Construction of synthetic microbial consortia for 2-keto-L-gulonic acid biosynthesis

Rhodotorula mucilaginosa A8, a potential helper strain in a vitamin C microbial fermentation process

In the vitamin C microbial fermentation system, oxidative stress limits the growth and 2-keto-l-gulonic acid (2-KLG, the precursor of vitamin C) production of Ketogulonicigenium vulgare. Most Bacillus strains, as helper strains, have been reported to release key biomolecules to reduce oxidative stress and promote the growth and 2-KLG production of K. vulgare. To understand the specific mechanism by which the helper strain and K. vulgare interact to reduce oxidative stress, a novel helper strain, Rhodotorula mucilaginosa A8, was used to construct a consortium in the co-culture fermentation system. Based on the activities of the antioxidant enzymes and quantitative polymerase chain reaction (qPCR) analysis, R. mucilaginosa A8 could reduce oxidative stress and increase 2-KLG production in K. vulgare by upregulating antioxidant enzyme activities and related gene-expression levels. In addition, the carotenoids of R. mucilaginosa promoted 2-KLG production in K. vulgare. Coculture of R. mucilaginosa with K. vulgare increased the yield of carotenoids. This study suggested that helper strains with the ability to reduce oxidative stress in K. vulgare would likely act as potential helper strains for facilitating 2-KLG biosynthesis. This work could provide a theoretical basis for the search for potential helper strains for vitamin C microbial fermentation and for the construction of synthetic microbial communities to produce valuable products.

Probabilistic Bayesian Deep Learning Approach for Online Forecasting of Fed-Batch Fermentation

The microbial fermentation process often involves various biological metabolic reactions and chemical processes. The mixed bacterial culture process of 2-keto-l-gulonic acid has strong nonlinear and time-varying characteristics. In this study, a probabilistic Bayesian deep learning approach is proposed to obtain a highly accurate and robust prediction of product formation. The Bayesian optimized deep neural network (BODNN) is utilized as basic model for prediction, the structural parameters of which are optimized. Then, the training datasets are classified into different categories according to the prior evaluation of prediction error. The final forecasting is a weighted combination of BODNN models based on the Bayesian hybrid method. The weights can be interpreted as Bayesian posterior probabilities and are computed recursively. The validation of 95 industrial batches is carried out, and the average root mean square errors are 1.51 and 2.01% for 4 and 8 h ahead prediction, respectively. The results illustrate that the proposed approach can capture the dynamics of fermentation batches and is suitable for online process monitoring.

Genetic and biochemical strategies for regulation of L-ascorbic acid biosynthesis in plants through the L-galactose pathway

Vitamin C (L-ascorbic acid, AsA) is an essential compound with pleiotropic functions in many organisms. Since its isolation in the last century, AsA has attracted the attention of the scientific community, allowing the discovery of the L-galactose pathway, which is the main pathway for AsA biosynthesis in plants. Thus, the aim of this review is to analyze the genetic and biochemical strategies employed by plant cells for regulating AsA biosynthesis through the L-galactose pathway. In this pathway, participates eight enzymes encoded by the genes PMI, PMM, GMP, GME, GGP, GPP, GDH, and GLDH. All these genes and their encoded enzymes have been well characterized, demonstrating their participation in AsA biosynthesis. Also, have described some genetic and biochemical strategies that allow its regulation. The genetic strategy includes regulation at transcriptional and post-transcriptional levels. In the first one, it was demonstrated that the expression levels of the genes correlate directly with AsA content in the tissues/organs of the plants. Also, it was proved that these genes are light-induced because they have light-responsive promoter motifs (e.g., ATC, I-box, GT1 motif, etc.). In addition, were identified some transcription factors that function as activators (e.g., SlICE1, AtERF98, SlHZ24, etc.) or inactivators (e.g., SlL1L4, ABI4, SlNYYA10) regulate the transcription of these genes. In the second one, it was proved that some genes have alternative splicing events and could be a mechanism to control AsA biosynthesis. Also, it was demonstrated that a conserved cis-acting upstream open reading frame (5'-uORF) located in the 5'-untranslated region of the GGP gene induces its post-transcriptional repression. Among the biochemical strategies discovered is the control of the enzyme levels (usually by decreasing their quantities), control of the enzyme catalytic activity (by increasing or decreasing its activity), feedback inhibition of some enzymes (GME and GGP), subcellular compartmentation of AsA, the metabolon assembly of the enzymes, and control of AsA biosynthesis by electron flow. Together, the construction of this basic knowledge has been establishing the foundations for generating genetically improved varieties of fruits and vegetables enriched with AsA, commonly used in animal and human feed.

