Micro sample and single cell analysis. UCLA 12-724.
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Cell Biology↗
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Muscular cavernous single cell analysis (MCSCA) in patients with venoocclusive dysfunction (VOD).
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Action Potentials↗
Single-cell analysis of intercellular heteroplasmy of mtDNA in Leber hereditary optic neuropathy.
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DNA Mutational Analysis↗
High resolution array-CGH analysis of single cells.
Heterogeneity in the genome copy number of tissues is of particular importance in solid tumor biology. Furthermore, many clinical applications such as pre-implantation and non-invasive prenatal diagnosis would benefit from the ability to characterize individual single cells. As the amount of DNA from single cells is so small, several PCR protocols have been developed in an attempt to achieve unbiased amplification. Many of these approaches are suitable for subsequent cytogenetic analyses using conventional methodologies such as comparative genomic hybridization (CGH) to metaphase spreads. However, attempts to harness array-CGH for single-cell analysis to provide improved resolution have been disappointing. Here we describe a strategy that combines single-cell amplification using GenomePlex library technology (GenomePlex) Single Cell Whole Genome Amplification Kit, Sigma-Aldrich, UK) and detailed analysis of genomic copy number changes by high-resolution array-CGH. We show that single copy changes as small as 8.3 Mb in single cells are detected reliably with single cells derived from various tumor cell lines as well as patients presenting with trisomy 21 and Prader-Willi syndrome. Our results demonstrate the potential of this technology for studies of tumor biology and for clinical diagnostics.
Carcinoma, Renal Cell↗
scSurv: a deep generative model for single-cell survival analysis.
MOTIVATION: Single-cell omics analysis has unveiled the heterogeneity of various cell types within tumors. However, no methodology currently reveals how this heterogeneity influences cancer patient survival at single-cell resolution. Here, we introduce scSurv, combining a Cox proportional hazards model with a deep generative model of single-cell transcriptome, to estimate individual cellular contributions to clinical outcomes. RESULTS: The accuracy of scSurv was validated using both simulated and real datasets. This method identifies cells associated with favorable or adverse prognoses and extracts genes correlated with their contribution levels. In melanoma, scSurv reproduces known prognostic macrophage classifications and facilitates hazard mapping through spatial transcriptomics in renal cell carcinoma. We also identified genes consistently associated with prognosis across multiple cancers and demonstrated the applicability of this method to infectious diseases. scSurv is a novel framework for quantifying the heterogeneity of individual cellular effects on clinical outcomes. AVAILABILITY: The implementation of scSurv is available on GitHub (https://github.com/3254c/scSurv) and Zenodo (https://doi.org/10.5281/zenodo.17793054).
Humans↗
Chemical analysis of single cells and exocytosis.
Recent advances in the development of microscale analytical techniques have allowed minute amounts of compounds of biological interest to be monitored in microenvironments. Microcolumn separation techniques, such as microcolumn liquid chromatography and capillary electrophoresis, provide a means of obtaining high-efficiency separations of analytes in picoliter to femtoliter volume samples. Voltammetric microelectrode techniques, such as amperometry and fast-scan cyclic voltammetry, are ideally suited for monitoring transiently occurring chemical events in cellular and subcellular processes owing to their rapid response times and small structural dimensions. The principles and applications of these techniques in single-cell analysis are discussed throughout this review. Multicomponent separations and quantitations of large invertebrate neurons of the land snail Helix neurons and the pond snail Planorbis corneus dopamine neurons, and of small mammalian cells, bovine adrenal cells, rat PC12 cells, and human lymphocytes, by use of microcolumn liquid chromatography and capillary electrophoresis are presented. Electrochemical monitoring of neurotransmitter exocytosis from single adrenal cells, from PC12 cells, and from the cell body of the Planorbis dopamine neuron is highlighted. Results obtained from both separation and voltammetric techniques in single-cell analyses will provide a better understanding of cellular and/or neuronal chemistry and biology in complicated living environments.
Adrenal Medulla↗
SLB-msSIM: A Spectral Library-Based Multiplex Segmented SIM Platform for Single-Cell Proteomic Analysis.
