Ependyma-expressed CCN1 restricts the size of the neural stem cell pool in the adult ventricular-subventricular zone.

Adult neural stem cells (NSCs) reside in specialized niches, which hold a balanced number of NSCs, their progeny, and other cells. How niche capacity is regulated to contain a specific number of NSCs remains unclear. Here, we show that ependyma-derived matricellular protein CCN1 (cellular communication network factor 1) negatively regulates niche capacity and NSC number in the adult ventricular-subventricular zone (V-SVZ). Adult ependyma-specific deletion of Ccn1 transiently enhanced NSC proliferation and reduced neuronal differentiation in mice, increasing the numbers of NSCs and NSC units. Although proliferation of NSCs and neurogenesis seen in Ccn1 knockout mice eventually returned to normal, the expanded NSC pool was maintained in the V-SVZ until old age. Inhibition of EGFR signaling prevented expansion of the NSC population observed in CCN1 deficient mice. Thus, ependyma-derived CCN1 restricts NSC expansion in the adult brain to maintain the proper niche capacity of the V-SVZ.

Sp2 regulates late neurogenic but not early expansive divisions of neural stem cells underlying population growth in the mouse cortex.

Cellular and molecular mechanisms underlying the switch from self-amplification of cortical stem cells to neuronal and glial generation are incompletely understood, despite their importance for neural development. Here, we have investigated the role of the transcription factor specificity protein 2 (Sp2) in expansive and neurogenic divisions of the developing cerebral cortex by combining conditional genetic deletion with the mosaic analysis with double markers (MADM) system in mice. We find that loss of Sp2 in progenitors undergoing neurogenic divisions results in prolonged mitosis due to extension of early mitotic stages. This disruption is correlated with depletion of the populations of upper layer neurons in the cortex. In contrast, early cortical neural stem cells proliferate and expand normally in the absence of Sp2. These results indicate a stage-specific requirement for Sp2 in neural stem and progenitor cells, and reveal mechanistic differences between the early expansive and later neurogenic periods of cortical development.This article has an associated 'The people behind the papers' interview.

Stomach curvature is generated by left-right asymmetric gut morphogenesis.

Left-right (LR) asymmetry is a fundamental feature of internal anatomy, yet the emergence of morphological asymmetry remains one of the least understood phases of organogenesis. Asymmetric rotation of the intestine is directed by forces outside the gut, but the morphogenetic events that generate anatomical asymmetry in other regions of the digestive tract remain unknown. Here, we show in mouse and Xenopus that the mechanisms that drive the curvature of the stomach are intrinsic to the gut tube itself. The left wall of the primitive stomach expands more than the right wall, as the left epithelium becomes more polarized and undergoes radial rearrangement. These asymmetries exist across several species, and are dependent on LR patterning genes, including Foxj1, Nodal and Pitx2 Our findings have implications for how LR patterning manifests distinct types of morphological asymmetries in different contexts.

TAK1 determines susceptibility to endoplasmic reticulum stress and leptin resistance in the hypothalamus.

Sustained endoplasmic reticulum (ER) stress disrupts normal cellular homeostasis and leads to the development of many types of human diseases, including metabolic disorders. TAK1 (also known as MAP3K7) is a member of the mitogen-activated protein kinase kinase kinase (MAP3K) family and is activated by a diverse set of inflammatory stimuli. Here, we demonstrate that TAK1 regulates ER stress and metabolic signaling through modulation of lipid biogenesis. We found that deletion of Tak1 increased ER volume and facilitated ER-stress tolerance in cultured cells, which was mediated by upregulation of sterol-regulatory-element-binding protein (SREBP)-dependent lipogenesis. In the in vivo setting, central nervous system (CNS)-specific Tak1 deletion upregulated SREBP-target lipogenic genes and blocked ER stress in the hypothalamus. Furthermore, CNS-specific Tak1 deletion prevented ER-stress-induced hypothalamic leptin resistance and hyperphagic obesity under a high-fat diet (HFD). Thus, TAK1 is a crucial regulator of ER stress in vivo, which could be a target for alleviation of ER stress and its associated disease conditions.

