Jing Yang
*
Siqi Sun
Shulei Jia
*The final, formatted version of the article will be published soon.
ORIGINAL RESEARCH article
Front. Genet.
Sec. Computational Genomics
Volume 15 - 2024 |
doi: 10.3389/fgene.2024.1469600
This article is part of the Research Topic Towards the Embedding of Artificial Intelligence into Synthetic Organisms: Engineering Intelligence in Microorganisms View all 4 articles
Genomic analysis and mechanisms exploration of a stress tolerance and high-yield pullulan producing strain
Provisionally accepted- Interfaculty Bioinformatics, Institut für Biologie, Fakultät für Naturwissenschaften und Naturwissenschaften, Universität Bern, Bern, Switzerland
Pullulan is a kind of natural polymer, which is widely used in medicine and food because of its solubility, plasticity, edible, non-toxicity and good biocompatibility. It is of great significance to improve the yield of pullulan by genetic modification of microorganisms. It was previously reported that Aureobasidium melanogenum TN3-1 isolated from honey-comb could produce high-yield of pullulan, but the molecular mechanisms of its production of pullulan had not been completely solved. In this study, the reported strains of Aureobasidium spp. were further compared and analyzed at genome level. It was found that genome duplication and genome genetic variations might be the crucial factors for the high yield of pullulan and stress resistance. This particular phenotype may be the result of adaptive evolution, which can adapt to its environment through genetic variation and adaptive selection. In addition, the TN3-1 strain has a large genome, and the special regulatory sequences of its specific genes and promoters may ensure a unique characteristics. This study is a supplement of the previous studies, and provides basic data for the research of microbial genome modification in food and healthcare applications.
Keywords: Pullulan and biomedicine, secondary metabolites, adaptive evolution, Comparative genomics, Aureobasidium spp
Received: 24 Jul 2024; Accepted: 10 Sep 2024.
Copyright: © 2024 Yang, Wang, Zhang, Sun, Li, Shi, Zeng and Jia. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Jing Yang, Interfaculty Bioinformatics, Institut für Biologie, Fakultät für Naturwissenschaften und Naturwissenschaften, Universität Bern, Bern, Switzerland
Wenru Wang, Interfaculty Bioinformatics, Institut für Biologie, Fakultät für Naturwissenschaften und Naturwissenschaften, Universität Bern, Bern, Switzerland
Ruihua Zhang, Interfaculty Bioinformatics, Institut für Biologie, Fakultät für Naturwissenschaften und Naturwissenschaften, Universität Bern, Bern, Switzerland
Biqi Li, Interfaculty Bioinformatics, Institut für Biologie, Fakultät für Naturwissenschaften und Naturwissenschaften, Universität Bern, Bern, Switzerland
Yue Shi, Interfaculty Bioinformatics, Institut für Biologie, Fakultät für Naturwissenschaften und Naturwissenschaften, Universität Bern, Bern, Switzerland
Junfeng Zeng, Interfaculty Bioinformatics, Institut für Biologie, Fakultät für Naturwissenschaften und Naturwissenschaften, Universität Bern, Bern, Switzerland
Shulei Jia, Interfaculty Bioinformatics, Institut für Biologie, Fakultät für Naturwissenschaften und Naturwissenschaften, Universität Bern, Bern, Switzerland
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