Biology subjects

Colantuoni, C.

Publications and source records attributed to Colantuoni, C..

At least 19 recordsLinked to original sources

bioRxiv2026

A comparative single-cell transcriptomic atlas for diverse populations of vertebrate hair cells

Mechanosensitive hair cells vary widely in morphology and regenerative capacity across vertebrate organs and species. To investigate their underlying transcriptomic diversity, we integrated human, mouse, chicken, and zebrafish single-cell and single-nucleus RNA sequencing datasets and assembled a cross-species atlas of hair cells spanning organs, developmental stages, and species. Analysis of 29 hair cell populations, encompassing the major cochlear, vestibular, and lateral-line hair cell types, identified approximately 5,000 genes enriched in at least one hair cell population compared to supporting cells from the same organs. Unsupervised clustering of these hair cell-enriched (HCE) genes defined species-, organ-, and hair cell state-associated cohorts as well as broadly conserved hair cell-enriched programs. Using an AUC-based scoring framework, we further defined 884 pan hair cell-enriched (pan-HCE) genes with elevated expression in most developing and/or mature hair cell populations, including genes implicated in deafness, mechanotransduction, and synaptic transmission, along with genes not previously linked to hair cell function. Independent analysis of developing hair cells using the same metrics stratified pan-HCE genes based on when they are first enriched and identified an additional 97 genes that are transiently enriched. We used the pan- and developing HCE gene sets to assess transcriptional similarity between baseline hair cell states and hair cells produced during avian hair cell regeneration and in mouse cochlear organoids, as well as hair cell-like populations produced by fibroblast reprogramming. HCE gene sets with different developmental dynamics identified young vs. more mature hair cells when projected onto independent single-cell RNA sequencing datasets from developing zebrafish, mouse, and human. We provide a web-based resource of all HCE metrics and expression profiles, enabling future exploration of vertebrate hair cell gene expression across organs, species, and experimental contexts.

neuroscience↗

bioRxiv2026

A consensus atlas of human brain development defines cell type-specific maturation trajectories across the lifespan

Human neurodevelopment is a continuous process that begins prenatally and extends into postnatal life. Current transcriptomic datasets are limited, fragmented across analytical frameworks, precluding comprehensive reconstruction of cellular trajectories linking developmental states to mature cell types. Here we present a consolidated cellular-resolution transcriptomic atlas of human brain development from the onset of neurogenesis to adulthood, covering [~]2.2 million cells from 156 donors across nine studies. All data were reprocessed from raw sequencing reads and annotated within a unified cell-type taxonomy, enabling reliable mapping across the lifespan. Cell types were highly replicable across heterogeneous datasets, enabling us to chart their maturation and cortical layer localization over time. We identify dynamic gene programs predictive of cell-type maturation, validate gene modules tracking known fate transitions, and leverage our atlas scale to characterize rare populations, including microglia. This resource establishes a standardized reference of human brain development and maturation gene modules for future comparisons across model systems, species, and disease states.

neuroscience↗

bioRxiv2025

Transcriptomic and protein analysis of human cortex reveals genes and pathways linked to NPTX2 disruption in Alzheimer's disease

