Combined mRNA and protein single cell analysis in a dynamic cellular system using SPARC

ABSTRACTCombined measurements of mRNA and protein expression in single cells enables in-depth analysis of cellular states. We present single-cell protein and RNA co-profiling (SPARC), an approach to simultaneously measure global mRNA and large sets of intracellular protein in individual cells. Using SPARC, we show that mRNA expression fails to accurately reflect protein abundance at the time of measurement in human embryonic stem cells, although the direction of changes of mRNA and protein expression are in agreement during cellular differentiation. Moreover, protein levels of transcription factors better predict their downstream effects than do the corresponding transcripts. We further show that changes of the balance between protein and mRNA expression levels can be applied to infer expression kinetic trajectories, revealing future states of individual cells. Finally, we highlight that mRNA expression may be more varied among cells than levels of the corresponding proteins. Overall, our results demonstrate that mRNA and protein measurements in single cells provide different and complementary information regarding cell states. Accordingly, SPARC can offer valuable insights in gene expression programs of single cells.

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Direct correlation between motile behavior and protein abundance in single cells

10.1101/067918 ◽

2016 ◽

Author(s):

Yann S Dufour ◽

Sébastien Gillet ◽

Nicholas W Frankel ◽

Douglas B Weibel ◽

Thierry Emonet

Keyword(s):

Protein Expression ◽

Single Cell ◽

Phenotypic Diversity ◽

Single Cells ◽

Selective Advantage ◽

Single Cell Protein ◽

Cell Protein ◽

Chemotaxis Proteins

AbstractUnderstanding how stochastic molecular fluctuations affect cell behavior requires the quantification of both behavior and protein numbers in the same cells. Here, we combine automated microscopy with in situ hydrogel polymerization to measure single-cell protein expression after tracking swimming behavior. We characterized the distribution of non-genetic phenotypic diversity in Escherichia coli motility, which affects single-cell exploration. By expressing fluorescently tagged chemotaxis proteins (CheR and CheB) at different levels, we quantitatively mapped motile phenotype (tumble bias) to protein numbers using thousands of single-cell measurements. Our results disagreed with established models until we incorporated the role of CheB in receptor deamidation and the slow fluctuations in receptor methylation. Beyond refining models, our central finding is that changes in numbers of CheR and CheB affect the population mean tumble bias and its variance independently. Therefore, it is possible to adjust the degree of phenotypic diversity of a population by adjusting the global level of expression of CheR and CheB while keeping their ratio constant, which, as shown in previous studies, confers functional robustness to the system. Since genetic control of protein expression is heritable, our results suggest that non-genetic diversity in motile behavior is selectable, supporting earlier hypotheses that such diversity confers a selective advantage.

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Single-cell proteomic and transcriptomic analysis of macrophage heterogeneity using SCoPE2

Genome Biology ◽

10.1186/s13059-021-02267-5 ◽

2021 ◽

Vol 22 (1) ◽

Cited By ~ 4

Author(s):

Harrison Specht ◽

Edward Emmott ◽

Aleksandra A. Petelski ◽

R. Gray Huffman ◽

David H. Perlman ◽

...

Keyword(s):

Single Cell ◽

Single Cell Analysis ◽

Single Cells ◽

Single Cell Protein ◽

Cellular Heterogeneity ◽

Cell Protein ◽

Alternatively Activated Macrophages ◽

Monocytes And Macrophages ◽

Molecular Phenotypes ◽

Post Transcriptional Regulation

Abstract Background Macrophages are innate immune cells with diverse functional and molecular phenotypes. This diversity is largely unexplored at the level of single-cell proteomes because of the limitations of quantitative single-cell protein analysis. Results To overcome this limitation, we develop SCoPE2, which substantially increases quantitative accuracy and throughput while lowering cost and hands-on time by introducing automated and miniaturized sample preparation. These advances enable us to analyze the emergence of cellular heterogeneity as homogeneous monocytes differentiate into macrophage-like cells in the absence of polarizing cytokines. SCoPE2 quantifies over 3042 proteins in 1490 single monocytes and macrophages in 10 days of instrument time, and the quantified proteins allow us to discern single cells by cell type. Furthermore, the data uncover a continuous gradient of proteome states for the macrophages, suggesting that macrophage heterogeneity may emerge in the absence of polarizing cytokines. Parallel measurements of transcripts by 10× Genomics suggest that our measurements sample 20-fold more protein copies than RNA copies per gene, and thus, SCoPE2 supports quantification with improved count statistics. This allowed exploring regulatory interactions, such as interactions between the tumor suppressor p53, its transcript, and the transcripts of genes regulated by p53. Conclusions Even in a homogeneous environment, macrophage proteomes are heterogeneous. This heterogeneity correlates to the inflammatory axis of classically and alternatively activated macrophages. Our methodology lays the foundation for automated and quantitative single-cell analysis of proteins by mass spectrometry and demonstrates the potential for inferring transcriptional and post-transcriptional regulation from variability across single cells.

