Proteomics Based Study of Soybean and Phakopsora pachyrhizi Interaction

2013 ◽  
Vol 14 (1) ◽  
pp. 29 ◽  
Author(s):  
M. Ganiger ◽  
D. R. Walker ◽  
Z. Y. Chen
Keyword(s):  
Gel Electrophoresis ◽  
Time Course ◽  
Molecular Level ◽  
Protein Profile ◽  
Differentially Expressed ◽  
Soybean Rust ◽  
Phakopsora Pachyrhizi ◽  
Yield Losses ◽  
Resistant Line ◽  
Differentially Expressed Protein

Phakopsora pachyrhizi, the causal agent of Asian soybean rust (ASR), has the potential to cause severe yield losses as all currently grown U.S. commercial soybean varieties are susceptible. In this proteomics study, we compared two soybean sibling lines, a resistant line 10G18 and a susceptible line 10G21 derived from Recombinant Inbred Line (RIL) population RN06-32-2 to understand the compatible and incompatible host-pathogen interactions at the molecular level. We compared the protein profile differences between the two lines over a time-course of 14 days with or without P. pachyrhizi inoculation using differential in-gel electrophoresis (DIGE). Approximately 70 differentially expressed spots between 10G18 and 10G21 lines with and without P. pachyrhizi inoculation were identified. Some of these spots, which were up- and down-regulated in resistant line 10G18, were sequenced using LC-MS/MS. Of the 70 differentially expressed protein spots, 31 up-regulated and 6 down-regulated spots in resistant line 10G18 were sequenced. These sequenced proteins were mostly involved in photosynthesis based on homology searches. The involvement in disease resistance for some of these differentially up-regulated proteins has been reported, indicating their possible role in soybean defense against ASR. However, further studies are necessary. Accepted for publication 3 September 2013. Published 25 November 2013.

scholarly journals Transcriptome analyses and virus induced gene silencing identify genes in the Rpp4-mediated Asian soybean rust resistance pathway

2013 ◽  
Vol 40 (10) ◽  
pp. 1029 ◽  
Author(s):  
Aguida M. A. P. Morales ◽  
Jamie A. O'Rourke ◽  
Martijn van de Mortel ◽  
Katherine T. Scheider ◽  
Timothy J. Bancroft ◽  
...  
Keyword(s):  
Gene Expression ◽  
Transcription Factors ◽  
Gene Silencing ◽  
Differentially Expressed ◽  
Soybean Rust ◽  
Phakopsora Pachyrhizi ◽  
R Gene ◽  
Virus Induced Gene Silencing ◽  
Asian Soybean Rust ◽  
Defence Responses

Rpp4 (Resistance to Phakopsora pachyrhizi 4) confers resistance to Phakopsora pachyrhizi Sydow, the causal agent of Asian soybean rust (ASR). By combining expression profiling and virus induced gene silencing (VIGS), we are developing a genetic framework for Rpp4-mediated resistance. We measured gene expression in mock-inoculated and P. pachyrhizi-infected leaves of resistant soybean accession PI459025B (Rpp4) and the susceptible cultivar (Williams 82) across a 12-day time course. Unexpectedly, two biphasic responses were identified. In the incompatible reaction, genes induced at 12 h after infection (hai) were not differentially expressed at 24 hai, but were induced at 72 hai. In contrast, genes repressed at 12 hai were not differentially expressed from 24 to 144 hai, but were repressed 216 hai and later. To differentiate between basal and resistance-gene (R-gene) mediated defence responses, we compared gene expression in Rpp4-silenced and empty vector-treated PI459025B plants 14 days after infection (dai) with P. pachyrhizi. This identified genes, including transcription factors, whose differential expression is dependent upon Rpp4. To identify differentially expressed genes conserved across multiple P. pachyrhizi resistance pathways, Rpp4 expression datasets were compared with microarray data previously generated for Rpp2 and Rpp3-mediated defence responses. Fourteen transcription factors common to all resistant and susceptible responses were identified, as well as fourteen transcription factors unique to R-gene-mediated resistance responses. These genes are targets for future P. pachyrhizi resistance research.

