Legon, L. | Search bioRxiv

bioRxiv2025

Genetic mapping of lifespan and mitochondrial stress response in C. elegans

The mitochondrial unfolded protein response (UPRmt) is one of the mito-nuclear regulatory circuits that restores mitochondrial function upon stress conditions, promoting metabolic health and longevity. However, the complex gene interactions that govern this pathway and its role in aging and healthspan remain to be fully elucidated. Here, we activated the UPRmt using doxycycline (Dox) in a genetically diverse C. elegans population comprising 85 strains and observed large variation in Dox-induced lifespan extension across these strains. Through multi-omic data integration, we identified an aging-related molecular signature that was partially reversed by Dox. To identify the mechanisms underlying Dox-induced lifespan extension, we applied quantitative trait locus (QTL) mapping analyses and found one UPRmt modulator, fipp-1/FIP1L1, which was functionally validated in C. elegans and humans. In the human UK Biobank, FIP1L1 was associated with metabolic homeostasis, underscoring its translational relevance. Overall, our findings demonstrate a novel UPRmt modulator across species and provide insights into potential translational research.

genetics↗

bioRxiv2021

gcFront: a tool for determining a Pareto front of growth-coupled cell factory designs

MotivationA widely applicable strategy to create cell factories is to knock out (KO) genes or reactions to redirect cell metabolism so that chemical synthesis is made obligatory when the cell grows at its maximum rate. Synthesis is thus growth-coupled, and the stronger the coupling the more deleterious any impediments in synthesis are to cell growth, making high producer phenotypes evolutionarily robust. Additionally, we desire that these strains grow and synthesise at high rates. Genome-scale metabolic models can be used to explore and identify KOs that growth-couple synthesis, but these are rare in an immense design space, making the search difficult and slow. ResultsTo address this multi-objective optimization problem, we developed a software tool named gcFront - using a genetic algorithm it explores KOs that maximise cell growth, product synthesis, and coupling strength. Moreover, our measure of coupling strength facilitates the search so that gcFront not only finds a growth coupled design in minutes but also outputs many alternative Pareto optimal designs from a single run - granting users flexibility in selecting designs to take to the lab. Availability and ImplementationgcFront, with documentation and a workable tutorial, is freely available at GitHub: https://github.com/lLegon/gcFront, the repository of which is archived at Zenodo, DOI: 10.5281/zenodo.6338595 (Legon et al., 2022). Supplementary InformationSupplementary notes and data files are available at Bioinformatics online.

bioinformatics↗