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Single-cell proteomic and transcriptomic analysis of macrophage heterogeneity

10.1101/665307 ◽

2019 ◽

Cited By ~ 20

Author(s):

Harrison Specht ◽

Edward Emmott ◽

Aleksandra A. Petelski ◽

R. Gray Huffman ◽

David H. Perlman ◽

...

Keyword(s):

Single Cell ◽

Single Cell Analysis ◽

Single Cells ◽

Single Cell Protein ◽

Cellular Heterogeneity ◽

Cell Protein ◽

Alternatively Activated Macrophages ◽

Monocytes And Macrophages ◽

Molecular Phenotypes ◽

Post Transcriptional Regulation

AbstractMacrophages are innate immune cells with diverse functional and molecular phenotypes. This diversity is largely unexplored at the level of single-cell proteomes because of limitations of quantitative single-cell protein analysis. To overcome this limitation, we developed SCoPE2, which substantially increases quantitative accuracy and throughput while lowering cost and hands-on time by introducing automated and miniaturized sample preparation. These advances enable us to analyze the emergence of cellular heterogeneity as homogeneous monocytes differentiate 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 allow us to discern single cells by cell type. Furthermore, the data uncover a continuous gradient of proteome states for the macrophages, suggesting that macrophage heterogeneity may emerge in the absence of polarizing cytokines. This gradient correlates to the inflammatory axis of classically and alternatively activated macrophages. Parallel measurements of transcripts by 10x Genomics suggest that our measurements sample 20-fold more protein copies than RNA copies per gene, and thus SCoPE2 supports quantification with improved count statistics. The joint distributions of proteins and transcripts allowed exploring regulatory interactions, such as between the tumor suppressor p53, its transcript, and the transcripts of genes regulated by p53. Our methodology lays the foundation for quantitative single-cell analysis of proteins by mass-spectrometry and demonstrates the potential for inferring transcriptional and post-transcriptional regulation from variability across single cells.Abstract Figure

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Multiplexed single-cell proteomics using SCoPE2

10.1101/2021.03.12.435034 ◽

2021 ◽

Author(s):

Aleksandra A Petelski ◽

Edward Emmott ◽

Andrew Leduc ◽

R. Gray Huffman ◽

Harrison Specht ◽

...

Keyword(s):

Single Cell ◽

Single Cell Analysis ◽

Single Cells ◽

Cost Effective ◽

Protein Analysis ◽

Single Cell Protein ◽

Protein Quantification ◽

Cell Protein ◽

Label Free ◽

Cost Effective Method

Many biological systems are composed of diverse single cells. This diversity necessitates functional and molecular single-cell analysis. Single-cell protein analysis has long relied on affinity reagents, but emerging mass-spectrometry methods (either label-free or multiplexed) have enabled quantifying over 1,000 proteins per cell while simultaneously increasing the specificity of protein quantification. Isobaric carrier based multiplexed single-cell proteomics is a scalable, reliable, and cost-effective method that can be fully automated and implemented on widely available equipment. It uses inexpensive reagents and is applicable to any sample that can be processed to a single-cell suspension. Here we describe an automated Single Cell ProtEomics (SCoPE2) workflow that allows analyzing about 200 single cells per 24 hours using only standard commercial equipment. We emphasize experimental steps and benchmarks required for achieving quantitative protein analysis.

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A combined approach for single-cell mRNA and intracellular protein expression analysis

Communications Biology ◽

10.1038/s42003-021-02142-w ◽

2021 ◽

Vol 4 (1) ◽

Author(s):

Johan Reimegård ◽

Marcel Tarbier ◽

Marcus Danielsson ◽

Jens Schuster ◽

Sathishkumar Baskaran ◽

...

