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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Molecular Plant Pathology Laboratory » Research » Publications at this Location » Publication #399540

Research Project: Emerging Biotechnologies for Developing Improved Pest and Pathogen Resistant Sugar Beet

Location: Molecular Plant Pathology Laboratory

Title: Data analysis of polygalacturonase inhibiting proteins (PGIPs) from agriculturally important proteomes

Author
item ACHARYA, SUDHA - Towson University
item TROELL, HALLIE - Mississippi State University
item BILLINGSLEY, REBECCA - Mississippi State University
item LAWERENCE, KATHERINE - Auburn University
item MCKIRGAN, DANIEL - Towson University
item ALKHAROUF, NADIM - Towson University
item Klink, Vincent

Submitted to: Data in Brief
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 11/14/2023
Publication Date: 11/19/2023
Citation: Acharya, S., Troell, H.A., Billingsley, R.L., Lawerence, K.S., Mckirgan, D., Alkharouf, N.W., Klink, V.P. 2023. Data analysis of polygalacturonase inhibiting proteins (PGIPs) from agriculturally important proteomes. Data in Brief. Article: 109831. https://doi.org/10.1016/j.dib.2023.109831.
DOI: https://doi.org/10.1016/j.dib.2023.109831

Interpretive Summary: As a model for Beta vulgaris (sugar beet) root defense processes, Glycine max (soybean) polygalacturonase inhibiting protein (PGIPs genes have been identified that are expressed in its root cell undergoing a defense response to a parasitic nematode attack. It is hypothesized that the PGIPs from different plant species will function broadly among different plant species to protect them from attack by different pathogens. Functional transgenic experiments demonstrate the candidate defense genes do function to protect soybean from infection by a root pathogenic nematode, Heterodera glycines. Using the protein sequences isolated from Genbank, analyses of 52 different plant proteomes have led to the identification of protein homologs from each of the 52 proteomes. Artificial intelligence analysis have identified whether the predicted PGIP proteins identified from the 52 proteomes have characteristics of secreted proteins and where in the cell they localize to. Furthermore, signal peptides and their cleavage sites, O- and N-glycosylation features have been determined. The work leads to the identification of PGIPs that are predicted by bioinformatics, functional transgenic experiments and artificial intelligence to work in sugar beet against root and other pathogens.

Technical Abstract: The plant cell wall structure can be altered by pathogen-secreted polygalacturonases (PGs) that cleave the a-(1'4) linkages occurring between D-galacturonic acid residues in homogalacturonan. The activity of the PGs macerates the cell wall, facilitating infection. Plant PG inhibiting proteins (PGIPs) impede pathogen PGs, impairing infection and leading to the ability of the plant to resist infection. Analyses show the Glycine max PGIP11 (GmPGIP11) is expressed within a root cell that is parasitized by the pathogenic nematode Heterodera glycines, the soybean cyst nematode (SCN), but while undergoing a defense response that leads to its demise. Transgenic experiments show GmPGIP11 overexpression leads to a successful defence response, while the overexpression of a related G. max PGIP, GmPGIP1 does not, indicating a level of specificity. The analyses presented here have identified PGIPs from 51 additional studied proteomes, many of agricultural importance. The analyses include the computational identification of signal peptides and their cleavage sites, O-, and N-glycosylation. Artificial intelligence analyses determine the location where the processed protein localize. The identified PGIPs are presented as a tool base from which functional transgenics can be performed to determine whether they may have a role in plant-pathogen interactions.