Improved prediction of MHC II antigen presentation through integration and motif deconvolution of mass spectrometry MHC eluted ligand data
William H. Hildebrand,
Posted 10 Oct 2019
bioRxiv DOI: 10.1101/799882 (published DOI: 10.1021/acs.jproteome.9b00874)
Posted 10 Oct 2019
Major Histocompatibility Complex II (MHC II) molecules play a vital role in the onset and control of cellular immunity. In a highly selective process, MHC II presents peptides derived from exogenous antigens on the surface of antigen-presenting cells for T cell scrutiny. Understanding the rules defining this presentation holds critical insights into the regulation and potential manipulation of the cellular immune system. Here, we apply the NNAlign\_MA machine learning framework to analyse and integrate large-scale eluted MHC II ligand mass spectrometry (MS) data sets to advance prediction of CD4+ epitopes. NNAlign\_MA allows integration of mixed data types, handling ligands with multiple potential allele annotations, encoding of ligand context, leveraging information between data sets, and has pan-specific power allowing accurate predictions outside the set of molecules included in the training data. Applying this framework, we identified accurate binding motifs of more than 50 MHC class II molecules described by MS data, particularly expanding coverage for DP and DQ beyond that obtained using current MS motif deconvolution techniques. Further, in large-scale benchmarking, the final model termed NetMHCIIpan-4.0, demonstrated improved performance beyond current state-of-the-art predictors for ligand and CD4+ T cell epitope prediction. These results suggest NNAlign_MA and NetMHCIIpan-4.0 are powerful tools for analysis of immunopeptidome MS data, prediction of T cell epitopes and development of personalized immunotherapies.
- Downloaded 1,037 times
- Download rankings, all-time:
- Site-wide: 20,729
- In bioinformatics: 2,448
- Year to date:
- Site-wide: 16,524
- Since beginning of last month:
- Site-wide: 28,770
Downloads over time
Distribution of downloads per paper, site-wide
- 27 Nov 2020: The website and API now include results pulled from medRxiv as well as bioRxiv.
- 18 Dec 2019: We're pleased to announce PanLingua, a new tool that enables you to search for machine-translated bioRxiv preprints using more than 100 different languages.
- 21 May 2019: PLOS Biology has published a community page about Rxivist.org and its design.
- 10 May 2019: The paper analyzing the Rxivist dataset has been published at eLife.
- 1 Mar 2019: We now have summary statistics about bioRxiv downloads and submissions.
- 8 Feb 2019: Data from Altmetric is now available on the Rxivist details page for every preprint. Look for the "donut" under the download metrics.
- 30 Jan 2019: preLights has featured the Rxivist preprint and written about our findings.
- 22 Jan 2019: Nature just published an article about Rxivist and our data.
- 13 Jan 2019: The Rxivist preprint is live!