Important Proteomics Datasets for Human Biology and Disease Research

Proteomics datasets are essential tools for understanding the complex molecular mechanisms that underpin human biology and disease. They provide a comprehensive view of protein expression across various tissues and conditions, enabling researchers to decipher cellular processes, identify potential biomarkers, and develop targeted therapies. In this blog, we highlight two significant proteomics datasets that contribute to these efforts: PXD008934, which focuses on proteomic changes in cardiomyocytes from human heart failure, and PXD010154, which presents a comprehensive proteome and transcriptome analysis across 29 healthy human tissues. Together, these datasets provide critical insights into tissue-specific protein expression, disease mechanisms, and potential therapeutic targets, driving forward our understanding of both normal human biology and pathological conditions.

Dataset 1

Dataset ID: PXD008934
Year of Publication: 2018
Disease: Heart Failure
Experiment Type: Comparative Proteomics Analysis
Total samples: 16 human heart samples (8 failing and 8 non-failing hearts)
Organism: Homo sapiens
Reference Link: Publication

Dataset 1: PXD008934 - Proteomic Changes in Cardiomyocytes from Human Heart Failure

Why This Dataset Matters for the Scientific Community?

The PXD008934 dataset is a significant resource for advancing our understanding of the molecular mechanisms underlying heart failure. This study utilized left ventricular (LV) myocardium from 105 non-failing (NF) and failing human hearts.

It provides an in-depth proteomic analysis of human left ventricular tissue from non-failing and failing hearts, focusing on the changes in the cytoskeletal proteins and their impact on cardiomyocyte function. By identifying over 3,700 proteins and examining how specific proteins, such as microtubule-associated proteins and intermediate filaments, are upregulated and stabilized in heart failure, this dataset sheds light on the pathophysiological changes that occur at the molecular level. This comprehensive proteomic data is crucial for researchers aiming to develop new therapeutic strategies that target the cytoskeleton to improve cardiac function in heart failure patients.

Decoding Impacts:

• Upregulation of Cytoskeletal Proteins:
  • Significant increases in the levels of cytoskeletal proteins such as microtubules (MTs) and intermediate filaments (IFs) were observed in failing hearts, highlighting a potential therapeutic target.
• Proteomic Profiling Across Heart Failure Types:
  • The study identified distinct proteomic profiles for different types of heart failure, such as ischemic cardiomyopathy (ICM) and dilated cardiomyopathy (DCM), which could aid in understanding disease-specific mechanisms.

• Post-Translational Modifications and Microtubule Behavior:
  • Changes in post-translational modifications, like detyrosination of microtubules, were found to affect the mechanical properties of cardiomyocytes, potentially contributing to impaired contractility in heart failure.
• Impact on Myocyte Mechanics:
  • Detyrosinated MTs increase the viscoelastic resistance of failing myocytes, and their suppression through pharmacological or genetic methods significantly improves contractility and stiffness, suggesting new therapeutic avenues.
• Correlation with Heart Function Parameters:
  • The dataset connects proteomic changes with functional parameters such as ejection fraction and myocardial stiffness, offering insights into how molecular alterations translate to clinical symptoms.

Insights into Heart Failure:

• Structural Remodeling in Failing Hearts:
  • The dataset reveals that heart failure is characterized by substantial cytoskeletal remodeling, with upregulation of proteins like MAP4 and detyrosinated tubulin, which are involved in stabilizing microtubules and affecting cardiomyocyte contraction.
• Potential Therapeutic Targets:
  • Targeting detyrosinated microtubules presents a novel therapeutic strategy for improving cardiac function without the adverse effects associated with traditional inotropes that increase metabolic demand.
• Understanding Mechanisms of Disease Progression:
  • The findings suggest that upregulated and stabilized cytoskeletal proteins may initially play a protective role but become maladaptive in chronic heart failure, contributing to impaired myocardial function.
• Genetic and Pharmacological Interventions:
  • Both genetic approaches (e.g., overexpression of tubulin tyrosine ligase) and pharmacological treatments (e.g., colchicine) demonstrated efficacy in modifying cytoskeletal components and improving contractile function, underscoring their therapeutic potential.

This dataset provides a comprehensive understanding of the proteomic landscape in heart failure, highlighting key molecular changes that could be targeted to develop novel therapies for improving heart function in patients with this debilitating condition.

