Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Quantifying Cell Heterogeneity and Subpopulations Using Single Cell Metabolomics

ABSTRACT: We combined the Single-probe single cell MS(SCMS) experimental technique with a bioinformatics software package, SinCHet-MS (Single Cell Heterogeneity for Mass Spectrometry), to characterize changes of tumor heterogeneity, quantify cell subpopulations, and prioritize the metabolite biomarkers of each subpopulation.

INSTRUMENT(S): LTQ Orbitrap XL

ORGANISM(S): Homo Sapiens (ncbitaxon:9606)

SUBMITTER: Zhibo Yang

PROVIDER: MSV000092178 | MassIVE | Thu Jun 15 10:45:00 BST 2023

REPOSITORIES: MassIVE

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Publications

Quantifying Cell Heterogeneity and Subpopulations Using Single Cell Metabolomics.

Liu Renmeng R Li Jiannong J Lan Yunpeng Y Nguyen Tra D TD Chen Y Ann YA Yang Zhibo Z

Analytical chemistry 20230428 18

Mass spectrometry (MS) has become an indispensable tool for metabolomics studies. However, due to the lack of applicable experimental platforms, suitable algorithm, software, and quantitative analyses of cell heterogeneity and subpopulations, investigating global metabolomics profiling at the single cell level remains challenging. We combined the Single-probe single cell MS (SCMS) experimental technique with a bioinformatics software package, SinCHet-MS (Single Cell Heterogeneity for Mass Spectr ...[more]

PMID: 37115510

Similar Datasets

GNPS - Quantifying Cell Heterogeneity and Subpopulations Using Single Cell Metabolomics

Project description:We combined the Single-probe single cell MS(SCMS) experimental technique with a bioinformatics software package, SinCHet-MS (Single Cell Heterogeneity for Mass Spectrometry), to characterize changes of tumor heterogeneity, quantify cell subpopulations, and prioritize the metabolite biomarkers of each subpopulation.

2023-06-15 | MSV000092178 | GNPS

Multilayered Omics Revealsl Sex- and Depot-Dependent Adipose Progenitor Cell Heterogeneity

Project description:White adipose tissue (WAT) harbors functionally diverse subpopulations of adipose progenitor cells that differentially impact tissue plasticity in a sex- and depot-dependent manner. To date, the molecular basis of this cellular heterogeneity has not been fully defined. Here, we describe a multilayered omics approach to dissect adipose progenitor cell heterogeneity from in three dimensions: progenitor subpopulation, sex, and anatomical localization. We applied state-of-the-art mass spectrometry methods to quantify 4870 proteins in eight different stromal cell populations from perigonadal and inguinal WAT of male and female mice and acquired transcript expression levels of 15477 genes using RNA-seq. Notably, our data highlight the molecular signatures defining sex differences in PDGFR+ preadipocyte differentiation and identify regulatory pathways that functionally distinguish adipose tissue PDGFRb+ subpopulations. The data are freely accessible as a resource at "Pread Profiler. Together, the multilayered omics analysis provides unprecedented insights into adipose stromal cell heterogeneity.

2023-03-11 | PXD023829 | Pride

Cell-to-cell heterogeneity drives host-virus coexistence in a bloom-forming alga

Project description:Algal blooms drive global biogeochemical cycles of key nutrients in the oceans and serve as hotspots for biological interactions. The massive spring blooms of the cosmopolitan coccolithophore Emiliania huxleyi (E. huxleyi) are often infected by the lytic Emiliania huxleyi specific virus (EhV) which is a major mortality agent triggering bloom demise. Nonetheless, the multi-annual 'boom and bust' pattern of E. huxleyi suggests that mechanisms of coexistence are essential for these host-virus dynamics. To investigate host-virus coexistence, we developed a new model system from an E. huxleyi culture which recovered from viral infection. The recovered population coexists with the virus, as host cells continue to grow in parallel to viral production. By applying a single-molecule fluorescence in situ hybridization (smFISH) approach to quantify the fraction of infected cells and assessing infection-specific lipid biomarkers, we identified a small subpopulation (5-7% of cells) that was infected and produced new virions, whereas the majority of the host population could resist infection. To further assess population heterogeneity, we generated monoclonal strain collections using single-cell sorting and subsequently phenotyped their susceptibility to EhV infection. This unraveled a substantial cell-to-cell heterogeneity across a continuum of susceptibility to resistance, suggesting that infection outcomes may vary depending on the individual cell. These results add a new dimension to our understanding of the complexity of host-virus interactions that are commonly assessed in bulk and described by binary definitions of resistance or susceptibility. We propose that phenotypic heterogeneity drives E. huxleyi-EhV coexistence and may potentially provide the coexisting strain an ecological advantage by killing competing susceptible strains.

