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1.
BMC Bioinformatics ; 21(Suppl 14): 369, 2020 Sep 30.
Artigo em Inglês | MEDLINE | ID: mdl-32998686

RESUMO

BACKGROUND: Chromosome conformation capture-based methods, especially Hi-C, enable scientists to detect genome-wide chromatin interactions and study the spatial organization of chromatin, which plays important roles in gene expression regulation, DNA replication and repair etc. Thus, developing computational methods to unravel patterns behind the data becomes critical. Existing computational methods focus on intrachromosomal interactions and ignore interchromosomal interactions partly because there is no prior knowledge for interchromosomal interactions and the frequency of interchromosomal interactions is much lower while the search space is much larger. With the development of single-cell technologies, the advent of single-cell Hi-C makes interrogating the spatial structure of chromatin at single-cell resolution possible. It also brings a new type of frequency information, the number of single cells with chromatin interactions between two disjoint chromosome regions. RESULTS: Considering the lack of computational methods on interchromosomal interactions and the unsurprisingly frequent intrachromosomal interactions along the diagonal of a chromatin contact map, we propose a computational method dedicated to analyzing interchromosomal interactions of single-cell Hi-C with this new frequency information. To the best of our knowledge, our proposed tool is the first to identify regions with statistically frequent interchromosomal interactions at single-cell resolution. We demonstrate that the tool utilizing networks and binomial statistical tests can identify interesting structural regions through visualization, comparison and enrichment analysis and it also supports different configurations to provide users with flexibility. CONCLUSIONS: It will be a useful tool for analyzing single-cell Hi-C interchromosomal interactions.


Assuntos
Cromossomos/metabolismo , Análise de Célula Única/métodos , Animais , Cromatina/metabolismo , Fase G1 , Sequenciamento de Nucleotídeos em Larga Escala/métodos , Camundongos , Células-Tronco Embrionárias Murinas/citologia , Células-Tronco Embrionárias Murinas/metabolismo , Oócitos/citologia , Oócitos/metabolismo , Fase S , Zigoto/citologia , Zigoto/metabolismo
2.
PLoS Comput Biol ; 16(9): e1008173, 2020 09.
Artigo em Inglês | MEDLINE | ID: mdl-32946435

RESUMO

Single-cell Hi-C (scHi-C) interrogates genome-wide chromatin interaction in individual cells, allowing us to gain insights into 3D genome organization. However, the extremely sparse nature of scHi-C data poses a significant barrier to analysis, limiting our ability to tease out hidden biological information. In this work, we approach this problem by applying topic modeling to scHi-C data. Topic modeling is well-suited for discovering latent topics in a collection of discrete data. For our analysis, we generate nine different single-cell combinatorial indexed Hi-C (sci-Hi-C) libraries from five human cell lines (GM12878, H1Esc, HFF, IMR90, and HAP1), consisting over 19,000 cells. We demonstrate that topic modeling is able to successfully capture cell type differences from sci-Hi-C data in the form of "chromatin topics." We further show enrichment of particular compartment structures associated with locus pairs in these topics.


Assuntos
Cromatina , Biologia Computacional/métodos , Sequenciamento de Nucleotídeos em Larga Escala/métodos , Análise de Célula Única/métodos , Linhagem Celular , Cromatina/química , Cromatina/genética , Análise por Conglomerados , Biblioteca Gênica , Humanos , Processamento de Linguagem Natural
3.
Adv Exp Med Biol ; 1255: 7-27, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32949387

RESUMO

Within the last decade, single-cell analysis has revolutionized our understanding of cellular processes and heterogeneity across all disciplines of life science. As the transcriptome, genome, or epigenome of individual cells can nowadays be analyzed at low cost and in high-throughput within a few days by modern techniques, tremendous improvements in disease diagnosis on the one hand and the investigation of disease-relevant mechanisms on the other were achieved so far. This relies on the parallel development of reliable cell capturing and single-cell sequencing approaches that have paved the way for comprehensive single-cell studies. Apart from single-cell isolation methods in high-throughput, a variety of methods with distinct specializations were developed, allowing for correlation of transcriptomics with cellular parameters like electrophysiology or morphology.For all single-cell-based approaches, accurate and reliable isolation with proper quality controls is prerequisite, whereby different options exist dependent on sample type and tissue properties. Careful consideration of an appropriate method is required to avoid incorrect or biased data that may lead to misinterpretations.In this chapter, we will provide a broad overview of the current state of the art in matters of single-cell isolation methods mostly applied for sequencing-based downstream analysis, and their respective advantages and drawbacks. Distinct technologies will be discussed in detail addressing key parameters like sample compatibility, viability, purity, throughput, and isolation efficiency.


