Network Analysis Reveals a Common Host-Pathogen Interaction Pattern in Arabidopsis Immune Responses

Role of molecular mimicry in the SARS-CoV-2-human interactome for pathogenesis of cardiovascular diseases: An update to ImitateDB

Mimicry of host proteins is a strategy employed by pathogens to hijack host functions. Domain and motif mimicry was explored in the experimental and predicted SARS-CoV-2-human interactome. The host first interactor proteins were also added to capture the continuum of the interactions. The domains and motifs of the proteins were annotated using NCBI CD Search and ScanProsite, respectively. Host and pathogen proteins with a common host interactor and similar domain/motif constitute a mimicry pair indicating global structural similarity (domain mimicry pair; DMP) or local sequence similarity (motif mimicry pair; MMP). 593 DMPs and 7,02,472 MMPs were determined. AAA, DEXDc and Macro domains were frequent among DMPs whereas glycosylation, myristoylation and RGD motifs were abundant among MMP. The proteins involved in mimicry were visualised as a SARS-CoV-2 mimicry interaction network. The host proteins were enriched in multiple CVD pathways indicating the role of mimicry in COVID-19 associated CVDs. Bridging nodes were identified as potential drug targets. Approved antihypertensive and anti-inflammatory drugs are proposed for repurposing against COVID-19 associated CVDs. The SARS-CoV-2 mimicry data has been updated in ImitateDB (http://imitatedb.sblab-nsit.net/SARSCoV2Mimicry). Determination of key mechanisms, proteins, pathways, drug targets and repurposing candidates is critical for developing therapeutics for SARS CoV-2 associated CVDs.

Delineating infection strategies of Leishmania donovani secretory proteins in Human through host-pathogen protein Interactome prediction

Interactions of Leishmania donovani secretory virulence factors with the host proteins and their interplay during the infection process in humans is poorly studied in Visceral Leishmaniasis. Lack of a holistic study of pathway level de-regulations caused due to these virulence factors leads to a poor understanding of the parasite strategies to subvert the host immune responses, secure its survival inside the host and further the spread of infection to the visceral organs. In this study, we propose a computational workflow to predict host-pathogen protein interactome of L.donovani secretory virulence factors with human proteins combining sequence-based Interolog mapping and structure-based Domain Interaction mapping techniques. We further employ graph theoretical approaches and shortest path methods to analyze the interactome. Our study deciphers the infection paths involving some unique and understudied disease-associated signaling pathways influencing the cellular phenotypic responses in the host. Our statistical analysis based in silico knockout study unveils for the first time UBC, 1433Z and HS90A mediator proteins as potential immunomodulatory candidates through which the virulence factors employ the infection paths. These identified pathways and novel mediator proteins can be effectively used as possible targets to control and modulate the infection process further aiding in the treatment of Visceral Leishmaniasis.

Arabidopsis-Based Dual-Layered Biological Network Analysis Elucidates Fully Modulated Pathways Related to Sugarcane Resistance on Biotrophic Pathogen Infection

We assembled a dual-layered biological network to study the roles of resistance gene analogs (RGAs) in the resistance of sugarcane to infection by the biotrophic fungus causing smut disease. Based on sugarcane-Arabidopsis orthology, the modeling used metabolic and protein-protein interaction (PPI) data from Arabidopsis thaliana (from Kyoto Encyclopedia of Genes and Genomes (KEGG) and BioGRID databases) and plant resistance curated knowledge for Viridiplantae obtained through text mining of the UniProt/SwissProt database. With the network, we integrated functional annotations and transcriptome data from two sugarcane genotypes that differ significantly in resistance to smut and applied a series of analyses to compare the transcriptomes and understand both signal perception and transduction in plant resistance. We show that the smut-resistant sugarcane has a larger arsenal of RGAs encompassing transcriptionally modulated subnetworks with other resistance elements, reaching hub proteins of primary metabolism. This approach may benefit molecular breeders in search of markers associated with quantitative resistance to diseases in non-model systems.

Pathogen Effectors: Exploiting the Promiscuity of Plant Signaling Hubs

Pathogens produce effectors to overcome plant immunity, thereby threatening crop yields and global food security. Large-scale interactomic studies have revealed that pathogens from different kingdoms of life target common plant proteins during infection, the so-called effector hubs. These hubs often play central roles in numerous plant processes through their ability to interact with multiple plant proteins. This ability arises partly from the presence of intrinsically disordered domains (IDDs) in their structure. Here, we highlight the role of the TEOSINTE BRANCHED1/CYCLOIDEA/PROLIFERATING CELL FACTOR (TCP) and JASMONATE-ZIM DOMAIN (JAZ) transcription regulator families as plant signaling and effector hubs. We consider different evolutionary hypotheses to rationalize the existence of diverse effectors sharing common targets and the possible role of IDDs in this interaction.

