代谢组学
化学计量学
计算生物学
疾病
生物
病菌
生物技术
微生物学
化学
生物信息学
色谱法
医学
病理
作者
João Guilherme de Moraes Pontes,William Y. Ohashi,Antonio Jadson Marreiro Brasil,Paulo R. Filgueiras,Ana Paula D.M. Espindola,Jaqueline S. Silva,Ronei J. Poppi,Helvécio Della Coletta-Filho,Ljubica Tasić
标识
DOI:10.1002/slct.201600064
摘要
Candidatus Liberibacter spp. is the pathogen associated with Huanglongbing (HLB), a disease with an economic impact in the order of billions of dollars to the worldwide citrus industry. A key point to reduce HLB economic losses lies on early detection on asymptomatic stages of the infection by new detection methods as it is still not possible to cultivate Candidatus Liberibacter spp. in vitro, and the polymerase chain reaction (PCR) method used nowadays is not manageable in large scale. In this study, we search for metabolic biomarkers from Citrus sinensis leaves in different disease stages using a combined approach of NMR spectroscopy and chemometrics. Chemometric clustering was observed, providing excellent tools for class discrimination, with high accuracy, therefore enabling metabolic profile differentiation on disease early stages. Around 20 different key biomarkers, metabolites responsible for the clustering of each group, were identified using 2D NMR experimental data.
科研通智能强力驱动
Strongly Powered by AbleSci AI