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Biology subjects

Dyekjaer, J. D.

Publications and source records attributed to Dyekjaer, J. D..

2 recordsLinked to original sources

Essential sterols from engineered yeast prevent honeybee colony population decline

Honeybees, the worlds most important crop pollinators, are increasingly facing pollen starvation arising from agricultural intensification and climate change. Frequent flowering dearth periods and high-density rearing conditions weaken colonies, often leading to their demise. Beekeepers provide colonies with pollen substitutes, but these feeds cannot sustain brood production because they lack essential sterols found in pollen. Here, we describe a technological breakthrough in honeybee nutrition with wide-reaching impacts on global food security. We first measured the quantity and proportion of sterols found in honeybee tissues. Using this information, we genetically engineered a strain of the oleaginous yeast, Yarrowia lipolytica, to produce a mixture of essential sterols for bees and incorporated it into an otherwise nutritionally complete diet. Colonies fed exclusively with this diet reared brood for significantly longer than those fed diets without suitable sterols. Incorporating sterol supplements into pollen substitutes using this method will enable beekeepers to rear healthier, longer-lived colonies to meet the growing demands for global crop pollination. It could also reduce competition between bee species for access to natural floral resources, stemming the decline of wild bee populations.

synthetic biology↗

TransporterPAL: An integrative database Transporter Prediction ALgorithm

MotivationNatural products are used as drugs, cosmetic ingredients, pigments, flavors, and agricultural products. The compounds are retrievable as extracts from natural sources, but the yields are often low, and the final product may contain various impurities. These challenges can be solved by expressing the biosynthetic pathway in microbial cell factories and ensuring product secretion from the cell by using an appropriate transporter. However, insufficient knowledge of transporters for specific compounds often obstructs efficient secretion of the natural product. Therefore, our goal was to develop an algorithm that predicts transporters for a given compound using available public data. ResultsThe web application TransporterPAL predicts suitable transporters for compounds by interconnecting data for biosynthetic genes and their interactions with transporters. The web application queries the STITCH, STRING, and UniProtKB databases via their respective APIs and returns a set of potential transporters based on a compound and, optionally, the organism as input. For a test set of 61 transporter systems, each containing one or more transporters, a total of 90 unique transporters with a known substrate, we could retrieve 45% of the transporters. To our knowledge, this is the first bioinformatics tool for predicting transporter candidates for a given molecule. Availabilityhttps://transporterpal.com Contactirbo@biosustain.dtu.dk Supplementary informationSupplementary data are available at Bioinformatics online.

bioinformatics↗