Metabolic engineering of long chain-polyunsaturated fatty acid biosynthetic pathway in oleaginous fungus for dihomo-gamma linolenic acid production

Chutrakul, Chanikul; Jeennor, Sukanya; Panchanawaporn, Sarocha; Cheawchanlertfa, Pattsarun; Suttiwattanakul, Sarinya; Veerana, Mayura; Laoteng, Kobkul

doi:10.1016/j.jbiotec.2015.12.003

Cited by 33 publications

(21 citation statements)

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“…Interestingly, the supplementation of ML into the cheap CSH medium could significantly enhance the biomass production. In addition, the significant increase in DGLA production by adding low amount of ML (1% v/v) into the CSH culture was a result of the increase of DGLA proportion up to 22.1 ± 2.3% in TFA that was very high as compared with the previous report of the same fungal strain (1.8-2.0% DGLA in TFA) (Chutrakul et al, 2016). Low DGLA proportions have also been reported for the recombinant strains of Mucor circinelloides (5.7% DGLA in TFA) and Saccharomyces cerevisiae (3.5% DGLA in TFA) even though they were challenged by cultivating at low temperatures (Yazawa et al, 2007;Khan et al, 2019).…”

Section: Strains Parameters Referencescontrasting

confidence: 51%

“…These might be explained by the structure role of PUFAs as constituents in biological membranes. It has been previously documented that DGLA and GLA were mostly esterified into phospholipid fraction of this engineered strain of A. oryzae even though they were also distributed into the neutral lipids, particularly in triacylglycerol (Chutrakul et al, 2016). However, it has been previously reported that the lipid over-production in oleaginous species is usually found at the end of growth phase, called lipid-accumulating phase, in which the nitrogen source is depleted and carbon source remains available (Papanikolaou and Aggelis, 2011;Lamers et al, 2016).…”

Section: Strains Parameters Referencesmentioning

confidence: 86%

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Physiological Traits of Dihomo-γ-Linolenic Acid Production of the Engineered Aspergillus oryzae by Comparing Mathematical Models

et al. 2020

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Dihomo-γ-linolenic acid (DGLA; C20:3 n-6) is expected to dominate the functional ingredients market for its role in anti-inflammation and anti-proliferation. The DGLA production by the engineered strain of Aspergillus oryzae with overexpressing Pythium 6-desaturase and 6-elongase genes was investigated by manipulating the nutrient and fermentation regimes. Of the nitrogen sources tested, the maximum biomass and DGLA titers were obtained in the cultures using NaNO 3 grown at pH 6.0. For establishing economically feasible process of DGLA production, the cost-effective medium was developed by using cassava starch hydrolysate (CSH) and NaNO 3 as carbon and nitrogen sources, respectively. The supplementation with 1% (v/v) mother liquor (ML) into the CSH medium promoted the specific yield of DGLA production (Y DGLA/X) comparable with the culture grown in the defined NaNO 3 medium, and the DGLA proportion was over 22% in total fatty acid (TFA). Besides, the GLA was also generated at a similar proportion (about 25% in TFA). The mathematical models of the cultures grown in the defined NaNO 3 and CSH/ML media were generated, describing that the lipid and DGLA were growth-associated metabolites corresponding to the relevant kinetic parameters of fermentations. The controlled mode of submerged fermentation of the engineered strain was explored for governing the PUFA biosynthesis and lipid-accumulating process in relation to the biomass production. This study provides an informative perspective in the n-6 fatty acid production through physiological manipulation, thus leading to a prospect in viable production of the DGLA-enriched oil by the engineered strain.

