ExMODE: A Multi-Omics Repository for Extremophile Adaptation and Bioprospecting
Denghui LiiD, Kailong MaiD, Yulu ZhangiD, Jieni Wang, Zhen Cui, Xiaoqiang Li, W J Wang, Jiawei Tong, Yang GuoiD, Zongan WangiD, Peiyun Zeng, Jieyu WangiD, Xiaokai Xu, Nannan Zhang, Y S ZhangiD, Jing Chen, Qingjiang HuiD, Wenzhen YangiD, Zhiyong LiiD, Tao Yang, Wensi Du, Zhicheng Xu, Zhen YueiD, Jian Wang, Guangyi FaniD, , Shanshan Liu
Abstract
Extreme environments, though hostile to most life forms, host specialized extremophile communities that have redefined biological cognition and emerged as vital biotechnological resources, with their unique adaptive traits and bioactive molecules driving advances in multiple scientific and industrial fields. However, research on extremophiles is hindered by limitations in culture-based methods, fragmented multi-omics data with non-uniform annotation standards across repositories, the lack of cross-extreme comparative research in existing resources, and the singularity of data dimensionality that neglects key structural information, all of which restrict the functional interpretation of extremophile microbes and the exploitation of their bioprospecting potential. To tackle these challenges, we developed ExMODE (https://db.genomics.cn/exmode/), a comprehensive multi-omics database platform dedicated to extremophiles. It centrally integrates multi-omics data from diverse extreme habitats with a standardized annotation framework, resolving data fragmentation and enabling systematic cross-environment comparative analyses to elucidate extremophile adaptive mechanisms. Moreover, ExMODE aggregates multi-dimensional datasets including genes, genomes, secondary metabolite sequences and protein structures, overcoming the constraints of single-dimensional data and significantly improving the efficiency of biotechnological resource discovery from extreme microorganisms.
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