1970-01-01 | MTBLS1956 | MetaboLights

Single cell transcriptome dynamics and subpopulation heterogeneity in radiation treated recurrent glioma

Project description:Radiation is the frontline treatment for malignant gliomas. Intra-tumoral heterogeneity has been proposed to grant cancer cells a superior trajectory and survival advantage to avoid therapeutic interventions including radiation. However, direct evidence to support the hypothesis via the transcriptome dynamics of glioma during radiation therapy is limited. The current study aim to measure the functional subpopulation dynamics before and after radiation treatment that assist the radiation resistance at single cell resolution. We investigate the single cell transcriptome and biological pathways of primary glioma mouse model and post-radiation early/late time point. Specifically, we used the RCAS mouse model for gliomas, which overexpress PDGFRA as the model. Using single cell transcriptome, for the first time, we confirmed the proneural classification of PDGFRA RCAS glioma mouse model and its heterogeneity. We found that recurrent dominant subpopulations are featured with elevated proliferation rate and hypoxia. In addition, we identified a subpopulation of radiation resistant cells in at early time points with elevated stemness. Lastly, the subpopulations composition undergoes large changes at late time point when the tumor recurred. Single cell transcriptome profiling of radiation treated mouse glioma mouse model identified tumor cell subpopulations dynamics. It provides novel insights into the molecular phenotype and biological functions of radiation resistant tumor cell population.

2016-12-01 | GSE76184 | GEO

Unravelling subclonal heterogeneity and aggressive disease states in TNBC through single-cell RNA-seq [WES]

Project description:Triple-negative breast cancer (TNBC) is an aggressive subtype characterized by extensive intratumoral heterogeneity. To investigate the underlying biology, we conduct single-cell RNA- sequencing (scRNA-seq) of >1500 cells from six primary TNBC, together with whole exome sequencing (WES) for four of the tumors. Intercellular heterogeneity of gene expression programs within each tumor was variable and largely correlated with clonality of inferred genomic copy number changes, suggesting that genotype drives the gene expression phenotype of individual subpopulations. Clustering of gene expression profiles identified distinct subgroups of malignant cells shared by multiple tumors, including a single subpopulation associated with multiple signatures of treatment resistance and metastasis, and characterized functionally by activation of glycosphingolipid metabolism and associated innate immunity pathways. A novel signature defining this subpopulation was predictive of long-term outcomes for TNBC patients in a large patient cohort. Collectively, this analysis reveals the functional heterogeneity and its association with genomic evolution in TNBC, and uncovers unanticipated biological principles dictating poor outcomes in this disease.

2018-08-11 | GSE118303 | GEO

Functional heterogeneity within the developing zebrafish epicardium

Project description:The epicardium is essential during cardiac development, homeostasis and repair and yet fundamental insights into its underlying cell biology, notably epicardium formation, lineage heterogeneity and functional cross-talk with other cell types in the heart, is currently lacking. In this study, we investigated epicardial heterogeneity and the functional diversity of discrete epicardial subpopulations in the developing zebrafish heart. Single-cell RNA-sequencing uncovered three epicardial subpopulations with specific genetic programmes and distinctive spatial distribution within the developing heart. Perturbation of unique gene signatures uncovered distinct functions associated with each subpopulation and established novel epicardial roles in cell adhesion, migration, and chemotaxis as a mechanism for recruitment of leukocytes into the heart. This work elucidates the mutual spatiotemporal relationships between different epicardial subpopulations and assigns unique function to each during cardiac development. Understanding which mechanisms cells employ to establish a functional epicardium and to communicate with other cardiovascular cell types during development will bring us closer to repairing cellular relationships that are disrupted during cardiovascular disease.

