Role of membrane proteins in bacterial synthesis of hyaluronic acid and their potential in industrial production

Gunasekaran, Vijay; Gowdhaman, D.; Venkatachalam, P.

doi:10.1016/j.ijbiomac.2020.08.077

Cited by 13 publications

(9 citation statements)

References 76 publications

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“…S7). These results are in agreement with the previous reports on recombinant B.subtilis that showed the HA Mw can vary from lower than 300 kDa to 4.5 MDa (Westbrook et al 2018a(Westbrook et al , 2018bYang et al 2017) The control mechanism of HA Mw is not clear, due to many intrinsic factors such as HAS enzyme structure and micro-environment, substrate availability, host background and culture condition (Gunasekaran et al 2020;Westbrook et al 2016). It was shown that the concentration of precursor N-GluNAc, which mediates cell wall structure too, strongly affects the Mw of HA products (Chen et al 2009;Jeong et al 2014).…”

Section: Discussionsupporting

confidence: 92%

“…Therefore, it would be advantageous to develop alternative sources for HA production such as GRAS (Generally Recognized As Safe) strains including Bacillus subtilis , Agrobacterium , Escherichia. coli and Lactococcus lactis (Gunasekaran et al 2020 ; Kogan et al 2007 ; Sze et al 2016 ). Among GRAS, B. subtilis strains have several advantages such as high yield and appropriate quality of the final product that proved them as a choice host for HA production (Manfrão‐Netto et al 2022 ; Westbrook et al 2018a ; Westbrook et al 2018b ).…”

Section: Introductionmentioning

confidence: 99%

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Hyaluronic acid production and characterization by novel Bacillus subtilis harboring truncated Hyaluronan Synthase

et al. 2022

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Hyaluronic Acid (HA) is a natural biopolymer that has important physiological and industrial applications due to its viscoelastic and hydrophilic characteristics. The responsible enzyme for HA production is Hyaluronan synthase (HAS). Although in vitro structure–function of intact HAS enzyme has been partly identified, there is no data on in vivo function of truncated HAS forms. In the current study, novel recombinant Bacillus subtilis strains harboring full length (RBSFA) and truncated forms of SeHAS (RBSTr4 and RBSTr3) were developed and HA production was studied in terms of titer, production rate and molecular weight (Mw). The maximum HA titer for RBSFA, RBSTr4 and RBSTr3 was 602 ± 16.6, 503 ± 19.4 and 728 ± 22.9 mg/L, respectively. Also, the HA production rate was 20.02, 15.90 and 24.42 mg/L.h−1, respectively. The findings revealed that RBSTr3 produced 121% and 137% more HA rather than RBSFA and RBSTr4, respectively. More interestingly, the HA Mw was about 60 kDa for all strains which is much smaller than those obtained in prior studies.

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Section: Discussionsupporting

confidence: 92%

Section: Introductionmentioning

confidence: 99%

Hyaluronic acid production and characterization by novel Bacillus subtilis harboring truncated Hyaluronan Synthase

et al. 2022

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“…Based on the above research status at home and abroad, it can be seen that the current research on total factor productivity at home and abroad is mainly focused on energy, agriculture, industry, or environment [21][22][23]. And most studies do not involve the cloud data analysis and evaluation model of the impact of financial structure on China's total factor productivity.…”

Section: Related Workmentioning

confidence: 99%

Construction of Spatiotemporal Difference Image of the Impact of Financial Structure on China’s Total Factor Productivity

2021

Computational Intelligence and Neuroscience

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My country’s current research on the influencing factors of total factor productivity has problems such as single evaluation method, low efficiency, and poor overall level in terms of evaluation methods and evaluation efficiency. Based on this, this study divides the financial structure into three traditional sections, banking, securities, and insurance, and uses the DEA model to study the temporal and spatial differences of the financial structure’s influence on the total factor productivity of the four major political and economic regions of China’s eastern, western, central, and northeastern China. First, establish a DEA model based on data mining algorithms, combine financial data comparisons over the years, to achieve a quantitative analysis of the financial structure’s impact on China’s total factor productivity, calculate financial efficiency, and then combine the DEA analysis data model with the grey correlation method. Analyze its internal influence rules, and design experiments for model verification analysis. The results show that the DEA analysis model can realize 8 iterations of data on the impact of financial structure on China’s total factor productivity, and its evaluation accuracy can reach more than 96.2%.

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“…However, MP expression and optimization is also becoming increasingly important for MCF optimization, e.g., to influence substrate uptake or product transport [ 13 , 14 ]. Secondly, MPs are crucial pathway enzymes for bacterial fermentation of some interesting pharmaceutical or cosmetic products, e.g., hyaluronic acid [ 15 ] or flavonoids [ 16 ], for which functional MP expression often remains a daunting task.…”

Section: Introductionmentioning

confidence: 99%

Dynamic feedback regulation for efficient membrane protein production using a small RNA-based genetic circuit in Escherichia coli

et al. 2022

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Background Membrane proteins (MPs) are an important class of molecules with a wide array of cellular functions and are part of many metabolic pathways. Despite their great potential—as therapeutic drug targets or in microbial cell factory optimization—many challenges remain for efficient and functional expression in a host such as Escherichia coli. Results A dynamically regulated small RNA-based circuit was developed to counter membrane stress caused by overexpression of different MPs. The best performing small RNAs were able to enhance the maximum specific growth rate with 123%. On culture level, the total MP production was increased two-to three-fold compared to a system without dynamic control. This strategy not only improved cell growth and production of the studied MPs, it also suggested the potential use for countering metabolic burden in general. Conclusions A dynamically regulated feedback circuit was developed that can sense metabolic stress caused by, in casu, the overexpression of an MP and responds to it by balancing the metabolic state of the cell and more specifically by downregulating the expression of the MP of interest. This negative feedback mechanism was established by implementing and optimizing simple-to-use genetic control elements based on post-transcriptional regulation: small non-coding RNAs. In addition to membrane-related stress when the MP accumulated in the cytoplasm as aggregates, the sRNA-based feedback control system was still effective for improving cell growth but resulted in a decreased total protein production. This result suggests promiscuity of the MP sensor for more than solely membrane stress.

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Role of membrane proteins in bacterial synthesis of hyaluronic acid and their potential in industrial production

Cited by 13 publications

References 76 publications

Hyaluronic acid production and characterization by novel Bacillus subtilis harboring truncated Hyaluronan Synthase

Hyaluronic acid production and characterization by novel Bacillus subtilis harboring truncated Hyaluronan Synthase

Construction of Spatiotemporal Difference Image of the Impact of Financial Structure on China’s Total Factor Productivity

Dynamic feedback regulation for efficient membrane protein production using a small RNA-based genetic circuit in Escherichia coli

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