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Carey, D.

Publications and source records attributed to Carey, D..

10 recordsLinked to original sources

A cargo receptor entrapment complex is a therapeutic node for genetically and clinically distinct proteinopathies

Severe proteinopathies--such as retinitis pigmentosa, a form of inherited blindness--are driven by genetic mutations that overwhelm the quality control of the post-endoplasmic reticulum (post-ER) secretory pathway, causing toxic protein accumulation. Here, we identify a therapeutic node defined by a hetero-oligomeric cargo receptor complex consisting of TMED7, 2, 9, and 10. This "entrapment complex" anchors structurally and functionally diverse mutant clients within the early secretory pathway via TMED7 binding to the integral Golgi protein GRASP55. Disruption of the entrapment complex results in the clearance of accumulated protein cargoes. In vivo ablation of the entrapment node via inducible genetic deletion or via the small molecule BRD7635 reverses histopathological hallmarks and rescues functional deficits in clinically distinct proteinopathies of the kidney and the eye, including mitigating vision loss in a mouse model of retinitis pigmentosa.

cell biology↗

Human Neocortical Glutamatergic Neurons Revealed Through Multimodal Profiling

The human neocortex underlies higher cognition and is the engine of complex thought. Yet our understanding of its neuronal diversity is limited by sparse access to tissue, inconsistent sampling across studies, and a lack of multiple modality data. Although single-cell transcriptomic taxonomies are an important framework for characterizing cell type diversity, transcriptomic information alone cannot reveal the cellular properties that define neuronal computations. To address this, we performed Patch-seq, a method for collecting Morphology, Electrophysiology, and Transcriptomic data from a single neuron. We focused on glutamatergic, neocortical, excitatory neurons, the principal long-range projecting neurons of the cortex, and systematically integrated their morphoelectric features with transcriptomic identity. In combination with spatial transcriptomic data, we interrogated 39 of 42 transcriptomically-defined neuron types with a layer-centric perspective. Morphoelectric properties, such as cortical depth, apical dendrite structure, and excitability clearly distinguish transcriptomic subclasses and support many finer transcriptomic types. Morphoelectric properties are influenced by spatial location in supragranular layers, while deeper layers exhibit greater heterogeneity. Cross-species comparisons reveal conserved subclass organization but pronounced differences in apical dendrite arborization between mouse and human, and surprising similarities between human and macaque. Together, these datasets provide a unified multimodal reference that advances our understanding of human cortical circuitry and establishes a foundation for experimental and computational studies of human brain function and disease.

neuroscience↗

Continuous cell type diversification throughout the embryonic and postnatal mouse visual cortex development

The mammalian cortex is composed of a highly diverse set of cell types and develops through a series of temporally regulated events that build out the cell type and circuit foundation for cortical function. The mechanisms underlying the development of different cell types remain elusive. Single-cell transcriptomics provides the capacity to systematically study cell types across the entire temporal range of cortical development. Here, we present a comprehensive and high-resolution transcriptomic and epigenomic cell type atlas of the developing mouse visual cortex. The atlas was built from a single-cell RNA-sequencing dataset of 568,674 high-quality single-cell transcriptomes and a single-nucleus Multiome dataset of 194,545 high-quality nuclei providing both transcriptomic and chromatin accessibility profiles, densely sampled throughout the embryonic and postnatal developmental stages from E11.5 to P56. We computationally reconstructed a transcriptomic developmental trajectory map of all excitatory, inhibitory, and non-neuronal cell types in the visual cortex, identifying branching points marking the emergence of new cell types at specific developmental ages and defining molecular signatures of cellular diversification. In addition to neurogenesis, gliogenesis and early postmitotic maturation in the embryonic stage which gives rise to all the cell classes and nearly all subclasses, we find that increasingly refined cell types emerge throughout the postnatal differentiation process, including the late emergence of many cell types during the eye-opening stage (P11-P14) and the onset of critical period (P21), suggesting continuous cell type diversification at different stages of cortical development. Throughout development, we find cooperative dynamic changes in gene expression and chromatin accessibility in specific cell types, identifying both chromatin peaks potentially regulating the expression of specific genes and transcription factors potentially regulating specific peaks. Furthermore, a single gene can be regulated by multiple peaks associated with different cell types and/or different developmental stages. Collectively, our study provides the most detailed dynamic molecular map directly associated with individual cell types and specific developmental events that reveals the molecular logic underlying the continuous refinement of cell type identities in the developing visual cortex.

