Saprotrophic soil fungus dissolves lithium lepidolite through inositol rescue metabolism

Authors

LaBonte, S., Perdue, C., Wietsma, T. W., Paurus, V. L., Kim, Y.-M., Kao, H.-M., Zhu, Z., Nuccio, E., Pett-Ridge, J., Lipton, M., Bhattacharjee, A.

Abstract

Microbial weathering of minerals represents a key biogeochemical process through which microorganisms access essential nutrients locked within rock and ore substrates. In this study, we investigated the metabolic response of a model fungus during growth on lithium (Li) ore to elucidate the mechanisms underpinning biologically mediated mineral weathering and subsequent metal mobilization. Our results revealed a distinct metabolic shift in the fungus when cultivated on Li ore, characterized by altered patterns of organic acid production and energy metabolism. This shift coincided with measurable weathering of the Li ore matrix and the consequent release of soluble Li into the surrounding environment, demonstrating a direct link between fungal metabolic reprogramming and mineral breakdown. Importantly, these observations are consistent with metabolic shifts documented in previous studies of mineral weathering by this fungus, suggesting that such responses constitute a conserved and reproducible strategy employed during the colonization of mineral substrates. Although the present work was conducted using a single model microorganism under controlled conditions, the findings carry broader ecological implications. Natural microbial communities inhabiting mineral-rich environments may undergo analogous metabolic shifts when weathering minerals to acquire limiting nutrients, thereby contributing to large-scale elemental cycling and metal release. Understanding these processes not only advances fundamental knowledge of microbe-mineral interactions but also informs emerging applications in biomining and bio-based recovery of critical metals such as lithium. Collectively, this study highlights the central role of microbial metabolism in driving mineral weathering and offers a framework for predicting and harnessing similar processes within complex microbial communities.

Preprint server: bioRxiv
The authors list and abstract were imported from bioRxiv on 30 Jul 2026.

Stats

1-terrible, 9-excellent. How would you rate this preprint? Sign in in to submit your rating.

Post a comment

You need to be signed in to post comments. You can sign in here.

Comments

There are no comments yet.