Adaptive evolution enhances freeze-thaw tolerance in baker’s yeast for better frozen-dough bread
image: (A) Schematic overview of the ALE strategy. Three independent ancestral S. cerevisiae strains, DBY12007, PGY7, and PGY34, were subjected to repeated freeze–thaw selection. The resulting evolved lineages were designated ALE1, ALE2, and ALE3. Unless otherwise stated, ALE1–ALE3 refer to mixed evolved lineages collected at the indicated generation checkpoints rather than clonal isolates. (B) Viable cell density of ancestral and evolved lineages during ALE, expressed as CFU mL−1 normalized to OD600. (C) Doubling time of each lineage at different evolutionary stages under non-stress growth conditions. (D) Freeze–thaw survival rate of each lineage across the evolutionary trajectory. (E) Spot assay showing colony-forming capacity of ancestral and evolved lineages before and after freeze–thaw treatment across serial dilutions. Data in panels B–D are presented as mean ± SD from three independent biological replicates. Statistical comparisons were performed by two-way ANOVA followed by Tukey’s post hoc test; ***P < 0.001. Panel e shows a representative spot assay from independent biological replicates.
Credit: ENGINEERING Foods
A study published in ENGINEERING Foods reports that researchers have applied adaptive laboratory evolution to improve baker’s yeast tolerance to repeated freezing and thawing. The approach boosts yeast survival and the quality of frozen-dough bread, without compromising the yeast’s regular growth.
Frozen dough technology is widely adopted in commercial baking. It enables centralized dough preparation, storage and transportation, followed by baking at a later stage. Even so, yeast cells frequently lose viability during frozen storage and recover slowly once thawed. Within real supply chains, dough is often subjected to repeated or partial freeze-thaw cycles. This builds up cumulative damage to yeast cells and leads to inconsistent product quality. For baking applications, yeast needs more than just the ability to survive freezing. It must recover rapidly, resume sugar metabolism, and generate sufficient carbon dioxide during proofing so the dough can rise properly.
To tackle this problem, researchers from Jiangnan University, together with collaborators at Zhejiang Yiming Food Co., Ltd., carried out adaptive evolution on three separate Saccharomyces cerevisiae lineages. The strains went through 300 generations of selection under repeated freeze-thaw stress. The starting strains included DBY12007, a laboratory strain, and two wild isolates PGY7 and PGY34. Each evolution round consisted of cell cultivation, freeze–thaw treatment, recovery of surviving cells, and serial passaging. The selection pressure was raised step by step: the medium for freeze-thaw treatment was switched from nutrient-rich medium to water, and later to phosphate-buffered saline.
The evolved populations achieved notably higher survival rates after freeze-thaw treatment. The top-performing lineage ALE1 reached roughly 96% viability after thawing. ALE2 and ALE3 had post-thaw viability of about 56-69% and 26-29%, respectively. Critically, these evolved lineages grew normally under non-stress conditions. This means the gain in stress tolerance did not come at the expense of regular growth.
These improvements also held up in actual baking trials. In frozen-dough tests, bread made with evolved yeast showed greater loaf expansion and a finer crumb structure after frozen storage, compared with bread produced using the original parent strains. Before freezing, loaves from evolved and parent strains looked comparable, which confirms the evolution process did not weaken the yeast’s basic leavening capacity.
Physiological tests help explain the improved performance. After thawing, evolved strains recovered faster and showed stronger fermentative activity. They also produced less intracellular reactive oxygen species and had adjusted antioxidant activity. Scanning electron microscopy further revealed that evolved yeast cells retained better cell envelope structure after freeze-thaw stress. Fewer cells developed irregular, wrinkled or collapsed surfaces than the parent strains.
Since ALE1 exhibited the best survival and recovery performance, the research team used transcriptomics and metabolomics to investigate its internal cellular changes. ALE1 had broad shifts in gene expression relative to its parent strain, with 1706 differentially expressed genes. These changes were not confined to one single stress response pathway. Instead, they reflected coordinated adjustments across multiple processes: substrate transport, carbohydrate consumption, sulfur amino acid metabolism, cell wall and surface structure maintenance, and cell cycle regulation. Metabolomic profiling also detected changes in amino acid pools, glutathione-related substances, carbon metabolic intermediates and lipid metabolites.
Combining transcriptomic and metabolomic results, the researchers grouped the adaptive traits into four functional modules: improved carbon uptake and metabolic recovery; nitrogen reallocation and amino acid rearrangement; rewired sulfur amino acid metabolism and redox homeostasis; and membrane modification supported by altered transporter function. Taken together, these modules form a working model for freeze-thaw tolerance gained through adaptive evolution. The improved trait does not rely on one single protective gene, but on system-wide adjustments to recovery metabolism, redox balance and cell envelope function.
The authors note that omics data can only show correlations, and cannot confirm direct causal mechanisms. More work is needed to find the exact mutations and regulatory changes behind the improved traits. This follow-up work should include whole-genome sequencing and targeted genetic validation. Even so, this study presents a practical adaptive evolution strategy suitable for food applications, as well as a multi-omics analysis workflow to develop more stable microbial starters for frozen food manufacturing.
The researchers point out that this work demonstrates evolutionary engineering can optimize a complex industrial trait while keeping normal growth intact. It provides a feasible way to stabilize fermentation in frozen dough and produce baked goods with more consistent quality.
Cite the Article:
Anqi Chen, Tianzhi Qu, Chenwei Pan, Jianghua Li, Hui Liu, Jian Chen. Integrated Multi-Omics Analysis Reveals Coordinated Remodeling Associated with Adaptive Evolution-Enhanced Freeze–Thaw Tolerance in Yeast. ENGINEERING Foods DOI:10.2738/ENGF.2026.0021
URL: https://journal.hep.com.cn/ef/EN/10.2738/ENGF.2026.0021