Biology subjects

Martinowich, K.

Publications and source records attributed to Martinowich, K..

51 records · Page 3Linked to original sources

bioRxiv2021

CaPTure: Calcium Peak Toolbox for analysis of in vitro calcium imaging data

BackgroundCalcium imaging is a powerful technique for recording cellular activity across large populations of neurons. However, analysis methods capable of single-cell resolution in cultured neurons, especially for cultures derived from human induced pluripotent stem cells (hiPSCs), are lacking. Existing methods lack scalability to accommodate high-throughput comparisons between multiple lines, across developmental timepoints, or across pharmacological manipulations. ResultsWe developed a scalable, automated Ca2+ imaging analysis pipeline called CaPTure (https://github.com/LieberInstitute/CaPTure). This method detects neurons, classifies and quantifies spontaneous activity, quantifies synchrony metrics, and generates cell- and network-specific metrics that facilitate phenotypic discovery. The method is compatible with parallel processing on computing clusters without requiring significant user input or parameter modification. ConclusionCaPTure allows for rapid assessment of neuronal activity in cultured cells at cellular resolution, rendering it amenable to high-throughput screening and phenotypic discovery. The platform can be applied to both human- and rodent-derived neurons and is compatible with many imaging systems.

neuroscience↗

bioRxiv2021

Stimulus degradation impairs performance in a rodent continuous performance test

Sustained attention is a core cognitive domain that is often disrupted in neuropsychiatric disorders. Continuous performance tests (CPTs) are the most common clinical assay of sustained attention. In CPTs, participants produce a behavioral response to target stimuli and refrain from responding to non-target stimuli. Performance in CPTs is measured as the ability to discriminate between targets and non-targets. Rodent versions of CPTs (rCPT) have been developed and validated with both anatomical and pharmacological studies, providing a translational platform for understanding the neurobiology of sustained attention. In human studies, using degraded stimuli (decreased contrast) in CPTs impairs performance and patients with schizophrenia experience a larger decrease in performance compared to healthy controls. In this study, we tested multiple levels of stimulus degradation in a touchscreen version of the CPT in mice. We found that stimulus degradation significantly decreased performance in both males and females. The changes in performance consisted of a decrease in stimulus discrimination, measured as d, and increases in hit reaction time and reaction time variability. These findings are in line with the effects of stimulus degradation in human studies. Overall, female mice demonstrated a more liberal response strategy than males, but response strategy was not affected by stimulus degradation. These data extend the utility of the mouse CPT by demonstrating that stimulus degradation produces equivalent behavioral responses in mice and humans. Therefore, the degraded stimuli rCPT has high translational value as a preclinical assay of sustained attention.

neuroscience↗

bioRxiv2021

VistoSeg: a MATLAB pipeline to process, analyze and visualize high resolution histology images for Visium spatial transcriptomics data

