Single-Cell Proteomics Service
Unlock the hidden complexity of cellular biology with Creative Proteomics' advanced single-cell proteomics services. Traditional bulk proteomics averages signals across millions of cells, often masking critical insights about rare cell populations and subtle protein changes. Our cutting-edge single-cell workflows enable precise identification and quantification of thousands of proteins, proteoforms, and post-translational modifications in individual cells,
- High Sensitivity & Coverage: Detect low-abundance proteins and subtle biological variations at the single-cell level using FAIMS-enabled Orbitrap and TMT multiplexing.
- Customized Workflows: Flexible options for qualitative, quantitative, targeted, or PTM-focused analysis to fit your research objectives.
- Comprehensive Data Analysis: Bioinformatics pipelines provide interactive visualizations, pathway mapping, and protein network analysis for deeper understanding.
- Trusted & Reliable: Collaborations with leading proteomics laboratories and adherence to rigorous quality standards guarantee reproducible, high-quality results.
Single-Cell Proteomics: Unlocking Cellular Heterogeneity for Advanced Research
Single-cell proteomics (SCP) is a transformative approach that enables the comprehensive analysis of protein expression at the level of individual cells. Unlike traditional bulk proteomics, which averages signals across millions of cells, SCP captures the nuanced variations that define cellular heterogeneity. This technology has become essential in modern biomedical research, allowing scientists to study rare cell populations, detect subtle changes in protein abundance, and investigate post-translational modifications (PTMs) that are critical to understanding biological pathways and disease mechanisms.
Single-cell proteomics holds particular promise for pharmaceutical research and development, enabling the discovery of novel biomarkers, optimizing research strategies, and providing a detailed molecular view of complex biological systems. Creative Proteomics provides advanced analysis service for Plant Single-Cell Proteomics.
Figure 1. Pipeline for single-cell proteomics of the brain (Goto-Silva L, et al., 2021).
Single-Cell Proteomics vs. Traditional Proteomics
| Aspect | Single-Cell Proteomics | Traditional Proteomics |
| Basic concept | Measures proteins in individual cells to reveal cell-to-cell differences. | Measures proteins from many cells pooled together; gives an average picture. |
| Sample input | One cell at a time. | Millions of cells pooled into one sample. |
| Sensitivity | Designed to detect very low-abundance proteins in a single cell. | Detects proteins present at higher levels across the pooled sample. |
| Quantitation | High precision for comparing single cells when optimized. | High precision for average protein levels across the population. |
| Throughput | Lower per run unless multiplexing is used; newer methods increase throughput to hundreds–thousands of cells/day. | Typically higher throughput per run for many bulk samples, easier scale. |
| Data complexity | High — sparse data matrices, more missing values, needs tailored statistics and visualization. | Lower — denser data, established pipelines and simpler stats. |
| Best applications | Studying cell heterogeneity, rare cell types, cell-state transitions, or single-cell responses. | Measuring average protein expression, large cohort comparisons, and method development. |
| Limitations | More expensive per informative cell; requires specialized instruments and bioinformatics. | Misses cell-level variation; can obscure minority or transient cell states. |
Advanced Technologies in Single-Cell Proteomics Analysis
Mass Spectrometry-Based Workflows
Orbitrap-based mass spectrometers provide high-resolution, high-accuracy measurements of thousands of proteins from individual cells. FAIMS (high-field asymmetric waveform ion mobility spectrometry) enhances signal-to-noise ratios, improving sensitivity and enabling the robust detection of low-abundance proteins.
Multiplexing and Isobaric Labeling Strategies
Tandem Mass Tag (TMT) multiplexing enables the simultaneous analysis of multiple single cells, thereby boosting throughput and quantitative precision. This approach supports high-throughput projects, allowing the analysis of hundreds to thousands of cells per day while maintaining data accuracy and reproducibility.
High-Sensitivity Sample Preparation
Accurate protein profiling begins with precise cell isolation. Techniques such as microfluidics, fluorescence-activated cell sorting (FACS), and single-cell microarrays enable researchers to capture individual cells while maintaining spatial and temporal context. Proteins are extracted, labeled, and prepared for mass spectrometry with minimal loss, ensuring reliable detection of low-abundance targets.
