From messy chemistry to ecology: Autocatalysis and heritability in prebiotically plausible chemical systems

A key question in origins-of-life research, is whether heritability, and thus evolution, could have preceded genes. Out-of-equilibrium chemical reaction networks with multiple autocatalytic motifs may provide chemical \"memory\" and serve as units of heritability, but experimental validation is lacking. We established conditions that may be conducive to the emergence of heritable variation and developed methods to search for heritability and autocatalysis. We prepared a food set (FS) of three organic species, three inorganic salts and pyrite. We conducted a serial dilution experiment where FS was incubated for 24 hours, after which a 20% fraction was transferred into freshly prepared FS that went through the same procedure, repeated for 10 generations. To serve as controls, we also incubated the fresh solutions in each generation. We compared the chemical composition of transfer vials and no-transfer controls using liquid chromatography-mass spectrometry (LCMS), with metrics adapted from ..., This is the supplementary data for a biorxiv preprint https://doi.org/10.1101/2024.08.03.606486. It is split into 3 folders:
1) python and R code to process LCMS data in ways described in the article;
2) raw outputs of CompoundDiscoverer software on the LCMS data from the two replicate 10-generation experiments and incubation tests described in the article and the Appendix A;
3) inputs and outputs for the computational pipeline using Rule-it and autocatalyticsubnetworks software described in the article and Appendix C., , # From messy chemistry to ecology: Autocatalysis and heritability in prebiotically plausible chemical systems

[https://doi.org/10.5061/dryad.hhmgqnkrt](https://doi.org/10.5061/dryad.hhmgqnkrt)

## Description of the data

This is a supplementary dataset for the preprint titled \"From messy chemistry to ecology: Autocatalysis and heritability in prebiotically plausible chemical systems\" ([https://www.biorxiv.org/content/10.1101/2024.08.03.606486v3.full](https://www.biorxiv.org/content/10.1101/2024.08.03.606486v3.full)), that includes 1) raw and processed experimental data generated in this study; 2) generated python and R code used to analyze the data; 3) inputs and outputs for the computational analyses in this study.

## File structure

-code,code used in this study

\--autocatalysis, code used for AC detection

\---food-search.py, searches the list of ACs for ACs with a specific food set

\---rxn-drawer-smiles.py, draws a reaction network with chemical structures from an input list o...