Design and construction of microbial cell factories based on systems biology

Environmental sustainability is an increasingly important issue in industry. As an environmentally friendly and sustainable way, constructing microbial cell factories to produce all kinds of valuable products has attracted more and more attention. In the process of constructing microbial cell factories, systems biology plays a crucial role. This review summarizes the recent applications of systems biology in the design and construction of microbial cell factories from four perspectives, including functional genes/enzymes discovery, bottleneck pathways identification, strains tolerance improvement and design and construction of synthetic microbial consortia. Systems biology tools can be employed to identify functional genes/enzymes involved in the biosynthetic pathways of products. These discovered genes are introduced into appropriate chassis strains to build engineering microorganisms capable of producing products. Subsequently, systems biology tools are used to identify bottleneck pathways, improve strains tolerance and guide design and construction of synthetic microbial consortia, resulting in increasing the yield of engineered strains and constructing microbial cell factories successfully.

Combined engineering of l-sorbose dehydrogenase and fermentation optimization to increase 2-keto-l-gulonic acid production in Escherichia coli

One-step fermentation to produce 2-keto-l-gulonic acid (2-KLG), the precursor of vitamin C, is a long-term goal. Improvement of the enzyme's activity through engineering could benefit 2-KLG production. This study aimed to conduct a semi-rational design of l-sorbose dehydrogenase (SDH) through structure-directed, to screen mutants that could enhance the 2-KLG titer. First, the predicted structure of SDH was obtained using AlphaFold2. The key mutation sites in the substrate pocket were identified by Ala scanning. Subsequently, the mutant V336I/V368A was obtained by iterative saturation mutagenesis, which increased the yield of 2-KLG 1.9-fold. Finally, 5.03 g/L of 2-KLG was obtained by a two-stage temperature control fermentation method, and the conversion rate was 50%. Furthermore, experiments showed that knockdown of the l-sorbose-associated phosphotransferase system delays 2-KLG production. The results show that the production of 2-KLG was effectively increased through a combination of SDH engineering and fermentation optimization.

Construction of microbial consortia for microbial degradation of complex compounds

Increasingly complex synthetic environmental pollutants are prompting further research into bioremediation, which is one of the most economical and safest means of environmental restoration. From the current research, using microbial consortia to degrade complex compounds is more advantageous compared to using isolated bacteria, as the former is more adaptable and stable within the growth environment and can provide a suitable catalytic environment for each enzyme required by the biodegradation pathway. With the development of synthetic biology and gene-editing tools, artificial microbial consortia systems can be designed to be more efficient, stable, and robust, and they can be used to produce high-value-added products with their strong degradation ability. Furthermore, microbial consortia systems are shown to be promising in the degradation of complex compounds. In this review, the strategies for constructing stable and robust microbial consortia are discussed. The current advances in the degradation of complex compounds by microbial consortia are also classified and detailed, including plastics, petroleum, antibiotics, azo dyes, and some pollutants present in sewage. Thus, this paper aims to support some helps to those who focus on the degradation of complex compounds by microbial consortia.

