Kidney Week

Abstract: FR-PO944

High-Throughput Analysis of Single Cells in Immunofluorescent Kidney Sections

Session Information

• Development, Stem Cells, Regenerative Medicine - II
  October 26, 2018 | Location: Exhibit Hall, San Diego Convention Center
  Abstract Time: 10:00 AM - 12:00 PM

Category: Development, Stem Cells, and Regenerative Medicine

• 501 Development, Stem Cells, and Regenerative Medicine: Basic

Authors

• Hugo, Christian, University of Dresden, Dresden, Germany, Dresden, SN, Germany

Christian Hugo,

• Kessel, Friederike, Unilkinikum Dresden, Dresden, Germany

Friederike Kessel,

• Gerlach, Michael, Division of Nephrology, Medical Clinic III, Universital Hospital Carl Gustav Carus Dresden, Dresden, Germany

Michael Gerlach,

• Steglich, Anne, Universitätsklinikum Carl Gustav Carus, Dresden, Germany

Anne Steglich,

• Tschongov, Todor, Uniklinikum Dresden, Dresden, Germany

Todor Tschongov,

• Gembardt, Florian, Universitätsklinikum Carl Gustav Carus, Dresden, Germany

Florian Gembardt,

• Ruhnke, Leo, Div of Nephrology, Dept of Internal Medicine III, Univ Hospital CGC, Dresden, Germany, Dresden, Germany

Leo Ruhnke,

• Todorov, Vladimir T., Dresden University of Technology, Dresden, Germany

Vladimir T. Todorov,

Background

Immunofluorescence staining is a standard method for analyzing histological, physiological and pathophysiological markers in a variety of cell types and compartments of kidney tissue. However the final quantification of image data is still often performed by manual counting, a time consuming and potentially biased process.

Methods

With the open source software Fiji and R we are able to automatically analyze a variety of markers in complete kidney sections. Following the automatic acquisition of high-resolution sections our batch-processing is able to classify and detect up to 100.000 nuclei per kidney section by marker-controlled watershed with a systematic error rate below 5%. This approach largely eliminates personal bias, reduces analysis time and enables semiautomatic tissue compartmentation for stereometric analysis. By thresholding and segmentation of additional channels cells can be classified as marker-positive. Parallel documentation and a database creation with nuclear characteristics, spatial parameters and marker-positivity enable complete reproducibility and verification of the results in the original image.

Results

We used our approach to quantify renin-abundancy in a previously described triple-transgenic mouse with an inducible Gs alpha knockout (Lachman et al., 2017, JASN). This evaluation correlated to the counting of renin-producing cells by kidney FACS (p<0.001, Pearson). Furthermore we successfully quantified proliferation (PCNA) and apoptosis (TUNEL)-staining in a mouse model of serum induced kidney damage with our analysis algorithms. We could also asses the differential activation of TGF-beta signaling pathway in kidney compartments in an animal model of STZ-induced diabetic nephropathy by quantifying nuclear pSMAD.

Conclusion

Our novel quantification approach is easily implementable, versatile and generates high amounts of data. The systematic nature of methodic errors combined with high cell count in complete sections and the absence of personal bias results in advantages towards manual quantification. While the high number of nuclei assessed per sample is comparable to FACS, our approach requires less tissue, avoids artifacts related to organ disintegration and provides a spatial resolution of the data sets.

Funding

• Government Support - Non-U.S.