BackgroundSpatial transcriptomics is a next-generation sequencing technology that combines the strengths of transcriptome-wide RNA-sequencing with histological imaging to generate spatial maps of gene expression in intact tissue sections. The 10x Genomics Visium and Visium-Immunofluorescence (Visium-IF) platforms are widely available commercial technologies for quantifying spatially-resolved gene expression. These technologies directly couple gene expression with high resolution histological or immunofluorescence images that contain rich morphological information about the tissue section. However, extracting and integrating image features with gene expression data remains challenging. ResultsUsing MATLAB, we developed VistoSeg, which is a pipeline to process, analyze, and interactively visualize the high-resolution images from the 10x Genomics Visium and Visium-IF platforms. The output from VistoSeg can then be integrated with the spatial-molecular information in downstream analyses using common programming languages, such as R or Python. ConclusionVistoSeg provides user-friendly tools for integrating image-derived metrics from histological and immunofluorescent images with spatially-resolved gene expression data. This integrated approach can advance our understanding of the transcriptional landscape within tissue architecture. VistoSeg is freely available at http://research.libd.org/VistoSeg/. Impact StatementTechnologies for measuring gene activity levels, referred to as gene expression, have been evolving over decades and are the core of the transcriptomics subfield within genomics. The first report describing individual cell gene expression is from 2009 and as a method it became commercially available in 2014. While single cell transcriptomics increased our resolution beyond homogenate tissue, the advent of spatial transcriptomics technologies and commercial availability of spatial gene expression platforms, such as Visium, has facilitated studying gene expression in anatomical context. Visium measures local gene expression within the histological organization of single 6.5 mm2 cryosection of tissue. Spatially-resolved transcriptomics provides a new challenge: integrating spatial gene expression with high resolution tissue images (brightfield histology or fluorescent antibody staining). VistoSeg image processing software is compatible with both Visium and Visium-IF from 10x Genomics, which are spatially-resolved transcriptomics assays employing histological and immunofluorescent images, respectively. From these images, the number of cells, identity of cell types, and other image-derived markers can be obtained for thousands of 2,375 {micro}m2 spots, where genome-wide gene expression is also measured. VistoSeg provides tools that enable processing these images in the context of gene expression maps to integrate these two high dimensional data types, and thus help unlock the new frontier in transcriptomics.

bioinformatics↗

bioRxiv2021

spatialLIBD: an R/Bioconductor package to visualize spatially-resolved transcriptomics data

MotivationSpatially-resolved transcriptomics has now enabled the quantification of high-throughput and transcriptome-wide gene expression in intact tissue while also retaining the spatial coordinates. Incorporating the precise spatial mapping of gene activity advances our understanding of intact tissuespecific biological processes. In order to interpret these novel spatial data types, interactive visualization tools are necessary. ResultsWe describe spatialLIBD, an R/Bioconductor package to interactively explore spatially-resolved transcriptomics data generated with the 10x Genomics Visium platform. The package contains functions to interactively access, visualize, and inspect the observed spatial gene expression data and data-driven clusters identified with supervised or unsupervised analyses, either on the users computer or through a web application. AvailabilityspatialLIBD is available at bioconductor.org/packages/spatialLIBD. Supplementary informationSupplementary data are available at Bioinformatics online.

bioinformatics↗

bioRxiv2021

Electrophysiological measures from human iPSC-derived neurons are associated with schizophrenia clinical status and predict individual cognitive performance

Neurons derived from human induced pluripotent stem cells (hiPSCs) have been used to model basic cellular aspects of neuropsychiatric disorders, but the relationship between the emergent phenotypes and the clinical characteristics of donor individuals has been unclear. We analyzed RNA expression and indices of cellular function in hiPSC-derived neural progenitors and cortical neurons generated from 13 individuals with high polygenic risk scores (PRS) for schizophrenia and a clinical diagnosis of schizophrenia, along with 15 neurotypical individuals with low PRS. We identified electrophysiological measures associated with diagnosis that implicated altered Na+ channel function and GABA-ergic neurotransmission. Importantly, electrophysiological measures predicted cardinal clinical and cognitive features found in these schizophrenia patients. The identification of basic neuronal physiological properties related to core clinical characteristics of illness is a potentially critical step in generating leads for novel therapeutics.

neuroscience↗

bioRxiv2021

Induction of Bdnf from promoter I following electroconvulsive seizures contributes to structural plasticity in neurons of the piriform cortex

The efficacy of electroconvulsive therapy (ECT) as a treatment for psychiatric disorders, including major depressive disorder (MDD) is hypothesized to depend on induction of molecular and cellular events that trigger structural plasticity in neurons. Electroconvulsive seizures (ECS) in animal models can help to inform our understanding of how electroconvulsive therapy (ECT) impacts the brain. ECS induces structural plasticity in neuronal dendrites in many brain regions, including the piriform cortex, a highly epileptogenic region that has also been implicated in depression. ECS-induced structural plasticity is associated with differential expression of unique isoforms encoding the neurotrophin, brain-derived neurotrophic factor (BDNF), but the functional significance of these transcripts in dendritic plasticity is not clear. Here, we demonstrate that different Bdnf isoforms are expressed non-stochastically across neurons of the piriform cortex following ECS. Specifically, cells expressing Bdnf exon 1-containing transcripts show a unique spatial recruitment pattern in response to ECS. We further demonstrate that Bdnf Ex1 expression in these cells is necessary for ECS-induced dendritic spine plasticity.

