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Results for “flow cytometry cell sorting”

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PubMed2024

Genome-wide association studies with experimental validation identify a protective role for B lymphocytes against chronic post-surgical pain.

BACKGROUND: Chronic post-surgical pain (CPSP) significantly impacts patients' recovery and quality of life. Although environmental risk factors are well-established, genetic risk remains less understood. METHODS: A meta-analysis of genome-wide association studies followed by partitioned heritability was performed on 1350 individuals across five surgery types: hysterectomy, mastectomy, abdominal, hernia, and knee. In subsequent animal studies, withdrawal thresholds to evoked mechanical stimulation were measured in Rag1 null mutant and wild-type mice after plantar incision and laparotomy. Cell sorting by flow cytometry tracked recruitment of immune cell types. RESULTS: We discovered 77 genome-wide significant single-nucleotide polymorphism (SNP) hits, distributed among 24 loci and 244 genes. Meta-analysis of all cohorts estimated a SNP-based narrow-sense heritability for CPSP at ∼39%, indicating a substantial genetic contribution. Partitioned heritability analysis across a wide variety of tissues revealed enrichment of heritability in immune system-related genes, particularly those associated with B and T cells. Rag1 null mutant mice lacking both T and B cells exhibited exacerbated and prolonged allodynia up to 42 days after surgery, which was rescued by B-cell transfer. Recruitment patterns of B cells but not T cells differed significantly during the first 7 days after injury in the footpad, lymph nodes, and dorsal root ganglia. CONCLUSIONS: These findings suggest a key protective role for the adaptive immune system in the development of chronic post-surgical pain.

Animals↗

PubMed2016

Loss of neurogenesis in Hydra leads to compensatory regulation of neurogenic and neurotransmission genes in epithelial cells.

Hydra continuously differentiates a sophisticated nervous system made of mechanosensory cells (nematocytes) and sensory-motor and ganglionic neurons from interstitial stem cells. However, this dynamic adult neurogenesis is dispensable for morphogenesis. Indeed animals depleted of their interstitial stem cells and interstitial progenitors lose their active behaviours but maintain their developmental fitness, and regenerate and bud when force-fed. To characterize the impact of the loss of neurogenesis in Hydra, we first performed transcriptomic profiling at five positions along the body axis. We found neurogenic genes predominantly expressed along the central body column, which contains stem cells and progenitors, and neurotransmission genes predominantly expressed at the extremities, where the nervous system is dense. Next, we performed transcriptomics on animals depleted of their interstitial cells by hydroxyurea, colchicine or heat-shock treatment. By crossing these results with cell-type-specific transcriptomics, we identified epithelial genes up-regulated upon loss of neurogenesis: transcription factors (Dlx, Dlx1, DMBX1/Manacle, Ets1, Gli3, KLF11, LMX1A, ZNF436, Shox1), epitheliopeptides (Arminins, PW peptide), neurosignalling components (CAMK1D, DDCl2, Inx1), ligand-ion channel receptors (CHRNA1, NaC7), G-Protein Coupled Receptors and FMRFRL. Hence epitheliomuscular cells seemingly enhance their sensing ability when neurogenesis is compromised. This unsuspected plasticity might reflect the extended multifunctionality of epithelial-like cells in early eumetazoan evolution.

Animals↗

PubMed2025

A Dual-Selection System for Enhanced Efficiency and Fidelity of Circular RNA Overexpression.

Circular RNAs (circRNAs) are essential regulators of cellular processes, but are challenging to study using traditional methods. Overexpression approaches, such as the use of linearized plasmids and viral vectors, often result in high rates of false-positive clones, where cells retain selection markers without expressing the target circRNA. This study addresses this limitation by developing a dual-selection circRNA system designed to enhance the accuracy and reliability of circRNA overexpression. Our system integrates a fluorescent reporter gene upstream of the circRNA expression cassette, under a shared promoter, and a downstream antibiotic resistance marker, allowing for both antibiotic selection and flow cytometric cell-sorting to identify and enrich cells with genuine circRNA expression. We successfully incorporated this system into an inducible lentiviral vector for controlled overexpression in various cell types. The dual-selection circRNA system offers a significant advance for circRNA research and studies of other RNA species where accurate and reliable overexpression is essential.

