Search PubMed⌕ Search

SEARCH · Search PubMed

Results for “Single cell”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 451 records · Page 25Linked to original sources

Scalable single-cell total RNA-seq reveals non-coding programs in immunity, infection, and brain development.

Non-coding RNAs represent a widespread and diverse layer of post-transcriptional regulation across cell types and states, yet much of their diversity remains uncharted at single-cell resolution. This gap stems from the limitations of widely used single-cell RNA-sequencing protocols, which focus on polyadenylated transcripts and miss many short or non-polyadenylated RNAs. Here, we adapted single-cell RNA-sequencing on the 10x Genomics platform to capture a broad complement of coding and non-coding RNAs-including miRNAs, tRNAs, lncRNAs, histone RNAs, and non-adenylated viral transcripts. This approach enabled the discovery of rich, dynamic non-coding RNA programs across immune cells, virally infected hepatocytes, and the developing human brain. In dengue virus-infected hepatocytes, we detect non-adenylated viral transcripts and distinguish active from transcriptionally quiescent infected states, each with distinct host regulatory signatures. In brain tissue, we identify biotype-specific, cell-type-restricted non-coding RNAs, including miRNAs whose expression anticorrelates with predicted targets, consistent with post-transcriptional regulatory relationships. We show that MIR137, one of the strongest GWAS loci associated with schizophrenia and intellectual disability, is expressed specifically in Cajal-Retzius cells, an early-born but transient population that guides subsequent cortical neuron migration. These findings demonstrate the importance of non-coding RNAs in defining cell identity and state, and show how expanded transcriptome coverage can reveal additional layers of gene control-now accessible through practical and scalable single-cell profiling.

Journal Article↗

Single-cell chemical lysis in picoliter-scale closed volumes using a microfabricated device.

Investigating the intracellular contents of single cells is essential for understanding physiologic and pathologic processes at the cellular level. While existing protocols for cell lysis and sample preparation work well for larger samples, scaling to a single-cell level is challenging because of unavoidable analyte dilution and losses. Thus, we are proposing a microfabricated device for the controlled handling and mixing of picoliter cell suspension and lysis solution volumes. Cells and fluids are independently isolated in two microchambers of 25-pL volumes using the geometry of the microchannels and the coordinated action of four on-chip thermopneumatic actuators. Virtual walls formed by liquid-air interfaces in the hydrophobic capillary separate the two volumes, which are subsequently allowed to mix after drawing the air out of the capillary connecting the two microchambers. Following cell lysis, a limited and stable dilution of intracellular components is achieved, simplifying the requirements for subsequent analysis. Two assays at single-cell level, one for direct estimation of the intracellular concentration of a soluble dye and the other for indirect evaluation of intracellular quantities of insoluble actin, demonstrate the use of the microfabricated device for single-cell assays.

Calibration↗

Cell sampling and analysis (SiCSA): metabolites measured at single cell resolution.

By using a fine oil-filled glass microcapillary mounted on a micromanipulator, the solutes of individual plant cells can be sampled. These samples can then be analysed using a range of physical and chemical methods. Hydrostatic pressure (cell pressure probe), osmotic pressure (picolitre osmometer), organic solutes (enzyme-linked fluorescence microscope spectrometry or capillary electrophoresis), inorganic solutes (X-ray microdroplet analysis or capillary electrophoresis), (14)C (mass spectrometry), proteins (microdroplet immunoblotting), and mRNA (rt PCR) have been measured. Collectively, the battery of techniques is called single cell sampling and analysis (SiCSA) and all of the techniques have relevance to the study of plant metabolism at the resolution of the individual cell. This review summarizes the techniques for SiCSA and presents examples of applications used in this laboratory, in particular those relating to cell metabolism.

Cells↗

Coalescing single-cell genomes and transcriptomes to decode breast cancer progression.

