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BackgroundGenetic mutations underlying familial Alzheimer's disease (AD) were identified decades ago, but the field is still in search of transformative therapies for patients. While mouse models based on overexpression of mutated transgenes have yielded key insights in mechanisms of disease, those models are subject to artifacts, including random genetic integration of the transgene, ectopic expression and non-physiological protein levels. The genetic engineering of novel mouse models using knock-in approaches addresses some of those limitations. With mounting evidence of the role played by microglia in AD, high-dimensional approaches to phenotype microglia in those models are critical to refine our understanding of the immune response in the brain.MethodsWe engineered a novel App knock-in mouse model (AppSAA) using homologous recombination to introduce three disease-causing coding mutations (Swedish, Arctic and Austrian) to the mouse App gene. Amyloid-β pathology, neurodegeneration, glial responses, brain metabolism and behavioral phenotypes were characterized in heterozygous and homozygous AppSAA mice at different ages in brain and/ or biofluids. Wild type littermate mice were used as experimental controls. We used in situ imaging technologies to define the whole-brain distribution of amyloid plaques and compare it to other AD mouse models and human brain pathology. To further explore the microglial response to AD relevant pathology, we isolated microglia with fibrillar Aβ content from the brain and performed transcriptomics and metabolomics analyses and in vivo brain imaging to measure energy metabolism and microglial response. Finally, we also characterized the mice in various behavioral assays.ResultsLeveraging multi-omics approaches, we discovered profound alteration of diverse lipids and metabolites as well as an exacerbated disease-associated transcriptomic response in microglia with high intracellular Aβ content. The AppSAA knock-in mouse model recapitulates key pathological features of AD such as a progressive accumulation of parenchymal amyloid plaques and vascular amyloid deposits, altered astroglial and microglial responses and elevation of CSF markers of neurodegeneration. Those observations were associated with increased TSPO and FDG-PET brain signals and a hyperactivity phenotype as the animals aged.DiscussionOur findings demonstrate that fibrillar Aβ in microglia is associated with lipid dyshomeostasis consistent with lysosomal dysfunction and foam cell phenotypes as well as profound immuno-metabolic perturbations, opening new avenues to further investigate metabolic pathways at play in microglia responding to AD-relevant pathogenesis. The in-depth characterization of pathological hallmarks of AD in this novel and open-access mouse model should serve as a resource for the scientific community to investigate disease-relevant biology.

The mammalian cortex is a laminar structure containing many areas and cell types that are densely interconnected in complex ways, and for which generalizable principles of organization remain mostly unknown. Here we describe a major expansion of the Allen Mouse Brain Connectivity Atlas resource.sup.1, involving around a thousand new tracer experiments in the cortex and its main satellite structure, the thalamus. We used Cre driver lines (mice expressing Cre recombinase) to comprehensively and selectively label brain-wide connections by layer and class of projection neuron. Through observations of axon termination patterns, we have derived a set of generalized anatomical rules to describe corticocortical, thalamocortical and corticothalamic projections. We have built a model to assign connection patterns between areas as either feedforward or feedback, and generated testable predictions of hierarchical positions for individual cortical and thalamic areas and for cortical network modules. Our results show that cell-class-specific connections are organized in a shallow hierarchy within the mouse corticothalamic network. Using mouse lines in which subsets of neurons are genetically labelled, the authors provide generalized anatomical rules for connections within and between the cortex and thalamus., Author(s): Julie A. Harris [sup.1] , Stefan Mihalas [sup.1] , Karla E. Hirokawa [sup.1] , Jennifer D. Whitesell [sup.1] , Hannah Choi [sup.1] [sup.2] , Amy Bernard [sup.1] , Phillip [...]

