The PTMeXchange project – mapping post-translational modifications across the Tree of Life

Hosts: Piers Hemsley, Tony Ly & Geoffrey Barton

Venue: MSI Small Lecture Theatre, SLS

Abstract: Post-translational modifications (PTMs) play a key role in most biological functions, and are often implicated in disease. Mass spectrometry (MS) coupled with database searching are commonly used to detect and localise modification sites on proteins, and many PTM-enriched, raw MS datasets are deposited in the public domain via ProteomeXchange.

In our group, we have previously profiled PTM-containing databases that lacked an evidence trail or robust statistics on site detection, demonstrating a high reporting of false positive PTM sites. We established the PTMeXchange project (Liverpool, EMBL-EBI, Institute of Systems Biology, USA) aimed at re-analysing publicly available, enriched PTM datasets, focusing on accurate PTM localisation and data sharing.

We have developed new statistical approaches for controlling the global false discovery rate in site detection, and for performing PTM meta-analyses. Our consortium has also developed new infrastructure, such as the Universal Spectrum Identifier, to capture and visualise a full evidence trail, and a data dissemination pipeline, enabling results to be visualised and accessible in protein knowledgebases, like UniProtKB, as well as in proteomics-specific resources – PRIDE and PeptideAtlas, thus making PTM data FAIR (Findable, Accessible, Interoperable and Reusable).

In this talk, I will describe the PTM analysis methods and infrastructure, as well as the results for species-phosphorylation builds, particularly focussed on rice and the malaria parasite Plasmodium falciparum, and briefly mention others e.g. Yeast, human and mouse. We also have on-going builds in production for lysine modifications in humans (SUMO, ubiquitin and acetylation).

For PTM builds, we explore PTM motifs and associated biological pathways, their conservation within or across species, and map to structural features (AlphaFold models and protein disorder predictions) to understand the function and evolution of PTMs.

Our team is also working on annotating the rice pan-genome, and contributes to the eukaryotic pathogen and vector database https://veupathdb.org which has popular component sites such as PlasmoDB, FungiDB and TriTrypDB (kinetoplastids), which I will mention briefly.

 

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