Immuno-Detection by sequencing (ID-seq) enables large-scale high- dimensional phenotyping in cells
Ontology highlight
ABSTRACT:
ORGANISM(S): synthetic construct Homo sapiens
PROVIDER: GSE100135 | GEO | 2017/07/01
SECONDARY ACCESSION(S): PRJNA390781
REPOSITORIES: GEO
Similar Datasets
Project description:We developed a single cell application of the sequencing-based immunodetection method ID-seq which makes it possible to multiplex measurements of many different epitopes from proteins and phosphoproteins in a high throughput setting. A FACS sort step was implemented to allow sorting of single cells in 96 well plates. With these DNA-tagged antibodies and dedicated sample preparation protocol adapted for single cells, we studied the studied the changes of 70 (phospho-)proteins in primary human skin cells compared to a subpopulation with low ITGB1 protein expression. Given that ITGB1 is a skin stem cell marker, we indeed found that the ITGB1 low cells are differentiated and we found a role for BMP signaling in this process.
2018-11-28 | GSE115925 | GEO
Project description:Cell-based small molecule screening is an effective strategy leading to new medicines. Scientists in the pharmaceutical industry as well as in academia have made tremendous progress in developing both large-scale and smaller-scale screening assays. However, an accessible and universal technology for measuring large numbers of molecular and cellular phenotypes in many samples in parallel is not available. Here we present the immuno-detection by sequencing (ID-seq) technology that combines antibody-based protein detection and DNA-sequencing via DNA-tagged antibodies. We use ID-seq to simultaneously measure 70 (phospho-)proteins in primary human epidermal stem cells to screen the effects of ~300 kinase inhibitor probes to characterise the role of 225 kinases. The results show an association between decreased mTOR signalling and increased differentiation and uncover 13 kinases potentially regulating epidermal renewal through distinct mechanisms. Taken together, our work establishes ID-seq as a flexible solution for large-scale high-dimensional phenotyping in fixed cell populations.
| S-EPMC6008431 | biostudies-literature
Project description:Immuno-Detection by sequencing (ID-seq) enables large-scale high- dimensional phenotyping in cells
| PRJNA390781 | ENA
Project description:The challenge of developing effective pharmacodynamic biomarkers for pre-clinical and clinical testing of FGFR signalling inhibition is significant. Assays that rely on the measurement of phospho-protein epitopes can be limited by the availability of effective antibody detection reagents. Transcript profiling enables accurate quantification of many biomarkers and a broader representation of pathway modulation. To identify dynamic transcript biomarkers of FGFR signalling inhibition by AZD4547, a potent inhibitor of FGF receptor 1, 2 and 3, a gene expression profiling study was performed in FGFR2 amplified drug sensitive tumour cell lines.
2016-08-25 | E-MTAB-4749 | biostudies-arrayexpress
Project description:Haploinsufficiency, a dominant phenotype caused by a heterozygous loss-of-function mutation, has been rarely observed. However, high-dimensional single-cell phenotyping of yeast morphological characteristics revealed haploinsufficiency phenotypes for more than half of 1,112 essential genes under optimal growth conditions. Additionally, 40% of the essential genes with no obvious phenotype under optimal growth conditions displayed haploinsufficiency under severe growth conditions. Haploinsufficiency was detected more frequently in essential genes than in nonessential genes. Similar haploinsufficiency phenotypes were observed mostly in mutants with heterozygous deletion of functionally related genes, suggesting that haploinsufficiency phenotypes were caused by functional defects of the genes. A global view of the gene network was presented based on the similarities of the haploinsufficiency phenotypes. Our dataset contains rich information regarding essential gene functions, providing evidence that single-cell phenotyping is a powerful approach, even in the heterozygous condition, for analyzing complex biological systems.
| S-EPMC5955526 | biostudies-literature
Project description:One of the most powerful techniques for attributing functions to genes in uni- and multicellular organisms is comprehensive analysis of mutant traits. In this study, systematic and quantitative analyses of mutant traits are achieved in the budding yeast Saccharomyces cerevisiae by investigating morphological phenotypes. Analysis of fluorescent microscopic images of triple-stained cells makes it possible to treat morphological variations as quantitative traits. Deletion of nearly half of the yeast genes not essential for growth affects these morphological traits. Similar morphological phenotypes are caused by deletions of functionally related genes, enabling a functional assignment of a locus to a specific cellular pathway. The high-dimensional phenotypic analysis of defined yeast mutant strains provides another step toward attributing gene function to all of the genes in the yeast genome.