Understanding epithelial lineages of breast cancer and genotype-phenotype relationships requires direct measurements of the genome and transcriptome of the same single cells at scale. To achieve this, we developed wellDR-seq, a high-genomic-resolution, high-throughput method to simultaneously profile the genome and transcriptome of thousands of single cells. We profiled 33,646 single cells from 12 estrogen-receptor-positive breast cancers and identified ancestral subclones in multiple patients that showed a luminal hormone-responsive lineage, indicating a potential cell of origin. In contrast to bulk studies, wellDR-seq enabled the study of subclone-level gene-dosage relationships, which showed near-linear correlations in large chromosomal segments and extensive variation at the single-gene level. We identified dosage-sensitive and dosage-insensitive genes, including many breast cancer genes as well as sporadic copy-number aberrations in non-cancer cells. Overall, these data reveal complex relationships between copy number and gene expression in single cells, improving our understanding of breast cancer progression.

Breast Neoplasms↗

Single cell analysis of switch-like induction of CYP1A1 in liver cell lines.

The shape of the dose-response curve may vary depending on whether one examines response at a population or a single cell level. Populations of cells may exhibit a graded response whereas single cell responses may have threshold or switch-like behavior. Studies in vivo and in vitro using primary hepatocyte cultures have shown that induction of CYP1A1 in the liver exhibits switch-like behavior in response to PCB 126 (3,3',4,4',5-pentachlorobiphenyl). The goal of the present study was to determine if two liver cell lines (H4IIE rat hepatoma and Hepa 1c1c7 mouse hepatoma) also show switch-like behavior and develop experimental models for studying mechanisms of these switch-like responses. Both cell lines were analyzed via concentration-response and time-course studies using quantitative real-time PCR, revealing a sigmoidal concentration-response curve for CYP1A1 mRNA induction at the population level. To study CYP1A1 protein induction on a single cell level, flow cytometry was employed. In both cell lines the distribution of fluorescence increased with increasing concentrations of PCB 126. The switch behavior was more pronounced in the H4IIE cells than in the Hepa 1c1c7 cells, exhibiting a well-defined shift of induction from the "off" to the "on" state. The concentration-response curve at the single cell level appeared more switch-like with two populations of cells-basal levels and maximally induced. Immunocytochemistry studies of individual cells also support these conclusions. Our data support the hypothesis that PCB 126 induces CYP1A1 in a switch-like fashion in H4IIE rat hepatoma cells. These cells can now be used to study the mechanism of the biological switch.

Animals↗

Polygenic enrichment analysis in multi-omics levels identifies cell/tissue specific associations with schizophrenia based on single-cell RNA sequencing data.

OBJECTIVE: Understanding the specific cellular origin and tissue heterogeneity in schizophrenia is critically important for exploring the disease etiology. This study aims to investigate these aspects by performing multiple analyses based on omics data. METHOD: We performed single-cell disease relevance score (scDRS) algorithm to link brain single-cell RNA sequencing (scRNA-seq) with schizophrenia risk across multi-omics scales at single-cell resolution. This approach identified cell types with overexpression of schizophrenia-related genes implicated by multi-omics panels (ATAC-seq, RNA-seq, TWAS, and GWAS). Schizophrenia-related genes from these multi-omics panels were extracted and combined with scRNA-seq data to calculate scDRS. Subsequently, the cell-type vs. disease association and tissue heterogeneity were assessed using scDRS for each omics panel. RESULTS: We identified two novel cell subpopulations in the brain that differentially express SCUBE3 (59 cells, 7.0 %) and FN1 (21 cells, 2.5 %). At the individual cell level, schizophrenia-associated cell subpopulations included microglial cell associated with ATAC-seq panel (Passociation = 0.002, Pheterogeneity = 0.009) and deep layer neuron suggestively associated with GWAS panel (Passociation = 0.033, Pheterogeneity = 0.017). At the brain tissue level, microglial cell was significantly associated with cortical plate in ATAC-seq panel (Passociation = 0.002, Pheterogeneity = 0.011). Gene level analysis identified several genes associated with schizophrenia across multi-omics panels. CONCLUSIONS: Our study outlines the signature of cell subpopulations, brain regions, and disease risk genes in schizophrenia at single-cell resolution across multi-omics scales. These findings provide a reference for future precision medicine approaches targeting specific cell types and brain regions in schizophrenia.

