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Quantitative mass spectrometry based spatial proteomics involves elaborate, expensive and time consuming experimental procedures and considerable effort is invested in the generation of such data. Multiple research groups have described a variety of approaches to establish high quality proteome-wide datasets. However, data analysis is as critical as data production for reliable and insightful biological interpretation, and no consistent and robust solutions have been offered to the community so far. Here, we introduce the requirements for rigorous spatial proteomics data analysis as well as the statistical machine learning methodologies needed to address them, including supervised and semi-supervised machine learning, clustering and novelty detection. We present freely available software solutions that implement innovative state-of-the-art analysis pipelines and illustrate these tools using several case studies, from multiple organisms, experimental designs, mass spectrometry platforms and quantitation techniques. We also propose sound analysis strategies to identify dynamic changes in sub-cellular localisation by comparing and contrasting data describing different biological conditions. We conclude by discussing future needs and developments in spatial proteomics data analysis.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes COVID-19. SARS-CoV-2 relies on cellular RNA-binding proteins (RBPs) to replicate and spread, although which RBPs control its life cycle remains largely unknown. Here, we employ a multi-omic approach to identify systematically and comprehensively the cellular and viral RBPs that are involved in SARS-CoV-2 infection. We reveal that SARS-CoV-2 infection profoundly remodels the cellular RNA-bound proteome, which includes wide-ranging effects on RNA metabolic pathways, non-canonical RBPs and antiviral factors. Moreover, we apply a new method to identify the proteins that directly interact with viral RNA, uncovering dozens of cellular RBPs and six viral proteins. Amongst them, several components of the tRNA ligase complex, which we show regulate SARS-CoV-2 infection. Furthermore, we discover that available drugs targeting host RBPs that interact with SARS-CoV-2 RNA inhibit infection. Collectively, our results uncover a new universe of host-virus interactions with potential for new antiviral therapies against COVID-19., Graphical Abstract, Kamel, Noerenberg, Cerikan and colleagues apply a multi-omic approach to identify the RNA-binding proteins that regulate SARS-CoV-2 infection. They discovered that the complement of RNA-binding proteins heavily remodels upon SARS-CoV-2 infection. They also show that the viral RNA interacts with dozens of cellular and six viral RNA-binding proteins. These host-virus interactions are fundamental for SARS-CoV-2 infection and have great potential for new therapeutic approaches against COVID-19.