Neural Stem Cells to Cerebral Cortex: Emerging Mechanisms Regulating Progenitor Behavior and Productivity.

This review accompanies a 2016 SFN mini-symposium presenting examples of current studies that address a central question: How do neural stem cells (NSCs) divide in different ways to produce heterogeneous daughter types at the right time and in proper numbers to build a cerebral cortex with the appropriate size and structure? We will focus on four aspects of corticogenesis: cytokinesis events that follow apical mitoses of NSCs; coordinating abscission with delamination from the apical membrane; timing of neurogenesis and its indirect regulation through emergence of intermediate progenitors; and capacity of single NSCs to generate the correct number and laminar fate of cortical neurons. Defects in these mechanisms can cause microcephaly and other brain malformations, and understanding them is critical to designing diagnostic tools and preventive and corrective therapies.

Neural development is dependent on the function of specificity protein 2 in cell cycle progression.

Faithful progression through the cell cycle is crucial to the maintenance and developmental potential of stem cells. Here, we demonstrate that neural stem cells (NSCs) and intermediate neural progenitor cells (NPCs) employ a zinc-finger transcription factor specificity protein 2 (Sp2) as a cell cycle regulator in two temporally and spatially distinct progenitor domains. Differential conditional deletion of Sp2 in early embryonic cerebral cortical progenitors, and perinatal olfactory bulb progenitors disrupted transitions through G1, G2 and M phases, whereas DNA synthesis appeared intact. Cell-autonomous function of Sp2 was identified by deletion of Sp2 using mosaic analysis with double markers, which clearly established that conditional Sp2-null NSCs and NPCs are M phase arrested in vivo. Importantly, conditional deletion of Sp2 led to a decline in the generation of NPCs and neurons in the developing and postnatal brains. Our findings implicate Sp2-dependent mechanisms as novel regulators of cell cycle progression, the absence of which disrupts neurogenesis in the embryonic and postnatal brain.

Unique glycan signatures regulate adeno-associated virus tropism in the developing brain.

UNLABELLED: Adeno-associated viruses (AAV) are thought to spread through the central nervous system (CNS) by exploiting cerebrospinal fluid (CSF) flux and hijacking axonal transport pathways. The role of host receptors that mediate these processes is not well understood. In the current study, we utilized AAV serotype 4 (AAV4) as a model to evaluate whether ubiquitously expressed 2,3-linked sialic acid and the developmentally regulated marker 2,8-linked polysialic acid (PSA) regulate viral transport and tropism in the neonatal brain. Modulation of the levels of SA and PSA in cell culture studies using specific neuraminidases revealed possibly opposing roles of the two glycans in AAV4 transduction. Interestingly, upon intracranial injection into lateral ventricles of the neonatal mouse brain, a low-affinity AAV4 mutant (AAV4.18) displayed a striking shift in cellular tropism from 2,3-linked SA(+) ependymal lining to 2,8-linked PSA(+) migrating progenitors in the rostral migratory stream and olfactory bulb. In addition, this gain-of-function phenotype correlated with robust CNS spread of AAV4.18 through paravascular transport pathways. Consistent with these observations, altering glycan dynamics within the brain by coadministering SA- and PSA-specific neuraminidases resulted in striking changes to the cellular tropisms and transduction efficiencies of both parental and mutant vectors. We postulate that glycan signatures associated with host development can be exploited to redirect novel AAV vectors to specific cell types in the brain. IMPORTANCE: Viruses invade the CNS through various mechanisms. In the current study, we utilized AAV as a model to study the dynamics of virus-carbohydrate interactions in the developing brain and their impact on viral tropism. Our findings suggest that carbohydrate content can be exploited to regulate viral transport and tropism in the brain.