scholarly journals Identifying Soybean Rust-resistant and Susceptible Populations of Kudzu to Increase Disease Monitoring Efficiency in Alabama

2016 ◽  
Vol 17 (4) ◽  
pp. 239-244 ◽  
Author(s):  
Edward J. Sikora ◽  
Mary A. Delaney
Keyword(s):  
Monitoring Program ◽  
Soybean Rust ◽  
Disease Monitoring ◽  
Phakopsora Pachyrhizi ◽  
Yield Losses ◽  
Early Disease ◽  
Soybean Production ◽  
Early Disease Detection ◽  
Significant Yield ◽  
Susceptible Populations

Soybean rust (SBR), caused by Phakopsora pachyrhizi, is considered to be one of the most damaging diseases of soybean worldwide. Monitoring for the disease in Alabama relies heavily on scouting kudzu on a biweekly basis in south and central portions of the state from late January through the end of July in areas where soybean production is minimal and is critical to help growers avoid significant yield losses from SBR. Previous studies have reported that some kudzu populations are naturally resistant or immune to infection from the pathogen which can complicate early disease detection. This study will apply that knowledge to determine locations of kudzu populations that are either resistant or susceptible to P. pachyrhizi in order to increase monitoring efficiency and reduce costs associated with the scouting program. Results show that approximately 34% of the 162 kudzu sites tested in Alabama were resistant to P. pachyrhizi. By focusing scouting efforts on SBR-susceptible kudzu sites, we will reduce costs associated with the monitoring program by approximately 25% which is critical at a time when funding for such efforts is decreasing. Accepted for publication 24 October 2016.

scholarly journals Asian soybean rust in Brazil: past, present, and future

2016 ◽  
Vol 51 (5) ◽  
pp. 407-421 ◽  
Author(s):  
Cláudia Vieira Godoy ◽  
Claudine Dinali Santos Seixas ◽  
Rafael Moreira Soares ◽  
Franscismar Correa Marcelino-Guimarães ◽  
Maurício Conrado Meyer ◽  
...  
Keyword(s):  
Severe Disease ◽  
Management Strategies ◽  
Soybean Rust ◽  
Phakopsora Pachyrhizi ◽  
Yield Losses ◽  
Current Management ◽  
Asian Soybean Rust ◽  
Regulatory Measures ◽  
Major Resistance Genes ◽  
Crop System

Abstract: Asian soybean rust, caused by the fungus Phakopsora pachyrhizi, is the most severe disease of the crop and can cause yield losses of up to 90%. The disease was first reported in Brazil in 2001. Epidemics of the disease are common in the country, where the fungus can survive year-round. Regulatory measures to reduce the inoculum between seasons and avoid late-season soybean have been adopted to manage the disease. Disease control has relied mainly on chemical control, but a lower sensibility of the fungus to fungicides has been reported in Brazil. Major-resistance genes have been mapped and incorporated into the cultivars. With the reduced efficacy of the fungicides, the adoption of integrated measures to control the disease will be important for the sustainability of the crop. This review presents the main changes in the soybean crop system caused by the introduction of the fungus in Brazil, the current management strategies adopted to avoid losses, and the new trends that, together with biotechnological strategies, can improve management in the future.

scholarly journals Bacillus thuringiensis Combined With Fungicide Applications in the Management of Soybean Leaf Diseases

2019 ◽  
Vol 11 (13) ◽  
pp. 226
Author(s):  
Mônica A. Müller ◽  
Ana C. Klosowski ◽  
Maristella Dalla Pria ◽  
Sérgio M. Mazaro ◽  
Louise L. May De Mio
Keyword(s):  
Bacillus Thuringiensis ◽  
Soybean Rust ◽  
Phakopsora Pachyrhizi ◽  
Yield Losses ◽  
Resistance Induction ◽  
Foliar Diseases ◽  
Asian Soybean Rust ◽  
Soybean Leaf

