Distributed X chromosome inactivation in brain circuitry is associated with X-linked disease penetrance of behavior.

The precise anatomical degree of brain X chromosome inactivation (XCI) that is sufficient to alter X-linked disorders in females is unclear. Here, we quantify whole-brain XCI at single-cell resolution to discover a prevalent activation ratio of maternal to paternal X at 60:40 across all divisions of the adult brain. This modest, non-random XCI influences X-linked disease penetrance: maternal transmission of the fragile X mental retardation 1 (Fmr1)-knockout (KO) allele confers 55% of total brain cells with mutant X-active, which is sufficient for behavioral penetrance, while 40% produced from paternal transmission is tolerated. Local XCI mosaicism within affected maternal Fmr1-KO mice further specifies sensorimotor versus social anxiety phenotypes depending on which distinct brain circuitry is most affected, with only a 50%-55% mutant X-active threshold determining penetrance. Thus, our results define a model of X-linked disease penetrance in females whereby distributed XCI among single cells populating brain circuitries can regulate the behavioral penetrance of an X-linked mutation.

Modeling the cell-type-specific mesoscale murine connectome with anterograde tracing experiments.

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.

Endogenous pathology in tauopathy mice progresses via brain networks.

Neurodegenerative tauopathies are hypothesized to propagate via brain networks. This is uncertain because we have lacked precise network resolution of pathology. We therefore developed whole-brain staining methods with anti-p-tau nanobodies and imaged in 3D PS19 tauopathy mice, which have pan-neuronal expression of full-length human tau containing the P301S mutation. We analyzed patterns of p-tau deposition across established brain networks at multiple ages, testing the relationship between structural connectivity and patterns of progressive pathology. We identified core regions with early tau deposition, and used network propagation modeling to determine the link between tau pathology and connectivity strength. We discovered a bias towards retrograde network-based propagation of tau. This novel approach establishes a fundamental role for brain networks in tau propagation, with implications for human disease.

Regional and cell-type-specific afferent and efferent projections of the mouse claustrum.

The claustrum (CLA) is a conspicuous subcortical structure interconnected with cortical and subcortical regions. Its regional anatomy and cell-type-specific connections in the mouse remain not fully determined. Using multimodal reference datasets, we confirmed the delineation of the mouse CLA as a single group of neurons embedded in the agranular insular cortex. We quantitatively investigated brain-wide inputs and outputs of CLA using bulk anterograde and retrograde viral tracing data and single neuron tracing data. We found that the prefrontal module has more cell types projecting to the CLA than other cortical modules, with layer 5 IT neurons predominating. We found nine morphological types of CLA principal neurons that topographically innervate functionally linked cortical targets, preferentially the midline cortical areas, secondary motor area, and entorhinal area. Together, this study provides a detailed wiring diagram of the cell-type-specific connections of the mouse CLA, laying a foundation for studying its functions at the cellular level.

A whole-brain monosynaptic input connectome to neuron classes in mouse visual cortex.

Identification of structural connections between neurons is a prerequisite to understanding brain function. Here we developed a pipeline to systematically map brain-wide monosynaptic input connections to genetically defined neuronal populations using an optimized rabies tracing system. We used mouse visual cortex as the exemplar system and revealed quantitative target-specific, layer-specific and cell-class-specific differences in its presynaptic connectomes. The retrograde connectivity indicates the presence of ventral and dorsal visual streams and further reveals topographically organized and continuously varying subnetworks mediated by different higher visual areas. The visual cortex hierarchy can be derived from intracortical feedforward and feedback pathways mediated by upper-layer and lower-layer input neurons. We also identify a new role for layer 6 neurons in mediating reciprocal interhemispheric connections. This study expands our knowledge of the visual system connectomes and demonstrates that the pipeline can be scaled up to dissect connectivity of different cell populations across the mouse brain.

GPU-Accelerated All-Atom Particle-Mesh Ewald Continuous Constant pH Molecular Dynamics in Amber.

