Biology subjects

Averbukh, I.

Publications and source records attributed to Averbukh, I..

10 recordsLinked to original sources

bioRxiv2026

Spatially resolved, multimodal in vivo Perturb-seq using antibody-based cell hashing

Large-scale perturbation screens have begun to map cell intrinsic gene-function relationships, yet how genes shape tissue architecture remains largely unexplored. To address this gap, we developed PerturbSpace, a novel approach that integrates CRISPR perturbations with spatially hashed single-cell multiomics. This approach enables the first high-throughput, spatially resolved Perturb-seq analysis across complex tissue architecture in vivo. Notably, PerturbSpace enables spatial transcriptome-wide perturbation readouts at organ scale and can be seamlessly integrated with orthogonal modalities. We combine PerturbSpace with surface proteomics and expressed lineage tracing barcodes to demonstrate multimodal compatibility. We use PerturbSpace to study the genetic determinants of tissue architecture. First, we map how 40 transcriptional regulators determine the size and lineage composition of colonies in the spleen during regenerative hematopoiesis. Second, we characterize immune-niche interactions in the liver by dissecting the extrinsic effects mediated by cytokine-secreting immune cells on their neighboring cells. Collectively, our work establishes PerturbSpace as a scalable and cost-effective approach for transcriptome-wide spatial profiling of whole cells while remaining compatible with the single-cell multiomics workflows that the field has already adopted at scale.

genomics↗

bioRxiv2025

Multi-omic landscape of human gliomas from diagnosis to treatment and recurrence

Gliomas are among the most lethal cancers, with limited treatment options. To uncover hallmarks of therapeutic escape and tumor microenvironment (TME) evolution, we applied spatial proteomics, transcriptomics, and glycomics to 670 lesions from 310 adult and pediatric patients. Single-cell analysis shows high B7H3+ tumor cell prevalence in glioblastoma (GBM) and pleomorphic xanthoastrocytoma (PXA), while most gliomas, including pediatric cases, express targetable tumor antigens in less than 50% of tumor cells, potentially explaining trial failures. Longitudinal samples of isocitrate dehydrogenase (IDH)-mutant gliomas reveal recurrence driven by tumor-immune spatial reorganization, shifting from T-cell and vasculature-associated myeloid cell-enriched niches to microglia and CD206+ macrophage-dominated tumors. Multi-omic integration identified N-glycosylation as the best classifier of grade, while the immune transcriptome best predicted GBM survival. Provided as a community resource, this study opens new avenues for glioma targeting, classification, outcome prediction, and a baseline of TME composition across all stages.

cancer biology↗

bioRxiv2024

IFNγ-Expressing Myeloid Cells Localize within Lipoproteinosis during Drug-Associated Pulmonary Alveolar Proteinosis occurring in Systemic Juvenile Idiopathic Arthritis

In the United States, approximately one in 1000 children are diagnosed with the autoinflammatory disease, Juvenile Idiopathic Arthritis (JIA). A subset of JIA cases manifests as Systemic JIA (sJIA), which is characterized by joint pain, fevers, rashes, and systemic inflammation. Severe pulmonary complications have not historically been associated with sJIA. Since 2010, inhibitors of interleukin-1 and interleukin 6 (IL-1i/IL-6i) are the recommended course of treatment for sJIA, yet recently studies show evidence of a severe drug hypersensitivity reaction implicating these medications in a subset of those treated. With this reaction, sJIA patients can develop severe lung disease, including pulmonary alveolar proteinosis (PAP). As this drug-associated lung disease has only recently been identified, the etiology of sJIA drug-associated PAP (sJIA-daPAP) is poorly understood. We used multiplexed ion beam imaging by time-of-flight (MIBI-TOF) to define the cellular immune infiltrate and describe pathological features of PAP in sJIA-daPAP patients. We found an enrichment of eosinophils, neutrophils, and M2 macrophages within regions of lipoproteinosis. These enriched subsets all upregulate IFN{gamma} within lipoproteinosis, a signature specific to sJIA-daPAP samples compared to non-sJIA-PAP samples. In a cellular neighborhood analysis, we identified that eosinophils, neutrophils and M2 macrophages frequently co-localize within the same cellular microenvironment, especially in lipoproteinosis regions. Therefore, this spatial coordination may be involved in clearance or persistence of lipoproteinosis in sJIA-daPAP. This study provides a comprehensive overview of sJIA-daPAP immune pathology and suggests cellular mechanisms that drive inflammation in sJIA patients experiencing pulmonary complications associated with delayed drug hypersensitivity during IL-1i/IL-6i treatment.

