Biology subjects

Kozareva, V.

Publications and source records attributed to Kozareva, V..

7 recordsLinked to original sources

bioRxiv2026

IGF1 peptide targets Rett Syndrome astrocytes to degrade IGF binding protein, rescue synaptogenesis and restore mitochondrial function

Rett syndrome (RTT), a severe neurodevelopmental disorder caused by mutations in MECP2, leads to profound synaptic and circuit deficits in the brain. While neurons have historically been the focus of RTT pathology, emerging evidence implicates astrocytes in non-cell autonomous mechanisms that impair synaptic structure, function and development. Here, we uncover a central role for astrocyte-secreted IGFBP2 in mediating these deficits and demonstrate that treatment with an IGF1-derived peptide restores synapse formation by promoting IGFBP2 degradation. Using an indirect astrocyte-neuron co-culture system, we show that astrocytes derived from RTT model mice suppress excitatory synapse formation in wild-type neurons and that this impairment is reversed when RTT astrocytes are treated with IGF1(1-3) peptide. Proteomic analysis reveals elevated levels of IGFBP2 in RTT astrocytes and their conditioned media. IGF1(1-3) peptide treatment leads to proteasomal degradation of IGFBP2, increasing IGF1 bioavailability, restoring mitochondrial function, and enhancing downstream PI3K/Akt signaling in neurons. Our data define a molecular mechanism by which astrocyte dysfunction in RTT can be rescued and provide a mechanistic basis for the therapeutic efficacy of IGF1(1-3) peptide, including Trofinetide, an FDA-approved IGF1 peptide mimetic, in RTT. Significance StatementAstrocyte dysfunction is increasingly recognized as a contributor to neurodevelopmental disorders, yet their precise mechanisms of action remain elusive. Here, we identify IGFBP2 as a key astrocyte-derived inhibitor of synaptogenesis in Rett syndrome. We show that an IGF1-derived peptide, IGF1(1-3), depletes IGFBP2 via proteasomal degradation. This restores IGF1 bioavailability and rescues synaptic function in a non-cell-autonomous manner. These findings provide a mechanistic explanation for the clinical efficacy of IGF1 peptide and its mimetics in Rett syndrome, and highlight astrocytes as rational therapeutic targets in neurodevelopmental and other disorders.

neuroscience↗

bioRxiv2025

Integrative multiomic analysis links TDP-43-driven splicing defects to cascading proteomic disruption of ALS/FTD pathways

Loss of nuclear TDP-43 is a hallmark of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD). Although TDP-43 is known to regulate RNA processing, including repression of cryptic exons, we currently lack a systems-level understanding of the consequences of TDP-43 loss. To address this, we generated multiomic datasets, including RNA-seq and proteomics, from human iPSC-derived neurons depleted of TDP-43. We found that differentially spliced genes, many expressing cryptic exons, had the greatest protein reductions. Surprisingly, nearly half of differentially expressed proteins were neither mis-spliced, nor differentially expressed genes; most of these also had no reported mis-splicing in seven additional post-mortem and iPSC-derived neuron datasets. Integrative network analysis identified a high-confidence disease-specific subnetwork of over 700 interacting proteins, enriched for mRNA processing, synaptic function, and autophagy. Comparison with post-mortem ALS and FTD samples revealed convergent protein and pathway disruptions. We experimentally validated network-predicted effects of cryptic splicing in ATG4B, STMN2, and DAPK1. Our analyses reveal new TDP-43-dependent molecular cascades and nominate central genes as potential ALS/FTD therapeutic targets.

neuroscience↗

bioRxiv2023

Disease related changes in ATAC-Seq of more than 450 iPSC-derived motor neuron lines from ALS patients and controls

Amyotrophic Lateral Sclerosis (ALS), like many other neurodegenerative diseases, is highly heritable, but with only a small fraction of cases explained by monogenic disease alleles. To better understand sporadic ALS, we report epigenomic profiles, as measured by ATAC-seq, of motor neuron cultures derived from a diverse group of 380 ALS patients and 80 healthy controls. We find that chromatin accessibility is heavily influenced by sex, the iPSC cell type of origin, ancestry, and the inherent variance arising from sequencing. Once these covariates are corrected for, we are able to identify robust ALS-specific signals in the data. Additionally, we find that the ATAC-seq data is able to predict ALS disease progression rates with similar accuracy to methods based on biomarkers and clinical status. These results suggest that iPSC-derived motor neurons recapitulate important disease-relevant epigenomic changes.

neuroscience↗

bioRxiv2021

Candelabrum cells are molecularly distinct, ubiquitous interneurons of the cerebellar cortex with specialized circuit properties

