A Novel, Computational Method for the Quantification of Histone Post-Translational Modifications using LC-MS/MS

Web Published:

Princeton Docket # 11-2630-1


Researchers in the department of molecular biology Princeton University have developed a method that directly incorporates chromatographic relationships between modified forms into post-translational modifications (PTMs) identification and quantitation problems. In particular, this method establishes a priori relative elution relationships between modified forms of the same peptide with respect to the type of chromatography (e.g., reversed phase) used to separate the sample mixture. These relationships are then built into the model, which is formulated as an optimization problem in order to simultaneously consider the retention time and m/z dimensions when solving the PTM identification and quantitation problem. Thus, just solving one optimization model, which is more reflective of the large-scale and complementary LC-MS/MS data structure, simultaneously identifies and quantifies all modified forms of the same peptide. Furthermore, the method is able to deconvolve co-eluting isobaric peptides present in mixed tandem MS (i.e., spectra containing the fragment ions of more than one modified form) and make accurate and robust identifications to incomplete tandem MS.



- High-quality and comprehensive unbiased, quantitative readouts of all modifications present on histone proteins

- Direct integration of chromatography information for the identification of modified peptides

- Ability to interpret `mixed¿ tandem mass spectra resulting from the co-fragmentation of co-eluting isobaric modified forms



- Study of post-translational modifications on histone proteins

- Drug discovery ¿ target identification

- Study of eukaryotic gene regulation and chromatin-related processes



Existing computational methods for quantitating peptide post-translational modifications (PTMs) using liquid chromatography tandem mass spectrometry (LC-MS/MS) data must decouple this large-scale data into smaller and sequential subproblems for tractability purposes. This type of approach loses important connectivity between modified species with regards to their physicochemical properties and is susceptible to the propagation of error between subproblems. In particular, modified forms are independently identified using isolated tandem mass spectra without considering their temporal relationship to other modified forms of the same peptide sequence. Furthermore, lower abundance modified forms for which no tandem MS are available (due to dynamic range limitations of the MS) or isobaric and co-eluting modified forms are not detected by such approaches.




Benjamin A Garcia

Benjamin Garcia is an Assistant Professor in the Department of Molecular Biology. His research is focused on developing novel mass spectrometry based proteomic methodologies for quantitatively characterizing changes in protein expression and post-translational modification state within a given proteome during significant biological events or in response to external perturbation. Garcia¿s goal is to utilize large-scale proteomic data to improve our understanding of biological processes at the molecular level. Histone modifications have emerged as a key mechanism of epigenetic inheritance. Utilization of advanced proteomic technology in chromatin biology will enhance investigations of histone modifications to a much higher scale.

Garcia received his B.S. from the University of California, Davis and a Ph.D from the University of Virginia, both in chemistry. Professor Garcia holds numerous awards of which most recent include the New Jersey American Chemical Society Early Career Award in Mass Spectrometry 2011, NIH Director¿s New Innovator Award 2010-2015, and the NSF Faculty Early CAREER Award 2010-2015.


Peter A. DiMaggio, Jr.

Peter DiMaggio is a post-doctoral research fellow in the Department of Molecular Biology. His research is centered upon the development of mathematically rigorous computational platforms for the characterization of targeted protein systems using LC-MS/MS data. DiMaggio received his B.S. from the University of Rhode Island and his Ph.D. from Princeton University, both in chemical engineering. He is a recipient of the Jacobus Honorific Fellowship, which is the highest honor conferred by the Graduate School at Princeton, and the NIH/NRSA Ruth L. Kirschstein Postdoctoral Fellowship.


Intellectual property and technology status:

Patent pending

The method has been rigorously tested and benchmarked against manually curated data. Industrial collaborators and licensees are sought to further establish this methodology.



Laurie Tzodikov

Princeton University Office of Technology Licensing ¿ (609) 258-7256¿ tzodikov@princeton.edu

Princeton docket # 11-2630

Patent Information:
For Information, Contact:
Cortney Cavanaugh
New Ventures and Licensing associate
Princeton University
Peter Dimaggio, Jr.
Benjamin Garcia