RNA, Circular↗

PubMed2025

FACS-Proteomics strategy toward extracellular vesicles single-phenotype characterization in biological fluids: exploring the role of leukocyte-derived EVs in multiple sclerosis.

BACKGROUND: The isolation and proteomics characterization of extracellular vesicles (EVs) from body fluids is challenging due to their vast heterogeneity. We have recently demonstrated that Fluorescence-activated Cell Sorting (FACS) efficiently isolates the whole EV circulating compartment directly from untouched body fluids enabling a comprehensive EV proteomics analysis. RESULTS: Here, we characterized, for the first time, a single-phenotype EV subset by sorting leukocyte-derived EVs (Leuko EVs) from peripheral blood and tears of healthy volunteers. Using an optimized and patented staining protocol of the whole EV compartment we identified and excluded non-EV particles, debris and damaged EVs. We further isolated, using an anti-CD45 antibody, Leuko EVs (CD45+ EVs), reaching a high level of purity (> 90%). Purified Leuko EVs were characterized using atomic force microscopy, nanoparticle tracking, and shotgun proteomics analysis revealing a similar coded protein cargo in both biological fluids. Subsequently, the same workflow was applied to tears from Relapsing-Remitting Multiple Sclerosis (RRMS) patients, revealing a Leuko EVs protein cargo enrichment that reflects the neuroinflammatory condition characteristics of RRMS. This enrichment was evidenced by the activation of upstream regulators TGFB1 and NFE2L2, which are associated with inflammatory responses. Additionally, the analysis identified markers indicative of endothelial cell proliferation and the development of enhanced vascular networks, with AGNPT2 and VEGF emerging as activated upstream regulators. These findings indicate the complex interplay between inflammation and angiogenesis in RRMS. CONCLUSIONS: In conclusion, our combined FACS-Proteomics strategy offers a promising approach for biomarker discovery, analysing cell-specific EV phenotypes directly from untouched body fluids, advancing the clinical value of tears EVs and improving the understanding of EV-mediated processes in vivo. Data are available via ProteomeXchange with the identifier PXD049036 and in EV-TRACK knowledgebase with ID: EV240150.

Humans↗

PubMed2026

Novel and High-Throughput Method of Isolating Single Fetal Cells Using FACS for NIPT.

OBJECTIVE: To evaluate fluorescence activated cell sorting (FACS) as a method of single-cell isolation of rare circulating fetal cells from maternal blood for use in cell-based non-invasive prenatal testing (cbNIPT). METHOD: Blood samples (30 mL) were collected from 75 'low-risk' pregnant women (gestational age 10-15 weeks). Fetal cells were enriched and stained using magnetic activated cell sorting. Following enrichment, single fetal cells were sorted in individual PCR tubes by FACS. After cell lysis, verification of fetal cell origin was performed using short tandem repeat (STR) analysis with the GlobalFiler PCR Amplification kit. RESULTS: An average of 13.7 cells were sorted using FACS. STR analysis identified 8.2 fetal cells on average, representing 60.2% of the sorted cells. The four-step single-cell isolation procedure facilitated an overall enrichment of approximately 16-million-fold. One sample did not render any fetal cell, corresponding to 1.3% of the samples. CONCLUSION: FACS, which is typically used for segregation of large populations of cells, can be used for single-cell isolation of rare fetal cells in an automated setup. This not only helps in making cell isolation faster and high throughput but also provides fetal cells for a more comprehensive genetic analysis of the fetus.

Humans↗

PubMed2026

VINE-seq and MultiVINE-seq for single-nucleus and multiome profiling of the brain vasculature.

