Predicting stress response and improved protein overproduction in Bacillus subtilis

Genome-scale metabolic network models for industrial microorganisms metabolic engineering: Current advances and future prospects

The construction of high-performance microbial cell factories (MCFs) is the centerpiece of biomanufacturing. However, the complex metabolic regulatory network of microorganisms poses great challenges for the efficient design and construction of MCFs. The genome-scale metabolic network models (GSMs) can systematically simulate the metabolic regulation process of microorganisms in silico, providing effective guidance for the rapid design and construction of MCFs. In this review, we summarized the development status of 16 important industrial microbial GSMs, and further outline the technologies or methods that continuously promote high-quality GSMs construction from five aspects: I) Databases and modeling tools facilitate GSMs reconstruction; II) evolving gap-filling technologies; III) constraint-based model reconstruction; IV) advances in algorithms; and V) developed visualization tools. In addition, we also summarized the applications of GSMs in guiding metabolic engineering from four aspects: I) exploring and explaining metabolic features; II) predicting the effects of genetic perturbations on metabolism; III) predicting the optimal phenotype; IV) guiding cell factories construction in practical experiment. Finally, we discussed the development of GSMs, aiming to provide a reference for efficiently reconstructing GSMs and guiding metabolic engineering.

Innovative approaches for amino acid production via consolidated bioprocessing of agricultural biomass

Agricultural plantations in Indonesia and Malaysia yield substantial waste, necessitating proper disposal to address environmental concerns. Yet, these wastes, rich in starch and lignocellulosic content, offer an opportunity for value-added product development, particularly amino acid production. Traditional methods often rely on costly commercial enzymes to convert biomass into fermentable sugars for amino acid production. An alternative, consolidated bioprocessing, enables the direct conversion of agricultural biomass into amino acids using selected microorganisms. This review provides a comprehensive assessment of the potential of agricultural biomass in Indonesia and Malaysia for amino acid production through consolidated bioprocessing. It explores suitable microorganisms and presents a case study on using Bacillus subtilis ATCC 6051 to produce 9.56 mg/mL of amino acids directly from pineapple plant stems. These findings contribute to the advancement of sustainable amino acid production methods using agricultural biomass especially in Indonesia and Malaysia through consolidated bioprocessing, reducing waste and enhancing environmental sustainability.

Establishing comprehensive quaternary structural proteomes from genome sequence

A critical body of knowledge has developed through advances in protein microscopy, protein-fold modeling, structural biology software, availability of sequenced bacterial genomes, large-scale mutation databases, and genome-scale models. Based on these recent advances, we develop a computational framework that; i) identifies the oligomeric structural proteome encoded by an organism's genome from available structural resources; ii) maps multi-strain alleleomic variation, resulting in the structural proteome for a species; and iii) calculates the 3D orientation of proteins across subcellular compartments with residue-level precision. Using the platform, we; iv) compute the quaternary E. coli K-12 MG1655 structural proteome; v) use a dataset of 12,000 mutations to build Random Forest classifiers that can predict the severity of mutations; and, in combination with a genome-scale model that computes proteome allocation, vi) obtain the spatial allocation of the E. coli proteome. Thus, in conjunction with relevant datasets and increasingly accurate computational models, we can now annotate quaternary structural proteomes, at genome-scale, to obtain a molecular-level understanding of whole-cell functions.

Significance

Advancements in experimental and computational methods have revealed the shapes of multi-subunit proteins. The absence of a unified platform that maps actionable datatypes onto these increasingly accurate structures creates a barrier to structural analyses, especially at the genome-scale. Here, we describe QSPACE, a computational annotation platform that evaluates existing resources to identify the best-available structure for each protein in a user's query, maps the 3D location of actionable datatypes ( e.g. , active sites, published mutations) onto the selected structures, and uses third-party APIs to determine the subcellular compartment of all amino acids of a protein. As proof-of-concept, we deployed QSPACE to generate the quaternary structural proteome of E. coli MG1655 and demonstrate two use-cases involving large-scale mutant analysis and genome-scale modelling.

Understanding the Effect of Different Glucose Concentrations in the Oligotrophic Bacterium Bacillus subtilis BS-G1 through Transcriptomics Analysis

Glucose is an important carbon source for microbial growth, and its content in infertile soils is essential for the growth of bacteria. Since the mechanism of oligotrophic bacterium adaptation in barren soils is unclear, this research employed RNA-seq technology to examine the impact of glucose concentration on the oligotrophic bacterium B. subtilis BS-G1 in soil affected by desertification. A global transcriptome analysis (RNA-Seq) revealed that the significantly differentially expressed genes (DEGs) histidine metabolism, glutamate synthesis, the HIF-1 signaling pathway, sporulation, and the TCA cycle pathway of B. subtilis BS-G1 were significantly enriched with a 0.015 g/L glucose concentration (L group), compared to a 10 g/L glucose concentration (H group). The DEGs amino acid system, two-component system, metal ion transport, and nitrogen metabolism system of B. subtilis BS-G1 were significantly enriched in the 5 g/L glucose concentration (M group), compared with the H group. In addition, the present study identified the regulation pattern and key genes under a low-glucose environment (7 mRNAs and 16 sRNAs). This study primarily investigates the variances in the regulatory pathways of the oligotrophic B. subtilis BS-G1, which holds substantial importance in comprehending the mechanism underlying the limited sugar tolerance of oligotrophic bacteria.

A model industrial workhorse: Bacillus subtilis strain 168 and its genome after a quarter of a century

The vast majority of genomic sequences are automatically annotated using various software programs. The accuracy of these annotations depends heavily on the very few manual annotation efforts that combine verified experimental data with genomic sequences from model organisms. Here, we summarize the updated functional annotation of Bacillus subtilis strain 168, a quarter century after its genome sequence was first made public. Since the last such effort 5 years ago, 1168 genetic functions have been updated, allowing the construction of a new metabolic model of this organism of environmental and industrial interest. The emphasis in this review is on new metabolic insights, the role of metals in metabolism and macromolecule biosynthesis, functions involved in biofilm formation, features controlling cell growth, and finally, protein agents that allow class discrimination, thus allowing maintenance management, and accuracy of all cell processes. New 'genomic objects' and an extensive updated literature review have been included for the sequence, now available at the International Nucleotide Sequence Database Collaboration (INSDC: AccNum AL009126.4).