To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.tins.2009.06.001 Byline: Diego Restrepo, Wilder Doucette, Jennifer D. Whitesell, Thomas S. McTavish, Ernesto Salcedo Abstract: Animals that depend on smell for communication and survival extract multiple pieces of information from a single complex odor. Mice can collect information on sex, genotype, health and dietary status from urine scent marks, a stimulus made up of hundreds of molecules. This ability is all the more remarkable considering that natural odors are encountered against varying olfactory backgrounds; the olfactory system must therefore provide some mechanism for extracting the most relevant information. Here we discuss recent data indicating that the readout of olfactory input by mitral cells in the olfactory bulb can be modified by behavioral context. We speculate that the olfactory cortex plays a key role in tuning the readout of olfactory information from the olfactory bulb. Author Affiliation: Department of Cell and Developmental Biology and Neuroscience Program, University of Colorado Denver, Anschutz Medical Campus, Aurora, CO 80045, USA

The delayed-rectifier voltage-gated [K.sup.+] channel (Kv) 2.1 underlies the cardiac slow [K.sup.+] current in the rodent heart and is particularly interesting in that both its function and localization are regulated by many stimuli in neuronal systems. However, standard immunolocalization approaches do not detect cardiac Kv2.1; therefore, little is known regarding its localization in the heart. In the present study, we used recombinant adenovirus to determine the subcellular localization and lateral mobility of green fluorescent protein (GFP)-Kv2.1 and yellow fluorescent protein-Kv 1.4 in atrial and ventricular myocytes. In atrial myocytes, Kv2.1 formed large clusters on the cell surface similar to those observed in hippocampal neurons, whereas Kv 1.4 was evenly distributed over both the peripheral sarcolemma and the transverse tubules. However, fluorescence recovery after photobleach (FRAP) experiments indicate that atrial Kv2.1 was immobile, whereas Kv1.4 was mobile ([tau] = 252 [+ or -] 42 s). In ventricular myocytes, Kv2.1 did not form clusters and was localized primarily in the transverse-axial tubules and sarcolemma. In contrast, Kv1.4 was found only in transverse tubules and sarcolemma. FRAP studies revealed that Kv2.1 has a higher mobility in ventricular myocytes ([tau] = 479 [+ or -] 178 s), although its mobility is slower than Kv1.4 ([[tau].sub.1[ = 18.9 [+ or -] 2.3 s; [[tau].sub.2] = 305 [+ or -] 55 s). We also observed the movement of small, intracellular transport vesicles containing GFP-Kv2.1 within ventricular myocytes. These data are the first evidence of Kv2.1 localization in living myocytes and indicate that Kv2.1 may have distinct physiological roles in atrial and ventricular myocytes. ion channel localization; lateral diffusion; adenovirus; voltage-gated potassium channels; live cell confocal microscopy

A variety of Alzheimer's disease (AD) mouse models overexpress mutant forms of human amyloid precursor protein (APP), producing high levels of amyloid β (Aβ) and forming plaques. However, the degree to which these models mimic spatiotemporal patterns of Aβ deposition in brains of AD patients is unknown. Here, we mapped the spatial distribution of Aβ plaques across age in three APP‐overexpression mouse lines (APP/PS1, Tg2576, and hAPP‐J20) using in vivo labeling with methoxy‐X04, high throughput whole brain imaging, and an automated informatics pipeline. Images were acquired with high resolution serial two‐photon tomography and labeled plaques were detected using custom‐built segmentation algorithms. Image series were registered to the Allen Mouse Brain Common Coordinate Framework, a 3D reference atlas, enabling automated brain‐wide quantification of plaque density, number, and location. In both APP/PS1 and Tg2576 mice, plaques were identified first in isocortex, followed by olfactory, hippocampal, and cortical subplate areas. In hAPP‐J20 mice, plaque density was highest in hippocampal areas, followed by isocortex, with little to no involvement of olfactory or cortical subplate areas. Within the major brain divisions, distinct regions were identified with high (or low) plaque accumulation; for example, the lateral visual area within the isocortex of APP/PS1 mice had relatively higher plaque density compared with other cortical areas, while in hAPP‐J20 mice, plaques were densest in the ventral retrosplenial cortex. In summary, we show how whole brain imaging of amyloid pathology in mice reveals the extent to which a given model recapitulates the regional Aβ deposition patterns described in AD. [ABSTRACT FROM AUTHOR]