neuroscience↗

bioRxiv2021

Decoding shared versus divergent transcriptomic signatures across cortico-amygdala circuitry in PTSD and depressive disorders

Post-traumatic stress disorder (PTSD) is a debilitating neuropsychiatric disease with a projected lifetime risk of 8.7%. PTSD is highly comorbid with depressive disorders including major depressive disorder (MDD) and bipolar disorder (BD). It is hypothesized that the overlap in symptoms stems from partially shared underlying neurobiological mechanisms. To better understand shared and unique transcriptional patterns of PTSD and MDD we performed RNA-sequencing in the postmortem brain of two prefrontal cortex (PFC) regions and two amygdala (AMY) regions, from neurotypical donors (N=109) as well as donors with diagnoses of PTSD (N=107) or MDD (N=109) across 1285 RNA-seq samples. We identified a small number of differentially expressed genes (DEGs) specific to PTSD, mostly in the cortex compared to amygdala. PTSD-specific DEGs were preferentially enriched in cortistatin-expressing cells, a subpopulation of somatostatin interneurons. These PTSD DEGs also showed strong enrichment for gene sets associated with immune-related pathways and microglia, largely driven by decreased expression of these genes in PTSD donors. While we identified a greater number of DEGs for MDD, there were only a few that were specific to MDD as they showed high overlap with PTSD DEGs. Finally, we used weighted gene co-expression network analysis (WGCNA) as an orthogonal approach to confirm the observed cellular and molecular associations. These findings highlight the sub-population of cortistatin-expressing interneurons as having potential functional significance in PTSD and provide supporting evidence for dysregulated neuroinflammation and immune signaling in MDD and PTSD pathophysiology.

neuroscience↗

bioRxiv2020

Single-nucleus transcriptome analysis reveals cell type-specific molecular signatures across reward circuitry in the human brain

Single cell/nucleus technologies are powerful tools to study cell type-specific expression in the human brain, but most large-scale efforts have focused on characterizing cortical brain regions and their constituent cell types. However, additional brain regions - particularly those embedded in basal ganglia and limbic circuits - play important roles in neuropsychiatric disorders and addiction, suggesting a critical need to better understand their molecular characteristics. We therefore created a single-nucleus RNA-sequencing (snRNA-seq) resource across five human brain regions (hippocampus, HPC; dorsolateral prefrontal cortex, DLPFC; subgenual anterior cingulate cortex, sACC; nucleus accumbens, NAc; and amygdala, AMY), with emphasis on the NAc and AMY, given their involvement in reward signaling and emotional processing. We identified distinct and potentially novel neuronal subpopulations, which we validated by smFISH for various subclasses of NAc interneurons and medium spiny neurons (MSNs). We additionally benchmarked these datasets against published datasets for corresponding regions in rodent models to define cross-species convergence and divergence across analogous cell subclasses. We characterized the transcriptomic architecture of regionally-defined neuronal subpopulations, which revealed strong patterns of similarities in specific neuronal subclasses across the five profiled regions. Finally, we measured genetic associations between risk for psychiatric disease and substance use behaviors with each of the regionally-defined cell types. This analysis further supported NAc and AMY involvement in risk for psychiatric illness by implicating specific neuronal subpopulations, and highlighted potential involvement of an MSN population associated with stress signaling in genetic risk for substance use.

neuroscience↗

bioRxiv2020

Transcriptome-scale spatial gene expression in the human dorsolateral prefrontal cortex

