Computational systems approach towards phosphoproteomics and their downstream regulation

Abstract

Protein phosphorylation plays an essential role in modulating cell signalling and its downstream transcriptional and translational regulations. Until recently, protein phosphorylation has been studied mostly using low‐throughput biochemical assays. The advancement of mass spectrometry (MS)‐based phosphoproteomics transformed the field by enabling measurement of proteome‐wide phosphorylation events, where tens of thousands of phosphosites are routinely identified and quantified in an experiment. This has brought a significant challenge in analysing large‐scale phosphoproteomic data, making computational methods and systems approaches integral parts of phosphoproteomics. Previous works have primarily focused on reviewing the experimental techniques in MS‐based phosphoproteomics, yet a systematic survey of the computational landscape in this field is still missing. Here, we review computational methods and tools, and systems approaches that have been developed for phosphoproteomics data analysis. We categorise them into four aspects including data processing, functional analysis, phosphoproteome annotation and their integration with other omics, and in each aspect, we discuss the key methods and example studies. Lastly, we highlight some of the potential research directions on which future work would make a significant contribution to this fast‐growing field. We hope this review provides a useful snapshot of the field of computational systems phosphoproteomics and stimulates new research that drives future development.

Delineation of signaling routes that underlie differences in macrophage phenotypic states

“…The main advantage of quantitative phosphoproteomics, compared to transcriptomics or proteomics, is that it provides closer insights into the active states of proteins. However, phosphoproteomics is still hampered by a high fraction of missing values and the absence of a certain phosphoprotein does not necessarily mean that the protein is not present in the phosphorylated form 88 . In order to infer the increased activity of upstream protein kinases, we further studied sequence motifs surrounding all significantly upregulated phosphosites and considered also upstream kinases that were themselves not measured.…”

Post‐translational modification and phenotype

“…The first group of articles feature three Review articles . In the first Review article , Xiao et al overviewed a plethora of computational methods developed for phosphoproteomic data analysis [4]. These methods include those for basic data processing (such as data filtering, imputation, and normalization), functional analysis (such as kinase‐substrate prediction, kinase activity inference, and signaling network reconstruction), phosphoproteome annotation, and multi‐omics integration.…”