Immunoprecipitation-mass spectrometry (IP-MS) stands as a pivotal investigational technique for exploring protein-protein interactions and elucidating the mechanistic underpinnings of protein function. Within this domain, Creative Proteomics introduces a comprehensive IP-MS protein interactome solution, comprising three constituent sub-projects:
IP-MS Efficacy Assessment:
This sub-project entails the critical evaluation of IP-MS experimental outcomes. The objective is to enhance the efficacy of IP-MS experiments, thereby elevating the subsequent experimental success rates and constricting the trial-and-error cycles.
Interacting Protein Screening:
Focused on the meticulous screening of proteins that interact with identified bait proteins, this sub-project aids in the discernment and selection of critical interacting proteins. The outcome serves as a valuable resource for understanding the intricate network of protein-protein interactions.
Dynamic Interactome Profiling:
Under this sub-project, a nuanced analysis of the dynamic alterations in protein-protein interactions associated with bait proteins is conducted. The exploration extends to diverse experimental conditions, providing insights into the dynamic changes in protein interactions under varying circumstances.
Principles of IP-MS Technology:
The IP-MS technique hinges upon the application of affinity purification methods, such as immunoprecipitation and Bio ID, to selectively enrich the target protein under investigation along with its interacting partners. Subsequently, parallel mass spectrometric analyses are conducted with a control group for comparative purposes. Through scrutiny of the identification and quantification data derived from mass spectrometry, proteins that are exclusive to the experimental group or exhibit significantly elevated quantitative values within the experimental context are discerned. These proteins represent the pool of candidate interacting partners for the target protein. The integration of affinity purification and mass spectrometry in this approach allows for a precise and systematic exploration of protein-protein interactions, shedding light on the intricacies of molecular associations within biological systems.
Principle of the ImmunoPrecipitation followed by Mass Spectrometry (IP-MS) technique. (Konstantin Yu. Kulichikhin et al,. 2021)
IP-MS Service Flow
The service framework involves the following steps:
Clients provide bead samples obtained from IP experiments.
Creative Proteomics employs advanced high-resolution LC-MS systems to conduct meticulous detection of the submitted bead samples.
A comprehensive report is generated based on the mass spectrometric data. The report encompasses various aspects outlined in the Service Configuration Table at the end of this document.
Evaluation results of IP-MS experiment effectiveness and data quality.
List of interacting proteins with high confidence, accompanied by annotation-enriched analysis conducive for assisting in the selection of critical interacting proteins.
Mining of protein-protein interaction databases.
Analysis of interaction networks, including screening, construction, and dynamic analysis of interaction networks.
Integration of publicly available protein-protein interaction database information for the selection and dynamic analysis of key nodes within interaction networks.
IP Efficacy Assessment
One of the primary challenges encountered in IP-MS experiments arises from suboptimal outcomes in the initial stages of IP experiments. This often leads to an overabundance or scarcity of identified interacting proteins, subsequently hindering successful validation in downstream analyses. Traditional approaches, such as Western Blot (WB) verification of IP experiment efficacy, frequently fall short due to factors like antibody quality discrepancies and variations in WB and mass spectrometry principles and sensitivity. Consequently, WB results may inadequately predict MS outcomes. IP efficacy assessment serves as a critical preemptive measure to evaluate the efficacy of IP experiments prior to mass spectrometric analysis, thereby enhancing the success rate of subsequent IP-MS experiments and abbreviating trial-and-error cycles.
Introducing our novel "IP Efficacy Assessment" product, we leverage mass spectrometric identification and quantification data of total proteins and bait proteins within the sample to evaluate the efficacy of IP experiments. This assessment discerns whether the sample meets the requirements for subsequent screening of interacting proteins or dynamic interactome profiling. In cases where preliminary experiments yield suboptimal results, our product facilitates timely decision-making to minimize losses. Additionally, we provide expert insights for experiment optimization, ensuring the attainment of reliable and desirable IP-MS experimental results. This proactive approach aims to streamline the experimental process, contributing to the generation of robust and meaningful scientific outcomes.
