Proteomics is ideally suited for investigating disease pathogenesis and biomarker discovery because it gives a functional snapshot of the operations of a cell or tissue under specific conditions. Unlike molecular-based approaches such as genome sequencing or transcriptome analysis, characterizing the proteome gives researchers the opportunity to discover unique biomarkers of disease and to develop novel therapeutics at the pathway level. In the field of oncology, because most chemotherapeutics act at the protein level, proteomics is a key tool in the fight against cancer.
However, researchers must analyze a large number of samples to characterize a disease proteome and generate powerful, statistically valid results. Although mass spectrometry (MS)-based proteomics leads the field in protein chemistry, the major obstacle to progress is slow processing speeds. In this interactive Web seminar, Harvard Medical School’s Wilhelm Haas explains how multiplexed protein quantitation has accelerated research on breast cancer as a high-coverage/high-throughput solution for proteome characterization. Dr. Haas explains the basic technology behind isobaric labeling and multiplexing, before showing the technique in action.
Working with tandem mass tag (TMT) technology (Thermo Scientific), researchers expanded the number of samples analyzed from six to ten per MS run (6-plex to 10-plex) by exploiting the small mass differences between isotopes 13C and 15N used in the construction of the TMTs. Even though the differences in mass are tiny, they can be detected easily on high-resolution mass spectrometers such as the Orbitrap Fusion Tribrid mass spectrometer (Thermo Scientific).
In addition to rewiring the architecture of the TMT reagents, researchers also compensated for the increase in contaminant ions seen with the two MS fragmentation steps (MS1 and MS2) used for traditional TMT multiplexed quantitation. Contaminant ions arise during MS2 fragmentation and cause loss of accuracy and intensity distortion, ultimately skewing reported ratios and introducing quantitation errors. Although each extra step reduces sensitivity by decreasing ion charges, by adding MS3 fragmentation that focuses on high-intensity TMT ions only, the researchers found they could improve accuracy and validity of the obtained results. Furthermore, they boosted sensitivity in the Orbitrap Fusion Tribrid mass spectrometer by co-isolating all fragment ions with a multi-notch waveform that reduced interference.
Having developed and confirmed the validity of the experimental protocol, Haas then described the application of synchronous precursor ion selection and 10-plexed proteomics for large-scale mapping, to characterize 34 breast cancer cell line proteomes.
The research team analyzed each cell line in duplicate, resulting in a total of 68 samples for characterization. Picking eight samples at random, the researchers labeled each one with a different 10-plex TMT for MS analysis. They used the remaining two available TMTs to label a pooled sample comprising all 68 duplicates. The pooled labeled samples were then added as two standards to each group of eight, thus creating a 10-plex sampling group. Following basic pH reverse-phase chromatography, the 12 fractions from each sample in each group were analyzed together in a single MS run (i.e., nine 10-plex experiments). The presence of the standard pooled pairs acted as a bridge between the nine different runs needed to characterize all 68 samples, allowing for accurate comparison of TMT ion intensities across the series.
Over 7,800 proteins were identified in each of the nine 10-plex experiments, with a total of 10,752 proteins identified in all. Each sample (12 fractions) took three hours to run, and the total analysis time taken was 13.5 days.
Across the experiments, reproducibility was tight: an average of 8,258 proteins were identified in each cell line. The median overall Pearson correlation was 0.83 and the pairwise replicates showed a very tight spread of values among assays.
When examined, the researchers found that their proteomic data clustered strongly along traditional breast cancer characterization categories according to receptor status and hormone sensitivity. They also, however, found discordant results, which upon closer examination reflected individual cell line response to various chemotherapeutic agents. From their proteomics data and published sensitivity reports, the team was able to construct a drug biomarker network that could be used to predict therapeutic success.
Drawing the workshop to a close and in response to questions from attendees, Dr. Haas estimated running costs of approximately $200 per proteome (reagents and MS run time) and a false discovery rate of less than 1%. He also revealed that it took approximately 4.5 hours to complete a comprehensive proteome map for each sample.
In summary, Dr. Haas proposed that TMT multiplexed protein quantitation with synchronous precursor selection and the MS3 fragmentation step in Orbitrap technology gives a high-throughput tool suitable for accurately and efficiently studying the proteomics of complex diseases.
Further Resources
- Access the interactive workshop by signing up here: http://view6.workcast.net/register?pak=9635235670412211
- Learn about Thermo Scientific’s TMT protocols here: http://www.piercenet.com/product/amine-reactive-10-plex-tandem-mass-tag-reagents
- Read about increasing the range of TMT multiplexing capacity: McAlister, G.C., et al. (2012) “Increasing the multiplexing capacity of TMT using reporter ion isotopologues with isobaric masses,” Analytical Chemistry, 84 (pp. 7469–78), doi: 10.1021/ac301572t.
Post Author: Amanda Maxwell. Mixed media artist; blogger and social media communicator; clinical scientist and writer.
A digital space explorer, engaging readers by translating complex theories and subjects creatively into everyday language.
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