Crypthecodinium cohnii Growth and Omega Fatty Acid Production in Mediums Supplemented with Extract from Recycled Biomass

Crypthecodinium cohnii is a marine heterotrophic dinoflagellate that can accumulate high amounts of omega-3 polyunsaturated fatty acids (PUFAs), and thus has the potential to replace conventional PUFAs production with eco-friendlier technology. So far, C. cohnii cultivation has been mainly carried out with the use of yeast extract (YE) as a nitrogen source. In the present study, alternative carbon and nitrogen sources were studied: the extraction ethanol (EE), remaining after lipid extraction, as a carbon source, and dinoflagellate extract (DE) from recycled algae biomass C. cohnii as a source of carbon, nitrogen, and vitamins. In mediums with glucose and DE, the highest specific biomass growth rate reached a maximum of 1.012 h−1, while the biomass yield from substrate reached 0.601 g·g−1. EE as the carbon source, in comparison to pure ethanol, showed good results in terms of stimulating the biomass growth rate (an 18.5% increase in specific biomass growth rate was observed). DE supplement to the EE-based mediums promoted both the biomass growth (the specific growth rate reached 0.701 h−1) and yield from the substrate (0.234 g·g−1). The FTIR spectroscopy data showed that mediums supplemented with EE or DE promoted the accumulation of PUFAs/docosahexaenoic acid (DHA), when compared to mediums containing glucose and commercial YE.

Correction: Garcia et al. Primary Model for Biomass Growth Prediction in Batch Fermentation. Symmetry 2021, 13, 1468

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Phosphorus and Nitrogen Limitation as a Part of the Strategy to Stimulate Microbial Lipid Biosynthesis

Microbial lipids called a sustainable alternative to traditional vegetable oils invariably capture the attention of researchers. In this study, the effect of limiting inorganic phosphorus (KH2PO4) and nitrogen ((NH4)2SO4) sources in lipid-rich culture medium on the efficiency of cellular lipid biosynthesis by Y. lipolytica yeast has been investigated. In batch cultures, the carbon source was rapeseed waste post-frying oil (50 g/dm3). A significant relationship between the concentration of KH2PO4 and the amount of lipids accumulated has been revealed. In the shake-flask cultures, storage lipid yield was correlated with lower doses of phosphorus source in the medium. In bioreactor culture in mineral medium with (g/dm3) 3.0 KH2PO4 and 3.0 (NH4)2SO4, the cellular lipid yield was 47.5% (w/w). Simultaneous limitation of both phosphorus and nitrogen sources promoted lipid accumulation in cells, but at the same time created unfavorable conditions for biomass growth (0.78 gd.m./dm3). Increased phosphorus availability with limited cellular access to nitrogen resulted in higher biomass yields (7.45 gd.m./dm3) than phosphorus limitation in a nitrogen-rich medium (4.56 gd.m./dm3), with comparable lipid yields (30% and 32%). Regardless of the medium composition, the yeast preferentially accumulated oleic and linoleic acids as well as linolenic acid up to 8.89%. Further, it is crucial to determine the correlation between N/P molar ratios, biomass growth and efficient lipid accumulation. In particular, considering the contribution of phosphorus as a component of coenzymes in many metabolic pathways, including lipid biosynthesis and respiration processes, its importance as a factor in the cultivation of the oleaginous microorganisms was highlighted.

Bayesian inference of biomass growth characteristics for sugi (C. japonica) and hinoki (C. obtusa) forests in self-thinned and managed stands

Background Forests are an important sink for atmospheric carbon and could release that carbon upon deforestation and degradation. Knowing stand biomass dynamic of evergreen forests has become necessary to improve current biomass production models. The different growth processes of managed forests compared to self-managed forests imply an adaptation of biomass prediction models. Methods In this paper we model through three models the biomass growth of two tree species (Japanese cedar, Japanese cypress) at stand level whether they are managed or not (self-thinning). One of them is named self-thinned model which uses a specific self-thinning parameter α and adapted to self-managed forests and an other model is named thinned model adapted to managed forests. The latter is compared to a Mitscherlich model. The self-thinned model takes into account the light competition between trees relying on easily observable parameters (e.g. stand density). A Bayesian inference was carried out to determine parameters values according to a large database collected. Results In managed forest, Bayesian inference results showed obviously a lack of identifiability of Mitscherlich model parameters and a strong evidence for the thinned model in comparison to Mitscherlich model. In self-thinning forest, the results of Bayesian inference are in accordance with the self-thinning 3/2 rule (α=1.4). Structural dependence between stand density and stand yield in self-thinned model allows to qualifying the expression of biological time as a function of physical time and better qualify growth and mortality rate. Relative mortality rate is 2.5 times more important than relative growth rate after about 40 years old. Stand density and stand yield can be expressed as function of biological time, showing that yield is independent of initial density. Conclusions This paper addressed stand biomass dynamic models of evergreen forests in order to improve biomass growth dynamic assessment at regional scale relying on easily observable parameters. These models can be used to dynamically estimate forest biomass and more generally estimate the carbon balance and could contribute to a better understanding of climate change factors.