BackgroundCognitive resilience to Alzheimers disease (AD) pathology is associated with preserved expression of NPTX2, an activity-regulated synaptic protein involved in circuit plasticity, excitation-inhibition balance, and complement-linked synapse regulation. However, the broader molecular programs coordinated with NPTX2 in resilient individuals remain unclear. MethodsWe analyzed postmortem middle temporal gyrus tissue using targeted PRM-MS proteomics in 135 individuals and bulk RNA-seq in an expanded 575-sample cohort. NPTX2-associated molecular coordination was assessed within cognitively normal low-pathology controls (CN-Lo), cognitively normal high-pathology controls (CN-Hi), mild cognitive impairment (MCI), and AD. Correlation-based approaches were applied using NPTX2 protein and NPTX2 mRNA expression as anchors to define resilience mechanisms in CN-Hi subjects. ResultsNPTX2 protein abundance was preserved across all controls regardless of age and pathology but reduced in MCI and AD. NPTX2 mRNA expression was also invariant across pathology within controls and reduced in MCI and AD but decreased markedly with age. Targeted proteomics identified NPTX2 relationships with synaptic and inhibitory-circuit proteins that were preserved across control groups, alongside CN-Hi-specific recruitment of trafficking, lysosomal, metabolic, and proteostasis-associated proteins. Transcriptome-wide correlations with NPTX2 revealed differences in gene co-expression between groups, identifying a prominent activity-dependent program including BDNF, VGF, SCG2, SST, SERTM1, DUSP4, and EGR4, that was preserved in both CN-Lo and CN-Hi subjects, while genes recruited to the NPTX2 network specifically in CN-Hi implicated immune, neuroprotective, translation, and proteostasis-related pathways. Coupling differential gene expression analysis with co-expression, we further identified five candidate resilience genes whose expression and NPTX correlation was preserved across controls, but lost in MCI and AD: SST, MAL2, TAC1, SERTM1, and RFK. Expression of genes in distinct NPTX2 co-expression classes can be freely explored in our bulk RNA-seq data and other public AD transcriptomic datasets at NeMO Analytics. ConclusionFindings suggest that cognitive resilience in the context of AD neuropathology engages a coordinated molecular state distinct from both persevered cognition without pathology and MCI/AD, which is organized around preserved and selectively remodeled NPTX2-associations. Rather than reflecting broad transcript abundance changes, resilience was characterized by maintained synaptic and inhibitory programs, and adaptive proteostasis and trafficking pathways that distinguish resilient high-pathology individuals from low-pathology controls or symptomatic AD.

bioinformatics↗

bioRxiv2025

Human-specific features of the cerebellum and ZP2-regulated synapse development

Understanding the unique features of the human brain compared to non-human primates has long intrigued humankind. The cerebellum refines motor coordination and cognitive functions, contributing to the evolutionary development of human adaptability and dexterity. To identify shared and divergent features across primates, we conducted single-nucleus transcriptomic and chromatin accessibility profiling of the adult cerebellar cortex in humans, chimpanzees, macaques, and marmosets. We revealed human-specific transcriptomic and regulatory features, particularly those involved in synaptogenesis. Notably, we identified an enrichment of the sperm receptor zona pellucida glycoprotein 2 (ZP2) and its potential interactors, known for their roles in gamete interaction, in human granule cells. Experimental data show that ZP2 expression in human granule cells is induced by pontine mossy fibers, reducing synaptic proteins at pontocerebellar glomerular synapses, and decreasing cerebellar neuron electrophysiological activity. This unexpected co-option of ZP2 in human-specific synapse regulation provides insights into the evolutionary specialization of the human cerebellum.

neuroscience↗

bioRxiv2024

Early Developmental Origins of Cortical Disorders Modeled in Human Neural Stem Cells

The implications of the early phases of human telencephalic development, involving neural stem cells (NSCs), in the etiology of cortical disorders remain elusive. Here, we explored the expression dynamics of cortical and neuropsychiatric disorder-associated genes in datasets generated from human NSCs across telencephalic fate transitions in vitro and in vivo. We identified risk genes expressed in brain organizers and sequential gene regulatory networks across corticogenesis revealing disease-specific critical phases, when NSCs are more vulnerable to gene dysfunctions, and converging signaling across multiple diseases. Moreover, we simulated the impact of risk transcription factor (TF) depletions on different neural cell types spanning the developing human neocortex and observed a spatiotemporal-dependent effect for each perturbation. Finally, single-cell transcriptomics of newly generated autism-affected patient-derived NSCs in vitro revealed recurrent alterations of TFs orchestrating brain patterning and NSC lineage commitment. This work opens new perspectives to explore human brain dysfunctions at the early phases of development. One-sentence summaryThe temporal analysis of gene regulatory networks in human neural stem cells reveals multiple early critical phases associated with cortical disorders and neuropsychiatric traits.

