{"id":232,"date":"2021-12-06T09:32:05","date_gmt":"2021-12-06T09:32:05","guid":{"rendered":"https:\/\/website.prod.unilu.spikeseed.cloud\/lcsb-fr\/news\/experimental-and-computational-synergy-promising-covid-19-results\/"},"modified":"2021-12-06T09:32:05","modified_gmt":"2021-12-06T09:32:05","slug":"experimental-and-computational-synergy-promising-covid-19-results","status":"publish","type":"news","link":"https:\/\/www.uni.lu\/lcsb-fr\/news\/experimental-and-computational-synergy-promising-covid-19-results\/","title":{"rendered":"Experimental and computational synergy \u2013 Promising COVID-19 results"},"content":{"rendered":"

An international collaboration between researchers from the Luxembourg Centre for Systems Biomedicine (LCSB) at the University of Luxembourg, the Centre for Cooperative Research in Biosciences (CIC bioGUNE, Bilbao) and the Department of Immunology of St Jude Children\u2019s Research Hospital (Kanneganti Lab, Memphis) highlights how fostering synergies between computational and experimental studies can lead to important results in the field of immunology. In an article published in November in\u00a0Trends in Immunology<\/i>, researchers illustrate the potential of this type of collaboration through recent results obtained on the modulation of hyperinflammation in COVID-19. Both a computational approach led by Prof. Antonio Del Sol and an experimental study led by Dr.\u00a0Thirumala-Devi\u00a0Kanneganti showed that a specific protein could help modulate COVID-19-induced lung hyperinflammation. Building on this success, the authors detail how experimental and computational approaches can support each other and advocate for coordinated efforts to accelerate the discovery of new therapeutic targets.<\/p>\n

\nSystems immunology \u2013 A promising new approach<\/h2>\n

Thanks to the large amount of -omics data becoming increasingly available, sophisticated computational models are developed for new fields such as immunology and the predictions they generate will help identify key molecules in inflammatory processes. The application of such computational systems biology approaches to immunology could lead to novel and more efficacious therapeutic strategies. \u201cThe recent work of our two teams on the modulation of hyperinflammation in COVID-19 illustrates really well how the synergy between experimental and computational researchers can accelerate the discovery of molecules of interest,\u201d explains\u00a0Prof. Antonio Del Sol<\/a>, head of the\u00a0Computational Biology<\/a>\u00a0groups at the LCSB and\u00a0CIC bioGUNE<\/a>. \u201cBy using computational modelling to inform traditional experimental approaches, we confirmed in a few months a potential target for medical intervention in COVID-19 patients. This is indeed very promising.\u201d<\/p>\n

\nUnderstanding the \u201ccytokine storm\u201d in COVID-19<\/h2>\n

In recent studies, researchers from the LCSB and CIC bioGUNE – on the computational side – and from the\u00a0Kanneganti Lab<\/a>\u00a0at St. Jude Children\u2019s Research Hospital – on the experimental side – focused on the mechanisms underlying the hyperinflammatory response in COVID-19. Hyperinflammation is caused when the immune response is amplified and maintained by positive feedback loops above the level needed to control disease. Kanneganti\u2019s lab recently found that in COVID-19, as well as other diseases, this hyperinflammatory \u201ccytokine storm\u201d could be mechanistically defined as a life-threatening condition caused by excessive production of proinflammatory proteins, cytokines, mediated by a form of inflammatory cell death called PANoptosis.\u00a0In COVID-19, PANoptosis and the concomitant cytokine storm\u00a0cause organ damage and increase the severity of the symptoms. This makes treatment challenging, as therapeutics need to alleviate inflammation while maintaining the patient\u2019s ability to clear the virus through cell death and other pathways. It is therefore crucial to identify the molecules that amplify and maintain the inflammatory response. It is the first step towards new and putative life-saving therapeutic strategies.<\/p>\n

\nTwo studies identify protein TLR2 as a target<\/h2>\n

In a first\u00a0Science Advances<\/i>\u00a0in February 2021, researchers from the Computational Biology groups of the LCSB and CIC bioGUNE used a novel computational method to analyse over 1700 cell-cell interactions and create a comprehensive map of the immune response in the lungs of COVID-19 patients. Their model identified Toll-like Receptor 2 (TLR2) as a molecule that might be able to modulate the inflammatory response, predicting that the inhibition of this protein could disrupt up to 75% of the feedback loops without interfering with the general immune response. The study put TLR2 on the map as a potential target for medical intervention in severe COVID-19 cases.<\/p>

Separately, in May 2021, the team of\u00a0Dr.\u00a0Thirumala-Devi Kanneganti<\/a>\u00a0from the Department of Immunology of St Jude Children\u2019s Research Hospital\u00a0published a\u00a0Nature Immunology<\/i>\u00a0that\u00a0<\/strong>independently suggested that TLR2 might act as a key modulator of COVID-19-induced hyperinflammation. Using\u00a0in vitro<\/i>\u00a0and\u00a0in vivo<\/i>\u00a0experiments, the researchers found that increased expression of\u00a0TLR2<\/i>\u00a0in the blood of patients with COVID-19 correlated with disease severity and that, upon infection by the virus, TLR2 mediated the production of cytokines. The study also showed that treatment of transgenic mice with a TLR2 inhibitor protected the animals against SARS-CoV-2-mediated inflammatory cytokine production and mortality. \u201cExperimental validation of computationally derived biomarkers is critical to provide multiple lines of evidence to support the proof-of-concept for the utility of targeting TLR2 to modulate inflammation. It is imperative to combine computational and experimental approaches to understand mechanisms involved in inflammatory processes,\u201d underlines Dr. Kanneganti.<\/p>\n