We used the 10x Genomics Visium platform to define the spatial topography of gene expression in the six-layered human dorsolateral prefrontal cortex (DLPFC). We identified extensive layer-enriched expression signatures, and refined associations to previous laminar markers. We overlaid our laminar expression signatures onto large-scale single nuclei RNA sequencing data, enhancing spatial annotation of expression-driven clusters. By integrating neuropsychiatric disorder gene sets, we showed differential layer-enriched expression of genes associated with schizophrenia and autism spectrum disorder, highlighting the clinical relevance of spatially-defined expression. We then developed a data-driven framework to define unsupervised clusters in spatial transcriptomics data, which can be applied to other tissues or brain regions where morphological architecture is not as well-defined as cortical laminae. We lastly created a web application for the scientific community to explore these raw and summarized data to augment ongoing neuroscience and spatial transcriptomics research (http://research.libd.org/spatialLIBD). O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=138 SRC="FIGDIR/small/969931v1_ufig1.gif" ALT="Figure 1"> View larger version (43K): org.highwire.dtl.DTLVardef@fcf6borg.highwire.dtl.DTLVardef@1fab44dorg.highwire.dtl.DTLVardef@53629dorg.highwire.dtl.DTLVardef@6f3de5_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

bioRxiv2020

Strategies for cellular deconvolution in human brain RNA sequencing data

Statistical deconvolution strategies have emerged over the past decade to estimate the proportion of various cell populations in homogenate tissue sources like brain using gene expression data. Here we show that several existing deconvolution algorithms which estimate the RNA composition of homogenate tissue, relates to the amount of RNA attributable to each cell type, and not the cellular composition relating to the underlying fraction of cells. Incorporating "cell size" parameters into RNA-based deconvolution algorithms can successfully recover cellular fractions in homogenate brain RNA-seq data. We lastly show that using both cell sizes and cell type-specific gene expression profiles from brain regions other than the target/user-provided bulk tissue RNA-seq dataset consistently results in biased cell fractions. We report several independently constructed cell size estimates as a community resource and extend the MuSiC framework to accommodate these cell size estimates (https://github.com/xuranw/MuSiC/).

genomics↗

bioRxiv2019

Molecularly-Defined Hippocampal Inputs Regulate Population Dynamics in the Prelimbic Cortex to Suppress Context Fear Memory Recall

Associating fearful events with the context in which they occur is critical for survival. Dysregulation of context-fear memory processing is a hallmark symptom of several neuropsychiatric disorders, including generalized anxiety disorder (GAD) and post-traumatic stress disorder (PTSD). Both the hippocampus and prelimbic subregion (PrL) of the medial prefrontal cortex (mPFC) have been linked with context fear memory recall in rodents, but the mechanisms by which hippocampal-prelimbic circuitry regulates this process remains poorly understood. Spatial and genetic targeting of this circuit in mice allowed us to use molecular profiling to show that hippocampal neurons with projections to the PrL (vHC-PrL projectors) are a transcriptomically-distinct sub-population that is enriched for expression of genes associated with both GAD and PTSD. We further show that stimulation of this population of vHC-PrL projectors suppresses context fear memory recall and impairs the ability of PrL neurons to dynamically distinguish between distinct phases of fear learning. Using transgenic and circuit-specific molecular targeting approaches, we demonstrate that unique patterns of activity-dependent gene transcription within vHC-PrL projectors causally regulate excitatory/inhibitory balance in the PrL during context fear memory recall. Together, our data illuminate the molecular mechanisms by which hippocampal-prelimbic circuitry regulates the retrieval of contextually-mediated fear memories.

neuroscience↗

bioRxiv2019

dotdotdot: an automated approach to quantify multiplex single molecule fluorescent in situ hybridization (smFISH) images in complex tissues

