The piece revisits the early days, our lab's initial work alongside other groups pioneering complementary approaches, together showing that mass-spec-based single-cell proteomics was feasible & promising. The proof-of-concept set the field in motion. 2/ nature.com/articles/d41586-0…

The preprint was available, and the peer review was rigorous and constructive even if very time consuming. Thanks to @biorxivpreprint enabled by @cshperspectives and colleagues, the long peer review times do not delay sharing new results as much as before preprinting.

Since the 1960s, the genetic code has been used to predict protein sequences from DNA and mRNA sequences.  Our @Nature article demonstrates that these predictions miss thousands of protein sequences present in human tissues. Across >1,000 human samples, we identified numerous abundant proteins whose amino acid sequences differ from those predicted by the genetic code. These proteins are not rare translation byproducts. They accumulate to thousands of copies per cell. Some are more abundant than the proteins predicted by the genetic code from the same transcripts. Their abundance reflects a combination of alternate RNA decoding mechanisms — including codon-anticodon mismatches, tRNA abundance, and RNA modifications — and selective stabilization of the resulting proteins. The last factor – protein stability – emerges as a major determinant of protein abundance across proteins, proteoforms and cell types: slavovlab.net/research.htm#P… Alternate RNA decoding is pervasive across functional groups of proteins, healthy and diseased tissues. It affects proteins playing key roles in neurodegeneration, and some alternately decoded proteins show strong enrichment in tumors compared to their surrounding tissues. This discovery has been a long and exhilarating journey with Shira Tsour and the @slavovLab team. It started in 2019 and proceeded through many challenges and thrilling highs. A journey that has opened new perspectives that we long to explore! 1/