Abstract

Histological alterations often constitute a fingerprint of toxicity and diseases. The extent to which these alterations are cause or consequence of compromised organ function, and the underlying mechanisms involved is a matter of intensive research. In particular, liver disease is often associated with altered tissue microarchitecture, which in turn may compromise perfusion and functionality. Research in this field requires the development and orchestration of new techniques into standardized processing pipelines that can be used to reproducibly quantify tissue architecture. Major bottlenecks include the lack of robust staining, and adequate reconstruction and quantification techniques. To bridge this gap, we established protocols employing specific antibody combinations for immunostaining, confocal imaging, three-dimensional reconstruction of approximately 100-μm-thick tissue blocks and quantification of key architectural features. We describe a standard procedure termed ‘liver architectural staining’ for the simultaneous visualization of bile canaliculi, sinusoidal endothelial cells, glutamine synthetase (GS) for the identification of central veins, and DAPI as a nuclear marker. Additionally, we present a second standard procedure entitled ‘S-phase staining’, where S-phase-positive and S-phase-negative nuclei (stained with BrdU and DAPI, respectively), sinusoidal endothelial cells and GS are stained. The techniques include three-dimensional reconstruction of the sinusoidal and bile canalicular networks from the same tissue block, and robust capture of position, size and shape of individual hepatocytes, as well as entire lobules from the same tissue specimen. In addition to the protocols, we have also established image analysis software that allows relational and hierarchical quantifications of different liver substructures (e.g. cells and vascular branches) and events (e.g. cell proliferation and death). Typical results acquired for routinely quantified parameters in adult mice (C57Bl6/N) include the hepatocyte volume (5,128.3 ± 837.8 μm3) and the fraction of the hepatocyte surface in contact with the neighbouring hepatocytes (67.4 ± 6.7 %), sinusoids (22.1 ± 4.8 %) and bile canaliculi (9.9 ± 3.8 %). Parameters of the sinusoidal network that we also routinely quantify include the radius of the sinusoids (4.8 ± 2.25 μm), the branching angle (32.5 ± 11.2°), the length of intersection branches (23.93 ± 5.9 μm), the number of intersection nodes per mm3 (120.3 × 103 ± 42.1 × 103), the average length of sinusoidal vessel per mm3 (5.4 × 103 ± 1.4 × 103mm) and the percentage of vessel volume in relation to the whole liver volume (15.3 ± 3.9) (mean ± standard deviation). Moreover, the provided parameters of the bile canalicular network are: length of the first-order branches (7.5 ± 0.6 μm), length of the second-order branches (10.9 ± 1.8 μm), length of the dead-end branches (5.9 ± 0.7 μm), the number of intersection nodes per mm3 (819.1 × 103 ± 180.7 × 103), the number of dead-end branches per mm3 (409.9 × 103 ± 95.6 × 103), the length of the bile canalicular network per mm3 (9.4 × 103 ± 0.7 × 103 mm) and the percentage of the bile canalicular volume with respect to the total liver volume (3.4 ± 0.005). A particular strength of our technique is that quantitative parameters of hepatocytes and bile canalicular as well as sinusoidal networks can be extracted from the same tissue block. Reconstructions and quantifications performed as described in the current protocols can be used for quantitative mathematical modelling of the underlying mechanisms. Furthermore, protocols are presented for both human and pig livers. The technique is also applicable for both vibratome blocks and conventional paraffin slices.Electronic supplementary materialThe online version of this article (doi:10.1007/s00204-014-1243-5) contains supplementary material, which is available to authorized users.

Highlights

  • Current studies in both cell biology and hepatology largely rely on imaging and image analysis of 2D pictures

  • We describe a standard procedure termed ‘liver architectural staining’ for the simultaneous visualization of bile canaliculi, sinusoidal endothelial cells, glutamine synthetase (GS) for the identification of central veins, and DAPI as a nuclear marker

  • In order to visualize all structures in the same tissue, we present an optimized antibody combination—anti-DPPIV/ CD26, anti-GS and secondary donkey anti-mouse IgG (DMs) antibodies

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Summary

Introduction

Current studies in both cell biology and hepatology largely rely on imaging and image analysis of 2D pictures. The architectural staining protocol generates a yellow fluorescence signal for the sinusoidal endothelial cells (Fig. 5a, right panel, merge + DAPI) This signal reflects the merged green signal of DPPIV/CD26 and the red signal from the binding of the donkey anti-mouse IgG (DMs) antibody to the sinusoids. Architectural staining of the CCl4-damaged liver tissue results in a red fluorescent signal at the pericentral dead cell area (Fig. 5c, ii, iii), caused by the binding of the anti-DMs antibody to necrotic hepatocytes. The anti-human DPPIV/CD26 antibody from goat exclusively stains bile canaliculi in liver tissue of humans and pigs, but not sinusoidal endothelial cells (Fig. 8, upper left panel). Wash tissue sections three times for 10 min each in reagent A at room temperature

Antigen de-masking
Primary antibodies
Counterstaining
Secondary antibodies
HCl digestion
First Primary antibody
11. Second primary antibody
13. Second secondary antibodies
First secondary antibody
15. Counterstaining
Unmask the antigen of interest using an acid and heat treatment as follows
Procedure
Validate this for both network types using the following parameters
Findings
Geometric pruning filter
Full Text
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