Multiplex single-molecule fluorescent in situ hybridization (smFISH) is a powerful method for validating RNA sequencing and emerging spatial transcriptomic data, but quantification remains a computational challenge. We present a framework for generating and analyzing smFISH data in complex tissues while overcoming autofluorescence and increasing multiplexing capacity. We developed dotdotdot (https://github.com/LieberInstitute/dotdotdot) as a corresponding software package to quantify RNA transcripts in single nuclei and perform differential expression analysis. We first demonstrate robustness of our platform in single mouse neurons by quantifying differential expression of activity-regulated genes. We then quantify spatial gene expression in human dorsolateral prefrontal cortex (DLPFC) using spectral imaging and dotdotdot to mask lipofuscin autofluorescence. We lastly apply machine learning to predict cell types and perform downstream cell type-specific expression analysis. In summary, we provide experimental workflows, imaging acquisition and analytic strategies for quantification and biological interpretation of smFISH data in complex tissues.

neuroscience↗

bioRxiv2019

Bdnf promoter IV-expressing cells in the hippocampus modulate fear expression and hippocampal-prefrontal synchrony in mice

Brain-derived neurotrophic factor (BDNF) signaling regulates synaptic plasticity in the hippocampus (HC) and prefrontal cortex (PFC), and has been extensively linked with fear memory expression in rodents. Notably, disrupting BDNF production from promoter IV-derived transcripts enhances fear expression in mice, and decreases fear-associated HC-PFC synchrony, suggesting that Bdnf transcription from promoter IV plays a key role in HC-PFC function during fear memory retrieval. To understand how promoter IV-derived BDNF affects fear expression and HC-PFC connectivity, we generated a viral construct that selectively targets cells expressing promoter IV-derived Bdnf transcripts ("p4-cells") for tamoxifen-inducible Cre-mediated recombination (AAV8-p4Bdnf-ERT2CreERT2-PEST). Using this construct, we found that ventral (vHC) p4-cells are recruited during fear expression, and that activation of these cells causes exaggerated fear expression that co-occurs with disrupted vHC-PFC synchrony in mice. Our data highlight how this novel construct can be used to interrogate genetically-defined cell types that selectively contribute to BDNF-dependent behaviors.

neuroscience↗

bioRxiv2018

Dissecting transcriptomic signatures of neuronal differentiation and maturation using iPSCs

Human induced pluripotent stem cells (hiPSCs) are a powerful model of neural differentiation and maturation. We present a hiPSC transcriptomics resource on corticogenesis from 5 iPSC donor and 13 subclonal lines across nine time points over 5 broad conditions: self-renewal, early neuronal differentiation, neural precursor cells (NPCs), assembled rosettes, and differentiated neuronal cells that were validated using electrophysiology. We identified widespread changes in the expression of individual transcript features and their splice variants, gene networks, and global patterns of transcription. We next demonstrated that co-culturing human NPCs with rodent astrocytes resulted in mutually synergistic maturation, and that cell type-specific expression data can be extracted using only sequencing read alignments without potentially disruptive cell sorting. We lastly developed and validated a computational tool to estimate the relative neuronal maturity of iPSC-derived neuronal cultures and human brain tissue, which were maturationally heterogeneous but contained subsets of cells most akin to adult human neurons.

genomics↗

bioRxiv2018

BDNF-TrkB signaling in oxytocin neurons contributes to maternal behavior

Brain-derived neurotrophic factor (Bdnf) transcription is controlled by several promoters, which drive expression of multiple transcripts encoding an identical protein. We previously reported that BDNF derived from promoters I and II is highly expressed in hypothalamus and is critical for regulating aggression in male mice. Here we report that BDNF loss from these promoters causes reduced sexual receptivity and impaired maternal care in female mice, which is concomitant with decreased oxytocin (Oxt) expression during development. We identify a novel link between BDNF signaling, oxytocin, and maternal behavior by demonstrating that ablation of TrkB selectively in OXT neurons partially recapitulates maternal care impairments observed in BDNF-deficient females. Using translating ribosome affinity purification and RNA-sequencing we define a molecular profile for OXT neurons and delineate how BDNF signaling impacts gene pathways critical for structural and functional plasticity. Our findings highlight BDNF as a modulator of sexually-dimorphic hypothalamic circuits that govern female-typical behaviors.

neuroscience↗