immunology↗

bioRxiv2024

Automated classification of cellular expression in multiplexed imaging data with Nimbus

Multiplexed imaging offers a powerful approach to characterize the spatial topography of tissues in both health and disease. To analyze such data, the specific combination of markers that are present in each cell must be enumerated to enable accurate phenotyping, a process that often relies on unsupervised clustering. We constructed the Pan-Multiplex (Pan-M) dataset containing 197 million distinct annotations of marker expression across 15 different cell types. We used Pan-M to create Nimbus, a deep learning model to predict marker positivity from multiplexed image data. Nimbus is a pre-trained model that uses the underlying images to classify marker expression across distinct cell types, from different tissues, acquired using different microscope platforms, without requiring any retraining. We demonstrate that Nimbus predictions capture the underlying staining patterns of the full diversity of markers present in Pan-M. We then show how Nimbus predictions can be integrated with downstream clustering algorithms to robustly identify cell subtypes in image data. We have open-sourced Nimbus and Pan-M to enable community use at https://github.com/angelolab/Nimbus-Inference.

bioinformatics↗

bioRxiv2022

Supervised dimensionality reduction for exploration of single-cell data by Hybrid Subset Selection - Linear Discriminant Analysis

Single-cell technologies generate large, high-dimensional datasets encompassing a diversity of omics. Dimensionality reduction enables visualization of data by representing cells in two-dimensional plots that capture the structure and heterogeneity of the original dataset. Visualizations contribute to human understanding of data and are useful for guiding both quantitative and qualitative analysis of cellular relationships. Existing algorithms are typically unsupervised, utilizing only measured features to generate manifolds, disregarding known biological labels such as cell type or experimental timepoint. Here, we repurpose the classification algorithm, linear discriminant analysis (LDA), for supervised dimensionality reduction of single-cell data. LDA identifies linear combinations of predictors that optimally separate a priori classes, enabling users to tailor visualizations to separate specific aspects of cellular heterogeneity. We implement feature selection by hybrid subset selection (HSS) and demonstrate that this flexible, computationally-efficient approach generates non-stochastic, interpretable axes amenable to diverse biological processes, such as differentiation over time and cell cycle. We benchmark HSS-LDA against several popular dimensionality reduction algorithms and illustrate its utility and versatility for exploration of single-cell mass cytometry, transcriptomics and chromatin accessibility data.

bioinformatics↗

bioRxiv2021

Spatio-temporal coordination at the maternal-fetal interface promotes trophoblast invasion and vascular remodeling in the first half of human pregnancy

Beginning in the first trimester, fetally derived extravillous trophoblasts (EVTs) invade the uterus and remodel its spiral arteries, transforming them into large, dilated blood vessels left with a thin, discontinuous smooth muscle layer and partially lined with EVTs. Several mechanisms have been proposed to explain how EVTs coordinate with the maternal decidua to promote a tissue microenvironment conducive to spiral artery remodeling (SAR). However, it remains a matter of debate which immune and stromal cell types participate in these interactions and how this process evolves with respect to gestational age. Here, we used a multiomic approach that combined the strengths of spatial proteomics and transcriptomics to construct the first spatiotemporal atlas of the human maternal-fetal interface in the first half of pregnancy. We used multiplexed ion beam imaging by time of flight (MIBI-TOF) and a 37-plex antibody panel to analyze [~]500,000 cells and 588 spiral arteries within intact decidua from 66 patients between 6-20 weeks of gestation, integrating this with coregistered transcriptomic profiles. Gestational age substantially influenced the frequency of many maternal immune and stromal cells, with tolerogenic subsets expressing CD206, CD163, TIM-3, Galectin-9, and IDO-1 increasingly enriched and colocalized at later time points. In contrast, SAR progression preferentially correlated with EVT invasion and was transcriptionally defined by 78 gene ontology pathways exhibiting unique monotonic and biphasic trends. Lastly, we developed an integrated model of SAR supporting an intravasation mechanism where invasion is accompanied by upregulation of pro-angiogenic, immunoregulatory EVT programs that promote interactions with vascular endothelium while avoiding activation of immune cells in circulating maternal blood. Taken together, these results support a coordinated model of decidualization in which increasing gestational age drives a transition in maternal decidua towards a tolerogenic niche conducive to locally regulated, EVT-dependent SAR.