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Section: Strains Parameters Referencescontrasting

confidence: 51%

Section: Strains Parameters Referencesmentioning

confidence: 86%

Physiological Traits of Dihomo-γ-Linolenic Acid Production of the Engineered Aspergillus oryzae by Comparing Mathematical Models

et al. 2020

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“…The protein sequences of SARS-CoV-2 were downloaded from GenBank (Accession number: MN908947.3). According to the optimized genetic algorithm 49 , the amino-acid sequences were converted into E. coli codon-optimized gene sequences. Subsequently, the sequences of optimized genes were synthesized by Sangon Biotech.…”

Section: Methodsmentioning

confidence: 99%

SARS-CoV-2 proteome microarray for global profiling of COVID-19 specific IgG and IgM responses

et al. 2020

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We still know very little about how the human immune system responds to SARS-CoV-2. Here we construct a SARS-CoV-2 proteome microarray containing 18 out of the 28 predicted proteins and apply it to the characterization of the IgG and IgM antibodies responses in the sera from 29 convalescent patients. We find that all these patients had IgG and IgM antibodies that specifically bind SARS-CoV-2 proteins, particularly the N protein and S1 protein. Besides these proteins, significant antibody responses to ORF9b and NSP5 are also identified. We show that the S1 specific IgG signal positively correlates with age and the level of lactate dehydrogenase (LDH) and negatively correlates with lymphocyte percentage. Overall, this study presents a systemic view of the SARS-CoV-2 specific IgG and IgM responses and provides insights to aid the development of effective diagnostic, therapeutic and vaccination strategies.

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“…The protein sequences of SARS-CoV-2 were downloaded from GenBank (Accession number: MN908947.3). According to the optimized genetic algorithm 28 , the amino acid sequences was converted into E.coli codon-optimized gene sequences. Subsequently, the sequence optimized genes were synthesized by Sangon Biotech.…”

Section: Construction Of Expression Vectorsmentioning

confidence: 99%

Global profiling of SARS-CoV-2 specific IgG/ IgM responses of convalescents using a proteome microarray

Jiang

Yang

Zhang

et al. 2020

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COVID-19 is caused by SARS-CoV-2, and has become a global pandemic. There is no highly effective medicine or vaccine, most of the patients were recovered by their own immune response, especially the virus specific IgG and IgM responses. However, the IgG/ IgM responses is barely known. To enable the global understanding of SARS-CoV-2 specific IgG/ IgM responses, a SARS-CoV-2 proteome microarray with 18 out of the 28 predicted proteins was constructed. The microarray was applied to profile the IgG/ IgM responses with 29 convalescent sera. The results suggest that at the convalescent phase 100% of patients had IgG/ IgM responses to SARS-CoV-2, especially to protein N, S1 but not S2. S1 purified from mammalian cell demonstrated the highest performance to differentiate COVID-19 patients from controls. Besides protein N and S1, significant antibody responses to ORF9b and NSP5 were also identified. Indepth analysis showed that the level of S1 IgG positively correlate to age and the level of LDH (lactate dehydrogenase), especially for women, while the level of S1 IgG negatively correlate to Ly% (Lymphocyte percentage). This study presents the first whole picture of the SARS-CoV-2 specific IgG/ IgM responses, and provides insights to develop precise immuno-diagnostics, effective treatment and vaccine. Highlights• A SARS-CoV-2 proteome microarray contains 18 of the 28 predicted proteins• The 1 st global picture of the SARS-CoV-2 specific IgG/ IgM response reveals that at the convalescent phase, 100% of patients have IgG/ IgM responses to protein N and S1• Significant antibody responses against ORF9b and NSP5 were identified • Protein S1 specific IgG positively correlates to age and LDH, while negatively to Ly%

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Metabolic engineering of long chain-polyunsaturated fatty acid biosynthetic pathway in oleaginous fungus for dihomo-gamma linolenic acid production

Cited by 33 publications

References 31 publications

Physiological Traits of Dihomo-γ-Linolenic Acid Production of the Engineered Aspergillus oryzae by Comparing Mathematical Models

Physiological Traits of Dihomo-γ-Linolenic Acid Production of the Engineered Aspergillus oryzae by Comparing Mathematical Models

SARS-CoV-2 proteome microarray for global profiling of COVID-19 specific IgG and IgM responses

Global profiling of SARS-CoV-2 specific IgG/ IgM responses of convalescents using a proteome microarray

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