Search

In many leukemia patients, a poor prognosis is attributed either to the development of chemotherapy resistance by leukemic stem cells (LSCs) or to the inefficient engraftment of transplanted hematopoietic stem/progenitor cells (HSPCs) into the bone marrow (BM). Here, we build a 3D in vitro model system of bone marrow organoids (BMOs) that recapitulate several structural and cellular components of native BM. These organoids are formed in a high-throughput manner from the aggregation of endothelial and mesenchymal cells within hydrogel microwells. Accordingly, the mesenchymal compartment shows partial maintenance of its self-renewal and multilineage potential, while endothelial cells self-organize into an interconnected vessel-like network. Intriguingly, such an endothelial compartment enhances the recruitment of HSPCs in a chemokine ligand/receptor-dependent manner, reminiscent of HSPC homing behavior in vivo. Additionally, we also model LSC migration and nesting in BMOs, thus highlighting the potential of this system as a well accessible and scalable preclinical model for candidate drug screening and patient-specific assays.

Excitatory and inhibitory neurons in diverse cortical regions are likely to contribute differentially to the transformation of sensory information into goal-directed motor plans. Here, we investigate the relative changes across mouse sensorimotor cortex in the activity of putative excitatory and inhibitory neurons-categorized as regular spiking (RS) or fast spiking (FS) according to their action potential (AP) waveform-comparing before and after learning of a whisker detection task with delayed licking as perceptual report. Surprisingly, we found that the whisker-evoked activity of RS versus FS neurons changed in opposite directions after learning in primary and secondary whisker motor cortices, while it changed similarly in primary and secondary orofacial motor cortices. Our results suggest that changes in the balance of excitation and inhibition in local circuits concurrent with changes in the long-range synaptic inputs in distinct cortical regions might contribute to performance of delayed sensory-to-motor transformation.

Image analysis workflows for Histology increasingly require the correlation and combination of measurements across several whole slide images. Indeed, for multiplexing, as well as multimodal imaging, it is indispensable that the same sample is imaged multiple times, either through various systems for multimodal imaging, or using the same system but throughout rounds of sample manipulation (e.g. multiple staining sessions). In both cases slight deformations from one image to another are unavoidable, leading to an imperfect superimposition Redundant and thus a loss of accuracy making it difficult to link measurements, in particular at the cellular level. Using pre-existing software components and developing missing ones, we propose a user-friendly workflow which facilitates the nonlinear registration of whole slide images in order to reach sub-cellular resolution level. The set of whole slide images to register and analyze is at first defined as a QuPath project. Fiji is then used to open the QuPath project and perform the registrations. Each registration is automated by using an elastix backend, or semi-automated by using BigWarp in order to interactively correct the results of the automated registration. These transformations can then be retrieved in QuPath to transfer any regions of interest from an image to the corresponding registered images. In addition, the transformations can be applied in QuPath to produce on-the-fly transformed images that can be displayed on top of the reference image. Thus, relevant data can be combined and analyzed throughout all registered slides, facilitating the analysis of correlative results for multiplexed and multimodal imaging.

NEUBIAS, the European Network of Bioimage Analysts, was created in 2016 with the goal of improving the communication and the knowledge transfer among the various stakeholders involved in the acquisition, processing and analysis of biological image data, and to promote the establishment and recognition of the profession of Bioimage Analyst. One of the most successful initiatives of the NEUBIAS programme was its series of 15 training schools, which trained over 400 new Bioimage Analysts, coming from over 40 countries. Here we outline the rationale behind the innovative three-level program of the schools, the curriculum, the trainer recruitment and turnover strategy, the outcomes for the community and the career path of analysts, including some success stories. We discuss the future of the materials created during this programme and some of the new initiatives emanating from the community of NEUBIAS-trained analysts, such as the NEUBIAS Academy. Overall, we elaborate on how this training programme played a key role in collectively leveraging Bioimaging and Life Science research by bringing the latest innovations into structured, frequent and intensive training activities, and on why we believe this should become a model to further develop in Life Sciences.

The number of grey values that can be displayed on monitors and be processed by the human eye is smaller than the dynamic range of image-based sensors. This makes the visualization of such data a challenge, especially with specimens where small dim structures are equally important as large bright ones, or whenever variations in intensity, such as non-homogeneous staining efficiencies or light depth penetration, becomes an issue. While simple intensity display mappings are easily possible, these fail to provide a one-shot observation that can display objects of varying intensities. In order to facilitate the visualization-based analysis of large volumetric datasets, we developed an easy-to-use ImageJ plugin enabling the compressed display of features within several magnitudes of intensities. The Display Enhancement for Visual Inspection of Large Stacks plugin (DEVILS) homogenizes the intensities by using a combination of local and global pixel operations to allow for high and low intensities to be visible simultaneously to the human eye. The plugin is based on a single, intuitively understandable parameter, features a preview mode, and uses parallelization to process multiple image planes. As output, the plugin is capable of producing a BigDataViewer-compatible dataset for fast visualization. We demonstrate the utility of the plugin for large volumetric image data.

