Deciphering the complete human-monkeypox virus interactome: Identifying immune responses and potential drug targets.

Monkeypox virus (MPXV) is a dsDNA virus, belonging to Poxviridae family. The outbreak of monkeypox disease in humans is critical in European and Western countries, owing to its origin in African regions. The highest number of cases of the disease were found in the United States, followed by Spain and Brazil. Understanding the complete infection mechanism of diverse MPXV strains and their interaction with humans is important for therapeutic drug development, and to avoid any future epidemics. Using computational systems biology, we deciphered the genome-wide protein-protein interactions (PPIs) between 22 MPXV strains and human proteome. Based on phylogenomics and disease severity, 3 different strains of MPXV: Zaire-96-I-16, MPXV-UK_P2, and MPXV_USA_2022_MA001 were selected for comparative functional analysis of the proteins involved in the interactions. On an average, we predicted around 92,880 non-redundant PPIs between human and MPXV proteomes, involving 8014 host and 116 pathogen proteins from the 3 strains. The gene ontology (GO) enrichment analysis revealed 10,624 common GO terms in which the host proteins of 3 strains were highly enriched. These include significant GO terms such as platelet activation (GO:0030168), GABA-A receptor complex (GO:1902711), and metalloendopeptidase activity (GO:0004222). The host proteins were also significantly enriched in calcium signaling pathway (hsa04020), MAPK signaling pathway (hsa04010), and inflammatory mediator regulation of TRP channels (hsa04750). These significantly enriched GO terms and KEGG pathways are known to be implicated in immunomodulatory and therapeutic role in humans during viral infection. The protein hubs analysis revealed that most of the MPXV proteins form hubs with the protein kinases and AGC kinase C-terminal domains. Furthermore, subcellular localization revealed that most of the human proteins were localized in cytoplasm (29.22%) and nucleus (26.79%). A few drugs including Fostamatinib, Tamoxifen and others were identified as potential drug candidates against the monkeypox virus disease. This study reports the genome-scale PPIs elucidation in human-monkeypox virus pathosystem, thus facilitating the research community with functional insights into the monkeypox disease infection mechanism and augment the drug development.

TRustDB: A comprehensive bioinformatics resource for understanding the complete Wheat-Stem rust host-pathogen interactome.

The increasing infectious diseases in wheat immensely reduce crop yield and quality, thus affecting global wheat production. The evolution in phytopathogens hinders the understanding of the disease infection mechanisms. TRustDB is an open-access, comprehensive database that is specifically focused on the disease stem rust (also known as black rust) in Triticum aestivum, which is caused by the fungal pathogen Puccinia graminis (Pgt), strains 'Ug99' and '21-0'. The database aims at a broader focus of providing the researchers with comprehensive tools to predict the protein-protein interactions and avail the functional annotations of the proteins involved in the interactions that cause the disease. The network of the predicted interactome can also be visualized on the browser. Various modules for the functional annotations of the host and pathogen proteins such as subcellular localization, functional domains, gene ontology annotations, pathogen orthologs and effector proteins have been implemented. The host proteins that serve as transcription factors, along with the respective Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways are also available, which further enhance the understanding of the disease infection mechanisms and the defense responses of the host. The database is also linked with several other databases such as InterPro, KEGG pathways, Ensembl and National Center for Biotechnology Information (NCBI). TRustDB has a user-friendly web interface, which can be accessed through . Database URL http://bioinfo.usu.edu/trustdb/.

Deciphering the Crosstalk Mechanisms of Wheat-Stem Rust Pathosystem: Genome-Scale Prediction Unravels Novel Host Targets.

Triticum aestivum (wheat), a major staple food grain, is affected by various biotic stresses. Among these, fungal diseases cause about 15-20% of yield loss, worldwide. In this study, we performed a comparative analysis of protein-protein interactions between two Puccinia graminis races (Pgt 21-0 and Pgt Ug99) that cause stem (black) rust in wheat. The available molecular techniques to study the host-pathogen interaction mechanisms are expensive and labor-intensive. We implemented two computational approaches (interolog and domain-based) for the prediction of PPIs and performed various functional analysis to determine the significant differences between the two pathogen races. The analysis revealed that T. aestivum-Pgt 21-0 and T. aestivum-Pgt Ug99 interactomes consisted of ∼90M and ∼56M putative PPIs, respectively. In the predicted PPIs, we identified 115 Pgt 21-0 and 34 Pgt Ug99 potential effectors that were highly involved in pathogen virulence and development. Functional enrichment analysis of the host proteins revealed significant GO terms and KEGG pathways such as O-methyltransferase activity (GO:0008171), regulation of signal transduction (GO:0009966), lignin metabolic process (GO:0009808), plastid envelope (GO:0009526), plant-pathogen interaction pathway (ko04626), and MAPK pathway (ko04016) that are actively involved in plant defense and immune signaling against the biotic stresses. Subcellular localization analysis anticipated the host plastid as a primary target for pathogen attack. The highly connected host hubs in the protein interaction network belonged to protein kinase domain including Ser/Thr protein kinase, MAPK, and cyclin-dependent kinase. We also identified 5,577 transcription factors in the interactions, associated with plant defense during biotic stress conditions. Additionally, novel host targets that are resistant to stem rust disease were also identified. The present study elucidates the functional differences between Pgt 21-0 and Pgt Ug99, thus providing the researchers with strain-specific information for further experimental validation of the interactions, and the development of durable, disease-resistant crop lines.