Schizophrenia↗

An improved single-cell cDNA amplification method for efficient high-density oligonucleotide microarray analysis.

A systems-level understanding of a small but essential population of cells in development or adulthood (e.g. somatic stem cells) requires accurate quantitative monitoring of genome-wide gene expression, ideally from single cells. We report here a strategy to globally amplify mRNAs from single cells for highly quantitative high-density oligonucleotide microarray analysis that combines a small number of directional PCR cycles with subsequent linear amplification. Using this strategy, both the representation of gene expression profiles and reproducibility between individual experiments are unambiguously improved from the original method, along with high coverage and accuracy. The immediate application of this method to single cells in the undifferentiated inner cell masses of mouse blastocysts at embryonic day (E) 3.5 revealed the presence of two populations of cells, one with primitive endoderm (PE) expression and the other with pluripotent epiblast-like gene expression. The genes expressed differentially between these two populations were well preserved in morphologically differentiated PE and epiblast in the embryos one day later (E4.5), demonstrating that the method successfully detects subtle but essential differences in gene expression at the single-cell level among seemingly homogeneous cell populations. This study provides a strategy to analyze biophysical events in medicine as well as in neural, stem cell and developmental biology, where small numbers of distinctive or diseased cells play critical roles.

Animals↗

Microscopy-based multicolor tissue cytometry at the single-cell level.

Cytomics is a novel perspective from which to look at life. As with genomics and proteomics before, this discipline requires novel and innovative techniques and technologies to focus on its substrate of research--the cytome. With cytomics being the discipline that analyzes cellular systems and their interdependencies, advanced microscopy represents a key technology in cytomics research. Yet, conventional microscopy-based investigations, i.e., "look and conclude" analyses, do not meet the major cytomics criteria of 1) relating multiple parameters to each other, 2) within large populations of cells, 3) on a single-cell basis, and 4) in a quantitative and observer-independent manner. However, emerging improvements in the fields of fluorophore technology, sensitive fluorescence detection devices, and sophisticated image analysis procedures, are important and necessary steps into the cytomics era. Tissue represents an important class of cytomes, hence tissue cytometry--on the single cell level--can be expected to become an important cytomics technology. In this report, the techniques and technologies of microscopy-based multicolor tissue cytometry (MMTC) are outlined and applications are discussed, including the phenotypic characterization of tissue infiltrating leukocytes, in situ quantification of proliferation markers and tumor suppressors, and in situ quantification of apoptosis.

Apoptosis↗

Resolution of DNA damage at the single-cell level shows largely different actions of X-rays and bleomycin.

Both X-rays and the radiomimetic agent bleomycin (BLM) induce DNA strand breaks, predominantly via reactive radicals. To compare the induction of breaks with the two agents in Chinese hamster (CHO-K1) cells, two different alkaline unwinding methods, a 3H tracer-based analysis of large cell populations and an optical adaption allowing measurement of single cells, were applied. Radiation and BLM show qualitatively similar dose responses when the average number of DNA strand breaks is measured in a large cell population. However, the breakage pattern at the single-cell level indicates large discrepancies between the actions of the two agents. Irradiated cells show a uniform distribution of DNA strand breaks over the cell population. Effects of treatment with 30 micrograms x ml-1 BLM for 2 hr vary from practically zero in some cells to high levels of DNA strand breakage in others. Unlike the repair of radiation-induced DNA breaks, the repair efficiency of BLM-induced DNA strand breaks, as measured at the single-cell level, varies strongly among cells of the same population. Such heterogeneity at the cellular level potentially reduces BLM's usefulness for tumor therapy because the appearance of BLM-resistant subpopulations may critically impair treatment outcome.

Animals↗

Multiple displacement amplification on single cell and possible PGD applications.