\nA coordinated effort to achieve full potential<\/h2>\n

This example is far from the only one: In a growing number of studies, systems immunology approaches are being successfully employed to help predict novel therapeutic targets for modulating uncontrolled immune responses. \u201cComputational modelling and experimental validation will become key partnerships in biomedical research and should be systematically developed to achieve their full potential,\u201d details Dr Ilya Potapov, member of the Computational Biology group at the LCSB.<\/p>

In their\u00a0Trends in Immunology<\/i>, the three co-authors mention the challenges researchers will have to tackle when building computational models in the context of hyperinflammation \u2013 such as technological limitations, shortage of good experimental models and mutual unawareness \u2013 and postulate that experimental and computational efforts should be synergised from the onset. \u201cThe technological advances have set the stage for us. Now, we\u00a0need to work together to build accurate computational models, define the necessary data and design experiments to validate the computational predictions. This is the key to designing novel and more efficacious therapeutic strategies,\u201d concludes Prof. Del Sol.<\/p>\n

\nReferences:<\/h5>\n

Trends in Immunology<\/i>Ilya Potapov, Thirumala-Devi Kanneganti & Antonio del Sol,\u00a0Fostering experimental and computational synergy to modulate hyperinflammation<\/strong><\/a>,\u00a0, 26\u00a0November 2021.<\/p>

Nature Immunology<\/i>Min Zheng, Rajendra Karki, Evan Peter Williams, Dong Yang, Elizabeth Fitzpatrick, Peter Vogel, Colleen Beth Jonsson & Thirumala-Devi Kanneganti,\u00a0TLR2 senses the SARS-CoV-2 envelope protein to produce inflammatory cytokines<\/strong><\/a>,\u00a0, 7 May 2021.<\/p>

Science Advances<\/i>Sascha Jung, Ilya Potapov, Samyukta Chillara & Antonio del Sol,\u00a0Leveraging systems biology for predicting modulators of inflammation in patients with COVID-19<\/strong><\/a>,\u00a0, 3 February 2021.<\/p><\/div><\/section>","protected":false},"excerpt":{"rendered":"

An international collaboration between researchers from the Luxembourg Centre for Systems Biomedicine (LCSB) at the University of Luxembourg, the Centre for Cooperative Research in Biosciences (CIC bioGUNE, Bilbao) and the Department of Immunology of St Jude Children\u2019s Research Hospital (Kanneganti Lab, Memphis) highlights how fostering synergies between computational and experimental studies can lead to important results in the field of immunology. In an article published in November in\u00a0Trends in Immunology, researchers illustrate the potential of this type of collaboration through recent results obtained on the modulation of hyperinflammation in COVID-19. Both a computational approach led by Prof. Antonio Del Sol and an experimental study led by Dr.\u00a0Thirumala-Devi\u00a0Kanneganti showed that a specific protein could help modulate COVID-19-induced lung hyperinflammation. Building on this success, the authors detail how experimental and computational approaches can support each other and advocate for coordinated efforts to accelerate the discovery of new therapeutic targets.<\/p>\n","protected":false},"author":0,"featured_media":233,"template":"","format":"standard","meta":{"featured_image_focal_point":[],"show_featured_caption":false,"ulux_newsletter_groups":"","uluxPostTitle":"","uluxPrePostTitle":"","_trash_the_other_posts":false,"_price":"","_stock":"","_tribe_ticket_header":"","_tribe_default_ticket_provider":"","_tribe_ticket_capacity":"0","_ticket_start_date":"","_ticket_end_date":"","_tribe_ticket_show_description":"","_tribe_ticket_show_not_going":false,"_tribe_ticket_use_global_stock":"","_tribe_ticket_global_stock_level":"","_global_stock_mode":"","_global_stock_cap":"","_tribe_rsvp_for_event":"","_tribe_ticket_going_count":"","_tribe_ticket_not_going_count":"","_tribe_tickets_list":"[]","_tribe_ticket_has_attendee_info_fields":false},"news-category":[3],"news-topic":[18],"organisation":[],"authorship":[],"acf":[],"yoast_head":"\nExperimental and computational synergy \u2013 Promising COVID-19 results - LCSB - Universit\u00e9 du Luxembourg I Uni.lu<\/title>\n<meta name=\"description\" content=\"An international collaboration between researchers from the Luxembourg Centre for Systems Biomedicine (LCSB) at the University of Luxembourg, the Centre for Cooperative Research in Biosciences (CIC bioGUNE, Bilbao) and the Department of Immunology of St Jude Children\u2019s Research Hospital (Kanneganti Lab, Memphis) highlights how fostering synergies between computational and experimental studies can lead to important results in the field of immunology. In an article published in November in\u00a0Trends in Immunology, researchers illustrate the potential of this type of collaboration through recent results obtained on the modulation of hyperinflammation in COVID-19. Both a computational approach led by Prof. Antonio Del Sol and an experimental study led by Dr.\u00a0Thirumala-Devi\u00a0Kanneganti showed that a specific protein could help modulate COVID-19-induced lung hyperinflammation. 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