Protein Interaction Screening:
Conventional IP-MS investigations, lacking a control group, often rely on a single experimental sample for mass spectrometric analysis. This approach may yield identifications of thousands of proteins, predominantly comprising nonspecifically bound entities. Consequently, downstream validation experiments become resource-intensive, time-consuming, and characterized by a lower success rate.
Introducing our novel "Protein Interaction Screening" product, we employ a quantitative differential analysis of total proteins between experimental and control group samples. This discerning process identifies high-confidence interacting proteins, mitigating the inclusion of non-specific binders. Integrated with the STRING database's known protein-protein interactions, a comprehensive protein interaction network is constructed. Further refinement is achieved through network importance scoring and functional annotation enrichment analysis. This multifaceted approach assists in the targeted selection of key interacting proteins with heightened potential for research significance.
Dynamic Interactome Profiling:
Within cellular environments, protein-protein interactions often undergo dynamic fluctuations. Certain interactions manifest exclusively under specific conditions, while others exhibit varying degrees of alteration in response to environmental changes.
Our company is pleased to introduce the "Dynamic Interactome Profiling" product. This innovative offering leverages the quantitative differences in protein expression between multiple experimental group samples under diverse conditions and corresponding control group samples. The primary objective is to discern interacting proteins associated with bait proteins. By utilizing quantitative information pertaining to bait proteins, we correct for variations in the degree of protein interaction. Furthermore, our approach encompasses an in-depth analysis of the changes in protein interaction levels under distinct experimental conditions.
|IP Efficacy Assessment
|Protein Interaction Screening
|Dynamic Interactome Profiling
|Protein Identification List
|Quantitative Interaction Screening*
|IP Experiment Efficacy Assessment*
|GO Enrichment Analysis
|KEGG Enrichment Analysis
|Quantitative Heat Map of Interacting Proteins
|Dynamic Clustering of Interaction Differences*
|STRING Database Exploration
|Protein-Protein Interaction (PPI) Network*
|Node Scoring and Subnetwork Analysis
|Materials and Methods
|Mass Spectrometry Quality Control
*Indicates Key Results.
Optimized Sample Submission: Enhanced by the synergy of Bead Sample Submission and Sample Matching, this approach significantly elevates the depth of detection and ensures data stability.
IP-MS Efficacy Assessment: Timely identification of potential issues in IP experiments, coupled with the provision of optimization recommendations, markedly enhances the success rate of subsequent validation experiments.
Interacting Protein Screening Methodology: Leveraging quantitative data and differential analysis, the screening of interacting proteins is refined, leading to a substantial improvement in identification efficiency and credibility.
Efficient Assistance in Selecting Key Proteins: a. Public Databases + IP-MS Experimental Data Integration: Construction of a comprehensive and systematic protein interaction network. Utilizing the cytoHubba network node importance scoring algorithm, critical protein nodes within the interaction network are analyzed. b. Functional Annotation and Enrichment Analysis using GO and KEGG Databases: Auxiliary selection of crucial interacting proteins through functional annotation and enrichment analysis.
Comparison of Interaction Levels: Calibration and standardization of protein interaction levels based on quantitative data from control groups and bait proteins. This approach enables a more accurate and effective analysis of the dynamic changes in protein interactions under varying conditions.
Sample Submission Requirements:
At least one sample from the IP-MS experimental group is required.
Ensure the inclusion of a minimum of one sample representative of the IP-MS experimental conditions.
Recommendation for Initial Cell Count per Individual Sample: >2*10^7 cells.
It is advised that each individual sample should have an initial cell count exceeding 2*10^7 cells.
Post-Affinity Enrichment Handling:
Following affinity enrichment, perform rinsing with a detergent-free buffer or PBS.
Preserve the samples in a bead-conducive state for optimal conditions during submission.