Intensity Ratio Nuclei Cytoplasm Tool - MontpellierRessourcesImagerie/imagej_macros_and_scripts GitHub Wiki

The tool calculates the ratio of the intensity in the nuclei and the cytoplasm. It needs two images as input: the cytoplasm channel and the nuclei channel. The nuclei channel is used to segment the nuclei. The measurements are made in the cytoplasm channel after the background intensity has been corrected.

Getting started

To install the tools, save the file Intensity_Ratio_Nuclei_Cytoplasm.ijm inti the macros/toolsets folder of your ImageJ installation.

Select the "Intensity_Ratio_Nuclei_Cytoplasm" toolset from the >> button of the ImageJ launcher.

toolset.png

  • the first button (the one with the image) opens this help page
  • the c-button runs the correct background method on the current image
  • the s-button measures the the intensity ratio for a single image (the second channel is loaded automatically)
  • the b-button runs the tool in batch mode on a given folder

Background correction

Open an image (cytoplasm channel) and press the c-button. The image will become black and after a moment the correction is done. Zero values will be displayed in blue. Everything displayed in grey will be counted as cytoplasm intensity later.

The operation will search the minimum value in the image and than take into account all pixels with intensities smaller than the minimum value in the image plus the offset. For all these pixels it will search the biggest value in the neighbourhood defined by the radius option. The biggest value found in one of those neighbourhoods will than be subtracted from the image.

Right click on the c-button to modify the options of the operation:

correct-background-options.png

  • radius - the radius of the neighbourhood in which the max. value near a minimum is searched.
  • offset - the maximum is searches around pixels with an intensity smaller than the global minimum plus the offset
  • iterations - the number of times the procedure is repeated
  • skip limit - the ratio of pixels with intensity zero in the image above which the operation is skipped to avoid subtracting from images for which the background is already zero

Intensity ratio for single image

Open an image and press the s-button. The corresponding second channel will be loaded and the intensity ratio between the intensity within the nuclei and the cytoplasm will be measured.

A right click on the s-button (or the b-button) opens the options-dialog:

intensity-ratio-options.png

  • nuclei channel - name of the staining for the nuclei channel (must be part of the filename)
  • cytoplasm channel - name of the staining of the cytoplasm channel (must be part of the filename and the rest of the filename must be the same as for the nuclei image).
  • max. % saturation - maximal percentage of saturated pixels allowed for the image to be taken into account
  • thresholding method - the thresholding method used to segment the nuclei
  • min. nucleus area - when selecting the nuclei, objects smaller than the min. area will not be taken into account
  • use Gaussian-blur filter on nuclei image - if selected a Gaussian-blur filter is applied to the nuclei image, before the nuclei are segmented
  • sigma of filter - the sigma of the Gaussian-blur filter
  • remove scale - if selected the spatial calibration of the image (if any) is removed, so that the area measurements are in pixel.

Intensity ratio batch

Click on the b-button. A file-dialog will be opened. Browse to the folder containing the input images and select it. The progress will be displayed in a log window. When the batch processing finished you can find a file "INTENSITY-RATIO.xls" containing the result measurements in the input folder. A subfolder containing the control images has been created in the input folder as well.

Results

results-table.png

The measured result values are:

  • image - the name of the image
  • icn factor - the factor between the cytoplasm and the nuclei intensity (%nuclei = %cytoplasm * icn)
  • % nuclei - percentage of the total intensity in the nuclei area
  • % cytoplasm - percentage of the total intensity in the cytoplasm area
  • av. nuclei intensity - the average intensity in the nuclei area
  • av. cytoplasm intensity - the average intensity in the cytoplasm area
  • nuclei area - the surface of the nuclei area (in pixel or in the scale set in the image)
  • cytoplasm area - the surface of the cytoplasm area (in pixel or in the scale set in the image)
  • t. nuclei intensity - the total intensity in the nuclei area (sum of all the intensity values)
  • t. cytoplasm intensity - the total intensity in the cytoplasm area (sum of all the intensity values)
  • folder - the folder from which the image was loaded