Assuntos
Separação Celular/métodos , Análise de Célula Única/métodos , Animais , Genoma , Humanos , Transcriptoma
4.
Nat Commun ; 11(1): 4361, 2020 08 31.
Artigo em Inglês | MEDLINE | ID: mdl-32868773

RESUMO

The sensory responses of cortical neuronal populations following training have been extensively studied. However, the spike firing properties of individual cortical neurons following training remain unknown. Here, we have combined two-photon Ca2+ imaging and single-cell electrophysiology in awake behaving mice following auditory associative training. We find a sparse set (~5%) of layer 2/3 neurons in the primary auditory cortex, each of which reliably exhibits high-rate prolonged burst firing responses to the trained sound. Such bursts are largely absent in the auditory cortex of untrained mice. Strikingly, in mice trained with different multitone chords, we discover distinct subsets of neurons that exhibit bursting responses specifically to a chord but neither to any constituent tone nor to the other chord. Thus, our results demonstrate an integrated representation of learned complex sounds in a small subset of cortical neurons.


Assuntos
Córtex Auditivo/fisiologia , Percepção Auditiva/fisiologia , Neurônios/fisiologia , Estimulação Acústica/métodos , Córtex Auditivo/citologia , Sinalização do Cálcio , Eletrofisiologia/métodos , Aprendizagem/fisiologia , Microscopia de Fluorescência por Excitação Multifotônica/métodos , Neurônios/metabolismo , Análise de Célula Única/métodos
5.
Nat Commun ; 11(1): 4364, 2020 08 31.
Artigo em Inglês | MEDLINE | ID: mdl-32868781

RESUMO

Pathophysiological roles of cardiac dopamine system remain unknown. Here, we show the role of dopamine D1 receptor (D1R)-expressing cardiomyocytes (CMs) in triggering heart failure-associated ventricular arrhythmia. Comprehensive single-cell resolution analysis identifies the presence of D1R-expressing CMs in both heart failure model mice and in heart failure patients with sustained ventricular tachycardia. Overexpression of D1R in CMs disturbs normal calcium handling while CM-specific deletion of D1R ameliorates heart failure-associated ventricular arrhythmia. Thus, cardiac D1R has the potential to become a therapeutic target for preventing heart failure-associated ventricular arrhythmia.


Assuntos
Arritmias Cardíacas/etiologia , Insuficiência Cardíaca , Miócitos Cardíacos/metabolismo , Receptores de Dopamina D1/metabolismo , Animais , Arritmias Cardíacas/prevenção & controle , Perfilação da Expressão Gênica/métodos , Humanos , Camundongos , Camundongos Transgênicos , Ratos , Receptores de Dopamina D1/genética , Análise de Sequência de RNA/métodos , Análise de Célula Única/métodos , Taquicardia Ventricular/etiologia , Taquicardia Ventricular/prevenção & controle
6.
PLoS Comput Biol ; 16(9): e1008195, 2020 09.
Artigo em Inglês | MEDLINE | ID: mdl-32898151

RESUMO

We present VALERIE (Visualising alternative splicing events from single-cell ribonucleic acid-sequencing experiments), an R package for visualising alternative splicing events at single-cell resolution. To explore any given specified genomic region, corresponding to an alternative splicing event, VALERIE generates an ensemble of informative plots to visualise cell-to-cell heterogeneity of alternative splicing profiles across single cells and performs statistical tests to compare percent spliced-in (PSI) values across the user-defined groups of cells. Among the features available, VALERIE displays PSI values, in lieu of read coverage, which is more suitable for representing alternative splicing profiles for a large number of samples typically generated by single-cell RNA-sequencing experiments. VALERIE is available on the Comprehensive R Archive Network (CRAN): https://cran.r-project.org/web/packages/VALERIE/index.html.


