From whole-organ imaging to in-silico blood flow modeling: A new multi-scale network analysis for revisiting tissue functional anatomy.

We present a multi-disciplinary image-based blood flow perfusion modeling of a whole organ vascular network for analyzing both its structural and functional properties. We show how the use of Light-Sheet Fluorescence Microscopy (LSFM) permits whole-organ micro-vascular imaging, analysis and modelling. By using adapted image post-treatment workflow, we could segment, vectorize and reconstruct the entire micro-vascular network composed of 1.7 million vessels, from the tissue-scale, inside a ∼ 25 × 5 × 1 = 125mm3 volume of the mouse fat pad, hundreds of times larger than previous studies, down to the cellular scale at micron resolution, with the entire blood perfusion modeled. Adapted network analysis revealed the structural and functional organization of meso-scale tissue as strongly connected communities of vessels. These communities share a distinct heterogeneous core region and a more homogeneous peripheral region, consistently with known biological functions of fat tissue. Graph clustering analysis also revealed two distinct robust meso-scale typical sizes (from 10 to several hundred times the cellular size), revealing, for the first time, strongly connected functional vascular communities. These community networks support heterogeneous micro-environments. This work provides the proof of concept that in-silico all-tissue perfusion modeling can reveal new structural and functional exchanges between micro-regions in tissues, found from community clusters in the vascular graph.

Mitochondrial 4-HNE derived from MAO-A promotes mitoCa2+ overload in chronic postischemic cardiac remodeling.

Chronic remodeling postmyocardial infarction consists in various maladaptive changes including interstitial fibrosis, cardiomyocyte death and mitochondrial dysfunction that lead to heart failure (HF). Reactive aldehydes such as 4-hydroxynonenal (4-HNE) are critical mediators of mitochondrial dysfunction but the sources of mitochondrial 4-HNE in cardiac diseases together with its mechanisms of action remain poorly understood. Here, we evaluated whether the mitochondrial enzyme monoamine oxidase-A (MAO-A), which generates H2O2 as a by-product of catecholamine metabolism, is a source of deleterious 4-HNE in HF. We found that MAO-A activation increased mitochondrial ROS and promoted local 4-HNE production inside the mitochondria through cardiolipin peroxidation in primary cardiomyocytes. Deleterious effects of MAO-A/4-HNE on cardiac dysfunction were prevented by activation of mitochondrial aldehyde dehydrogenase 2 (ALDH2), the main enzyme for 4-HNE metabolism. Mechanistically, MAO-A-derived 4-HNE bound to newly identified targets VDAC and MCU to promote ER-mitochondria contact sites and MCU higher-order complex formation. The resulting mitochondrial Ca2+ accumulation participated in mitochondrial respiratory dysfunction and loss of membrane potential, as shown with the protective effects of the MCU inhibitor, RU360. Most interestingly, these findings were recapitulated in a chronic model of ischemic remodeling where pharmacological or genetic inhibition of MAO-A protected the mice from 4-HNE accumulation, MCU oligomer formation and Ca2+ overload, thus mitigating ventricular dysfunction. To our knowledge, these are the first evidences linking MAO-A activation to mitoCa2+ mishandling through local 4-HNE production, contributing to energetic failure and postischemic remodeling.

Toward quantitative three-dimensional microvascular networks segmentation with multiview light-sheet fluorescence microscopy.

Three-dimensional (3-D) large-scale imaging of microvascular networks is of interest in various areas of biology and medicine related to structural, functional, developmental, and pathological issues. Light-sheet fluorescence microscopy (LSFM) techniques are rapidly spreading and are now on the way to offer operational solutions for large-scale tissue imaging. This contribution describes how reliable vessel segmentation can be handled from LSFM data in very large tissue volumes using a suitable image analysis workflow. Since capillaries are tubular objects of a few microns scale radius, they represent challenging structures to reliably reconstruct without distortion and artifacts. We provide a systematic analysis of multiview deconvolution image processing workflow to control and evaluate the accuracy of the reconstructed vascular network using various low to high level, metrics. We show that even if low-level structural metrics are sensitive to isotropic imaging enhancement provided by a larger number of views, functional high-level metrics, including perfusion permeability, are less sensitive. Hence, combining deconvolution and registration onto a few number of views appears sufficient for a reliable quantitative 3-D vessel segmentation for their possible use for perfusion modeling.