Multiple displacement amplification (MDA) is a technique used in the amplification of very low amounts of DNA and reported to yield large quantities of high-quality DNA. We used MDA to amplify the whole genome directly from a single cell. The most common techniques used in PGD are PCR and fluorescent in-situ hybridization (FISH). There are many limitations to these techniques including, the number of chromosomes diagnosed for FISH or the quality of DNA issued from a single cell PCR. This report shows, for the first time, use of MDA for single cell whole genome amplification. A total of 16 short tandem repeats (STRs) were amplified successfully with a similar pattern to the genomic DNA. Furthermore, allelic drop out (ADO) derived from MDA was assessed in 40 single cells by analysing (i) heterozygosity for a known beta globin mutation (IVSI-5 C-G) and by studying (ii) the heterozygous loci present in the STRs. ADO turned out to be 10.25% for the beta globin gene sequencing and 5% for the fluorescent PCR analysis of STRs. Moreover, the amplification accuracy of MDA permitted the detection of trisomy 21 on a single cell using comparative genome hybridization-array. Altogether, these data suggest that MDA can be used for single cell molecular karyotyping and the diagnosis of any single gene disorder in PGD.

Alleles↗

Comparison of the survival of fresh or cultured pancreatic islets, pseudoislets and single cells following allotransplantation beneath the kidney capsule in non-immunosuppressed diabetic rats.

The purpose of the present study was to examine the effect of culture pretreatment and islet structure on transplantation survival time. Donors for islet isolation were highly inbred male Lewis rats (RT 1(1)). Production of single cells was performed by using EDTA and Trypsin. Pseudo-islets were produced by culturing single cell suspensions at 37 degrees C for 12-14 days. Recipients were BDE rats (RT 1u), made diabetic by streptozotocin injection. 1000-1200 islets (or corresponding amount of single cells or pseudoislets) were transplanted to the subcapsular renal space. Five groups were transplanted. Group 1 (n = 5) received freshly isolated islets of Langerhans. Group 2 (n = 7) received single cells, produced from freshly isolated islets. In group III (n = 7) pseudoislets were transplanted. The animals of group IV received 37 degrees C cultured islets (12-14 days), while group V received single cells consisting of 12-14 day cultured islets at 37 degrees C. The median survival times were: gr. I 7 d.; gr. II 5 d.; gr. III 120 d.; gr. IV 11 d.; gr. V 9 d.. Group III showed a prolongation of allograft survival that was statistically significant compared to all other groups. 4 from 7 animals showed a long-term acceptance. It can be concluded that neither culturing islets at 37 degrees C nor producing single cells achieves long-term acceptance. Transplanting pseudoislets resulted in a long-term acceptance of allograft, without immunosuppression of the host. Three factors may be responsible for this success: Firstly, a reduced number of class-II-antigen positive cells, secondly, metabolic state of rest, and thirdly, the transplantation site.

Animals↗

Single-cell transcript analysis of pancreas development.

DNA microarray analysis was combined with a modified single-cell PCR procedure to study gene expression profiles of single cells at different stages of pancreatic development. This method identifies distinct cell types at embryonic day 10.5, a stage when the pancreatic epithelium is morphologically uniform. Some cells express unexpected combinations of genes, and these expression patterns provide new insights into pancreas development. Following on these findings, we use PCR products from different cell types to identify novel pancreatic genes, some of which mark subtypes of developing pancreatic cells. By integrating these data with previous genetic and biochemical studies, we propose a pathway for pancreatic cell development. This form of single-cell transcriptional analysis can be applied to any developmental process or tissue to characterize distinct cell types.

Animals↗

Microfluidic techniques for single-cell protein expression analysis.

