Growth factor thermostability dataset derived from experimental and computational approaches to accelerate cultured meat development

Wei Ng, Kiana Aghakasiri, Rebecca Pierce, Julia Marschallinger, Kimberly J. Ong, Steven D. Rees d, David Staszak, Breanna Duffy

https://doi.org/10.1016/j.dib.2026.113042

This project compiled experimentally measured and computationally predicted thermostability data for growth factors (GFs) commonly used in cultured meat and seafood (CM) production. Data were generated on recombinant GFs using thermal shift assays and combined with publicly available data using a structured literature curation workflow developed using a Large Language Model (LLM) with manual validation. In addition, in silico protein stability calculations were generated using FoldX. Data such as GF identity, species origin, recombinant host, variant information, method of measurement, and experimental conditions were collected and standardized into a tabular format. The combined dataset contains 513 melting temperature (Tm) values across diverse GFs and variants, along with additional thermodynamic parameters on a subset of 15 GFs.

The data were harmonized, standardized, and released as an open-source dataset suitable for computational modeling, machine learning workflows, culture media design, and safety assessment frameworks. This resource supports research evaluating GF stability under production- and processing- relevant conditions and provides a foundation for future data expansion, including additional GF variants and other growth factors. By consolidating dispersed thermostability measurements into a unified dataset, supported by experimental data, the resource supports accessibility and reuse across the CM, protein engineering, and regulatory science communities.

Learn more about this project here!