Integrating Proteome and Metabolome Analysis in Diverse Biological Contexts

What is Metabolome and Proteome Analysis?

Proteomics is a discipline in the era of functional genomics that focuses on the comprehensive study of the composition, activity patterns, and interactions of proteins within a cell at the global level. Serving as the executors of life processes, proteins play crucial roles in cellular functions. Proteomics, particularly mass spectrometry-based proteomics, investigates the entirety of the cellular protein landscape.

Metabolomics, on the other hand, is a burgeoning post-genomic technology that characterizes qualitative and quantitative changes in small-molecule metabolites (metabolites with molecular masses below 1,000 Da) across different biological systems. It aims to explore key scientific questions related to the metabolism of organisms and cells. Metabolomics serves as a descriptor of phenotype states and an active regulator of cellular function. Metabolites can modulate protein interactions, alter enzyme activity, and influence protein stability, thereby regulating overall cellular metabolism.

The integration of proteomics and metabolomics, collectively known as integrated proteomic and metabolomic analysis, provides an effective research strategy for describing the regulatory networks of organismal metabolism. Proteomics, investigating the global protein landscape, and metabolomics, characterizing small-molecule metabolites, collectively offer a comprehensive view of the molecular interactions that govern biological systems.

The integration and analysis of data from both proteomics and metabolomics allow for the rapid screening and identification of proteins and metabolites that participate in specific metabolic pathways or exhibit similar trends in changes. This systematic approach facilitates the description of molecular regulatory mechanisms within organisms. Moreover, it provides a foundational data basis for subsequent experimental validation and analysis.

In summary, proteome analysis, focusing on the global study of proteins, and metabolome analysis, characterizing small-molecule metabolites, contribute to a comprehensive understanding of cellular functions and metabolic regulation. The integrated analysis of proteomic and metabolomic data forms a powerful strategy for unraveling the intricate molecular networks that govern biological organisms.

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How Do the Proteome and Metabolome Relate to Each Other?

Pathway-Centric Integrated Analysis

The integration of proteomic and metabolomic data is facilitated through the utilization of the KEGG metabolic pathways. This approach aims to identify proteins and metabolites exhibiting significant changes within the same biological process, as delineated by KEGG Pathways. The rapid identification of key proteins and metabolites is achieved through the amalgamation of data, followed by visualization of associated outcomes through enrichment analysis and KEGG pathway coloration.

Expression-Centric Integrated Analysis

Operating at the expression level, this approach involves the joint analysis of differential expression data for proteins and metabolites. The objective is to pinpoint entities that exhibit synchronized patterns of variation. Complementing this analysis are visualization techniques such as correlation coefficient matrices, clustering heatmaps for correlation analysis, and regulatory network diagrams based on correlation coefficients, enabling personalized insights into the relationship dynamics.

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Summary of data integration workflow combining proteomics and metabolomics data for a comprehensive understanding of the biochemical alterations of pathogenic drug resistant bacteria (Fortuin et al., 2022).

Application of Joint Proteomic and Metabolomic Analysis

Application 1: Unraveling Molecular Characteristics of Spontaneous Type 2 Diabetes Mellitus (T2DM) in Chinese Hamsters

The study focuses on unraveling the molecular characteristics of spontaneous Type 2 Diabetes Mellitus (T2DM) in Chinese hamsters, utilizing the powerful integrated approach of proteomic and metabolomic analysis. T2DM is a metabolic disorder characterized by high blood sugar levels, often resulting from defects in insulin secretion, insulin resistance (IR), or a combination of both. Chinese hamsters, presenting a unique non-obese animal model for spontaneous T2DM, offer a valuable opportunity to delve into the molecular intricacies of diabetes pathogenesis.

Integrated Proteomic and Metabolomic Analysis: The researchers employed a sophisticated combination of small intestine proteomic analysis and serum metabolomic analysis, utilizing liquid chromatography-tandem mass spectrometry (LC-MS/MS) and gas chromatography-time-of-flight mass spectrometry (GC-TOF/MS). This comprehensive approach allowed the identification of 213 differential proteins and 14 differential metabolites in Chinese hamsters with T2DM. The integration of these datasets provided a holistic understanding of the molecular characteristics associated with diabetes.

