Assigning functions to the vast array of proteins present in eukaryotic cells remains challenging. To identify relationships between proteins, and thereby enable functional annotations of proteins, we determined changes of abundance of 10,323 human proteins in response to 294 biological perturbations using isotope-labelling mass spectrometry. We applied the machine learning algorithm treeClust to reveal functional associations between co-regulated human proteins from ProteomeHD, a compilation of our own data and datasets from the Proteomics Identifications (PRIDE) database. This produced a co-regulation map of the human proteome. Co-regulation was able to capture relationships between proteins that do not physically interact or co-localize. For example, co-regulation of the peroxisomal membrane protein PEX11β with mitochondrial respiration factors led us to discover an organelle interface between peroxisomes and mitochondria ✉

Genes are not randomly distributed in the genome. In humans, 10% of protein‐coding genes are transcribed from bidirectional promoters and many more are organised in larger clusters. Intriguingly, neighbouring genes are frequently coexpressed but rarely functionally related. Here we show that coexpression of bidirectional gene pairs, and closeby genes in general, is buffered at the protein level. Taking into account the 3D architecture of the genome, we find that co‐regulation of spatially close, functionally unrelated genes is pervasive at the transcriptome level, but does not extend to the proteome. We present evidence that non‐functional mRNA coexpression in human cells arises from stochastic chromatin fluctuations and direct regulatory interference between spatially close genes. Protein‐level buffering likely reflects a lack of coordination of post‐transcriptional regulation of functionally unrelated genes. Grouping human genes together along the genome sequence, or through long‐range chromosome folding, is associated with reduced expression noise. Our results support the hypothesis that the selection for noise reduction is a major driver of the evolution of genome organisation.

Data-independent acquisition proteomics was used to study proteome changes of naive human neutrophils in rare monogenic diseases affecting their functions. Neutrophils of patients with mutations in the neutrophil elastase gene ELANE demonstrated global proteome dysregulation, whereas chronic granulomatous disease and leukocyte adhesion deficiency had modest effects on the respective neutrophil proteomes. Proteomics then guided targeted genetic assays to resolve two clinical cases with undetermined genetic causes, highlighting the usefulness of mass spectrometry-based clinical diagnostics.

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