Universidade de Brasilia (UnB), Brasília, Distrito Federal, 70910-900, Brazil.
Embrapa Recursos Genéticos e Biotecnologia, C.P. 02372, Brasília, Distrito Federal, 70770-917, Brazil.
Braz J Microbiol. 2019 Oct;50(4):905-914. doi: 10.1007/s42770-019-00104-3. Epub 2019 Jun 25.
Biological nitrogen fixation (BNF) with the soybean crop probably represents the major sustainable technology worldwide, saving billions of dollars in N fertilizers and decreasing water pollution and the emission of greenhouse gases. Accordingly, the identification of strains occupying nodules under field conditions represents a critical step in studies that are aimed at guaranteeing increased BNF contribution. Current methods of identification are mostly based on serology, or on DNA profiles. However, the production of antibodies is restricted to few laboratories, and to obtain DNA profiles of hundreds of isolates is costly and time-consuming. Conversely, the matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) MS technique might represent a golden opportunity for replacing serological and DNA-based methods. However, MALDI-TOF databases of environmental microorganisms are still limited, and, most importantly, there are concerns about the discrimination of protein profiles at the strain level. In this study, we investigated four soybean rhizobial strains carried in commercial inoculants used in over 35 million hectares in Brazil and also in other countries of South America and Africa. A supplementary MALDI-TOF database with the protein profiles of these rhizobial strains was built and allowed the identification of unique profiles statistically supported by multivariate analysis and neural networks. To test this new database, the nodule occupancy by Bradyrhizobium strains in symbiosis with soybean was characterized in a field experiment and the results were compared with serotyping of bacteria by immuno-agglutination. The results obtained by both techniques were highly correlated and confirmed the viability of using the MALDI-TOF MS technique to effectively distinguish bacteria at the strain level.
生物固氮(BNF)与大豆作物相结合,可能代表了全球主要的可持续技术,节省了数十亿美元的氮肥,并减少了水污染和温室气体排放。因此,在旨在保证增加 BNF 贡献的研究中,鉴定在田间条件下占据根瘤的菌株是一个关键步骤。目前的鉴定方法主要基于血清学或 DNA 图谱。然而,抗体的产生仅限于少数几个实验室,而获得数百个分离株的 DNA 图谱既昂贵又耗时。相比之下,基质辅助激光解吸/电离飞行时间(MALDI-TOF)MS 技术可能为替代血清学和基于 DNA 的方法提供了一个绝佳机会。然而,环境微生物的 MALDI-TOF 数据库仍然有限,最重要的是,人们对在菌株水平上区分蛋白质图谱表示担忧。在这项研究中,我们研究了四种商业接种剂中携带的大豆根瘤菌株,这些接种剂在巴西和南美洲和非洲的其他国家使用了超过 3500 万公顷。建立了一个包含这些根瘤菌株蛋白质图谱的补充 MALDI-TOF 数据库,通过多元分析和神经网络统计支持,鉴定了独特的图谱。为了测试这个新数据库,我们在田间试验中对与大豆共生的布拉氏根瘤菌菌株的根瘤占据情况进行了表征,并将结果与免疫凝集法对细菌的血清型进行了比较。两种技术获得的结果高度相关,证实了使用 MALDI-TOF MS 技术有效区分菌株水平上细菌的可行性。