Biology subjects

Starosvetsky, E.

Publications and source records attributed to Starosvetsky, E..

6 recordsLinked to original sources

bioRxiv2022

Systematic mapping of neural signals in the periphery reveals a rich and specific alphabet for immune cell communication

Accumulating evidence indicate a strong link between neural signals and the immune system. Given neural signals constitute a large family that may be leveraged for communication, we systematically explored the neuro-immune regulation network in the periphery and uncovered a broad yet lineage selective expression of neuro-receptors on immune cells. We constructed a rich social immune network map showing the neural molecular pathways supporting the regulation of the immune system at steady state. Our results emphasize neuro-receptors role in the commitment and differentiation of B and T cells along their developmental process. We identified the immune cells functionality in the specific tissue is extensively shaped by the communication with the microenvironment and nervous systems via a rich alphabet of neural mediators. Collectively, our findings suggest neural genes are an integral part of the immune regulatory system and provide clear testable new avenues of experimental follow up for neuroimmunologists and immunologists alike. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=185 SRC="FIGDIR/small/522179v1_ufig1.gif" ALT="Figure 1"> View larger version (44K): org.highwire.dtl.DTLVardef@d4032eorg.highwire.dtl.DTLVardef@11ce763org.highwire.dtl.DTLVardef@9b279eorg.highwire.dtl.DTLVardef@45fc89_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LI160 neural genes potentially active in immune cells in the periphery with high specificity to lineage C_LIO_LINeuro-receptors co-expressed in immune lineages are enriched for biological functions C_LIO_LIChanges in neuro-receptors expression influence the HCS differentiation and commitment C_LIO_LIImmune-microenvironment neural signaling architecture reflects tissue biological role C_LI

immunology↗

bioRxiv2021

CytoPro: A computational platform for accurate and robust assessment of cell contributions in bulk expression from diverse tissues and conditions

Cells are the quanta unit of biology and their relative composition in a tissue is the prime driver of bulk tissue gene expression variation. When there is no cell information, deconvolution is an effective tool to achieve cell resolution, which provides important information for learning disease complexity and its interactions with treatments, drugs and/or the environment in a wide variety of contexts. Here we present CytoPro, a production-level tissue and condition-specific deconvolution platform, based on a large collection of human tissue-specific signatures derived from single and sorted cells. CytoPro infer per-sample multiple cell-type composition, given input bulk gene expression. CytoPro includes a rigorous QC pipeline for learning, generating and selecting signatures and performs internal automated validation using multiple QC test criteria including: Comparison to ground truth cytometry and pure sorted cells data, performance evaluation using simulated data including robustness to noise as well as agreement with biological expectations in validation datasets regarding genes and cells. We demonstrate that CytoPro outperforms existing deconvolution tools, in both accuracy and robustness. By exploring multiple datasets with predefined disease phenotypes, and analyzing a use-case of biological treatment response, we show the ability of CytoPro to flush out relevant cell biology in real pathological conditions.

bioinformatics↗

bioRxiv2021

A personalized network framework reveals predictive axis of anti-TNF response across diseases

Personalized treatment of complex diseases has been mostly predicated on biomarker identification of one drug-disease combination at a time. Here, we used a novel computational approach termed Disruption Networks to generate a new data type, contextualized by cell-centered individual-level networks, that captures biology otherwise overlooked when performing standard statistics. The new data-type extends beyond the feature level space, to the relations space, by quantifying individual-level breaking or rewiring of cross-feature relations. Applying disruption network to dissect high-dimensional blood data, we discover and validate that the RAC1-PAK1 axis is predictive of anti-TNF response in inflammatory bowel disease. Intermediate monocytes, which correlate with the inflammatory state, play a key role in the RAC1-PAK1 responses, supporting their modulation as a therapeutic target. This axis also predicts response in rheumatoid arthritis, validated in three public cohorts. Our findings support blood-based drug response diagnostics across immune-mediated diseases, implicating common mechanisms of non-response.

systems biology↗

bioRxiv2018

High Resolution Comparison of Cancer-Related Developmental Processes Using Trajectory Alignment

Abnormal differentiation is a key feature of cancer, yet currently there is no framework that enables a comparative analysis of differentiation processes across patients while preserving their individual-level resolution. Here, we present devMap, an algorithm that uses high-dimensional trajectory alignment to anchor cancer-related developmental processes to a common backbone process, thus allowing for their systematic comparison. We applied devMap to bone marrow samples from healthy individuals and AML patients profiled by single-cell mass-cytometry at cancer diagnosis and following treatment. devMap standardization enabled us to infer the developmental status of the AML samples and characterize its evolution following treatment and in relapse. Application of devMap on an external dataset of AML bone marrow samples revealed conserved patterns of developmental signaling responses in AML that were obscured by traditional methodologies for developmental inference.

systems biology↗

bioRxiv2018

CD38 is a key regulator of enhanced NK cell immune responses during pregnancy through its role in immune synapse formation

Natural killer (NK) cells use a diverse array of activating and inhibitory surface receptors to detect threats and provide an early line of defense against viral infections and cancer. Here, we demonstrate that the cell surface protein CD38 is a key human NK cell functional receptor through a role in immune synapse formation. CD38 expression marks a mature subset of human NK cells with a high functional capacity. NK cells expressing high levels of CD38 display enhanced killing and IFN-{gamma} secretion in response to influenza virus-infected and tumor cells. Inhibition of CD38 enzymatic activity does not influence NK cell function, but blockade of CD38 and its ligand CD31 abrogates killing and IFN-{gamma} expression in response to influenza-infected cells. Blockade of CD38 on NK cells similarly inhibits killing of tumor cells. CD38 localizes and accumulates at the immune synapse between NK cells and their targets, and blocking CD38 severely abrogates the ability of NK cells to form conjugates and immune synapses with target cells. Thus, CD38 plays a critical role in NK cell immune synapse formation. These findings open new avenues in immunotherapeutic development for cancer and infection by revealing a critical role for CD38 in NK cell function.

immunology↗

bioRxiv2018

Immune cellular homeostasis in early life is determined by genetic variants of cellular production and turnover

Complex physiological functionality is often the outcome of multiple interacting cell-types, yet mechanistically how a large number of trait-associated genes yield a single multi-cellular network governing the phenotype has not been well defined. Individuals immune-cellular profiles at homeostasis show high heritability and inter-individual variation with functional and clinical implications. We profiled immune cellular variation by mass-cytometry in 55 genetically diverse mouse strains. We identify 788 genes associated with cellular homeostasis, supporting a polygenic model where 52% of genes correspond to core homeostatic functions whose genetic variants suffice to predict phenotype. Trait genes form a multi-cellular network architecture showing increased functional complexity over evolutionary timescales for shared regulation to all cells, specialized cell-specific programs, and between-cell synchronization. Contrasting to human studies suggests the regulatory network expands with environmental exposure history. Our findings shed light on the origin of immune-cellular variation and regulatory architectures that may generalize to other environmentally sensitive systems.

immunology↗