Sauce-flavor Baijiu owes its layered aroma to a diverse microbial consortium fermenting under extreme, open, solid-state conditions. High-throughput sequencing has revealed marked spatiotemporal heterogeneity in community composition, yet a fundamental composition-function disconnect persists: bulk omics average signals across heterogeneous micro-niches and cultivation recovers only a minor fraction of total diversity, leaving “who is doing what” unresolved. Closing this disconnect is a prerequisite for rational design of fermentation microbiomes and demands cell-resolved functional tools within an iterative engineering framework. This review proposes that Single-Cell Raman Spectroscopy (SCRS) and its derivatives, including D 2 O-Raman activity mapping, scRACS-Seq phenotype-to-genome linkage, scRACS-Culture recovery of rare functional strains, and Intra-Ramanome Correlation Analysis (IRCA) predictive metabolic phenotyping, collectively provide a label-free, culture-independent toolkit suited to this role in solid-state matrices. We delineate how these single-cell insights feed each stage of a Design-Build-Test-Learn (DBTL) cycle, from phenotype-informed strain selection through consortium assembly and functional validation to data-driven iterative optimization. This convergence of cell-resolved functional dissection, synthetic ecology, and process analytical technologies establishes the foundation for advancing Sauce-flavor Baijiu from experience-dependent craftsmanship toward intelligent brewing.
Sun et al. (Fri,) studied this question.