Lateral inhibition between neurons occurs in many different sensory systems, where it can perform such functions as contrast enhance-ment. In the olfactory bulb, lateral inhibition may occur between odorant receptor-specific glomeruli that are linked anatomically by GABAergic granule cells (GCs) and cells within the glomerular layer, although evidence supporting lateral inhibition at a functional level is modest. Here, we used patch-clamp, imaging, and glutamate uncaging methods in rat olfactory bulb slices to test for the presence of interglomerular lateral inhibition, as well as its underlying mechanisms. We found that a conditioning stimulus applied at one or a small group of glomeruli could suppress stimulus-evoked excitation of output mitral cells (MCs) at another glomerulus for interstimulus intervals of 20 -50 ms and glomerular separations of up to 600 /xm. The observed lateral inhibition was entirely dependent on circuitry within the glomerular layer, rather than GCs, and it involved GABAergic synaptic inputs that were targeted mainly onto tufted cells, which act as intermediaries in the excitation between olfactory sensory neurons and MCs. The key cell type responsible for mediating lateral interactions between glomeruli were GABAergic short-axon cells. These results suggest a functional segregation of GABAergic cells within the bulb, with one set located in the glomerular layer mediating suppression of MC spiking across glomeruli, and a second set, the GCs, synchronizing different glomeruli. [ABSTRACT FROM AUTHOR]

Within the olfactory system, information flow from the periphery onto output mitral cells (MCs) of the olfactory bulb (OB) has been thought to be mediated by direct synaptic inputs from olfactory sensory neurons (OSNs). Here, we performed patch-clamp measurements in rat and mouse OB slices to investigate mechanisms of OSN signaling onto MCs, including the assumption of a direct path, using electrical and optogenetic stimulation methods that selectively activated OSNs. We found that MCs are in fact not typically activated by direct OSN inputs and instead require a multistep, diffuse mechanism involving another glutamatergic cell type, the tufted cells. The preference for a multistep mechanism reflects the fact that signals arising from direct OSN inputs are drastically shunted by connexin 36-mediated gap junctions on MCs, but not tufted cells. An OB circuit with tufted cells intermediate between OSNs and MCs suggests that considerable processing of olfactory information occurs before its reaching MCs. [ABSTRACT FROM AUTHOR]

The delayed-rectifier voltage-gated K+ channel (Kv) 2.1 underlies the cardiac slow K+ current in the rodent heart and is particularly interesting in that both its function and localization are regulated by many stimuli in neuronal systems. However, standard immunolocalization approaches do not detect cardiac Kv2.1; therefore, little is known regarding its localization in the heart. In the present study, we used recombinant adenovirus to determine the subcellular localization and lateral mobility of green fluorescent protein (GFP)-Kv2.1 and yellow fluorescent protein-Kv1.4 in atrial and ventricular myocytes. In atrial myocytes, Kv2.1 formed large clusters on the cell surface similar to those observed in hippocampal neurons, whereas Ky 1.4 was evenly distributed over both the peripheral sarcolemma and the transverse tubules. However, fluorescence recovery after photobleach (FRAP) experiments indicate that atrial Kv2.1 was immobile, whereas Kv1.4 was mobile (π = 252 ± 42 s). In ventricular myocytes, Kv2.1 did not form clusters and was localized primarily in the transverse-axial tubules and sarcolemma. In contrast, Kv1.4 was found only in transverse tubules and sarcolemma. FRAP studies revealed that Kv2.1 has a higher mobility in ventricular myocytes (π = 479 ± 178 s), although its mobility is slower than Kv1.4 (π = 18.9 ± 2.3 s; π2 = 305 ± 55 s). We also observed the movement of small, intracellular transport vesicles containing GFP-Kv2.1 within ventricular myocytes. These data are the first evidence of Kv2.1 localization in living myocytes and indicate that Kv2.1 may have distinct physiological roles in atrial and ventricular myocytes. [ABSTRACT FROM AUTHOR]

