Detalle de: Disentangling protein metabolic costs in human cells and tissues

While more data are becoming available on gene activity at different levels of biological organization, our understanding of the underlying biology remains incomplete. Here, we introduce a metabolic efficiency framework that considers highly expressed proteins (HEPs), their length, and biosynthetic costs in terms of the amino acids (AAs) they contain to address the observed balance of expression costs in cells, tissues, and cancer transformation. Notably, the combined set of HEPs in either cells or tissues shows an abundance of large and costly proteins, yet tissues compensate this with short HEPs comprised of economical AAs, indicating a stronger tendency toward mitigating costs. We additionally observe that short proteins are prevalent HEPs across individual cells and tissues, whereas long ones are more specific. Furthermore, the precise proportion of short, long, economical, or costly HEP classes indicates that particular cell types and tissues align more closely with the metabolic efficiency model, with some tissues displaying behavior akin to their constituent cells. Finally, tumors typically increase the production of short and low-cost HEPs compared with matched normal tissues, while genes that decrease their high expression levels in tumors often tend to be associated with high costs. Overall, the metabolic efficiency framework serves as a useful simplifying model for interpreting genome-wide expression data across scales.