Identification and characterization of sequence signatures in the Bacillus subtilis promoter Pylb for tuning promoter strength

Precise Prediction of Promoter Strength Based on a De Novo Synthetic Promoter Library Coupled with Machine Learning

Promoters are one of the most critical regulatory elements controlling metabolic pathways. However, the fast and accurate prediction of promoter strength remains challenging, leading to time- and labor-consuming promoter construction and characterization processes. This dilemma is caused by the lack of a big promoter library that has gradient strengths, broad dynamic ranges, and clear sequence profiles that can be used to train an artificial intelligence model of promoter strength prediction. To overcome this challenge, we constructed and characterized a mutant library of Trc promoters (P_trc) using 83 rounds of mutation-construction-screening-characterization engineering cycles. After excluding invalid mutation sites, we established a synthetic promoter library that consisted of 3665 different variants, displaying an intensity range of more than two orders of magnitude. The strongest variant was ∼69-fold stronger than the original P_trc and 1.52-fold stronger than a 1 mM isopropyl-β-d-thiogalactoside-driven P_T7 promoter, with an ∼454-fold difference between the strongest and weakest expression levels. Using this synthetic promoter library, different machine learning models were built and optimized to explore the relationships between promoter sequences and transcriptional strength. Finally, our XgBoost model exhibited optimal performance, and we utilized this approach to precisely predict the strength of artificially designed promoter sequences (R² = 0.88, mean absolute error = 0.15, and Pearson correlation coefficient = 0.94). Our work provides a powerful platform that enables the predictable tuning of promoters to achieve optimal transcriptional strength.

An overview and future prospects of recombinant protein production in Bacillus subtilis

Bacillus subtilis is a well-characterized Gram-positive bacterium and a valuable host for recombinant protein production because of its efficient secretion ability, high yield, and non-toxicity. Here, we comprehensively review the recent studies on recombinant protein production in B. subtilis to update and supplement other previous reviews. We have focused on several aspects, including optimization of B. subtilis strains, enhancement and regulation of expression, improvement of secretion level, surface display of proteins, and fermentation optimization. Among them, optimization of B. subtilis strains mainly involves undirected chemical/physical mutagenesis and selection and genetic manipulation; enhancement and regulation of expression comprises autonomous plasmid and integrated expression, promoter regulation and engineering, and fine-tuning gene expression based on proteases and molecular chaperones; improvement of secretion level predominantly involves secretion pathway and signal peptide screening and optimization; surface display of proteins includes surface display of proteins on spores or vegetative cells; and fermentation optimization incorporates medium optimization, process condition optimization, and feeding strategy optimization. Furthermore, we propose some novel methods and future challenges for recombinant protein production in B. subtilis.Key points• A comprehensive review on recombinant protein production in Bacillus subtilis.• Novel techniques facilitate recombinant protein expression and secretion.• Surface display of proteins has significant potential for different applications.