Bleeker, P. M. | Search bioRxiv

bioRxiv2020

Two novel 7-epi-zingiberene derivatives with biological activity from Solanum habrochaites are produced by a single cytochrome P450 monooxygenase

Secretions from glandular trichomes potentially protect the plant against a variety of aggressors. In the tomato genus, wild species constitute a rich source of chemical diversity produced at the leaf surface by glandular trichomes. Previously, 7-epi-zingiberene produced in several accessions of Solanum habrochaites was found to confer resistance to whiteflies (Bemisia tabaci) and other insect pests. Here, we identify two derivatives of 7-epi-zingiberene from S. habrochaites that had not been reported as yet. We identified them as 9-hydroxy-zingiberene and 9-hydroxy-10,11-epoxyzingiberene. Using a combination of genetics and transcriptomics we identified a single cytochrome P450 oxygenase, ShCYP71D184 that carries out two successive oxidations to generate the two sesquiterpenoids. Bioactivity assays showed that only 9-hydroxy-10,11-epoxyzingiberene exhibits substantial toxicity against B. tabaci. In addition, both 9-hydroxy-zingiberene and 9-hydroxy-10,11-epoxyzingiberene display substantial growth inhibitory activities against a range of microorganisms, including Bacillus subtilis, Phytophtora infestans and Botrytis cinerea. Our work shows that trichome secretions from wild tomato species can provide protection against a wide variety of organisms. In addition, the availability of the genes encoding the enzymes for the pathway of 7-epi-zingiberene derivatives makes it possible to introduce this trait in cultivated tomato by precision breeding.

plant biology↗

bioRxiv2018

Building a local community of practice in scientific programming for Life Scientists

For most experimental biologists, handling the avalanche of data generated is similar to learning how to drive on your own. Although that might be doable, it is preferable and safer to learn programming and good practices together and preferably from experienced scientists. One way to achieve this is to build local communities of practice in scientific programming by bringing together life scientists that perform code-intensive research to spread know-how and good practices. The community will make sure that, for a given researcher working for an academic institution, their capacity to conduct data-intensive research will not be arbitrarily reliant on the presence of well-trained bioinformaticians in their vicinity.\n\nIn this paper, we propose a three-step field guide for building a local community of practice in scientific programming for life scientists. The first step is organizing a Carpentries programming workshop designed for researchers new to computational biology. However, while such workshops provide an immediate solution for learning, more regular long-term assistance is also needed. Researchers need persisting, local support to continue learning and solving programming issues that may hamper their research progress. The solution we describe here is to implement a Mozilla Study Group where researchers can meet-up and help each other in a \"safe-learning atmosphere\". We describe two real-life examples of building local communities of practice: one in the Netherlands at the Amsterdam Science Park and one in the United States at the University of Wisconsin-Madison. In order to help future researchers to build their own community of practice in scientific programming we discuss challenges and implemented solutions.\n\nWe believe that our local communities of practice will prove useful for other life scien-tists who want to set up similar support groups for researchers involved in scientific programming and data science.\n\nAuthor summaryIn this paper, we describe why and how to build a community of practice for life scientists that start to make more use of computers and programming in their research. A community of practice is a small group of scientists that meet regularly to help each other and promote good practices in scientific computing. While most life scientists are well-trained in the laboratory to conduct experiments, good practices with (big) datasets and their analysis are often missing. This paper proposes a field-guide on how to build such a community of practice at a local academic institution. Based on two real-life examples, challenges and related recommendations are provided. We believe that the current data deluge that life scientists will increasingly face can benefit from the implementation of these small communities. Good practices spread among experimental scientists will foster open, transparent, sound scientific results beneficial to society.

scientific communication and education↗