TransOmic analysis of forebrain sections in Sp2 conditional knockout embryonic mice using IR-MALDESI imaging of lipids and LC-MS/MS label-free proteomics.

Quantitative methods for detection of biological molecules are needed more than ever before in the emerging age of "omics" and "big data." Here, we provide an integrated approach for systematic analysis of the "lipidome" in tissue. To test our approach in a biological context, we utilized brain tissue selectively deficient for the transcription factor Specificity Protein 2 (Sp2). Conditional deletion of Sp2 in the mouse cerebral cortex results in developmental deficiencies including disruption of lipid metabolism. Silver (Ag) cationization was implemented for infrared matrix-assisted laser desorption electrospray ionization (IR-MALDESI) to enhance the ion abundances for olefinic lipids, as these have been linked to regulation by Sp2. Combining Ag-doped and conventional IR-MALDESI imaging, this approach was extended to IR-MALDESI imaging of embryonic mouse brains. Further, our imaging technique was combined with bottom-up shotgun proteomic LC-MS/MS analysis and western blot for comparing Sp2 conditional knockout (Sp2-cKO) and wild-type (WT) cortices of tissue sections. This provided an integrated omics dataset which revealed many specific changes to fundamental cellular processes and biosynthetic pathways. In particular, step-specific altered abundances of nucleotides, lipids, and associated proteins were observed in the cerebral cortices of Sp2-cKO embryos.

Transplantation of GABAergic Interneurons into the Neonatal Primary Visual Cortex Reduces Absence Seizures in Stargazer Mice.

Epilepsies are debilitating neurological disorders characterized by repeated episodes of pathological seizure activity. Absence epilepsy (AE) is a poorly understood type of seizure with an estimated 30% of affected patients failing to respond to antiepileptic drugs. Thus, novel therapies are needed for the treatment of AE. A promising cell-based therapeutic strategy is centered on transplantation of embryonic neural stem cells from the medial ganglionic eminence (MGE), which give rise to gamma-aminobutyric acidergic (GABAergic) interneurons during embyronic development. Here, we used the Stargazer (Stg) mouse model of AE to map affected loci using c-Fos immunohistochemistry, which revealed intense seizure-induce activity in visual and somatosensory cortices. We report that transplantation of MGE cells into the primary visual cortex (V1) of Stg mice significantly reduces AE episodes and lowers mortality. Electrophysiological analysis in acute cortical slices of visual cortex demonstrated that Stg V1 neurons exhibit more pronounced increases in activity in response to a potassium-mediated excitability challenge than wildtypes (WT). The defective network activity in V1 was significantly altered following WT MGE transplantation, associating it with behavioral rescue of seizures in Stgs. Taken together, these findings present MGE grafting in the V1 as a possible clinical approach in the treatment of AE.

A knock-in Foxj1(CreERT2::GFP) mouse for recombination in epithelial cells with motile cilia.

The transcription factor Foxj1 is expressed by cells destined to differentiate into epithelial cells projecting motile cilia into fluid- or air-filled cavities. Here, we report the generation of an inducible knock-in Foxj1(CreERT2::GFP) mouse, which we show reliably induces Cre-mediated recombination for genetic studies in epithelial cells with motile cilia throughout embryonic and postnatal development. Induction during embryonic stages revealed efficient recombination in the epithelial component of the choroid plexus in the developing brain as early as E12.5. Induction during late embryonic stages showed confined recombination not only in the choroid plexus but also in the ventricular walls of the brain. Recombination induced during postnatal periods expanded to include epithelia of the lungs, testis, oviduct, and brain. Using these mice, we confirmed our recent discovery of a perinatally derived neuronal population in the mouse olfactory bulbs, which is derived from the Foxj1 lineage. Our Foxj1(CreERT2::GFP) knock-in mouse will be a powerful tool for studying molecular mechanisms associated with the continuum of cells that form the Foxj1 lineage, and for assessing their physiological significance during development and aging.

