Quantitative Proteomics: The Difference a Generation Makes

In consideration of the American Society of Mass Spectrometry annual conference in Indianapolis in early June, we thought a historical case study to showcase, not only cutting-edge technology, but the technological leaps that have advanced research over time, would be appropriate.

The proteome

The concept and the term "Proteome" is nothing new to us, and in fact has been eclipsed by emerging terms such as "Microbiome". Nonetheless, proteomic research has forged a strong and important place in the biomedical sciences, spawning fields such as systems biology and motivating technological advances across a wide spectrum of instrumentation. Perhaps the most visible and prolific beneficiary has been the field of mass spectrometry, and the tools and systems associated with this powerful technology.


Many moons ago, genome projects aimed at identifying the complete collection of genes in humans, as well as model research organisms, were in varying levels of completion. The budding yeast Saccharomyces cerevisiae was sequenced in the mid-90's, adding significant value in identifying the sequence and traits of the entire collection of yeast proteins known at that time. The YPD (or Yeast Protein Database) was an essential data repository of protein information curated from the expanse of research and publications available.

Around that time, I performed research with a start-up company name Proteome Inc., aimed at developing advanced techniques towards protein identification and characterization. In 1997, we published a paper entitled "Proteome studies of Saccharomyces cerevisiae: Identification and characterization of abundant proteins" which used advanced 2-dimensional gel electrophoresis, amino acid analysis, various genetic tools, and the Yeast Protein Database in identifying 169 spots indicative of proteins (the most to date) arising from differing cell culture conditions.

Advanced quantitative proteomics

Fast forward 20 years and former colleagues of mine publish a paper entitled, "Quantitative mass spectrometry-based multiplexing compares the abundance of 5000 S. cerevisiae proteins across 10 carbon sources". In this paper, the authors used a TMT10-plex strategy to study multiple growth conditions in a single experiment. Use of the SPS-MS3 method on an Orbitrap Fusion Lumos mass spectrometer enabled the quantification of over 5000 yeast proteins across ten carbon sources at a 1% protein-level false discovery rate (FDR). 5000 proteins is the highest to date and includes both qualitative and quantitative information. This speaks volumes to the creativity and intelligence of, not only the scientists performing the research, but to the advances that have been made over the years in mass spectrometry instrumentation.

TMT isobaric labelling technology for proteome-wide quantitation

The SPS-MS3 TMT10-plex analysis workflow is a complete system offered by ThermoFisher. The synchronous precursor selection (SPS)-based MS3 technology on the Orbitrap Fusion Lumos Tribrid systems enables a unique capability to accurately measure very subtle changes in low-abundance proteins. The workflow allows for simultaneous quantitative analysis of ten samples, with improved accuracy achieved by reducing the co-isolation of tagged interferences. The increased sensitivity and ion transmission boosts the number of quantifiable peptides present at low levels, enabling fast, accurate, and more comprehensive proteome-wide quantitation.

What is isobaric chemical tagging?

Isobaric chemical tagging is a fast, unbiased, and sensitive method to quantify almost all proteins in a simultaneous analysis. Traditional TMT experiments involved the isolation of precursor ions and generation of peptide fragment and TMT reporter ions in a single spectrum, producing MS/MS data that enabled peptide identification and relative quantitation.

What are limitations of isobaric labelling?

The quantitative accuracy of this approach is highly dependent on the purity of the precursor ions that are selected for MS/MS analysis. However, the reality is that when dealing with complex digests, even rigorous pre-fractionation and subsequent reversed-phase liquid chromatography separation steps fail to remove all co-eluting isobaric species. The result is these interfering species are co-isolated and co-fragmented with the ions of interest. The reporter ions generated from fragmentation of these species are indistinguishable from the reporter ions from the selected parent fragment, and thereby contribute to a loss of quantitative accuracy and precision. This leads to loss of information, results in misinterpretation of true fold changes, and leads to the unpredictable loss of quantitative values.

What is Synchronous Precursor Selection (SPS)?

Synchronous precursor selection (SPS) for MS3 is a novel method designed to overcome the problem of isobaric ion contamination and to restore quantitative accuracy and precision while preventing loss of sensitivity. The SPS method begins with selection of the parent ion in the MS scan, followed by its isolation in the quadrupole and fragmentation by collisionally induced dissociation (CID) in the ion trap.

Following fragmentation, SPS enables simultaneous isolation of up to 20 MS2 fragment ions. A select group of MS2 fragment ions are then transferred back into the ion routing multipole (IRM) where they undergo higher energy collisional dissociation (HCD) fragmentation, with the MS3 fragments then detected in the Orbitrap analyzer. The use of SPS dramatically increases the reporter ion signal intensity and improves the ratio accuracy, due to improved counting statistics, leading to a significant increase in the number of quantified peptides.

Outlook for the quantitative proteomics field

The pace of research and technological innovation go hand-in-hand, and it's impressive to observe this up close and personal. Perhaps a takeaway here is to be vigilant in staying current with cutting edge research while keeping aware of new technologies. Mass Spectrometry and quantitative proteomics are constantly evolving sciences.

Revised August 2019