Chouhan Usha, Gamad Umesh, Choudhari Jyoti Kant
Department of Mathematics, Bioinformatics & Computer Applications, Maulana Azad National Institute of Technology, Bhopal, 462051, MP, India.
School of Biotechnology, Devi Ahilya Vishwavidyalaya, Indore, MP, 452001, India.
J Genet Eng Biotechnol. 2023 Aug 16;21(1):84. doi: 10.1186/s43141-023-00535-4.
Soil metagenomics is a cultivation-independent molecular strategy for investigating and exploiting the diversity of soil microbial communities. Soil microbial diversity is essential because it is critical to sustaining soil health for agricultural productivity and protection against harmful organisms. This study aimed to perform a metagenomic analysis of the soybean endosphere (all microbial communities found in plant leaves) to reveal signatures of microbes for health and disease.
The dataset is based on the National Center for Biotechnology Information (NCBI) Sequence Read Archive (SRA) release "microbial diversity in soybean". The quality control process rejected 21 of the evaluated sequences (0.03% of the total sequences). Dereplication determined that 68,994 sequences were artificial duplicate readings, and removed them from consideration. Ribosomal Ribonucleic acid (RNA) genes were present in 72,747 sequences that successfully passed quality control (QC). Finally, we found that hierarchical classification for taxonomic assignment was conducted using MG-RAST, and the considered dataset of the metagenome domain of bacteria (99.68%) dominated the other groups. In Eukaryotes (0.31%) and unclassified sequence 2 (0.00%) in the taxonomic classification of bacteria in the genus group, Streptomyces, Chryseobacterium, Ppaenibacillus, Bacillus, and Mitsuaria were found. We also found some biological pathways, such as CMP-KDO biosynthesis II (from D-arabinose 5-phosphate), tricarboxylic acid cycle (TCA) cycle (plant), citrate cycle (TCA cycle), fatty acid biosynthesis, and glyoxylate and dicarboxylate metabolism. Gene prediction uncovered 1,180 sequences, 15,172 of which included gene products, with the shortest sequence being 131 bases and maximum length 3829 base pairs. The gene list was additionally annotated using Integrated Microbial Genomes and Microbiomes. The annotation process yielded a total of 240 genes found in 177 bacterial strains. These gene products were found in the genome of strain 7598. Large volumes of data are generated using modern sequencing technology to sample all genes in all species present in a given complex sample.
These data revealed that it is a rich source of potential biomarkers for soybean plants. The results of this study will help us to understand the role of the endosphere microbiome in plant health and identify the microbial signatures of health and disease. The MG-RAST is a public resource for the automated phylogenetic and functional study of metagenomes. This is a powerful tool for investigating the diversity and function of microbial communities.
土壤宏基因组学是一种不依赖培养的分子策略，用于研究和开发土壤微生物群落的多样性。土壤微生物多样性至关重要，因为它对于维持土壤健康以保障农业生产力和抵御有害生物至关重要。本研究旨在对大豆内生菌（植物叶片中发现的所有微生物群落）进行宏基因组分析，以揭示健康和患病状态下微生物的特征。
数据集基于美国国立生物技术信息中心（NCBI）序列读取存档（SRA）发布的“大豆中的微生物多样性”。质量控制过程剔除了21条评估序列（占总序列的0.03%）。重复数据去除确定68,994条序列为人工重复读数，并将其排除在考虑范围之外。核糖体核糖核酸（RNA）基因存在于72,747条成功通过质量控制（QC）的序列中。最后，我们发现使用MG-RAST进行分类学归属的层次分类，细菌宏基因组域的考虑数据集（99.68%）在其他组中占主导地位。在真核生物（0.31%）和分类学分类中细菌属组的未分类序列2（0.00%）中，发现了链霉菌属、金黄杆菌属、类芽孢杆菌属、芽孢杆菌属和光岗菌属。我们还发现了一些生物途径，如CMP-KDO生物合成II（从D-阿拉伯糖5-磷酸开始）、三羧酸循环（TCA循环）（植物）、柠檬酸循环（TCA循环）脂肪酸生物合成以及乙醛酸和二羧酸代谢。基因预测发现了1,180条序列，其中15,172条包含基因产物，最短序列为131个碱基，最长为3829个碱基对。基因列表还使用综合微生物基因组和微生物群落进行了注释。注释过程共产生了在177株细菌菌株中发现的240个基因。这些基因产物存在于菌株7598的基因组中。使用现代测序技术生成大量数据，以对给定复杂样本中存在的所有物种的所有基因进行采样。
这些数据表明，它是大豆植物潜在生物标志物的丰富来源。本研究结果将有助于我们了解内生微生物群落在植物健康中的作用，并识别健康和患病状态下的微生物特征。MG-RAST是用于宏基因组自动系统发育和功能研究的公共资源。这是研究微生物群落多样性和功能的有力工具。