TritiKBdb: A Functional Annotation Resource for Deciphering the Complete Interaction Networks in Wheat-Karnal Bunt Pathosystem.

The study of molecular interactions, especially the inter-species protein-protein interactions, is crucial for understanding the disease infection mechanism in plants. These interactions play an important role in disease infection and host immune responses against pathogen attack. Among various critical fungal diseases, the incidences of Karnal bunt (Tilletia indica) around the world have hindered the export of the crops such as wheat from infected regions, thus causing substantial economic losses. Due to sparse information on T. indica, limited insight is available with regard to gaining in-depth knowledge of the interaction mechanisms between the host and pathogen proteins during the disease infection process. Here, we report the development of a comprehensive database and webserver, TritiKBdb, that implements various tools to study the protein-protein interactions in the Triticum species-Tilletia indica pathosystem. The novel 'interactomics' tool allows the user to visualize/compare the networks of the predicted interactions in an enriched manner. TritiKBdb is a user-friendly database that provides functional annotations such as subcellular localization, available domains, KEGG pathways, and GO terms of the host and pathogen proteins. Additionally, the information about the host and pathogen proteins that serve as transcription factors and effectors, respectively, is also made available. We believe that TritiKBdb will serve as a beneficial resource for the research community, and aid the community in better understanding the infection mechanisms of Karnal bunt and its interactions with wheat. The database is freely available for public use at http://bioinfo.usu.edu/tritikbdb/.

WeCoNET: a host-pathogen interactome database for deciphering crucial molecular networks of wheat-common bunt cross-talk mechanisms.

BACKGROUND: Triticum aestivum is the most important staple food grain of the world. In recent years, the outbreak of a major seed-borne disease, common bunt, in wheat resulted in reduced quality and quantity of the crop. The disease is caused by two fungal pathogens, Tilletia caries and Tilletia laevis, which show high similarity to each other in terms of life cycle, germination, and disease symptoms. The host-pathogen protein-protein interactions play a crucial role in initiating the disease infection mechanism as well as in plant defense responses. Due to the availability of limited information on Tilletia species, the elucidation of infection mechanisms is hampered. RESULTS: We constructed a database WeCoNET ( http://bioinfo.usu.edu/weconet/ ), providing functional annotations of the pathogen proteins and various tools to exploit host-pathogen interactions and other relevant information. The database implements a host-pathogen interactomics tool to predict protein-protein interactions, followed by network visualization, BLAST search tool, advanced 'keywords-based' search module, etc. Other features in the database include various functional annotations of host and pathogen proteins such as gene ontology terms, functional domains, and subcellular localization. The pathogen proteins that serve as effector and secretory proteins have also been incorporated in the database, along with their respective descriptions. Additionally, the host proteins that serve as transcription factors were predicted, and are available along with the respective transcription factor family and KEGG pathway to which they belong. CONCLUSION: WeCoNET is a comprehensive, efficient resource to the molecular biologists engaged in understanding the molecular mechanisms behind the common bunt infection in wheat. The data integrated into the database can also be beneficial to the breeders for the development of common bunt-resistant cultivars.

Deciphering the Host-Pathogen Interactome of the Wheat-Common Bunt System: A Step towards Enhanced Resilience in Next Generation Wheat.

Common bunt, caused by two fungal species, Tilletia caries and Tilletia laevis, is one of the most potentially destructive diseases of wheat. Despite the availability of synthetic chemicals against the disease, organic agriculture relies greatly on resistant cultivars. Using two computational approaches-interolog and domain-based methods-a total of approximately 58 M and 56 M probable PPIs were predicted in T. aestivum-T. caries and T. aestivum-T. laevis interactomes, respectively. We also identified 648 and 575 effectors in the interactions from T. caries and T. laevis, respectively. The major host hubs belonged to the serine/threonine protein kinase, hsp70, and mitogen-activated protein kinase families, which are actively involved in plant immune signaling during stress conditions. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis of the host proteins revealed significant GO terms (O-methyltransferase activity, regulation of response to stimulus, and plastid envelope) and pathways (NF-kappa B signaling and the MAPK signaling pathway) related to plant defense against pathogens. Subcellular localization suggested that most of the pathogen proteins target the host in the plastid. Furthermore, a comparison between unique T. caries and T. laevis proteins was carried out. We also identified novel host candidates that are resistant to disease. Additionally, the host proteins that serve as transcription factors were also predicted.

