Systems Metabolic Engineering of Escherichia coli Improves Coconversion of Lignocellulose-Derived Sugars

Current models in bacterial hemicellulase-encoding gene regulation

The discovery and characterization of bacterial carbohydrate-active enzymes is a fundamental component of biotechnology innovation, particularly for renewable fuels and chemicals; however, these studies have increasingly transitioned to exploring the complex regulation required for recalcitrant polysaccharide utilization. This pivot is largely due to the current need to engineer and optimize enzymes for maximal degradation in industrial or biomedical applications. Given the structural simplicity of a single cellulose polymer, and the relatively few enzyme classes required for complete bioconversion, the regulation of cellulases in bacteria has been thoroughly discussed in the literature. However, the diversity of hemicelluloses found in plant biomass and the multitude of carbohydrate-active enzymes required for their deconstruction has resulted in a less comprehensive understanding of bacterial hemicellulase-encoding gene regulation. Here we review the mechanisms of this process and common themes found in the transcriptomic response during plant biomass utilization. By comparing regulatory systems from both Gram-negative and Gram-positive bacteria, as well as drawing parallels to cellulase regulation, our goals are to highlight the shared and distinct features of bacterial hemicellulase-encoding gene regulation and provide a set of guiding questions to improve our understanding of bacterial lignocellulose utilization. KEY POINTS: • Canonical regulatory mechanisms for bacterial hemicellulase-encoding gene expression include hybrid two-component systems (HTCS), extracytoplasmic function (ECF)-σ/anti-σ systems, and carbon catabolite repression (CCR). • Current transcriptomic approaches are increasingly being used to identify hemicellulase-encoding gene regulatory patterns coupled with computational predictions for transcriptional regulators. • Future work should emphasize genetic approaches to improve systems biology tools available for model bacterial systems and emerging microbes with biotechnology potential. Specifically, optimization of Gram-positive systems will require integration of degradative and fermentative capabilities, while optimization of Gram-negative systems will require bolstering the potency of lignocellulolytic capabilities.

Co-utilization of carbon sources in microorganisms for the bioproduction of chemicals

Carbon source is crucial for the cell growth and metabolism in microorganisms, and its utilization significantly affects the synthesis efficiency of target products in microbial cell factories. Compared with a single carbon source, co-utilizing carbon sources provide an alternative approach to optimize the utilization of different carbon sources for efficient biosynthesis of many chemicals with higher titer/yield/productivity. However, the efficiency of bioproduction is significantly limited by the sequential utilization of a preferred carbon source and secondary carbon sources, attributed to carbon catabolite repression (CCR). This review aimed to introduce the mechanisms of CCR and further focus on the summary of the strategies for co-utilization of carbon sources, including alleviation of CCR, engineering of the transport and metabolism of secondary carbon sources, compulsive co-utilization in single culture, co-utilization of carbon sources via co-culture, and evolutionary approaches. The findings of representative studies with a significant improvement in the bioproduction of chemicals via the co-utilization of carbon sources were discussed in this review. It suggested that by combining rational metabolic engineering and irrational evolutionary approaches, co-utilizing carbon sources can significantly contribute to the bioproduction of chemicals.

Synergistic application of atmospheric and room temperature plasma mutagenesis and adaptive laboratory evolution improves the tolerance of Escherichia coli to L-cysteine

L-Cysteine production through fermentation stands as a promising technology. However, excessive accumulation of L-cysteine poses a challenge due to the potential to inflict damage on cellular DNA. In this study, we employed a synergistic approach encompassing atmospheric and room temperature plasma mutagenesis (ARTP) and adaptive laboratory evolution (ALE) to improve L-cysteine tolerance in Escherichia coli. ARTP-treated populations obtained substantial enhancement in L-cysteine tolerance by ALE. Whole-genome sequencing, transcription analysis, and reverse engineering, revealed the pivotal role of an effective export mechanism mediated by gene eamB in augmenting L-cysteine resistance. The isolated tolerant strain, 60AP03/pTrc-cysEf , achieved a 2.2-fold increase in L-cysteine titer by overexpressing the critical gene cysEf during batch fermentation, underscoring its enormous potential for L-cysteine production. The production evaluations, supplemented with L-serine, further demonstrated the stability and superiority of tolerant strains in L-cysteine production. Overall, our work highlighted the substantial impact of the combined ARTP and ALE strategy in increasing the tolerance of E. coli to L-cysteine, providing valuable insights into improving L-cysteine overproduction, and further emphasized the potential of biotechnology in industrial production.

Engineering the Metabolic Landscape of Microorganisms for Lignocellulosic Conversion

Bacteria and yeast are being intensively used to produce biofuels and high-added-value products by using plant biomass derivatives as substrates. The number of microorganisms available for industrial processes is increasing thanks to biotechnological improvements to enhance their productivity and yield through microbial metabolic engineering and laboratory evolution. This is allowing the traditional industrial processes for biofuel production, which included multiple steps, to be improved through the consolidation of single-step processes, reducing the time of the global process, and increasing the yield and operational conditions in terms of the desired products. Engineered microorganisms are now capable of using feedstocks that they were unable to process before their modification, opening broader possibilities for establishing new markets in places where biomass is available. This review discusses metabolic engineering approaches that have been used to improve the microbial processing of biomass to convert the plant feedstock into fuels. Metabolically engineered microorganisms (MEMs) such as bacteria, yeasts, and microalgae are described, highlighting their performance and the biotechnological tools that were used to modify them. Finally, some examples of patents related to the MEMs are mentioned in order to contextualize their current industrial use.

Adaptive Laboratory Evolution of Microorganisms: Methodology and Application for Bioproduction

Adaptive laboratory evolution (ALE) is a useful experimental methodology for fundamental scientific research and industrial applications to create microbial cell factories. By using ALE, cells are adapted to the environment that researchers set based on their objectives through the serial transfer of cell populations in batch cultivations or continuous cultures and the fitness of the cells (i.e., cell growth) under such an environment increases. Then, omics analyses of the evolved mutants, including genome sequencing, transcriptome, proteome and metabolome analyses, are performed. It is expected that researchers can understand the evolutionary adaptation processes, and for industrial applications, researchers can create useful microorganisms that exhibit increased carbon source availability, stress tolerance, and production of target compounds based on omics analysis data. In this review article, the methodologies for ALE in microorganisms are introduced. Moreover, the application of ALE for the creation of useful microorganisms as cell factories has also been introduced.

Minireview: Engineering evolution to reconfigure phenotypic traits in microbes for biotechnological applications

Adaptive laboratory evolution (ALE) has long been used as the tool of choice for microbial engineering applications, ranging from the production of commodity chemicals to the innovation of complex phenotypes. With the advent of systems and synthetic biology, the ALE experimental design has become increasingly sophisticated. For instance, implementation of in silico metabolic model reconstruction and advanced synthetic biology tools have facilitated the effective coupling of desired traits to adaptive phenotypes. Furthermore, various multi-omic tools now enable in-depth analysis of cellular states, providing a comprehensive understanding of the biology of even the most genomically perturbed systems. Emerging machine learning approaches would assist in streamlining the interpretation of massive and multiplexed datasets and promoting our understanding of complexity in biology. This review covers some of the representative case studies among the 700 independent ALE studies reported to date, outlining key ideas, principles, and important mechanisms underlying ALE designs in bioproduction and synthetic cell engineering, with evidence from literatures to aid comprehension.