Creative Proteomics' Single-Cell Proteomics Service Workflow
- Single-Cell Screening: Isolation of individual cells via microfluidic sorting, FACS, or microdissection.
- Protein Extraction: Gentle lysis and optimized digestion protocols ensure maximal protein recovery from ultra-low input samples.
- Protein Identification and Quantification: Performed using LC-MS/MS, protein microarrays, or targeted Western blot assays.
- Bioinformatics Analysis: Raw data undergo statistical, pathway, and network analyses to extract biological meaning.
- Result Delivery: Clear, structured data and interpretive insights are delivered in publication-ready formats.
Optimizing Single-Cell Proteomics for Your Research Goals
Choosing the Right Sample and Cell Type
Selecting the appropriate cell population is crucial. Rare or phenotypically distinct cells may require enrichment strategies to ensure sufficient material for analysis. Creative Proteomics offers consultation services to define sample requirements and optimize experimental design for maximum impact.
Workflow Customization for Targeted Analyses
Depending on the research goal, workflows can focus on qualitative or quantitative proteomics, PTM detection, or multi-omics integration. Customization enables researchers to prioritize sensitivity, throughput, or depth of coverage according to their project objectives.
Deliverables and Reporting Standards
- Quantitative protein abundance tables per cell
- PTM identification and mapping
- Visualizations such as volcano plots, heatmaps, dot plots, and pathway networks
- Interactive analyses for signaling and functional pathways
- Comprehensive reports with interpretations and recommendations for follow-up studies
Applications of Single-Cell Proteomics
- Identifies proteomic biomarkers in resistant or metastatic subclones to inform target selection and patient stratification.
- Resolves immune cell activation states and signaling dynamics that support vaccine development and immunotherapy programs.
- Maps proteome changes across differentiation trajectories to enhance directed differentiation and regenerative protocols.
- Profiling discriminates cell-type-specific proteoforms implicated in neurodegeneration and synaptic function.
- Plant single-cell proteomics reveals cell-type-specific stress responses and trait mechanisms that guide crop improvement.
Sample Requirements
| Sample Type | Recommended Format | Minimum Quantity | Storage/Transport Conditions |
| Cultured Cells | Fresh or cryopreserved single-cell suspension | ≥1,000–10,000 cells per sample | Cryopreserved in liquid nitrogen or on dry ice |
| Primary Tissue Samples | Single-cell suspension after dissociation | ≥50,000 cells per sample | Fresh on ice or cryopreserved |
| PBMCs / Blood Cells | Isolated single-cell suspension | ≥10,000 cells per sample | Cryopreserved in DMSO-based media |
| Rare Cell Populations | Enriched using FACS or microfluidics | ≥1,000 cells per subpopulation | Cryopreserved or processed immediately |
| Plant Cells / Protoplasts | Freshly isolated single-cell suspension | ≥50,000 cells per sample | Keep on ice or use preservation buffer |
Why Choose Creative Proteomics for Your Single-Cell Proteomics Service
- Over years of proteomics experience serving academia, biotechnology, and pharmaceutical industries.
- Equipped with next-generation Orbitrap, timsTOF, and nanoLC platforms for superior sensitivity.
- Tailored analysis plans that align with specific research goals and sample characteristics.
- Efficient workflows ensure timely project delivery without compromising data quality.
- Scientific consultation at every stage—from experimental design to final data interpretation.
FAQ
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Q1: What is the role of multiplexing in single-cell proteomics?
A1: Multiplexing, particularly using TMT (Tandem Mass Tag) labeling, allows multiple single cells to be analyzed simultaneously. This improves throughput, reduces experimental variability, and maintains high quantitative precision, enabling studies on hundreds or thousands of cells in a single experiment.
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Q2: How are rare or fragile cells protected during single-cell isolation?
A2: Techniques such as gentle microfluidic sorting, fluorescence-activated cell sorting (FACS) with optimized settings, and minimal handling protocols help maintain cell viability and protein integrity, ensuring accurate downstream proteomic analysis.
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Q3: Can single-cell proteomics be combined with spatial proteomics?