Keyword(s):

Protein Expression ◽

Single Cell ◽

Protein Localization ◽

Single Cells ◽

Mrna Level ◽

Protein Levels ◽

Downstream Effects ◽

Depth Analysis ◽

Mrna And Protein Expression ◽

Cell Fixation

AbstractCombined measurements of mRNA and protein expression in single cells enable in-depth analysis of cellular states. We present SPARC, an approach that combines single-cell RNA-sequencing with proximity extension essays to simultaneously measure global mRNA and 89 intracellular proteins in individual cells. We show that mRNA expression fails to accurately reflect protein abundance at the time of measurement, although the direction of changes is in agreement during neuronal differentiation. Moreover, protein levels of transcription factors better predict their downstream effects than do their corresponding transcripts. Finally, we highlight that protein expression variation is overall lower than mRNA variation, but relative protein variation does not reflect the mRNA level. Our results demonstrate that mRNA and protein measurements in single cells provide different and complementary information regarding cell states. SPARC presents a state-of-the-art co-profiling method that overcomes current limitations in throughput and protein localization, including removing the need for cell fixation.

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Single‐Cell Analysis of Cytokine mRNA and Protein Expression by Flow Cytometry

Current Protocols in Cytometry ◽

10.1002/cpcy.69 ◽

2020 ◽

Vol 92 (1) ◽

Author(s):

Rubina Pal ◽

Jayne Schaubhut ◽

Darcey Clark ◽

Lynette Brown ◽

Jennifer J. Stewart

Keyword(s):

Flow Cytometry ◽

Protein Expression ◽

Single Cell ◽

Single Cell Analysis ◽

Cell Analysis ◽

Cytokine Mrna ◽

Mrna And Protein Expression

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Expression Profiling of Single Mammalian Cells – Small is Beautiful

Yeast ◽

10.1002/1097-0061(20000930)17:3<211::aid-yea26>3.0.co;2-7 ◽

2000 ◽

Vol 1 (3) ◽

pp. 211-217 ◽

Cited By ~ 31

Author(s):

Gerard Brady

Keyword(s):

Mrna Expression ◽

Single Cell ◽

Mammalian Cells ◽

Single Cell Analysis ◽

Single Cells ◽

Expression Patterns ◽

Global Gene Expression ◽

Small Samples ◽

Biological Research ◽

Cell Expression

Increasingly mRNA expression patterns established using a variety of molecular technologies such as cDNA microarrays, SAGE and cDNA display are being used to identify potential regulatory genes and as a means of providing valuable insights into the biological status of the starting sample. Until recently, the application of these techniques has been limited to mRNA isolated from millions or, at very best, several thousand cells thereby restricting the study of small samples and complex tissues. To overcome this limitation a variety of amplification approaches have been developed which are capable of broadly evaluating mRNA expression patterns in single cells. This review will describe approaches that have been employed to examine global gene expression patterns either in small numbers of cells or, wherever possible, in actual isolated single cells. The first half of the review will summarize the technical aspects of methods developed for single-cell analysis and the latter half of the review will describe the areas of biological research that have benefited from single-cell expression analysis.

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NOMA: a high-throughput microchip for robust sequential measurements of secretions from the same single-cells

10.1101/2021.01.21.427049 ◽

2021 ◽

Author(s):

Meimei Liu ◽

Yahui Ji ◽

Fengjiao Zhu ◽

Xue Bai ◽

Linmei Li ◽

...

Keyword(s):

Single Cell ◽

Protein Secretion ◽

Single Cells ◽

Extended Period ◽

Extracellular Vesicle ◽

Single Cell Protein ◽

Cell Protein ◽

Cell Secretion ◽

Suspension Cells ◽

Sequential Measurements

AbstractDespite advances in single-cell secretion analysis technologies, lacking simple methods to reliably keep the live single-cells traceable for longitudinal detection poses a significant obstacle. Here we developed the high-density NOMA (narrow-opening microwell array) microchip that realized the retention of ≥97% of trapped single cells during repetitive detection procedures, regardless of adherent or suspension cells. We demonstrated its use to decode the correlation of protein abundance between secreted extracellular vesicles (EVs) and its donor cells at the same single-cell level, in which we found that these two were poorly correlated with each other. We further applied it in monitoring single-cell protein secretions sequentially from the same single cells. Notably, we observed the digital protein secretion patterns dominate the protein secretion. We also applied the microchip for longitudinally tracking of the single-cell integrative secretions over days, which revealed the presence of “super secretors” within the cell population that could be more persistent to secrete protein or extracellular vesicle for an extended period. The NOMA platform reported here is simple, robust, and easy to operate for realizing sequential measurements from the same single cells, representing a novel and informative tool to inspire new observations in biomedical research.

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