Genomic and Molecular Interaction Analysis of NodD1 in a Novel Bradyrhizobium yuanmingense sp. B64 Isolate for Nodulation and Symbiosis of Legume Plants.

IF 1.9 4区 生物学 Q4 BIOCHEMISTRY & MOLECULAR BIOLOGY
Biochemical Genetics Pub Date : 2026-10-01 Epub Date: 2026-06-08 DOI:10.1007/s10528-026-11403-4
Aura Aslan, Rumella Simarmata, Dwi Santosa, Tiwit Widowati, Sylvia Lekatompessy, Ananda Merrisa, Misbakhul Bait, Rendi Palar
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引用次数: 0

Abstract

Rhizobial bacteria are known for their ability to fix nitrogen for leguminous plants and their essential function for sustainable agriculture. This study characterizes the taxonomic status and functional potential of the Bradyrhizobium B64 isolate using integrated genomic and molecular approaches. The whole genome of the B64 isolate was sequenced via Illumina paired-end technology. Species delimitation was performed using average nucleotide identity (ANI) and digital DNA-DNA Hybridization (dDDH). The NodD1 protein structure was modeled using AlphaFold3 and validated by Ramachandran plot analysis. Molecular docking was then conducted to evaluate interactions between NodD1 and four signaling flavonoids: Apigenin, Daidzein, Genistein, and Naringenin. Genomic analysis revealed a maximum ANI of 94.4% and dDDH values between 51.4 and 62.4%. Since these values fall below the standard prokaryotic thresholds (ANI < 95%; dDDH < 70%), the B64 isolate is identified as a novel species. Physiological assays confirmed nitrogen fixation (1.97 ppm), IAA production (3.67 ppm), and phosphate solubilization (26.10 ppm). Structural validation showed 100% of NodD1 residues in allowed regions, ensuring high model reliability. Docking simulations demonstrated strong binding affinities across all flavonoids, with binding free energies ranging from - 8.8 to - 9.0 kcal/mol. Daidzein exhibited the highest thermodynamic stability (- 9.0 kcal/mol), whereas apigenin showed the most extensive residue interaction network. The B64 isolate is a novel Bradyrhizobium species with a high symbiotic capacity. The stable NodD1-flavonoid interactions provide a molecular basis for efficient nodulation, positioning B64 as a promising candidate for developing lipo-chitooligosaccharide (LCO)-based biofertilizers.

基因组和分子间相互作用分析小说中的NodD1 Bradyrhizobium yuanmingense sp。B64隔离有节和豆科植物共生。
根瘤菌以其为豆科植物固定氮的能力和对可持续农业的重要作用而闻名。本研究利用基因组学和分子生物学相结合的方法对慢生根瘤菌B64分离株的分类地位和功能潜力进行了研究。利用Illumina配对端技术对B64分离物进行全基因组测序。采用平均核苷酸同一性(ANI)和数字DNA-DNA杂交(dDDH)进行物种划分。利用AlphaFold3对NodD1蛋白结构进行建模,并通过Ramachandran图分析进行验证。然后进行分子对接,评估NodD1与4种信号黄酮类化合物(Apigenin, Daidzein, Genistein, Naringenin)之间的相互作用。基因组分析显示ANI最大值为94.4%,dDDH值在51.4 ~ 62.4%之间。由于这些值低于标准的原核阈值(ANI)
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来源期刊
Biochemical Genetics
Biochemical Genetics 生物-生化与分子生物学
CiteScore
3.90
自引率
0.00%
发文量
133
审稿时长
4.8 months
期刊介绍: Biochemical Genetics welcomes original manuscripts that address and test clear scientific hypotheses, are directed to a broad scientific audience, and clearly contribute to the advancement of the field through the use of sound sampling or experimental design, reliable analytical methodologies and robust statistical analyses. Although studies focusing on particular regions and target organisms are welcome, it is not the journal’s goal to publish essentially descriptive studies that provide results with narrow applicability, or are based on very small samples or pseudoreplication. Rather, Biochemical Genetics welcomes review articles that go beyond summarizing previous publications and create added value through the systematic analysis and critique of the current state of knowledge or by conducting meta-analyses. Methodological articles are also within the scope of Biological Genetics, particularly when new laboratory techniques or computational approaches are fully described and thoroughly compared with the existing benchmark methods. Biochemical Genetics welcomes articles on the following topics: Genomics; Proteomics; Population genetics; Phylogenetics; Metagenomics; Microbial genetics; Genetics and evolution of wild and cultivated plants; Animal genetics and evolution; Human genetics and evolution; Genetic disorders; Genetic markers of diseases; Gene technology and therapy; Experimental and analytical methods; Statistical and computational methods.
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