Unraveling Asian Soybean Rust metabolomics using mass spectrometry and Molecular Networking approach

Abstract

Asian Soybean Rust (ASR), caused by the biotrophic fungus Phakopsora pachyrhizi, is a devastating disease with an estimated crop yield loss of up to 90%. Yet, there is a nerf of information on the metabolic response of soybean plants to the pathogen Untargeted metabolomics and Global natural products Social Molecular networking platform approach was used to explore soybean metabolome modulation to P. pachyrhizi infection. Soybean plants susceptible to ASR was inoculated with P. pachyrhizi spore suspension and non-inoculated plants were used as controls. Leaves from both groups were collected 14 days post-inoculation and extracted using different extractor solvent mixtures. The extracts were analyzed on an ultra-high performance liquid chromatography system coupled to high-definition electrospray ionization-mass spectrometry. There was a significant production of defense secondary metabolites (phenylpropanoids, terpenoids and flavonoids) when P. pachyrhizi infected soybean plants, such as putatively identified liquiritigenin, coumestrol, formononetin, pisatin, medicarpin, biochanin A, glyoceollidin i, glyoceollidin ii, glyoceollin i, glyoceolidin ii, glyoceolidin III, glyoceolidin IV, glyoceolidin VI. Primary metabolites (amino acids, peptides and lipids) also were putatively identified. This is the first report using untargeted metabolomics and GNPS-Molecular Networking approach to explore ASR in soybean plants. Our data provide insights into the potential role of some metabolites in the plant resistance to ASR, which could result in the development of resistant genotypes of soybean to P. pachyrhizi, and effective and specific products against the pathogen. The soybean (Glycine max (L.) Merrill) is prominent among crops due to its agro-economic and nutritional value, used mainly as a source of proteins and oils for human consumption, in animal feeds and for biofuel production 1,2. However, estimates indicate a necessity to double global agricultural output by 2050 to feed a rising population, hence soybean productivity needs to be increased by 2.4% per annum 3. Yet, soybean diseases were estimated to reduce crop yield by 11% in the United States 4 and 50% or greater in the southeastern United States 5. The Asian Soybean Rust (ASR) was registered for the first time in Brazil during the 2001/2002 harvest 6. Recently, Brazilian soybean farmers spent US$ 2.16 billion with fungicides during the 2016/2017 harvest, and 96% of the sum was used for ASR control. Another US$ 1.62 billion was invested on insecticides, totaling US$ 3.78 billion. This amount represented 12.4% of the production costs for the harvest 7. Despite increasing costs, disease management practices are needed as yield losses of up to 90% have already been reported when control measures were absent 4 .

Untargeted Metabolomics Analysis by UHPLC-MS/MS of Soybean Plant in a Compatible Response to Phakopsora pachyrhizi Infection

“…Daidzein is a precursor in the metabolic pathway that results in the production of soybean isoflavonoids [44]. In the study previously reported by us, using genotype susceptible to ASR, we observed through qualitative analysis a significant production of flavonoids and isoflavonoids in plants inoculated with P. pachyrhizi, as a plant defense response [24].…”

“…The get seeds (daughters seeds) having homogeneous physiological characteristics were obtained from a single seed (mother seed). The experiment using the seeds was carried out in a greenhouse under the same growth conditions described in Silva et al 2020 [24].…”

“…The spores of P. pachyrhizi were supplied by the Embrapa Soybean Phytopathology Laboratory (Londrina, Parana, Brazil), obtained from cultivar BRS 284 (susceptible standard), with 92% of germination viability. The inoculum was prepared as described in Silva et al 2020 [24]. The soybean plants were divided into two groups: 6 control plants and 6 inoculated plants.…”

“…Soybean leaves were macerated, separately, using liquid nitrogen to preserve the sample during the process. The metabolite extraction was performed as described in Silva et al 2020 [24]. The samples were concentrated in nitrogen flow and stored in a freezer at −20 • C until analysis.…”

“…We previously reported the metabolomics of a soybean genotype susceptible to P. pachyrhizi using mass spectrometry combined with the Molecular Networking tool. The results revealed a significant production of secondary defense metabolites in the plant infected by P. pachyrhizi, which originated from the phenylpropanoid and flavonoid pathways [24]. In this study, we performed an untargeted metabolomics analysis of a soybean plant containing the Rpp3 gene [25], that shows incomplete resistance with RB-type lesion, in response to infection by P. pachyrhizi.…”