Influence of exogenous phytohormone supplementation on the pigment and fatty acid content of three marine diatoms

Fierli, David; Aranyos, Anita; Barone, Maria Elena; Parkes, Rachel; Touzet, Nicolas

doi:10.1007/s00253-022-12140-5

Cited by 12 publications

(8 citation statements)

References 83 publications

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“…Wu et al [ 70 ] also found the strain-specific influence of ABA on Chlorella when the biomass production of FACHB31 strain was not affected by ABA in the range of 0.4 to 75 µM, while the biomass yield of ZF strain was promoted and increased by 1.4-fold at maximum. Fiery et al [ 66 ] examined low ABA concentrations of 0.5 to 5 µM, which are close to the most effective ABA concentration of ABA in our study, and observed a weak induction of ABA on biomass yield of Phaeodactylum tricornutum and no effect on Stauroneis sp and Nitzschia sp. Contrary to some works on different Chlorella species [ 15 , 70 , 74 ], no effect on growth parameters of C. vulgaris was observed [ 75 ] when comparable to our range ABA concentrations were applied.…”

Section: Discussionsupporting

confidence: 74%

“…Unlike the population growth and biomass yield of C. zofingiensis , accumulation of the tested biomolecules demonstrated nonlinear dependence on the ABA concentrations. This pattern was also observed in relation to the effect of other phytohormones on the production of lipids and pigments [ 15 , 66 , 84 ] and a well-known effect in pharmaceutics [ 85 , 86 ]. Clearly, this pattern is also species-specific [ 66 , 87 ].…”

Section: Discussionmentioning

confidence: 58%

“…This pattern was also observed in relation to the effect of other phytohormones on the production of lipids and pigments [ 15 , 66 , 84 ] and a well-known effect in pharmaceutics [ 85 , 86 ]. Clearly, this pattern is also species-specific [ 66 , 87 ]. Thus, a wider range of phytohormone concentrations needs to be studied to clarify the optimal concentration for the induction of the target metabolites in each algae species of industrial interest.…”

Section: Discussionmentioning

confidence: 58%

“…However, phytohormone applications as the inductors of microalgae productivity are poorly studied, and previous results have to be proven for a wide range of species of industrial interest. To date, only a few studies, including our research on Scenedesmus quadricauda , have been conducted on microalgae using ABA in low concentrations relevant to that in hydroponic wastewater [ 13 , 14 , 15 , 66 ].…”

Section: Discussionmentioning

confidence: 99%

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Effect of Abscisic Acid on Growth, Fatty Acid Profile, and Pigment Composition of the Chlorophyte Chlorella (Chromochloris) zofingiensis and Its Co-Culture Microbiome

Kozlova

Карташов

Zadneprovskaya

et al. 2023

Life

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Microalga Chlorella (Chromochloris) zofingiensis has been gaining increasing attention of investigators as a potential competitor to Haematococcus pluvialis for astaxanthin and other xanthophylls production. Phytohormones, including abscisic acid (ABA), at concentrations relevant to that in hydroponic wastewater, have proven themselves as strong inductors of microalgae biomass productivity and biosynthesis of valuable molecules. The main goal of this research was to evaluate the influence of phytohormone ABA on the physiology of C. zofingiensis in a non-aseptic batch experiment. Exogenous ABA stimulated C. zofingiensis cell division, biomass production, as well as chlorophyll, carotenoid, and lipid biosynthesis. The relationship between exogenous ABA concentration and the magnitude of the observed effects was non-linear, with the exception of cell growth and biomass production. Fatty acid accumulation and composition depended on the concentration of ABA tested. Exogenous ABA induced spectacular changes in the major components of the culture microbiome of C. zofingiensis. Thus, the abundance of the representatives of the genus Rhodococcus increased drastically with an increase in ABA concentration, whereas the abundance of the representatives of Reyranella and Bradyrhizobium genera declined. The possibilities of exogenous ABA applications for the enhancing of the biomass, carotenoid, and fatty acid productivity of the C. zofingiensis cultures are discussed.

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Section: Discussionsupporting

confidence: 74%

Section: Discussionmentioning

confidence: 58%

Section: Discussionmentioning

confidence: 58%

Section: Discussionmentioning

confidence: 99%

See 2 more Smart Citations

Effect of Abscisic Acid on Growth, Fatty Acid Profile, and Pigment Composition of the Chlorophyte Chlorella (Chromochloris) zofingiensis and Its Co-Culture Microbiome

Kozlova

Карташов

Zadneprovskaya

et al. 2023

Life

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“…Then, the freshly prepared phytohormones were added to the flasks at specific concentrations ( Supplemental Table S1 ). The concentration of phytohormones was based on previous studies (Chu et al 2019; Fierli et al 2022; Mc Gee et al 2020). Each treatment employed three biological replicates.…”

Section: Methodsmentioning

confidence: 99%

Enhancing cellular production of fucoxanthin through machine learning assisted predictive approach inIsochrysis galbana

Manochkumar,

Jonnalagadda,

Cherukuri

et al. 2024

Preprint

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The marine microalgae, Isochrysis galbana is a prolific producer of fucoxanthin which is a xanthophyll carotenoid with substantial global market value boasting extensive applications in the food, nutraceutical, pharmaceutical, and cosmetic industries. Although supplementation of different phytohormones to medium enhances fucoxanthin production, the quantification of pigment by conventional means is time-consuming and labor-intensive. This study addressed the multiple methodological limitations of HPLC-based fucoxanthin quantification and emphasized the need to develop a Machine Learning (ML) model as optimization and precise prediction remain a challenging task. Hence, an integrated experimental approach coupled with ML models was employed to predict fucoxanthin yield by supplementation of various phytohormones. The accuracy of fucoxanthin prediction excluding and including hormone descriptors was compared and evaluated using the ML models namely Random Forest (RF), Linear Regression (LR), Artificial Neural Network (ANN), and Support Vector Machine (SVM). RF model provided the most accurate prediction excluding hormone descriptors with coefficient of determination (R^2=0.809) and root-mean-square error (RMSE=0.776) followed by the ANN model with (R^2=0.722) and (RMSE=0.937). The inclusion of hormone descriptors for training and pre-processing of data further improved the fucoxanthin prediction accuracy of the RF model to (R^2=0.839) and (RMSE=0.712) and ANN model to (R^2=0.738) and (RMSE=0.909). These results indicated that the combination of low-cost, Ultraviolet (UV) spectrometric-based fucoxanthin quantification coupled with ML algorithms can be efficiently used for reliable prediction and enhanced fucoxanthin production, therefore highlighting a promising approach and furnishing invaluable insights towards the commercialization of microalgal fucoxanthin production.

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Effects of organic carbon source and pH on growth, astaxanthin accumulation and endogenous phytohormone secretion of Haematococcus pluvialis

Li,

Tao,

Wang

et al. 2023

J Appl Phycol

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Influence of exogenous phytohormone supplementation on the pigment and fatty acid content of three marine diatoms

Cited by 12 publications

References 83 publications

Effect of Abscisic Acid on Growth, Fatty Acid Profile, and Pigment Composition of the Chlorophyte Chlorella (Chromochloris) zofingiensis and Its Co-Culture Microbiome

Effect of Abscisic Acid on Growth, Fatty Acid Profile, and Pigment Composition of the Chlorophyte Chlorella (Chromochloris) zofingiensis and Its Co-Culture Microbiome

Enhancing cellular production of fucoxanthin through machine learning assisted predictive approach inIsochrysis galbana

Effects of organic carbon source and pH on growth, astaxanthin accumulation and endogenous phytohormone secretion of Haematococcus pluvialis

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