Single-cell Proteomics
Single-cell Proteomics - Related Videos
09:29
Skeletal Muscle Gender Dimorphism from Proteomics
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Cited by 4 •
2011
A straight-forward set of methods to isolate and determine the identity of the most abundant proteins expressed in skeletal muscle. About 800 spots are discerned on a two-dimensional gel from 10 mg muscle; this allows for the determination of gender-specific protein expression. These methods will give equivalent results in most tissues.
10:11
Glycopeptide Capture for Cell Surface Proteomics
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Cited by 8 •
2014
Cell surface proteins are biologically important and widely glycosylated. We introduce here a glycopeptide-capture approach to solubilize, enrich, and deglycosylate these proteins for facile LC-MS based proteomic analyses.
09:20
Proteomic Sample Preparation from Formalin Fixed and Paraffin Embedded Tissue
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Cited by 50 •
2013
Archival formalin fixed and paraffin embedded (FFPE) clinical samples are valuable material for investigation of diseases. Here we demonstrate a sample preparation workflow allowing in-depth proteomic analysis of microdissected FFPE tissue.
14:23
Bottom-up and Shotgun Proteomics to Identify a Comprehensive Cochlear Proteome
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Cited by 6 •
2014
Proteome analysis of the cochlear sensory epithelium can be challenging due to its small size and because membrane proteins are difficult to isolate and identify. Both membrane and soluble proteins can be identified by combining multiple preparative methods and separation techniques along with high-resolution mass spectrometry.
11:44
Metabolic Labeling and Membrane Fractionation for Comparative Proteomic Analysis of Arabidopsis thaliana Suspension Cell Cultures
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Cited by 5 •
2013
Here we describe a robust method for the fractionation of plant plasma membranes into detergent resistant and detergent soluble membranes based on a mixture of unlabeled and in vivo fully 15N labeled Arabidopsis thaliana cell cultures. The procedure is applied for comparative proteomic studies to understand signaling processes.
FAQs
Population-averaged measurements combine signals from many cells, so a minority state can disappear within the overall profile. Single-cell proteomics retains the molecular signature of each analyzed cell, allowing researchers to compare cellular states rather than only a sample-wide average. This distinction is especially important when immune cells respond differently to activation or infection, revealing heterogeneity that bulk assays may conceal.
After lysis, digestion converts cellular proteins into peptides that can be measured and identified. Ultrasensitive mass spectrometry then links peptide signals to protein identities and quantities, while also enabling analysis of protein modifications. Together, these steps translate the limited material from one cell into molecular measurements suitable for comparing immune or infection-associated states.
Mass spectrometry measures identified and quantified peptides, including protein modifications, whereas antibody-based platforms provide complementary targeted measurements. A targeted antibody panel can focus analysis on selected proteins across individual cells. This distinction helps investigators match the platform to the research question, choosing targeted measurement when predefined immune-related markers are the priority.
A typical workflow starts by isolating or barcoding individual cells so their measurements remain attributable to the correct cell. Researchers lyse those cells, digest the released proteins into peptides, and analyze the peptides with ultrasensitive mass spectrometry. The resulting identifications and quantities are then compared across cells, enabling analysis of immune-cell states or infection-associated response patterns.
It is especially informative when cells within an immune sample may occupy different states during activation or infection. Cell-level measurements can distinguish heterogeneous immune responses, track signaling changes, and identify rare populations that population-averaged assays could obscure. Researchers can therefore examine host responses associated with infection and investigate how those responses vary among individual cells.
Profiles from individual cells can reveal molecular patterns associated with host responses and disease-related heterogeneity. Those patterns may support biomarker discovery and disease stratification by distinguishing groups with different cellular profiles. The same resolution can inform more precise therapeutic studies, where researchers need to evaluate responses at the level of individual cell states rather than relying only on a combined sample measurement.