Multiomics
Proteomics Research
Add granularity to proteomics data with metabolomics
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Metabolomics in Proteomics Research
Proteins are the workhorses of our cells, performing a vast array of essential functions. From providing structural support to catalyzing chemical reactions, proteins are involved in virtually every biological process. These complex molecules are made up of chains of amino acids, folded into intricate three-dimensional structures that determine their specific roles within our bodies.
Proteomics is the large-scale study of proteins, encompassing their structures, functions, and interactions within a biological system. Despite the plethora of information elucidated from the proteome, biological processes cannot be completely understood from this system alone.
Metabolites (i.e., biochemicals) are the small molecule reactants, intermediates, and products of metabolism. Unlike proteins, which are situated at an intermediate step in the central dogma of biology, metabolites usually constitute the final stage of biological processes, making them reflectors of the combined inputs from the genome, proteome, microbiome, and environment. Thus, using metabolomics to evaluate the metabolome alongside the proteome is beneficial for numerous types of studies including, but not limited to, characterizing mechanisms of disease onset and progression, evaluating the therapeutic response, and elucidating various facets of non-human biology.
Gain Additional Insight from Proteomics data Using Metabolomics
To fully understand cellular processes, the “whole set” of interacting components in an organism must be evaluated through an integrative multiomics approach. As the key drivers of metabolism, metabolites regulate protein post-translational modifications, which regulate enzymes, and these enzymes regulate metabolites through feedback loops. Given their interconnectivity, evaluating singular sets of molecules limits scientific discovery. Here, we discuss several case studies that show the benefit of evaluating metabolomics alongside proteomics.
Characterizing Mechanisms of Disease Pathology
Alzheimer’s disease is a heterogeneous condition that reflects a spectrum of neurodegenerative processes. Understanding these processes is essential to developing novel treatments and selecting the best precision therapies. The complementarity of proteomic and metabolomic data has the potential to reveal molecular dependencies that go beyond genetic or transcriptional regulation. The Alzheimer’s Disease Metabolomics Consortium (ADMC) demonstrated the combined use of metabolomics and proteomics to better understand the key role lipid mediators play in Alzheimer’s disease (AD). The ADMC performed untargeted metabolomics analysis on a cohort of AD patients and then used matched proteomics panels to probe interactions between neighboring levels of lipid mediators in the omics cascade. The findings revealed novel associations between cytochrome p450/soluble epoxide hydrolase metabolites, bile acids, and cerebrospinal fluid (CSF) proteins involved in glycolysis, coagulation, and vascular inflammation. These metabolic associations were not observed at the gene-co-expression level showing the importance of investigating pathway interactions with metabolomics, at the terminal part of the omic cascade.
Determining how Cancer Escapes Therapeutic Approaches
Renal cell carcinoma (RCC) is the most common type of kidney cancer in adults, accounting for about 90% of cases. Despite recent advances in treatment options, there remains a significant need for more effective therapies, particularly for advanced or metastatic RCC, as current treatments often lead to drug resistance and have limited long-term efficacy. . It is thought to progress through non-physiologic metabolic pathways owing to the unique proteomic changes associated with it. A study by Wettersten et al, 2015, combined tumor grade-dependent proteomics and metabolomics analyses to determine how metabolic reprogramming occurring in this disease allows it to escape today’s therapies. This extensive study s showed that glucose was metabolized to lactate, rather than used for aerobic respiration, at the expense of the tricarboxylic acid cycle and oxidative metabolism in general. The glutamine metabolism pathway inhibited reactive oxygen species, while the beta-oxidation pathway was also inhibited, leading to increased fatty acylcarnitines. Tryptophan catabolism associated with immune suppression was also highly represented in RCC compared to other metabolic pathways. Altogether, this study revealed novel findings about RCC biology that can serve as a springboard for important clinical advances. Furthermore, these data show that combining omics techniques can lead to synergism in knowledge. In this case, it elucidated concepts of grade-dependent tumor biology that would otherwise not be obvious using a single technique in isolation.