Mass spectrometry (MS)-based single-cell proteomics, while highly challenging, offers unique potential for a wide range of applications to interrogate cellular heterogeneity, trajectories, and phenotypes at a functional level. We report here the development of the spectral library-based multiplex segmented selected ion monitoring (SLB-msSIM) method, a conceptually unique approach with significantly enhanced sensitivity and robustness for single-cell analysis. The single-cell MS data is acquired by a multiplex segmented selected ion monitoring (msSIM) technique, which sequentially applies multiple isolation cycles with the quadrupole using a wide isolation window in each cycle to accumulate and store precursor ions in the C-trap for a single scan in the Orbitrap. Proteomic identification is achieved through spectral matching using a well-defined spectral library. We applied the SLB-msSIM method to interrogate cellular heterogeneity in various pancreatic cancer cell lines, revealing common and distinct functional traits among PANC-1, MIA-PaCa2, AsPc-1, HPAF, and normal HPDE cells. Furthermore, for the first time, our novel data revealed the diverse cell trajectories of individual PANC-1 cells during the induction and reversal of epithelial-mesenchymal transition (EMT). Collectively, our results demonstrate that SLB-msSIM is a highly sensitive and robust platform, applicable to a wide range of instruments for single-cell proteomic studies. SUMMARY: We present the SLB-msSIM method, a conceptually unique approach in mass spectrometry-based single-cell proteomics that significantly enhances sensitivity and robustness. This innovative platform enables detailed analysis of the proteome landscape, capturing cellular heterogeneity, trajectories, and phenotypes at a single-cell resolution. Utilizing the SLB-msSIM technique, we identified both common and distinct functional traits among various pancreatic cancer cell lines and normal cells. Moreover, our study unveiled new insights into the diverse cell trajectories of individual cancer cells during the induction and reversal of epithelial-mesenchymal transition (EMT). In summary, the SLB-msSIM method offers a highly sensitive and robust platform for single-cell proteomic studies, with broad applicability across different instruments.
Single-Cell Analysis↗
Rapid assessment of the physiological status of Streptococcus macedonicus by flow cytometry and fluorescence probes.
Flow cytometry in combination with fluorescence probes was applied to rapidly assess the physiological status of Streptococcus macedonicus ACA-DC 198, a newly described member of the lactic acid bacteria group with technologically important features (e.g. lantibiotic production). A sonication procedure was developed for disaggregating typical streptococci chains in order to optimize cell preparations for single cell analysis. Single stained live and dead populations of S. macedonicus cells were clearly resolved based on membrane potential by bis-oxonol [DiBAC(4)(3)], membrane integrity by Propidium Iodide (PI) and enzymatic activity as well as membrane integrity by Carboxyfluorescein Diacetate (cFDA). Further, estimation of both live and dead cells by a cFDA/PI two-colour flow cytometric assay showed excellent correlation with the dead cells in the samples (dead(FCM)=0.9945 dead(S)-0.806, R(2)=0.9986 and live(FCM)=-0.978 dead(S)+98.895, R(2)=0.9992). Finally, the assay was applied to study the physiology of S. macedonicus after acid stress. Interestingly, in situ assessment of the physiological status of stressed S. macedonicus cells by flow cytometry and single cell sorting revealed the coexistence of three distinct subpopulations according to their fluorescence labelling behaviour and culturability, representing intact/culturable, permeabilized/dead and potentially injured cells with the latter exhibiting both metabolic activity and membrane permeabilization as well as decreased culturability.
Cell Membrane Permeability↗
Challenges of single-cell diagnostics: analysis of gene expression.
Analysis of single-cell gene expression promises a more precise understanding of human disease pathogenesis and important diagnostic applications. Here, we review the rationale for the study of gene expression at the single-cell level, practical methods to isolate homogeneous or single-cell samples, and current approaches to the analysis of single-cell gene expression. Finally, we highlight applications of laser microdissection-based gene expression analysis to the study of human disease and clinical diagnosis.
Animals↗
Single-cell protein analysis of a single mouse embryo by two-dimensional capillary electrophoresis.
The characterization of protein expression from a single-cell mouse embryo using two-dimensional capillary electrophoresis (2D-CE) is described. These zygotes were obtained from Hsf1 gene knockout mice. Single zygotes were lysed off-column and proteins were fluorescently labeled using the fluorogenic dye 3-(2-furoyl)quinoline-2-carboxaldehyde (FQ). After injection, analytes were separated first according to molecular weight using capillary sieving electrophoresis (CSE) and then by micellar electrokinetic capillary chromatography (MEKC) to obtain protein expression fingerprints. Analytes were detected in a sheath flow cuvette using laser-induced fluorescence. In a 1-h 2D-CE separation, over 100 components were resolved with a spot capacity of 380.
Animals↗
Quantitative chemical analysis of single cells.
