Biased IL-2 signals induce Foxp3-rich pulmonary lymphoid structures and facilitate long-term lung allograft acceptance in mice.

Transplantation of solid organs can be life-saving in patients with end-stage organ failure, however, graft rejection remains a major challenge. In this study, by pre-conditioning with interleukin-2 (IL-2)/anti-IL-2 antibody complex treatment biased toward IL-2 receptor α, we achieved acceptance of fully mismatched orthotopic lung allografts that remained morphologically and functionally intact for more than 90 days in immunocompetent mice. These allografts are tolerated by the actions of forkhead box p3 (Foxp3)+ regulatory T (Treg) cells that home to the lung allografts. Although counts of circulating Treg cells rapidly return to baseline following cessation of IL-2 treatment, Foxp3+ Treg cells persist in peribronchial and peribronchiolar areas of the grafted lungs, forming organized clusters reminiscent of inducible tertiary lymphoid structures (iTLS). These iTLS in lung allografts are made of Foxp3+ Treg cells, conventional T cells, and B cells, as evidenced by using microscopy-based distribution and neighborhood analyses. Foxp3-transgenic mice with inducible and selective deletion of Foxp3+ cells are unable to form iTLS in lung allografts, and these mice acutely reject lung allografts. Collectively, we report that short-term, high-intensity and biased IL-2 pre-conditioning facilitates acceptance of vascularized and ventilated lung allografts without the need of immunosuppression, by inducing Foxp3-controlled iTLS formation within allografts.

Probabilistic spatial analysis in quantitative microscopy with uncertainty-aware cell detection using deep Bayesian regression.

The investigation of biological systems with three-dimensional microscopy demands automatic cell identification methods that not only are accurate but also can imply the uncertainty in their predictions. The use of deep learning to regress density maps is a popular successful approach for extracting cell coordinates from local peaks in a postprocessing step, which then, however, hinders any meaningful probabilistic output. We propose a framework that can operate on large microscopy images and output probabilistic predictions (i) by integrating deep Bayesian learning for the regression of uncertainty-aware density maps, where peak detection algorithms generate cell proposals, and (ii) by learning a mapping from prediction proposals to a probabilistic space that accurately represents the chances of a successful prediction. Using these calibrated predictions, we propose a probabilistic spatial analysis with Monte Carlo sampling. We demonstrate this in a bone marrow dataset, where our proposed methods reveal spatial patterns that are otherwise undetectable.

Chronic viral infections persistently alter marrow stroma and impair hematopoietic stem cell fitness.

Chronic viral infections are associated with hematopoietic suppression, bone marrow (BM) failure, and hematopoietic stem cell (HSC) exhaustion. However, how persistent viral challenge and inflammatory responses target BM tissues and perturb hematopoietic competence remains poorly understood. Here, we combine functional analyses with advanced 3D microscopy to demonstrate that chronic infection with lymphocytic choriomeningitis virus leads to (1) long-lasting decimation of the BM stromal network of mesenchymal CXCL12-abundant reticular cells, (2) proinflammatory transcriptional remodeling of remaining components of this key niche subset, and (3) durable functional defects and decreased competitive fitness in HSCs. Mechanistically, BM immunopathology is elicited by virus-specific, activated CD8 T cells, which accumulate in the BM via interferon-dependent mechanisms. Combined antibody-mediated inhibition of type I and II IFN pathways completely preempts degeneration of CARc and protects HSCs from chronic dysfunction. Hence, viral infections and ensuing immune reactions durably impact BM homeostasis by persistently decreasing the competitive fitness of HSCs and disrupting essential stromal-derived, hematopoietic-supporting cues.

Modality Attention and Sampling Enables Deep Learning with Heterogeneous Marker Combinations in Fluorescence Microscopy.