Assuntos
Processamento Alternativo/genética , Análise de Sequência de RNA/métodos , Análise de Célula Única/métodos , Software , Animais , Células Cultivadas , Biologia Computacional , Camundongos
7.
PLoS Comput Biol ; 16(9): e1008205, 2020 09.
Artigo em Inglês | MEDLINE | ID: mdl-32903255

RESUMO

Single-cell RNA sequencing (scRNA-seq) can map cell types, states and transitions during dynamic biological processes such as tissue development and regeneration. Many trajectory inference methods have been developed to order cells by their progression through a dynamic process. However, when time series data is available, most of these methods do not consider the available time information when ordering cells and are instead designed to work only on a single scRNA-seq data snapshot. We present Tempora, a novel cell trajectory inference method that orders cells using time information from time-series scRNA-seq data. In performance comparison tests, Tempora inferred known developmental lineages from three diverse tissue development time series data sets, beating state of the art methods in accuracy and speed. Tempora works at the level of cell clusters (types) and uses biological pathway information to help identify cell type relationships. This approach increases gene expression signal from single cells, processing speed, and interpretability of the inferred trajectory. Our results demonstrate the utility of a combination of time and pathway information to supervise trajectory inference for scRNA-seq based analysis.


Assuntos
Biologia Computacional/métodos , Perfilação da Expressão Gênica/métodos , Análise de Sequência de RNA/métodos , Análise de Célula Única/métodos , Software , Algoritmos , Animais , Células Cultivadas , Humanos , Camundongos , Mioblastos/metabolismo , RNA/genética , RNA/metabolismo , Reprodutibilidade dos Testes
8.
Nat Commun ; 11(1): 4175, 2020 08 21.
Artigo em Inglês | MEDLINE | ID: mdl-32826903

RESUMO

Somatic sensation is defined by the existence of a diversity of primary sensory neurons with unique biological features and response profiles to external and internal stimuli. However, there is no coherent picture about how this diversity of cell states is transcriptionally generated. Here, we use deep single cell analysis to resolve fate splits and molecular biasing processes during sensory neurogenesis in mice. Our results identify a complex series of successive and specific transcriptional changes in post-mitotic neurons that delineate hierarchical regulatory states leading to the generation of the main sensory neuron classes. In addition, our analysis identifies previously undetected early gene modules expressed long before fate determination although being clearly associated with defined sensory subtypes. Overall, the early diversity of sensory neurons is generated through successive bi-potential intermediates in which synchronization of relevant gene modules and concurrent repression of competing fate programs precede cell fate stabilization and final commitment.


Assuntos
Neurogênese/genética , Células Receptoras Sensoriais/citologia , Células Receptoras Sensoriais/fisiologia , Análise de Sequência de RNA/métodos , Análise de Célula Única/métodos , Animais , Diferenciação Celular , Subunidade alfa 3 de Fator de Ligação ao Core/genética , Modelos Animais de Doenças , Feminino , Regulação da Expressão Gênica no Desenvolvimento , Redes Reguladoras de Genes , Camundongos , Camundongos Endogâmicos C57BL , Camundongos Knockout , Neurônios/fisiologia , Células-Tronco
9.
Proc Natl Acad Sci U S A ; 117(33): 20171-20179, 2020 08 18.
Artigo em Inglês | MEDLINE | ID: mdl-32747561

RESUMO

Extracellular electron transfer (EET) allows microorganisms to gain energy by linking intracellular reactions to external surfaces ranging from natural minerals to the electrodes of bioelectrochemical renewable energy technologies. In the past two decades, electrochemical techniques have been used to investigate EET in a wide range of microbes, with emphasis on dissimilatory metal-reducing bacteria, such as Shewanella oneidensis MR-1, as model organisms. However, due to the typically bulk nature of these techniques, they are unable to reveal the subpopulation variation in EET or link the observed electrochemical currents to energy gain by individual cells, thus overlooking the potentially complex spatial patterns of activity in bioelectrochemical systems. Here, to address these limitations, we use the cell membrane potential as a bioenergetic indicator of EET by S. oneidensis MR-1 cells. Using a fluorescent membrane potential indicator during in vivo single-cell-level fluorescence microscopy in a bioelectrochemical reactor, we demonstrate that membrane potential strongly correlates with EET. Increasing electrode potential and associated EET current leads to more negative membrane potential. This EET-induced membrane hyperpolarization is spatially limited to cells in contact with the electrode and within a near-electrode zone (<30 µm) where the hyperpolarization decays with increasing cell-electrode distance. The high spatial and temporal resolution of the reported technique can be used to study the single-cell-level dynamics of EET not only on electrode surfaces, but also during respiration of other solid-phase electron acceptors.


