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Integrative proteomics and phosphoproteome analysis services for biomarker discovery, signaling pathways, and drug target insights.

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Integrative Analysis Services of Proteomics and Phosphoproteome

What is the Phosphoproteome?

Proteins are the central executors of biological processes, and their regulation often depends on chemical modifications. Among these, phosphorylation represents one of the most dynamic and reversible events. Proteomics provides a global view of protein abundance, while phosphoproteomics reveals signaling activity by identifying phosphorylation events. Integrating these two dimensions enables researchers to understand cellular regulation's static and dynamic layers.

The phosphoproteome refers to the complete set of phosphorylated proteins in a cell, tissue, or organism at a given time. Phosphorylation is catalyzed by kinases and reversed by phosphatases. This reversible modification alters protein conformation, stability, localization, and interaction networks. Unlike total proteomics, which focuses on protein expression levels, phosphoproteomics highlights functional regulation within signaling pathways. Because phosphorylation is tightly linked to cellular responses such as proliferation, apoptosis, and immune activation, the phosphoproteome provides essential information about the dynamic state of biological systems.

Application of phosphoproteomics.

Figure 1. Application of phosphoproteomics in cancer research (Higgins L, et al., 2023).

Why is Proteomics and Phosphoproteome Integrative Analysis Necessary?

Integrating proteomics with phosphoproteomics is critical because protein expression alone does not fully explain functional activity. Many signaling pathways operate independently of protein abundance, relying instead on phosphorylation switches. For example, a kinase may remain at stable expression levels but exhibit increased activity through phosphorylation at specific residues. Without phosphoproteomic data, such regulatory events would remain hidden. Therefore, combining proteome and phosphoproteome analysis is essential for:

Advanced Technologies for Proteomics and Phosphoproteome Integrative Analysis

High-Resolution Mass Spectrometry (MS)

Phosphopeptide Enrichment Strategies

Quantitative Labeling Techniques

Bioinformatics Integration

Advantages of Our Proteomics and Phosphoproteome Integrative Analysis

Workflow for Proteomics and Phosphoproteome Integrative Analysis

Workflow for proteomics and phosphoproteome integrative analysis.

Deliverables and Reporting Standards

Creative Proteomics ensures that results are both detailed and actionable. Deliverables include:

Applications of Proteomics and Phosphoproteome Integrative Analysis

Simple Requirements

Requirement Category Details
Sample Type Accepts a wide range of biological samples, including tissues, cells, plasma, serum, urine, and other biofluids.
Sample Quantity Typically ≥ 100 μg of total protein per sample for proteomics; specific amounts may vary based on project design.
Sample Quality Samples should be free from contaminants such as salts, detergents, and nucleic acids to ensure accurate phosphoproteomic profiling.
Sample Storage Store samples at −80 °C to maintain protein and phosphorylation integrity. Avoid repeated freeze-thaw cycles.
Shipping Conditions Ship samples on dry ice with proper labeling and secure packaging to prevent degradation during transit.

Why Choose Creative Proteomics

FAQ

Q1: What is the difference between proteomics and phosphoproteomics?

A1: Proteomics involves the large-scale study of proteins, particularly their functions and structures. It provides a comprehensive analysis of the protein content in a biological sample. Phosphoproteomics, on the other hand, focuses specifically on identifying and characterizing proteins that have undergone phosphorylation. This post-translational modification is crucial in regulating protein function and cellular signaling.

Q2: Can integrative proteomics detect low-abundance phosphoproteins?

A2: Advanced enrichment strategies (TiO₂, IMAC) combined with high-resolution mass spectrometry allow sensitive detection of low-abundance phosphoproteins that may be critical for signaling pathways or disease mechanisms.

Q3: What are the common methods for phosphopeptide enrichment?

A3: Several strategies are employed to enrich phosphopeptides from complex biological samples:

  • IMAC (Immobilized Metal Affinity Chromatography): Utilizes metal ions to bind phosphopeptides, enriching them for subsequent analysis selectively.
  • TiO₂ (Titanium Dioxide) Chromatography: Offers high specificity for phosphorylated peptides, minimizing non-specific binding.
  • Fe-NTA (Iron-Nitrilotriacetic Acid): Provides low non-specific binding, making it suitable for complex sample analysis.

Q4: What is the difference between site-specific and global phosphorylation analysis?

A4: Site-specific analysis identifies the exact amino acid residue phosphorylated, allowing detailed mapping of signaling networks. Global phosphorylation analysis provides an overview of phosphorylation levels across all proteins but does not resolve individual sites. Integrating both approaches improves pathway interpretation.

