A Network Approach of Gene Co-expression in the Zea mays/Aspergillus flavus Pathosystem to Map Host/Pathogen Interaction Pathways.

A gene co-expression network (GEN) was generated using a dual RNA-seq study with the fungal pathogen Aspergillus flavus and its plant host Zea mays during the initial 3 days of infection. The analysis deciphered novel pathways and mapped genes of interest in both organisms during the infection. This network revealed a high degree of connectivity in many of the previously recognized pathways in Z. mays such as jasmonic acid, ethylene, and reactive oxygen species (ROS). For the pathogen A. flavus, a link between aflatoxin production and vesicular transport was identified within the network. There was significant interspecies correlation of expression between Z. mays and A. flavus for a subset of 104 Z. mays, and 1942 A. flavus genes. This resulted in an interspecies subnetwork enriched in multiple Z. mays genes involved in the production of ROS. In addition to the ROS from Z. mays, there was enrichment in the vesicular transport pathways and the aflatoxin pathway for A. flavus. Included in these genes, a key aflatoxin cluster regulator, AflS, was found to be co-regulated with multiple Z. mays ROS producing genes within the network, suggesting AflS may be monitoring host ROS levels. The entire GEN for both host and pathogen, and the subset of interspecies correlations, is presented as a tool for hypothesis generation and discovery for events in the early stages of fungal infection of Z. mays by A. flavus

A predicted protein interactome identifies conserved global networks and disease resistance subnetworks in maize

Interactomes are genome-wide roadmaps of protein-protein interactions. They have been produced for humans, yeast, the fruit fly, and Arabidopsis thaliana and have become invaluable tools for generating and testing hypotheses. A predicted interactome for Zea mays (PiZeaM) is presented here as an aid to the research community for this valuable crop species. PiZeaM was built using a proven method of interologs (interacting orthologs) that were identified using both one-to-one and many-to-many orthology between genomes of maize and reference species. Where both maize orthologs occurred for an experimentally determined interaction in the reference species, we predicted a likely interaction in maize. A total of 49,026 unique interactions for 6004 maize proteins were predicted. These interactions are enriched for processes that are evolutionarily conserved, but include many otherwise poorly annotated proteins in maize. The predicted maize interactions were further analyzed by comparing annotation of interacting proteins, including different layers of ontology. A map of pairwise gene co-expression was also generated and compared to predicted interactions. Two global subnetworks were constructed for highly conserved interactions. These subnetworks showed clear clustering of proteins by function. Another subnetwork was created for disease response using a bait and prey strategy to capture interacting partners for proteins that respond to other organisms. Closer examination of this subnetwork revealed the connectivity between biotic and abiotic hormone stress pathways. We believe PiZeaM will provide a useful tool for the prediction of protein function and analysis of pathways for Z. mays researchers and is presented in this paper as a reference tool for the exploration of protein interactions in maize

THE HOST-PATHOGEN INTERACTOME AND REGULATORY NETWORKS OF ASPERGILLUS FLAVUS PATHOGENESSIS OF ZEA MAYS: RESISTANCE IN MAIZE TO ASPERGILLUS EAR ROT AND TO AFLATOXIN ACCUMULATION

The relationship between a pathogen and its host is a complex series of events that occurs at the molecular level and is controlled by transcriptional and protein interactions. To facilitate the understanding of these mechanisms in Aspergillus flavus and Zea mays, three approaches were taken: 1) the development of a predicted interactome for Z. mays (PiZeaM), 2) the development of co-expression networks for Z. mays and A. flavus from RNA-seq data, and 3) the development of causal inference networks depicting interactions between the host and the pathogen. PiZeaM is the genome-wide roadmap of protein-protein interactions that occur within Z. mays. PiZeaM helps create a novel map of the interactions in Z. mays in response to biotic and abiotic stresses. To further support the predicted interactions, an analysis of microarray-based gene expression was used to produce a gene co-expression network. PiZeaM was able to capture conserved resistance pathways involved involved in the response to pathogens, abiotic stress and development. Gene Co-expression networks were developed by the simultaneous use of correlations to develop networks for differentially expressed genes, resistance marker genes, pathogenicity genes, and genes involved is secondary metabolism in Z. mays and A. flavus. From these networks, correlation and anti-correlation of host and pathogen gene expression was detected, revealing genes that potentially interact at different stages of pathogenesis. Finally, causal gene regulatory relationships were inferred using partial correlation analysis of Z. mays infected with A. flavus over a 3 day period. The gene regulatory network (GRN) sheds light on the specifics of the mechanisms of pathogenesis and resistance that govern the Z. mays-A. flavus interaction. The direct product of this research is the understanding of key transcription factors and signaling genes involved in resistance. This body of research highlights how PPIs and GRNs can be utilized to identify biomarkers and gene functions in both Z. mays and A. flavus