systems biology↗

bioRxiv2020

Clump sequencing exposes the spatial expression programs of intestinal secretory cells

Single-cell RNA sequencing combined with spatial information on landmark genes enables reconstruction of spatially-resolved tissue cell atlases. However, such approaches are challenging for rare cell types, since their mRNA contents are diluted in the spatial transcriptomics bulk measurements used for landmark gene detection. In the small intestine, enterocytes, the most common cell type, exhibit zonated expression programs along the crypt-villus axis, but zonation patterns of rare cell types such as goblet and tuft cells remain uncharacterized. Here, we present ClumpSeq, an approach for sequencing small clumps of attached cells. By inferring the crypt-villus location of each clump from enterocyte landmark genes, we establish spatial atlases for all epithelial cell types in the small intestine. We uncover immune-modulatory programs in villus tip goblet and tuft cells and heterogeneous migration patterns of enteroendocrine cells. ClumpSeq can be applied for reconstructing spatial atlases of rare cell types in other tissues and tumors.

cell biology↗

bioRxiv2019

Lgr5+ telocytes are a signaling hub at the intestinal villus tip

The intestinal epithelium is a structured organ composed of crypts harboring Lgr5+ stem cells, and villi harboring differentiated cells. Spatial transcriptomics have demonstrated profound zonation of epithelial gene expression along the villus axis, but the mechanisms shaping this spatial variability are unknown. Here, we combined laser capture micro-dissection and single cell RNA sequencing to uncover spatially zonated populations of mesenchymal cells along the crypt-villus axis. These included villus tip telocytes (VTTs) that express Lgr5, a gene previously considered a specific crypt epithelial stem cell marker. VTTs are elongated cells that line the villus tip epithelium and signal through Bmp morphogens and the non-canonical Wnt5a ligand. Their ablation strongly perturbs the zonation of enterocyte genes induced at the villus tip. Our study provides a spatially-resolved cell atlas of the small intestinal stroma and exposes Lgr5+ villus tip telocytes as regulators of the epithelial spatial expression programs along the villus axis.

cell biology↗

bioRxiv2018

Dynamics of Spaetzle morphogen shuttling in the Drosophila embryo shapes pattern

Establishment of morphogen gradients in the early Drosophila embryo is challenged by a diffusible extracellular milieu, and rapid nuclear divisions that occur at the same time. To understand how a sharp gradient is formed within this dynamic environment, we followed the generation of graded nuclear Dorsal (Dl) protein, the hallmark of pattern formation along the dorso-ventral axis, in live embryos. We show that a sharp gradient is formed through extracellular, diffusion-based morphogen shuttling that progresses through several nuclear divisions. Perturbed shuttling in wntD mutant embryos results in a flat activation peak and aberrant gastrulation. Re-entry of Dl into the nuclei at each cycle refines the signaling output, by guiding graded accumulation of the T48 transcript that drives patterned gastrulation. We conclude that diffusion-based ligand shuttling, coupled with dynamic readout, establishes a refined pattern within the diffusible environment of early embryos.

bioinformatics↗

bioRxiv2018

A repressor-decay timer for robust temporal patterning in embryonic Drosophila neuroblast lineages

Biological timers synchronize patterning processes during embryonic development. In the Drosophila embryo, neural progenitors (neuroblasts; NBs) produce a sequence of unique neurons whose identities depend on the sequential expression of temporal transcription factors (TTFs). The stereotypy and precision of the NB lineages indicate reproducible temporal progression of the TTF timer. To examine the basis of this robustness, we combine theory and experiments. The TTF timer is commonly described as a relay of activators, but its regulatory circuit is also consistent with a repressor-decay timer, in which expression of each TTF begins once its repressor is sufficiently reduced. We find that repressor-decay timers are more robust to parameter variations compared to activator-relay timers. This suggests that the in-vivo TTF sequence progresses primarily by repressor-decay, a prediction that we support experimentally. Our results emphasize the role of robustness in the evolutionary design of patterning circuits.

bioinformatics↗