Under Pressure: The Art of Sensing Acoustic Power in the Realm of Bacteria and Fungi

It proposes and implements a bioinformatics comparative-analysis pipeline for mechanoreceptors in non-model microbes Comprehensive characterization of mechanoreceptors in lactic acid bacteria and fungi was previously lacking; this work integrates sequence retrieval, consensus-sequence construction, genome mapping, and structure prediction into a reusable analysis path A methodological pipeline based on UniProt sequences and publicly available genome data, with structures shown in Fig. 1, representing computational prediction-level evidence

For the data-poor Pleurotus floridanus, it generates a consensus sequence via multiple sequence alignment of homologues and maps it onto the genome using BLAST to delineate the gene region of interest It offers an alternative strategy from homology alignment to genome localization when ready-made sequence data are unavailable The method is clearly described but depends on the representativeness of homologues and alignment quality; no quantitative validation metrics are reported

It uses AlphaFold3 to generate protein structures with the correct oligomeric state configured for each channel It brings AI structure prediction into research on mechanoreceptors relevant to microbial acoustics, offering a structural entry point for mechanosensitive proteins that are difficult to characterize in vivo Structures come from AI prediction rather than experimental determination and are presented in Fig. 1, constituting predictive evidence

This work addresses the structural knowledge gap for mechanoreceptors in lactic acid bacteria and fungi, suited to research settings that aim to optimize bioprocesses with ultrasound in the context of sustainable food production; its pipeline is informative for data-poor non-model systems and can supply structural hypotheses for further evolutionary and functional studies.

Readers may still watch how robust the consensus-sequence strategy is when homologues are limited, how closely AlphaFold3-predicted structures correspond to in vivo conformations and oligomeric states, and how these predicted structures connect to functional performance under ultrasound; moreover, this reading is at the summary level, so specific structural details such as Fig. 1 and any quantitative assessments are not elaborated in the text.