Early role for a Na+,K+-ATPase (ATP1A3) in brain development

Osmotic equilibrium and membrane potential in animal cells depend on concentration gradients of sodium (Na+) and potassium (K+) ions across the plasma membrane, a function catalyzed by the Na+,K+-ATPase α-subunit. Here, we describe ATP1A3 variants encoding dysfunctional α3-subunits in children affected by polymicrogyria, a developmental malformation of the cerebral cortex characterized by abnormal folding and laminar organization. To gain cell-biological insights into the spatiotemporal dynamics of prenatal ATP1A3 expression, we built an ATP1A3 transcriptional atlas of fetal cortical development using mRNA in situ hybridization and transcriptomic profiling of ∼125,000 individual cells with single-cell RNA sequencing (Drop-seq) from 11 areas of the midgestational human neocortex. We found that fetal expression of ATP1A3 is most abundant to a subset of excitatory neurons carrying transcriptional signatures of the developing subplate, yet also maintains expression in nonneuronal cell populations. Moving forward a year in human development, we profiled ∼52,000 nuclei from four areas of an infant neocortex and show that ATP1A3 expression persists throughout early postnatal development, most predominantly in inhibitory neurons, including parvalbumin interneurons in the frontal cortex. Finally, we discovered the heteromeric Na+,K+-ATPase pump complex may form nonredundant cell-type–specific α-β isoform combinations, including α3-β1 in excitatory neurons and α3-β2 in inhibitory neurons. Together, the developmental malformation phenotype of affected individuals and single-cell ATP1A3 expression patterns point to a key role for α3 in human cortex development, as well as a cell-type basis for pre- and postnatal ATP1A3-associated diseases.

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Role for the Na+/K+ ATPase pump alpha 3 (ATP1A3) subunit in folding and lamination of the human neocortex

10.1101/2020.10.03.319137 ◽

2020 ◽

Author(s):

Richard S. Smith ◽

Marta Florio ◽

Shyam K. Akula ◽

Jennifer E. Neil ◽

Yidi Wang ◽

...

Keyword(s):

Neurological Diseases ◽

Expression Patterns ◽

Inhibitory Neurons ◽

Alpha Subunit ◽

Animal Cells ◽

Α Subunit ◽

Early Postnatal Development ◽

Human Neocortex ◽

Excitatory Neurons ◽

Subunit Isoforms

ABSTRACTOsmotic equilibrium and membrane potential in animal cells depend on concentration gradients of sodium (Na+) and potassium (K+) ions across the plasma membrane, a function that is catalyzed by the Na,K-ATPase alpha subunit. In vertebrates, four paralogous genes, ATP1A1-4, encode distinct alpha subunit isoforms (a1-a4), three of which (a1, a2, a3) are expressed in the brain, and two (a1, a3) predominantly in neurons. The a3 isoform, encoded by ATP1A3, is critical to neuronal physiology, and a growing spectrum of neurological diseases are associated with ATP1A3 pathogenic variants, with ages of onset ranging from early childhood to adulthood. Here, we describe ATP1A3 variants encoding dysfunctional a3 subunits in children affected by polymicrogyria, a developmental malformation of the cerebral cortex characterized by abnormal folding and laminar organization. To gain cell-biological insights into the spatiotemporal dynamics of prenatal ATP1A3 expression, we established a transcriptional atlas of ATP1A3 expression during cortical development using mRNA in situ hybridization and transcriptomic profiling of ~125,000 individual cells with single-cell RNA sequencing (Drop-Seq) from various areas of the midgestational human neocortex. We find that fetal expression of ATP1A3 is restricted to a subset of excitatory neurons carrying transcriptional signatures of neuronal activity and maturation characteristic of the developing subplate. Furthermore, by performing Drop-Seq on ~52,000 nuclei from four different areas of an infant human neocortex, we show that ATP1A3 expression persists throughout early postnatal development, not only within excitatory neurons across all cortical layers, but also and more predominantly in inhibitory neurons, with specific enrichment in fast-spiking basket cells. In addition, we show that ATP1A3 expression, both in fetal and postnatal neurons, tends to be higher in frontal cortical areas than in occipital areas, in a pattern consistent with the rostro-caudal maturation gradient of the human neocortex. Finally, we discover distinct co-expression patterns linking catalytic α subunit isoforms (ATP1A1,2,3) and auxiliary isoforms (ATP1B1,2,3), suggesting the ATPase pump may form non-redundant, cell-type specific α-β combinations. Together, the importance of the developmental phenotypes and dynamic expression patterns of ATP1A3 point to a key role for a3 in the development and function of human cortex.