A3: Yes. Spatially resolved SCP combines protein profiling with localization data, providing insights into tissue architecture, microenvironments, and cell–cell interactions. Techniques such as laser capture microdissection or imaging mass spectrometry facilitate spatially informed proteome analysis.
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Q4: Can single-cell proteomics support longitudinal or time-course studies?
A4: Yes. By sampling cells at multiple time points, SCP can track dynamic changes in proteome profiles, signaling pathways, and PTMs, providing temporal insights into cellular processes, differentiation, or drug responses.
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Q5: What is the typical turnaround time for single-cell proteomics projects?
A5: Turnaround depends on sample type, workflow complexity, and throughput. Standard projects can deliver results within a few weeks, while large-scale or multi-omics projects may require additional time for data analysis, bioinformatics interpretation, and reporting.
Demo
Demo: Ultrasensitive single-cell proteomics workflow identifies> 1000 protein groups per mammalian cell.
Figure 2. Representative mass spectra obtained without (A) and with (B) FAIMS filtering (Cong Y, et al. 2021).
Figure 3. Single-cell proteomic interrogation of human spinal motor neurons and interneurons (Cong Y, et al. 2021).
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Case Study
Case: Single-cell proteomics reveals changes in expression during hair-cell development
Abstract
The study applied single-cell proteomics with sensitive mass spectrometry to characterize protein expression in embryonic chick utricle cells, including supporting cells, hair cell progenitors, and differentiated hair cells. This approach enabled the reconstruction of a developmental trajectory based solely on protein data, revealing cell-type-specific proteins and dynamic changes in cytoskeletal proteins, such as actin and TMSB4X, which were not evident from transcriptomic analysis alone.
Methods
- Single-Cell Isolation: Utricles from E15 chick embryos were dissociated and FACS-sorted into supporting cells, hair cell progenitors, and hair cells using FM1-43 labeling and SYTOX Red exclusion.
- Sample Preparation: Cells were sorted into nanowells; proteins were lysed, reduced, alkylated, and digested sequentially with Lys-C and trypsin. Peptides were collected and analyzed using an Orbitrap Fusion Lumos mass spectrometer.
- Additional Analyses: Immunocytochemistry and volumetric measurements were used to validate protein localization and cell morphology.
Results
- Proteome Coverage: Detected abundant proteins in single cells (~75 robustly detected proteins) with improved detection of small proteins (<20 kDa). Membrane proteins remained underrepresented.
- Cell Type-Specific Proteins: Identified novel hair cell-specific proteins (CRABP1, GSTO1, GPX2, AK1) and supporting cell-specific proteins (AGR3, TMSB4X). TMSB4X was highly abundant in supporting cells but decreased in hair cells.
- Actin Dynamics: ACTB was downregulated during hair cell differentiation, particularly in extrastriolar cells, while ACTG1 increased to compensate. Total actin protein levels remained similar across cell types.
- Developmental Trajectories: Protein-based trajectories reconstructed differentiation from progenitors to hair cells. GAPDH levels increased independently of mRNA, suggesting post-transcriptional regulation.
Figure 4. Mass spectrometry of single cells and small cell pools from E15 chick utricle.
Figure 5. Pseudotemporal ordering of single utricle cells based on proteomics measurements.
Conclusion
Single-cell proteomics enables the direct measurement of protein dynamics in extremely small cells, revealing developmental trajectories, post-transcriptional regulation, and cell-type-specific protein expression that is not apparent from transcriptomic data alone. Further methodological improvements will enhance the detection of low-abundance proteins and facilitate the analysis of post-translational modifications, thereby providing a robust platform for studying cellular differentiation at the protein level.
Related Services
References
- Goto-Silva L, Junqueira M. Single-cell proteomics: A treasure trove in neurobiology. Biochimica et Biophysica Acta (BBA)-Proteins and Proteomics, 2021, 1869(7): 140658.
- Cong Y, et al. Ultrasensitive single-cell proteomics workflow identifies> 1000 protein groups per mammalian cell. Chemical science, 2021, 12(3): 1001-1006.
- Zhu Y, et al. Single-cell proteomics reveals changes in expression during hair-cell development. Elife, 2019, 8: e50777.
