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Microbial-derived salt-tolerant proteases and their applications in high-salt traditional soybean fermented foods: a review.

Hongli YaoShuangping LiuTiantian LiuDongliang RenZhilei ZhouQilin YangJian Mao
Published in: Bioresources and bioprocessing (2023)
Different microorganisms can produce different proteases, which can adapt to different industrial requirements such as pH, temperature, and pressure. Salt-tolerant proteases (STPs) from microorganisms exhibit higher salt tolerance, wider adaptability, and more efficient catalytic ability under extreme conditions compared to conventional proteases. These unique enzymes hold great promise for applications in various industries including food, medicine, environmental protection, agriculture, detergents, dyes, and others. Scientific studies on microbial-derived STPs have been widely reported, but there has been little systematic review of microbial-derived STPs and their application in high-salt conventional soybean fermentable foods. This review presents the STP-producing microbial species and their selection methods, and summarizes and analyzes the salt tolerance mechanisms of the microorganisms. It also outlines various techniques for the isolation and purification of STPs from microorganisms and discusses the salt tolerance mechanisms of STPs. Furthermore, this review demonstrates the contribution of modern biotechnology in the screening of novel microbial-derived STPs and their improvement in salt tolerance. It highlights the potential applications and commercial value of salt-tolerant microorganisms and STPs in high-salt traditional soy fermented foods. The review ends with concluding remarks on the challenges and future directions for microbial-derived STPs. This review provides valuable insights into the separation, purification, performance enhancement, and application of microbial-derived STPs in traditional fermented foods.
Keyphrases
  • microbial community
  • systematic review
  • mass spectrometry
  • machine learning
  • wastewater treatment
  • artificial intelligence
  • deep learning