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Single-cell transcriptomic analysis identifies neocortical developmental differences between human and mouse

10.1101/2020.04.23.056390 ◽

2020 ◽

Author(s):

Ziheng Zhou ◽

Shuguang Wang ◽

Dengwei Zhang ◽

Xiaosen Jiang ◽

Jie Li ◽

...

Keyword(s):

Cerebral Cortex ◽

Single Cell ◽

Developmental Trajectories ◽

Expression Patterns ◽

Development Stage ◽

Inhibitory Neurons ◽

Projection Neurons ◽

Cerebral Cortex Development ◽

Excitatory Neurons ◽

Human And Mouse

AbstractBackgroundThe specification and differentiation of neocortical projection neurons is a complex process under precise molecular regulation; however, little is known about the similarities and differences in cerebral cortex development between human and mouse at single-cell resolution.ResultsHere, using single-cell RNA-seq (scRNA-seq) data we explore the divergence and conservation of human and mouse cerebral cortex development using 18,446 and 7,610 neocortical cells. Systematic cross-species comparison reveals that the overall transcriptome profile in human cerebral cortex is similar to that in mouse such as cell types and their markers genes. By single-cell trajectories analysis we find human and mouse excitatory neurons have different developmental trajectories of neocortical projection neurons, ligand-receptor interactions and gene expression patterns. Further analysis reveals a refinement of neuron differentiation that occurred in human but not in mouse, suggesting that excitatory neurons in human undergo refined transcriptional states in later development stage. By contrast, for glial cells and inhibitory neurons we detected conserved developmental trajectories in human and mouse.ConclusionsTaken together, our study integrates scRNA-seq data of cerebral cortex development in human and mouse, and uncovers distinct developing models in neocortical projection neurons. The earlier activation of cognition -related genes in human may explain the differences in behavior, learning or memory abilities between the two species.

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Parallel RNA and DNA analysis after Deep-sequencing (PRDD-seq) reveals cell type specific lineage patterns in human brain

10.1101/2020.04.19.046904 ◽

2020 ◽

Author(s):

August Yue Huang ◽

Pengpeng Li ◽

Rachel E. Rodin ◽

Sonia N. Kim ◽

Yanmei Dou ◽

...

Keyword(s):