Fluorescence microscopy allows for a detailed inspection of cells, cellular networks, and anatomical landmarks by staining with a variety of carefully-selected markers visualized as color channels. Quantitative characterization of structures in acquired images often relies on automatic image analysis methods. Despite the success of deep learning methods in other vision applications, their potential for fluorescence image analysis remains underexploited. One reason lies in the considerable workload required to train accurate models, which are normally specific for a given combination of markers, and therefore applicable to a very restricted number of experimental settings. We herein propose Marker Sampling and Excite - a neural network approach with a modality sampling strategy and a novel attention module that together enable (i) flexible training with heterogeneous datasets with combinations of markers and (ii) successful utility of learned models on arbitrary subsets of markers prospectively. We show that our single neural network solution performs comparably to an upper bound scenario where an ensemble of many networks is naïvely trained for each possible marker combination separately. In addition, we demonstrate the feasibility of this framework in high-throughput biological analysis by revising a recent quantitative characterization of bone marrow vasculature in 3D confocal microscopy datasets and further confirm the validity of our approach on an additional, significantly different dataset of microvessels in fetal liver tissues. Not only can our work substantially ameliorate the use of deep learning in fluorescence microscopy analysis, but it can also be utilized in other fields with incomplete data acquisitions and missing modalities.

Multiparametric imaging reveals that mitochondria-rich intercalated cells in the kidney collecting duct have a very high glycolytic capacity.

Alpha intercalated cells (αICs) in the kidney collecting duct (CD) belong to a family of mitochondria rich cells (MRCs) and have a crucial role in acidifying the urine via apical V-ATPase pumps. The nature of metabolism in αICs and its relationship to transport was not well-understood. Here, using multiphoton live cell imaging in mouse kidney tissue, FIB-SEM, and other complementary techniques, we provide new insights into mitochondrial structure and function in αICs. We show that αIC mitochondria have a rounded structure and are not located in close proximity to V-ATPase containing vesicles. They display a bright NAD(P)H fluorescence signal and low uptake of voltage-dependent dyes, but are energized by a pH gradient. However, expression of complex V (ATP synthase) is relatively low in αICs, even when stimulated by metabolic acidosis. In contrast, anaerobic glycolytic capacity is surprisingly high, and sufficient to maintain intracellular calcium homeostasis in the presence of complete aerobic inhibition. Moreover, glycolysis is essential for V-ATPase-mediated proton pumping. Key findings were replicated in narrow/clear cells in the epididymis, also part of the MRC family. In summary, using a range of cutting-edge techniques to investigate αIC metabolism in situ, we have discovered that these mitochondria dense cells have a high glycolytic capacity.

Imaging and spatial analysis of hematopoietic stem cell niches.

Hematopoietic stem cells (HSCs) have been long proposed to reside in defined anatomical locations within bone marrow (BM) tissues in direct contact or close proximity to nurturing cell types. Imaging techniques that allow the simultaneous mapping of HSCs and interacting cell types have been central to the discovery of basic principles of these so-called HSC niches. Despite major progress in the field, a quantitative and comprehensive model of the cellular and molecular components that define these specialized microenvironments is lacking to date, and uncertainties remain on the preferential localization of HSCs in the context of complex BM tissue landscapes. Recent technological breakthroughs currently allow for the quantitative spatial analysis of BM cellular components with extraordinary precision. Here, we critically discuss essential technical aspects related to imaging approaches, image processing tools, and spatial statistics, which constitute the three basic elements of rigorous quantitative spatial analyses of HSC niches in the BM microenvironment.

In-Vivo Quantitative Image Analysis of Age-Related Morphological Changes of C. elegans Neurons Reveals a Correlation between Neurite Bending and Novel Neurite Outgrowths.

The aging of the human brain in the absence of diseases is accompanied by subtle changes of neuronal morphology, such as dendrite restructuring, neuronal sprouting, and synaptic deteriorations, rather than neurodegeneration or gross deterioration. Similarly, the nervous system of Caenorhabditis elegans does not show neurodegeneration or gross deterioration during normal aging, but displays subtle alterations in neuronal morphology. The occurrence of these age-dependent abnormalities is stochastic and dynamic, which poses a major challenge to fully capture them for quantitative comparison. Here, we developed a semi-automated pipeline for quantitative image analysis of these features during aging. We employed and evaluated this pipeline herein to reproduce findings from previous studies using visual inspection of neuronal morphology. Importantly, our approach can also quantify additional features, such as soma volume, the length of neurite outgrowths, and their location along the aged neuron. We found that, during aging, the soma of neurons decreases in volume, whereas the number and length of neurite outgrowths from the soma both increase. Long-lived animals showed less decrease in soma volume, fewer and shorter neurite outgrowths, and protection against abnormal sharp bends preferentially localized at the distal part of the dendrites during aging. We found a correlation of sharp bends with neurite outgrowth, suggesting the hypothesis that sharp bends might proceed neurite outgrowths. Thus, our semi-automated pipeline can help researchers to obtain and analyze quantitative datasets of this stochastic process for comparison across genotypes and to identify correlations to facilitate the generation of novel hypothesis.