The Interactomic Analysis Reveals Pathogenic Protein Networks in Phomopsis longicolla Underlying Seed Decay of Soybean

Phomopsis longicolla T. W. Hobbs (syn. Diaporthe longicolla) is the primary cause of Phomopsis seed decay (PSD) in soybean, Glycine max (L.) Merrill. This disease results in poor seed quality and is one of the most economically important seed diseases in soybean. The objectives of this study were to infer protein–protein interactions (PPI) and to identify conserved global networks and pathogenicity subnetworks in P. longicolla including orthologous pathways for cell signaling and pathogenesis. The interlog method used in the study identified 215,255 unique PPIs among 3,868 proteins. There were 1,414 pathogenicity related genes in P. longicolla identified using the pathogen host interaction (PHI) database. Additionally, 149 plant cell wall degrading enzymes (PCWDE) were detected. The network captured five different classes of carbohydrate degrading enzymes, including the auxiliary activities, carbohydrate esterases, glycoside hydrolases, glycosyl transferases, and carbohydrate binding molecules. From the PPI analysis, novel interacting partners were determined for each of the PCWDE classes. The most predominant class of PCWDE was a group of 60 glycoside hydrolases proteins. The glycoside hydrolase subnetwork was found to be interacting with 1,442 proteins within the network and was among the largest clusters. The orthologous proteins FUS3, HOG, CYP1, SGE1, and the g5566t.1 gene identified in this study could play an important role in pathogenicity. Therefore, the P. longicolla protein interactome (PiPhom) generated in this study can lead to a better understanding of PPIs in soybean pathogens. Furthermore, the PPI may aid in targeting of genes and proteins for further studies of the pathogenicity mechanisms

Analysis of the genome sequence of Phomopsis longicolla: a fungal pathogen causing Phomopsis seed decay in soybean

Abstract Background Phomopsis longicolla T. W. Hobbs (syn. Diaporthe longicolla) is a seed-borne fungus causing Phomopsis seed decay in soybean. This disease is one of the most devastating diseases reducing soybean seed quality worldwide. To facilitate investigation of the genomic basis of pathogenicity and to understand the mechanism of the disease development, the genome of an isolate, MSPL10–6, from Mississippi, USA was sequenced, de novo assembled, and analyzed. Results The genome of MSPL 10–6 was estimated to be approximately 62 Mb in size with an overall G + C content of 48.6%. Of 16,597 predicted genes, 9866 genes (59.45%) had significant matches to genes in the NCBI nr database, while 18.01% of them did not link to any gene ontology classification, and 9.64% of genes did not significantly match any known genes. Analysis of the 1221 putative genes that encoded carbohydrate-activated enzymes (CAZys) indicated that 715 genes belong to three classes of CAZy that have a direct role in degrading plant cell walls. A novel fungal ulvan lyase (PL24; EC 4.2.2.-) was identified. Approximately 12.7% of the P. longicolla genome consists of repetitive elements. A total of 510 potentially horizontally transferred genes were identified. They appeared to originate from 22 other fungi, 26 eubacteria and 5 archaebacteria. Conclusions The genome of the P. longicolla isolate MSPL10–6 represented the first reported genome sequence in the fungal Diaporthe-Phomopsis complex causing soybean diseases. The genome contained a number of Pfams not described previously. Information obtained from this study enhances our knowledge about this seed-borne pathogen and will facilitate further research on the genomic basis and pathogenicity mechanism of P. longicolla and aids in development of improved strategies for efficient management of Phomopsis seed decay in soybean