The control image shows the segmented nuclei and the cytoplasm area taken into account:

control-image.png

How to cite the tool

You can use the tool's resource id (see scicrunch.org):

(Intensity Ratio Nuclei Cytoplasm Tool, RRID:SCR_018573)

Publications using the tool

  1. Iwanski, J.B., Pappas, C.T., Mayfield, R.M., Farman, G.P., Ahrens-Nicklas, R., Churko, J.M., Gregorio, C.C., 2024. Leiomodin 2 neonatal dilated cardiomyopathy mutation results in altered actin gene signatures and cardiomyocyte dysfunction. npj Regen Med 9, 21. 10.1038/s41536-024-00366-y

  2. Marugán, C., Sanz‐Gómez, N., Ortigosa, B., Monfort‐Vengut, A., Bertinetti, C., Teijo, A., González, M., Alonso De La Vega, A., Lallena, M.J., Moreno‐Bueno, G., De Cárcer, G., 2024. TPX2 overexpression promotes sensitivity to dasatinib in breast cancer by activating YAP transcriptional signaling. Molecular Oncology 18, 1531–1551. 10.1002/1878-0261.13602

  3. Bougon, J., Kadijk, E., Gallot-Lavallee, L., Curtis, B.A., Landers, M., Archibald, J.M., Khaperskyy, D.A., 2024. Influenza A virus NS1 effector domain is required for PA-X-mediated host shutoff in infected cells. J Virol 98, e01901-23. 10.1128/jvi.01901-23

  4. Papadimitriou, L., Karagiannaki, A., Stratakis, E., and Ranella, A. (2024). Substrate topography affects PC12 cell differentiation through mechanotransduction mechanisms. Mechanobiology in Medicine 2, 100039. 10.1016/j.mbm.2024.100039.

  5. Prekovic, S., Chalkiadakis, T., Roest, M., Roden, D., Lutz, C., Schuurman, K., Opdam, M., Hoekman, L., Abbott, N., Tesselaar, T., et al. (2023). Luminal breast cancer identity is determined by loss of glucocorticoid receptor activity. EMBO Mol Med 15, e17737. 10.15252/emmm.202317737.

  6. Li, Y., Shah, R.B., Sarti, S., Belcher, A.L., Lee, B.J., Gorbatenko, A., Nemati, F., Yu, H., Stanley, Z., Rahman, M., et al. (2023). A noncanonical IRAK4-IRAK1 pathway counters DNA damage–induced apoptosis independently of TLR/IL-1R signaling. Sci. Signal. 16, eadh3449. 10.1126/scisignal.adh3449.

  7. Claude-Taupin, A., Isnard, P., Bagattin, A., Kuperwasser, N., Roccio, F., Ruscica, B., Goudin, N., Garfa-Traoré, M., Regnier, A., Turinsky, L., et al. (2023). The AMPK-Sirtuin 1-YAP axis is regulated by fluid flow intensity and controls autophagy flux in kidney epithelial cells. Nat Commun 14, 8056. 10.1038/s41467-023-43775-1.

  8. Mathai, C., Jourd’heuil, F., Pham, L.G.C., Gilliard, K., Howard, D., Balnis, J., Jaitovich, A., Chittur, S.V., Rilley, M., Peredo-Wende, R., et al. (2023). Regulation of DNA damage and transcriptional output in the vasculature through a cytoglobin-HMGB2 axis. Redox Biology 65, 102838. 10.1016/j.redox.2023.102838.

  9. Vélez, E.J., Schnebert, S., Goguet, M., Balbuena-Pecino, S., Dias, K., Beauclair, L., Fontagné-Dicharry, S., Véron, V., Depincé, A., Beaumatin, F., et al. (2023). Chaperone-mediated autophagy protects against hyperglycemic stress. Autophagy, 1–17. 10.1080/15548627.2023.2267415.

  10. Messelodi, D., Strocchi, S., Bertuccio, S.N., Baden, P., Indio, V., Giorgi, F.M., Taddia, A., Serravalle, S., Valente, S., Di Fonzo, A., et al. (2023). Neuronopathic Gaucher disease models reveal defects in cell growth promoted by Hippo pathway activation. Commun Biol 6, 431. 10.1038/s42003-023-04813-2.