neuroscience↗

Genetic barcodes for ash (Fraxinus) species and generation of new wide hybrids

Native ash tree species in Europe and North America are being devastated by ash dieback and the emerald ash borer, respectively. As worldwide ash species differ in their level of susceptibility to these threats, hybrid breeding may allow resistance to be transferred among species. However, we do not know the extent to which distantly related ash species can be crossed, and many ash species are difficult to identify from morphology alone leading to some mislabelling in living collections. Here, we develop a genetic barcode system for the identification of Fraxinus species based on three low-copy-number protein coding genes. We also conduct experimental crosses among ash species in different sections. Our barcodes are effective in identifying ash samples to sectional level and in some cases to species level, and can also identify hybrids. They highlight that F. mandshurica, F. platypoda and F. chiisanensis may be frequently mistaken for one another in living collections. We succeeded in generating ten wide hybrid plants: two of section Melioides (species: F. pennsylvanica) {square} section Fraxinus (species: F. excelsior) and eight of section Ornus (species unclear) {square} section Fraxinus (species: F. excelsior). One hybrid from each of our crosses has survived natural infection with the ash dieback pathogen in Ireland. We also discovered a hybrid between section Melioides (species: F. latifolia) {square} section Fraxinus (species: F. excelsior) formed spontaneously in the ash collection at Kew. Our findings facilitate the deployment of global ash species diversity in response to alien pests and pathogens. Societal impact statementThe world-wide diversity of ash trees includes genetic information encoding resistance to the ash dieback fungus and the emerald ash borer beetle, which are currently devastating ash populations in Europe and North America. In order to mobilise this genetic diversity in conventional breeding programmes we need to be able to accurately identify ash species from around the world, and cross them with one another. Here, we present a genetic barcoding system for ash species, and a series of hybridisation experiments between European ash and other species. Two of the hybrids show early promise against ash dieback.

plant biology↗

Cell-type specific molecular signatures of aging revealed in a brain-wide transcriptomic cell-type atlas

Biological aging can be defined as a gradual loss of homeostasis across various aspects of molecular and cellular function. Aging is a complex and dynamic process which influences distinct cell types in a myriad of ways. The cellular architecture of the mammalian brain is heterogeneous and diverse, making it challenging to identify precise areas and cell types of the brain that are more susceptible to aging than others. Here, we present a high-resolution single-cell RNA sequencing dataset containing [~]1.2 million high-quality single-cell transcriptomic profiles of brain cells from young adult and aged mice across both sexes, including areas spanning the forebrain, midbrain, and hindbrain. We find age-associated gene expression signatures across nearly all 130+ neuronal and non-neuronal cell subclasses we identified. We detect the greatest gene expression changes in non-neuronal cell types, suggesting that different cell types in the brain vary in their susceptibility to aging. We identify specific, age-enriched clusters within specific glial, vascular, and immune cell types from both cortical and subcortical regions of the brain, and specific gene expression changes associated with cell senescence, inflammation, decrease in new myelination, and decreased vasculature integrity. We also identify genes with expression changes across multiple cell subclasses, pointing to certain mechanisms of aging that may occur across wide regions or broad cell types of the brain. Finally, we discover the greatest gene expression changes in cell types localized to the third ventricle of the hypothalamus, including tanycytes, ependymal cells, and Tbx3+ neurons found in the arcuate nucleus that are part of the neuronal circuits regulating food intake and energy homeostasis. These findings suggest that the area surrounding the third ventricle in the hypothalamus may be a hub for aging in the mouse brain. Overall, we reveal a dynamic landscape of cell-type-specific transcriptomic changes in the brain associated with normal aging that will serve as a foundation for the investigation of functional changes in the aging process and the interaction of aging and diseases.