Human Brain ◽

Single Cell ◽

Cell Lineage ◽

Neuronal Cell ◽

Cell Types ◽

Inhibitory Neurons ◽

Cell Type ◽

Cell Divisions ◽

Excitatory Neurons ◽

The Brain

AbstractElucidating the lineage relationships among different cell types is key to understanding human brain development. Here we developed Parallel RNA and DNA analysis after Deep-sequencing (PRDD-seq), which combines RNA analysis of neuronal cell types with analysis of nested spontaneous DNA somatic mutations as cell lineage markers, identified from joint analysis of single cell and bulk DNA sequencing by single-cell MosaicHunter (scMH). PRDD-seq enables the first-ever simultaneous reconstruction of neuronal cell type, cell lineage, and sequential neuronal formation (“birthdate”) in postmortem human cerebral cortex. Analysis of two human brains showed remarkable quantitative details that relate mutation mosaic frequency to clonal patterns, confirming an early divergence of precursors for excitatory and inhibitory neurons, and an “inside-out” layer formation of excitatory neurons as seen in other species. In addition our analysis allows the first estimate of excitatory neuron-restricted precursors (about 10) that generate the excitatory neurons within a cortical column. Inhibitory neurons showed complex, subtype-specific patterns of neurogenesis, including some patterns of development conserved relative to mouse, but also some aspects of primate cortical interneuron development not seen in mouse. PRDD-seq can be broadly applied to characterize cell identity and lineage from diverse archival samples with single-cell resolution and in potentially any developmental or disease condition.Significance StatementStem cells and progenitors undergo a series of cell divisions to generate the neurons of the brain, and understanding this sequence is critical to studying the mechanisms that control cell division and migration in developing brain. Mutations that occur as cells divide are known as the basis of cancer, but have more recently been shown to occur with normal cell divisions, creating a permanent, forensic map of the clonal patterns that define the brain. Here we develop new technology to analyze both DNA mutations and RNA gene expression patterns in single cells from human postmortem brain, allowing us to define clonal patterns among different types of human brain neurons, gaining the first direct insight into how they form.

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Neuron-specific spinal cord translatomes reveal a neuropeptide code for mouse dorsal horn excitatory neurons

Scientific Reports ◽

10.1038/s41598-021-84667-y ◽

2021 ◽

Vol 11 (1) ◽

Cited By ~ 1

Author(s):

Rebecca Rani Das Gupta ◽

Louis Scheurer ◽

Pawel Pelczar ◽

Hendrik Wildner ◽

Hanns Ulrich Zeilhofer

Keyword(s):

Spinal Cord ◽

Dorsal Horn ◽

Functional Organization ◽

Affinity Purification ◽

Expression Patterns ◽

Inhibitory Neurons ◽

Dorsal Horn Neurons ◽

Expression Of Genes ◽

Excitatory Neurons ◽

Genes Encoding

AbstractThe spinal dorsal horn harbors a sophisticated and heterogeneous network of excitatory and inhibitory neurons that process peripheral signals encoding different sensory modalities. Although it has long been recognized that this network is crucial both for the separation and the integration of sensory signals of different modalities, a systematic unbiased approach to the use of specific neuromodulatory systems is still missing. Here, we have used the translating ribosome affinity purification (TRAP) technique to map the translatomes of excitatory glutamatergic (vGluT2+) and inhibitory GABA and/or glycinergic (vGAT+ or Gad67+) neurons of the mouse spinal cord. Our analyses demonstrate that inhibitory and excitatory neurons are not only set apart, as expected, by the expression of genes related to the production, release or re-uptake of their principal neurotransmitters and by genes encoding for transcription factors, but also by a differential engagement of neuromodulator, especially neuropeptide, signaling pathways. Subsequent multiplex in situ hybridization revealed eleven neuropeptide genes that are strongly enriched in excitatory dorsal horn neurons and display largely non-overlapping expression patterns closely adhering to the laminar and presumably also functional organization of the spinal cord grey matter.

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Comprehensive analysis of single cell ATAC-seq data with SnapATAC

Nature Communications ◽

10.1038/s41467-021-21583-9 ◽

2021 ◽

Vol 12 (1) ◽

Author(s):

Rongxin Fang ◽

Sebastian Preissl ◽

Yang Li ◽

Xiaomeng Hou ◽

Jacinta Lucero ◽

...