neuroscience↗

bioRxiv2024

in silico transcriptome dissection of neocortical excitatory neurogenesis via joint matrix decomposition and transfer learning

Vast quantities of multi-omic data have been produced to characterize the development and diversity of cell types in the cerebral cortex of humans and other mammals. To more fully harness the collective discovery potential of these data, we have assembled gene-level transcriptomic data from 188 published studies of neocortical development, including the transcriptomes of [~]30 million single-cells, extensive spatial transcriptomic experiments and RNA sequencing of sorted cells and bulk tissues: nemoanalytics.org/landing/neocortex. Applying joint matrix decomposition (SJD) to mouse, macaque and human data in this collection, we defined transcriptome dynamics that are conserved across mammalian neurogenesis and which elucidate the evolution of outer, or basal, radial glial cells. Decomposition of adult human neocortical data identified layer-specific signatures in mature neurons and, in combination with transfer learning methods in NeMO Analytics, enabled the charting of their early developmental emergence and protracted maturation across years of postnatal life. Interrogation of data from cerebral organoids demonstrated that while broad molecular elements of in vivo development are recapitulated in vitro, many layer-specific transcriptomic programs in neuronal maturation are absent. We invite computational biologists and cell biologists without coding expertise to use NeMO Analytics in their research and to fuel it with emerging data (carlocolantuoni.org).

neuroscience↗

bioRxiv2023

CellCover Defines Conserved Cell Types and Temporal Progression in scRNA-seq Data across Mammalian Neocortical Development

1Definition of cell classes across the tissues of living organisms is central in the analysis of growing atlases of single-cell RNA sequencing (scRNA-seq) data across biomedicine. Marker genes for cell classes are most often defined by differential expression (DE) methods that serially assess individual genes across landscapes of diverse cells. This serial approach has been extremely useful, but is limited because it ignores possible redundancy or complementarity across genes that can only be captured by analyzing multiple genes simultaneously. Interrogating binarized expression data, we aim to identify discriminating panels of genes that are specific to, not only enriched in, individual cell types. To efficiently explore the vast space of possible marker panels, leverage the large number of cells often sequenced, and overcome zero-inflation in scRNA-seq data, we propose viewing marker gene panel selection as a variation of the "minimal set-covering problem" in combinatorial optimization. Using scRNA-seq data from blood and brain tissue, we show that this new method, CellCover, performs as good or better than DE and other methods in defining cell-type discriminating gene panels, while reducing gene redundancy and capturing cell-class-specific signals that are distinct from those defined by DE methods. Transfer learning experiments across mouse, primate, and human data demonstrate that CellCover identifies markers of conserved cell classes in neocortical neurogenesis, as well as developmental progression in both progenitors and neurons. Exploring markers of human outer radial glia (oRG, or basal RG) across mammals, we show that transcriptomic elements of this key cell type in the expansion of the human cortex likely appeared in gliogenic precursors of the rodent before the full program emerged in neurogenic cells of the primate lineage. We have assembled the public datasets we use in this report within the NeMO Analytics multi-omic data exploration environment [1], where the expression of individual genes (NeMO: Individual genes in cortex and NeMO: Individual genes in blood) and marker gene panels (NeMO: Telley 3 CellCover Panels, NeMO: Telley 12 CellCover Panels, NeMO: Sorted Brain Cell CellCover Panels, and NeMO: Blood 34 CellCover Panels) can be freely explored without coding expertise. CellCover is available in CellCover R and CellCover Python. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=67 SRC="FIGDIR/small/535943v6_ufig1.gif" ALT="Figure 1"> View larger version (19K): org.highwire.dtl.DTLVardef@893301org.highwire.dtl.DTLVardef@173a6baorg.highwire.dtl.DTLVardef@1c70e7eorg.highwire.dtl.DTLVardef@1888ab3_HPS_FORMAT_FIGEXP M_FIG C_FIG

genomics↗

bioRxiv2022

Structured Joint Decomposition (SJD) identifies conserved molecular dynamics across collections of biologically related multi-omics data matrices

