Molecular Microbiology Research 2024, Vol.14, No.1, 61-64 http://microbescipublisher.com/index.php/mmr 61 Scientific Commentary Open Access Ecological Niche Changes of Microbial Communities in the Tasman Sea: the Interaction between Temperature and Diversity Henry Smith Molecular Microbiology Research, MicroSci Publisher, Richmond, BC, V7A 4Z5, Canada Corresponding email: Henry Smith@sophiapublisher.com Molecular Microbiology Research, 2024, Vol.14, No.1 doi: 10.5376/mmr.2024.14.0007 Received: 28 Jan., 2024 Accepted: 16 Feb., 2024 Published: 25 Feb., 2024 Copyright © 2024 Smith, This is an open access article published under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Preferred citation for this article: Smith H., 2024, Ecological niche changes of microbial communities in the Tasman Sea: the interaction between temperature and diversity, Molecular Microbiology Research, 14(1): 61-64 (doi: 10.5376/mmr.2024.14.0007) On January 24, 2024, Mark V. Brown, Martin Ostrowski, Lauren F. Messer, and others published a research paper titled "A marine heatwave drives significant shifts in polar microbiology" in the journal Communications Biology. Given the global trends and potential impacts of MHWs on marine ecosystems, this study analyzed the changes in microbial communities during the 2015/16 and 2017/18 Tasman Sea MHW events, revealing the impact of MHWs on microbial community structure, function, and niche status. Researchers used a large amount of microbial sample data from the southern hemisphere to systematically evaluate the selection pressure, community transformation, and diversity changes of MHWs on microbial communities through temperature index and niche indicators. The innovation and importance of this study lies in providing the world's first comprehensive framework for the impact of MHWs on microbial ecosystems, which helps to monitor, predict, and develop adaptation strategies for the future impact of MHWs on marine ecosystems. 1 Materials and Methods The research team used thousands of samples from the southern hemisphere, covering the Tasman Sea and surrounding waters. The samples were mainly collected from the Maria Island National Reference Station (MAI NRS) of the Integrated Marine Observing System (IMOS) network and other sites. The sampling covers different depths, temperatures, and nutrient gradients from the surface to the deep layers, ensuring the representativeness of the data. The DNA in each sample is passed through DNeasy ® PowerWater ® Sterivex ™ DNA Isolation Kit (Qiagen, Germany) extraction. To identify and classify microbial communities, specific primers are used to amplify target gene regions, and the amplified products are sequenced using the Illumina high-throughput sequencing platform. The V1-V3 region of the 16S rRNA gene in bacteria was amplified using 27f and 519R primers, while the 16S rRNA gene in archaea was amplified using A2F and 519R * primers. The 18S rRNA gene in eukaryotic microorganisms was amplified using euk454FWD1 and TAReuk Rev3 primers. Subsequently, the sequencing data was processed using the DADA2 pipeline to remove low-quality and chimeric sequences, generating ASVs (Amplicon Sequence Variants). Bacteria and archaea ASVs are classified using the Genome Taxonomy Database (GTDB), while eukaryotic ASVs are classified using the PR2 database. To evaluate the impact of marine heatwave events on microbial communities, this study calculated multiple niche indices, including species temperature index (STI) and community temperature index (CTI). STI is calculated using kernel density estimation to represent the optimal temperature preference for each ASV. CTI is based on the weighted average of STI for all ASVs in the sample, used to evaluate the average temperature preference of the entire microbial community. They also calculated other indices, including Salinity Index (CSI), Nutrient Index (CNI), and Oxygen Index (COI). Data analysis and chart drawing are conducted using R programming language.
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