skip to main content
US FlagAn official website of the United States government
dot gov icon
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
https lock icon
Secure .gov websites use HTTPS
A lock ( lock ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.


Title: S2Map: a novel computational platform for identifying secretio-types through cell secretion-signal map
Abstract MotivationCell communication is predominantly governed by secreted proteins, whose diverse secretion patterns often signify underlying physiological irregularities. Understanding these secreted signals at an individual cell level is crucial for gaining insights into regulatory mechanisms involving various molecular agents. To elucidate the array of cell secretion signals, which encompass different types of biomolecular secretion cues from individual immune cells, we introduce the secretion-signal map (S2Map). ResultsS2Map is an online interactive analytical platform designed to explore and interpret distinct cell secretion-signal patterns visually. It incorporates two innovative qualitative metrics, the signal inequality index and the signal coverage index, which are exquisitely sensitive in measuring dissymmetry and diffusion of signals in temporal data. S2Map’s innovation lies in its depiction of signals through time-series analysis with multi-layer visualization. We tested the SII and SCI performance in distinguishing the simulated signal diffusion models. S2Map hosts a repository for the single-cell’s secretion-signal data for exploring cell secretio-types, a new cell phenotyping based on the cell secretion signal pattern. We anticipate that S2Map will be a powerful tool to delve into the complexities of physiological systems, providing insights into the regulation of protein production, such as cytokines at the remarkable resolution of single cells. Availability and implementationThe S2Map server is publicly accessible via https://au-s2map.streamlit.app/.  more » « less
Award ID(s):
1943302
PAR ID:
10581340
Author(s) / Creator(s):
; ; ; ; ; ;
Publisher / Repository:
Oxford University Press
Date Published:
Journal Name:
Bioinformatics Advances
Volume:
5
Issue:
1
ISSN:
2635-0041
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. null (Ed.)
    Quantification of cell-secreted molecules, e.g. , cytokines, is fundamental to the characterization of immune responses. Cytokine capture assays that use engineered antibodies to anchor the secreted molecules to the secreting cells are widely used to characterize immune responses because they allow both sensitive identification and recovery of viable responding cells. However, if the cytokines diffuse away from the secreting cells, non-secreting cells will also be identified as responding cells. Here we encapsulate immune cells in microfluidic droplets and perform in-droplet cytokine capture assays to limit the diffusion of the secreted cytokines. We use microfluidic devices to rapidly encapsulate single natural killer NK-92 MI cells and their target K562 cells into microfluidic droplets. We perform in-droplet IFN-γ capture assays and demonstrate that NK-92 MI cells recognize target cells within droplets and become activated to secrete IFN-γ. Droplet encapsulation prevents diffusion of secreted products to neighboring cells and dramatically reduces both false positives and false negatives, relative to assays performed without droplets. In a sample containing 1% true positives, encapsulation reduces, from 94% to 2%, the number of true-positive cells appearing as negatives; in a sample containing 50% true positives, the number of non-stimulated cells appearing as positives is reduced from 98% to 1%. After cells are released from the droplets, secreted cytokine remains captured onto secreting immune cells, enabling FACS-isolation of populations highly enriched for activated effector immune cells. Droplet encapsulation can be used to reduce background and improve detection of any single-cell secretion assay. 
    more » « less
  2. Abstract MotivationSingle-cell Hi-C (scHi-C) data provide critical insights into chromatin interactions at individual cell levels, uncovering unique genomic 3D structures. However, scHi-C datasets are characterized by sparsity and noise, complicating efforts to accurately reconstruct high-resolution chromosomal structures. In this study, we present ScUnicorn, a novel blind super-resolution framework for scHi-C data enhancement. ScUnicorn uses an iterative degradation kernel optimization process, unlike traditional super-resolution approaches, which rely on downsampling, predefined degradation ratios, or constant assumptions about the input data to reconstruct high-resolution interaction matrices. Hence, our approach more reliably preserves critical biological patterns and minimizes noise. Additionally, we propose 3DUnicorn, a maximum likelihood algorithm that leverages the enhanced scHi-C data to infer precise 3D chromosomal structures. ResultsOur evaluation demonstrates that ScUnicorn achieves superior performance over the state-of-the-art methods in terms of Peak Signal-to-Noise Ratio, Structural Similarity Index Measure, and GenomeDisco scores. Moreover, 3DUnicorn’s reconstructed structures align closely with experimental 3D-FISH data, underscoring its biological relevance. Together, ScUnicorn and 3DUnicorn provide a robust framework for advancing genomic research by enhancing scHi-C data fidelity and enabling accurate 3D genome structure reconstruction. Availability and implementationUnicorn implementation is publicly accessible at https://github.com/OluwadareLab/Unicorn. 
