Engineering precursor supply for the high-level production of ergothioneine in Saccharomyces cerevisiae.

Ergothioneine (ERG) is an unusual sulfur-containing amino acid. It is a potent antioxidant, which shows great potential for ameliorating neurodegenerative and cardiovascular diseases. L-ergothioneine is rare in nature, with mushrooms being the primary dietary source. The chemical synthesis process is complex and expensive. Alternatively, ERG can be produced by fermentation of recombinant microorganisms engineered for ERG overproduction. Here, we describe the engineering of S. cerevisiae for high-level ergothioneine production on minimal medium with glucose as the only carbon source. To this end, metabolic engineering targets in different layers of the amino acid metabolism were selected based on literature and tested. Out of 28 targets, nine were found to improve ERG production significantly by 10%-51%. These targets were then sequentially implemented to generate an ergothioneine-overproducing yeast strain capable of producing 106.2 ± 2.6 mg/L ERG in small-scale cultivations. Transporter engineering identified that the native Aqr1 transporter was capable of increasing the ERG production in a yeast strain with two copies of the ERG biosynthesis pathway, but not in the strain that was further engineered for improved precursor supply. Medium optimization indicated that additional supplementation of pantothenate improved the strain's productivity further and that no supplementation of amino acid precursors was necessary. Finally, the engineered strain produced 2.39 ± 0.08 g/L ERG in 160 h (productivity of 14.95 ± 0.49 mg/L/h) in a controlled fed-batch fermentation without supplementation of amino acids. This study paves the way for the low-cost fermentation-based production of ergothioneine.

Engineering energetically efficient transport of dicarboxylic acids in yeast Saccharomyces cerevisiae.

Biobased C4-dicarboxylic acids are attractive sustainable precursors for polymers and other materials. Commercial scale production of these acids at high titers requires efficient secretion by cell factories. In this study, we characterized 7 dicarboxylic acid transporters in Xenopus oocytes and in Saccharomyces cerevisiae engineered for dicarboxylic acid production. Among the tested transporters, the Mae1(p) from Schizosaccharomyces pombe had the highest activity toward succinic, malic, and fumaric acids and resulted in 3-, 8-, and 5-fold titer increases, respectively, in S. cerevisiae, while not affecting growth, which was in contrast to the tested transporters from the tellurite-resistance/dicarboxylate transporter (TDT) family or the Na+ coupled divalent anion-sodium symporter family. Similar to SpMae1(p), its homolog in Aspergillus carbonarius, AcDct(p), increased the malate titer 12-fold without affecting the growth. Phylogenetic and protein motif analyses mapped SpMae1(p) and AcDct(p) into the voltage-dependent slow-anion channel transporter (SLAC1) clade of transporters, which also include plant Slac1(p) transporters involved in stomata closure. The conserved phenylalanine residue F329 closing the transport pore of SpMae1(p) is essential for the transporter activity. The voltage-dependent SLAC1 transporters do not use proton or Na+ motive force and are, thus, less energetically expensive than the majority of other dicarboxylic acid transporters. Such transporters present a tremendous advantage for organic acid production via fermentation allowing a higher overall product yield.

The biology of ergothioneine, an antioxidant nutraceutical.

Ergothioneine (ERG) is an unusual thio-histidine betaine amino acid that has potent antioxidant activities. It is synthesised by a variety of microbes, especially fungi (including in mushroom fruiting bodies) and actinobacteria, but is not synthesised by plants and animals who acquire it via the soil and their diet, respectively. Animals have evolved a highly selective transporter for it, known as solute carrier family 22, member 4 (SLC22A4) in humans, signifying its importance, and ERG may even have the status of a vitamin. ERG accumulates differentially in various tissues, according to their expression of SLC22A4, favouring those such as erythrocytes that may be subject to oxidative stress. Mushroom or ERG consumption seems to provide significant prevention against oxidative stress in a large variety of systems. ERG seems to have strong cytoprotective status, and its concentration is lowered in a number of chronic inflammatory diseases. It has been passed as safe by regulatory agencies, and may have value as a nutraceutical and antioxidant more generally.

How do various maize crop models vary in their responses to climate change factors?

Potential consequences of climate change on crop production can be studied using mechanistic crop simulation models. While a broad variety of maize simulation models exist, it is not known whether different models diverge on grain yield responses to changes in climatic factors, or whether they agree in their general trends related to phenology, growth, and yield. With the goal of analyzing the sensitivity of simulated yields to changes in temperature and atmospheric carbon dioxide concentrations [CO2 ], we present the largest maize crop model intercomparison to date, including 23 different models. These models were evaluated for four locations representing a wide range of maize production conditions in the world: Lusignan (France), Ames (USA), Rio Verde (Brazil) and Morogoro (Tanzania). While individual models differed considerably in absolute yield simulation at the four sites, an ensemble of a minimum number of models was able to simulate absolute yields accurately at the four sites even with low data for calibration, thus suggesting that using an ensemble of models has merit. Temperature increase had strong negative influence on modeled yield response of roughly -0.5 Mg ha(-1) per °C. Doubling [CO2 ] from 360 to 720 µmol mol(-1) increased grain yield by 7.5% on average across models and the sites. That would therefore make temperature the main factor altering maize yields at the end of this century. Furthermore, there was a large uncertainty in the yield response to [CO2 ] among models. Model responses to temperature and [CO2 ] did not differ whether models were simulated with low calibration information or, simulated with high level of calibration information.

Deorphanizing solute carriers in Saccharomyces cerevisiae for secondary uptake of xenobiotic compounds.

