Achieving a high‐density oleaginous yeast culture: Comparison of four processing strategies using <i>Metschnikowia pulcherrima</i>

Microbial lipids have the potential to displace terrestrial oils for fuel, value chemical, and food production, curbing the growth in tropical oil plantations and helping to reduce deforestation. However, commercialization remains elusive partly due to the lack of suitably robust organisms and their low lipid productivity. Extremely high cell densities in oleaginous cultures are needed to increase reaction rates, reduce reactor volume, and facilitate downstream processing. In this investigation, the oleaginous yeast Metschnikowia pulcherrima, a known antimicrobial producer, was cultured using four different processing strategies to achieve high cell densities and gain suitable lipid productivity. In batch mode, the yeast demonstrated lipid contents more than 40% (w/w) under high osmotic pressure. In fed‐batch mode, however, high‐lipid titers were prevented through inhibition above 70.0 g L−1 yeast biomass. Highly promising were a semi‐continuous and continuous mode with cell recycle where cell densities of up to 122.6 g L−1 and maximum lipid production rates of 0.37 g L−1 h−1 (daily average), a nearly two‐fold increase from the batch, were achieved. The findings demonstrate the importance of considering multiple fermentation modes to achieve high‐density oleaginous yeast cultures generally and indicate the limitations of processing these organisms under the extreme conditions necessary for economic lipid production.This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 665992

Seasonal adjustment of daily data with CAMPLET

In the last decade large data sets have become available, both in terms of the number of time series and with higher frequencies (weekly, daily and even higher). All series may suffer from seasonality, which hides other important fluctuations. Therefore time series are typically seasonally adjusted. However, standard seasonal adjustment methods cannot handle series with higher than monthly frequencies. Recently, Abeln et al. (2019) presented CAMPLET, a new seasonal adjustment method, which does not produce revisions when new observations become available. The aim of this paper is to show the attractiveness of CAMPLET for seasonal adjustment of daily time series. We apply CAMPLET to daily data on the gas system in the Netherlands

Consistent treatment of hydrophobicity in protein lattice models accounts for cold denaturation

The hydrophobic effect stabilizes the native structure of proteins by minimizing the unfavourable interactions between hydrophobic residues and water through the formation of a hydrophobic core. Here we include the entropic and enthalpic contributions of the hydrophobic effect explicitly in an implicit solvent model. This allows us to capture two important effects: a length-scale dependence and a temperature dependence for the solvation of a hydrophobic particle. This consistent treatment of the hydrophobic effect explains cold denaturation and heat capacity measurements of solvated proteins.Comment: Added and corrected references for design procedure in main text (p. 2) and in Supplemental Information (p. 8