Obtaining a catalog of cell types is a fundamental building block for understanding the brain. The ideal classification of cell-types is based on the profile of molecules expressed by a cell, in particular, the profile of genes expressed. One strategy is, therefore, to obtain as many single-cell transcriptomes as possible and isolate clusters of neurons with similar gene expression profiles. In this study, we explored an alternative strategy. We explored whether cell-types can be algorithmically derived by combining protein tissue stains with transcript expression profiles. We developed an algorithm that aims to distribute cell-types in the different layers of somatosensory cortex of the developing rat constrained by the tissue- and cellular level data. We found that the spatial distribution of major inhibitory cell types can be approximated using the available data. The result is a depth-wise atlas of inhibitory cell-types of the rat somatosensory cortex. In principle, any data that constrains what can occur in a particular part of the brain can also strongly constrain the derivation of cell-types. This draft inhibitory cell-type mapping is therefore dynamic and can iteratively converge towards the ground truth as further data is integrated.

Dendritic cells (DC) are professional Antigen-Presenting Cells scattered throughout antigen-exposed tissues and draining lymph nodes, and survey the body for pathogens. Their ability to migrate through tissues, a 3D environment, is essential for an effective immune response. Upon infection, recognition of Pathogen-Associated Molecular Patterns (PAMP) by Toll-like receptors (TLR) triggers DC maturation. Mature DC (mDC) essentially use the protease-independent, ROCK-dependent amoeboid mode in vivo, or in collagen matrices in vitro. However, the mechanisms of 3D migration used by human immature DC (iDC) are still poorly characterized. Here, we reveal that human monocyte-derived DC are able to use two migration modes in 3D. In porous matrices of fibrillar collagen I, iDC adopted the amoeboid migration mode. In dense matrices of gelled collagen I or Matrigel, iDC used the protease-dependent, ROCK-independent mesenchymal migration mode. Upon TLR4 activation by LPS, mDC-LPS lose the capacity to form podosomes and degrade the matrix along with impaired mesenchymal migration. TLR2 activation by Pam3CSK4 resulted in DC maturation, podosome maintenance, and efficient mesenchymal migration. Under all these conditions, when DC used the mesenchymal mode in dense matrices, they formed 3D podosomes at the tip of cell protrusions. Using PGE2, known to disrupt podosomes in DC, we observed that the cells remained in an immature status and the mesenchymal migration mode was abolished. We also observed that, while CCL5 (attractant of iDC) enhanced both amoeboid and mesenchymal migration of iDC, CCL19 and CCL21 (attractants of mDC) only enhanced mDC-LPS amoeboid migration without triggering mesenchymal migration. Finally, we examined the migration of iDC in tumor cell spheroids, a tissue-like 3D environment. We observed that iDC infiltrated spheroids of tumor cells using both migration modes. Altogether, these results demonstrate that human DC adopt the mesenchymal mode to migrate in 3D dense environments, which relies on their capacity to form podosomes independent of their maturation status, paving the way of further investigations on in vivo DC migration in dense tissues and its regulation during infections.

Approximately one-third of the world's population suffers from chronic helminth infections with no effective vaccines currently available. Antibodies and alternatively activated macrophages (AAM) form crucial components of protective immunity against challenge infections with intestinal helminths. However, the mechanisms by which antibodies target these large multi-cellular parasites remain obscure. Alternative activation of macrophages during helminth infection has been linked to signaling through the IL-4 receptor alpha chain (IL-4Rα), but the potential effects of antibodies on macrophage differentiation have not been explored. We demonstrate that helminth-specific antibodies induce the rapid trapping of tissue migrating helminth larvae and prevent tissue necrosis following challenge infection with the natural murine parasite Heligmosomoides polygyrus bakeri (Hp). Mice lacking antibodies (JH (-/-)) or activating Fc receptors (FcRγ(-/-)) harbored highly motile larvae, developed extensive tissue damage and accumulated less Arginase-1 expressing macrophages around the larvae. Moreover, Hp-specific antibodies induced FcRγ- and complement-dependent adherence of macrophages to larvae in vitro, resulting in complete larval immobilization. Antibodies together with helminth larvae reprogrammed macrophages to express wound-healing associated genes, including Arginase-1, and the Arginase-1 product L-ornithine directly impaired larval motility. Antibody-induced expression of Arginase-1 in vitro and in vivo occurred independently of IL-4Rα signaling. In summary, we present a novel IL-4Rα-independent mechanism of alternative macrophage activation that is antibody-dependent and which both mediates anti-helminth immunity and prevents tissue disruption caused by migrating larvae.