rocF affects the production of tetramethylpyrazine in fermented soybeans with Bacillus subtilis BJ3-2

Abstract Background Tetramethylpyrazine (TTMP) is a flavoring additive that significantly contributes to the formation of flavor compounds in soybean-based fermented foods. Over recent years, the application of TTMP in the food industry and medicine has been widely investigated. In addition, several methods for the industrial-scale production of TTMP, including chemical and biological synthesis, have been proposed. However, there have been few reports on the synthesis of TTMP through amino acid metabolic flux. In this study, we investigated genetic alterations of arginine metabolic flux in solid-state fermentation (SSF) of soybeans with Bacillus subtilis (B.subtilis) BJ3-2 to enhance the TTMP yield. Results SSF of soybeans with BJ3-2 exhibited a strong Chi-flavour (a special flavour of ammonia-containing smelly distinct from natto) at 37 °C and a prominent soy sauce-like aroma at 45 °C. Transcriptome sequencing and RT-qPCR verification showed that the rocF gene was highly expressed at 45 °C but not at 37 °C. Moreover, the fermented soybeans with BJ3-2ΔrocF (a rocF knockout strain in B. subtilis BJ3-2 were obtained by homologous recombination) at 45 °C for 72 h displayed a lighter color and a slightly decreased pH, while exhibiting a higher arginine content (increased by 14%) than that of BJ3-2. However, the ammonia content of fermented soybeans with BJ3-2ΔrocF was 43% lower than that of BJ3-2. Inversely, the NH4 + content in fermented soybeans with BJ3-2ΔrocF was increased by 28% (0.410 mg/kg). Notably, the TTMP content in fermented soybeans with BJ3-2ΔrocF and BJ3-2ΔrocF + Arg (treated with 0.05% arginine) were significantly increased by 8.6% (0.4617 mg/g) and 18.58% (0.504 mg/g) respectively than that of the BJ3-2. Conclusion The present study provides valuable information for understanding the underlying mechanism during the TTMP formation process through arginine metabolic flux.

Abstract licence: CC BY-NC-ND

A person counts once a day per paper. We keep no cookie and no address: a reader is a hash that changes every day. Any month under five reads shows no number.