It is necessary to develop exploratory tools to learn from the unprecedented volume of high-dimensional multi-omic data currently being produced across the field of biomedicine. We have developed an R package, Structured Joint Decomposition (SJD), which identifies components of variation that are shared across multiple matrices. The approach focuses specifically on variation across the samples/cells within each dataset while incorporating biologist-defined hierarchical structure among input experiments that can span in vivo and in vitro systems, multi-omic data modalities, and species. SJD enables the definition of molecular variation that is conserved across systems, those that are shared within subsets of studies, and elements unique to individual matrices. We have included functions to simplify the construction and visualization of highly complex in silico experiments involving many diverse multi-omic matrices from multiple species. Here we apply SJD to decompose four RNA-seq experiments focused on neurogenesis in the neocortex. The public datasets used in this analysis are at NeMO Analytics and can be explored at the individual gene level or using the conserved transcriptomic dynamics in mammalian neurogenesis that we define here. The SJD R package and tutorial can be found at https://chuansite.github.io/SJD. Contact: hzchenhuan@gmail.com; ccolant1@jhmi.edu [carlocolantuoni.org]

bioinformatics↗

bioRxiv2022

The Neuroscience Multi-Omic Archive: A BRAIN Initiative resource for single-cell transcriptomic and epigenomic data from the mammalian brain

Scalable technologies to sequence the transcriptomes and epigenomes of single cells are transforming our understanding of cell types and cell states. The Brain Research through Advancing Innovative Neurotechnologies (BRAIN) Initiative Cell Census Network (BICCN) is applying these technologies at unprecedented scale to map the cell types in the mammalian brain. In an effort to increase data FAIRness (Findable, Accessible, Interoperable, Reusable), the NIH has established repositories to make data generated by the BICCN and related BRAIN Initiative projects accessible to the broader research community. Here, we describe the Neuroscience Multi-Omic Archive (NeMO Archive; nemoarchive.org), which serves as the primary repository for genomics data from the BRAIN Initiative. Working closely with other BRAIN Initiative researchers, we have organized these data into a continually expanding, curated repository, which contains transcriptomic and epigenomic data from over 50 million brain cells, including single-cell genomic data from all of the major regions of the adult and prenatal human and mouse brains, as well as substantial single-cell genomic data from non-human primates. We make available several tools for accessing these data, including a searchable web portal, a cloud-computing interface for large-scale data processing (implemented on Terra, terra.bio), and a visualization and analysis platform, NeMO Analytics (nemoanalytics.org). KEY POINTSO_LIThe Neuroscience Multi-Omic Archive serves as the genomics data repository for the BRAIN Initiative. C_LIO_LIGenomic data from >50 million cells span all the major regions of the brains of humans and mice. C_LIO_LIWe provide a searchable web portal, a cloud-computing interface, and a data visualization platform. C_LI

genomics↗

bioRxiv2022

Early-childhood inflammation blunts the transcriptional maturation of cerebellar neurons

Inflammation early in life is a clinically established risk factor for autism spectrum disorders and schizophrenia, yet the impact of inflammation on human brain development is poorly understood. The cerebellum undergoes protracted postnatal maturation, making it especially susceptible to perturbations contributing to risk of neurodevelopmental disorders. Here, using single-cell genomics, we characterize the postnatal development of cerebellar neurons and glia in 1-5-year-old children, comparing those who died while experiencing inflammation vs. non-inflamed controls. Our analyses reveal that inflammation and postnatal maturation are associated with extensive, overlapping transcriptional changes primarily in two subtypes of inhibitory neurons: Purkinje neurons and Golgi neurons. Immunohistochemical analysis of a subset of these brains revealed no change to Purkinje neuron soma size but evidence for increased activation of microglia in those subjects experiencing inflammation. Maturation- and inflammation-associated genes were strongly enriched for those implicated in neurodevelopmental disorders. A gene regulatory network model integrating cell type-specific gene expression and chromatin accessibility identified seven temporally specific gene networks in Purkinje neurons and suggested that the effects of inflammation correspond to blunted cellular maturation. One Sentence SummaryPost-mortem cerebelli from children who perished under conditions that included inflammation exhibit transcriptomic changes consistent with blunted maturation of Purkinje neurons compared to those who succumbed to sudden accidental death.

