16S amplicon sequencing and functional gene prediction of microbial community in Inner West Aegean, Turkey

IF 3.1 4区 生物学 Q2 BIOLOGY Computational Biology and Chemistry Pub Date : 2025-02-08 DOI:10.1016/j.compbiolchem.2025.108373
Belma Nural Yaman
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Abstract

Thermal springs are aquatic environments with high temperatures that often host thermophilic organisms which is important for an ecological and evolutionary perspective, as they have developed adaptation mechanisms to thrive at different temperatures based on their ideal growth requirements. This study analyzed water samples to identify thermophilic prokaryotic populations via 16S amplicon sequencing. The sequencing reads were processed using QIIME2 2023.2. Prediction of functional profiles were made using q2-picrust2. All the files generated were visualized using ggPICRUST2. Some species of Thermus, Hydrogenobacter subterraneus, Acinetobacter species, Geothermobacterium ferrireducens, Bacillus altitudinis complex, Flavobacterium lindanitolerans, and Thermomicrobium roseum were found in KTB. Moreover, the Acinetobacter calcoaceticus/baumannii complex, some species of Thermus, the Burkholderia cepacia complex, Hydrocarboniphaga daqingensis, Hydrogenophaga defluvii, Chromohalobacter salexigens, the Bacillus subtilis group, and Methylobacterium komagatae were found in the ATB. Component analysis revealed a difference in microbial diversity between the two samples. The predicted pathways included lipid metabolism, bacterial cell motility, glycan metabolism, and DNA replication and repair systems. ggPICRUST2 was utilized for prediction of functional profiles. These findings enhance the current knowledge of the microbiology of Kütahya and Afyonkarahisar thermal springs and enable comparisons with other geothermal systems.
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土耳其内西爱琴海地区微生物群落16S扩增子测序及功能基因预测
温泉是高温的水生环境,通常是嗜热生物的宿主,这对生态和进化的角度很重要,因为它们已经发展出适应机制,根据理想的生长需求在不同的温度下茁壮成长。本研究通过对水样进行16S扩增子测序来鉴定嗜热原核生物群体。测序reads使用QIIME2 2023.2进行处理。利用q2-picrust2进行功能谱预测。所有生成的文件都使用ggPICRUST2可视化。在KTB中发现了一些热菌、地下氢杆菌、不动杆菌、铁还原地热杆菌、高原芽孢杆菌复合体、林达尼托尔黄杆菌和玫瑰热微生物。此外,在ATB中还发现了钙酸不动杆菌/鲍曼不动杆菌复合体、热菌复合体、绿色伯克氏菌复合体、大庆食氢菌、脱氟食氢菌、沙利色盐杆菌、枯草芽孢杆菌群和komagatae甲基杆菌。成分分析揭示了两个样品之间微生物多样性的差异。预测的途径包括脂质代谢、细菌细胞运动、聚糖代谢和DNA复制和修复系统。利用ggPICRUST2进行功能谱预测。这些发现增强了目前对k塔哈亚和Afyonkarahisar温泉微生物学的认识,并可以与其他地热系统进行比较。
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来源期刊
Computational Biology and Chemistry
Computational Biology and Chemistry 生物-计算机:跨学科应用
CiteScore
6.10
自引率
3.20%
发文量
142
审稿时长
24 days
期刊介绍: Computational Biology and Chemistry publishes original research papers and review articles in all areas of computational life sciences. High quality research contributions with a major computational component in the areas of nucleic acid and protein sequence research, molecular evolution, molecular genetics (functional genomics and proteomics), theory and practice of either biology-specific or chemical-biology-specific modeling, and structural biology of nucleic acids and proteins are particularly welcome. Exceptionally high quality research work in bioinformatics, systems biology, ecology, computational pharmacology, metabolism, biomedical engineering, epidemiology, and statistical genetics will also be considered. Given their inherent uncertainty, protein modeling and molecular docking studies should be thoroughly validated. In the absence of experimental results for validation, the use of molecular dynamics simulations along with detailed free energy calculations, for example, should be used as complementary techniques to support the major conclusions. Submissions of premature modeling exercises without additional biological insights will not be considered. Review articles will generally be commissioned by the editors and should not be submitted to the journal without explicit invitation. However prospective authors are welcome to send a brief (one to three pages) synopsis, which will be evaluated by the editors.
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