Longitudinal Transcriptomic, Proteomic, and Metabolomic Analyses of Citrus sinensis (L.) Osbeck Graft-Inoculated with “Candidatus Liberibacter asiaticus”

• Published in: Journal of proteome research 2020-02, Vol.19 (2), p.719-732
• Main Authors: Chin, Elizabeth L, Ramsey, John S, Mishchuk, Darya O, Saha, Surya, Foster, Elizabeth, Chavez, Juan D, Howe, Kevin, Zhong, Xuefei, Polek, MaryLou, Godfrey, Kris E, Mueller, Lukas A, Bruce, James E, Heck, Michelle, Slupsky, Carolyn M
• Format: Article
• Language: English
• ISSN: 1535-3893; 1535-3907
• DOI: 10.1021/acs.jproteome.9b00616

“Candidatus Liberibacter asiaticus” (CLas) is the bacterium associated with the citrus disease Huanglongbing (HLB). Current CLas detection methods are unreliable during presymptomatic infection, and understanding CLas pathogenicity to help develop new detection techniques is challenging because CLas has yet to be isolated in pure culture. To understand how CLas affects citrus metabolism and whether infected plants produce systemic signals that can be used to develop improved detection techniques, leaves from Washington Navel orange (Citrus sinensis (L.) Osbeck) plants were graft-inoculated with CLas and longitudinally studied using transcriptomics (RNA sequencing), proteomics (liquid chromatography–tandem mass spectrometry), and metabolomics (proton nuclear magnetic resonance). Photosynthesis gene expression and protein levels were lower in infected plants compared to controls during late infection, and lower levels of photosynthesis proteins were identified as early as 8 weeks post-grafting. These changes coordinated with higher sugar concentrations, which have been shown to accumulate during HLB. Cell wall modification and degradation gene expression and proteins were higher in infected plants during late infection. Changes in gene expression and proteins related to plant defense were observed in infected plants as early as 8 weeks post-grafting. These results reveal coordinated changes in greenhouse navel leaves during CLas infection at the transcript, protein, and metabolite levels, which can inform of biomarkers of early infection.