neuroscience↗

A high-resolution transcriptomic and spatial atlas of cell types in the whole mouse brain

The mammalian brain is composed of millions to billions of cells that are organized into numerous cell types with specific spatial distribution patterns and structural and functional properties. An essential step towards understanding brain function is to obtain a parts list, i.e., a catalog of cell types, of the brain. Here, we report a comprehensive and high-resolution transcriptomic and spatial cell type atlas for the whole adult mouse brain. The cell type atlas was created based on the combination of two single-cell-level, whole-brain-scale datasets: a single- cell RNA-sequencing (scRNA-seq) dataset of [~]7 million cells profiled, and a spatially resolved transcriptomic dataset of [~]4.3 million cells using MERFISH. The atlas is hierarchically organized into five nested levels of classification: 7 divisions, 32 classes, 306 subclasses, 1,045 supertypes and 5,200 clusters. We systematically analyzed the neuronal, non-neuronal, and immature neuronal cell types across the brain and identified a high degree of correspondence between transcriptomic identity and spatial specificity for each cell type. The results reveal unique features of cell type organization in different brain regions, in particular, a dichotomy between the dorsal and ventral parts of the brain: the dorsal part contains relatively fewer yet highly divergent neuronal types, whereas the ventral part contains more numerous neuronal types that are more closely related to each other. We also systematically characterized cell-type specific expression of neurotransmitters, neuropeptides, and transcription factors. The study uncovered extraordinary diversity and heterogeneity in neurotransmitter and neuropeptide expression and co-expression patterns in different cell types across the brain, suggesting they mediate a myriad of modes of intercellular communications. Finally, we found that transcription factors are major determinants of cell type classification in the adult mouse brain and identified a combinatorial transcription factor code that defines cell types across all parts of the brain. The whole-mouse-brain transcriptomic and spatial cell type atlas establishes a benchmark reference atlas and a foundational resource for deep and integrative investigations of cell type and circuit function, development, and evolution of the mammalian brain.

neuroscience↗

Connectome-based predictive modeling of cognitive reserve using task-based functional connectivity

Cognitive reserve supports cognitive function in the presence of pathology or atrophy. Functional neuroimaging may enable direct and accurate measurement of cognitive reserve which could have considerable clinical potential. The present study aimed to develop and validate a measure of cognitive reserve using task-based fMRI data that could then be applied to independent resting-state data. Connectome-based predictive modeling with leave-one-out cross-validation was applied to predict a residual measure of cognitive reserve using task-based functional connectivity from the Cognitive Reserve/Reference Ability Neural Network studies (n = 220, mean age = 51.91 years, SD = 17.04 years). Three network-strength predicted cognitive reserve measures were generated that accurately predicted the residual measures of unseen participants. The theoretical validity of these measures was established via a positive correlation with a socio-behavioural proxy of cognitive reserve (verbal intelligence) and a positive correlation with global cognition, independent of brain structure. This fitted model was then applied to external test data: resting-state functional connectivity data from The Irish Longitudinal Study on Ageing (TILDA, n = 294, mean age = 68.3 years, SD = 7.18 years). The network-strength predicted measures were not positively associated with a residual measure of cognitive reserve nor with measures of verbal intelligence and global cognition. The present study demonstrated that task-based functional connectivity data can be used to generate theoretically valid measures of cognitive reserve. Further work is needed to establish if, and how, measures of cognitive reserve derived from task-based functional connectivity can be applied to independent resting-state data.

neuroscience↗

Anthropogenic marine debris and its dynamics across peri-urban and urban mangroves on Penang Island, Malaysia

