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

ABSTRACT: The plant cell wall structure can be altered by pathogen-secreted polygalacturonases (PGs) that cleave the α-(1→4) linkages occurring between D-galacturonic acid residues in homogalacturonan. The activity of the PGs leads to cell wall maceration, 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 defence 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.

SUBMITTER: Acharya S

PROVIDER: S-EPMC10698527 | biostudies-literature | 2024 Feb

REPOSITORIES: biostudies-literature

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

Acharya Sudha S Troell Hallie A HA Billingsley Rebecca L RL Lawrence Katherine S KS McKirgan Daniel S DS Alkharouf Nadim W NW Klink Vincent P VP

Data in brief 20231119

The plant cell wall structure can be altered by pathogen-secreted polygalacturonases (PGs) that cleave the α-(1→4) linkages occurring between D-galacturonic acid residues in homogalacturonan. The activity of the PGs leads to cell wall maceration, 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 <i>Glycine max</i> PGIP11 (<i>GmPGIP11</i>) is expressed within a root c ...[more]

PMID: 38076472

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Project description:BackgroundThe PolyGalacturonase-Inhibiting Proteins (PGIP) of plant cell wall limit the invasion of phytopathogenic organisms by interacting with the enzyme PolyGalacturonase (PG) they secrete to degrade pectin present in the cell walls. PGIPs from different or same plant differ in their inhibitory activity towards the same PG. PGIP2 from Phaseolus vulgaris (Pv) inhibits the PG from Fusarium moniliforme (Fm) although PGIP1, another member of the multigene family from the same plant sharing 99% sequence similarity, cannot. Interestingly, PGIP3 from Glycine max (Gm) which is a homologue of PGIP2 is capable of inhibiting the same PG although the extent of similarity is lower and is 88%. It therefore appears that subtle changes in the sequence of plant PGIPs give rise to different specificity for inhibiting pathogenic PGs and there exists no direct dependence of function on the extent of sequence similarity.ResultsStructural information for any PGIP-PG complex being absent, we resorted to molecular modelling to gain insight into the mechanism of recognition and discrimination of PGs by PGIPs. We have built homology models of PvPGIP1 and GmPGIP3 using the crystal structure of PvPGIP2 (1OGQ) as template. These PGIPs were then docked individually to FmPG to elucidate the characteristics of their interactions. The mode of binding for PvPGIP1 to FmPG considerably differs from the mode observed for PvPGIP2-FmPG complex, regardless of the high sequence similarity the two PGIPs share. Both PvPGIP2 and GmPGIP3 despite being relatively less similar, interact with residues of FmPG that are known from mutational studies to constitute the active site of the enzyme. PvPGIP1 tends to interact with residues not located at the active site of FmPG. Looking into the electrostatic potential surface for individual PGIPs, it was evident that a portion of the interacting surface for PvPGIP1 differs from the corresponding region of PvPGIP2 or GmPGIP3.Conclusionvan der Waals and electrostatic interactions play an active role in PGIPs for proper recognition and discrimination of PGs. Docking studies reveal that PvPGIP2 and GmPGIP3 interact with the residues constituting the active site of FmPG with implications that the proteins bind/block FmPG at its active site and thereby inhibit the enzyme.

Project description:Grain aphid (Sitobion avenae F) and pea aphid (Acyrthosiphon pisum) are two agriculturally important pest species, which cause significant yield losses to crop plants each year by inflicting damage both through the direct effects of feeding and by vectoring debilitating plant viruses. Although a close phylogenetic relationship between grain aphid and pea aphid was proposed, the biological variations between these two aphid species are obvious. While the host ranges of grain aphid is restricted to cereal crops and in particular wheat, that of pea aphid is wider, mainly colonizing leguminous plant species. Until now, the genetic factors underlying the divergence between grain aphid and pea aphid still remain unclear due to the limited genomic data of grain aphid available in public databases.Based on a set of transcriptome data of grain aphid generated by using Roche 454 GS-FLX pyrosequencing, comparative analysis between this set of transcriptome data of grain aphid and mRNA sequences of pea aphid available in the public databases was performed. Compared with mRNA sequences of pea aphid, 4,857 unigenes were found to be specifically presented in the transcriptome of grain aphid under the rearing conditions described in this study. Furthermore, 3,368 orthologous pairs which could be calculated with both nonsynonymous (Ka) and synonymous (Ks) substitutions were used to infer their sequence divergences. The average differences in the coding, 5' and 3' untranslated regions of these orthologs were 10.53%, 21.29% and 18.96%, respectively. Moreover, of 340 orthologs which were identified to have evolved in response to positive selection based on the rates of Ka and Ks substitutions, 186 were predicted to be involved in secondary metabolism and xenobiotic metabolisms which might contribute to the divergence of these two aphid species.The comprehensive transcriptome divergent sequence analysis between grain aphid and pea aphid provides an invaluable resource for the investigation of genes involved in host plant adaptation and evolution. Moreover, the demonstration of divergent transcriptome sequences between grain aphid and pea aphid pave the way for the investigation of the molecular mechanisms underpinning the biological variations of these two agriculturally important aphid species.

Project description:Different sugarcane cultivars are grown to produce renewable energy and sugar in China. However, we have a limited awareness of the interactive influence of varying sugarcane cultivars on rhizosphere bacterial structure and diversity. Assessing cultivar choice impact on soil bacterial communities is vital since bacterial taxa are frequently impacted by planting performance. Employing high-throughput Illumina sequencing, we examined bacterial communities' assemblage in the rhizosphere of six Chinese sugarcane cultivars (Regan14-62, Guitang 08-120, Haizhe 22, Guitang 08-1180, Taitang 22 and Liucheng 05-136). Our results indicated that different sugarcane cultivars have no significant influence on the Shannon index; however, their impact on richness was substantial. There was a difference in the bacterial community structure that is also associated with a change in the community composition, as determined by the DESeq2 results, suggesting that "Haizhe 22 (HZ22)" had a completely different beta diversity as compared to other five cultivars by enriching abundance of Firmicutes, Proteobacteria, Gemmatimonadetes, Saccharibacteria and Bacteroidetes and reducing the quantity of Actinobacteria, Chloroflexi, Acidobacteria, and Planctomycetes, respectively. The HZ22 rhizosphere significantly enriched six genera (e.g., Devosia, Mizugakiibacter, Mycobacterium, Nakamurella, Rhizomicrobium, and Virgibacillus) relative to other varieties, suggesting an important role in plant disease tolerance and growth development, including soil nutrient cycling and bioremediation. Analysis of similarity (ANOSIM) and correlation analysis revealed that cultivars, soil organic matter, pH and soil moisture were central factors influencing bacterial composition. These findings may help in selection of plant cultivars capable of supporting highly abundant specific beneficial microbial groups, improving plant disease resistance, growth stimulation, and soil bioremediation capabilities, further leading to improvements in breeding strategies.Supplementary informationThe online version contains supplementary material available at 10.1007/s13205-021-03091-1.

Dataset Information

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

Publications

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

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