A prerequisite for the systems biology analysis of tissues is an accurate digital three-dimensional reconstruction of tissue structure based on images of markers covering multiple scales. Here, we designed a flexible pipeline for the multi-scale reconstruction and quantitative morphological analysis of tissue architecture from microscopy images. Our pipeline includes newly developed algorithms that address specific challenges of thick dense tissue reconstruction. Our implementation allows for a flexible workflow, scalable to high-throughput analysis and applicable to various mammalian tissues. We applied it to the analysis of liver tissue and extracted quantitative parameters of sinusoids, bile canaliculi and cell shapes, recognizing different liver cell types with high accuracy. Using our platform, we uncovered an unexpected zonation pattern of hepatocytes with different size, nuclei and DNA content, thus revealing new features of liver tissue organization. The pipeline also proved effective to analyse lung and kidney tissue, demonstrating its generality and robustness.DOI: http://dx.doi.org/10.7554/eLife.11214.001

Selective inhibition of exclusively transcription‐regulating PTEFb/CDK9 is a promising new approach in cancer therapy. Starting from lead compound BAY‐958, lead optimization efforts strictly focusing on kinase selectivity, physicochemical and DMPK properties finally led to the identification of the orally available clinical candidate atuveciclib (BAY 1143572). Structurally characterized by an unusual benzyl sulfoximine group, BAY 1143572 exhibited the best overall profile in vitro and in vivo, including high efficacy and good tolerability in xenograft models in mice and rats. BAY 1143572 is the first potent and highly selective PTEFb/CDK9 inhibitor to enter clinical trials for the treatment of cancer.

Bile, the central metabolic product of the liver, is transported by the bile canaliculi network. The impairment of bile flow in cholestatic liver diseases has urged a demand for insights into its regulation. Here, we developed a predictive 3D multi-scale model that simulates fluid dynamic properties successively from the subcellular to the tissue level. The model integrates the structure of the bile canalicular network in the mouse liver lobule, as determined by high-resolution confocal and serial block-face scanning electron microscopy, with measurements of bile transport by intravital microscopy. The combined experiment-theory approach revealed spatial heterogeneities of biliary geometry and hepatocyte transport activity. Based on this, our model predicts gradients of bile velocity and pressure in the liver lobule. Validation of the model predictions by pharmacological inhibition of Rho kinase demonstrated a requirement of canaliculi contractility for bile flow in vivo. Our model can be applied to functionally characterize liver diseases and quantitatively estimate biliary transport upon drug-induced liver injury.

Peroxisome proliferators, which function as peroxisome proliferator-activated receptor-alpha (PPARalpha) agonists, are a group of structurally diverse nongenotoxic hepatocarcinogens including the fibrate class of hypolipidemic drugs that induce peroxisome proliferation in liver parenchymal cells. Sustained activation of PPARalpha by these agents leads to the development of liver tumors in rats and mice. To understand the molecular mechanisms responsible for the pleiotropic effects of these agents, we have utilized the cDNA microarray to generate a molecular portrait of gene expression in the liver of mice treated for 2 weeks with Wy-14,643, a potent peroxisome proliferator. PPARalpha activation resulted in the stimulation of expression (fourfold or greater) of 36 genes and decreased the expression (fourfold or more decrease) of 671 genes. Enhanced expression of several genes involved in lipid and glucose metabolism and many other genes associated with peroxisome biogenesis, cell surface function, transcription, cell cycle, and apoptosis has been observed. These include: CYP2B9, CYP2B10, monoglyceride lipase, pyruvate dehydrogenase-kinase-4, cell death-inducing DNA-fragmentation factor-alpha, peroxisomal biogenesis factor 11beta, as well as several cell recognition surface proteins including annexin A2, CD24, CD39, lymphocyte antigen 6, and retinoic acid early transcript-gamma, among others. Northern blotting of total RNA extracted from the livers of PPARalpha-/- mice and from mice lacking both PPARalpha and peroxisomal fatty acyl-CoA oxidase (AOX), that were fed control and Wy-14,643-containing diets for 2 weeks, as well as time course of induction following a single dose of Wy-14,643, revealed that upregulation of genes identified by microarray procedure is dependent upon peroxisome proliferation vis-à-vis PPARalpha. However, cell death-inducing DNA-fragmentation factor-alpha mRNA, which is increased in the livers of wild-type mice treated with peroxisome proliferators, was not enhanced in AOX-/- mice with spontaneous peroxisome proliferation. These observations indicate that the activation of PPARalpha leads to increased and decreased expression of many genes not associated with peroxisomes, and that delayed onset of enhanced expression of some genes may be the result of metabolic events occurring secondary to PPARalpha activation and alterations in lipid metabolism.

Functional tissue architecture originates by self-assembly of distinct cell types, following tissue-specific rules of cell-cell interactions. In the liver, a structural model of the lobule was pioneered by Elias in 1949. This model, however, is in contrast with the apparent random 3D arrangement of hepatocytes. Since then, no significant progress has been made to derive the organizing principles of liver tissue. To solve this outstanding problem, we computationally reconstructed 3D tissue geometry from microscopy images of mouse liver tissue and analyzed it applying soft-condensed-matter-physics concepts. Surprisingly, analysis of the spatial organization of cell polarity revealed that hepatocytes are not randomly oriented but follow a long-range liquid-crystal order. This does not depend exclusively on hepatocytes receiving instructive signals by endothelial cells, since silencing Integrin-β1 disrupted both liquid-crystal order and organization of the sinusoidal network. Our results suggest that bi-directional communication between hepatocytes and sinusoids underlies the self-organization of liver tissue.