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Considered a "Generally Recognized As Safe" (GRAS) bacterium, the plant growth-promoting rhizobacterium Paenibacillus has been widely applied in: agriculture, medicine, industry, and environmental remediation. Paenibacillus species not only accelerate plant growth and degrade toxic substances in wastewater and soil but also produce industrially-relevant enzymes and antimicrobial peptides. Due to a lack of genetic manipulation tools and methods, exploitation of the bioresources of naturally isolated Paenibacillus species has long been limited. Genetic manipulation tools and methods continue to improve in Paenibacillus, such as shuttle plasmids, promoters, and genetic tools of CRISPR. Furthermore, genetic transformation systems develop gradually, including: penicillin-mediated transformation, electroporation, and magnesium amino acid-mediated transformation. As genetic manipulation methods of homologous recombination and CRISPR-mediated editing system have developed gradually, Paenibacillus has come to be regarded as a promising microbial chassis for biomanufacturing, expanding its application scope, such as: industrial enzymes, bioremediation and bioadsorption, surfactants, and antibacterial agents. In this review, we describe the applications of Paenibacillus bioproducts, and then discuss recent advances and future challenges in the development of genetic manipulation systems in this genus. This work highlights the potential of Paenibacillus as a new microbial chassis for mining bioresources. [ABSTRACT FROM AUTHOR]

Gamma-aminobutyric acid (GABA) is a non-protein amino acid which is widely applied in agriculture and pharmaceutical additive industries. GABA is synthesized from glutamate through irreversible α-decarboxylation by glutamate decarboxylase. Recently, microbial synthesis has become an inevitable trend to produce GABA due to its sustainable characteristics. Therefore, reasonable microbial platform design and metabolic engineering strategies for improving production of GABA are arousing a considerable attraction. The strategies concentrate on microbial platform optimization, fermentation process optimization, rational metabolic engineering as key metabolic pathway modification, promoter optimization, site-directed mutagenesis, modular transporter engineering, and dynamic switch systems application. In this review, the microbial producers for GABA were summarized, including lactic acid bacteria, Corynebacterium glutamicum, and Escherichia coli, as well as the efficient strategies for optimizing them to improve the production of GABA. [ABSTRACT FROM AUTHOR]

Central carbon metabolism (CCM), including glycolysis, tricarboxylic acid cycle and the pentose phosphate pathway, is the most fundamental metabolic process in the activities of living organisms that maintains normal cellular growth. CCM has been widely used in microbial metabolic engineering in recent years due to its unique regulatory role in cellular metabolism. Using yeast and Escherichia coli as the representative organisms, we summarized the metabolic engineering strategies on the optimization of CCM in eukaryotic and prokaryotic microbial chassis, such as the introduction of heterologous CCM metabolic pathways and the optimization of key enzymes or regulatory factors, to lay the groundwork for the future use of CCM optimization in metabolic engineering. Furthermore, the bottlenecks in the application of CCM optimization in metabolic engineering and future application prospects are summarized. [ABSTRACT FROM AUTHOR]

Accumulating plastics in the biosphere implicates adverse effects, raising serious concern among scientists worldwide. Plastic waste in nature disintegrates into microplastics. Because of their minute appearance, at a scale of <5 mm, microplastics easily penetrate different pristine water bodies and terrestrial niches, posing detrimental effects on flora and fauna. The potential bioremediative application of microbial enzymes is a sustainable solution for the degradation of microplastics. Studies have reported a plethora of bacterial and fungal species that can degrade synthetic plastics by excreting plasticdegrading enzymes. Identified microbial enzymes, such as IsPETase and IsMHETase from Ideonella sakaiensis 201-F6 and Thermobifida fusca cutinase (Tfc), are able to depolymerize plastic polymer chains producing ecologically harmless molecules like carbon dioxide and water. However, thermal stability and pH sensitivity are among the biochemical limitations of the plasticdegrading enzymes that affect their overall catalytic activities. The application of biotechnological approaches improves enzyme action and production. Protein-based engineering yields enzyme variants with higher enzymatic activity and temperature-stable properties, while site-directed mutagenesis using the Escherichia coli model system expresses mutant thermostable enzymes. Furthermore, microalgal chassis is a promising model system for “green” microplastic biodegradation. Hence, the bioremediative properties of microbial enzymes are genuinely encouraging for the biodegradation of synthetic microplastic polymers. [ABSTRACT FROM AUTHOR]

Metabolic engineering (ME) and synthetic biology (SynBio) are two intersecting fields with different focal points. While SynBio focuses more on genomic aspects to build novel cell devices, ME emphasizes the phenotypic outputs (e.g., production). SynBio has the potential to revolutionize the bio-productions; however, the introduction of synthetic devices/pathways often consumes significant cellular resources and incurs fitness costs. Currently, SynBio applications still lack guidelines in re-allocating cellular carbon and energy fluxes. To resolve this, ME principles may help the SynBio community. First, 13C MFA (metabolic flux analysis) can characterize the burdens of genetic infrastructures and reveal optimal strategies for distributing cellular resources. Second, novel microbial chassis should be explored to employ their unique metabolic features for product synthesis. Third, standardization and classification of bio-production papers will not only improve the communication between ME and SynBio, but also facilitate text mining and machine learning to harness information for rational strain design. Ultimately, the data-driven modeling and 13C MFA will be integral components of the SynBio design-build-test-learn cycle for generating novel microbial cell factories. [ABSTRACT FROM AUTHOR]