Sharpening the tool of single-cell proteomics

March 16, 2018
Figure: Optimization of liquid chromatography and mass spectrometry (LC-MS) single-cell proteomics tools for sequencing and quantifying the proteome from individual cells.

The motivation – Single-cell proteomics is the study of protein expression at the level of individual cells.

Achieving this level of sensitivity in analysis would be a dream come true for many scientists. Ultimately, this would allow the identification of components from rare cells; whereas this level of detail is not possible in conventional bulk analysis because bulk samples contain a complicated mix of proteins from many different cells. All naturally existing cell populations are heterogeneous, including those found in cancerous tissues. Mixing of cell types and states in bulk analysis masks the detection of disease-causing cells; these abnormal cells are present in rare amounts at early stages of disease. Because these rare cells are undetectable until large numbers develop, life-saving treatment is delayed. The capability of analyzing one cell at a time in single-cell proteomics avoids the mixing of cell populations, and is a critical technique for studying cellular function, disease diagnosis and therapy.  

The discovery – To study single-cell proteomics is technically challenging. The most powerful tool for single-cell proteomics is liquid chromatography and mass spectrometry (LC-MS). Simon Fraser University’s Bingyun Sun and her coworkers have developed and mathematically modeled a set of parameters that allow the cutting-edge LC-MS system—Thermo Q-Exactive HF orbitrap mass spectrometer coupled to EASY nLC 1000—to detect hundreds of proteins from 1-2 mammalian cells, and several thousand proteins from 10-20 mammalian cells.

Its significance – The developed parameter set is a huge step forward from what can be accomplished with conventional bulk proteomic analysis.  In single-cell proteomics, a total of 1 nanogram of thousands of proteins are present at concentrations ranging 5-6 orders of magnitude, whereas bulk studies can only detect micrograms of proteins. This study also presents the first mathematical model to describe and predict the best parameters. The findings help to address a decade old question of whether the current instrumentation is sensitive enough for single-cell proteomics. The demonstrated instrument sensitivity is leading in the field. The optimized parameters and developed mathematical models sharpen the analytical tool for single-cell proteomics and will benefit researchers who are interested in trace sample proteomics studies. Indeed, it has already been noted in recent work, including studies looking at single neurons and prostate cancer.

Read the paper – “Optimization and Modeling of Quadrupole Orbitrap Parameters for Sensitive Analysis toward Single-Cell Proteomics” by Bingyun Sun, Jessica Rae Kovatch, Albert Badiong, and Nabyl Merbouh. Proteome Research 16(10): 3711–3721 (2017). DOI: 10.1021/acs.jproteome.7b00416

Website article compiled by Jacqueline Watson with Theresa Kitos