The exchange of small molecules between the cell and the environment happens through transporter proteins. Besides nutrients and native metabolic products, xenobiotic molecules are also transported, however it is not well understood which transporters are involved. In this study, by combining exo-metabolome screening in yeast with transporter characterization in Xenopus oocytes, we mapped the activity of 30 yeast transporters toward six small non-toxic substrates. Firstly, using LC-MS, we determined 385 compounds from a chemical library that were imported and exported by S. cerevisiae. Of the 385 compounds transported by yeast, we selected six compounds (viz. sn-glycero-3-phosphocholine, 2,5-furandicarboxylic acid, 2-methylpyrazine, cefadroxil, acrylic acid, 2-benzoxazolol) for characterization against 30 S. cerevisiae xenobiotic transport proteins expressed in Xenopus oocytes. The compounds were selected to represent a diverse set of chemicals with a broad interest in applied microbiology. Twenty transporters showed activity toward one or more of the compounds. The tested transporter proteins were mostly promiscuous in equilibrative transport (i.e., facilitated diffusion). The compounds 2,5-furandicarboxylic acid, 2-methylpyrazine, cefadroxil, and sn-glycero-3-phosphocholine were transported equilibratively by transporters that could transport up to three of the compounds. In contrast, the compounds acrylic acid and 2-benzoxazolol, were strictly transported by dedicated transporters. The prevalence of promiscuous equilibrative transporters of non-native substrates has significant implications for strain development in biotechnology and offers an explanation as to why transporter engineering has been a challenge in metabolic engineering. The method described here can be generally applied to study the transport of other small non-toxic molecules. The yeast transporter library is available at AddGene (ID 79999).

Engineering ergothioneine production in Yarrowia lipolytica.

Ergothioneine is a naturally occurring antioxidant that has shown potential in ameliorating neurodegenerative and cardiovascular diseases. In this study, we investigated the potential of the Crabtree-negative, oleaginous yeast Yarrowia lipolytica as an alternative host for ergothioneine production. We expressed the biosynthetic enzymes EGT1 from Neurospora crassa and EGT2 from Claviceps purpurea to obtain 158 mg·L-1 of ergothioneine in small-scale cultivation, with an additional copy of each gene improving the titer to 205 mg·L-1 . The effect of phosphate limitation on ergothioneine production was studied, and finally, a phosphate-limited fed-batch fermentation in 1 L bioreactors yielded 1.63 ± 0.04 g·L-1 ergothioneine in 220 h, corresponding to an overall volumetric productivity of 7.41 mg·L-1 ·h-1 , showing that Y. lipolytica is a promising host for ergothioneine production.

Transporter engineering in microbial cell factories: the ins, the outs, and the in-betweens.

Engineering the transport of small molecules is an effective approach to improve the performance of microbial cell factories. Transporter engineering can improve the utilization of low-cost alternative substrates, reduce the loss of pathway intermediates, and increase the titer and production rate of the target product. However, transporters are not commonly engineered in strain development programs because the functions of most of the transport proteins are not known. In the recent years, a variety of methods have been developed for identification of transporters for specific substrates and for characterizing transport mechanisms. This review presents recent examples of successful transport engineering for cell factories and discusses the methods for transporter identification and characterization.

Engineering the Yeast Saccharomyces cerevisiae for the Production of L-(+)-Ergothioneine.

L-(+)-Ergothioneine (ERG) is an unusual, naturally occurring antioxidant nutraceutical that has been shown to help reduce cellular oxidative damage. Humans do not biosynthesise ERG, but acquire it from their diet; it exploits a specific transporter (SLC22A4) for its uptake. ERG is considered to be a nutraceutical and possible vitamin that is involved in the maintenance of health, and seems to be at too low a concentration in several diseases in vivo. Ergothioneine is thus a potentially useful dietary supplement. Present methods of commercial production rely on extraction from natural sources or on chemical synthesis. Here we describe the engineering of the baker's yeast Saccharomyces cerevisiae to produce ergothioneine by fermentation in defined media. After integrating combinations of ERG biosynthetic pathways from different organisms, we screened yeast strains for their production of ERG. The highest-producing strain was also engineered with known ergothioneine transporters. The effect of amino acid supplementation of the medium was investigated and the nitrogen metabolism of S. cerevisiae was altered by knock-out of TOR1 or YIH1. We also optimized the media composition using fractional factorial methods. Our optimal strategy led to a titer of 598 ± 18 mg/L ergothioneine in fed-batch culture in 1 L bioreactors. Because S. cerevisiae is a GRAS ("generally recognized as safe") organism that is widely used for nutraceutical production, this work provides a promising process for the biosynthetic production of ERG.

The Global Gridded Crop Model Intercomparison phase 1 simulation dataset.

The Global Gridded Crop Model Intercomparison (GGCMI) phase 1 dataset of the Agricultural Model Intercomparison and Improvement Project (AgMIP) provides an unprecedentedly large dataset of crop model simulations covering the global ice-free land surface. The dataset consists of annual data fields at a spatial resolution of 0.5 arc-degree longitude and latitude. Fourteen crop modeling groups provided output for up to 11 historical input datasets spanning 1901 to 2012, and for up to three different management harmonization levels. Each group submitted data for up to 15 different crops and for up to 14 output variables. All simulations were conducted for purely rainfed and near-perfectly irrigated conditions on all land areas irrespective of whether the crop or irrigation system is currently used there. With the publication of the GGCMI phase 1 dataset we aim to promote further analyses and understanding of crop model performance, potential relationships between productivity and environmental impacts, and insights on how to further improve global gridded crop model frameworks. We describe dataset characteristics and individual model setup narratives.