Asian soybean rust (ASR) caused by Phakopsora pachyrhizi is the main soybean leaf disease in Brazil. Downy mildew (Peronospora manshurica) and powdery mildew (Microsphaera diffusa) are important soybean foliar diseases of occurrence in Paraná state. To reduce severity and yield losses caused by soybean foliar diseases, this work aimed to verify the efficacy of different application doses of the commercial product Dipel® Bacillus thuringiensis (Bt), which is a biological insect controller, combined with number of Opera® fungicide (pyraclostrobin + epoxiconazole) intercalated applications, and to investigate the effect of the Bt Dipel® in the resistance induction of soybean. For this study, different methodologies were used, including in vitro, in vivo and field assays. The results showed that Bt Dipel® can reduce soybean foliar diseases by inducing β-1,3 glucanase enzime and phytoalexin gliceolin. The fungicide application in the experiment condition reduced yield losses.

scholarly journals ITRAQ-based quantitative proteomic analysis of Fusarium moniliforme (Fusarium verticillioides) in response to Phloridzin inducers

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Rong Zhang ◽  
Weitao Jiang ◽  
Xin Liu ◽  
Yanan Duan ◽  
Li Xiang ◽  
...  
Keyword(s):  
Fusarium Moniliforme ◽  
Abiotic Factors ◽  
Fusarium Verticillioides ◽  
Protein Profile ◽  
Sugar Metabolism ◽  
Differentially Expressed ◽  
Pcr Analysis ◽  
Differentially Expressed Proteins ◽  
Apple Replant Disease ◽  
Qrt Pcr

Abstract Background Apple replant disease (ARD) has been reported from all major fruit-growing regions of the world, and is often caused by biotic factors (pathogen fungi) and abiotic factors (phenolic compounds). In order to clarify the proteomic differences of Fusarium moniliforme under the action of phloridzin, and to explore the potential mechanism of F. moniliforme as the pathogen of ARD, the role of Fusarium spp. in ARD was further clarified. Methods In this paper, the quantitative proteomics method iTRAQ analysis technology was used to analyze the proteomic differences of F. moniliforme before and after phloridzin treatment. The differentially expressed protein was validated by qRT-PCR analysis. Results A total of 4535 proteins were detected, and 293 proteins were found with more than 1.2 times (P< 0.05) differences. In-depth data analysis revealed that 59 proteins were found with more than 1.5 times (P< 0.05) differences, and most proteins were consistent with the result of qRT-PCR. Differentially expressed proteins were influenced a variety of cellular processes, particularly metabolic processes. Among these metabolic pathways, a total of 8 significantly enriched KEGG pathways were identified with at least 2 affiliated proteins with different abundance in conidia and mycelium. Functional pathway analysis indicated that up-regulated proteins were mainly distributed in amino sugar, nucleotide sugar metabolism, glycolysis/ gluconeogenesis and phagosome pathways. Conclusions This study is the first to perform quantitative proteomic investigation by iTRAQ labeling and LC-MS/MS to identify differentially expressed proteins in F. moniliforme under phloridzin conditions. The results confirmed that F. moniliforme presented a unique protein profile that indicated the adaptive mechanisms of this species to phloridzin environments. The results deepened our understanding of the proteome in F. moniliforme in response to phloridzin inducers and provide a basis for further exploration for improving the efficiency of the fungi as biocontrol agents to control ARD.

scholarly journals The Alterations in Methylene Blue/Light-Treated Frozen Plasma Proteins Revealed by Proteomics