genomics↗

bioRxiv2022

Insights for disease modeling from single cell transcriptomics of iPSC-derived neurons and astrocytes across differentiation time and co-culture

Trans-differentiation of human induced pluripotent stem cells into neurons via Ngn2-induction (hiPSC-N) has become an efficient system to quickly generate neurons for disease modeling and in vitro assay development, a significant advance from previously used neoplastic and other cell lines. Recent single-cell interrogation of Ngn2-induced neurons however, has revealed some similarities to unexpected neuronal lineages. Similarly, a straightforward method to generate hiPSC derived astrocytes (hiPSC-A) for the study of neuropsychiatric disorders has also been described. Here we examine the homogeneity and similarity of hiPSC-N and hiPSC-A to their in vivo counterparts, the impact of different lengths of time post Ngn2 induction on hiPSC-N (15 or 21 days) and of hiPSC-N / hiPSC-A co-culture. Leveraging the wealth of existing public single-cell RNA-seq (scRNA-seq) data in Ngn2-induced neurons and in vivo data from the developing brain, we provide perspectives on the lineage origins and maturation of hiPSC-N and hiPSC-A. While induction protocols in different labs produce consistent cell type profiles, both hiPSC-N and hiPSC-A show significant heterogeneity and similarity to multiple in vivo cell fates, and both more precisely approximate their in vivo counterparts when co-cultured. Gene expression data from the hiPSC-N show enrichment of genes linked to schizophrenia (SZ) and autism spectrum disorders (ASD) as has been previously shown for neural stem cells and neurons. These overrepresentations of disease genes are strongest in our system at early times (day 15) in Ngn2-induction/maturation of neurons, when we also observe the greatest similarity to early in vivo excitatory neurons. We have assembled this new scRNA-seq data along with the public data explored here as an integrated biologist-friendly web-resource for researchers seeking to understand this system more deeply: nemoanalytics.org/p?l=DasEtAlNGN2&g=PRPH.

genetics↗

bioRxiv2021

Cochlear organoids reveal epigenetic and transcriptional programs of postnatal hair cell differentiation from supporting cells

We explored the transcriptional and epigenetic programs underlying the differentiation of hair cells from postnatal progenitor cells in cochlear organoids. Heterogeneity in the cells including cells with the transcriptional signatures of mature hair cells allowed a full picture of possible cell fates. Construction of trajectories identified Lgr5+ cells as progenitors for hair cells and the genomic data revealed gene regulatory networks leading to hair cells. We validated these networks, demonstrating dynamic changes both in expression and predicted binding sites of these transcription factors during organoid differentiation. We identified known regulators of hair cell development, Atoh1, Pou4f3, and Gfi1, and predicted novel regulatory factors, Tcf4, an E-protein and heterodimerization partner of Atoh1, and Ddit3, a CCAAT/enhancer-binding protein (C/EBP) that represses Hes1 and activates transcription of Wnt signaling-related genes. Deciphering the signals for hair cell regeneration from mammalian cochlear supporting cells reveals candidates for HC regeneration which is limited in the adult.

developmental biology↗

bioRxiv2021

Regulome-wide association study identifies enhancer properties associated with risk for schizophrenia

