A generalized growth law for translation- and transcription-targeting antibiotics captures drug interactions

Bacterial growth laws, which connect intracellular resource allocation to growth rate, typically offer reliable predictions for a drug's impact on physiology and antibiotic response. However, these laws have only been thoroughly tested for a limited number of perturbations. In a groundbreaking study, researchers demonstrate that the growth law linking ribosome levels to growth rate under translation-inhibiting antibiotics is not universal, but instead hinges on the antibiotic's mechanism of action.

Using quantitative proteomics across finely resolved one- and two-dimensional antibiotic gradients, the team discovered that inhibitors of translocation elongation or peptide bond formation trigger a consistent rise in ribosome levels, in line with the growth law. In contrast, antibiotics disrupting translation initiation or fidelity result in unique responses that lack ribosome upregulation. Even more intriguing, the transcription inhibitor rifampicin actually decreased ribosome abundance.

By comparing antibiotics that exhibit different ribosome responses, the researchers identified a generalized growth law. This law enables the amalgamation of individual responses to various perturbations, revealing a pattern that emerges when multiple antibiotics are combined. By embedding this law in a mathematical model, the team explains distinct drug interaction patterns observed between rifampicin and different translation inhibitors.

The model also predicts that a low-dimensional structure pervades the entire proteome, enabling researchers to forecast responses to drug pairs based on single-drug measurements. This finding broadens the scope of bacterial growth laws and offers new principles for predicting antibiotic combinations' impacts.