ArticleCellular & molecular biology letters2024
Monitoring correlates of SARS-CoV-2 infection in cell culture using a two-photon-active calcium-sensitive dye.
Article in Cellular & molecular biology letters, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
17 authors.
Funding
Abstract
backgroundThe organism-wide effects of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral infection are well studied, but little is known about the dynamics of how the infection spreads in time among or within cells due to the scarcity of suitable high-resolution experimental systems. It has been reported that SARS-CoV-2 infection pathways converge at calcium influx and subcellular calcium distribution changes. Imaging combined with a proper staining technique is an effective tool for studying subcellular calcium-related infection and replication mechanisms at such resolutions.
methodsUsing two-photon (2P) fluorescence imaging with our novel Ca-selective dye, automated image analysis and clustering analysis were applied to reveal titer and variant effects on SARS-CoV-2-infected Vero E6 cells.
resultsThe application of a new calcium sensor molecule is shown, combined with a high-end 2P technique for imaging and identifying the patterns associated with cellular infection damage within cells. Vero E6 cells infected with SARS-CoV-2 variants, D614G or B.1.1.7, exhibit elevated cytosolic calcium levels, allowing infection monitoring by tracking the cellular changes in calcium level by the internalized calcium sensor. The imaging provides valuable information on how the level and intracellular distribution of calcium are perturbed during the infection. Moreover, two-photon calcium sensing allowed the distinction of infections by two studied viral variants via cluster analysis of the image parameters. This approach will facilitate the study of cellular correlates of infection and their quantification depending on viral variants and viral load.
conclusionsWe propose a new two-photon microscopy-based method combined with a cell-internalized sensor to quantify the level of SARS-CoV-2 infection. We optimized the applied dye concentrations to not interfere with viral fusion and viral replication events. The presented method ensured the proper monitoring of viral infection, replication, and cell fate. It also enabled distinguishing intracellular details of cell damage, such as vacuole and apoptotic body formation. Using clustering analysis, 2P microscopy calcium fluorescence images were suitable to distinguish two different viral variants in cell cultures. Cellular harm levels read out by calcium imaging were quantitatively related to the initial viral multiplicity of infection numbers. Thus, 2P quantitative calcium imaging might be used as a correlate of infection or a correlate of activity in cellular antiviral studies.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.