A fundamental perspective can be achieved by targeting single cells for analysis with the goal of deconvoluting complex biological functions. However, single-cell studies have their own difficulties, such as minute volumes and sample amounts. Quantitative chemical analysis of single cells has emerged as a powerful new area in recent years due to several technological advancements. The development of microelectrodes has allowed the measurement of redox-active species as a function of cellular dynamics. This miniaturization trend is also evident in the separation sciences with the application of small column separations to single cells. Desorption ionization methods with mass spectrometric detection have shown single-cell capability owing to numerous technological developments. Finally, fluorescence imaging has also progressed to the point where single-cell dynamics can be probed by native fluorescence utilizing either single or multiple photon excitation. The results of these studies are reviewed with an emphasis on the quantitation of single-cell dynamics.
Animals↗
mRNA analysis of single living cells.
Analysis of specific gene expression in single living cells may become an important technique for cell biology. So far, no method has been available to detect mRNA in living cells without killing or destroying them. We have developed here a novel method to examine gene expression of living cells using an atomic force microscope (AFM). AFM tip was inserted into living cells to extract mRNAs. The obtained mRNAs were analyzed with RT-PCR, nested PCR, and quantitative PCR. This method enabled us to examine time-dependent gene expression of single living cells without serious damage to the cells.
Journal Article↗
Integrative analyses of mendelian randomization and bioinformatics reveal casual relationship and genetic links between COVID-19 and knee osteoarthritis.
BACKGROUND: Clinical and epidemiological analyses have found an association between coronavirus disease 2019 (COVID-19) and knee osteoarthritis (KOA). Infection with COVID-19 may increase the risk of developing KOA. OBJECTIVES: This study aimed to investigate the potential causal relationship between COVID-19 and KOA using Mendelian randomization (MR) and to explore the underlying mechanisms through a systematic bioinformatics approach. METHODS: Our investigation focused on exploring the potential causal relationship between COVID-19, acute upper respiratory tract infection (URTI) and KOA utilizing a bidirectional MR approach. Additionally, we conducted differential gene expression analysis using public datasets related to these three conditions. Subsequent analyses, including transcriptional regulation analysis, immune cell infiltration analysis, single-cell analysis, and druggability evaluation, were performed to explore potential mechanisms and prioritize therapeutic targets. RESULTS: The results indicate that COVID-19 has a one-way impact on KOA, while URTI does not play a causal role in this association. Ribosomal dysfunction may serve as an intermediate factor connecting COVID-19 with KOA. Specifically, COVID-19 has the potential to influence the metabolic processes of the extracellular matrix, potentially impacting the joint homeostasis. A specific group of genes (COL10A1, BGN, COL3A1, COMP, ACAN, THBS2, COL5A1, COL16A1, COL5A2) has been identified as a shared transcriptomic signature in response to KOA with COVID-19. Imatinib, Adiponectin, Myricetin, Tranexamic acid, and Chenodeoxycholic acid are potential drugs for the treatment of KOA patients with COVID-19. CONCLUSIONS: This study uniquely combines Mendelian randomization and bioinformatics tools to explore the possibility of a causal relationship and genetic association between COVID-19 and KOA. These findings are expected to provide novel perspectives on the underlying biological mechanisms that link COVID-19 and KOA.
Humans↗
Global gene expression analysis of single cells.
Gene expression profiling is increasingly being used to study complex disease processes, with a focus toward generating new hypotheses and identifying novel therapeutic approaches. This method requires not only the ability to assign expression data to the correct cell type, but also the aptitude to interpret the subsequent deluge of gene expression patterns. Single-cell gene expression analysis is currently used to generate data within the fundamental unit, the single cell, thereby freeing the analysis from assumptions or questions regarding cell population homogeneity, whether cell-type or temporal. Single-cell expression profiling also offers a highly parallel view of the workings of a gene regulatory network at one specific point in time, and will hopefully provide insights that could lead to an improved ability to interpret gene expression patterns.
Animals↗
Imaging analysis of STAT1 and NF-kappaB translocation in dendritic cells at the single cell level.