Deep learning-based adaptive optics for light sheet fluorescence microscopy.

Light sheet fluorescence microscopy (LSFM) is a high-speed imaging technique that is often used to image intact tissue-cleared specimens with cellular or subcellular resolution. Like other optical imaging systems, LSFM suffers from sample-induced optical aberrations that decrement imaging quality. Optical aberrations become more severe when imaging a few millimeters deep into tissue-cleared specimens, complicating subsequent analyses. Adaptive optics are commonly used to correct sample-induced aberrations using a deformable mirror. However, routinely used sensorless adaptive optics techniques are slow, as they require multiple images of the same region of interest to iteratively estimate the aberrations. In addition to the fading of fluorescent signal, this is a major limitation as thousands of images are required to image a single intact organ even without adaptive optics. Thus, a fast and accurate aberration estimation method is needed. Here, we used deep-learning techniques to estimate sample-induced aberrations from only two images of the same region of interest in cleared tissues. We show that the application of correction using a deformable mirror greatly improves image quality. We also introduce a sampling technique that requires a minimum number of images to train the network. Two conceptually different network architectures are compared; one that shares convolutional features and another that estimates each aberration independently. Overall, we have presented an efficient way to correct aberrations in LSFM and to improve image quality.

COMBINe enables automated detection and classification of neurons and astrocytes in tissue-cleared mouse brains.

Tissue clearing renders entire organs transparent to accelerate whole-tissue imaging; for example, with light-sheet fluorescence microscopy. Yet, challenges remain in analyzing the large resulting 3D datasets that consist of terabytes of images and information on millions of labeled cells. Previous work has established pipelines for automated analysis of tissue-cleared mouse brains, but the focus there was on single-color channels and/or detection of nuclear localized signals in relatively low-resolution images. Here, we present an automated workflow (COMBINe, Cell detectiOn in Mouse BraIN) to map sparsely labeled neurons and astrocytes in genetically distinct mouse forebrains using mosaic analysis with double markers (MADM). COMBINe blends modules from multiple pipelines with RetinaNet at its core. We quantitatively analyzed the regional and subregional effects of MADM-based deletion of the epidermal growth factor receptor (EGFR) on neuronal and astrocyte populations in the mouse forebrain.

Enhancing Light-Sheet Fluorescence Microscopy Illumination Beams through Deep Design Optimization.

Light sheet fluorescence microscopy (LSFM) provides the benefit of optical sectioning coupled with rapid acquisition times for imaging of tissue-cleared specimen. This allows for high-resolution 3D imaging of large tissue volumes. Inherently to LSFM, the quality of the imaging heavily relies on the characteristics of the illumination beam, with the notion that the illumination beam only illuminates a thin section that is being imaged. Therefore, substantial efforts are dedicated to identifying slender, non-diffracting beam profiles that can yield uniform and high-contrast images. An ongoing debate concerns the employment of the most optimal illumination beam; Gaussian, Bessel, Airy patterns and/or others. Comparisons among different beam profiles is challenging as their optimization objective is often different. Given that our large imaging datasets (~0.5TB images per sample) is already analyzed using deep learning models, we envisioned a different approach to this problem by hypothesizing that we can tailor the illumination beam to boost the deep learning models performance. We achieve this by integrating the physical LSFM illumination model after passing through a variable phase mask into the training of a cell detection network. Here we report that the joint optimization continuously updates the phase mask, improving the image quality for better cell detection. Our method's efficacy is demonstrated through both simulations and experiments, revealing substantial enhancements in imaging quality compared to traditional Gaussian light sheet. We offer valuable insights for designing microscopy systems through a computational approach that exhibits significant potential for advancing optics design that relies on deep learning models for analysis of imaging datasets.

