March 2020

Tayvich Vorapreeda, Chinae Thammarongtham, Thanaporn Palasak, Tanawut Srisuk, Piroon Jenjaroenpun, Thidathip Wongsurawat, Intawat Nookaew, Kobkul Laoteng

[published online ahead of print, 2020 Mar 10]. Gene. 2020;144559. doi:10.1016/j.gene.2020.144559

Abstract

The fungi in order Mortierellales are attractive producers for long-chain polyunsaturated fatty acids (PUFAs). Here, the genome sequencing and assembly of a novel strain of Mortierella sp. BCC40632 were done, yielding 65 contigs spanning of 49,964,116 total bases with predicted 12,149 protein-coding genes. We focused on the acetyl-CoA in relevant to its derived metabolic pathways for biosynthesis of macromolecules with biological functions, including PUFAs, eicosanoids and carotenoids. By comparative genome analysis between Mortierellales and Mucorales, the signature genetic characteristics of the arachidonic acid-producing strains, including Δ⁵-desaturase and GLELO-like elongase, were also identified in the strain BCC40632. Remarkably, this fungal strain contained only n-6 pathway of PUFA biosynthesis due to the absence of Δ¹⁵-desaturase or ω3-desaturase gene in contrast to other Mortierella species. Four putative enzyme sequences in the eicosanoid biosynthetic pathways were identified in the strain BCC40632 and others Mortierellale fungi, but were not detected in the Mucorales. Another unique metabolic trait of the Mortierellales was the inability in carotenoid synthesis as a result of the lack of phytoene synthase and phytoene desaturase genes. The findings provide a perspective in strain optimization for production of tailored-made products with industrial applications.

Keywords Arachidonic acid; Carotenoids, Eicosanoids; Genome analysis; Microbial lipids; Mortierella sp.; Oleaginous fungi

Read the publication here: https://www.sciencedirect.com/science/article/abs/pii/S0378111920302286

Christian Lieven, Moritz E Beber, Brett G Olivier, Frank T Bergmann, Meric Ataman, Parizad Babaei, Jennifer A Bartell, Lars M Blank, Siddharth Chauhan, Kevin Correia, Christian Diener, Andreas Dräger, Birgitta E Ebert, Janaka N Edirisinghe, José P Faria, Adam M Feist, Georgios Fengos, Ronan MT Fleming, Beatriz García-Jiménez, Vassily Hatzimanikatis, Wout van Helvoirt, Christopher S Henry, Henning Hermjakob, Markus J Herrgård, Ali Kaafarani, Hyun Uk Kim, Zachary King, Steffen Klamt, Edda Klipp, Jasper J Koehorst, Matthias König, Meiyappan Lakshmanan, Dong-Yup Lee, Sang Yup Lee, Sunjae Lee, Nathan E Lewis, Filipe Liu, Hongwu Ma, Daniel Machado, Radhakrishnan Mahadevan, Paulo Maia, Adil Mardinoglu, Gregory L Medlock, Jonathan M Monk, Jens Nielsen, Lars Keld Nielsen, Juan Nogales, Intawat Nookaew, Bernhard O Palsson, Jason A Papin, Kiran R Patil, Mark Poolman, Nathan D Price, Osbaldo Resendis-Antonio, Anne Richelle, Isabel Rocha, Benjamín J Sánchez, Peter J Schaap, Rahuman S Malik Sheriff, Saeed Shoaie, Nikolaus Sonnenschein, Bas Teusink, Paulo Vilaça, Jon Olav Vik, Judith AH Wodke, Joana C Xavier, Qianqian Yuan, Maksim Zakhartsev, Cheng Zhang

Nature Biotechnology. 2020 Mar 2:1-5.

Abstract

Reconstructing metabolic reaction networks enables the development of testable hypotheses of an organism’s metabolism under different conditions. State-of-the-art genome-scale metabolic models (GEMs) can include thousands of metabolites and reactions that are assigned to subcellular locations. Gene–protein–reaction (GPR) rules and annotations using database information can add meta-information to GEMs. GEMs with metadata can be built using standard reconstruction protocols, and guidelines have been put in place for tracking provenance and enabling interoperability, but a standardized means of quality control for GEMs is lacking. Here we report a community effort to develop a test suite named MEMOTE (for metabolic model tests) to assess GEM quality.

Read the publication here: https://www.nature.com/articles/s41587-020-0446-y