Ion channel localization to specific cell surface regions is essential for proper neuronal function. The Kv2.1 K+ channel forms large clusters on the plasma membrane of hippocampal neurons and transfected human embryonic kidney (HEK) cells. Using live cell imaging, we address mechanisms underlying this Kv2.1 clustering in both HEK cells and cultured hippocampal neurons. The Kv2.1-containing surface clusters have properties unlike those expected for a scaffolding protein bound channel. After channel is delivered to the plasma membrane via intracellular transport vesicles, it remains localized at the insertion site. Fluorescence recovery after photobleaching (FRAP) and quantum dot tracking experiments indicate that channel within the surface cluster is mobile (FRAP, τ = 14.1 ± 1.5 and 11.5 ± 6.1 s in HEK cells and neurons, respectively). The cluster perimeter is not static, because after fusion of adjacent clusters, green fluorescent protein (GFP)-Kv2.1 completely exchanged between the two domains within 60s. Treatment of hippocampal neurons expressing GFP-Kv2.1 with 5 µM latrunculin A resulted in a significant increase in average cluster size from 0.89 ± 0.16 µm² to 12.15±1.4 µm² with a concomitant decrease in cluster number. Additionally, Kv2.1 was no longer restricted to the cell body, suggesting a role for cortical actin in both cluster maintenance and localization. Thus, Kv2.1 surface domains likely trap mobile Kv2.1 channels within a well defined, but fluid, perimeter rather than being tightly bound to a scaffolding protein-containing complex. Channel moves directly into these clusters via trafficking vesicles. Such domains allow for efficient trafficking to the cell surface while sequestering channel with signaling proteins. [ABSTRACT FROM AUTHOR]

The Allen Mouse Brain Connectivity Atlas consists of anterograde tracing experiments targeting diverse structures and classes of projecting neurons. Beyond regional anterograde tracing done in C57BL/6 wild-type mice, a large fraction of experiments are performed using transgenic Cre-lines. This allows access to cell-class-specific whole-brain connectivity information, with class defined by the transgenic lines. However, even though the number of experiments is large, it does not come close to covering all existing cell classes in every area where they exist. Here, we study how much we can fill in these gaps and estimate the cell-class-specific connectivity function given the simplifying assumptions that nearby voxels have smoothly varying projections, but that these projection tensors can change sharply depending on the region and class of the projecting cells. This paper describes the conversion of Cre-line tracer experiments into class-specific connectivity matrices representing the connection strengths between source and target structures. We introduce and validate a novel statistical model for creation of connectivity matrices. We extend the Nadaraya-Watson kernel learning method that we previously used to fill in spatial gaps to also fill in gaps in cell-class connectivity information. To do this, we construct a "cell-class space" based on class-specific averaged regionalized projections and combine smoothing in 3D space as well as in this abstract space to share information between similar neuron classes. Using this method, we construct a set of connectivity matrices using multiple levels of resolution at which discontinuities in connectivity are assumed. We show that the connectivities obtained from this model display expected cell-type- and structure-specific connectivities. We also show that the wild-type connectivity matrix can be factored using a sparse set of factors, and analyze the informativeness of this latent variable model., Competing Interests: Competing Interests: The authors have declared that no competing interests exist., (© 2023 Massachusetts Institute of Technology.)

Knowledge of mesoscopic brain connectivity is important for understanding inter- and intraregion information processing. Models of structural connectivity are typically constructed and analyzed with the assumption that regions are homogeneous. We instead use the Allen Mouse Brain Connectivity Atlas to construct a model of whole-brain connectivity at the scale of 100 μm voxels. The data consist of 428 anterograde tracing experiments in wild type C57BL/6J mice, mapping fluorescently labeled neuronal projections brain-wide. Inferring spatial connectivity with this dataset is underdetermined, since the approximately 2 × 10 5 source voxels outnumber the number of experiments. To address this issue, we assume that connection patterns and strengths vary smoothly across major brain divisions. We model the connectivity at each voxel as a radial basis kernel-weighted average of the projection patterns of nearby injections. The voxel model outperforms a previous regional model in predicting held-out experiments and compared with a human-curated dataset. This voxel-scale model of the mouse connectome permits researchers to extend their previous analyses of structural connectivity to much higher levels of resolution, and it allows for comparison with functional imaging and other datasets., Competing Interests: Competing Interests: The authors have declared that no competing interests exist.