Assuntos
Membrana Externa Bacteriana/fisiologia , Transporte de Elétrons/fisiologia , Potenciais da Membrana/fisiologia , Shewanella/fisiologia , Benzotiazóis/metabolismo , Fenômenos Eletrofisiológicos , Corantes Fluorescentes , Análise de Célula Única/métodos , Gravação em Vídeo
10.
Nat Commun ; 11(1): 4158, 2020 08 27.
Artigo em Inglês | MEDLINE | ID: mdl-32855417

RESUMO

Visceral organs, such as the lungs, stomach and liver, are derived from the fetal foregut through a series of inductive interactions between the definitive endoderm (DE) and the surrounding splanchnic mesoderm (SM). While DE patterning is fairly well studied, the paracrine signaling controlling SM regionalization and how this is coordinated with epithelial identity is obscure. Here, we use single cell transcriptomics to generate a high-resolution cell state map of the embryonic mouse foregut. This identifies a diversity of SM cell types that develop in close register with the organ-specific epithelium. We infer a spatiotemporal signaling network of endoderm-mesoderm interactions that orchestrate foregut organogenesis. We validate key predictions with mouse genetics, showing the importance of endoderm-derived signals in mesoderm patterning. Finally, leveraging these signaling interactions, we generate different SM subtypes from human pluripotent stem cells (hPSCs), which previously have been elusive. The single cell data can be explored at: https://research.cchmc.org/ZornLab-singlecell .


Assuntos
Sistema Digestório/metabolismo , Endoderma/metabolismo , Redes Reguladoras de Genes , Mesoderma/metabolismo , Organogênese/genética , Transdução de Sinais/genética , Animais , Linhagem da Célula/genética , Sistema Digestório/citologia , Sistema Digestório/embriologia , Endoderma/citologia , Endoderma/embriologia , Perfilação da Expressão Gênica/métodos , Regulação da Expressão Gênica no Desenvolvimento , Humanos , Internet , Mesoderma/citologia , Mesoderma/embriologia , Camundongos Endogâmicos C57BL , Análise de Célula Única/métodos , Fatores de Transcrição/genética , Fatores de Transcrição/metabolismo
12.
Nat Commun ; 11(1): 4318, 2020 08 28.
Artigo em Inglês | MEDLINE | ID: mdl-32859930

RESUMO

A common analysis of single-cell sequencing data includes clustering of cells and identifying differentially expressed genes (DEGs). How cell clusters are defined has important consequences for downstream analyses and the interpretation of results, but is often not straightforward. To address this difficulty, we present singleCellHaystack, a method that enables the prediction of DEGs without relying on explicit clustering of cells. Our method uses Kullback-Leibler divergence to find genes that are expressed in subsets of cells that are non-randomly positioned in a multidimensional space. Comparisons with existing DEG prediction approaches on artificial datasets show that singleCellHaystack has higher accuracy. We illustrate the usage of singleCellHaystack through applications on 136 real transcriptome datasets and a spatial transcriptomics dataset. We demonstrate that our method is a fast and accurate approach for DEG prediction in single-cell data. singleCellHaystack is implemented as an R package and is available from CRAN and GitHub.


Assuntos
Biologia Computacional/métodos , Perfilação da Expressão Gênica/métodos , Transcriptoma , Medula Óssea , Análise por Conglomerados , Mineração de Dados , Expressão Gênica , Redes Reguladoras de Genes , Análise de Célula Única/métodos , Software
13.
BMC Bioinformatics ; 21(1): 342, 2020 Aug 04.
Artigo em Inglês | MEDLINE | ID: mdl-32753029