Genetic risk for complex traits is strongly enriched in non-coding genomic regions involved in gene regulation, especially enhancers. However, we lack adequate tools to connect the characteristics of these disruptions to genetic risk. Here, we propose RWAS (Regulome Wide Association Study), a new framework to identify the characteristics of enhancers that contribute to genetic risk for disease. Applying our technique to interrogate genetic risk for schizophrenia, we found that risk-associated enhancers in this disease are predominantly active in the brain, evolutionarily conserved, and AT-rich. The association between AT percentage and risk corresponds to an overrepresentation in risk-associated enhancers for the binding sites of transcription factors that recognize AT-rich cis-regulatory motifs. Several of the TFs identified in our model as being overrepresented in risk-associated enhancers, including MEF2C, are master regulators of neuronal development. The genes that encode several of these TFs are themselves located at genetic risk loci for schizophrenia. This list also includes brain-expressed TFs that have not previously been linked to schizophrenia. In summary, we developed a generalizable approach that integrates GWAS summary statistics with enhancer characteristics to identify risk factors in tissue-specific regulatory regions. AUTHOR SUMMARYEnhancers are regulatory regions that influence gene expression via the binding of transcription factors. Risk for many heritable diseases is enriched in regulatory regions, including enhancers. In this study, we introduce a novel method of testing for association between enhancer attributes and risk and use this method to determine the enhancer characteristics that are associated with risk for schizophrenia. We found that enhancers associated with schizophrenia risk are both evolutionarily conserved and in physical contact with mutation-intolerant genes, many of which have neurodevelopmental functions. Risk-associated enhancers are also AT-rich and contain binding sites for neurodevelopmental transcription factors.

genomics↗

bioRxiv2021

Two-stage Linked Component Analysis for Joint Decomposition of Multiple Biologically Related Data Sets

SO_SCPLOWUMMARYC_SCPLOWIntegrative analysis of multiple data sets has the potential of fully leveraging the vast amount of high throughput biological data being generated. In particular such analysis will be powerful in making inference from publicly available collections of genetic, transcriptomic and epigenetic data sets which are designed to study shared biological processes, but which vary in their target measurements, biological variation, unwanted noise, and batch variation. Thus, methods that enable the joint analysis of multiple data sets are needed to gain insights into shared biological processes that would otherwise be hidden by unwanted intra-data set variation. Here, we propose a method called two-stage linked component analysis (2s-LCA) to jointly decompose multiple biologically related experimental data sets with biological and technological relationships that can be structured into the decomposition. The consistency of the proposed method is established and its empirical performance is evaluated via simulation studies. We apply 2s-LCA to jointly analyze four data sets focused on human brain development and identify meaningful patterns of gene expression in human neurogenesis that have shared structure across these data sets.

bioinformatics↗

bioRxiv2021

Mapping origins of variation in neural trajectories of human pluripotent stem cells

Variability between human pluripotent stem cell (hPSC) lines remains a challenge and opportunity in biomedicine. We identified differences in the early lineage emergence across hPSC lines that mapped on the antero-posterior axis of embryonic development. RNA-seq analysis revealed dynamic transcriptomic patterns that defined the emergence of mesendodermal versus neuroectodermal lineages conserved across hPSC lines and cell line-specific transcriptional signatures that were invariant across differentiation. The stable cell line-specific transcriptomic patterns predicted the retinoic acid (RA) response of the cell lines, resulting in distinct bias towards fore-versus hind-brain fates. Replicate hPSC lines and paired adult donor tissue demonstrated that cells from individual humans expressed unique and long-lasting transcriptomic signatures associated with evolutionarily recent genes. In addition to this genetic contribution, we found that replicate lines from a single donor showed divergent brain regional fates linked to distinct chromatin states, indicating that epigenetic mechanisms also contribute to neural fate differences. This variation in lineage bias and its correlation with RA responsive gene expression was also observed in a large collection of hPSC lines. These results define transcriptomic differences in hPSCs that initiate a critical early step specifying anterior or posterior neural fates.