Mesenchymal Niche-Specific Expression of Cxcl12 Controls Quiescence of Treatment-Resistant Leukemia Stem Cells.

Chronic myeloid leukemia (CML) originates in a hematopoietic stem cell (HSC) transformed by the breakpoint cluster region (BCR)-abelson (ABL) oncogene and is effectively treated with tyrosine kinase inhibitors (TKIs). TKIs do not eliminate disease-propagating leukemic stem cells (LSCs), suggesting a deeper understanding of niche-dependent regulation of CML LSCs is required to eradicate disease. Cxcl12 is expressed in bone marrow niches and controls HSC maintenance, and here, we show that targeted deletion of Cxcl12 from mesenchymal stromal cells (MSCs) reduces normal HSC numbers but promotes LSC expansion by increasing self-renewing cell divisions, possibly through enhanced Ezh2 activity. In contrast, endothelial cell-specific Cxcl12 deletion decreases LSC proliferation, suggesting niche-specific effects. During CML development, abnormal clusters of colocalized MSCs and LSCs form but disappear upon Cxcl12 deletion. Moreover, MSC-specific deletion of Cxcl12 increases LSC elimination by TKI treatment. These findings highlight a critical role of niche-specific effects of Cxcl12 expression in maintaining quiescence of TKI-resistant LSC populations.

Quantitative spatial analysis of haematopoiesis-regulating stromal cells in the bone marrow microenvironment by 3D microscopy.

Sinusoidal endothelial cells and mesenchymal CXCL12-abundant reticular cells are principal bone marrow stromal components, which critically modulate haematopoiesis at various levels, including haematopoietic stem cell maintenance. These stromal subsets are thought to be scarce and function via highly specific interactions in anatomically confined niches. Yet, knowledge on their abundance, global distribution and spatial associations remains limited. Using three-dimensional quantitative microscopy we show that sinusoidal endothelial and mesenchymal reticular subsets are remarkably more abundant than estimated by conventional flow cytometry. Moreover, both cell types assemble in topologically complex networks, associate to extracellular matrix and pervade marrow tissues. Through spatial statistical methods we challenge previous models and demonstrate that even in the absence of major specific interaction forces, virtually all tissue-resident cells are invariably in physical contact with, or close proximity to, mesenchymal reticular and sinusoidal endothelial cells. We further show that basic structural features of these stromal components are preserved during ageing.

Pathogen-Induced TLR4-TRIF Innate Immune Signaling in Hematopoietic Stem Cells Promotes Proliferation but Reduces Competitive Fitness.

Bacterial infection leads to consumption of short-lived innate immune effector cells, which then need to be replenished from hematopoietic stem and progenitor cells (HSPCs). HSPCs express pattern recognition receptors, such as Toll-like receptors (TLRs), and ligation of these receptors induces HSPC mobilization, cytokine production, and myeloid differentiation. The underlying mechanisms involved in pathogen signal transduction in HSCs and the resulting biological consequences remain poorly defined. Here, we show that in vivo lipopolysaccharide (LPS) application induces proliferation of dormant HSCs directly via TLR4 and that sustained LPS exposure impairs HSC self-renewal and competitive repopulation activity. This process is mediated via TLR4-TRIF-ROS-p38, but not MyD88 signaling, and can be inhibited pharmacologically without preventing emergency granulopoiesis. Live Salmonella Typhimurium infection similarly induces proliferative stress in HSCs, in part via TLR4-TRIF signals. Thus, while direct TLR4 activation in HSCs might be beneficial for controlling systemic infection, prolonged TLR4 signaling has detrimental effects and may contribute to inflammation-associated HSPC dysfunction.