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Bioinformatics analysis of the differentially expressed proteins revealed their association with various aspects of metabolism, including lipid metabolism abnormalities, insulin resistance, impaired insulin secretion, amino acid metabolism disorders, and inflammation. These findings provide critical insights into the molecular underpinnings of T2DM in Chinese hamsters. The integrated approach not only identified individual molecular components but also highlighted the interconnectedness of these components in the context of diabetes.

The integrated proteomic and metabolomic analysis sheds new light on the T2DM model in Chinese hamsters, offering a molecular perspective on the disease. This information is crucial for understanding the pathogenesis and molecular mechanisms underlying diabetes. The study opens new avenues for exploring potential therapeutic targets and interventions for T2DM, providing researchers and clinicians with valuable insights that can contribute to the development of more effective treatment strategies.

Application 2: Exploring Taxol Biosynthesis in Taxus media Stem Bark

Taxol, a potent anticancer compound, is naturally produced by certain plants, including Taxus species. Taxus media, commonly known as the Chinese yew, is a valuable source of taxol. However, the detailed understanding of taxol biosynthesis, especially in specific stem tissues, has remained elusive. The integration of proteomic and metabolomic approaches provides a comprehensive strategy to decipher the complex biochemical pathways involved in taxol production.

To unravel the intricacies of taxol biosynthesis, researchers employed integrated metabolomic and proteomic methods on cultivated Taxus media stem tissues. This involved utilizing advanced analytical techniques such as liquid chromatography-tandem mass spectrometry (LC-MS/MS) and gas chromatography-time-of-flight mass spectrometry (GC-TOF/MS). The integration of these techniques allowed for a detailed examination of both the chemical composition and protein profile of the stem tissues.

The integrated approach revealed tissue-specific differences in metabolite accumulation within the stem tissues of Taxus media. This information is crucial for understanding where and how taxol biosynthesis occurs. The findings indicated that the cambium layer, a specific tissue in the stem, showed significant accumulation of taxol. This knowledge not only enhances our understanding of taxol distribution within the plant but also provides insights into the potential biotechnological applications of different stem tissues.

Integrated proteomic and metabolomic analysis enabled the identification of ten key enzymes involved in taxol biosynthesis, with the majority being predominantly produced in the cambium layer. Furthermore, the study elucidated the role of a specific transcription factor, TmMYB3, in the transcriptional regulation of genes associated with taxol biosynthesis. This integrated approach not only mapped out the biosynthetic pathway but also provided insights into the regulatory mechanisms governing taxol production in Taxus media.

The discovery of tissue-specific taxol accumulation and the identification of key enzymes and regulatory factors open avenues for exploiting the biotechnological potential of Taxus media. Understanding the biosynthetic processes in specific stem tissues can inform strategies for enhancing taxol production or developing alternative approaches for sustainable taxol extraction.

Application 3: Molecular Insights into COVID-19 in Children through Plasma Proteomics and Metabolomics

The 2019 coronavirus disease (COVID-19) pandemic, caused by the novel coronavirus, has emerged as a rare public health crisis. Researchers conducted plasma proteomic and metabolomic analyses on blood samples from healthy children and those infected with COVID-19 to identify molecular changes specific to COVID-19 in children. Comparative analysis with adult multi-omics data identified 44 proteins and 249 metabolites with differential changes in COVID-19 children compared to healthy children or COVID-19 adults. Further analysis revealed significant induction of deteriorative immune response/inflammation processes and protective antioxidant or anti-inflammatory processes in COVID-19 children. Prioritization using integrated biomarker models accurately distinguished COVID-19 children from healthy children or COVID-19 adults. Experimental validation confirmed the upregulation of all five prioritized proteins after coronavirus infection. Interestingly, prioritized metabolites suppressed the expression of pro-inflammatory factors, and two metabolites, methylmalonic acid (MMA) and mannitol, inhibited coronavirus replication, suggesting their protective role in COVID-19 children. This study provides new insights into the mechanisms and pathogenesis of mild symptoms in children with COVID-19, with dynamically altered metabolites identified as potential therapeutic agents.

Reference

Fortuin, Suereta, and Nelson C. Soares. "The integration of proteomics and metabolomics data paving the way for a better understanding of the mechanisms underlying microbial acquired drug resistance." Frontiers in Medicine 9 (2022): 849838.

* For Research Use Only. Not for use in diagnostic procedures.

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