4 years ago

Optimized fragmentation schemes and data analysis strategies for proteome-wide cross-link identification

Optimized fragmentation schemes and data analysis strategies for proteome-wide cross-link identification
Rosa Viner, Albert J. R. Heck, Philip Lössl, Fan Liu, Richard Scheltema
We describe optimized fragmentation schemes and data analysis strategies substantially enhancing the depth and accuracy in identifying protein cross-links using non-restricted whole proteome databases. These include a novel hybrid data acquisition strategy to sequence cross-links at both MS2 and MS3 level and a new algorithmic design XlinkX v2.0 for data analysis. As proof-of-concept we investigated proteome-wide protein interactions in E. coli and HeLa cell lysates, respectively, identifying 1,158 and 3,301 unique cross-links at 1% false discovery rate. These protein interaction repositories provide meaningful structural information on many endogenous macromolecular assemblies, as we showcase on several protein complexes involved in translation, protein folding and carbohydrate metabolism.

Publisher URL: http://www.nature.com/articles/ncomms15473

DOI: 10.1038/ncomms15473

You might also like
Discover & Discuss Important Research

Keeping up-to-date with research can feel impossible, with papers being published faster than you'll ever be able to read them. That's where Researcher comes in: we're simplifying discovery and making important discussions happen. With over 19,000 sources, including peer-reviewed journals, preprints, blogs, universities, podcasts and Live events across 10 research areas, you'll never miss what's important to you. It's like social media, but better. Oh, and we should mention - it's free.

  • Download from Google Play
  • Download from App Store
  • Download from AppInChina

Researcher displays publicly available abstracts and doesn’t host any full article content. If the content is open access, we will direct clicks from the abstracts to the publisher website and display the PDF copy on our platform. Clicks to view the full text will be directed to the publisher website, where only users with subscriptions or access through their institution are able to view the full article.