13 research outputs found

    NGS compatible streamlined DNA recovery from 3D cell cultures in GrowDex®

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    Here, we describe a streamlined workflow for constructing an NGS whole exome sequencing (WES) from a low amount of PDCs grown as spheroids in GrowDex.Non peer reviewe

    T Cell Epitopes in Coxsackievirus B4 Structural Proteins Concentrate in Regions Conserved between Enteroviruses

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    AbstractThe present study aimed to characterize systematically the target epitopes of T cell responses in CBV4 structural proteins. These were studied by synthesizing 86 overlapping 20-aa-long peptides covering the known sequence of CBV4 structural proteins and analyzing the proliferation responses of 18 CBV4-specific T cell lines against these peptides. Recognized peptides differed depending on the HLA-DR genotype of the T cell donor. They were concentrated to the VP4 and VP2 regions as six of seven common peptide epitopes located in this region, whereas there was only one in the VP3 region and none in the VP1 region. Peptides from conserved areas were recognized more often (on average, 15% of them stimulated each T cell line) than those derived from variable areas (3%) (P < 0.0001, Fisher's exact test). Some conserved peptides inducing T cell responsiveness in most subjects were identified, a knowledge which can be useful in the development of new synthetic vaccines

    Enzymatic Synthesis of the C-glycosidic Moiety of Nogalamycin R

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    Carbohydrate moieties are essential for the biological activity of anthracycline anticancer agents such as nogalamycin, which contains l-nogalose and l-nogalamine units. The former of these is attached through a canonical O-glycosidic linkage, but the latter is connected via an unusual dual linkage composed of C–C and O-glycosidic bonds. In this work, we have utilized enzyme immobilization techniques and synthesized l-rhodosamine-thymidine diphosphate (TDP) from α-d-glucose-1-TDP using seven enzymes. In a second step, we assembled the dual linkage system by attaching the aminosugar to an anthracycline aglycone acceptor using the glycosyl transferase SnogD and the α-ketoglutarate dependent oxygenase SnoK. Furthermore, our work indicates that the auxiliary P450-type protein SnogN facilitating glycosylation is surprisingly associated with attachment of the neutral sugar l-nogalose rather than the aminosugar l-nogalamine in nogalamycin biosynthesis.</p

    Image-based and machine learning-guided multiplexed serology test for SARS-CoV-2

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    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 measurement 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 coronavirus 2 (SARS-CoV-2) as the model pathogen, we demonstrate that this method allows differentiation between 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

    Image-based and machine learning-guided multiplexed serology test for SARS-CoV-2

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    Funding Information: The authors thank the Minerva Institute (Helsinki, Finland) for providing utilities for the project, Prof. Perttu Hämäläinen (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-SpheroidPicker , 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-JÖVŐ-2021-00010 and TKP2020-NKA-17 ). The authors thank Dora Bokor, PharmD, for proofreading the manuscript.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 measurement 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 coronavirus 2 (SARS-CoV-2) as the model pathogen, we demonstrate that this method allows differentiation between 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.Peer reviewe
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