IDENTIFICATION OF GROWTH INHIBITING METABOLITE COMPOUNDS FUSARIUM OXYSPORUM F.SP. CUBENSE BY THE BACTERIA CONSORTIUM: A METABOLOMICS APPROACH WITH 1H NMR

• Main Author: El Hadi, Atikah
• Format: Theses
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/78520
• Institution: Institut Teknologi Bandung

Fusarium oxysporum f.sp. cubense (Foc) is a banana plant disease that causes yellowish, wilted, and brown leaves, and inhibits growth until the plant dies. This disease is a major factor in the decline in the productivity and quality of banana plants in Indonesia. Foc produces a toxin as Fusaric acid which contributes to Fusarium wilt disease, so it is necessary to control Foc wilt using biological agents. Using soil bacteria as a consortium has been shown to have the potential to inhibit Foc growth in-vitro and in-vivo. Researchers conducted a metabolomics study on a consortium of bacteria (Bacillus cereus strain CCM 2010 and Lysinibacillus xylanilyticus strain XDB9) and Foc, an inhibitory agent, to understand the mechanism of inhibition. They used the NMR approach as a tool for this study. This study aims to identify the optimum inoculum age for inhibiting bacteria and Foc and the metabolite profile of the bacteria consortium inhibiting Foc. We evaluated bacterial consortium and Foc through growth curves, in vitro activity test of extracellular bacteria consortium antagonists and Agilent 500 MHz 1H NMR metabolomics analysis. Metabolomic analysis of 1H NMR was performed on the bacterial consortium (K), the bacterial consortium and Fusaric acid (KFA) and the bacterial consortium and Fusarium oxysporum f.sp. cubense (KFOC). Each treatment consisted of 5 biological replicas and 3 technical replicas. The Agilent 500 MHz 1H NMR metabolomics data was analyzed by pre-processing with MestreNova (V14.2.1), signal processing with R studio v2023.03.1, and data analysis with MetaboAnalyst 5.0. Data analysis methods included enrichment analysis, ANOVA, principal component analysis (PCA), partial least squares-discriminant analysis (PLS-DA), orthogonal partial least squares-discriminant analysis (OPLS-DA) and biomarker analysis. The results showed that the optimum inoculum age for the inhibition of the bacterial consortium on the growth of Foc culture occurred on the 10th day at 45.27%. The K treatment had 40 metabolites, KFA treatment had 56, KFOC had 63, and all treatments had a total of 60 metabolites identified by 1H NMR spectral analysis. Replications of each treatment showed consistent results and the metabolites in the samples were divided into two major groups, namely K and KFOC treatments. Meanwhile, the KFA treatment was in the second group. We classified identified metabolites as fatty acids, organic acids, organic oxygen compounds, carbohydrates, organoheterocyclic compounds, and benzenoids. Meanwhile, the metabolites of organic nitrogen compounds and nucleic acids were found in the KFA treatment and the polyketide groups in the KFA and KFOC treatments. The highest organic compounds in the K treatment were fatty acids and the highest organic compounds in the KFA and KFOC treatments were organic acids. Metabolites from all treatments produced 40 metabolites with concentrations of significant value based on the ANOVA test with a p value <0.05. Organic acids, fatty acids, organic oxygen compounds, carbohydrates, and organoheterocyclic compounds appeared in all three treatments. PCA analysis revealed a 70.5% difference in component diversity among the three treatments. The PLS-DA analysis results show data accuracy with VIP value > 1; the R2 value is 0.99 and the Q2 value is 0.97. The results of the analysis of the OPLS-DA method with a VIP value of > 1.0 and an ROC with an AUC value of 1 identified 29 biomarkers of the KFA treatment and 20 biomarkers of the KFOC treatment from the groups of fatty acid compounds, organic oxygen compounds, organic acids, organoheterocyclic compounds, carbohydrates and nucleic acids. Analysis of bacterial pathways using the KEGG database showed that 9 pathways involved with a p value <0.05 and pathway impact > 0.1 were aminoacyl-tRNA biosynthesis; biosynthesis of valine, leucine and isoleucine; arginine and proline metabolism; synthesis and degradation of ketone bodies; metabolism of glycine, serine and threonine; arginine biosynthesis; butanoate metabolism; pantothenic and CoA biosynthesis and metabolism of alanine, aspartate and glutamate. The study found differences in metabolite profiles and concentrations for each treatment of K, KFA, KFOC. L-valine, N-acetylglycine, 2-oxobutyric and 2-aminobutyric acid can prevent Fusarium sp. growth as they are antifungal. Metabolite compounds belong to groups of organic acids, fatty acids, organic oxygen compounds, carbohydrates and organoheterocyclic compounds.