Constant pH molecular dynamics (MD) simulations sample protonation states on the fly according to the conformational environment and user specified pH conditions; however, the current accuracy is limited due to the use of implicit-solvent models or a hybrid solvent scheme. Here, we report the first GPU-accelerated implementation, parametrization, and validation of the all-atom continuous constant pH MD (CpHMD) method with particle-mesh Ewald (PME) electrostatics in the Amber22 pmemd.cuda engine. The titration parameters for Asp, Glu, His, Cys, and Lys were derived for the CHARMM c22 and Amber ff14sb and ff19sb force fields. We then evaluated the PME-CpHMD method using the asynchronous pH replica-exchange titration simulations with the c22 force field for six benchmark proteins, including BBL, hen egg white lysozyme (HEWL), staphylococcal nuclease (SNase), thioredoxin, ribonuclease A (RNaseA), and human muscle creatine kinase (HMCK). The root-mean-square deviation from the experimental pKa's of Asp, Glu, His, and Cys is 0.76 pH units, and the Pearson's correlation coefficient for the pKa shifts with respect to model values is 0.80. We demonstrated that a finite-size correction or much enlarged simulation box size can remove a systematic error of the calculated pKa's and improve agreement with experiment. Importantly, the simulations captured the relevant biology in several challenging cases, e.g., the titration order of the catalytic dyad Glu35/Asp52 in HEWL and the coupled residues Asp19/Asp21 in SNase, the large pKa upshift of the deeply buried catalytic Asp26 in thioredoxin, and the large pKa downshift of the deeply buried catalytic Cys283 in HMCK. We anticipate that PME-CpHMD will offer proper pH control to improve the accuracies of MD simulations and enable mechanistic studies of proton-coupled dynamical processes that are ubiquitous in biology but remain poorly understood due to the lack of experimental tools and limitation of current MD simulations.

Novel App knock-in mouse model shows key features of amyloid pathology and reveals profound metabolic dysregulation of microglia.

BACKGROUND: Genetic 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. METHODS: We 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-ß 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 Aß 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. RESULTS: Leveraging 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 Aß 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. DISCUSSION: Our findings demonstrate that fibrillar Aß 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.

A Guide to the Continuous Constant pH Molecular Dynamics Methods in Amber and CHARMM [Article v1.0].

Like temperature and pressure, solution pH is an important environmental variable in biomolecular simulations. Virtually all proteins depend on pH to maintain their structure and function. In conventional molecular dynamics (MD) simulations of proteins, pH is implicitly accounted for by assigning and fixing protonation states of titratable sidechains. This is a significant limitation, as the assigned protonation states may be wrong and they may change during dynamics. In this tutorial, we guide the reader in learning and using the various continuous constant pH MD methods in Amber and CHARMM packages, which have been applied to predict pK a values and elucidate proton-coupled conformational dynamics of a variety of proteins including enzymes and membrane transporters.

Genetic dissection of the glutamatergic neuron system in cerebral cortex.

Diverse types of glutamatergic pyramidal neurons mediate the myriad processing streams and output channels of the cerebral cortex1,2, yet all derive from neural progenitors of the embryonic dorsal telencephalon3,4. Here we establish genetic strategies and tools for dissecting and fate-mapping subpopulations of pyramidal neurons on the basis of their developmental and molecular programs. We leverage key transcription factors and effector genes to systematically target temporal patterning programs in progenitors and differentiation programs in postmitotic neurons. We generated over a dozen temporally inducible mouse Cre and Flp knock-in driver lines to enable the combinatorial targeting of major progenitor types and projection classes. Combinatorial strategies confer viral access to subsets of pyramidal neurons defined by developmental origin, marker expression, anatomical location and projection targets. These strategies establish an experimental framework for understanding the hierarchical organization and developmental trajectory of subpopulations of pyramidal neurons that assemble cortical processing networks and output channels.

Survey of spiking in the mouse visual system reveals functional hierarchy.

The anatomy of the mammalian visual system, from the retina to the neocortex, is organized hierarchically1. However, direct observation of cellular-level functional interactions across this hierarchy is lacking due to the challenge of simultaneously recording activity across numerous regions. Here we describe a large, open dataset-part of the Allen Brain Observatory2-that surveys spiking from tens of thousands of units in six cortical and two thalamic regions in the brains of mice responding to a battery of visual stimuli. Using cross-correlation analysis, we reveal that the organization of inter-area functional connectivity during visual stimulation mirrors the anatomical hierarchy from the Allen Mouse Brain Connectivity Atlas3. We find that four classical hierarchical measures-response latency, receptive-field size, phase-locking to drifting gratings and response decay timescale-are all correlated with the hierarchy. Moreover, recordings obtained during a visual task reveal that the correlation between neural activity and behavioural choice also increases along the hierarchy. Our study provides a foundation for understanding coding and signal propagation across hierarchically organized cortical and thalamic visual areas.

