Under pressure: the art of sensing acoustic power in the realm of bacteria and fungi

To handle increasing resource scarcity, optimizing bioprocesses is crucial. Ultrasound is a promising tool to enhance microbial growth and protein production in these hosts [1]. It is postulated that mechanotransduction, the process translating environmental mechanical stimuli into cellular responses, is mediated by evolutionarily conserved membrane proteins [2; 3]. Though evolutionarily distant, lactic acid bacteria and fungi share a central role as microbial workhorses for sustainable food production [4; 5] despite lacking a comprehensive characterization of their mechanoreceptors. These mechanosensitive proteins are difficult to characterize in vivo. In this study, we conceived a bioinformatics pipeline to carry out a comparative analysis on these elements. For Streptococcus thermophilus and Lactobacillus delbrueckii subsp. bulgaricus we used the sequences from the UniProt database. For Pleurotus floridanus, due to the lack of available data, a consensus sequence was generated via multiple sequence alignment of homologues and subsequently mapped onto the P. floridanus genome using BLAST to delineate the gene region of interest. Protein structures were generated using the AlphaFold3 artificial intelligence platform, with the correct oligomeric state configured for each channel [Fig.1]. Ultimately, this work highlights how combining bioinformatics with AI-driven prediction can successfully bridge the structural knowledge gap for mechanoreceptors in non-model systems, paving the way for broader evolutionary and functional studies on microbial acoustics.