Single-Cell Proteomics: Unveiling Biological Heterogeneity

EasyChair Preprint 12386

Abstract

Single-cell proteomics has emerged as a powerful tool for investigating the complex and dynamic nature of biological systems. It enables the comprehensive analysis of proteins within individual cells, allowing researchers to uncover cellular heterogeneity and understand the underlying molecular mechanisms that drive diverse biological processes. This abstract highlights the significance of single-cell proteomics in capturing the intricacies of biological heterogeneity.

Traditional bulk proteomic approaches provide valuable insights into the average protein expression levels within a population of cells. However, they fail to capture the inherent diversity that exists between individual cells. Single-cell proteomics, on the other hand, enables the characterization of protein expression patterns at the single-cell level, unraveling the heterogeneity that arises from cellular diversity, stochastic gene expression, and microenvironmental influences.

The advent of cutting-edge technologies such as mass spectrometry-based approaches, microfluidics, and high-throughput single-cell isolation techniques has propelled the field of single-cell proteomics. These advancements have facilitated the identification and quantification of thousands of proteins within individual cells, paving the way for in-depth investigations into cellular heterogeneity.

By analyzing the protein expression profiles of single cells, researchers can elucidate cellular subtypes, identify rare cell populations, and uncover dynamic changes in protein expression during cellular development, disease progression, and response to therapeutic interventions. Furthermore, single-cell proteomics allows the study of cellular signaling pathways, protein-protein interactions, post-translational modifications, and spatial organization within individual cells.

Keyphrases: Healthcare, environment, proteins

@booklet{EasyChair:12386,
  author    = {Favour Olaoye and Kaledio Potter},
  title     = {Single-Cell Proteomics: Unveiling Biological Heterogeneity},
  howpublished = {EasyChair Preprint 12386},
  year      = {EasyChair, 2024}}