Metagenomic analysis of soybean endosphere microbiome to reveal signatures of microbes for health and disease.

IF 3.6 Q2 BIOTECHNOLOGY & APPLIED MICROBIOLOGY Journal, genetic engineering & biotechnology Pub Date : 2023-08-16 DOI:10.1186/s43141-023-00535-4
Usha Chouhan, Umesh Gamad, Jyoti Kant Choudhari
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Abstract

Background: 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.

Results: 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.

Conclusions: 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.

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大豆内球微生物组的宏基因组分析揭示健康和疾病微生物的特征。
背景:土壤宏基因组学是研究和开发土壤微生物群落多样性的一种不依赖于栽培的分子策略。土壤微生物多样性至关重要,因为它对维持土壤健康、农业生产力和防止有害生物的侵害至关重要。本研究旨在对大豆内球(植物叶片中发现的所有微生物群落)进行宏基因组分析,以揭示与健康和疾病有关的微生物特征。结果:该数据集基于美国国家生物技术信息中心(NCBI)序列读取档案(SRA)发布的“大豆微生物多样性”。质控过程不合格率为0.03%(21个)。重复分析确定68,994个序列是人为重复读数,并将其从考虑中删除。核糖体核糖核酸(RNA)基因在72,747个序列中存在,成功通过质量控制(QC)。最后,我们发现利用MG-RAST进行分级分类,细菌宏基因组结构域的考虑数据集(99.68%)优势于其他类群。真核生物(0.31%)和未分类序列2(0.00%)在属群细菌的分类分类中发现了链霉菌(Streptomyces)、黄杆菌(Chryseobacterium)、芽孢杆菌(Ppaenibacillus)、芽孢杆菌(Bacillus)和Mitsuaria。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)、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盐和二羧酸盐代谢。基因预测共发现1180条序列,其中含有基因产物的序列为15172条,最短序列为131个碱基对,最长序列为3829个碱基对。此外,还使用集成微生物基因组和微生物组对基因列表进行了注释。在注释过程中,共在177个菌株中发现了240个基因。这些基因产物均存在于菌株7598的基因组中。使用现代测序技术对给定复杂样本中所有物种的所有基因进行采样,产生大量数据。结论:这些数据表明它是大豆植物潜在生物标志物的丰富来源。本研究的结果将有助于我们了解内球微生物组在植物健康中的作用,并确定健康和疾病的微生物特征。MG-RAST是一个用于宏基因组系统发育和功能自动研究的公共资源。这是研究微生物群落多样性和功能的有力工具。
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