Microbial consortia are the foundational engines of food fermentation, yet batch-to-batch inconsistency remains a significant industrial challenge. Traditional metatranscriptomics relies on differential expression analysis, which captures global shifts but frequently overlooks inherent transcriptomic noise that governs community stability. In this study, we applied a transcriptomic approach to a defined cheese starter culture using a strain dropout strategy. By quantifying Shannon entropy, transcriptional noise, and switch-like ‘toggle genes’, we identified key functional dependencies and instability points within the consortium. We demonstrate that toggle genes, comprising 4% to 8% of the metatranscriptome, are the primary drivers of community plasticity, exhibiting high expression noise despite not altering global expression entropy. Our network deconvolution identified Lactococcus lactis as a potential keystone strain contributing to the transcriptional complexity of the community, where its removal was associated with a narrower metabolic state. Conversely, the omission of Lactococcus blend was accompanied by pronounced transcriptional instability in Streptococcus thermophilus , characterized by high-magnitude toggling of energetically costly histidine and sugar transport pathways. Together, these findings establish transcriptomic noise as a fundamental feature of microbial consortia and provide a molecular framework for understanding functional redundancy, to complement conventional approaches for evaluating starter culture stability and batch reproducibility in fermented foods.
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Yuan et al. (2026) studied this question.
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