Discovery Proteomics Service

Discovery proteomics involves unbiased, large-scale analysis of proteins in complex biological samples. Unlike targeted proteomics, which focuses on known proteins or specific pathways, the goal of discovery proteomics is to identify and quantify as many proteins as possible without prior assumptions. This approach relies on advanced techniques such as mass spectrometry (MS) to explore the entire proteome, detect post-translational modifications, and discover new biomarkers or disease-associated proteins. Discovery proteomics provides a comprehensive understanding of the proteome, allowing researchers to explore it in an unbiased way and offering new insights into biological phenomena that are not yet understood. By identifying previously unknown proteins or pathways, it opens up new opportunities for solving complex biological problems, such as identifying novel disease biomarkers, understanding disease mechanisms, or discovering new therapeutic targets. This approach overcomes the limitations of traditional methods, which focus only on predefined proteins, and provides a more holistic view of protein functions and interactions. Discovery proteomics plays a key role in advancing personalized medicine and therapeutic development by revealing dynamic changes in protein expression and modification in response to disease or treatment, helping us better understand the onset and progression of diseases.

 



Mesri, M. Adv Med. 2014.

Figure 1. Comparision Between Targeted Proteomics and Discovery Proteomics

 

Service at MtoZ Biolabs

MtoZ Biolabs, an integrated Chromatography and Mass Spectrometry (MS) Services Provider, provides advanced proteomics, metabolomics, and biopharmaceutical analysis services to researchers in biochemistry, biotechnology, and biopharmaceutical fields. MtoZ Biolabs' discovery proteomics service uses mass spectrometry to conduct comprehensive, unbiased analysis of complex biological samples, identifying and quantifying a wide range of proteins, exploring new biomarkers and disease mechanisms, and providing critical support for personalized medicine and therapeutic development.

 

Service Advantages

MtoZ Biolabs' discovery proteomics service offers the following three major advantages:

1. High-throughput Analysis and Comprehensive Coverage  

MtoZ Biolabs' discovery proteomics service utilizes advanced mass spectrometry technology to perform high-throughput analysis of complex biological samples, identifying and quantifying thousands of proteins. This unbiased approach avoids the limitations of focusing only on known proteins, providing a comprehensive view of the proteome and helping researchers explore previously unknown proteins and potential biomarkers.

 

2. Precise Analysis of Post-translational Modifications (PTMs)  

The mass spectrometry-based platform can accurately identify and quantify post-translational modifications (PTMs) of proteins. These modifications play a critical role in regulating protein function, cellular signaling, and disease mechanisms. MtoZ Biolabs' service helps clients gain deep insights into the complexity of protein function, especially in the study of cellular processes and diseases, uncovering potential therapeutic targets.

 

3. High-quality Data Interpretation and Quantification  

MtoZ Biolabs provides not only raw mass spectrometry data but also data analysis and result interpretation. With advanced data processing techniques, the service offers precise quantitative analysis, helping clients better understand protein expression levels and their dynamic changes. This advantage is particularly beneficial for studying the relationship between proteins and diseases or drug responses, driving research and applications in personalized medicine.

 

Case Study

1. Combining Discovery and Targeted Proteomics Reveals a Prognostic Signature in Oral Cancer

Oral squamous cell carcinoma (OSCC) exhibits specific histological and molecular features in different regions, which limits the standard tumor-node-metastasis prognostic classification. Therefore, defining biological characteristics that allow for the assessment of prognosis in OSCC patients would have significant clinical implications. Using histology-guided discovery proteomics, researchers analyzed the tumor islands and stroma of the invasive tumor front (ITF) and internal tumor to identify differentially expressed proteins. Potential feature proteins were prioritized and further studied through immunohistochemistry (IHC) and targeted proteomics. IHC showed that the expression of cystatin B in the tumor islands of the ITF was lower and was an independent marker for local recurrence. Combining machine learning methods, targeted proteomics analysis of prioritized proteins in saliva highlighted peptide-based features as the most powerful predictor to distinguish patients with or without lymph node metastasis. In conclusion, the researchers identified a strong feature that may enhance prognostic decision-making for OSCC and better guide treatment to reduce tumor recurrence or lymph node metastasis.

 



Carnielli, CM. et al. Nat Commun. 2018.

Figure 2. Spatial Characterization of Oral Squamous Cell Carcinoma (OSCC) by Discovery Proteomics

 

2. Discovery Proteomics Reveals Potential Protein Signature Associated with Malignant Phenotype Acquisition in Pleomorphic Adenoma

Microdissection was performed on 30 samples (10 PA, 16 CXPA, and 4 residual PA) followed by liquid chromatography-tandem mass spectrometry (LC-MS/MS). Proteomic data were analyzed using MaxQuant software for LC-MS/MS spectrum analysis and protein identification. Discovery proteomics identified and quantified a total of 240 proteins, of which 135 were present in PA, residual PA, and CXPA. Shared proteins were divided into 6 subgroups, and proteins that showed statistically significant differences (p > 0.05) and fold changes >2.5 or <2.5 between subgroups were included. Seven proteins (Apolipoprotein A-I—APOA1, Haptoglobin—HP, Synaptonemal complex protein 1—SYCP1, Anion exchanger 3—SLC4A1, μ1 subunit of the AP-1 complex—AP1M1, Hemoglobin beta—HBB, and Dermcidin—DCD) were categorized as potential protein features. Among these, HP, AP1M1, and HBB showed higher abundance from PA to residual PA, APOA1 was higher from PA to CXPA, SLC4A1 was lower from PA to CXPA, SYCP1 showed lower abundance from residual PA to CXPA, and DCD was higher in CXPA during epithelial to myoepithelial differentiation. In this study, the researchers presented a comparative proteomic analysis of PA, residual PA, and CXPA, and proposed seven protein features, some of which may be associated with the malignant phenotype of CXPA.

 



 

De, Lima-Souza, RA. et al. Oral Dis. 2023.

Figure 3. Log2-LFQ intensity of the candidate proteins for protein signature

 

FAQ

Q1: How can the quantitative accuracy and sensitivity for low-abundance proteins be improved in discovery proteomics analysis, while reducing biases and errors in data processing, to more accurately reflect the true protein expression in biological samples?

Answer: First, optimizing sample preparation is essential, as improving sample extraction efficiency and minimizing protein degradation can enhance the accuracy of quantitative results. Secondly, the sensitivity of mass spectrometry analysis is key. Using high-resolution mass spectrometers and high-sensitivity ionization techniques, such as electrospray ionization (ESI) or MALDI, can significantly improve the detection of low-abundance proteins. Furthermore, optimizing data analysis algorithms is also critical. Employing more precise quantification methods, such as labeling approaches (SILAC, TMT) or label-free quantification, combined with complex statistical methods, can effectively reduce data bias and improve analysis accuracy. Finally, standardization and validation across laboratories are essential. Through multiple experimental validations and repeat analyses with various samples, the reliability of the data can be further confirmed, ensuring that discovery proteomics results reflect the true biological state. The integration of these technologies and strategies can help overcome the challenges of quantifying low-abundance proteins.

 

Deliverables

1. Comprehensive Experimental Details

2. Materials, Instruments, and Methods

3. Relevant Liquid Chromatography and Mass Spectrometry Parameters

4. The Detailed Information of Proteomics

5. Mass Spectrometry Image

6. Raw Data