TY - JOUR AU - Pietiäinen, Vilja AU - Polso, Minttu AU - Migh, Ede AU - Guckelsberger, Christian AU - Harmati, Mária AU - Diósdi, Ákos AU - Turunen, Laura AU - Hassinen, Antti AU - Potdar, Swapnil AU - Koponen, Annika AU - Gyukity-Sebestyén, Edina AU - Kovács, Ferenc AU - Kriston, András AU - Hollandi, Réka AU - Burián, Katalin AU - Terhes, Gabriella AU - Visnyovszki, Ádám AU - Fodor, Eszter AU - Lacza, Zsombor AU - Kantele, Anu AU - Kolehmainen, Pekka AU - Kakkola, Laura AU - Strandin, Tomas AU - Levanov, Lev AU - Kallioniemi, Olli AU - Kemény, Lajos AU - Julkunen, Ilkka AU - Vapalahti, Olli AU - Buzás, Krisztina AU - Paavolainen, Lassi AU - Horváth, Péter AU - Hepojoki, Jussi TI - Image-based and machine learning-guided multiplexed serology test for SARS-CoV-2 JF - CELL REPORTS METHODS J2 - CELL REP METH VL - 3 PY - 2023 IS - 8 PG - 19 SN - 2667-2375 DO - 10.1016/j.crmeth.2023.100565 UR - https://m2.mtmt.hu/api/publication/34107493 ID - 34107493 N1 - HCEMM-USZ Skin Research Group Funding Agency and Grant Number: LENDULET-BIOMAG grant; European Regional Development Funds; H2020-discovAIR; H2020 ATTRACT-Spheroid -Picker; Chan Zuckerberg Initiative, Seed Networks for the HCA-DVP [2018-342, GINOP-2.3.2-15-2016-00006, GINOP-2.3.2-15-2016-00026]; Finnish TEKES/BusinessFinland FiDiPro [GINOP-2.3.2-15-2016-00037]; Academy of Finland; EU H2020 VEO project; Minerva Foundation for COVID-19 Research project grant [874656]; Academy of Finland Flagship program, Finnish Center for Artificial Intelligence [40294/13, iCOIN-336496, 308613, 321809, 310552, 337530]; NKFIH grants; [FIRI2020-337036]; [2020-1.1.6-JOVO-2021-00010]; [TKP2020-NKA-17] Funding text: The authors thank the Minerva Institute (Helsinki, Finland) for providing utilities for the project, Prof. Perttu Hamalainen (Aalto University, Finland) for providing the expertise of his group for the project, the FIMM High Throughput Biomedicine Unit for providing access to high-throughput robotics, the FIMM High Content Imaging and Analysis Unit for HC imaging and analysis (HiLIFE, University of Helsinki and Biocenter Finland; EuroBioImaging, ISIDORe partner), and the CSC - IT Center for Science, Finland, for computational resources. We acknowledge support from the LENDULET-BIOMAG grant (2018-342), from the European Regional Development Funds (GINOP-2.3.2-15-2016-00006, GINOP-2.3.2-15-2016-00026, and GINOP-2.3.2-15-2016-00037), from the H2020-discovAIR (874656), from the H2020 ATTRACT-Spheroid -Picker, and from the Chan Zuckerberg Initiative, Seed Networks for the HCA-DVP. The Finnish TEKES/BusinessFinland FiDiPro Fellow Grant 40294/13 (to V.P., O.K., L.P., and P.H.), grants awarded by the Academy of Finland (iCOIN-336496 to O.K., V.P., and O.V.; 308613 to J.H.; 321809 to T.S.; 310552 to L.P.; 337530 to I.J.; and FIRI2020-337036 to FIMM-HCA, A.H., L.P., V.P., and P.H.), the EU H2020 VEO project (O.V.), and a Minerva Foundation for COVID-19 Research project grant (to V.P.) are also acknowledged. C.G. is funded by the Academy of Finland Flagship program, Finnish Center for Artificial Intelligence. OrthoSera Ltd. was funded by NKFIH grants (2020-1.1.6-JOVO-2021-00010 and TKP2020-NKA-17). The authors thank Dora Bokor, PharmD, for proofreading the manuscript. AB - We present a miniaturized immunofluorescence assay (mini-IFA) for measuring antibody response in patient blood samples. The method utilizes machine learning-guided image analysis and enables simultaneous mea- surement of immunoglobulin M (IgM), IgA, and IgG responses against different viral antigens in an automated and high-throughput manner. The assay relies on antigens expressed through