Melvin's digital garden

Shotgun proteonomics

CREATED: 200808140219 Speaker: Christian von Mering

** Proteonomics workflow

peptide sequencing

identify proteins

spectral counting

abundance levels

  • About 50% of proteins are detected in current workflow
  • Detailed qualitative characterization of proteins not identified in C. elegans
  • Improved genome annotation (new start site, alternative splicing)

** Spectral counting: quantitative information of protein abundance

  • convectional methods relay on peptide labeling, measure relative changes
  • spectral counting: directly from shotgun data, no need for peptide labels
  • problem: not all peptides are produced at cleavage points, not all peptides are detected by the machine
  • very short/long peptides are not observed
  • $a = (\sum_i count(p_i) \times length(p_i))/(\sum_j length(q_j) \times f(q_j))$
  • p = identified peptides, q = tryptic peptides, f(q) = peptide length correction factor
  • comparison of worm with yeast
  • genes which are part of operons in C. elegans are more abundant and more easily detected
  • operons are probably not cause for abundance, because orthologous genes in fly are also more abundant

** Comparative analysis

  • orthologous protein pairs in worm and fly
  • correlation of 0.79 between abundance of orthologs in worm and fly (2691 pairs of orthologs)
  • breakdown of correlation of abundance levels according to functional categories
  • protein abundance have better correlation compared to comparison of transcript abundance => mRNA can drift
  • protein vs transcript within an organism

** Future work

  • multiple species
  • protein networks
  • comparative approach to PTM

Links to this note