Highlights from the Era of Open Source Web-Based Tools.

High digital connectivity and a focus on reproducibility are contributing to an open science revolution in neuroscience. Repositories and platforms have emerged across the whole spectrum of subdisciplines, paving the way for a paradigm shift in the way we share, analyze, and reuse vast amounts of data collected across many laboratories. Here, we describe how open access web-based tools are changing the landscape and culture of neuroscience, highlighting six free resources that span subdisciplines from behavior to whole-brain mapping, circuits, neurons, and gene variants.

Regional, Layer, and Cell-Type-Specific Connectivity of the Mouse Default Mode Network.

The evolutionarily conserved default mode network (DMN) is a distributed set of brain regions coactivated during resting states that is vulnerable to brain disorders. How disease affects the DMN is unknown, but detailed anatomical descriptions could provide clues. Mice offer an opportunity to investigate structural connectivity of the DMN across spatial scales with cell-type resolution. We co-registered maps from functional magnetic resonance imaging and axonal tracing experiments into the 3D Allen mouse brain reference atlas. We find that the mouse DMN consists of preferentially interconnected cortical regions. As a population, DMN layer 2/3 (L2/3) neurons project almost exclusively to other DMN regions, whereas L5 neurons project in and out of the DMN. In the retrosplenial cortex, a core DMN region, we identify two L5 projection types differentiated by in- or out-DMN targets, laminar position, and gene expression. These results provide a multi-scale description of the anatomical correlates of the mouse DMN.

Network structure of the mouse brain connectome with voxel resolution.

Fine-grained descriptions of brain connectivity are required to understand how neural information is processed and relayed across spatial scales. Previous investigations of the mouse brain connectome have used discrete anatomical parcellations, limiting spatial resolution and potentially concealing network attributes critical to connectome organization. Here, we provide a voxel-level description of the network and hierarchical structure of the directed mouse connectome, unconstrained by regional partitioning. We report a number of previously unappreciated organizational principles in the mammalian brain, including a directional segregation of hub regions into neural sink and sources, and a strategic wiring of neuromodulatory nuclei as connector hubs and critical orchestrators of network communication. We also find that the mouse cortical connectome is hierarchically organized along two superimposed cortical gradients reflecting unimodal-transmodal functional processing and a modality-specific sensorimotor axis, recapitulating a phylogenetically conserved feature of higher mammals. These findings advance our understanding of the foundational wiring principles of the mammalian connectome.

Linking axon morphology to gene expression: a strategy for neuronal cell-type classification.

To study how the brain drives cognition and behavior we need to understand its cellular composition. Advances in single-cell transcriptomics have revolutionized our ability to characterize neuronal diversity. To arrive at meaningful descriptions of cell types, however, gene expression must be linked to structural and functional properties. Axonal projection patterns are an appropriate measure, as they are diverse, change only gradually over time, and they influence and constrain circuit function. Here, we consider how efforts to map transcriptional and morphological diversity in the mouse brain could be linked to generate a modern taxonomy of the mouse brain.

A second X chromosome contributes to resilience in a mouse model of Alzheimer's disease.

A major sex difference in Alzheimer's disease (AD) is that men with the disease die earlier than do women. In aging and preclinical AD, men also show more cognitive deficits. Here, we show that the X chromosome affects AD-related vulnerability in mice expressing the human amyloid precursor protein (hAPP), a model of AD. XY-hAPP mice genetically modified to develop testicles or ovaries showed worse mortality and deficits than did XX-hAPP mice with either gonad, indicating a sex chromosome effect. To dissect whether the absence of a second X chromosome or the presence of a Y chromosome conferred a disadvantage on male mice, we varied sex chromosome dosage. With or without a Y chromosome, hAPP mice with one X chromosome showed worse mortality and deficits than did those with two X chromosomes. Thus, adding a second X chromosome conferred resilience to XY males and XO females. In addition, the Y chromosome, its sex-determining region Y gene (Sry), or testicular development modified mortality in hAPP mice with one X chromosome such that XY males with testicles survived longer than did XY or XO females with ovaries. Furthermore, a second X chromosome conferred resilience potentially through the candidate gene Kdm6a, which does not undergo X-linked inactivation. In humans, genetic variation in KDM6A was linked to higher brain expression and associated with less cognitive decline in aging and preclinical AD, suggesting its relevance to human brain health. Our study suggests a potential role for sex chromosomes in modulating disease vulnerability related to AD.

