Biology subjects

Camacho, O. M.

Publications and source records attributed to Camacho, O. M..

2 recordsLinked to original sources

bioRxiv2023

A meta-analysis of rice phosphoproteomics data to understand variation in cell signalling across the rice pan-genome

Phosphorylation is the most studied post-translational modification, and has multiple biological functions. In this study, we have re-analysed publicly available mass spectrometry proteomics datasets enriched for phosphopeptides from Asian rice (Oryza sativa). In total we identified 15,522 phosphosites on serine, threonine and tyrosine residues on rice proteins. We identified sequence motifs for phosphosites, and link motifs to enrichment of different biological processes, indicating different downstream regulation likely caused by different kinase groups. We cross-referenced phosphosites against the rice 3,000 genomes, to identify single amino acid variations (SAAVs) within or proximal to phosphosites that could cause loss of a site in a given rice variety. The data was clustered to identify groups of sites with similar patterns across rice family groups, for example those highly conserved in Japonica, but mostly absent in Aus type rice varieties - known to have different responses to drought. These resources can assist rice researchers to discover alleles with significantly different functional effects across rice varieties. The data has been loaded into UniProt Knowledge-Base - enabling researchers to visualise sites alongside other data on rice proteins e.g. structural models from AlphaFold2, PeptideAtlas and the PRIDE database - enabling visualisation of source evidence, including scores and supporting mass spectra.

bioinformatics↗

bioRxiv2022

Assessing multiple evidence streams to decide on confidence for identification of post-translational modifications, within and across data sets

Phosphorylation is a post-translational modification of great interest to researchers due to its relevance in many biological processes. LC-MS/MS techniques have enabled high-throughput data acquisition with studies claiming identification and localisation of thousands of phosphosites. The identification and localisation of phosphosites emerge from different analytical pipelines and scoring algorithms, with uncertainty embedded throughout the pipeline. For many pipelines and algorithms, arbitrary thresholding is used, but little is known about the actual global false localisation rate in these studies. Recently, it has been suggested using decoy amino acids to estimate global false localisation rates of phosphosites, amongst the peptide-spectrum matches reported. We here describe a simple pipeline aiming to maximize the information extracted from these studies by objectively collapsing from peptide-spectrum match to peptidoform-site level, as well as combining findings from multiple studies while maintaining track of false localisation rates. We show that the approach is more effective than current processes that use a simpler mechanism for handling phosphosite identification redundancy within and across studies. In our case study using 8 rice phophoproteomics data sets, 6,368 unique sites were identified confidently identified using our decoy approach compared to 4,687 using traditional thresholding in which false localisation rates are unknown.

bioinformatics↗