AUTHOR=Ou Shu-ning , Liang Jie-Liang , Jiang Xiao-min , Liao Bin , Jia Pu , Shu Wen-sheng , Li Jin-tian TITLE=Physiological, Genomic and Transcriptomic Analyses Reveal the Adaptation Mechanisms of Acidiella bohemica to Extreme Acid Mine Drainage Environments JOURNAL=Frontiers in Microbiology VOLUME=12 YEAR=2021 URL=https://www.frontiersin.org/journals/microbiology/articles/10.3389/fmicb.2021.705839 DOI=10.3389/fmicb.2021.705839 ISSN=1664-302X ABSTRACT=

Fungi in acid mine drainage (AMD) environments are of great concern due to their potentials of decomposing organic carbon, absorbing heavy metals and reducing AMD acidity. Based on morphological analysis and ITS/18S high-throughput sequencing technology, previous studies have provided deep insights into the diversity and community composition of fungi in AMD environments. However, knowledge about physiology, metabolic potential and transcriptome profiles of fungi inhabiting AMD environments is still scarce. Here, we reported the physiological, genomic, and transcriptomic characterization of Acidiella bohemica SYSU C17045 to improve our understanding of the physiological, genomic, and transcriptomic mechanisms underlying fungal adaptation to AMD environments. A. bohemica was isolated from an AMD environment, which has been proved to be an acidophilic fungus in this study. The surface of A. bohemica cultured in AMD solutions was covered with a large number of minerals such as jarosite. We thus inferred that the A. bohemica might have the potential of biologically induced mineralization. Taking advantage of PacBio single-molecule real-time sequencing, we obtained the high-quality genome sequences of A. bohemica (50 Mbp). To our knowledge, this was the first attempt to employ a third-generation sequencing technology to explore the genomic traits of fungi isolated from AMD environments. Moreover, our transcriptomic analysis revealed that a series of genes in the A. bohemica genome were related to its metabolic pathways of C, N, S, and Fe as well as its adaptation mechanisms, including the response to acid stress and the resistance to heavy metals. Overall, our physiological, genomic, and transcriptomic data provide a foundation for understanding the metabolic potential and adaptation mechanisms of fungi in AMD environments.