Baeshen Naseebh N, Baz Lina, Shami Ashwag Y, Ashy Ruba A, Jalal Rewaa S, Abulfaraj Aala A, Refai Mohammed, Majeed Mazen A, Abuzahrah Samah S, Abdelkader Hayam, Baeshen Nabih A, Baeshen Mohammed N
Department of Biology, College of Sciences and Arts at Khulais, University of Jeddah, Jeddah 21959, Saudi Arabia.
Department of Biochemistry, Faculty of Science, King Abdulaziz University, Jeddah 21589, Saudi Arabia.
Plants (Basel). 2023 May 30;12(11):2176. doi: 10.3390/plants12112176.
The coast of the Red Sea in Jeddah City is home to a unique microbial community that has adapted to extreme environmental conditions. Therefore, it is essential to characterize the microbial community in this unique microbiome to predict how environmental changes will affect it. The aim of this study was to conduct metagenomic sequencing of 16S rRNA and ITS rRNA genes for the taxonomic classification of the microbial community in soil samples associated with the halophytic plants and . Fifteen soil samples were collected in triplicate to enhance robustness and minimize sampling bias. Firstly, to identify novel microbial candidates, the gDNAs were isolated from the saline soil samples surrounding each plant, and then bacterial 16S (V3-V4) and fungal ITS1 regions were sequenced utilizing a high-throughput approach (next-generation sequencing; NGS) on an Illumina MiSeq platform. Quality assessment of the constructed amplicon libraries was conducted using Agilent Bioanalyzer and fluorometric quantification methods. The raw data were processed and analyzed using the Pipeline (Nova Lifetech, Singapore) for bioinformatics analysis. Based on the total number of readings, it was determined that the phylum was the most prevalent in the soil samples examined, followed by the phylum . Based on ITS rRNA gene analysis, the alpha and beta fungal diversity in the studied soil samples revealed that the fungal population is structured into various groups according to the crust (c) and/or rhizosphere (r) plant parts. Fungal communities in the soil samples indicated that Ascomycota and Basidiomycota were the two most abundant phyla based on the total amount of sequence reads. Secondly, heat-map analysis of the diversity indices showed that the bacterial alpha diversity, as measured by Shannon, Simpson, and InvSimpson, was associated with soil crust (Hc and Tc enclosing and , respectively) and that the soil rhizosphere (Hr and Tr) was strongly correlated with bacterial beta diversity. Finally, fungal-associated Tc and Hc samples clustered together, according to observations made using the Fisher and Chao1 methods, and Hr and Tr samples clustered together according to Shannon, Simpson, and InvSimpson analyses. As a result of the soil investigation, potential agents that have been identified could lead to innovative agricultural, medical, and industrial applications.
吉达市红海沿岸是一个独特的微生物群落的栖息地，该群落已适应极端环境条件。因此，有必要对这个独特微生物组中的微生物群落进行特征描述，以预测环境变化将如何影响它。本研究的目的是对16S rRNA和ITS rRNA基因进行宏基因组测序，以便对与盐生植物相关的土壤样本中的微生物群落进行分类。采集了15份土壤样本，每份样本重复采集3次，以增强稳健性并尽量减少采样偏差。首先，为了识别新的微生物候选者，从每株植物周围的盐渍土壤样本中分离出基因组DNA，然后利用Illumina MiSeq平台上的高通量方法（下一代测序；NGS）对细菌16S（V3-V4）和真菌ITS1区域进行测序。使用安捷伦生物分析仪和荧光定量方法对构建的扩增子文库进行质量评估。原始数据使用Pipeline（新加坡Nova Lifetech）进行处理和分析，以进行生物信息学分析。根据读数总数，确定在所检测的土壤样本中，门是最普遍的，其次是门。基于ITS rRNA基因分析，所研究土壤样本中的真菌α和β多样性表明，真菌种群根据地壳（c）和/或根际（r）植物部分被构建成不同的组。土壤样本中的真菌群落表明，基于序列读数总量，子囊菌门和担子菌门是两个最丰富的门。其次，多样性指数的热图分析表明，用香农、辛普森和逆辛普森测量的细菌α多样性与土壤地壳（分别为包围和的Hc和Tc）相关，并且土壤根际（Hr和Tr）与细菌β多样性密切相关。最后，根据使用费舍尔和Chao1方法的观察结果，与真菌相关的Tc和Hc样本聚集在一起，根据香农、辛普森和逆辛普森分析，Hr和Tr样本聚集在一起。土壤调查的结果表明，已识别出的潜在因子可能会带来创新的农业、医学和工业应用。