| S-EPMC1316885 | biostudies-literature
Project description:To further our understanding of how biochemical information flows through cells upon external stimulation, we require single-cell multi-omics methods that concurrently map changes in (phospho)protein levels across signaling networks and the associated gene expression profiles. Here, we present Quantification of RNA and Intracellular Epitopes by sequencing (QuRIE-seq), a droplet-based platform for single-cell RNA and intra- and extracellular (phospho)protein quantification through sequencing. We applied QuRIE-seq to quantify cell-state changes of 6976 cells, at both the signaling and transcriptome level following 2, 4, 6, 60, and 180-minute stimulation of the B-cell receptor pathway (BCR) in Burkitt lymphoma cells (BJABs). Using the recently developed multi-factor omics analysis (MOFA+) framework we delineated changes in single-cell (phospho)protein and gene expression patterns over multiple timescales and revealed the effect of an inhibitory drug (Ibrutinib) on signaling and gene expression landscape.
2022-03-03 | GSE162461 | GEO
Project description:Differences in gene-expression profiles between individual cells can give rise to distinct cell fate decisions. Yet how localisation on a micropattern impacts initial changes in mRNA, protein, and phosphoprotein abundance remains unclear. To identify the effect of cellular position on gene expression, we developed a scalable antibody and mRNA targeting sequential fluorescence in situ hybridization (ARTseq-FISH) method capable of simultaneously profiling mRNAs, proteins, and phosphoproteins in single cells. We studied 67 (phospho-)protein and mRNA targets in individual mouse embryonic stem cells (mESCs) cultured on circular micropatterns. To validate the detection of the mRNA targets quantified with ARTseq-FISH, we utilized single-cell RNA sequencing to profile a comparable population of mouse embryonic stem cells.
2024-04-24 | GSE264348 | GEO
Project description:Accurate positional information concerning ribosomes and RNA binding proteins with respect to their transcripts is important to understand the global regulatory network underlying protein and RNA fate in living cells. Most footprinting approaches generate RNA fragments bearing a phosphate or cyclic phosphate groups at their 3′ end. Unfortunately, all current protocols for library preparation rely only on the presence of a 3′ hydroxyl group. Here, we developed circAID-p-seq, a PCR-free library preparation for 3′ phospho-RNA sequencing. We applied circAID-p-seq to ribosome profiling, which produces fragments protected by ribosomes after endonuclease digestion. CircAID-p-seq, combined with the dedicated computational pipeline circAidMe, facilitates accurate, fast, highly efficient and low-cost sequencing of phospho-RNA fragments from eukaryotic cells and tissues. While assessing circAID-p-seq to portray ribosomes engaged with transcripts, we provide a versatile tool to unravel any 3′-phospho RNA molecules.
2022-03-09 | GSE174754 | GEO
Project description:BACKGROUND:Relying on diagnostic categories of neuropsychiatric illness obscures the complexity of these disorders. Capturing multiple dimensional measures of neuropathology could facilitate the clinical and neurobiological investigation of cognitive and behavioral phenotypes. METHODS:We developed a natural language processing-based approach to extract five symptom dimensions, based on the National Institute of Mental Health Research Domain Criteria definitions, from narrative clinical notes. Estimates of Research Domain Criteria loading were derived from a cohort of 3619 individuals with 4623 hospital admissions. We applied this tool to a large corpus of psychiatric inpatient admission and discharge notes (2010-2015), and using the same cohort we examined face validity, predictive validity, and convergent validity with gold standard annotations. RESULTS:In mixed-effect models adjusted for sociodemographic and clinical features, greater negative and positive symptom domains were associated with a shorter length of stay (? = -.88, p = .001 and ? = -1.22, p < .001, respectively), while greater social and arousal domain scores were associated with a longer length of stay (? = .93, p < .001 and ? = .81, p = .007, respectively). In fully adjusted Cox regression models, a greater positive domain score at discharge was also associated with a significant increase in readmission risk (hazard ratio = 1.22, p < .001). Positive and negative valence domains were correlated with expert annotation (by analysis of variance [df = 3], R2 = .13 and .19, respectively). Likewise, in a subset of patients, neurocognitive testing was correlated with cognitive performance scores (p < .008 for three of six measures). CONCLUSIONS:This shows that natural language processing can be used to efficiently and transparently score clinical notes in terms of cognitive and psychopathologic domains.
| S-EPMC5972065 | biostudies-literature