neuroscience↗

bioRxiv2020

A multimodal cell census and atlas of the mammalian primary motor cortex

We report the generation of a multimodal cell census and atlas of the mammalian primary motor cortex (MOp or M1) as the initial product of the BRAIN Initiative Cell Census Network (BICCN). This was achieved by coordinated large-scale analyses of single-cell transcriptomes, chromatin accessibility, DNA methylomes, spatially resolved single-cell transcriptomes, morphological and electrophysiological properties, and cellular resolution input-output mapping, integrated through cross-modal computational analysis. Together, our results advance the collective knowledge and understanding of brain cell type organization: First, our study reveals a unified molecular genetic landscape of cortical cell types that congruently integrates their transcriptome, open chromatin and DNA methylation maps. Second, cross-species analysis achieves a unified taxonomy of transcriptomic types and their hierarchical organization that are conserved from mouse to marmoset and human. Third, cross-modal analysis provides compelling evidence for the epigenomic, transcriptomic, and gene regulatory basis of neuronal phenotypes such as their physiological and anatomical properties, demonstrating the biological validity and genomic underpinning of neuron types and subtypes. Fourth, in situ single-cell transcriptomics provides a spatially-resolved cell type atlas of the motor cortex. Fifth, integrated transcriptomic, epigenomic and anatomical analyses reveal the correspondence between neural circuits and transcriptomic cell types. We further present an extensive genetic toolset for targeting and fate mapping glutamatergic projection neuron types toward linking their developmental trajectory to their circuit function. Together, our results establish a unified and mechanistic framework of neuronal cell type organization that integrates multi-layered molecular genetic and spatial information with multi-faceted phenotypic properties.

neuroscience↗

bioRxiv2020

gEAR: gene Expression Analysis Resource portal for community-driven, multi-omic data exploration

The gEAR portal (gene Expression Analysis Resource, umgear.org) is an open access community-driven tool for multi-omic and multi-species data visualization, analysis and sharing. The gEAR supports visualization of multiple RNA-seq data types (bulk, sorted, single cell/nucleus) and epigenomics data, from multiple species, time points and tissues in a single-page, user-friendly browsable format. An integrated scRNA-seq workbench provides access to raw data of scRNA-seq datasets for de novo analysis, as well as marker-gene and cluster comparisons of pre-assigned clusters. Users can upload, view, analyze and privately share their own data in the context of previously published datasets. Short, permanent URLs can be generated for dissemination of individual or collections of datasets in published manuscripts. While the gEAR is currently curated for auditory research with over 90 high-value datasets organized in thematic profiles, the gEAR also supports the BRAIN initiative (via nemoanalytics.org) and is easily adaptable for other research domains.

bioinformatics↗

bioRxiv2020

UPREGULATION OF SUPEROXIDE DISMUTASE 2 BY ASTROCYTES IN THE SIV/MACAQUE MODEL OF HIV-ASSOCIATED NEUROLOGIC DISEASE

HIV-associated neurocognitive disorders (HAND) remain prevalent despite implementation of antiretroviral therapy (ART). Development of HAND is linked to mitochondrial dysfunction and oxidative stress in the brain; therefore, upregulation of antioxidant defenses is critical to curtail neuronal damage. Superoxide dismutase 2 (SOD2) is a mitochondrial antioxidant enzyme essential for maintaining cellular viability. We hypothesized that SOD2 was upregulated during retroviral infection. Using a simian immunodeficiency virus (SIV)-infected macaque model of HIV, quantitative PCR showed elevated SOD2 mRNA in cortical gray (GM, 7.6-fold for SIV vs. uninfected) and white matter (WM, 77-fold for SIV vs. uninfected) during SIV infection. Further, SOD2 immunostaining was enhanced in GM and WM from SIV-infected animals. Double immunofluorescence labeling illustrated that SOD2 primarily co-localized with astrocyte marker glial fibrillary acidic protein (GFAP) in SIV-infected animals. Interestingly, in ART-treated SIV-infected animals, brain SOD2 RNA levels were similar to uninfected animals. Additionally, using principal component analysis in a transcriptomic approach, SOD2 and GFAP expression separated SIV-infected from uninfected brain tissue. Projection of these data into a HIV dataset revealed similar expression changes, thereby validating the clinical relevance. Together, our findings suggest that novel SOD2-enhancing therapies may delay the onset or reduce severity of HAND seen in ART-treated HIV-infected patients.

neuroscience↗