Bulk and mosaic deletions of Egfr reveal regionally defined gliogenesis in the developing mouse forebrain.

The epidermal growth factor receptor (EGFR) plays a role in cell proliferation and differentiation during healthy development and tumor growth; however, its requirement for brain development remains unclear. Here we used a conditional mouse allele for Egfr to examine its contributions to perinatal forebrain development at the tissue level. Subtractive bulk ventral and dorsal forebrain deletions of Egfr uncovered significant and permanent decreases in oligodendrogenesis and myelination in the cortex and corpus callosum. Additionally, an increase in astrogenesis or reactive astrocytes in effected regions was evident in response to cortical scarring. Sparse deletion using mosaic analysis with double markers (MADM) surprisingly revealed a regional requirement for EGFR in rostrodorsal, but not ventrocaudal glial lineages including both astrocytes and oligodendrocytes. The EGFR-independent ventral glial progenitors may compensate for the missing EGFR-dependent dorsal glia in the bulk Egfr-deleted forebrain, potentially exposing a regenerative population of gliogenic progenitors in the mouse forebrain.

Specification of a Foxj1-dependent lineage in the forebrain is required for embryonic-to-postnatal transition of neurogenesis in the olfactory bulb.

Establishment of a neural stem cell niche in the postnatal subependymal zone (SEZ) and the rostral migratory stream (RMS) is required for postnatal and adult neurogenesis in the olfactory bulbs (OB). We report the discovery of a cellular lineage in the SEZ-RMS-OB continuum, the specification of which is dependent on the expression of the forkhead transcription factor Foxj1 in mice. Spatially and temporally restricted Foxj1+ neuronal progenitors emerge during embryonic periods, surge during perinatal development, and are active only for the first few postnatal weeks. We show that the development of the unique Foxj1-derived lineage is dependent on Foxj1 expression and is required for overall postnatal neurogenesis in the OB. Strikingly, the production of neurons from Foxj1+ progenitors significantly declines after the early postnatal weeks, but Foxj1-derived neurons in the OB persist during adult periods. For the first time, our study identifies the time- and region-specific activity of a perinatal progenitor domain that is required for transition and progression of OB neurogenesis from the embryonic-to-postnatal periods.

FoxJ1-dependent gene expression is required for differentiation of radial glia into ependymal cells and a subset of astrocytes in the postnatal brain.

Neuronal specification occurs at the periventricular surface of the embryonic central nervous system. During early postnatal periods, radial glial cells in various ventricular zones of the brain differentiate into ependymal cells and astrocytes. However, mechanisms that drive this time- and cell-specific differentiation remain largely unknown. Here, we show that expression of the forkhead transcription factor FoxJ1 in mice is required for differentiation into ependymal cells and a small subset of FoxJ1(+) astrocytes in the lateral ventricles, where these cells form a postnatal neural stem cell niche. Moreover, we show that a subset of FoxJ1(+) cells harvested from the stem cell niche can self-renew and possess neurogenic potential. Using a transcriptome comparison of FoxJ1-null and wild-type microdissected tissue, we identified candidate genes regulated by FoxJ1 during early postnatal development. The list includes a significant number of microtubule-associated proteins, some of which form a protein complex that could regulate the transport of basal bodies to the ventricular surface of differentiating ependymal cells during FoxJ1-dependent ciliogenesis. Our results suggest that time- and cell-specific expression of FoxJ1 in the brain acts on an array of target genes to regulate the differentiation of ependymal cells and a small subset of astrocytes in the adult stem cell niche.

Erratum: Deep learning-based autofocus method enhances image quality in light-sheet fluorescence microscopy: publisher's note.

[This corrects the article on p. 5214 in vol. 12, PMID: 34513252.].

Illumination angle correction during image acquisition in light-sheet fluorescence microscopy using deep learning.