RESUMO

BACKGROUND: Recent advances in single-cell RNA sequencing (scRNA-seq) technology have enabled the identification of individual cell types, such as epithelial cells, immune cells, and fibroblasts, in tissue samples containing complex cell populations. Cell typing is one of the key challenges in scRNA-seq data analysis that is usually achieved by estimating the expression of cell marker genes. However, there is no standard practice for cell typing, often resulting in variable and inaccurate outcomes. RESULTS: We have developed a comprehensive and user-friendly R-based scRNA-seq analysis and cell typing package, scTyper. scTyper also provides a database of cell type markers, scTyper.db, which contains 213 cell marker sets collected from literature. These marker sets include but are not limited to markers for malignant cells, cancer-associated fibroblasts, and tumor-infiltrating T cells. Additionally, scTyper provides three customized methods for estimating cell-type marker expression, including nearest template prediction (NTP), gene set enrichment analysis (GSEA), and average expression values. DNA copy number inference method (inferCNV) has been implemented with an improved modification that can be used for malignant cell typing. The package also supports the data preprocessing pipelines by Cell Ranger from 10X Genomics and the Seurat package. A summary reporting system is also implemented, which may facilitate users to perform reproducible analyses. CONCLUSIONS: scTyper provides a comprehensive and user-friendly analysis pipeline for cell typing of scRNA-seq data with a curated cell marker database, scTyper.db.


Assuntos
RNA-Seq , Análise de Célula Única/métodos , Software , Sequência de Bases , Análise de Dados , Bases de Dados Genéticas , Humanos
14.
Nat Commun ; 11(1): 4296, 2020 08 27.
Artigo em Inglês | MEDLINE | ID: mdl-32855387

RESUMO

Assays to study cancer cell responses to pharmacologic or genetic perturbations are typically restricted to using simple phenotypic readouts such as proliferation rate. Information-rich assays, such as gene-expression profiling, have generally not permitted efficient profiling of a given perturbation across multiple cellular contexts. Here, we develop MIX-Seq, a method for multiplexed transcriptional profiling of post-perturbation responses across a mixture of samples with single-cell resolution, using SNP-based computational demultiplexing of single-cell RNA-sequencing data. We show that MIX-Seq can be used to profile responses to chemical or genetic perturbations across pools of 100 or more cancer cell lines. We combine it with Cell Hashing to further multiplex additional experimental conditions, such as post-treatment time points or drug doses. Analyzing the high-content readout of scRNA-seq reveals both shared and context-specific transcriptional response components that can identify drug mechanism of action and enable prediction of long-term cell viability from short-term transcriptional responses to treatment.


Assuntos
Perfilação da Expressão Gênica/métodos , Neoplasias/genética , Análise de Célula Única/métodos , Antineoplásicos/farmacologia , Sequência de Bases , Linhagem Celular Tumoral , Sobrevivência Celular/genética , Regulação Neoplásica da Expressão Gênica/efeitos dos fármacos , Humanos , Modelos Estatísticos , Neoplasias/tratamento farmacológico , Neoplasias/patologia , Polimorfismo de Nucleotídeo Único , Piridonas/farmacologia , Pirimidinonas/farmacologia
15.
Nat Protoc ; 15(9): 3105-3128, 2020 09.
Artigo em Inglês | MEDLINE | ID: mdl-32826993

RESUMO

Zebrafish are an ideal cell transplantation model. They are highly fecund, optically clear and an excellent platform for preclinical drug discovery studies. Traditionally, xenotransplantation has been carried out using larval zebrafish that have not yet developed adaptive immunity. Larval engraftment is a powerful short-term transplant platform amenable to high-throughput drug screening studies, yet animals eventually reject tumors and cannot be raised at 37 °C. To address these limitations, we have recently developed adult casper-strain prkdc-/-, il2rgα-/- immunocompromised zebrafish that robustly engraft human cancer cells for in excess of 28 d. Because the adult zebrafish can be administered drugs by oral gavage or i.p. injection, our model is suitable for achieving accurate, preclinical drug dosing. Our platform also allows facile visualization of drug effects in vivo at single-cell resolution over days. Here, we describe the procedures for xenograft cell transplantation into the prkdc-/-, il2rgα-/- model, including refined husbandry protocols for optimal growth and rearing of immunosuppressed zebrafish at 37 °C; optimized intraperitoneal and periocular muscle cell transplantation; and epifluorescence and confocal imaging approaches to visualize the effects of administering clinically relevant drug dosing at single-cell resolution in vivo. After identification of adult homozygous animals, this procedure takes 35 d to complete. 7 days are required to acclimate adult fish to 37 °C, and 28 d are required for engraftment studies. Our protocol provides a comprehensive guide for using immunocompromised zebrafish for xenograft cell transplantation and credentials the model as a new preclinical drug discovery platform.