Metabolomic insight into the synergistic mechanism of action of a bacterial consortium in plant growth promotion

It has been established that a consortium consisting of compatible plant growth promoting rhizobacterial strains outperforms their individual impacts on plant attributes. While the phenomenon of synergism is extensively reported, the mechanism that underpins it is yet to be elucidated. In the present study the impact of three plant growth promoting bacteria, Azotobacter chroococcum (A), Priestia megaterium (formerly Bacillus megaterium) (B), and Pseudomonas sp. SK3 (P) was studied as a consortium on the growth attributes of pigeonpea. In addition, microbe-microbe interactions were investigated through metabolomic profiling to understand the mechanism of synergism. Plant growth experiments revealed that bacterial consortium A + B + P showed a significant increase in plant attributes such as shoot length, root length, fresh weight, and dry weight as compared to monocultures and two-membered consortia. Metabolomic profiling through high resolution liquid chromatograph mass spectrometer revealed the presence of a few bioactive compounds in the consortium that might play a potential role in the enhancement of biometric parameters of the plant. Several compounds, such as antipyrine, 6,6-dimethoxy-2,5,5-trimethyl-2-hexene, N-methyltryptamine, 2,2-dimethyl-3,4-bis(4-methoxyphenyl)-2H-1-benzopyran-7-ol acetate, N6-hydroxy-l-lysine, and l-furosin, were detected in the metabolome of the consortium, which was unique among all the treatments. The study also detected a few metabolites involved in sphingolipid biosynthesis (ketosphinganine and sphinganine) known for cell signaling in the consortium. This unravels the possible mechanism of synergism between bacterial strains in a consortium. The metabolomic profile would be helpful to strategically develop unique and more effective consortia that are tailored to the soil type.

Microbial Interactions in a Vitamin C Industrial Fermentation System: Novel Insights and Perspectives

In industrial production, the precursor of l-ascorbic acid (L-AA, also referred to as vitamin C), 2-keto-l-gulonic acid (2-KLG), is mainly produced using a classic two-step fermentation process performed by Gluconobacter oxydans, Bacillus megaterium, and Ketogulonicigenium vulgare. In the second step of the two-step fermentation process, the microbial consortium of K. vulgare and B. megaterium is used to achieve 2-KLG production. K. vulgare can transform l-sorbose to 2-KLG, but the yield of 2-KLG is much lower in the monoculture than in the coculture fermentation system. The relationship between the two strains is too diverse to analyze and has been a hot topic in the field of vitamin C fermentation. With the development of omics technology, the relationships between the two strains are well explained; nevertheless, the cell-cell communication is unclear. In this review, based on current omics results, the interactions between the two strains are summarized, and the potential cell-cell communications between the two strains are discussed, which will shed a light on the further understanding of synthetic consortia.

Toward merging bottom-up and top-down model-based designing of synthetic microbial communities

The increasing interest of microbial communities as promising biocatalyst is leading an intense effort into the development of computational frameworks assisting the analysis and rational engineering of such complex ecosystems. Here, we critically review the recent computational and model-guided advances in the system-level engineering of microbiome, including both the rational bottom-up and the evolutionary top-down approaches. Furthermore, we highlight modeling and computational methods supporting both engineering paradigms. Finally, we discuss the advantages of combining both strategies into a hybrid top-down/bottom-up (middle-out) strategy to engineer synthetic microbial communities with improved performance and scope.

Combined evolutionary and metabolic engineering improve 2-keto-L-gulonic acid production in Gluconobacter oxydans WSH-004

The direct fermentation of the precursor of vitamin C, 2-keto-L-gulonic acid (2-KLG), has been a long-pursued goal. Previously, a strain of Gluconobacter oxydans WSH-004 was isolated that produced 2.5 g/L 2-KLG, and through adaptive evolution engineering, the strain G. oxydans MMC3 could tolerate 300 g/L D-sorbitol. This study verified that the sndh-sdh gene cluster encoded two key dehydrogenases for the 2-KLG biosynthesis pathway in this strain. Then G. oxydans MMC3 further evolved through adaptive evolution to G. oxydans 2-KLG5, which can tolerate high concentrations of D-sorbitol and 2-KLG. Finally, by increasing the gene expression levels of the sndh-sdh and terminal oxidase cyoBACD in G. oxydans 2-KLG5, the 2-KLG accumulation in the 5-L fermenter increased to 45.14 g/L by batch fermentation. The results showed that combined evolutionary and metabolic engineering efficiently improved the direct production of 2-KLG from D-sorbitol in G. oxydans.