Q5: What bioinformatics analyses are typically performed after integrative profiling?

A5: Pathway and Gene Ontology (GO) enrichment analysis.

Kinase-substrate network prediction.

Protein-protein interaction (PPI) network mapping.

Temporal or condition-specific phosphorylation dynamics.

Integration with transcriptomics or metabolomics for multi-omics insights.

Q6: Can integrative proteomics and phosphoproteomics be applied to non-mammalian systems?

A6: Yes. Enrichment strategies and mass spectrometry workflows are compatible with plant, microbial, and model organism samples, enabling cross-species signaling studies.

Demo

Demo: Integrated proteome and phosphoproteome analysis of gastric adenocarcinoma reveals molecular signatures capable of stratifying patient outcome

Tumor vs. adjacent tissue profiling integrated global protein abundance with site-specific phosphorylation to define prognostic signatures in gastric adenocarcinoma.

Quantitative proteomic comparison of patients with and without LNM.

Figure 2. Quantitative proteomic comparison of tissues between GAC patients with and without LNM (Lu X, et al., 2022).

Phosphoproteomic comparison of patients with and without LNM.

Figure 3. Phosphoproteomic comparison of tissues between GAC patients with and without LNM (Lu X, et al., 2022).

KEGG pathways of changed proteins.

Figure 4. KEGG pathways of upregulated proteins, phosphoproteins, and abnormal activity kinases (Lu X, et al., 2022).

Case Study

Case: Integrated proteome and phosphoproteome analysis of gastric adenocarcinoma reveals molecular signatures capable of stratifying patient outcome

Abstract:

Naive T cells reside in quiescence and exit quiescence upon antigen stimulation. Transcriptional measurements alone do not fully predict protein-level responses, and phosphorylation acts as a rapid, reversible signaling regulator. Therefore, simultaneous temporal profiling of the proteome and phosphoproteome is required to reconstruct signaling networks that drive T cell activation. To generate a temporal, integrative proteomic and phosphoproteomic atlas of naive mouse T cell activation and to use that multi-layer dataset to infer kinase-transcription factor (TF) networks and identify bioenergetic pathways critical for quiescence exit. The authors also sought functional validation of key predictions.

Methods

  • Naive mouse T cells were stimulated with anti-CD3/anti-CD28 and sampled at multiple time points (0, 2, 8, 16 h).
  • Tandem Mass Tag (TMT) multiplexed labeling was used for quantitative proteomics.
  • Deep LC/LC-MS/MS profiled the global proteome and an enriched phosphopeptide fraction from the same pooled samples.
  • Bioinformatics pipelines integrated time-series proteome and phosphoproteome data with TF-target and kinase-substrate databases to reconstruct regulatory networks.
  • Key predictions were functionally tested by genetic perturbation (e.g., COX10 knockout) and pharmacology.

Results

  • The authors quantified ~8,400 proteins and ~13,700 phosphopeptides with high confidence. Early (2 h) responses were dominated by phosphorylation dynamics, whereas later time points (8–16 h) showed large changes in protein abundance.
  • Integrative clustering revealed co-expression modules linking translation, mitochondrial function (mitoribosomes, complex IV), and metabolic pathways to T cell activation.
  • Kinase-activity inference identified dynamic rewiring of kinase signaling (e.g., central roles of AKT-mTOR as positive regulators and modulation of GSK3β and DNA-damage response kinases).  
  • Functional validation: COX10 (complex IV assembly factor) was required for oxidative phosphorylation (OXPHOS) activation and for efficient exit from quiescence, supporting a causal role for the mitochondrial pathways inferred from the integrated data.
Temporal profiling of whole proteome and phosphoproteome.

Figure 5. Temporal profiling of whole proteome and phosphoproteome during T cell activation.

Temporal expression profiling of whole proteome.

Figure 6. Temporal expression profiling of whole proteome reveals co-expression clusters and functional modules during T cell activation.

T cell phosphoproteome profiling.

Figure 7. T cell phosphoproteome profiling reveals co-expression clusters, multiple active kinases, and dynamically regulated kinase signaling networks.

Conclusion

Temporal integrative profiling of the proteome and phosphoproteome reveals that T cell activation proceeds via an early phosphorylation-driven signaling phase followed by a later proteome reprogramming phase. Systems-level integration identifies key kinase-TF circuits and bioenergetics modules (notably mitoribosomes and complex IV) that are functionally necessary for naive T cells to exit quiescence. The multi-tier pipeline (proteome + phosphoproteome + databases + perturbation) provides superior sensitivity for discovering core molecular circuits compared with single-omic approaches.

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References

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