Project description:Single H358 cells analyzed using SCOPE2 on a TIMSTOF Flex mass spectrometer. Bruker .d folders, MGFs, Proteome Discoverer 2.5 and MaxQuant 1.6.17 results are uploaded.
Project description:In this work, we compared different protocols to prepare single-cell suspensions used for scRNAseq and suggest an optimized dissociation protocol for mouse retina, which preserves cell morphology to a higher level leading to an overall increase of gene number per cell. We compared scRNAseq libraries generated with our optimized protocol to publicly available scRNAseq data of mouse retina. We further demonstrate a pipeline to reduce noise in scRNAseq caused by multiplets and ambient RNA.
Project description:In this work, we compared different protocols to prepare single-cell suspensions used for scRNAseq and suggest an optimized dissociation protocol for mouse retina, which preserves cell morphology to a higher level leading to an overall increase of gene number per cell. We compared scRNAseq libraries generated with our optimized protocol to publicly available scRNAseq data of mouse retina. We further demonstrate a pipeline to reduce noise in scRNAseq caused by multiplets and ambient RNA.
Project description:The fate and physiology of individual cells are controlled by proteins. Yet, our ability to quantitatively analyze proteins in single cells has remained limited. To overcome this barrier, we developed SCoPE2. It substantially increases quantitative accuracy and throughput while lowering cost and hands-on time by introducing automated and miniaturized sample preparation. These advances enabled us to analyze the emergence of cellular heterogeneity as homogeneous monocytes differentiated into macrophage-like cells in the absence of polarizing cytokines. SCoPE2 quantified over 3,042 proteins in 1,490 single monocytes and macrophages in ten days of instrument time, and the quantified proteins allowed us to discern single cells by cell type. Furthermore, the data uncovered a continuous gradient of proteome states for the macrophage-like cells, suggesting that macrophage heterogeneity may emerge even in the absence of polarizing cytokines. Parallel measurements of transcripts by 10x Genomics scRNA-seq suggest that our measurements sampled 20-fold more protein copies than RNA copies per gene, and thus SCoPE2 supports quantification with improved count statistics. Joint analysis of the data illustrates how variability across single cells can reveal transcriptional and post-transcriptional gene regulation. Our methodology lays the foundation for automated and quantitative single-cell analysis of proteins by mass-spectrometry.
Project description:Single cell combinatorial indexing RNA sequencing (sci-RNA-seq) is a powerful method for recovering gene expression data from an exponentially scalable number of individual cells or nuclei. However, sci-RNA-seq is a complex protocol that has historically exhibited variable performance on different tissues, as well as lower sensitivity than alternative methods. Here we report a simplified, optimized version of the three-level sci-RNA-seq protocol that is faster, higher yield, more robust, and more sensitive, than the original sci-RNA-seq3 protocol, with reagent costs on the order of 1 cent per cell or less. We showcase the optimized protocol via whole organism analysis of an E16.5 mouse embryo, profiling ~380,000 nuclei in a single experiment. Finally, we introduce a “tiny sci-*” protocol for experiments where input is extremely limited.