Assuntos
Transformação Celular Neoplásica , Imagem Molecular/métodos , Análise de Célula Única/métodos , Peixe-Zebra/imunologia , Animais , Linhagem Celular Tumoral , Humanos
16.
Nat Commun ; 11(1): 3924, 2020 08 06.
Artigo em Inglês | MEDLINE | ID: mdl-32764665

RESUMO

Several studies show that the immunosuppressive drugs targeting the interleukin-6 (IL-6) receptor, including tocilizumab, ameliorate lethal inflammatory responses in COVID-19 patients infected with SARS-CoV-2. Here, by employing single-cell analysis of the immune cell composition of two severe-stage COVID-19 patients prior to and following tocilizumab-induced remission, we identify a monocyte subpopulation that contributes to the inflammatory cytokine storms. Furthermore, although tocilizumab treatment attenuates the inflammation, immune cells, including plasma B cells and CD8+ T cells, still exhibit robust humoral and cellular antiviral immune responses. Thus, in addition to providing a high-dimensional dataset on the immune cell distribution at multiple stages of the COVID-19, our work also provides insights into the therapeutic effects of tocilizumab, and identifies potential target cell populations for treating COVID-19-related cytokine storms.


Assuntos
Anticorpos Monoclonais Humanizados/efeitos adversos , Betacoronavirus/imunologia , Infecções por Coronavirus/imunologia , Citocinas/imunologia , Monócitos/imunologia , Pneumonia Viral/imunologia , Anticorpos Monoclonais Humanizados/administração & dosagem , Linfócitos B/efeitos dos fármacos , Linfócitos B/imunologia , Linfócitos T CD8-Positivos/efeitos dos fármacos , Linfócitos T CD8-Positivos/imunologia , Biologia Computacional , Infecções por Coronavirus/sangue , Infecções por Coronavirus/tratamento farmacológico , Infecções por Coronavirus/virologia , Citocinas/sangue , Humanos , Inflamação/tratamento farmacológico , Macrófagos/efeitos dos fármacos , Macrófagos/imunologia , Pandemias , Pneumonia Viral/sangue , Pneumonia Viral/tratamento farmacológico , Pneumonia Viral/virologia , Receptores de Interleucina-6/imunologia , Análise de Célula Única/métodos
17.
Nat Commun ; 11(1): 3715, 2020 07 24.
Artigo em Inglês | MEDLINE | ID: mdl-32709844

RESUMO

Esophageal squamous cell carcinoma (ESCC) is prevalent in some geographical regions of the world. ESCC development presents a multistep pathogenic process from inflammation to invasive cancer; however, what is critical in these processes and how they evolve is largely unknown, obstructing early diagnosis and effective treatment. Here, we create a mouse model mimicking human ESCC development and construct a single-cell ESCC developmental atlas. We identify a set of key transitional signatures associated with oncogenic evolution of epithelial cells and depict the landmark dynamic tumorigenic trajectories. An early downregulation of CD8+ response against the initial tissue damage accompanied by the transition of immune response from type 1 to type 3 results in accumulation and activation of macrophages and neutrophils, which may create a chronic inflammatory environment that promotes carcinogen-transformed epithelial cell survival and proliferation. These findings shed light on how ESCC is initiated and developed.


Assuntos
Neoplasias Esofágicas/genética , Neoplasias Esofágicas/metabolismo , Regulação Neoplásica da Expressão Gênica , Análise de Célula Única/métodos , Transcriptoma , Animais , Linhagem Celular Tumoral , Proliferação de Células , Transformação Celular Neoplásica/genética , Transformação Celular Neoplásica/metabolismo , Modelos Animais de Doenças , Regulação para Baixo , Células Epiteliais/patologia , Neoplasias Esofágicas/imunologia , Neoplasias Esofágicas/patologia , Carcinoma de Células Escamosas do Esôfago , Feminino , Fibroblastos/metabolismo , Fibroblastos/patologia , Humanos , Camundongos , Camundongos Endogâmicos C57BL , Linfócitos T , Fatores de Transcrição , Microambiente Tumoral
18.
Proc Natl Acad Sci U S A ; 117(31): 18412-18423, 2020 08 04.
Artigo em Inglês | MEDLINE | ID: mdl-32694205