2021 ◽  
pp. 1-8
Author(s):  
Tiange Wu ◽  
Xiaoning Wang ◽  
Kai Ren ◽  
Xiaochen Huang ◽  
Jiankai Liu
Keyword(s):  
Mass Spectrometry ◽  
Methylene Blue ◽  
Western Blot ◽  
Blue Light ◽  
Differentially Expressed ◽  
Enzyme Linked Immunosorbent Assay ◽  
Differentially Expressed Protein ◽  
Significant Difference ◽  
Modified Proteins ◽  
Frozen Plasma

Introduction: The aim of this study was to investigate the modified proteins in methylene blue/light-treated frozen plasma (MB-FP) compared with fresh frozen plasma (FFP) in order to gain a better application of MB/light-treated plasma in clinic transfusion. Methods: MB-FP and FFP were collected from Changchun central blood station, and a trichloroacetic acid/acetone precipitation method was used to remove albumin for the enrichment of lower abundance proteins. The plasma protein in MB-FP and FFP were separated using two-dimensional gel electrophoresis (2-DE) and the differentially expressed protein spots were analyzed using mass spectrometry. Finally, the differentially expressed proteins were tested using Western blot and enzyme-linked immunosorbent assay (ELISA). Results: Approximately 14 differentially expressed protein spots were detected in the MB-FP, and FFP was chosen as the control. After 2-DE comparison analysis and mass spectrometry, 8 significantly differentially expressed protein spots were identified, corresponding to 6 different proteins, including complement C1r subcomponent (C1R), inter-alpha-trypsin inhibitor heavy chain H4 (ITI-H4), keratin, type II cytoskeletal 1 (KRT1), hemopexin (HPX), fibrinogen gamma chain (FGG), and transthyretin (TTR). Western blot showed no significant difference in the expression level of KRT1 between MB-FP and FFP (p > 0.05). Both Western blot and ELISA indicated that the level of HPX was significantly higher in FFP than in MB-FP (p < 0.05). Conclusion: This comparative proteomics study revealed that some significantly modified proteins occur in MB-FP, such as C1R, ITI-H4, KRT1, HPX, FGG, and TTR. Our findings provide more theoretical data for using MB-FP in transfusion medicine. However, the relevance of the data for the transfusion of methylene blue/light-treated plasma remains unclear. The exact modification of these proteins and the effects of these modified proteins on their functions and their effects in clinical plasma infusion need to be further studied.

scholarly journals Prediction of Short-Distance Aerial Movement of Phakopsora pachyrhizi Urediniospores Using Machine Learning

2017 ◽  
Vol 107 (10) ◽  
pp. 1187-1198 ◽  
Author(s):  
L. Wen ◽  
C. R. Bowen ◽  
G. L. Hartman
Keyword(s):  
Machine Learning ◽  
Random Forest ◽  
Short Distance ◽  
Soybean Rust ◽  
Machine Learning Techniques ◽  
Phakopsora Pachyrhizi ◽  
Primary Means ◽  
Soybean Plants ◽  
Selection Operator ◽  
Active Trap

Dispersal of urediniospores by wind is the primary means of spread for Phakopsora pachyrhizi, the cause of soybean rust. Our research focused on the short-distance movement of urediniospores from within the soybean canopy and up to 61 m from field-grown rust-infected soybean plants. Environmental variables were used to develop and compare models including the least absolute shrinkage and selection operator regression, zero-inflated Poisson/regular Poisson regression, random forest, and neural network to describe deposition of urediniospores collected in passive and active traps. All four models identified distance of trap from source, humidity, temperature, wind direction, and wind speed as the five most important variables influencing short-distance movement of urediniospores. The random forest model provided the best predictions, explaining 76.1 and 86.8% of the total variation in the passive- and active-trap datasets, respectively. The prediction accuracy based on the correlation coefficient (r) between predicted values and the true values were 0.83 (P < 0.0001) and 0.94 (P < 0.0001) for the passive and active trap datasets, respectively. Overall, multiple machine learning techniques identified the most important variables to make the most accurate predictions of movement of P. pachyrhizi urediniospores short-distance.

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