2020-01-20 | GSE121750 | GEO

Unravelling subclonal heterogeneity and aggressive disease states in TNBC through single-cell RNA-seq [RNA-Seq]

Project description:Triple-negative breast cancer (TNBC) is an aggressive subtype characterized by extensive intratumoral heterogeneity. To investigate the underlying biology, we conduct single-cell RNA- sequencing (scRNA-seq) of >1500 cells from six primary TNBC. Intercellular heterogeneity of gene expression programs within each tumor was variable and largely correlated with clonality of inferred genomic copy number changes, suggesting that genotype drives the gene expression phenotype of individual subpopulations. Clustering of gene expression profiles identified distinct subgroups of malignant cells shared by multiple tumors, including a single subpopulation associated with multiple signatures of treatment resistance and metastasis, and characterized functionally by activation of glycosphingolipid metabolism and associated innate immunity pathways. A novel signature defining this subpopulation was predictive of long-term outcomes for TNBC patients in a large patient cohort. Collectively, this analysis reveals the functional heterogeneity and its association with genomic evolution in TNBC, and uncovers unanticipated biological principles dictating poor outcomes in this disease.

2018-08-11 | GSE118389 | GEO

Multilayer-omics Reveal Sex- and Depot-Dependent Adipose Progenitor Cell Heterogeneity

Project description:White adipose tissue (WAT) harbors functionally diverse subpopulations of adipose progenitor cells that differentially impact tissue plasticity in a sex- and depot-dependent manner. To date, the molecular basis of this cellular heterogeneity has not been fully defined. Here, we describe a multilayered omics approach to dissect adipose progenitor cell heterogeneity in three dimensions: progenitor subpopulation, sex, and anatomical localization. We applied state-of-the-art mass spectrometry methods to quantify 4870 proteins in eight different stromal cell populations from perigonadal and inguinal WAT of male and female mice and acquired transcript expression levels of 15477 genes using RNA-seq. Notably, our data highlight the molecular signatures defining sex differences in PDGFRb+ preadipocyte differentiation and identify regulatory pathways that functionally distinguish adipose tissue PDGFRb+ subpopulations. Together, the multilayered omics analysis provides unprecedented insights into adipose stromal cell heterogeneity.

2022-01-26 | GSE165600 | GEO

An Improved Bacterial Single-cell RNA-seq Reveals Biofilm Heterogeneity [scRNA-seq]

Project description:In contrast to mammalian cells, bacterial cells lack mRNA polyadenylated tails, presenting a hurdle in isolating mRNA amidst the prevalent rRNA during single-cell RNA-seq. This study introduces a novel method, Ribosomal RNA-derived cDNA Depletion (RiboD), seamlessly integrated into the PETRI-seq technique, yielding RiboD-PETRI. This innovative approach offers a cost-effective, equipment-free, and high-throughput solution for bacterial single-cell RNA sequencing (scRNA-seq). By efficiently eliminating rRNA reads and substantially enhancing mRNA detection rates (up to 92%), our method enables precise exploration of bacterial population heterogeneity. Applying RiboD-PETRI to investigate biofilm heterogeneity, distinctive subpopulations marked by unique genes within biofilms were successfully identified. Notably, PdeI, a marker for the cell-surface attachment subpopulation, was observed to elevate cyclic diguanylate (c-di-GMP) levels, promoting persister cell formation. Thus, we address a persistent challenge in bacterial single-cell RNA-seq regarding rRNA abundance, exemplifying the utility of this method in exploring biofilm heterogeneity. Our method effectively tackles a long-standing issue in bacterial scRNA-seq: the overwhelming abundance of rRNA. This advancement significantly enhances our ability to investigate the intricate heterogeneity within biofilms at unprecedented resolution.

2024-12-10 | GSE260457 | GEO

An Improved Bacterial Single-cell RNA-seq Reveals Biofilm Heterogeneity [RNA-seq]

2024-12-10 | GSE259433 | GEO