  11. Mehak Passi (2023). CDK5 interacts with STK3- A consequence to the Hippo Signaling.

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  14. Mehak Passi, CDK5 interacts with STK3- A consequence to the Hippo Signaling, Ludwig-Maximilians-Universität, München, 2023.

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  25. Sacco, M.T., Bland, K.M., and Horner, S.M. (2022). WTAP Targets the METTL3 m 6 A-Methyltransferase Complex to Cytoplasmic Hepatitis C Virus RNA to Regulate Infection. J Virol 96, e00997-22. 10.1128/jvi.00997-22.

  26. Fort, L., Gama, V., and Macara, I.G. (2022). Stem cell conversion to the cardiac lineage requires nucleotide signalling from apoptosing cells. Nat Cell Biol 24, 434–447. 10.1038/s41556-022-00888-x.

  27. Kaur, N., Ruiz-Velasco, A., Raja, R., Howell, G., Miller, J.M., Abouleisa, R.R.E., Ou, Q., Mace, K., Hille, S.S., Frey, N., Binder, P., Smith, C.P., Fachim, H., Soran, H., Swanton, E., Mohamed, T.M.A., Müller, O.J., Wang, X., Chernoff, J., Cartwright, E.J., Liu, W., 2022. Paracrine signal emanating from stressed cardiomyocytes aggravates inflammatory microenvironment in diabetic cardiomyopathy. iScience 25, 103973. https://doi.org/10.1016/j.isci.2022.103973

  28. Kadiri, M., Charbonneau, M., Lalanne, C., Harper, K., Balg, F., Marotta, A., Dubois, C.M., 2021. 14-3-3η Promotes Invadosome Formation via the FOXO3–Snail Axis in Rheumatoid Arthritis Fibroblast-like Synoviocytes. IJMS 23, 123. https://doi.org/10.3390/ijms23010123

  29. Zhu, C., Kim, S.-J., Mooradian, A., Wang, F., Li, Z., Holohan, S., Collins, P.L., Wang, K., Guo, Z., Hoog, J., Ma, C.X., Oltz, E.M., Held, J.M., Shao, J., 2021. Cancer-associated exportin-6 upregulation inhibits the transcriptionally repressive and anticancer effects of nuclear profilin-1. Cell Reports 34, 108749. 10.1016/j.celrep.2021.108749

  30. Hsu, C. G., Fazal, F., Rahman, A., Berk, B. C. & Yan, C. Phosphodiesterase 10A Is a Key Mediator of Lung Inflammation. J.I. 206, 3010–3020 (2021).

  31. Payapilly, A. et al. TIAM1-RAC1 promote small-cell lung cancer cell survival through antagonizing Nur77-induced BCL2 conformational change. Cell Reports 37, 109979 (2021).

  32. Ramic, M. et al. Epigenetic Small Molecules Rescue Nucleocytoplasmic Transport and DNA Damage Phenotypes in C9ORF72 ALS/FTD. Brain Sciences 11, 1543 (2021).

  33. Pablos, I. et al. Mechanistic insights into COVID-19 by global analysis of the SARS-CoV-2 3CLpro substrate degradome. Cell Reports 37, 109892 (2021).

  34. Gendrisch, F., Haarhaus, B., Schempp, C. M. & Wölfle, U. Anti-Psoriatic Effects of Antimony Compounds In Vitro. Molecules 26, 5814 (2021).

  35. Daria Messelodi (2021). Study of pathway alterations in Gaucher disease by induced pluripotent stem cell models.

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  38. Chandrasekaran, A. et al. (2021) Neural Derivates of Canine Induced Pluripotent Stem Cells-Like Cells From a Mild Cognitive Impairment Dog, Frontiers in Veterinary Science, 8, p. 725386. doi:10.3389/fvets.2021.725386.

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  41. Tan, Y., and Song, J. (2021). Independent and Synergistic Modulations of Viscoelasticity and Stiffness of Dynamically Cross-Linked Cell-Encapsulating ClickGels by Covalently Tethered Polymer Brushes. Biomacromolecules 22, 3408–3415.

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