Data from: Live imaging of SARS-CoV-2 infected airway epithelium cultures
Data files
Oct 07, 2024 version files 257.75 GB
Abstract
SARS-CoV-2 infects the conducting airways, where mucociliary clearance inhibits pathogen penetrance. Mucociliary clearance is a dynamic system, and both the host and the pathogen can influence it. To better understand how SARS-CoV-2 changes MCC, we performed live imaging of infected differentiated primary human bronchial epithelium cultures over multiple days. We used a fluorescent reporter virus and fluorescent markers for tubulin and apoptotic cells to understand changes in the culture in both infected and bystander cells. In whole culture movies, we saw that SARS-CoV-2 infection foci traced the motion of mucus, suggesting that mucociliary clearance shapes the spread of the virus. We then monitored how mucociliary clearance changed during infection. We found that SARS-CoV-2 infection induced defects in ciliary motion in both infected and bystander cells, taking ~4 days for the infected cells to become numerous and old enough to impact culture-wide ciliary motion.
README: Data from: Live imaging of SARS-CoV-2 infected airway epithelium cultures
This dataset consists of live microscopy data of SARS-CoV-2 infected primary human bronchial epithelium cultures. We wanted to understand how SARS-CoV-2 spreads in the airway, so we infected these cultures with a fluorescent reporter virus and then imaged the entire culture surface for some days. We also used fluorescent dyes to monitor parameters for culture health. In this repository, we share data relating to how the virus changes ciliary motion over time. We find that changes in infected cell ciliary motion take a few days to become noticeable and that it takes 4 days for culturewide changes in ciliary motion to be significant.
Any questions should be directed to the corresponding author: Thomas Hope, thope@northwestern.edu.
Description of the data and file structure
Data are organized by file type. The bullet points below mirror the file structure.
- keys: .csv files containing information linking files to experimental info.
- 'exptlog_iii.csv' contains details of every live-imaged culture. Each row is one culture.
- 'filename' = name of .tif file containing stitched, concatenated, and registered movie
- 'csv' = name of .csv file containing trackmate data from the .tif file
- 'expt.name' = name of the experiment as recorded in each .tif file
- 'date' = date of experiment (start of infection)
- 'usable' = whether the culture is valid for use in analysis. see 'notes' for details.
- 'sample.no' = # of each culture. This is in each .tif and .csv.
- 'donor' = donor id #
- 'virus' = which virus/whether the culture was infected
- 'dyes' = which dye combination the culture received
- 'condition' = any experiment-specific factor.
- 'notes' = notes on culture appearance, experimental procedure, etc.
- 'jammed' = whether the culture exhibited cell migration, and if so to what extent. Assessed by eye.
- 'crypts' = whether the culture exhibited crypts, and if so what kind. Assessed by eye.
- 'cyst' = whether the culture exhibited cysts, and if so what kind. Assessed by eye.
- 'infxn.in.crypt' = whether there were foci in crypts.
- 'mucus.simple' = mucus motion type, simplified into rotary/disorganized/static.
- 'mucus.mvmt.type' = mucus motion type, more complex (ex. rotary.many = multiple spinning mucus discs)
- 'mucus.stop.frame' = what frame the mucus last moved on (ex. if mucus.stop.frame = 60, there was a change from 59-60 and no change from 60-61)
- 'video.end.frame' = last frame of video
- 'mucus.stop.frame.end' = was the mucus.stop.frame the same as the last frame of the video?
- 'focus.type' = dominant focus morphology within the culture (detailed)
- 'focus.num' = Number code for the dominant focus morphology within the culture (detailed)
- 'focus.simple' = Dominant focus morphology, simplified to mock/plaque/comet/diffuse. The major categorization used in the manuscript.
- '20hpi.spots' = # of cell-sized GFP foci evident at 20 hours post-infection.
- '48hpi.focicount' = The number of distinct foci evident at 48 hours post-infection. A fuzzy metric, as at this timepoint foci often blur together.
- 'n.mm.2a', 'n.mm.2b', 'n.mm.2mean' = # of N RNA copies per mm^2 culture area. 'a' and 'b' are technical duplicates, 'mean' is the mean of the technical duplicates.
- 'fromold' = was this culture infected in the old bsl3 facility or the new one (the bsl3 core)?
- 'piv.*': particle image velocitometry data based on the farthest red channel of the .tif. this is only informative when that channel is SPY650-tubulin; otherwise, it reflects mucus motion which is typically much faster than the framerate of whole culture videos can capture.
- 'piv.total' = # of particle image velocitometry sectors, total.