The human cerebrovasculature is a critical yet historically understudied component of neurological health. Dysfunction of the diverse endothelial, mural, and perivascular cells that comprise cerebral vessels is central to diseases ranging from stroke to Alzheimer's disease. However, characterizing these cell populations at a molecular level has proven exceptionally challenging. Encased within a robust basement membrane, vascular cells resist standard dissociation methods, leading to their systematic depletion and underrepresentation in existing single-nucleus genomic atlases. This has created a major blind spot in neuroscience. To overcome this barrier, we developed vessel isolation and nucleus extraction for sequencing (VINE-seq) and its advanced iteration, MultiVINE-seq. The protocol provides a robust, reproducible workflow for the enrichment and high-resolution profiling of vascular, perivascular, and immune cells from fresh or frozen human and mouse brain tissue. First, intact vessels (predominantly capillaries and small arterioles/venules, 100 µm in diameter) are isolated from homogenized brain tissue via dextran-based density-gradient centrifugation, separating the vascular pellet from myelin and the parenchymal fraction. Second, the collected vessels are rigorously washed over a cell strainer to remove trapped contaminants. A critical innovation lies in the third stage: the optimized extraction of nuclei from purified vessels using enzymatic digestion. After extraction, the protocol uses fluorescence-activated cell sorting (FACS) to ensure collection of high-purity nuclei suitable for widely used droplet-based sequencing platforms (e.g., 10x Genomics single cell 3' or multiome). This protocol requires 4-5 h to complete and can be carried out by researchers with single-cell and flow cytometry training.

Journal Article↗

PubMed2026

Defining active and repressive chromatin states in neural crest cells using low-input CUT&RUN.

The transition of neural crest cells (NCCs) from a multipotent state to lineage-restricted derivatives, including melanocytes, is governed by tightly regulated epigenetic mechanisms that orchestrate cell type specific gene expression programs. Histone post-translational modifications (PTMs), in particular, play an important role in modulating chromatin accessibility, enhancer activation, and transcription factor occupancy, thereby facilitating dynamic chromatin and transcriptional reprogramming required during development. However, profiling such chromatin states in rare and transient Neural Crest Cell (NCC) populations in vivo remains technically challenging. To address this, we present an optimized low-input Cleavage Under Targets and Release Using Nuclease (CUT&RUN) workflow tailored for fluorescence-activated cell sorting (FACS) isolated NCCs from zebrafish embryos. This approach enables high-resolution and low-background mapping of key histone modifications, including H3K27ac, H3K4me3, and H3K27me3, from limited cell numbers. Collectively, these methodologies provide a robust framework for dissecting chromatin state dynamics in developmental systems and can also offer insights into epigenetic dysregulation associated with disease.

Animals↗

PubMed2026

Tumor-associated macrophages display differential protein cargo sorting in extracellular vesicles associated with poor survival in ovarian cancer.

Ovarian cancer (OC) progression and metastasis are promoted by ascites, which constitutes a central part of the tumor microenvironment (TME). In this fluid, tumor-associated macrophages (TAMs) represent a prominent immune cell type. In addition to tumor and other host cells such as TAMs, ascites is highly enriched in soluble factors as well as extracellular vesicles (EVs). How TAMs contribute to the EV compartment of the OC TME remains, however, underexplored. In this work peripheral blood monocytes from healthy donors were differentiated into monocyte-derived macrophages (MDMs) and polarized into classically activated (M1-like), alternatively activated (M2-like) and TAM-like (by ascites incubation). For all subtypes, serum-free conditioned medium was collected for 24 h and EVs were isolated and characterized by nano-flow cytometry (nFC), label-free mass spectrometry-based proteomics and electron microscopy, among others. Our results demonstrated distinct traits for EV release and cargo across the different macrophage subtypes. Specifically, TAM-like macrophages exhibited impaired release of small EVs and reduced frequency of tetraspanin-positive particles. These EV subpopulations displayed sizing profiles closer to M1-like than to M2-like samples. Also, the low EV release in TAM-like MDMs was accompanied by altered expression of biogenesis-related markers like flotillin-1 (FLOT1) and a decreased N-glycosylation of CD63 protein, which was validated in patient-derived samples. Remarkably, the EV-associated proteome of TAMs displayed significant enrichment in both pro- and anti-inflammatory molecules with clinical value. Markers significantly enriched in the ascites TAM-EV signature were mostly associated with poor prognosis, whereas M1-like EV-related markers (pro-inflammatory) were mostly associated with longer survival. Our results confirmed previous data for proteins like CD163 and MRC1 to be associated to TAM-EVs, while also describing novel candidates with diagnostic (i.e., COLEC12) and/or prognostic (i.e., MSR1) value in plasma. Taken together, our data support a unique secretory profile of TAMs in OC and provide new EV-associated biomarkers with translational impact. Our results pave the way for a better understanding of the mechanisms behind TAM-EV cargo loading and function, and how these cells participate in the TME landscape.