Keyword(s):

Single Cell ◽

Single Cell Analysis ◽

Expression Patterns ◽

Regulatory Elements ◽

Cellular Heterogeneity ◽

Specific Gene ◽

Open Chromatin ◽

Cell Type ◽

Process Data ◽

Cell Type Specific

AbstractIdentification of the cis-regulatory elements controlling cell-type specific gene expression patterns is essential for understanding the origin of cellular diversity. Conventional assays to map regulatory elements via open chromatin analysis of primary tissues is hindered by sample heterogeneity. Single cell analysis of accessible chromatin (scATAC-seq) can overcome this limitation. However, the high-level noise of each single cell profile and the large volume of data pose unique computational challenges. Here, we introduce SnapATAC, a software package for analyzing scATAC-seq datasets. SnapATAC dissects cellular heterogeneity in an unbiased manner and map the trajectories of cellular states. Using the Nyström method, SnapATAC can process data from up to a million cells. Furthermore, SnapATAC incorporates existing tools into a comprehensive package for analyzing single cell ATAC-seq dataset. As demonstration of its utility, SnapATAC is applied to 55,592 single-nucleus ATAC-seq profiles from the mouse secondary motor cortex. The analysis reveals ~370,000 candidate regulatory elements in 31 distinct cell populations in this brain region and inferred candidate cell-type specific transcriptional regulators.

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Identification of cell-type-specific marker genes from co-expression patterns in tissue samples

Bioinformatics ◽

10.1093/bioinformatics/btab257 ◽

2021 ◽

Author(s):

Yixuan Qiu ◽

Jiebiao Wang ◽

Jing Lei ◽

Kathryn Roeder

Keyword(s):

Single Cell ◽

Expression Patterns ◽

R Package ◽

Supplementary Information ◽

Marker Genes ◽

Specific Marker ◽

Cell Type ◽

Correlation Pattern ◽

Tissue Samples ◽

Bulk Data

Abstract Motivation Marker genes, defined as genes that are expressed primarily in a single cell type, can be identified from the single cell transcriptome; however, such data are not always available for the many uses of marker genes, such as deconvolution of bulk tissue. Marker genes for a cell type, however, are highly correlated in bulk data, because their expression levels depend primarily on the proportion of that cell type in the samples. Therefore, when many tissue samples are analyzed, it is possible to identify these marker genes from the correlation pattern. Results To capitalize on this pattern, we develop a new algorithm to detect marker genes by combining published information about likely marker genes with bulk transcriptome data in the form of a semi-supervised algorithm. The algorithm then exploits the correlation structure of the bulk data to refine the published marker genes by adding or removing genes from the list. Availability and implementation We implement this method as an R package markerpen, hosted on CRAN (https://CRAN.R-project.org/package=markerpen). Supplementary information Supplementary data are available at Bioinformatics online.

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Revealing immune responses in the Mycobacterium avium subsp. paratuberculosis-infected THP-1 cells using single cell RNA-sequencing

PLoS ONE ◽

10.1371/journal.pone.0254194 ◽

2021 ◽

Vol 16 (7) ◽

pp. e0254194

Author(s):

Hong-Tae Park ◽

Woo Bin Park ◽

Suji Kim ◽

Jong-Sung Lim ◽

Gyoungju Nah ◽

...

Keyword(s):

Crohn’S Disease ◽

Crohn's Disease ◽

Single Cell ◽

Mycobacterium Avium ◽

Expression Patterns ◽

Cell Types ◽

Marker Genes ◽

Specific Marker ◽

Cell Type ◽

Cytokines And Chemokines

Mycobacterium avium subsp. paratuberculosis (MAP) is a causative agent of Johne’s disease, which is a chronic and debilitating disease in ruminants. MAP is also considered to be a possible cause of Crohn’s disease in humans. However, few studies have focused on the interactions between MAP and human macrophages to elucidate the pathogenesis of Crohn’s disease. We sought to determine the initial responses of human THP-1 cells against MAP infection using single-cell RNA-seq analysis. Clustering analysis showed that THP-1 cells were divided into seven different clusters in response to phorbol-12-myristate-13-acetate (PMA) treatment. The characteristics of each cluster were investigated by identifying cluster-specific marker genes. From the results, we found that classically differentiated cells express CD14, CD36, and TLR2, and that this cell type showed the most active responses against MAP infection. The responses included the expression of proinflammatory cytokines and chemokines such as CCL4, CCL3, IL1B, IL8, and CCL20. In addition, the Mreg cell type, a novel cell type differentiated from THP-1 cells, was discovered. Thus, it is suggested that different cell types arise even when the same cell line is treated under the same conditions. Overall, analyzing gene expression patterns via scRNA-seq classification allows a more detailed observation of the response to infection by each cell type.