    more » « less
  3. Abstract Integrated microfluidic cellular phenotyping platforms provide a promising means of studying a variety of inflammatory diseases mediated by cell‐secreted cytokines. However, immunosensors integrated in previous microfluidic platforms lack the sensitivity to detect small signals in the cellular secretion of proinflammatory cytokines with high precision. This limitation prohibits researchers from studying cells secreting cytokines at low abundance or existing at a small population. Herein, the authors present an integrated platform named the “digital Phenoplate (dPP),” which integrates digital immunosensors into a microfluidic chip with on‐chip cell assay chambers, and demonstrates ultrasensitive cellular cytokine secretory profile measurement. The integrated sensors yield a limit of detection as small as 0.25 pg mL−1for mouse tumor necrosis factor alpha (TNF‐α). Each on‐chip cell assay chamber confines cells whose population ranges from ≈20 to 600 in arrayed single‐cell trapping microwells. Together, these microfluidic features of the dPP simultaneously permit precise counting and image‐based cytometry of individual cells while performing parallel measurements of TNF‐α released from rare cells under multiple stimulant conditions for multiple samples. The dPP platform is broadly applicable to the characterization of cellular phenotypes demanding high precision and high throughput. 
    more » « less
  4. Abstract Insulin is a peptide hormone that is secreted in Golgi-derived dense-core vesicles from mammalian pancreatic beta-cells in response to nutrients. InDrosophila melanogaster, three insulin-like peptides are secreted as neuropeptides from the insulin-producing cells in the brain. Peroxisomes are lipid-metabolizing organelles that engage into various membrane contact sites with other organelles. Impaired peroxisomal metabolism has been associated with beta-cell apoptosis and impaired insulin secretion. How peroxisomes contribute to insulin and neuropeptide secretion is unknown. Here we demonstrate that peroxisomes interact with the Golgi apparatus inDrosophilainsulin-producing cells. Secretion of insulin-like peptide 2 is cell-intrinsically impaired in mutants lacking the peroxisome assembly factor Pex19. Loss of peroxisomes shifts the profile of sphingolipids towards longer sphingoid bases and leads to accumulation of sphingolipids in the Golgi. We show that peroxisomes dynamically interact with the Golgi in insulin-producing cells and that Pex19 directly contributes to peroxisome-Golgi interaction via the fatty acyl-CoA reductase FAR2/waterproof in the peroxisomal membrane. We propose that this peroxisome-Pex19-Golgi axis is required to adjust Golgi membranes upon starvation by withdrawing lipids with longer side chains, thereby optimizing Golgi membrane flexibility for dense-core vesicle secretion upon refeeding. 
    more » « less
  5. Abstract BackgroundMesenchymal stromal cell derived extracellular vesicles (MSC-EVs) are a promising therapeutic for neuroinflammation. MSC-EVs can interact with microglia, the resident immune cells of the brain, to exert their immunomodulatory effects. In response to inflammatory cues, such as cytokines, microglia undergo phenotypic changes indicative of their function e.g. morphology and secretion. However, these changes in response to MSC-EVs are not well understood. Additionally, no disease-relevant screening tools to assess MSC-EV bioactivity exist, which has further impeded clinical translation. Here, we developed a quantitative, high throughput morphological profiling approach to assess the response of microglia to neuroinflammation- relevant signals and whether this morphological response can be used to indicate the bioactivity of MSC-EVs. ResultsUsing an immortalized human microglia cell-line, we observed increased size (perimeter, major axis length) and complexity (form factor) upon stimulation with interferon-gamma (IFN-γ) and tumor necrosis factor-alpha (TNF-α). Upon treatment with MSC-EVs, the overall morphological score (determined using principal component analysis) shifted towards the unstimulated morphology, indicating that MSC-EVs are bioactive and modulate microglia. The morphological effects of MSC-EVs in TNF-α /IFN-γ stimulated cells were concomitant with reduced secretion of 14 chemokines/cytokines (e.g. CXCL6, CXCL9) and increased secretion of 12 chemokines/cytokines (e.g. CXCL8, CXCL10). Proteomic analysis of cell lysates revealed significant increases in 192 proteins (e.g. HIBADH, MEAK7, LAMC1) and decreases in 257 proteins (e.g. PTEN, TOM1, MFF) with MSC-EV treatment. Of note, many of these proteins are involved in regulation of cell morphology and migration. Gene Set Variation Analysis revealed upregulation of pathways associated with immune response, such as regulation of cytokine production, immune cell infiltration (e.g. T cells, NK cells) and morphological changes (e.g. Semaphorin, RHO/Rac signaling). Additionally, changes in microglia mitochondrial morphology were measured suggesting that MSC-EV modulate mitochondrial metabolism. ConclusionThis study comprehensively demonstrates the effects of MSC-EVs on human microglial morphology, cytokine secretion, cellular proteome, and mitochondrial content. Our high-throughput, rapid, low-cost morphometric approach enables screening of MSC-EV batches and manufacturing conditions to enhance EV function and mitigate EV functional heterogeneity in a disease relevant manner. This approach is highly generalizable and can be further adapted and refined based on selection of the disease-relevant signal, target cell, and therapeutic product. 
    more » « less