Microscopy deep learning predicts virus infections and reveals mechanics of lytic-infected cells

نویسندگان

چکیده

•Artificial intelligence identifies HSV- and AdV-infected cells without specific probes.•Imaging lytic-infected reveals nuclear envelope rupture AdV dissemination.•Live cell imaging neural networks presciently pinpoint cells.•Lytic-infected nuclei have mechanical properties distinct from non-lytic nuclei. Imaging across scales disease mechanisms in organisms, tissues, cells. Yet, particular infection phenotypes, such as virus-induced lysis, remained difficult to study. Here, we developed modalities deep learning procedures identify herpesvirus adenovirus (AdV) infected virus-specific stainings. Fluorescence microscopy of vital DNA-dyes live-cell revealed learnable patterns transferable related viruses the same family. Deep predicted two major outcomes, (nonspreading) lytic (spreading) infections, up about 20 hr prior lysis. Using these predictive algorithms, had levels green fluorescent protein (GFP)-tagged virion proteins but enriched faster, collapsed more extensively upon laser-rupture than nuclei, revealing impaired Our algorithms may be used infer phenotypes emerging viruses, enhance single biology, facilitate differential diagnosis infections. Virus infections give rise a wide range with complex biology. Depending on virus, can lead cycle growth enhancement or arrest, swelling shrinkage, membrane blebbing contraction, organelle alterations, collapse secretory pathway, mitochondrial aggregation condensation, increasingly studied virus resolution (Belov, 2016Belov G.A. Dynamic lipid landscape picornavirus replication organelles.Curr. Opin. Virol. 2016; 19: 1-6Crossref PubMed Scopus (18) Google Scholar; den Boon et al., 2010den J.A. Diaz A. Ahlquist P. Cytoplasmic viral complexes.Cell Host Microbe. 2010; 8: 77-85Abstract Full Text PDF (237) Roulin 2014Roulin P.S. Lotzerich M. Torta F. 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Machine biology teaching computers recognize phenotypes.J. 126: 5529-5539Crossref work here provides resource analyzing challenging topic owing rapid terminal nature death. To explore power content implemented pipeline scoring morphology mode DNA-dye (Figures 1A 1B ). noticed Hoechst-stained appeared uninfected presence throughout multi-round cycles did affect plaques (Figure S1A). wild-type AdV-C2 immuno-staining, GFP-expressing replication-competent AdV-C2-dE3B-GFP, AdV-C2-dE3B-dADP, AdV-C2-V-GFP, HSV-1-VP16-GFP, C12 (Crameri 2018Crameri Bauer Caduff Walker Steiner Franzoso F.D. Gujer Kucera Zbinden al.MxB interferon-induced restriction factor herpesviruses.Nat. Commun. 1980Crossref (47) Glauser 2010Glauser D.L. Seyffert Strasser Franchini Laimbacher Dresch Vogel Buning Salvetti al.Inhibition type adeno-associated rep depends combined ATPase/helicase activities.J. 84: 3808-3824Crossref (15) 2008bYamauchi Kubota Usukura UL14 tegument efficient alpha transinducing VP16 capsids.J. 82: 1094-1106Crossref (29) For AdV, acquired 72 post (pi), 48 pi, reflecting kinetics were computationally segmented individually annotated according signal, processed obtain individual S1B). procedure generated 2000 per condition. dataset using modified cutting-edge ResNet-50 Scholar) named ViResNet. classifiers, one S1C). accommodate resized 224 x pixels, adapted classes, additional hidden untrained initialized ImageNet weights. accuracies 95% 94% considerably higher k-nearest neighbors (k-NN), support vector (SVM), decision tree all test (Table 1). classifiers precision values 0.94 recall 0.92, respectively, much those determined namely 0.6 0.58 average HSV-1, receiver operating characteristic (ROC) curves k-NN, SVM, Figure S1D. 2-class then assess status population level. allows visualization quantification enables assessment plaque 1B). challenge performed AdV-C5-IX-FS2A-GFP, serotype accuracy 93% S1E).Table 1Accuracy, precision, performance detecting AdV-C2- HSV-1-infected compared methodsAccuracy=TP+TNTP+TN+FP+FNPrecision=TPTP+FPRecall=TPTP+FNAdV-C2:ViResNet0.950.940.92k-NN0.640.620.61SVM0.630.630.58Decision tree0.640.620.59HSV-1:ViResNet0.940.920.93k-NN0.640.610.56SVM0.610.580.59Decision tree0.650.620.61TP, TN, FP, FN denote true positives, negatives, false negatives predictions correspondingly. Open table tab TP, sum, accurately identified plaquing populations, outperformed methods. Notably, identification possible absence staining, previously possible. next employed analyze AdV-C2-GFP-V. incorporates 40 GFP-V fusion particle, could purified tracked (Puntener Infection HeLa stably expressing histone H2B-mCherry AdV-C2-GFP-V multiplicity (MOI) 0.2 showed newly synthesized accumulated 30 pi 2A, Video S1). At 39 localization changed, indicated increased diffuse cytosol, followed appearance clusters cytoplasm. largely devoid H2B-mCherry, consistent notion made particles, histones (Ostapchuk 2017Ostapchuk Zheng Hearing VII dispensable assembly essential infection.PLoS Pathog. 13: e1006455Crossref (24) After clusters, cytoplasm progressively lost GFP-V, also albeit extents, indicative cellular least partial disintegration 2A 2B, Videos S1 S2). 5.5% until 45 2C). confirmed EM 35 clustered particles 2D). Together show induced comprising several hundred extracellular medium. Towards harnessing assessing quantifying spreading efficiency high-throughput MOI 4 days. Monolayers A549 AdV-C2-GFP-V, AdV-C2-dE3B-GFP-dADP AdV-C2-dE3B-GFP lacks E3B region encoding internalization degradation RID? RID?, 14.7K, involved protecting premature tumor necrosis (Gooding 1988Gooding L.R. Elmore L.W. Tollefson A.E. Brady Wold W.S. 14,700 MW E3 cytolysis

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ژورنال

عنوان ژورنال: iScience

سال: 2021

ISSN: ['2589-0042']

DOI: https://doi.org/10.1016/j.isci.2021.102543