Humans↗

PubMed2026

Sperm subpopulations differing in mitochondrial abundance show divergent nuclear allele frequencies.

Mammalian ejaculates contain heterogeneous sperm subpopulations that differ in subcellular architecture and developmental history, despite appearing morphologically uniform. The extent to which this cellular heterogeneity reflects underlying nuclear genomic structure within a sire remains largely unexplored. Mitochondrial architecture in sperm is established during spermatogenesis, with final assembly and organization occurring during spermiogenesis under nuclear genomic control, positioning variation in mitochondrial abundance and organization as a potential phenomic indicator of within-sire allelic segregation. Here, we tested whether sperm subpopulations defined by differing mitochondrial abundance exhibit systematic differences in nuclear allele representation. Boar sperm were resolved into low and high mitochondrial subpopulations using fluorescence-activated cell sorting based on MitoTracker™ Green fluorescence while excluding debris, doublets, and non-viable cells. Epifluorescence microscopy confirmed that high MitoTracker™ Green fluorescence sperm possessed longer mitochondrial sheaths, validating a structural distinction between subpopulations. Whole-genome sequencing of paired mitochondrial subpopulations from three boars was performed, and allelic ratio distortion was evaluated relative to heterozygous baseline populations. Analyses across heterozygous loci genome-wide identified candidate allele frequency shifts between mitochondrial-defined subpopulations, suggesting non-random segregation of alleles within ejaculates. Using a minimum sequencing depth of 30 reads in both sorted fractions, 182 candidate SNPs were identified with evidence of allele-frequency differences between mitochondrial fluorescence-defined subpopulations. These findings suggest that sperm mitochondrial abundance can potentially serve as an indirect, high-throughput marker of nuclear genomic heterogeneity within sires. This proof-of-concept framework establishes a foundation for future studies integrating sperm phenotyping, genome-wide allele-frequency analysis and functional validation to better characterize gamete-level heterogeneity.

Male↗

PubMed2024

Exploring the clinical and biological significance of the cell cycle-related gene CHMP4C in prostate cancer.

BACKGROUND: Prostate cancer (PCa) stands as the second most prevalent malignancy impacting male health, and the disease's evolutionary course presents formidable challenges in the context of patient treatment and prognostic management. Charged multivesicular body protein 4 C (CHMP4C) participates in the development of several cancers by regulating cell cycle functions. However, the role of CHMP4C in prostate cancer remains unclear. METHODS: In terms of bioinformatics, multiple PCa datasets were employed to scrutinize the expression of CHMP4C. Survival analysis coupled with a nomogram approach was employed to probe into the prognostic significance of CHMP4C. Gene set enrichment analysis (GSEA) was conducted to interrogate the functional implications of CHMP4C. In terms of cellular experimentation, the verification of RNA and protein expression levels was executed through the utilization of qRT-PCR and Western blotting. Upon the establishment of a cell line featuring stable CHMP4C knockdown, a battery of assays, including Cell Counting Kit-8 (CCK-8), wound healing, Transwell, and flow cytometry, were employed to discern the impact of CHMP4C on the proliferation, migration, invasion, and cell cycle function of PCa cells. RESULTS: The expression of CHMP4C exhibited upregulation in both PCa cells and tissues, and patients demonstrating elevated CHMP4C expression levels experienced a notably inferior prognosis. The nomogram, constructed using CHMP4C along with clinicopathological features, demonstrated a commendable capacity for prognostic prediction. CHMP4C knockdown significantly inhibited the proliferation, migration, and invasion of PCa cells (LNcaP and PC3). CHMP4C could impact the advancement of the PCa cell cycle, and its expression might be regulated by berberine. Divergent CHMP4C expression among PCa patients could induce alterations in immune cell infiltration and gene mutation frequency. CONCLUSIONS: Our findings suggest that CHMP4C might be a prognostic biomarker in PCa, potentially offering novel perspectives for the advancement of precision therapy for PCa.

Humans↗

PubMed2025

Live-Cell Monitoring and Omics Analysis of Liquid-Solid Transitions of Biomolecular Condensates.