Rapid assessment of immune or stem cells, which are now widely applied in the clinical setting of cancer treatment, is necessary to speed their development and to determine their quality. We have evaluated immature dendritic cells (iDC) by semiautomated imaging cytometry which provides detailed assessment at a single cell level. Nuclear translocation of NF-kappaB was studied by imaging analysis as well as electrophoretic mobility shift assay with an excellent correlation (r=0.981) over a broad range of lipopolysaccharide (LPS) concentrations. Imaging analysis was time saving (5 h vs. 3 days), and required 30- to 100-fold less cells per analysis. Single cell information revealed remarkable heterogeneity between individual iDC and permitted detection of responses to 40 pg/ml of LPS. In IL-1beta/IFNgamma activated iDC, STAT1 responses preceded NF-kappaB responses, and the expression of both was strongly correlated in individual cells (p<0.001). IFNgamma amplified IL-1-induced NF-kappaB responses. NF-kappaB responses to IL-1beta, CD40L, and LPS were donor-dependent (n=7), correlated with the quality of iDC preparations (p=0.002), and IL-12 p70 production (p=0.010). NF-kappaB measurements in iDC within mixed cell cultures (iDC, NK, K562) demonstrated that these strategies are applicable for analyses of complex cell-cell interactions. Imaging analysis is a method that could be valuable for quality control of cell therapy preparations.
Antineoplastic Agents↗
[Analysis of single cells by capillary electrophoresis].
A review with 46 references is given on the application of capillary electrophoresis to the analysis of single cells. Injection modes, detectors and future prospects of this microseparation technique for single-cell analysis are described in detail.
Animals↗
Gene expression in individual cells: analysis using global single cell reverse transcription polymerase chain reaction (GSC RT-PCR).
The determination of the gene expression pattern of single cells has important implications for many areas of cellular and developmental biology including lineage determination, identification of primitive stem cells and temporal gene expression patterns induced by changes in the cellular microenvironment. Global Single Cell Reverse Transcription-Polymerase Chain Reaction (GSC RT-PCR) enables the study of single cell gene expression patterns. Initial observations of significant heterogeneity among single cells derived from a population of cells prompted us to determine how much of this observed heterogeneity was due to the intrinsic variation within the method. In this paper we discuss the sensitivity of GSC RT-PCR for analysis of differences in gene expression between single cells and, in particular, detail the amount of variation generated by the method itself. We found that most of the intrinsic variation in the method occurred in the PCR step. The total variation induced by the method was in the range of 5 fold. While we have determined that there is a five fold methodological variation in GSC RT-PCR, any method which use its components (including generation of cDNAs for microarray analysis) is likely to be affected by such experimental variability, which could limit the interpretation of the resulting data.
Analysis of Variance↗
Single cell mutational analysis of PIK3CA in circulating tumor cells and metastases in breast cancer reveals heterogeneity, discordance, and mutation persistence in cultured disseminated tumor cells from bone marrow.
BACKGROUND: Therapeutic decisions in cancer are generally guided by molecular biomarkers or, for some newer therapeutics, primary tumor genotype. However, because biomarkers or genotypes may change as new metastases emerge, circulating tumor cells (CTCs) from blood are being investigated for a role in guiding real-time drug selection during disease progression, expecting that CTCs will comprehensively represent the full spectrum of genomic changes in metastases. However, information is limited regarding mutational heterogeneity among CTCs and metastases in breast cancer as discerned by single cell analysis. The presence of disseminated tumor cells (DTCs) in bone marrow also carry prognostic significance in breast cancer, but with variability between CTC and DTC detection. Here we analyze a series of single tumor cells, CTCs, and DTCs for PIK3CA mutations and report CTC and corresponding metastatic genotypes. METHODS: We used the MagSweeper, an immunomagnetic separation device, to capture live single tumor cells from breast cancer patients' primary and metastatic tissues, blood, and bone marrow. Single cells were screened for mutations in exons 9 and 20 of the PIK3CA gene. Captured DTCs grown in cell culture were also sequenced for PIK3CA mutations. RESULTS: Among 242 individual tumor cells isolated from 17 patients and tested for mutations, 48 mutated tumor cells were identified in three patients. Single cell analyses revealed mutational heterogeneity among CTCs and tumor cells in tissues. In a patient followed serially, there was mutational discordance between CTCs, DTCs, and metastases, and among CTCs isolated at different time points. DTCs from this patient propagated in vitro contained a PIK3CA mutation, which was maintained despite morphological changes during 21 days of cell culture. CONCLUSIONS: Single cell analysis of CTCs can demonstrate genotypic heterogeneity, changes over time, and discordance from DTCs and distant metastases. We present a cautionary case showing that CTCs from any single blood draw do not always reflect metastatic genotype, and that CTC and DTC analyses may provide independent clinical information. Isolated DTCs remain viable and can be propagated in culture while maintaining their original mutational status, potentially serving as a future resource for investigating new drug therapies.
Bone Marrow↗