BACKGROUND: The analysis of single cells obtained from needle aspirates of tumors is constrained by the need for processing. To this end, we investigated two microfluidic approaches to measure the expression of surface proteins in single cancer cells or in small populations (<50 cells). METHODS: One approach involved indirect fluorescence labeling of cell-surface proteins and channeling of cells in a microfluidic device past a fluorescence detector for signal quantification and analysis. A second approach channeled cells in a microfluidic device over detection zones coated with ligands to surface proteins and measured rates of passage and of retardation based on transient interactions between surface proteins and ligands. RESULTS: The fluorescence device detected expression of integrin alpha5 induced by basic fibroblast growth factor (FGF-2) treatment in MCF-7 cells and that of Her-2/neu in SK-BR-3 cells compared with controls. Experiments measuring passage retardation showed significant differences in passage rates between FGF-2-treated and untreated MCF-7 cells over reaction regions coated with fibronectin and antibody to integrin alpha5beta1 compared with control regions. Blocking peptides reversed the retardation, demonstrating specificity. CONCLUSIONS: Immunofluorescence detection in a microfluidic channel demonstrates the potential for assaying surface protein expression in a few individual cells and will permit the development of future iterations not requiring cell handling. The flow retardation device represents the first application of this technology for assessing cell-surface protein expression in cancer cells and may provide a way for analyzing expression profiles of single cells without preanalytical manipulation.

Antibodies↗

Causal assessment of Bayesian gene regulatory networks from single-cell transcriptomics.

Gene regulatory network (GRN) inference is an essential tool for revealing dysregulated relationships between genes in different cell types from single-cell transcriptomic (SCT) data. GRNs based on Bayesian networks (BNs) learned from SCT data can elucidate directed regulatory relationships representing complex disease mechanisms and their interplay through graphical modeling. However, software for learning BNs from SCT data is not widely available, nor is software for evaluating the BNs' structural accuracy in representing causal relationships between genes. Here, we describe the scstruc R package. This package provides a suite of BN structure learning algorithms specifically designed to handle SCT data, to evaluate the resulting networks based on the causal relationships they represent regardless of the availability of established molecular interaction networks, and to compare regulatory relationships between conditions. We demonstrated that scstruc can identify biologically relevant differential regulatory relationships between groups on a per-cell basis.

Bayesian networks↗

High-dose combination alkylating agents with autologous bone-marrow support in patients with breast cancer: preliminary assessment of DNA damage in individual peripheral blood lymphocytes using the single cell gel electrophoresis assay.

The single cell gel (SCG) assay is a sensitive electrophoretic technique for detecting the presence of DNA single strand breaks and alkali-labile damage in individual cells. This technique was used to evaluate the levels of DNA damage in cryopreserved peripheral blood lymphocytes (PBLs) from 11 breast cancer patients treated with high doses of cyclophosphamide and cisplatin and provided autologous bone marrow transplantation after treatment. PBL specimens for the SCG study were obtained just prior to treatment, following the administration of cyclophosphamide and cisplatin for 2 days, and upon lymphocytic recovery. Based on a concurrent analysis of DNA damage in cryopreserved and non-cryopreserved PBL samples from three patients, the mean level of DNA migration or the dispersion of damage among cells was not affected by the process of cryopreservation. The pre-treatment samples of several patients contained PBL with increased levels of DNA damage, presumably reflecting persistent DNA damage induced by previous treatment regimens. Chemotherapy resulted in a significant but variable increase in DNA damage in PBL samples from all patients. In this limited study, the level of damage did not correlate with serum levels of cyclophosphamide or with lymphocyte toxicity. Among the post-treatment samples, increased levels of DNA damage were absent in most but not all patients. The presence of damaged cells in the post-treatment samples may be indicative of an inadequate therapy regimen or of DNA damage resulting from non-therapy related processes. Because of its simplicity and short processing time, the SCG assay can be used to evaluate levels of DNA damage during the course of therapy, allowing the dose schedule to be altered to achieve a desired effect level.

Adult↗

Unveiling tumor heterogeneity by single cell RNA-sequencing: From basic considerations to clinical applications.