Wettersten H, et.al. Grade-Dependent Metabolic Reprogramming in Kidney Cancer Revealed by Combined Proteomics and Metabolomics Analysis. Tumor and Cell Biology. Jun 14, 2015. https://doi.org/10.1158/0008-5472.CAN-14-1703
Plant Biology
Metabolomics has significantly advanced our understanding of human health and disease. It should be noted however, that metabolomics has made an impact on non-human fields of biology. A study performed by Gene et.al. demonstrates this point. In plants, stomatal guard cells open and close in response to stimuli, which balances the uptake of water and carbon dioxide (CO2). Low levels of CO2 open stomatal cells, yet the mechanism(s) that regulate this process are poorly understood. To better characterize this process, Brassica napus guard cells were exposed to low CO2, then their metabolomes and proteomes were analyzed. Metabolites and proteins involved in fatty acid metabolism, starch and sucrose metabolism, and glycolysis and redox regulation changed significantly in response to low CO2. Multiple hormones that promote stomatal opening were also elevated, and interestingly, jasmonic acid precursors were diverted to a branch pathway of traumatic acid biosynthesis. Altogether, these findings suggest that the response of stomatal cells to low levels of CO2 is mediated by crosstalk between different phytohormones.
Geng, S et.al. Metabolomics and Proteomics of Brassica napus Guard Cells in Response to Low CO2. Front Mol Biosci. July 24, 2017.
Metabolomics Applications for Proteomics
- EBiomarker discovery
- EDisease phenotyping
- EValidation of proteomic findings
- ETherapeutic target identification and validation
- EPrecision medicine
- ECharacterizing disease mechanisms
- EStudying systems biology
- EMetabolic phenotyping
- EPathway analysis
“Integration of proteomics and metabolomics data is crucial to obtain biological insight for a correct hazard assessment. Furthermore, information achieved based on the knowledge of networks, processes, and pathways modified can be used to improve drug design or to identify specific biomarkers of toxicity.”
Gioria S, Lobo Vicente J, Barboro P, et al.
A combined proteomics and metabolomics approach to assess the effects of gold nanoparticles in vitro. Nanotoxicology. 2016;10(6):736-748. doi:10.3109/17435390.2015.1121412
Identifying Organ Injury Patterns in Trauma Patients
Severe traumatic injury with shock can lead to direct and indirect organ injury and is associated with significant morbidity. Even in cases with similar initial trauma conditions, the outcomes can vary, highlighting a need for more tissue-specific biomarkers to understand individual response to severe injury. One study attempted to identify useful diagnostic biomarkers by using proteomic and metabolomics databases to characterize patterns of organ injury after severe trauma.
Patients were classified according to outcome. Non-resolvers were defined as those who died less than 72 hours after injury or required 7 or more days of critical care while resolvers were defined as those who survived to 30 days and required less than 7 days of critical care. Individuals with low Injury Severity Scores served as controls. Untargeted metabolomics analysis was performed on plasma samples collected from patients upon arrival and 24 and 72 hours after admission to the trauma center. Metabolomics analysis, conducted with Metabolon, analyzed 898 metabolites to understand the changing levels of these metabolites across pathways of interest that helped to identify organ injury. Tissue-specific protein biomarkers were identified through a literature review and cross-referenced with tissue specificity from the Human Protein Atlas.
Figure 1. Network of correlated biomarkers. Cardiac markers identified by Somalogic, Fatty acid makers identified by Metabolon..
Results showed that a broad range of tissue-specific biomarkers of damage were present at admission and was greater in non-resolvers. By 72 hours specific cardiac, liver, neurologic, and pulmonary proteins remained significantly elevated in non-resolvers. Non-resolvers also had lower concentration of fatty acid metabolites relative to resolvers. Cardiac damage biomarkers had significant positive correlations with proinflammatory mediators and endothelial damage biomarkers. Altogether, these findings identified tissue-specific biomarkers with sustained elevation in patients at greater risk of succumbing to traumatic injury with shock.
This study demonstrates the value of utilizing an integrated approach as it can reveal multi-factorial mechanisms of disease to help improve overall intervention strategies and patient outcomes.
Li, Shimena et.al. High-dimensional proteomics identifies organ injury patterns associated with outcomes in human trauma. J Trauma Acute Care Surg. 2023 Jun 1;94(6):803-813.
Proteomics Publications and Citations
Metabolon has contributed extensively to multiomics publications.
Multiomics Knowledge Base
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