 1500oC with a yield of 97%. Whereas using nano-Al2O3 precursor powder, AT phase was formed at 1350oC with a yield of 91% and almost phase pure powder can be prepared at 1500oC. Average particle size of the AT powder was 11 µm (using large particle Al2O3) and 10.2 µm (using nano-size Al2O3) for calcination at 1500oC. AT powder was also synthesized by citrate-nitrate solution combustion method. The molar ratio of metal (Al:Ti) and citric acid was varied to get a uniform and complete combustion. A significant amount Al2TiO5 phase was formed at 1350°C. The stability of the solid state route prepared AT powder was investigated by keeping the powder at 1150°C/6hr. It was observed from the XRD analysis that only 40% AT-phase was retained in samples prepared with micron size Al2O3, but, in case of sample prepared using nano size Al2O3, 93% AT-phase was retained.

27. Phase Evolution and Stability of Aluminum Titanate Prepared by Solid -State Route and Solution Combustion Route

Author

Singh, Vidisha and Singh, Vidisha

Abstract

Aluminum titanate (Al2TiO5) powder was synthesized using two different route, namely, solid-state route and solution combustion route. In solid-state route, two different types (micron and nano-size powder) of Al2O3 precursor powder was used. Phase evolution and powder morphology were investigated by X-ray diffraction method and Field emission scanning electron microscope (FESEM) respectively. In case of large particle Al2O3 precursor powder, Al2TiO5 (AT) phase was formed at 1500oC with a yield of 97%. Whereas using nano-Al2O3 precursor powder, AT phase was formed at 1350oC with a yield of 91% and almost phase pure powder can be prepared at 1500oC. Average particle size of the AT powder was 11 µm (using large particle Al2O3) and 10.2 µm (using nano-size Al2O3) for calcination at 1500oC. AT powder was also synthesized by citrate-nitrate solution combustion method. The molar ratio of metal (Al:Ti) and citric acid was varied to get a uniform and complete combustion. A significant amount Al2TiO5 phase was formed at 1350°C. The stability of the solid state route prepared AT powder was investigated by keeping the powder at 1150°C/6hr. It was observed from the XRD analysis that only 40% AT-phase was retained in samples prepared with micron size Al2O3, but, in case of sample prepared using nano size Al2O3, 93% AT-phase was retained.

28. Brain microglia serve as a persistent HIV reservoir despite durable antiretroviral therapy.

Author

Yuyang Tang, Chaillon, Antoine, Gianella, Sara, Wong, Lilly M., Dajiang Li, Simermeyer, Theresa L., Porrachia, Magali, Ignacio, Caroline, Woodworth, Brendon, Zhong, Daniel, Jiayi Du, de la Parra Polina, Eduardo, Kirchherr, Jennifer, Allard, Brigitte, Clohosey, Matthew L., Moeser, Matt, Sondgeroth, Amy L., Whitehill, Gregory D., Singh, Vidisha, and Dashti, Amir

Subjects
*ANTIRETROVIRAL agents, *HIV, *MICROGLIA, *VIRUS diseases, *PARIETAL lobe
Abstract

Brain microglia (MG) may serve as a human immunodeficiency virus 1 (HIV) reservoir and ignite rebound viremia following cessation of antiretroviral therapy (ART), but they have yet to be proven to harbor replication-competent HIV. Here, we isolated brain myeloid cells (BrMCs) from nonhuman primates and rapid autopsy of people with HIV (PWH) on ART and sought evidence of persistent viral infection. BrMCs predominantly displayed microglial markers, in which up to 99.9% of the BrMCs were TMEM119+ MG. Total and integrated SIV or HIV DNA was detectable in the MG, with low levels of cell- associated viral RNA. Provirus in MG was highly sensitive to epigenetic inhibition. Outgrowth virus from parietal cortex MG in an individual with HIV productively infected both MG and PBMCs. This inducible, replication-competent virus and virus from basal ganglia proviral DNA were closely related but highly divergent from variants in peripheral compartments. Phenotyping studies characterized brain-derived virus as macrophage tropic based on the ability of the virus to infect cells expressing low levels of CD4. The lack of genetic diversity in virus from the brain suggests that this macrophage-tropic lineage quickly colonized brain regions. These data demonstrate that MG harbor replication-competent HIV and serve as a persistent reservoir in the brain. [ABSTRACT FROM AUTHOR]

Published
2023
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29. Drug-target identification in COVID-19 disease mechanisms using computational systems biology approaches.

