Deciphering the single-cell omic: innovative application for translational medicine

Expert Rev Proteomics. 2012 Dec;9(6):635-48. doi: 10.1586/epr.12.61.

Abstract

Traditional technologies to investigate system biology are limited by the detection of parameters resulting from the averages of large populations of cells, missing cells produced in small numbers, and attempting to uniform the heterogeneity. The advent of proteomics and genomics at a single-cell level has set the basis for an outstanding improvement in analytical technology and data acquisition. It has been well demonstrated that cellular heterogeneity is closely related to numerous stochastic transcriptional events leading to variations in patterns of expression among single genetically identical cells. The new-generation technology of single-cell analysis is able to better characterize a cell's population, identifying and differentiating outlier cells, in order to provide both a single-cell experiment and a corresponding bulk measurement, through the identification, quantification and characterization of all system biology aspects (genomics, transcriptomics, proteomics, metabolomics, degradomics and fluxomics). The movement of omics into single-cell analysis represents a significant and outstanding shift.

Publication types

  • Review

MeSH terms

  • Animals
  • Genome
  • Humans
  • Metabolomics
  • Neoplasms
  • Proteomics
  • Single-Cell Analysis*
  • Stem Cell Research
  • Stochastic Processes
  • Systems Biology
  • Transcriptome
  • Translational Medical Research*