scholarly journals Single cell protein analysis for systems biology

Author(s):  
Ezra Levy ◽  
Nikolai Slavov

The cellular abundance of proteins can vary even between isogenic single cells. This variability between single-cell protein levels can have functional roles, such as controlling cell fate during apoptosis induction or the proliferation/quiescence decision. Here, we review such examples of connecting protein levels and their dynamics in single cells to cellular functions. Such findings were made possible by the introduction of antibodies, and subsequently fluorescent proteins, for tracking protein levels in single cells. However, in heterogeneous cell populations, such as tumors or differentiating stem cells, cellular decisions are controlled by hundreds, even thousands of proteins acting in concert. Characterizing such complex systems demands measurements of thousands of proteins across thousands of single cells. This demand has inspired the development of new methods for single cell protein analysis, and we discuss their trade-offs, with emphasis on their specificity and coverage. We finish by highlighting the potential of emerging mass-spec methods to enable systems-level measurement of single-cell proteomes with unprecedented coverage and specificity. Combining such methods with methods for quantifying the trasncriptomes and metabolomes of single cells will provide essential data for advancing quantitative systems biology.

2018 ◽  
Vol 62 (4) ◽  
pp. 595-605 ◽  
Author(s):  
Ezra Levy ◽  
Nikolai Slavov

The cellular abundance of proteins can vary even between isogenic single cells. This variability between single-cell protein levels can have regulatory roles, such as controlling cell fate during apoptosis induction or the proliferation/quiescence decision. Here, we review examples connecting protein levels and their dynamics in single cells to cellular functions. Such findings were made possible by the introduction of antibodies, and subsequently fluorescent proteins, for tracking protein levels in single cells. However, in heterogeneous cell populations, such as tumors or differentiating stem cells, cellular decisions are controlled by hundreds, even thousands of proteins acting in concert. Characterizing such complex systems demands measurements of thousands of proteins across thousands of single cells. This demand has inspired the development of new methods for single-cell protein analysis, and we discuss their trade-offs, with an emphasis on their specificity and coverage. We finish by highlighting the potential of emerging mass-spec methods to enable systems-level measurement of single-cell proteomes with unprecedented coverage and specificity. Combining such methods with methods for quantitating the transcriptomes and metabolomes of single cells will provide essential data for advancing quantitative systems biology.


Author(s):  
Ezra Levy ◽  
Nikolai Slavov

The cellular abundance of proteins can vary even between isogenic single cells. This variability between single-cell protein levels can have functional roles, such as controlling cell fate during apoptosis induction or the proliferation/quiescence decision. Here, we review such examples of connecting protein levels and their dynamics in single cells to cellular functions. Such findings were made possible by the introduction of antibodies, and subsequently fluorescent proteins, for tracking protein levels in single cells. However, in heterogeneous cell populations, such as tumors or differentiating stem cells, cellular decisions are controlled by hundreds, even thousands of proteins acting in concert. Characterizing such complex systems demands measurements of thousands of proteins across thousands of single cells. This demand has inspired the development of new methods for single cell protein analysis, and we discuss their trade-offs, with emphasis on their specificity and coverage. We finish by highlighting the potential of emerging mass-spec methods to enable systems-level measurement of single-cell proteomes with unprecedented coverage and specificity. Combining such methods with methods for quantifying the trasncriptomes and metabolomes of single cells will provide essential data for advancing quantitative systems biology.


2021 ◽  
Author(s):  
Aleksandra A Petelski ◽  
Edward Emmott ◽  
Andrew Leduc ◽  
R. Gray Huffman ◽  
Harrison Specht ◽  
...  

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.


2019 ◽  
Vol 411 (19) ◽  
pp. 4339-4347
Author(s):  
Siwen Wang ◽  
Fei Ji ◽  
Zhonghan Li ◽  
Min Xue

Lab on a Chip ◽  
2013 ◽  
Vol 13 (11) ◽  
pp. 2066 ◽  
Author(s):  
Ali Salehi-Reyhani ◽  
Sanjiv Sharma ◽  
Edward Burgin ◽  
Michael Barclay ◽  
Anthony Cass ◽  
...  

Author(s):  
Zhihang Yu ◽  
Jing Jin ◽  
Lingling Shui ◽  
Huaying Chen ◽  
Yonggang Zhu

2016 ◽  
Author(s):  
Yann S Dufour ◽  
Sébastien Gillet ◽  
Nicholas W Frankel ◽  
Douglas B Weibel ◽  
Thierry Emonet

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.


2021 ◽  
Author(s):  
Meimei Liu ◽  
Yahui Ji ◽  
Fengjiao Zhu ◽  
Xue Bai ◽  
Linmei Li ◽  
...  

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.


2021 ◽  
Author(s):  
Julea Vlassakis ◽  
Louise L Hansen ◽  
Amy E Herr

Abstract We introduce micro-arrayed, differential detergent fractionation for the simultaneous detection of protein complexes in 100s of individual cells with SIFTER (Single-cell protein Interaction Fractionation Through Electrophoresis and immunoassay Readout). Size-based fractionation of protein complexes is accomplished with five assay steps. First, a cell suspension generated by trypsinization is introduced onto a microwell array, and single cells are settled into the microwells by gravity. Cells are lysed in F-actin stabilization buffer that is delivered by a hydrogel lid. Second, the protein complexes are fractionated from the smaller monomers by polyacrylamide gel electrophoresis. Monomers are electrophoresed into the gel and are immobilized using a UV-induced covalent reaction to benzophenone. Third, a protein-complex depolymerization buffer is introduced by another hydrogel lid. Fourth, the recently depolymerized complexes are electrophoresed into a region of the gel separate from the immobilized monomers, where the complex fraction are in turn immobilized. Fifth, in-gel immunoprobing detects the immobilized populations of monomer and depolymerized complexes. These general steps are built on previously published protocols for bulk actin studies, single-cell western blotting, and bidirectional separations1-4.


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