Diversity and conservation of plant small secreted proteins associated with arbuscular mycorrhizal symbiosis.

Arbuscular mycorrhizal symbiosis (AMS) is widespread mutualistic association between plants and fungi, which plays an essential role in nutrient exchange, enhancement in plant stress resistance, development of host, and ecosystem sustainability. Previous studies have shown that plant small secreted proteins (SSPs) are involved in beneficial symbiotic interactions. However, the role of SSPs in the evolution of AMS has not been well studied yet. In this study, we performed computational analysis of SSPs in 60 plant species and identified three AMS-specific ortholog groups containing SSPs only from at least 30% of the AMS species in this study and three AMS-preferential ortholog groups containing SSPs from both AMS and non-AMS species, with AMS species containing significantly more SSPs than non-AMS species. We found that independent lineages of monocot and eudicot plants contained genes in the AMS-specific ortholog groups and had significant expansion in the AMS-preferential ortholog groups. Also, two AMS-preferential ortholog groups showed convergent changes, between monocot and eudicot species, in gene expression in response to arbuscular mycorrhizal fungus Rhizophagus irregularis. Furthermore, conserved cis-elements were identified in the promoter regions of the genes showing convergent gene expression. We found that the SSPs, and their closely related homologs, in each of three AMS-preferential ortholog groups, had some local variations in the protein structural alignment. We also identified genes co-expressed with the Populus trichocarpa SSP genes in the AMS-preferential ortholog groups. This first plant kingdom-wide analysis on SSP provides insights on plant-AMS convergent evolution with specific SSP gene expression and local diversification of protein structures.

alfaNET: A Database of Alfalfa-Bacterial Stem Blight Protein-Protein Interactions Revealing the Molecular Features of the Disease-causing Bacteria.

Alfalfa has emerged as one of the most important forage crops, owing to its wide adaptation and high biomass production worldwide. In the last decade, the emergence of bacterial stem blight (caused by Pseudomonas syringae pv. syringae ALF3) in alfalfa has caused around 50% yield losses in the United States. Studies are being conducted to decipher the roles of the key genes and pathways regulating the disease, but due to the sparse knowledge about the infection mechanisms of Pseudomonas, the development of resistant cultivars is hampered. The database alfaNET is an attempt to assist researchers by providing comprehensive Pseudomonas proteome annotations, as well as a host-pathogen interactome tool, which predicts the interactions between host and pathogen based on orthology. alfaNET is a user-friendly and efficient tool and includes other features such as subcellular localization annotations of pathogen proteins, gene ontology (GO) annotations, network visualization, and effector protein prediction. Users can also browse and search the database using particular keywords or proteins with a specific length. Additionally, the BLAST search tool enables the user to perform a homology sequence search against the alfalfa and Pseudomonas proteomes. With the successful implementation of these attributes, alfaNET will be a beneficial resource to the research community engaged in implementing molecular strategies to mitigate the disease. alfaNET is freely available for public use at http://bioinfo.usu.edu/alfanet/.

Computational Systems Biology of Alfalfa - Bacterial Blight Host-Pathogen Interactions: Uncovering the Complex Molecular Networks for Developing Durable Disease Resistant Crop.

Medicago sativa (also known as alfalfa), a forage legume, is widely cultivated due to its high yield and high-value hay crop production. Infectious diseases are a major threat to the crops, owing to huge economic losses to the agriculture industry, worldwide. The protein-protein interactions (PPIs) between the pathogens and their hosts play a critical role in understanding the molecular basis of pathogenesis. Pseudomonas syringae pv. syringae ALF3 suppresses the plant's innate immune response by secreting type III effector proteins into the host cell, causing bacterial stem blight in alfalfa. The alfalfa-P. syringae system has little information available for PPIs. Thus, to understand the infection mechanism, we elucidated the genome-scale host-pathogen interactions (HPIs) between alfalfa and P. syringae using two computational approaches: interolog-based and domain-based method. A total of ∼14 M putative PPIs were predicted between 50,629 alfalfa proteins and 2,932 P. syringae proteins by combining these approaches. Additionally, ∼0.7 M consensus PPIs were also predicted. The functional analysis revealed that P. syringae proteins are highly involved in nucleotide binding activity (GO:0000166), intracellular organelle (GO:0043229), and translation (GO:0006412) while alfalfa proteins are involved in cellular response to chemical stimulus (GO:0070887), oxidoreductase activity (GO:0016614), and Golgi apparatus (GO:0005794). According to subcellular localization predictions, most of the pathogen proteins targeted host proteins within the cytoplasm and nucleus. In addition, we discovered a slew of new virulence effectors in the predicted HPIs. The current research describes an integrated approach for deciphering genome-scale host-pathogen PPIs between alfalfa and P. syringae, allowing the researchers to better understand the pathogen's infection mechanism and develop pathogen-resistant lines.