Biomolecular condensates, or so-called membraneless organelles, transition from liquid into more solid-like states over time, contributing to the development of pathological conditions. The present study proposes a simple method using photoactive yellow protein (PYP) and its specific fluorescent covalent ligands to distinguish between the liquid and solid states of protein condensates in live cells. The method, compatible with fluorescence-activated cell sorting (FACS), correlates the stiffness of specific protein condensates with their accessibility to PYP ligands, enabling quantitative multicolor monitoring of condensate solidification. We applied this technique to 12 phase-separating proteins and their mutants, finding that TDP-43, particularly its A315T mutant linked to familial amyotrophic lateral sclerosis, most readily forms solid aggregates. Furthermore, this FACS-compatible strategy enabled the isolation of distinct cell populations based on condensate states, allowing for subsequent proteomic and transcriptomic analyses. Our findings demonstrate that condensate solidification is accompanied by the upregulated expression of extracellular matrix proteins, suggesting a previously unrecognized link between solid aggregate formation and extracellular matrix hardening.

Humans↗

PubMed2024

Revealing differential expression patterns of piRNA in FACS blood cells of SARS-CoV-2 infected patients.

Non-coding RNA expression has shown to have cell type-specificity. The regulatory characteristics of these molecules are impacted by changes in their expression levels. We performed next-generation sequencing and examined small RNA-seq data obtained from 6 different types of blood cells separated by fluorescence-activated cell sorting of severe COVID-19 patients and healthy control donors. In addition to examining the behavior of piRNA in the blood cells of severe SARS-CoV-2 infected patients, our aim was to present a distinct piRNA differential expression portrait for each separate cell type. We observed that depending on the type of cell, different sorted control cells (erythrocytes, monocytes, lymphocytes, eosinophils, basophils, and neutrophils) have altering piRNA expression patterns. After analyzing the expression of piRNAs in each set of sorted cells from patients with severe COVID-19, we observed 3 significantly elevated piRNAs - piR-33,123, piR-34,765, piR-43,768 and 9 downregulated piRNAs in erythrocytes. In lymphocytes, all 19 piRNAs were upregulated. Monocytes were presented with a larger amount of statistically significant piRNA, 5 upregulated (piR-49039 piR-31623, piR-37213, piR-44721, piR-44720) and 35 downregulated. It has been previously shown that piR-31,623 has been associated with respiratory syncytial virus infection, and taking in account the major role of piRNA in transposon silencing, we presume that the differential expression patterns which we observed could be a signal of indirect antiviral activity or a specific antiviral cell state. Additionally, in lymphocytes, all 19 piRNAs were upregulated.

Humans↗

PubMed2025

Development and validation of a deep learning model based on cascade mask regional convolutional neural network to noninvasively and accurately identify human round spermatids.

INTRODUCTION: The difficulty of identifying human round spermatids (hRSs) has impeded applications of the human round spermatid injection (ROSI) technique. RSs can be accurately screened through flow cytometric analysis utilizing the Hoechst fluorescence profile reflecting DNA, but this method is not suitable for isolating hRSs due to the toxicity associated with Hoechst staining. OBJECTIVE: To evaluate the capacity of a deep learning model grounded in a cascade mask region-based convolutional neural network (R-CNN) for the noninvasive and accurate identification of hRSs. METHODS: In this study, we presented the development and validation of a deep learning model for identifying hRSs through the analysis of 3457 optical light microscope images of sorted hRSs obtained via flow cytometric analysis. The model's accuracy and specificity were evaluated by calculating the mean average precision (mAP). Furthermore, a double-blind experiment was conducted to access the reliability of the proposed model in accurately identifying hRSs. It detected the expression of protamine (PRM1) and/or peanut lectin (PNA), which are established markers for RSs. RESULTS: Our deep learning-based model demonstrated a high precision, achieving a mAP of over 0.80 for isolating hRSs in test datasets. The expression of PRM1 and/or PNA was observed in all cells noninvasively selected by our AI model during an independent double-blind test. This phenomenon confirmed the accuracy and effectiveness of the proposed model. The model's capability for noninvasive and accurate isolation of hRSs among spermatogenic cells highlighted its robustness and generalizability for clinical applications. CONCLUSION: The deep learning AI model based on a cascade R-CNN has the ability to accurately identify hRSs among spermatogenic cells. The application of this noninvasive method, which requires no additional procedures in clinical practice, is able to facilitate the widespread implementation of ROSI technique. Therefore, it can provide patients with spermatogenic arrest the opportunity to become biological fathers.

Humans↗