Dataset 2

Dataset ID: PXD010154
Year of Publication: 2019
Disease: N/A (Healthy Human Tissues)
Experiment Type: Integrated Proteomics and Transcriptomics Analysis
Total Samples: 29 healthy human tissues
Organism: Homo sapiens
Reference Link: Publication

Dataset 2: PXD010154 - Comprehensive Proteome and Transcriptome Analysis of 29 Human Tissues

Why This Dataset Matters for the Scientific Community?

The PXD010154 dataset is an invaluable resource for researchers studying human biology and disease. This dataset provides a comprehensive proteome and transcriptome atlas of 29 healthy human tissues, offering unprecedented insights into the variability of protein and mRNA expression across different tissue types. The extensive profiling of over 13,640 proteins and 18,072 transcripts helps elucidate the fundamental mechanisms governing protein expression, stability, and function in normal human tissues. This data serves as a reference for understanding tissue-specific protein expression and can be leveraged for various applications, such as biomarker discovery, drug target validation, and understanding the proteogenomic landscape. The dataset is particularly significant because it addresses the gap in high-resolution, cross-tissue analyses that integrate both transcriptomic and proteomic data, facilitating a more holistic view of gene regulation and expression.

Decoding Impacts:

• Tissue-Specific Expression Profiles:
  • Identified 7,244 proteins and 7,866 transcripts with elevated expression in specific tissues, aiding in the study of tissue-specific biological processes and potential drug targets.
• Core Human Proteome:
  • Defined a "core proteome" with 5,400 proteins expressed across all tissues, providing a baseline for understanding essential cellular functions that are conserved across different tissue types.
• Mismatch Between mRNA and Protein Levels:
  • Revealed significant discrepancies between mRNA and protein abundances, highlighting the complexities of post-transcriptional regulation and the need for multi-omic approaches to fully understand gene expression.
• Proteogenomic Insights:
  • Identified 37 proteins with no prior evidence at the protein level, expanding our knowledge of the human proteome and highlighting the importance of integrating proteomics with genomics.
• Dynamic Range Differences:
  • Demonstrated that protein expression has a broader dynamic range compared to mRNA expression, suggesting that protein stability and synthesis rates play critical roles in cellular regulation.

• Alternative Translation Initiation Sites:
  • Discovered 344 peptides from alternative translation initiation sites (aTIS), providing insights into previously unannotated protein-coding regions and novel regulatory mechanisms.

Insights into Human Biology:

• Understanding Tissue-Specific Biology:
  • The dataset enables the identification of proteins and transcripts that are highly enriched in specific tissues, such as brain or testis, revealing insights into the molecular basis of tissue-specific functions and specialization.
• Regulation of Protein Expression:
  • By comparing protein and transcript abundances, the dataset highlights the importance of post-transcriptional and translational control mechanisms that determine protein levels in different tissues, which can inform studies on protein degradation, translation efficiency, and post-translational modifications.
• Implications for Disease Research and Drug Discovery:
  • The data can be used to assess the expression of drug targets across multiple tissues, helping to predict potential side effects and off-target activities, thereby aiding in the development of safer and more effective therapeutics

• Novel Insights into Proteogenomics:
  • The dataset provides a rich source of data for identifying novel protein isoforms, single amino acid variants, and previously unknown proteins, enhancing our understanding of the functional complexity of the human proteome and contributing to efforts in personalized medicine.

This dataset serves as a foundational resource for exploring human tissue biology at the molecular level and has significant implications for advancing research in genetics, molecular biology, drug development, and precision medicine.

Conclusion: The Path Forward

PXD008934 reveals key proteomic changes in cardiomyocytes associated with heart failure, highlighting potential therapeutic targets for improving cardiac function. Meanwhile, PXD010154 presents an extensive proteome and transcriptome atlas of 29 healthy human tissues, emphasizing the complexity of protein expression regulation and its tissue-specific variability. Together, these datasets enhance our understanding of the molecular landscape in health and disease, driving forward discoveries in personalized medicine and targeted therapies.

By leveraging these datasets, researchers can better understand cellular processes, identify potential biomarkers, and develop targeted therapies. As proteomics continues to evolve, such comprehensive datasets will be essential in driving precision medicine and advancing scientific discovery.

Connect with us to explore how Elucidata can expedite your research journey or reach us at [email protected] to learn more.