Table_1.XLSX

<p>Phomopsis longicolla T. W. Hobbs (syn. Diaporthe longicolla) is the primary cause of Phomopsis seed decay (PSD) in soybean, Glycine max (L.) Merrill. This disease results in poor seed quality and is one of the most economically important seed diseases in soybean. The objectives of this study were to infer protein–protein interactions (PPI) and to identify conserved global networks and pathogenicity subnetworks in P. longicolla including orthologous pathways for cell signaling and pathogenesis. The interlog method used in the study identified 215,255 unique PPIs among 3,868 proteins. There were 1,414 pathogenicity related genes in P. longicolla identified using the pathogen host interaction (PHI) database. Additionally, 149 plant cell wall degrading enzymes (PCWDE) were detected. The network captured five different classes of carbohydrate degrading enzymes, including the auxiliary activities, carbohydrate esterases, glycoside hydrolases, glycosyl transferases, and carbohydrate binding molecules. From the PPI analysis, novel interacting partners were determined for each of the PCWDE classes. The most predominant class of PCWDE was a group of 60 glycoside hydrolases proteins. The glycoside hydrolase subnetwork was found to be interacting with 1,442 proteins within the network and was among the largest clusters. The orthologous proteins FUS3, HOG, CYP1, SGE1, and the g5566t.1 gene identified in this study could play an important role in pathogenicity. Therefore, the P. longicolla protein interactome (PiPhom) generated in this study can lead to a better understanding of PPIs in soybean pathogens. Furthermore, the PPI may aid in targeting of genes and proteins for further studies of the pathogenicity mechanisms.</p

Data_Sheet_1.ZIP

<p>Phomopsis longicolla T. W. Hobbs (syn. Diaporthe longicolla) is the primary cause of Phomopsis seed decay (PSD) in soybean, Glycine max (L.) Merrill. This disease results in poor seed quality and is one of the most economically important seed diseases in soybean. The objectives of this study were to infer protein–protein interactions (PPI) and to identify conserved global networks and pathogenicity subnetworks in P. longicolla including orthologous pathways for cell signaling and pathogenesis. The interlog method used in the study identified 215,255 unique PPIs among 3,868 proteins. There were 1,414 pathogenicity related genes in P. longicolla identified using the pathogen host interaction (PHI) database. Additionally, 149 plant cell wall degrading enzymes (PCWDE) were detected. The network captured five different classes of carbohydrate degrading enzymes, including the auxiliary activities, carbohydrate esterases, glycoside hydrolases, glycosyl transferases, and carbohydrate binding molecules. From the PPI analysis, novel interacting partners were determined for each of the PCWDE classes. The most predominant class of PCWDE was a group of 60 glycoside hydrolases proteins. The glycoside hydrolase subnetwork was found to be interacting with 1,442 proteins within the network and was among the largest clusters. The orthologous proteins FUS3, HOG, CYP1, SGE1, and the g5566t.1 gene identified in this study could play an important role in pathogenicity. Therefore, the P. longicolla protein interactome (PiPhom) generated in this study can lead to a better understanding of PPIs in soybean pathogens. Furthermore, the PPI may aid in targeting of genes and proteins for further studies of the pathogenicity mechanisms.</p

