Biology subjects

Maynard, K.

Publications and source records attributed to Maynard, K..

7 recordsLinked to original sources

bioRxiv2026

Spatially-resolved integration of microglia morphological diversity and gene expression using Visium with protein co-detection

Microglia exhibit a dynamic range of morphologies that actively shift in response to local environmental cues. There has been a concerted effort as a field to move away from dualistic characterization of all microglia as resting or activated, which is often described in terms of their morphological differences alone, towards more integrated definitions of microglial states based on multiple data types. Recent advances in spatially-resolved transcriptomics offer new ways to understand microglial gene expression in situ. Here, we related microglia morphology to gene expression within a published, spatially-resolved proteogenomics (Visium-SPG) dataset of the human dorsolateral prefrontal cortex as proof of principle to combine the contributions of microglia morphology to regional transcriptomics differences in the brain. The published dataset uniquely combined spatial transcriptomics with immunofluorescent staining for four major brain cell types, including microglia, which enabled us to link microglial morphologies to gene expression in a spatially-resolved manner. Using a computational toolset, MicrogliaMorphology and MicrogliaMorphologyR, we classified individual microglia into morphological subtypes, assigned microglia to spots, and integrated these data with transcriptomic profiles for each Visium-SPG spot. We applied non-negative matrix factorization to account for contributions from multiple cell types, morphological features, and regional context in downstream differential expression modeling. Our approach offers a methodological framework for investigating the relationship between microglial morphology and gene expression in larger cohorts and within disease contexts where changes in microglia morphology are anticipated. Author summaryRecent advances in spatially-resolved transcriptomics and the development of methods to deconvolve cell type signals has offered new ways to understand microglial gene expression in various tissue contexts. In this work, we related microglia morphologies to gene expression within a published spatial transcriptomics dataset of the human dorsolateral prefrontal cortex to assess whether morphologically different microglia are transcriptomically different in the healthy human brain. This dataset uniquely combines spatial transcriptomics with immunofluorescent staining for four major brain cell types, including microglia, enabling the linkage of microglial morphologies to gene expression in a spatially-resolved manner. Using a computational toolset for microglia morphology analysis, we classified individual microglia into morphological subtypes and integrated these data with spatial transcriptomic profiles while accounting for contributions from multiple cell types, morphological features, and regional context. This allowed for the identification of microglia morphology-related genes that are differentially expressed between microglial subtypes and relevant to human brain disorders. Findings together provide proof of principle for exploring the relationship between microglial morphology and gene expression in larger cohorts and diverse experimental contexts.

neuroscience↗

bioRxiv2025

Spatiomolecular mapping reveals anatomical organization of heterogeneous cell types in the human nucleus accumbens

The nucleus accumbens (NAc) is a key component of the mesolimbic dopamine system that critically regulates many behaviors related to reward and motivation. The NAc is implicated in several neuropsychiatric disorders, including major depressive disorder, schizophrenia, and substance use disorders. Rodent studies have identified spatial organization of heterogeneous medium spiny neuron (MSN) subtypes across the NAc core and shell, but the extent to which this cellular diversity and spatial organization is conserved in the human brain remains unclear. Here, we generated a spatiomolecular atlas of NAc cell types and spatial domains by integrating spatial transcriptomics and single-nucleus RNA sequencing data from postmortem NAc tissue from 10 neurotypical adult donors. We identified 20 transcriptionally unique cell populations and 8 spatial domains, including specialized D1 islands composed of distinct dopamine receptor 1 (DRD1) MSN subtypes, which were enriched for OPRM1. In contrast to a discrete core vs. shell division, we observed continuous spatial gradients of gene expression across MSN domains, suggesting a more complex organization of DRD1 and DRD2 MSNs. Cross-species comparisons demonstrated conservation of MSN subtypes and spatial features between human, rodent, and nonhuman primate NAc. Genetic enrichment analysis with stratified linkage disequilibrium score regression revealed specific spatial domains associated with risk for psychiatric and addiction-related traits. To investigate this further, we spatially mapped ligand-receptor interactions involving neuropsychiatric risk genes. Finally, we leveraged existing rodent NAc data to identify drug-responsive transcriptional programs and predict their spatial distribution in the human NAc. Collectively, we provide a spatiomolecular framework for understanding the human NAc and its relevance to neuropsychiatric disease.

neuroscience↗

bioRxiv2024

Network nature of ligand-receptor interactions underlies disease comorbidity in the brain

Neurodegenerative disorders have overlapping symptoms and have high comorbidity rates, but this is not reflected in overlaps of risk genes. We have investigated whether ligand-receptor interactions (LRIs) are a mechanism by which distinct genes associated with disease risk can impact overlapping outcomes. We found that LRIs are likely disrupted in neurological disease and that the ligand-receptor networks associated with neurological diseases have substantial overlaps. Specifically, 96.8% of LRIs associated with disease risk are interconnected in a single LR network. These ligands and receptors are enriched for roles in inflammatory pathways and highlight the role of glia in cross-disease risk. Disruption to this LR network due to disease-associated processes (e.g. differential transcript use, protein misfolding) is likely to contribute to disease progression and risk of comorbidity. Our findings have implications for drug development, as they highlight the potential benefits and risks of pursuing cross-disease drug targets.

neuroscience↗

bioRxiv2021

Expression of brain-derived neurotrophic factor in basolateral amygdala inputs to lateral septum is necessary for mice to identify socially novel individuals

The lateral septum (LS) is a GABAergic region in the basal forebrain that is implicated in sociability. However, the neural circuits and cell signaling pathways that converge on the LS to mediate social behaviors arent well understood. Multiple lines of evidence suggest that brain-derived neurotrophic factor (BDNF) signaling through its receptor TrkB plays important roles in social behavior. While BDNF is not locally produced in LS, we demonstrate that nearly all GABAergic neurons in LS express TrkB. Local knock-down of TrkB expression from LS neurons decreased sociability and reduced recruitment of social novelty-induced neural activity. Since BDNF is not synthesized in LS, we evaluated which inputs to the LS could serve as potential BDNF sources for controlling sociability. By selectively ablating inputs to LS, we demonstrated that inputs from the basolateral amygdala (BLA), but not ventral CA1 (vCA1), regulate sociability. Moreover, depleting BDNF selectively in BLA-LS projection neurons phenocopied the decreased sociability observed following either local LS TrkB knockdown or ablation of BLA-LS inputs. These data support the hypothesis that BLA-LS projection neurons could serve as a critical source of BDNF for activating TrkB signaling in LS neurons to control sociability.

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↗

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↗