- 'piv.fxn.3', 'piv.fxn.6', etc. = # of particle image velocitometry sectors with speed above N microns/hour (N = 3, 6, 12, 24, 48).
- 'piv.mean.speed' = mean speed of particle image velocitometry data.
- 'piv.median.speed' = medianspeed of particle image velocitometry data.
- 'maxgfp0', 'maxgfp850', etc. = # of pixels with GFP intensities above N (N = 0, 850, 900, 1000, 1100) at the frame with the highest value for each threshold.
- 'frame.maxgfp0', 'frame.maxgfp850', etc. = The frame with the highest # of pixels with GFP intensities above N (N = 0, 850, 900, 1000, 1100) for each threshold.
- 't0spy0', 't0spy350', etc. = # of pixels in the farthest red channel with signal intensity above N (N = 0, 350, 400, 500) at a given frame t (t = 0 or 20).
- na = not applicable (i.e. the given column is not informative or meaningful for a culture)
- nd = not determined (i.e. file was available but a given metric was not measured)
- undetermined = qpcr was run & no target detected, for 'n.mm.*' columns
- none = no notes taken, for 'notes' column
- -- = script failed to quantify, for 'piv.*' columns.
- ciliakeys contains .csv files necessary for telling which culture and timepoint each ciliary beat frequency video corresponds to. These files are used in the Python code to concatenate summarized ciliary beat frequency data for analysis.
- *timepoints.csv files: Each row is one timepoint.
- 'timepoints' column = number code corresponding to each timepoint in raw data files, 'hpi' column = hours post-infection each number code corresponds to
- *pts.csv files: Each row is one consecutive run of imaging ciliary beat frequency videos/reference images for a single culture on the microscope. For this imaging, additional points were appended at successive time points; thus, there may be more than one row for each culture.
- 'culturepoint' = which individual culture, 'vidpoint.start' = number corresponding to the first beat frequency movie point for a given culture, 'vidpoint.end' = number corresponding to the last beat frequency movie point for a given culture, 'donor' = donor for that culture, 'condition' = experimental condition for that culture, 'experiment' = which experiment that culture was a part of.
- multitest_unprocessed: Unprocessed reference images and ciliary beat frequency movies plus denoised ciliary beat frequency movies from a single experiment. The unprocessed images themselves are in .dv format; logs containing info about imaging conditions are .dv.log. Denoised movies are .tif. Owing to the prohibitively large size of the full dataset, only one experiment is provided.
- cbf_bulk is concatenated data from each pixel of each ciliary beat frequency movie, with data from reference images appended in additional columns where applicable. Each .csv is from one experiment.
- cbf_vis contains .tifs for each ciliary beat frequency movie, with channels ordered like so: power, beat frequency (Hz), sum spy650 tubulin signal across the ciliary beat frequency movie, max intensity projection of spy650-tubulin signal in the reference image, max intensity projection of NucView 530 signal in the reference image, max intensity projection of GFP signal in the reference image, and max intensity projection of brightfield signal in the reference image. Files are grouped in folders by experiment.
- trackmate_spotdetection contains trackmate spot detection files (.csv format) for whole culture movies.
- d7d8 contains processed whole culture movies for the experiment where cultures were rinsed at 120 hours post-infection.
Code/Software
Code used for data processing and smaller summary data is available on GitHub (see Related Works for the link).
Methods
Live imaging of inverted ALI cultures was performed on a DeltaVision Elite microscope outfitted with a stagetop incubator. For movies of entire cultures, imaging was done in a 5x5 panel of 1024 x 1024 FOVs across 4 Z planes spanning 80 um with a 4x air lens (Olympus UPLXAPO4X), with panels acquired every 2 hours. For ciliary motion movies, 256x256 pixel FOVs were acquired with a 10x air lens at 125 frames per second. Centered on the smaller FOV of each ciliary motion movie, 1024 x 1024 reference images of all channels spanning approximately 20 microns of Z were also acquired with the same 10x lens. Channels include SPY650-Tubulin (far red), NucView 530 (orange), GFP (green), and white light. Details of each experiment are provided in the accompanying .csv.
Ciliary motion movies were denoised using cellpose 3 cytoplasm denoising model. Ciliary beat frequency was calculated using scipy.signal.periodogram on ciliary motion movies. Whole culture movies were stitched in ImageJ using the Grid/Collection stitching plugin (doi: 10.1093/bioinformatics/btp184), Z projected and concatenated across multiple days of imaging, registered using the Linear Stack Alignment with SIFT Multichannel, and cropped to remove areas outside the culture. The code used for these tasks is provided in the GitHub repository accompanying the manuscript (link in Related Works).