Light-sheet fluorescence microscopy (LSFM) is a high-speed imaging technique that provides optical sectioning with reduced photodamage. LSFM is routinely used in life sciences for live cell imaging and for capturing large volumes of cleared tissues. LSFM has a unique configuration, in which the illumination and detection paths are separated and perpendicular to each other. As such, the image quality, especially at high resolution, largely depends on the degree of overlap between the detection focal plane and the illuminating beam. However, spatial heterogeneity within the sample, curved specimen boundaries, and mismatch of refractive index between tissues and immersion media can refract the well-aligned illumination beam. This refraction can cause extensive blur and non-uniform image quality over the imaged field-of-view. To address these issues, we tested a deep learning-based approach to estimate the angular error of the illumination beam relative to the detection focal plane. The illumination beam was then corrected using a pair of galvo scanners, and the correction significantly improved the image quality across the entire field-of-view. The angular estimation was based on calculating the defocus level on a pixel level within the image using two defocused images. Overall, our study provides a framework that can correct the angle of the light-sheet and improve the overall image quality in high-resolution LSFM 3D image acquisition.

Phosphorylation-dependent proteome of Marcks in ependyma during aging and behavioral homeostasis in the mouse forebrain.

Ependymal cells (ECs) line the ventricular surfaces of the mammalian central nervous system (CNS) and their development is indispensable to structural integrity and functions of the CNS. We previously reported that EC-specific genetic deletion of the myristoylated alanine-rich protein kinase C substrate (Marcks) disrupts barrier functions and elevates oxidative stress and lipid droplet accumulation in ECs causing precocious cellular aging. However, little is known regarding the mechanisms that mediate these changes in ECs. To gain insight into Marcks-mediated mechanisms, we performed mass spectrometric analyses on Marcks-associated proteins in young and aged ECs in the mouse forebrain using an integrated approach. Network analysis on annotated proteins revealed that the identified Marcks-associated complexes are in part involved in protein transport mechanisms in young ECs. In fact, we found perturbed intracellular vesicular trafficking in cultured ECs with selective deletion of Marcks (Marcks-cKO mice), or upon pharmacological alteration to phosphorylation status of Marcks. In comparison, Marcks-associated protein complexes in aged ECs appear to be involved in regulation of lipid metabolism and responses to oxidative stress. Confirming this, we found elevated signatures of inflammation in the cerebral cortices and the hippocampi of young Marcks-cKO mice. Interestingly, behavioral testing using a water maze task indicated that spatial learning and memory is diminished in young Marcks-cKO mice similar to aged wildtype mice. Taken together, our study provides first line of evidence for potential mechanisms that may mediate differential Marcks functions in young and old ECs, and their effect on forebrain homeostasis during aging.

Detection and classification of neurons and glial cells in the MADM mouse brain using RetinaNet.

The ability to automatically detect and classify populations of cells in tissue sections is paramount in a wide variety of applications ranging from developmental biology to pathology. Although deep learning algorithms are widely applied to microscopy data, they typically focus on segmentation which requires extensive training and labor-intensive annotation. Here, we utilized object detection networks (neural networks) to detect and classify targets in complex microscopy images, while simplifying data annotation. To this end, we used a RetinaNet model to classify genetically labeled neurons and glia in the brains of Mosaic Analysis with Double Markers (MADM) mice. Our initial RetinaNet-based model achieved an average precision of 0.90 across six classes of cells differentiated by MADM reporter expression and their phenotype (neuron or glia). However, we found that a single RetinaNet model often failed when encountering dense and saturated glial clusters, which show high variability in their shape and fluorophore densities compared to neurons. To overcome this, we introduced a second RetinaNet model dedicated to the detection of glia clusters. Merging the predictions of the two computational models significantly improved the automated cell counting of glial clusters. The proposed cell detection workflow will be instrumental in quantitative analysis of the spatial organization of cellular populations, which is applicable not only to preparations in neuroscience studies, but also to any tissue preparation containing labeled populations of cells.