Mangroves act as sinks to a variety of anthropogenic marine debris (AMD) forms. However, knowledge of their distribution and accumulation dynamics is limited. To address this shortfall, abundance, sorting, and diversity parameters of AMD were evaluated across the canopy of Penangs urban and peri-urban mangroves. Two urban and two peri-urban mangroves were sampled at different periods over 2 months, with differences constrained by possible changes in their wind fields, and neap-spring tidal development. Debris were counted and classified across transects parallel to the coastline at progressively higher water marks. Plastics made up most of the AMD across all sites. More AMD was retained in the urban sites, consistent with their larger resident population density. Diversity of debris forms were consistent with the type of land use and population livelihood in each area. The greatest differences in abundance, diversity, and evenness were recorded between the lower tidal zones and the remaining inner transects consistent with sorting towards the coastal edge in favour of plastic items. Overall, differences across transects and sites suggested: 1) the canopy and root structure within the main body of the mangrove efficiently retained debris with little sorting; and 2) debris deposited closer to the edge is increasingly sorted and lost to the water body in favour of smaller plastic items, for a constant wind field and irrespective of neap-spring phases. The findings show that mangrove areas are vulnerable to a constant build of potentially harmful debris with selective leakage and sorting of materials back to the water body closer to their coastal edges. For Penang Island, the study highlights the areas in need of attention and prioritization, lists the types of debris needing proper management, and will aid in the future monitoring, mitigation and/or rehabilitation of these sensitive ecosystems.

ecology↗

Brain-predicted age difference score is related to specific cognitive functions: A multi-site replication analysis

Brain-predicted age difference scores are calculated by subtracting chronological age from brain age, which is estimated using neuroimaging data. Positive scores reflect accelerated ageing and are associated with increased mortality risk and poorer physical function. To date, however, the relationship between brain-predicted age difference scores and specific cognitive functions has not been systematically examined using appropriate statistical methods. First, applying machine learning to 1,359 T1-weighted MRI scans, we predicted the relationship between chronological age and voxel-wise grey matter data. This model was then applied to MRI data from three independent datasets, significantly predicting chronological age in each dataset: Dokuz Eylul University (n=175), the Cognitive Reserve/Reference Ability Neural Network study (n=380), and The Irish Longitudinal Study on Ageing (n=487). Each independent dataset had rich neuropsychological data. Brain-predicted age difference scores were significantly negatively correlated with performance on measures of general cognitive status (two datasets); processing speed, visual attention, and cognitive flexibility (three datasets); visual attention and cognitive flexibility (two datasets); and semantic verbal fluency (two datasets). As such, there is firm evidence of correlations between increased brain-predicted age differences and reduced cognitive function in some domains that are implicated in cognitive ageing.

neuroscience↗

Quantitative MRI Provides Markers Of Intra-, Inter-Regional, And Age-Related Differences In Young Adult Cortical Microstructure

Measuring the structural composition of the cortex is critical to understanding typical development, yet few investigations in humans have charted markers in vivo that are sensitive to tissue microstructural attributes. Here, we used a well-validated quantitative MR protocol to measure four parameters (R1, MT, R2*, PD*) that differ in their sensitivity to facets of the tissue microstructural environment (R1, MT: myelin, macromolecular content; R2*: paramagnetic ions, i.e., iron; PD*: free water content). Mapping these parameters across cortical regions in a young adult cohort (18-30 years, N=93) revealed expected patterns of increased macromolecular content as well as reduced tissue water content in primary and primary adjacent cortical regions. Mapping across cortical depth within regions showed decreased expression of myelin and related processes - but increased tissue water content - when progressing from the grey/white to the grey/pial boundary, in all regions. Charting developmental change in cortical microstructure, we found that parameters with the greatest sensitivity to tissue myelin (R1 & MT) showed linear increases with age across frontal and parietal cortex (change 0.5-1.0% per year). Overlap of robust age effects for both parameters emerged in left inferior frontal, right parietal and bilateral pre-central regions. Our findings afford an improved understanding of ontogeny in early adulthood and offer normative quantitative MR data for inter- and intra-cortical composition, which may be used as benchmarks in further studies.\n\nHighlights O_LIWe mapped multi-parameter maps (MPMs) across and within cortical regions\nC_LIO_LIWe charted age effects on myelin and related processes at mid-cortical depth\nC_LIO_LIInter- and intra-regional differences in MPMs emerged at primary and association cortex\nC_LIO_LIIron-sensitive R2* map foci tended to overlap MPMs sensitive to myelin (R1, MT)\nC_LIO_LIR1 and MT increased with age (0.5-1.0% per year) in frontal and parietal cortex\nC_LI

neuroscience↗