Table_2.XLSX

<p>Phomopsis longicolla T. W. Hobbs (syn. Diaporthe longicolla) is the primary cause of Phomopsis seed decay (PSD) in soybean, Glycine max (L.) Merrill. This disease results in poor seed quality and is one of the most economically important seed diseases in soybean. The objectives of this study were to infer protein–protein interactions (PPI) and to identify conserved global networks and pathogenicity subnetworks in P. longicolla including orthologous pathways for cell signaling and pathogenesis. The interlog method used in the study identified 215,255 unique PPIs among 3,868 proteins. There were 1,414 pathogenicity related genes in P. longicolla identified using the pathogen host interaction (PHI) database. Additionally, 149 plant cell wall degrading enzymes (PCWDE) were detected. The network captured five different classes of carbohydrate degrading enzymes, including the auxiliary activities, carbohydrate esterases, glycoside hydrolases, glycosyl transferases, and carbohydrate binding molecules. From the PPI analysis, novel interacting partners were determined for each of the PCWDE classes. The most predominant class of PCWDE was a group of 60 glycoside hydrolases proteins. The glycoside hydrolase subnetwork was found to be interacting with 1,442 proteins within the network and was among the largest clusters. The orthologous proteins FUS3, HOG, CYP1, SGE1, and the g5566t.1 gene identified in this study could play an important role in pathogenicity. Therefore, the P. longicolla protein interactome (PiPhom) generated in this study can lead to a better understanding of PPIs in soybean pathogens. Furthermore, the PPI may aid in targeting of genes and proteins for further studies of the pathogenicity mechanisms.</p

The Pathogenesis-Related Maize Seed (PRms) Gene Plays a Role in Resistance to Aspergillus flavus Infection and Aflatoxin Contamination

Aspergillus flavus is an opportunistic plant pathogen that colonizes and produces the toxic and carcinogenic secondary metabolites, aflatoxins, in oil-rich crops such as maize (Zea mays ssp. mays L.). Pathogenesis-related (PR) proteins serve as an important defense mechanism against invading pathogens by conferring systemic acquired resistance in plants. Among these, production of the PR maize seed protein, ZmPRms (AC205274.3_FG001), has been speculated to be involved in resistance to infection by A. flavus and other pathogens. To better understand the relative contribution of ZmPRms to A. flavus resistance and aflatoxin production, a seed-specific RNA interference (RNAi)-based gene silencing approach was used to develop transgenic maize lines expressing hairpin RNAs to target ZmPRms. Downregulation of ZmPRms in transgenic kernels resulted in a ∼250–350% increase in A. flavus infection accompanied by a ∼4.5–7.5-fold higher accumulation of aflatoxins than control plants. Gene co-expression network analysis of RNA-seq data during the A. flavus-maize interaction identified ZmPRms as a network hub possibly responsible for regulating several downstream candidate genes associated with disease resistance and other biochemical functions. Expression analysis of these candidate genes in the ZmPRms–RNAi lines demonstrated downregulation (vs. control) of a majority of these ZmPRms-regulated genes during A. flavus infection. These results are consistent with a key role of ZmPRms in resistance to A. flavus infection and aflatoxin accumulation in maize kernels

Table_3.XLSX

<p>Phomopsis longicolla T. W. Hobbs (syn. Diaporthe longicolla) is the primary cause of Phomopsis seed decay (PSD) in soybean, Glycine max (L.) Merrill. This disease results in poor seed quality and is one of the most economically important seed diseases in soybean. The objectives of this study were to infer protein–protein interactions (PPI) and to identify conserved global networks and pathogenicity subnetworks in P. longicolla including orthologous pathways for cell signaling and pathogenesis. The interlog method used in the study identified 215,255 unique PPIs among 3,868 proteins. There were 1,414 pathogenicity related genes in P. longicolla identified using the pathogen host interaction (PHI) database. Additionally, 149 plant cell wall degrading enzymes (PCWDE) were detected. The network captured five different classes of carbohydrate degrading enzymes, including the auxiliary activities, carbohydrate esterases, glycoside hydrolases, glycosyl transferases, and carbohydrate binding molecules. From the PPI analysis, novel interacting partners were determined for each of the PCWDE classes. The most predominant class of PCWDE was a group of 60 glycoside hydrolases proteins. The glycoside hydrolase subnetwork was found to be interacting with 1,442 proteins within the network and was among the largest clusters. The orthologous proteins FUS3, HOG, CYP1, SGE1, and the g5566t.1 gene identified in this study could play an important role in pathogenicity. Therefore, the P. longicolla protein interactome (PiPhom) generated in this study can lead to a better understanding of PPIs in soybean pathogens. Furthermore, the PPI may aid in targeting of genes and proteins for further studies of the pathogenicity mechanisms.</p