RESUMO

Stem cells with the capability to self-renew and differentiate into multiple cell derivatives provide platforms for drug screening and promising treatment options for a wide variety of neural diseases. Nevertheless, clinical applications of stem cells have been hindered partly owing to a lack of standardized techniques to characterize cell molecular profiles noninvasively and comprehensively. Here, we demonstrate that a label-free and noninvasive single-cell Raman microspectroscopy (SCRM) platform was able to identify neural cell lineages derived from clinically relevant human induced pluripotent stem cells (hiPSCs). By analyzing the intrinsic biochemical profiles of single cells at a large scale (8,774 Raman spectra in total), iPSCs and iPSC-derived neural cells can be distinguished by their intrinsic phenotypic Raman spectra. We identified a Raman biomarker from glycogen to distinguish iPSCs from their neural derivatives, and the result was verified by the conventional glycogen detection assays. Further analysis with a machine learning classification model, utilizing t-distributed stochastic neighbor embedding (t-SNE)-enhanced ensemble stacking, clearly categorized hiPSCs in different developmental stages with 97.5% accuracy. The present study demonstrates the capability of the SCRM-based platform to monitor cell development using high content screening with a noninvasive and label-free approach. This platform as well as our identified biomarker could be extensible to other cell types and can potentially have a high impact on neural stem cell therapy.


Assuntos
Células-Tronco Pluripotentes Induzidas/citologia , Neurônios/citologia , Análise de Célula Única/métodos , Análise Espectral Raman/métodos , Diferenciação Celular , Humanos
19.
Phys Rev Lett ; 125(1): 018102, 2020 Jul 03.
Artigo em Inglês | MEDLINE | ID: mdl-32678664

RESUMO

Many types of cells require the ability to pinpoint the location of an external stimulus from the arrival of diffusing signaling molecules at cell-surface receptors. How does the organization (number and spatial configuration) of these receptors shape the limit of a cell's ability to infer the source location? In the idealized scenario of a spherical cell, we apply asymptotic analysis to compute splitting probabilities between individual receptors and formulate an information-theoretic framework to quantify the role of receptor organization. Clustered configurations of receptors provide an advantage in detecting sources aligned with the clusters, suggesting a possible multiscale mechanism for single-cell source inference.


Assuntos
Comunicação Celular/fisiologia , Modelos Biológicos , Receptores de Superfície Celular/fisiologia , Análise por Conglomerados , Receptores de Superfície Celular/metabolismo , Transdução de Sinais , Análise de Célula Única/métodos
20.
PLoS One ; 15(7): e0221241, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32634153

RESUMO

Radioluminescence microscopy (RLM) is an imaging technique that allows quantitative analysis of clinical radiolabeled drugs and probes in single cells. However, the modality suffers from slow data acquisition (15-30 minutes), thus critically affecting experiments with short-lived radioactive drugs. To overcome this issue, we suggest an approach that significantly accelerates data collection. Instead of using a single scintillator to image the decay of radioactive molecules, we sandwiched the radiolabeled cells between two scintillators. As proof of concept, we imaged cells labeled with [18F]FDG, a radioactive glucose popularly used in oncology to image tumors. Results show that the double scintillator configuration increases the microscope sensitivity by two-fold, thus reducing the image acquisition time by half to achieve the same result as the single scintillator approach. The experimental results were also compared with Geant4 Monte Carlo simulation to confirm the two-fold increase in sensitivity with only minor degradation in spatial resolution. Overall, these findings suggest that the double scintillator configuration can be used to perform time-sensitive studies such as cell pharmacokinetics or cell uptake of short-lived radiotracers.


Assuntos
Microscopia de Fluorescência/métodos , Compostos Radiofarmacêuticos/química , Análise de Célula Única/métodos , Linhagem Celular Tumoral , Fluordesoxiglucose F18/química , Humanos , Microscopia de Fluorescência/instrumentação , Método de Monte Carlo , Contagem de Cintilação
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