transfection, enabling use at a low biosafety level and fast adaptation to emerging pathogens. Using severe acute respiratory syndrome co- ronavirus 2 (SARS-CoV-2) as the model pathogen, we demonstrate that this method allows differentiation be- tween vaccine-induced and infection-induced antibody responses. Additionally, we established a dedicated web page for quantitative visualization of sample-specific results and their distribution, comparing them with controls and other samples. Our results provide a proof of concept for the approach, demonstrating fast and accurate measurement of antibody responses in a research setup with prospects for clinical diagnostics. LA - English DB - MTMT ER - TY - JOUR AU - Sahin, Ugur AU - Muik, Alexander AU - Derhovanessian, Evelyna AU - Vogler, Isabel AU - Kranz, Lena M. AU - Vormehr, Mathias AU - Baum, Alina AU - Pascal, Kristen AU - Quandt, Jasmin AU - Maurus, Daniel AU - Brachtendorf, Sebastian AU - Loerks, Verena AU - Sikorski, Julian AU - Hilker, Rolf AU - Becker, Dirk AU - Eller, Ann-Kathrin AU - Gruetzner, Jan AU - Boesler, Carsten AU - Rosenbaum, Corinna AU - Kuehnle, Marie-Cristine AU - Luxemburger, Ulrich AU - Kemmer-Brueck, Alexandra AU - Langer, David AU - Bexon, Martin AU - Bolte, Stefanie AU - Karikó, Katalin AU - Palanche, Tania AU - Fischer, Boris AU - Schultz, Armin AU - Shi, Pei-Yong AU - Fontes-Garfias, Camila AU - Perez, John L. AU - Swanson, Kena A. AU - Loschko, Jakob AU - Scully, Ingrid L. AU - Cutler, Mark AU - Kalina, Warren AU - Kyratsous, Christos A. AU - Cooper, David AU - Dormitzer, Philip R. AU - Jansen, Kathrin U. AU - Tuereci, Oezlem TI - COVID-19 vaccine BNT162b1 elicits human antibody and T(H)1 T cell responses JF - NATURE J2 - NATURE VL - 586 PY - 2020 IS - 7830 SP - 594 EP - 599 PG - 19 SN - 0028-0836 DO - 10.1038/s41586-020-2814-7 UR - https://m2.mtmt.hu/api/publication/32039122 ID - 32039122 AB - In a phase I/II dose-escalation clinical trial, the mRNA COVID-19 vaccine BNT162b1 elicits specific T cell and antibody responses that suggest it has protective potential. An effective vaccine is needed to halt the spread of the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) pandemic. Recently, we reported safety, tolerability and antibody response data from an ongoing placebo-controlled, observer-blinded phase I/II coronavirus disease 2019 (COVID-19) vaccine trial with BNT162b1, a lipid nanoparticle-formulated nucleoside-modified mRNA that encodes the receptor binding domain (RBD) of the SARS-CoV-2 spike protein(1). Here we present antibody and T cell responses after vaccination with BNT162b1 from a second, non-randomized open-label phase I/II trial in healthy adults, 18-55 years of age. Two doses of 1-50 mu g of BNT162b1 elicited robust CD4(+)and CD8(+)T cell responses and strong antibody responses, with RBD-binding IgG concentrations clearly above those seen in serum from a cohort of individuals who had recovered from COVID-19. Geometric mean titres of SARS-CoV-2 serum-neutralizing antibodies on day 43 were 0.7-fold (1-mu g dose) to 3.5-fold (50-mu g dose) those of the recovered individuals. Immune sera broadly neutralized pseudoviruses with diverse SARS-CoV-2 spike variants. Most participants had T helper type 1 (T(H)1)-skewed T cell immune responses with RBD-specific CD8(+)and CD4(+)T cell expansion. Interferon-gamma was produced by a large fraction of RBD-specific CD8(+)and CD4(+)T cells. The robust RBD-specific antibody, T cell and favourable cytokine responses induced by the BNT162b1 mRNA vaccine suggest that it has the potential to protect against COVID-19 through multiple beneficial mechanisms. LA - English DB - MTMT ER -