Tumor heterogeneity-encompassing diverse cellular phenotypes, genomic alterations, and microenvironmental contexts-is a principal barrier to effective cancer therapy. Single-cell RNA sequencing (scRNA-seq) has transformed our ability to resolve this complexity by capturing transcriptomes at single-cell resolution. Here, we review the technical foundations required for high-quality scRNA-seq studies. We then trace the evolution of scRNA-seq platforms from manual micromanipulation to high-throughput systems, and describe the computational pipelines that enable reliable data interpretation. The application of scRNA-seq is exemplarily shown in the context of lung cancer, where single-cell profiling has revealed (i) the clonal and sub-clonal architecture of tumors, (ii) extensive remodeling of the immune microenvironment, iii) key mechanisms underlying resistance to targeted agents and immune-checkpoint blockade, and (iv) the dynamics of neo-antigen-specific T-cell responses. Integrating machine-learning techniques-such as deep-learning classifiers and graph-based models-with single-cell transcriptomic data has markedly sped up biomarker discovery, produced more accurate risk-stratification scores, and enabled the generation of patient-specific therapeutic predictions. We surveyed the major trial registry ClinicalTrials.gov and identified &#x223c;380&#xa0;ongoing or completed studies that explicitly incorporate scRNA-seq as a correlative or pharmacodynamic endpoint. Overall, the analysis shows that scRNA-seq becomes an increasingly important component of modern trials, providing high-resolution cellular and molecular readouts that complement conventional imaging and bulk-omics endpoints. While key challenges remain, ranging from costs, scalability and need for rigorous validation before routine clinical deployment, ongoing technological advances continue to expand the potential of scRNA-seq as a cornerstone of precision medicine.

Humans↗

Allele dropout in sequential PCR and FISH analysis of single cells (cell recycling).

PURPOSE: Our purpose was to investigate the feasability of using sequential PCR and FISH analysis of single cells for preimplantation diagnosis. METHODS: Protocols for sequential PCR and FISH analysis of a single fibroblast (cell recycling) were optimized for six loci and the rates of allele specific dropout (ADO) were determined. RESULTS: Conditions that allow reliable genotyping of single cells in lysis buffer were not optimal for amplifying fibroblasts fixed to coverslips. After optimizing conditions, we observed a success rate of 85% for both analyses in sequential PCR-FISH experiments in single cells for the four loci studied. The individual success rates for each technique revealed a slightly higher rate for FISH (91-95%) than for PCR (85-87%) for single cells on coverslips. The presence of two hybridization signals in FISH experiments demonstrated that the failure to amplify both alleles from heterozygous cells on coverslips was due to true ADO, and not the loss of chromosomal material. The ADO rate observed on coverslips varied between 10 and 14%, which is significantly higher than that observed in solution, even after meticulous optimization. CONCLUSIONS: Sequential PCR and FISH analysis of single cells remains an attractive possibility. However, until the problem of the increased rate of ADO is resolved, cell recycling should be applied to clinical preimplantation genetic analysis.

Alleles↗

Single-cell multiomics reveals exosome-mediated reprogramming and clonotypic remodeling of T cells in triple-negative breast cancer.

Triple-negative breast cancer (TNBC) is an aggressive and immunogenic subtype lacking targeted therapies. While tumor-derived exosomes are known to modulate immune function, their direct impact on human T cell plasticity and antigen specificity remains poorly defined. Here, we conducted a comprehensive single-cell multiomic analysis of primary human T cells exposed to exosomes derived from 17 genomically diverse TNBC cell lines and 35 patient samples. Integrating single-cell RNA-seq, V(D)J sequencing, non-coding RNA profiling, bulk and single-cell cytokine analyses, we uncovered conserved and subtype-specific immunomodulatory programs induced by TNBC exosomes. Exosome-treated T cells displayed skewing toward regulatory and dysfunctional phenotypes, including Th17-like, Treg, and PD-1&#x207a;/PD-L1&#x207a; Tfh cells. Functional profiling revealed suppression of early activation markers and cytokine responses, alongside selective preservation of cytotoxic features in &#x3b3;&#x3b4; T and NKT subsets. Transcriptomic and miRNA network analyses demonstrated widespread downregulation of immune effector genes (e.g., HBEGF and TNFSF9) mediated by exosome-delivered regulatory miRNAs (has-miR-98-5p). Notably, exosome-stimulated T cells displayed distinct clonotypic expansions, characterized by the emergence of five tumor-specific &#x3b3;&#x3b4; TCR clonotypes and 30 unique &#x3b1;&#x3b2; TCR CDR3 sequences that were absent in mock-treated controls, underscoring the role of exosomes in shaping TCR repertoire dynamics.

Humans↗