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Enabling more sophisticated proteomic profile analysis

Mass spectrometry (MS)-based proteomics is a powerful tool for profiling systems-wide protein expression changes. It can be applied for various purposes, e.g., biomarker discovery in diseases and study of drug responses. However, MS-based proteomics tend to have consistency (poor reproducibility and inter-sample agreement) and coverage (inability to detect the entire proteome) issues that need to be urgently addressed. The former implies that multiple analytical runs of the same sample under constant experimental conditions will result in the detection of different but overlapping sets of proteins. Intuitively, this means more LC-MS/MS runs are required to identify a sufficiently large portion of any proteome and is intricately linked to the second issue of inadequate proteome coverage.

Experimental methods to overcome these issues are technically challenging, resource heavy or place an unreasonable heavy dependency on the quality of the initial data set. These include exhaustive fractionation of samples, repeated MS runs of the same sample to reach saturation and compilation of MS data specific to a sample type generated and archived from different laboratories. The problems are particularly exemplified in a large-scale collaborative study to assess the extent of reproducibility across different laboratories. The results were striking: only 7 out of 27 laboratories correctly reported all 20 proteins, and only 1 laboratory successfully reported all 22 unique peptides. Therefore, alternative approaches are needed to complement existing experimental approaches to circumvent the stochastic sampling of peptides by MS and increase the comprehensiveness of proteome coverage.


Team members

  1. Wilson Goh
  2. Limsoon Wong
  3. Zhao Yaxing

Relevant publications

  1. Wilson Wen Bin Goh, Yie Hou Lee, Maxey Chung, Limsoon Wong. How advancement in biological network analysis methods empowers proteomics. Proteomics, 12(4–5):550–563, February 2012.
  2. Wilson Wen Bin Goh, Yie Hou Lee, Ramdzan Zubaidah, Jingjing Jin, Difeng Dong, Qingsong Lin, Maxey Chung, Limsoon Wong. A Network-based pipeline for analyzing MS data—An application towards liver cancer. Journal of Proteome Research, 10(5):2261–2272, May 2011.
  3. Wilson Wen Bin Goh, Yie Hou Lee, Zubaidah Ramdzan, Marek Sergot, Maxey Chung, Limsoon Wong. Proteomics Signature Profiling (PSP): A novel contextualization approach for cancer proteomics. Journal of Proteome Research, 11(3):1571–1581, March 2012. PDF
  4. Wilson Wen Bin Goh, Yie Hou Lee, Zubaidah M. Ramdzan, Maxey Chung, Limsoon Wong, Marek Sergot. A network-based maximum link approach towards MS identifies potentially important roles for undetected ARRB1/2 and ACTB in liver cancer progression. International Journal of Bioinformatics Research and Applications, 8(3/4):155–170, August 2012.
  5. Wilson Wen Bin Goh, Mengyuan Fan, Hong Sang Low, Marek Sergot, Limsoon Wong. Enhancing the utility of Proteomics Signature Profiling (PSP) with Pathway Derived Subnets (PDSs), performance analysis and specialised ontologies. BMC Genomics, 14:35, February 2013.
  6. Wilson Wen Bin Goh, Marek Sergot, Judy Sng, Limsoon Wong. Comparative network-based recovery analysis and proteomic profiling of neurological changes in valporic acid-treated mice. Journal of Proteome Research, 12(5):2116–2127, April 2013.
  7. Yie Hou Lee, Wilson Wen Bin Goh, Choon Keow Ng, Manfred Raida, Limsoon Wong, Qingsong Lin, Urs A. Boelsterli, Maxey Chung. Integrative toxicoproteomics implicates impaired mitochondrial glutathione import as off-target effect of troglitazone. Journal of Proteome Research, 12(6):2933–2945, May 2013.
  8. Wilson Wen Bin Goh, Limsoon Wong. Networks in proteomic analysis of cancer. Current Opinion in Biotechnology, 24(6):1122–1128, December 2013.
  9. Wilson Wen Bin Goh, Limsoon Wong, Judy Chia Ghee Sng. Contemporary network proteomics and its requirements. Biology, 3(1):22–38, December 2013.
  10. Wilson Wen Bin Goh, Limsoon Wong. Computational proteomics: Designing a comprehensive analytical strategy. Drug Discovery Today, 19(3):266-274, March 2014.
  11. Hirotaka Oikawa, Wilson Wen Bin Goh, Vania Lim, Limsoon Wong, Judy Sng. Valporic acid mediates BDNF through miR-124 by down-regulating a novel protein target, GNAI1. Neurochemistry International, 91:62–71, December 2015.
  12. Wilson Wen Bin Goh, Tiannan Guo, Ruedi Aebersold, Limsoon Wong. Quantitative proteomics signature profiling based on network contextualization. Biology Direct, 10:71. December 2015.
  13. Wilson Wen Bin Goh, Limsoon Wong. Design principles for clinical network-based proteomics. Drug Discovery Today, 21(7):1130–1138, July 2016.
  14. Wilson Wen Bin Goh, Limsoon Wong. Advancing clinical proteomics via analysis based on biological complexes: A tale of five paradigms. Journal of Proteome Research, 15(9):3167–3179, July 2016.
  15. Wilson Wen Bin Goh, Limsoon Wong. Evaluating feature-selection stability in next-generation proteomics. Journal of Bioinformatics and Computational Biology, 14(5):1650029, October 2016.
  16. Wilson Wen Bin Goh, Limsoon Wong. Spectra-first feature analysis in clinical proteomics—A case study in renal cancer. Journal of Bioinformatics and Computational Biology, 14(5):1644004, October 2016.
  17. Wilson Wen Bin Goh, Limsoon Wong. Integrating networks and proteomics: Moving forward. Trends in Biotechnology, 34(12):951–959, December 2016.
  18. Wilson Wen Bin Goh, Limsoon Wong. Protein complex-based analysis is resistant to the obfuscating consequences of batch effects—a case study in clinical proteomis. BMC Genomics, 18(Suppl 2):142, March 2017.
  19. Wilson Wen Bin Goh, Limsoon Wong. Class-paired Fuzzy SubNETs: A paired variant of the rank-based network analysis family for feature selected based on protein complexes. Proteomics, 17(10):1700093, May 2017.
  20. Wilson Wen Bin Goh, Limsoon Wong. NetProt: Complex-based feature selection. Journal of Proteome Research, 16(8):3102–3112, June 2017. NetProt v0.1
  21. Longjian Zhou, Limsoon Wong, Wilson Wen Bin Goh. Understanding missing proteins: A functional perspective. Drug Discovery Today, 23(3):644-651, March 2018.
  22. Wilson Wen Bin Goh, Limsoon Wong. Advanced bioinformatics methods for practical applications in proteomics. Briefings in Bioinformatics, 20(1):347–355, January 2019.
  23. Wilson Wen Bin Goh, Yaxing Zhao, Andrew Chi-Hau Sue, Tiannan Guo, Limsoon Wong. Proteomic investigation of intra-tumor heterogeneity using network-based contextualization—a case study on prostate cancer. Journal of Proteomics, 206:103446, August 2019