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Lipidomics，as an critical branch of metabolomics can effective reveal the relationship between lipid metabolism and life activities. Proteomes are all the proteins expressed by a organism. Proteomics is the science that analyzes the composition of proteins and their activity patterns in an organism, tissue or cell at the overall level. Changes in protein content play an important role in the growth of an organism, environmental stress, disease development and other processes.
The integrated analysis of proteomics and lipidomics can establishes the relationship between data at different levels of molecules. At the same time, combined with functional analysis, metabolic pathway enrichment, molecular interactions and other biofunctional analyses, it will offer researchers more systematically and comprehensively analyze the functions and regulatory mechanisms of biomolecules, and screen the key biological pathways or genes, lipid metabolites and proteases, etc., so as to ultimately achieve a comprehensive understanding of the general trend and direction of biological changes, and then put forward the model of the mechanism of change in molecular biology, which will promote the in-depth analysis and application of the subsequent research and application.
Creative Proteomics has rich experience in multi-omics integrated analysis. We use advanced detection and analysis software to provide customers with customized detection and analysis services, to maximize to meet the diversified needs of customers' detection. At the same time, we provide customers with customized bioinformatics analysis services, one-stop provision of integrated analysis of lipidomics and proteomics, to help customers to promote the progress of project research. We also provide customized bioinformatics analysis services and one-stop integrated lipidomics and proteomics analysis services to help our clients advance their research projects.
Integrated analysis of lipidomic and proteomic data into the assembly pathway of TAGs. (Liu H, et al. 2020)
What are the main analyses we provide?
- Multivariate statistical integration analysis of the proteome and lipidome.
- WGCNA analysis.
- Proteome-lipome correlation analysis.
- Proteome-lipome PCA comparative analysis.
Applications of integrated proteomics and lipidomics analysis
- Agricultural research. Mechanisms of plant stress resistance, plant growth and development mechanisms, crop breeding for conservation, etc.
- Animal research. Meat and milk quality research, pathogenesis research, etc.
- Biomedical research. Clinical diagnosis, biomarkers, disease mechanism, disease typing, targeted therapy, etc.
- Pharmaceutical Research. Drug action mechanism, efficacy evaluation, drug development, etc.
- Microbiology Research. Pathogenesis, drug resistance mechanism, pathogen-host interaction, etc.
- Food Nutrition. Optimization of food storage and processing conditions, identification of food components and quality, functional food development, food safety monitoring and testing.
Advantages of integrated proteomics and lipidomics analysis
- Integrates different levels of biological information. Proteomics focuses on protein expression, modification and interactions, while lipidomics focuses on lipid molecules composition and metabolism. Combined analysis can provide information at both protein and lipid levels, leading to a more comprehensive understanding of biological systems' functions and regulatory mechanisms.
- Provide complementary information. Through integrated analysis, the interrelationships between proteins and lipids, such as protein-lipid interactions and lipid-protein modifications, can be revealed, leading to a better understanding of their functions in biological processes.
- Improve biomarker discovery. Integrative analysis can provide more information and identify key markers missed by individual histological approaches. This can improve biomarker discovery rates and accuracy.
- Enhanced understanding of disease mechanisms. Integrated analysis can reveal the interactions and regulatory mechanisms of proteins and lipids during disease development, and provide deeper insights into disease diagnosis and treatment.
- Supporting individualized medicine. The combined analysis of proteins and lipids in individual samples can provide insights into differences between individuals. This can establish the basis for personalized diagnosis and treatment.
What do we offer?
Creative Proteomics will provide you with a detailed technical report on the following.
- Experimental steps.
- Relevant experimental parameters.
- Mass spectrometry images.
- Raw data.
- Results of lipidomics and proteomics analyses
Our service workflow
- Liu H,Hong Y,Lu Q, et al. Integrated Analysis of Comparative Lipidomics and Proteomics Reveals the Dynamic Changes of Lipid Molecular Species in High-Oleic Acid Peanut Seed. J Agric Food Chem. 2020;68 (1):426-438.
Integrated Lipidomics and Proteomics Point to Early Blood-Based Changes in Childhood Preceding Later Development of Psychotic Experiences: Evidence From the Avon Longitudinal Study of Parents and Children
Journal: Biol Psychiatry
Identifying early biomarkers of psychotic experiences (PE) is of interest because early diagnosis and treatment of individuals at risk for future illness is associated with improved outcomes. In this study, the authors investigated early lipidomic and coagulation pathway protein profiles of late-stage PE in subjects from the Avon Longitudinal Study of Parents and Children cohort through an integrated and targeted lipidomic and semi-targeted proteomic approach. Used to help investigators identify and treat subjects with psychiatric disorders (both psychotic and affective) early and significantly improve their clinical outcomes.
Integrated lipidomic and proteomic analyses revealed that coagulation and complement pathway proteins are closely related functionally. The authors included complement protein levels from the total dataset with available data in the integrated lipid and protein analysis. The regularized canonical correlation analysis revealed that 17 lipids have a positive correlation with six proteins (PLG, heparin cofactor 2, complement C2, complement factor H, clusterin, and vitronectin), which exceeded a similarity score higher than 0.3. The coagulation protein PLG, the heparin cofactor 2, and the complement pathway protein blebbins were strongly and positively correlated with 16 lipids (Figure 1).
The KODAMA algorithm was applied to all individuals with available clinical data ( n = 90) in order for the authors to detect potential metabolic phenotypes present in the study population. Thereafter, the KODAMA scores were partitioned around centroid clustering to identify potentially similar phenotypes in this study population. Four distinct clusters were identified based on the highest profile median, named A, B, C, and D. The incidence of PE was significantly different between clusters ( p = .007) (Figure 2).
The findings that the lipidome and proteome of subjects reporting PE at 18 years of age were altered by 12 years of age suggest that metabolic dysregulation may contribute to early susceptibility to PE and suggest crosstalk between these lysophosphatidylcholine, phosphatidylcholine, and coagulation and complement proteins.
- Madrid-Gambin F, Föcking M, Sabherwal S, et al. Integrated Lipidomics and Proteomics Point to Early Blood-Based Changes in Childhood Preceding Later Development of Psychotic Experiences: Evidence From the Avon Longitudinal Study of Parents and Children. Biol Psychiatry. 2019 Jul 1;86(1):25-34.