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ESCO: single cell expression simulation incorporating gene co-expression

10.1101/2020.10.20.347211 ◽

2020 ◽

Author(s):

Jinjin Tian ◽

Jiebiao Wang ◽

Kathryn Roeder

Keyword(s):

Single Cell ◽

R Package ◽

Brain Cell ◽

Gene Interactions ◽

Cell Type ◽

Imputation Methods ◽

Biological Interest ◽

A Cell ◽

Cell Expression ◽

Cell Data

AbstractMotivationGene-gene co-expression networks (GCN) are of biological interest for the useful information they provide for understanding gene-gene interactions. The advent of single cell RNA-sequencing allows us to examine more subtle gene co-expression occurring within a cell type. Many imputation and denoising methods have been developed to deal with the technical challenges observed in single cell data; meanwhile, several simulators have been developed for benchmarking and assessing these methods. Most of these simulators, however, either do not incorporate gene co-expression or generate co-expression in an inconvenient manner.ResultsTherefore, with the focus on gene co-expression, we propose a new simulator, ESCO, which adopts the idea of the copula to impose gene co-expression, while preserving the highlights of available simulators, which perform well for simulation of gene expression marginally. Using ESCO, we assess the performance of imputation methods on GCN recovery and find that imputation generally helps GCN recovery when the data are not too sparse, and the ensemble imputation method works best among leading methods. In contrast, imputation fails to help in the presence of an excessive fraction of zero counts, where simple data aggregating methods are a better choice. These findings are further verified with mouse and human brain cell data.AvailabilityThe ESCO implementation is available as R package SplatterESCO (https://github.com/JINJINT/SplatterESCO)[email protected]

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The Cell's Biological Rods and Ropes

MRS Bulletin ◽

10.1557/s0883769400053239 ◽

1999 ◽

Vol 24 (10) ◽

pp. 27-31 ◽

Cited By ~ 2

Author(s):

David Boal

Keyword(s):

Cell Wall ◽

Plasma Membrane ◽

Chemical Composition ◽

Intermediate Filaments ◽

Plant Cells ◽

Cell Type ◽

Animal Cells ◽

Limited Variation ◽

A Cell ◽

Mechanical Elements

Despite a variety of shapes and sizes, the generic mechanical structure of cells is remarkably similar from one cell type to the next. All cells are bounded by a plasma membrane, a fluid sheet that controls the passage of materials into and out of the cell. Plant cells and bacteria reinforce this membrane with a cell wall, permitting the cell to operate at an elevated osmotic pressure. Simple cells, such as the bacterium shown in Figure 1a, possess a fairly homogeneous interior containing the cell's genetic blueprint and protein workhorses, but no mechanical elements. In contrast, as can be seen in Figure 1b, plant and animal cells contain internal compartments and a filamentous cytoskeleton—a network of biological ropes, cables, and poles that helps maintain the cell's shape and organize its contents.Four principal types of filaments are found in the cytoskeleton: spectrin, actin, microtubules, and a family of intermediate filaments. Not all filaments are present in all cells. The chemical composition of the filaments shows only limited variation from one cell to another, even in organisms as diverse as humans and yeasts. Membranes have a more variable composition, consisting of a bi-layer of dual-chain lipid molecules in which are embedded various proteins and frequently a moderate concentration of cholesterol. The similarity of the cell's mechanical elements in chemical composition and physical characteristics encourages us to search for universal strategies that have developed in nature for the engineering specifications of the cell. In this article, we concentrate on the cytoskeleton and its filaments.

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