Author

Niarakis A, Ostaszewski M, Mazein A, Kuperstein I, Kutmon M, Gillespie ME, Funahashi A, Acencio ML, Hemedan A, Aichem M, Klein K, Czauderna T, Burtscher F, Yamada TG, Hiki Y, Hiroi NF, Hu F, Pham N, Ehrhart F, Willighagen EL, Valdeolivas A, Dugourd A, Messina F, Esteban-Medina M, Peña-Chilet M, Rian K, Soliman S, Aghamiri SS, Puniya BL, Naldi A, Helikar T, Singh V, Fernández MF, Bermudez V, Tsirvouli E, Montagud A, Noël V, Ponce-de-Leon M, Maier D, Bauch A, Gyori BM, Bachman JA, Luna A, Piñero J, Furlong LI, Balaur I, Rougny A, Jarosz Y, Overall RW, Phair R, Perfetto L, Matthews L, Rex DAB, Orlic-Milacic M, Gomez LCM, De Meulder B, Ravel JM, Jassal B, Satagopam V, Wu G, Golebiewski M, Gawron P, Calzone L, Beckmann JS, Evelo CT, D'Eustachio P, Schreiber F, Saez-Rodriguez J, Dopazo J, Kuiper M, Valencia A, Wolkenhauer O, Kitano H, Barillot E, Auffray C, Balling R, and Schneider R

Subjects
Humans, SARS-CoV-2, Drug Repositioning, Systems Biology, Computer Simulation, COVID-19
Abstract

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., Competing Interests: AN collaborates with SANOFI-AVENTIS R&D via a public–private partnership grant CIFRE contract, n° 2020/0766. DM and AB are employed at Labvantage-Biomax GmbH and will be affected by any effect of this publication on the commercial version of the AILANI software. JB and BG received consulting fees from Two Six Labs, LLC. TH has served as a shareholder and has consulted for Discovery Collective, Inc. RB and RS are founders and shareholders of MEGENO SA and ITTM SA. JS-R reports funding from GSK, Pfizer and Sanofi and fees/honoraria from Travere Therapeutics, Stadapharm, Astex, Owkin, Pfizer and Grunenthal. JP and LF are employees and shareholders of MedBioinformatics Solutions SL. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be constructed as a potential conflict of interest. The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision., (Copyright © 2024 Niarakis, Ostaszewski, Mazein, Kuperstein, Kutmon, Gillespie, Funahashi, Acencio, Hemedan, Aichem, Klein, Czauderna, Burtscher, Yamada, Hiki, Hiroi, Hu, Pham, Ehrhart, Willighagen, Valdeolivas, Dugourd, Messina, Esteban-Medina, Peña-Chilet, Rian, Soliman, Aghamiri, Puniya, Naldi, Helikar, Singh, Fernández, Bermudez, Tsirvouli, Montagud, Noël, Ponce-de-Leon, Maier, Bauch, Gyori, Bachman, Luna, Piñero, Furlong, Balaur, Rougny, Jarosz, Overall, Phair, Perfetto, Matthews, Rex, Orlic-Milacic, Gomez, De Meulder, Ravel, Jassal, Satagopam, Wu, Golebiewski, Gawron, Calzone, Beckmann, Evelo, D’Eustachio, Schreiber, Saez-Rodriguez, Dopazo, Kuiper, Valencia, Wolkenhauer, Kitano, Barillot, Auffray, Balling, Schneider and the COVID-19 Disease Map Community.)

Published
2024
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30. Automated inference of Boolean models from molecular interaction maps using CaSQ.

Author

Aghamiri SS, Singh V, Naldi A, Helikar T, Soliman S, and Niarakis A

Subjects
Models, Biological, Software, Systems Biology
Abstract

Motivation: Molecular interaction maps have emerged as a meaningful way of representing biological mechanisms in a comprehensive and systematic manner. However, their static nature provides limited insights to the emerging behaviour of the described biological system under different conditions. Computational modelling provides the means to study dynamic properties through in silico simulations and perturbations. We aim to bridge the gap between static and dynamic representations of biological systems with CaSQ, a software tool that infers Boolean rules based on the topology and semantics of molecular interaction maps built with CellDesigner., Results: We developed CaSQ by defining conversion rules and logical formulas for inferred Boolean models according to the topology and the annotations of the starting molecular interaction maps. We used CaSQ to produce executable files of existing molecular maps that differ in size, complexity and the use of Systems Biology Graphical Notation (SBGN) standards. We also compared, where possible, the manually built logical models corresponding to a molecular map to the ones inferred by CaSQ. The tool is able to process large and complex maps built with CellDesigner (either following SBGN standards or not) and produce Boolean models in a standard output format, Systems Biology Marked Up Language-qualitative (SBML-qual), that can be further analyzed using popular modelling tools. References, annotations and layout of the CellDesigner molecular map are retained in the obtained model, facilitating interoperability and model reusability., Availability and Implementation: The present tool is available online: https://lifeware.inria.fr/∼soliman/post/casq/ and distributed as a Python package under the GNU GPLv3 license. The code can be accessed here: https://gitlab.inria.fr/soliman/casq., Supplementary Information: Supplementary data are available at Bioinformatics online., (© The Author(s) 2020. Published by Oxford University Press.)

Published
2020
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