Databases and resources for proteome-level PTM information

A foundation of our work is the ability to have proteome information at our fingertips. This includes the current knowledge of tyrosine phosphorylation, quantitative measurements measured on those sites, and related protein annotations.  In enabling this research for our own lab, we also construct tools that can be used by the broader research community, with a focus on extendibility and reproducibility.

ProteomeScout

ProteomeScout is our database of post-translational modifications and their protein annotations.  The major features of ProteomeScout include:

  • Deposition of experimental data.  The current standard of publishing static files regarding PTM-measurements is a serious problem in quantitative proteomics. Database records quickly change and it becomes difficult to map older experiments to new databases.  ProteomeScout serves as a living repository of this information.
  • Exploration and analysis of experimental data. ProteomeScout includes flexible interfaces to explore datasets, including automatic enrichment testing. This framework can be interfaced to MCAM (our ensemble clustering framework).
  • Up-to-date protein and PTM information from both databases and primary experiments.
  • Database download. The database can be downloaded in flat-text files and is updated weekly, with stable releases every six months. This avoids the hassle of having to hand-wrangle multiple resources when one would like to perform a proteome-level PTM computational exploration.
  • Protein viewer. Inspired by the UCSC genome browser, we built a protein browser that allows you to visualize protein feature elements in relation to each other (for example, PTMs relative to mutations and protein domains).  These tracks can be manipulated for size and features and exported for insertion into web pages, grants, articles, etc.

ProteomeScoutAPI

The ProteomeScoutAPI is a Python library that allows you to easily interact with the entire database download of ProteomeScout. Building proteome-level analysis with the ProteomeScout database and the API means that re-analysis of future data is as easy as re-running your code with a new file download.  We demonstrated this in our ProteomeScoutAPI paper, where we tested the hypothesis that missense mutations near sites of modifications are more likely to be related disease since they may have a functional consequence in altering the regulation or recognition of a modification.  This paper also includes historical data that demonstrates that the speed of discovery requires flexible tools for analysis of the proteome as the results are changing significantly between the time of the results and the publication of a paper (let alone years after the study).

proteome level PTM

A foundation of our work is the ability to have proteome information at our fingertips.

Our Research Areas

  • Databases and resources for proteome-level PTM information

    A foundation of our work is the ability to have proteome information at our fingertips. This includes the current knowledge of tyrosine phosphorylation, quantitative measurements measured on those sites, and related protein annotations.  In enabling this research for our own lab, we also construct tools that can be used by the broader research community, with a focus on extendibility and reproducibility.

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  • Inferring biological insight from high-dimensional data

    Kristen Naegle developed ensemble approaches to clustering of biological data in her Ph.D. work that demonstrated that one can infer function of tyrosine phosphorylation from quantitative measurements of the dynamic changes of network phosphorylation in cells in response to growth factor stimulation.  During her post-doctoral work, Dr. Naegle went on to show that robustness in clustering was predictive of protein interactions and inferred novel interactions in the epidermal growth factor receptor network.

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  • SH2 domain binding

    A major piece of ongoing work in the lab is to develop methods that will allow us to identify what phosphotyrosines will be recognized by a binding domain. Specifically, we hope to push this area of research into arenas that allow us to predict the relative competition between domains for phosphotyrosine sequences and phosphotyrosine sequences for domains. This information will enable us to begin to predict the consequence of context differences between cells in response to the same extracellular cue. We will feel we have succeeded when these predictions can be used to explain complex network phenomena.

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  • Engineering enzymatic interactions

    A major barrier to the study of protein phosphorylation is the ability to create phosphorylated proteins for in vitro study. The Naegle lab has been developing a cheap and fast method for producing phosphorylated proteins that capitalizes on observations made of enzymatic specificity.

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