Distinct Transcriptomic Cell Types and Neural Circuits of the Subiculum and Prosubiculum along the Dorsal-Ventral Axis.

Subicular regions play important roles in spatial processing and many cognitive functions, and these are mainly attributed to the subiculum (Sub) rather than the prosubiculum (PS). Using single-cell RNA sequencing, we identify 27 transcriptomic cell types residing in sub-domains of the Sub and PS. Based on in situ expression of reliable transcriptomic markers, the precise boundaries of the Sub and PS are consistently defined along the dorsoventral axis. Using these borders to evaluate Cre-line specificity and tracer injections, we find bona fide Sub projections topographically to structures important for spatial processing and navigation. In contrast, the PS sends its outputs to widespread brain regions crucial for motivation, emotion, reward, stress, anxiety, and fear. The Sub and PS, respectively, dominate dorsal and ventral subicular regions and receive different afferents. These results reveal two molecularly and anatomically distinct circuits centered in the Sub and PS, respectively, providing a consistent explanation for historical data and a clearer foundation for future studies.

The Allen Mouse Brain Common Coordinate Framework: A 3D Reference Atlas.

Recent large-scale collaborations are generating major surveys of cell types and connections in the mouse brain, collecting large amounts of data across modalities, spatial scales, and brain areas. Successful integration of these data requires a standard 3D reference atlas. Here, we present the Allen Mouse Brain Common Coordinate Framework (CCFv3) as such a resource. We constructed an average template brain at 10 µm voxel resolution by interpolating high resolution in-plane serial two-photon tomography images with 100 µm z-sampling from 1,675 young adult C57BL/6J mice. Then, using multimodal reference data, we parcellated the entire brain directly in 3D, labeling every voxel with a brain structure spanning 43 isocortical areas and their layers, 329 subcortical gray matter structures, 81 fiber tracts, and 8 ventricular structures. CCFv3 can be used to analyze, visualize, and integrate multimodal and multiscale datasets in 3D and is openly accessible (https://atlas.brain-map.org/).

Individual structural features constrain the mouse functional connectome.

Whole brain dynamics intuitively depend upon the internal wiring of the brain; but to which extent the individual structural connectome constrains the corresponding functional connectome is unknown, even though its importance is uncontested. After acquiring structural data from individual mice, we virtualized their brain networks and simulated in silico functional MRI data. Theoretical results were validated against empirical awake functional MRI data obtained from the same mice. We demonstrate that individual structural connectomes predict the functional organization of individual brains. Using a virtual mouse brain derived from the Allen Mouse Brain Connectivity Atlas, we further show that the dominant predictors of individual structure-function relations are the asymmetry and the weights of the structural links. Model predictions were validated experimentally using tracer injections, identifying which missing connections (not measurable with diffusion MRI) are important for whole brain dynamics in the mouse. Individual variations thus define a specific structural fingerprint with direct impact upon the functional organization of individual brains, a key feature for personalized medicine.

Hierarchical organization of cortical and thalamic connectivity.

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 resource1, 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.

Classification of electrophysiological and morphological neuron types in the mouse visual cortex.

Understanding the diversity of cell types in the brain has been an enduring challenge and requires detailed characterization of individual neurons in multiple dimensions. To systematically profile morpho-electric properties of mammalian neurons, we established a single-cell characterization pipeline using standardized patch-clamp recordings in brain slices and biocytin-based neuronal reconstructions. We built a publicly accessible online database, the Allen Cell Types Database, to display these datasets. Intrinsic physiological properties were measured from 1,938 neurons from the adult laboratory mouse visual cortex, morphological properties were measured from 461 reconstructed neurons, and 452 neurons had both measurements available. Quantitative features were used to classify neurons into distinct types using unsupervised methods. We established a taxonomy of morphologically and electrophysiologically defined cell types for this region of the cortex, with 17 electrophysiological types, 38 morphological types and 46 morpho-electric types. There was good correspondence with previously defined transcriptomic cell types and subclasses using the same transgenic mouse lines.