To understand how the cerebellar cortex transforms mossy fiber (MF) inputs into Purkinje cell (PC) outputs, it is vital to delineate the elements of this circuit. Candelabrum cells (CCs) are enigmatic interneurons of the cerebellar cortex that have been identified based on their morphology, but their electrophysiological properties, synaptic connections, and function remain unknown. Here we clarify these properties using electrophysiology, snRNA sequencing, in situ hybridization, and serial electron microscopy. We find that CCs are the most abundant PC layer interneuron. They are GABAergic, molecularly distinct, and present in all cerebellar lobules. Their high resistance renders CC firing highly sensitive to synaptic inputs. CCs are excited by MFs and granule cells, and strongly inhibited by PCs. CCs in turn inhibit molecular layer interneurons, which leads to PC disinhibition. Thus, inputs, outputs and local signals all converge onto CCs to allow them to assume a unique role in controlling cerebellar output.

neuroscience↗

bioRxiv2020

Single Cell Sequencing Reveals Glial Specific Responses to Tissue Processing & Enzymatic Dissociation in Mice and Humans

A key aspect of nearly all single cell experiments is the necessity to dissociate intact tissues into single cell suspensions for processing. While many protocols have been optimized for optimal cell yield, they have often overlooked the effects that dissociation can have on ex vivo gene expression changes during this process. Microglia, the brains resident macrophages, are a highly dynamic population that are extremely sensitive to their microenvironment and have been shown to dramatically alter their transcriptome upon stimulation. We demonstrate that use of enzymatic dissociation methods on mouse central nervous system (CNS) tissue induces an aberrant gene expression signature in microglia that can significantly confound downstream analysis. To minimize this issue, we developed a flexible protocol, that can be used with existing enzymatic protocols for fresh tissue, to eliminate artifactual gene expression while allowing for increased cell type diversity and yield. We demonstrate efficacy of this protocol in analysis of diverse CNS cell types and sorted myeloid populations while using enzymatic dissociation. Generation of new and reanalysis of previously published human brain single nucleus RNAseq (snRNA-seq) datasets reveal that a similar signature is also present in post-mortem tissue. Through novel snRNA-seq analysis of acutely-resected neurosurgical tissue we demonstrate that this signature can be induced in human tissue due to technical differences in sample processing. These results provide key insight into the potential confounds of enzymatic digestion and provide a solution to allow for enzymatic digestion for scRNA-seq while avoiding ex vivo transcriptional artifacts. Analysis of human tissue reveals potential for artifacts in current and future snRNA-seq datasets that will require deeper analysis and careful consideration to separate true biology from artifacts related to post-mortem processes.

neuroscience↗

bioRxiv2020

A transcriptomic atlas of the mouse cerebellum reveals regional specializations and novel cell types

The cerebellum is a well-studied brain structure with diverse roles in motor learning, coordination, cognition, and autonomic regulation. Nonetheless, a complete inventory of cerebellar cell types is presently lacking. We used high-throughput transcriptional profiling to molecularly define cell types across individual lobules of the adult mouse cerebellum. Purkinje and granule neurons showed considerable regional specialization, with the greatest diversity occurring in the posterior lobules. For multiple types of cerebellar interneurons, the molecular variation within each type was more continuous, rather than discrete. For the unipolar brush cells (UBCs)--an interneuron population previously subdivided into two discrete populations--the continuous variation in gene expression was associated with a graded continuum of electrophysiological properties. Most surprisingly, we found that molecular layer interneurons (MLIs) were composed of two molecularly and functionally distinct types. Both show a continuum of morphological variation through the thickness of the molecular layer, but electrophysiological recordings revealed marked differences between the two types in spontaneous firing, excitability, and electrical coupling. Together, these findings provide the first comprehensive cellular atlas of the cerebellar cortex, and outline a methodological and conceptual framework for the integration of molecular, morphological, and physiological ontologies for defining brain cell types.

genomics↗

bioRxiv2018

Integrative inference of brain cell similarities and differences from single-cell genomics

Defining cell types requires integrating diverse measurements from multiple experiments and biological contexts. Recent technological developments in single-cell analysis have enabled high-throughput profiling of gene expression, epigenetic regulation, and spatial relationships amongst cells in complex tissues, but computational approaches that deliver a sensitive and specific joint analysis of these datasets are lacking. We developed LIGER, an algorithm that delineates shared and dataset-specific features of cell identity, allowing flexible modeling of highly heterogeneous single-cell datasets. We demonstrated its broad utility by applying it to four diverse and challenging analyses of human and mouse brain cells. First, we defined both cell-type-specific and sexually dimorphic gene expression in the mouse bed nucleus of the stria terminalis, an anatomically complex brain region that plays important roles in sex-specific behaviors. Second, we analyzed gene expression in the substantia nigra of seven postmortem human subjects, comparing cell states in specific donors, and relating cell types to those in the mouse. Third, we jointly leveraged in situ gene expression and scRNA-seq data to spatially locate fine subtypes of cells present in the mouse frontal cortex. Finally, we integrated mouse cortical scRNA-seq profiles with single-cell DNA methylation signatures, revealing mechanisms of cell-type-specific gene regulation. Integrative analyses using the LIGER algorithm promise to accelerate single-cell investigations of cell-type definition, gene regulation, and disease states.

neuroscience↗