Aims:  To improve the yield and productivity of docosahexaenoic acid (DHA) by Schizochytrium sp. in terms of the analysis of microbial physiology. Methods and Results:  A two‐stage oxygen supply control strategy, aimed at achieving high concentration and high productivity of DHA, was proposed. At the first 40 h, KLa was controlled at 150·1 h−1 to obtain high μ for cell growth, subsequently KLa was controlled at 88·5 h−1 to maintain high qp for high DHA accumulation. Finally, the maximum lipid, DHA content and DHA productivity reached 46·6, 17·7 g l−1 and 111 mg l−1 h−1, which were 43·83%, 63·88% and 32·14% over the best results controlled by constant KLa. Conclusions:  This paper described a two‐stage oxygen supply control strategy based on the kinetic analysis for efficient DHA fermentation by Schizochytrium sp. Significance and Impact of the study:  This study showed the advantage of two‐stage control strategy in terms of microbial physiology. As KLa is a scaling‐up parameter, the idea developed in this paper could be scaled‐up to industrial process and applied to other industrial biotechnological processes to achieve both high product concentration and high productivity.

Salutaxel (3) is a conjugate of docetaxel (7) and a muramyl dipeptide (MDP) analogue. Docetaxel (7) has been recognized as a highly active chemotherapeutic agent against various cancers. MDP and its analogues are powerful potentiators of the antitumor actions of various tumor-necrotizing agents. This article documents the discovery of compound 3 and presents pharmacological proof of its biological function in tumor-bearing mice. Drug candidate 3 was superior to compound 7 in its ability to prevent tumor growth and metastasis. Compound 3 suppressed myeloid-derived suppressor cell (MDSC) accumulation in the spleens of tumor-bearing mice and decreased various serum inflammatory cytokines levels. Furthermore, compound 3 antagonized the nucleotide-binding oligomerization domain-like receptor 1 (NOD1) signaling pathway both in vitro and in vivo.

l-Phenylalanine is an important amino acid that is widely used in the production of food flavors and pharmaceuticals. Generally, l-phenylalanine production by engineered Escherichia coli requires a high rate of oxygen supply. However, the coexpression of Vitreoscilla hemoglobin gene (vgb), driven bya tac promoter, with the genes encoding 3-deoxy-d-arabinoheptulosonate-7-phosphate synthetase (aroF) and feedback-resistant chorismate mutase/prephenate dehydratase (pheA ), led to increased productivity and decreased demand for aeration by E. coli CICC10245. Shake-flask studies showed that vgb-expressing strains displayed higher rates of oxygen uptake, and l-phenylalanine production under standard aeration conditions was increased. In the aerobic fermentation process, cell growth, l-phenylalanine production, and glucose consumption by the recombinant E. coli strain PAPV, which harbored aroF, pheA , and tac-vgb genes, were increased compared to that in the strain harboring only aroF and pheA (E. coli strain PAP), especially under oxygen-limited conditions. The vgb-expressing strain PAPV produced 21.9% more biomass and 16.6% more l-phenylalanine, while consuming only approximately 5% more glucose after 48 H of fermentation. This study demonstrates a method to enhance the l-phenylalanine production by E. coli using less intensive and thus more economical aeration conditions.

To obtain high-cell-density cultures of sp. FJU-512 for DHA production, two stages of fermentation strategy were used and carbon/nitrogen ratio, DO and temperature were controlled at different levels. The final dry cell weight, total lipid production and DHA yield in 15 l bioreactor reached 103.9, 37.2 and 16.0 g/l, respectively. For the further study of microbial growth and DHA production dynamics, we established a set of kinetic models for the fed-batch production of DHA by sp. FJU-512 in 15 and 100 l fermenters and a compensatory parameter was integrated into the model in order to find the optimal mathematical equations. A modified Logistic model was proposed to fit the cell growth data and the following kinetic parameters were obtained: = 0.0525/h, = 100 g/l and = 4.1717 for the 15 l bioreactor, as well as = 0.0382/h, = 107.4371 g/l and = 10 for the 100 l bioreactor. The Luedeking-Piret equations were utilized to model DHA production, yielding values of = 0.0648 g/g and = 0.0014 g/g/h for the 15 l bioreactor, while the values of and obtained for the 100 l fermentation were 0.0209 g/g and 0.0030 g/g/h. The predicted results compared with experimental data showed that the established models had a good fitting precision and were able to exactly depict the dynamic features of the DHA production process.

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