Metabolite correlation networks reveal complex phenotypes of adaptation-driving mutations
Sharon Samuel, Weronika Jasinska, Ezra Sternlicht, Matvey Nikelshparg, Daniel Kleiner, Shai Pilosof, Shimon Bershtein · 2026
Read Metabolite correlation networks reveal complex phenotypes of adaptation-driving mutations by Sharon Samuel, Weronika Jasinska, Ezra Sternlicht, Matvey Nikelshparg, Daniel Kleiner, Shai Pilosof, Shimon Bershtein (2026) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-13677671.txt.
Description
Mutations in wide-reaching genes reshape a cell's chemistry in many ways at once, and sorting out which change drives adaptation is hard. A seven-author team proposes reading the pattern of links among metabolites as the trait under selection. They evolved an Escherichia coli strain whose metK gene, needed to make the compound SAM, was replaced by a weaker version from another bacterium. They then mapped how the web of links between chemical levels shifted over generations.
After evolution, SAM moved from the edge of the web to a hub position joining separate clusters, even though none of the new mutations touched SAM itself. Other chemicals that shifted in the same way also sat in SAM-linked routes. The authors conclude that correlation webs can reveal system-level traits that selection acts on, and can point researchers to the chemicals and pathways most worth testing next.
Catalog record
| CREATOR | Sharon Samuel, Weronika Jasinska, Ezra Sternlicht, Matvey Nikelshparg, Daniel Kleiner, Shai Pilosof, Shimon Bershtein |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 68 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |