Proteomics Core Lab

Committee members:

Institute of Plant and Microbial Biology

Assistant Research Specialist:

Research Assistant:

  • Chin-Wen Chen
  • Ying-Mi Lai
  • Pei-Yi Lin

Contact phone number:

  • 02-27871157 (Chuan-Chih)
  • 02-27871030 (Lab)



  • A227, Agricultural Technology Building

Global proteomic quantification

Protein identification is only part of puzzle, and modern proteomics emphasizes the expression profiles of identified proteins to gain the whole view of proteomic chances. Quantitative proteomics allows to identify the significantly regulated proteins and post-translational modifications between different biological samples on a proteome-wide scale. A variety of quantitative approaches can be utilized to compare the protein levels among samples.  

Label free quantification

Label free quantification (LFQ) has two main strategies: spectral counting quantification and peptide MS1 peak intensity-based strategy for a specific peptide in different samples.  Spectral counting is based on MS2 scan, which counts the number of identified MS/MS spectra for a given peptide. The proteomic software then integrates the results for all measured peptides of the proteins that are quantified.  On the other hand, LFQ is also available using precursor ion intensity. In this strategy, a peptide is identified using MS/MS first and then subsequently peak area of the peptide is extracted. Precursor ion intensity is assumed to be correlated with the actual peptide abundance, and the intensities are summed and normalized to quantify the relative protein amount. However, due to the stochastic nature of data-dependent acquisition (DDA) for MS/MS analysis, not all the peptides are sampling in all the runs. This leads to generate missing quantitative values which are difficult to perform statistical analysis. To address the issue of missing values, match between run (MBR) approach has been developed to align the MS1 peak without MS2 information with the corresponding peak which has MS/MS information, improving the depth of experimental coverage. The problem of LFQ is that the interference of MS1 peaks due to high dynamic range and complexity of the proteome. We suggest to select potential candidates for targeted PRM analysis to further validate the LFQ result before you perform any genome-editing experiments.

Isobaric labeling-based quantification

Two Isobaric labeling reagents are widely used: TMT (tandem mass tag) and iTRAQ (isobaric tags for relative and absolute quantification). These tags are isobaric in nature, meaning that they have the same molecular mass in MS1 peak. After MS/MS analysis, the fragmented precursor ion releases reporter ions which are utilized for quantification. Isobaric tags provide multiplexing capabilities and without the problem of missing values representing in LFQ approach; currently we support TMT 6- and 10-plex, as well as iTRAQ 4- and 8-plex. These tags are labeled at peptide level and therefore are applicable to almost all experimental scenarios. Please discuss with us details including maximizing proteome depth, co-isolation impurities and kit preferences and purchases.

The isobaric labeling services include:

  • Enzymatic digestion (trypsin or other proteases available)
  • Isobaric labeling (TMT or iTRAQ reagent)
  • Peptide purification and concentration (C18 desalting)
  • Peptide fractionation (SCX or high pH RP)
  • A quality control run (digested BSA or Hela cells)
  • LC-MS/MS analysis (DDA mode)
  • Database search and reporter ion quantification (Proteome Discoverer and Mascot)
  • Results returned via Excel file