Measuring Single-Cell Aging with an Imaging-based Biomarker of Chromatin and Epigenetic Aging

We developed imaging-based chromatin and epigenetic age image, a novel technique designed to quantify aging and rejuvenation at single cell resolution. DNA methylation clocks estimate biological age, but depend on linear regression, need large cohorts, and destroy samples, making them costly and unsuitable for large-scale or longitudinal studies. To begin, transfer the frozen organs and tissues to a pre-chilled mortar placed over dry ice.

Pour liquid nitrogen over the frozen tissue and grind it thoroughly using a pre-chilled pestle until a uniformly-fine powder is obtained. Using a pre-chilled metal spatula, aliquot the ground tissue into multiple tubes. After extracting the nuclei, mix them with trypan blue in an equal ratio in a separate tube.

Transfer 10 microliters of the mixture to a hemocytometer, or load it into an automated cell counter. Enter and verify all metadata, including sample IDs, conditions, and biomarkers in the plate map and export a CSV file. Now, dispense 10, 000 nuclei per well in a 20 to 30 microliter volume into a 384 well plate.

Centrifuge the plate at 1000g, with acceleration setting nine and deceleration setting four, for 10 minutes at four degrees Celsius. Next, fix the nuclei by adding an equal volume of 8%paraformaldehyde and PBS, and incubate for 10 minutes at room temperature. After removing the fixative, add 30 microliters of 0.1 molar glycine in PBS and incubate for five minutes at room temperature.

Remove the glycine solution and wash the wells twice with 100 microliters of PBS. Remove the PBS from each well and add 30 microliters of blocking solution containing 2%BSA and 0.5%Triton X-100 in PBS. Incubate the plate for one hour at room temperature.

After removing the blocking solution, incubate the sample with 25 microliters of primary antibody solution at four degrees Celsius. Next, wash the wells three times with 100 microliters of PBS, each wash lasting three minutes at room temperature. Add 25 microliters of secondary antibody solution and incubate for two hours at four degrees Celsius.

Then, wash the wells three times with 100 microliters of PBS, each wash lasting three minutes at room temperature. Stain the nuclei with DAPI or Hoechst by adding 30 microliters of the dye at a concentration of 0.01 milligram per milliliter, and wash the plate once with 100 microliters of PBS to remove excess dye. Download the workflow scripts from the GitHub repository.

Once the download is complete, unzip the file to extract its contents. Organize the cloned image repository so that the folder structure matches the format assumed by the workflow for correct script execution. Then, open the Terminal application if operating on Linux or Mac OS, or the WSL application if using Windows.

Change the working directory to the cloned repository folder by typing the required command in the terminal and pressing Enter. Create a new computational environment named Image_workflow using Conda with Python version 3.10 and press Enter. Activate the newly-created Conda environment with the command conda activate Image_workflow.

Install Poetry, a Python package manager, within the activated environment using the PIP installer. Then, install all prerequisite Python packages required for the workflow using Poetry. Now, configure CUDA within the Conda environment to enable graphics processing unit functionality during the segmentation step.

Open the Terminal application and change the folder to the cloned. Activate the Conda environment by typing the command below and pressing Enter. Open the workflow main file in a code or text editor such as VS Code or Notepad to configure the analysis parameters.

Set the project name by assigning the variable p to a short file system safe identifier used to organize outputs. Set the list of channels for feature extraction in chs, including the segmentation channel if features from that channel are required. Using ImageIndex and the channel label as the key, map the image channel identifier from file names to the exact case-sensitive plate map column header saved earlier.

Then, set data locations by assigning orgDataLoadPath to the dataset route, orgDataSubfolder to the image subfolder if needed, and resultsSavePath to the output route. Confirm the file name extension in imageFileFormat. Then, edit imageFileRegEx to use Python-named capturing groups for the required parts, including row, column, field, Z position, and channel.

Now, set the segmentation channel in segmentation_ch to the nuclear channel used for object detection. Decide whether to use illumination correction by setting a illumiCorrection and set to true to compute and apply basic models. Then, set the physical voxel size in micrometers in voxel_dim as ZYX using microscope metadata.

Save the file and close the editor after verifying each parameter. Finally, run the workflow script to obtain image readouts and perform validation, keeping the terminal open while the script is running. Visualize results and export raw image readouts for additional analysis in external software.

Representative images of induced pluripotent stem cells showed clearly-separated nuclei stained with DAPI, trimethylated histone H3 at lysine 27, and acetylated histone H3 at lysine 27. Image analysis of liver and skeletal muscles revealed a significant difference between young and old samples, with old OSKM mice showing reduced image compared to old, indicating partial reprogramming. Analysis of individual animals indicated that some old OSKM samples displayed significantly-reduced image values compared to old mice.

This protocol enables researchers to investigate age-associated changes in chromatin and epigenetic organization at a single cell resolution across different cell types and different tissues. Our imaging-based method is non-destructive, it preserves chromatin structure, and allows for repeated measurements, and is more cost-effective in large-scale or longitudinal studies. Future research will focus on adding more epigenetic markers and studying aging-related, intranuclear structures.