Network-based analysis of virulence factors for uncovering Aeromonas veronii pathogenesis

BACKGROUND

Aeromonas veronii is a bacterial pathogen in aquaculture, which produces virulence factors to enable it colonize and evade host immune defense. Given that experimental verification of virulence factors is time-consuming and laborious, few virulence factors have been characterized. Moreover, most studies have only focused on single virulence factors, resulting in biased interpretation of the pathogenesis of A. veronii.

RESULTS

In this study, a PPI network at genome-wide scale for A. veronii was first constructed followed by prediction and mapping of virulence factors on the network. When topological characteristics were analyzed, the virulence factors had higher degree and betweenness centrality than other proteins in the network. In particular, the virulence factors tended to interact with each other and were enriched in two network modules. One of the modules mainly consisted of histidine kinases, response regulators, diguanylate cyclases and phosphodiesterases, which play important roles in two-component regulatory systems and the synthesis and degradation of cyclic-diGMP. Construction of the interspecies PPI network between A. veronii and its host Oreochromis niloticus revealed that the virulence factors interacted with homologous proteins in the host. Finally, the structures and interacting sites of the virulence factors during interaction with host proteins were predicted.

CONCLUSIONS

The findings here indicate that the virulence factors probably regulate the virulence of A. veronii by involving in signal transduction pathway and manipulate host biological processes by mimicking and binding competitively to host proteins. Our results give more insight into the pathogenesis of A. veronii and provides important information for designing targeted antibacterial drugs.

Review of the efficacy of infrared thermography for screening infectious diseases with applications to COVID-19

Purpose: The recent coronavirus disease 2019 (COVID-19) pandemic, which spread across the globe in a very short period of time, revealed that the transmission control of disease is a crucial step to prevent an outbreak and effective screening for viral infectious diseases is necessary. Since the severe acute respiratory syndrome (SARS) outbreak in 2003, infrared thermography (IRT) has been considered a gold standard method for screening febrile individuals at the time of pandemics. The objective of this review is to evaluate the efficacy of IRT for screening infectious diseases with specific applications to COVID-19. Approach: A literature review was performed in Google Scholar, PubMed, and ScienceDirect to search for studies evaluating IRT screening from 2002 to present using relevant keywords. Additional literature searches were done to evaluate IRT in comparison to traditional core body temperature measurements and assess the benefits of measuring additional vital signs for infectious disease screening. Results: Studies have reported on the unreliability of IRT due to poor sensitivity and specificity in detecting true core body temperature and its inability to identify asymptomatic carriers. Airport mass screening using IRT was conducted during occurrences of SARS, Dengue, Swine Flu, and Ebola with reported sensitivities as low as zero. Other studies reported that screening other vital signs such as heart and respiratory rates can lead to more robust methods for early infection detection. Conclusions: Studies evaluating IRT showed varied results in its efficacy for screening infectious diseases. This suggests the need to assess additional physiological parameters to increase the sensitivity and specificity of non-invasive biosensors.

EffectorK, a comprehensive resource to mine for Ralstonia, Xanthomonas, and other published effector interactors in the Arabidopsis proteome

Pathogens deploy effector proteins that interact with host proteins to manipulate the host physiology to the pathogen's own benefit. However, effectors can also be recognized by host immune proteins, leading to the activation of defence responses. Effectors are thus essential components in determining the outcome of plant-pathogen interactions. Despite major efforts to decipher effector functions, our current knowledge on effector biology is scattered and often limited. In this study, we conducted two systematic large-scale yeast two-hybrid screenings to detect interactions between Arabidopsis thaliana proteins and effectors from two vascular bacterial pathogens: Ralstonia pseudosolanacearum and Xanthomonas campestris. We then constructed an interactomic network focused on Arabidopsis and effector proteins from a wide variety of bacterial, oomycete, fungal, and invertebrate pathogens. This network contains our experimental data and protein-protein interactions from 2,035 peer-reviewed publications (48,200 Arabidopsis-Arabidopsis and 1,300 Arabidopsis-effector protein interactions). Our results show that effectors from different species interact with both common and specific Arabidopsis interactors, suggesting dual roles as modulators of generic and adaptive host processes. Network analyses revealed that effector interactors, particularly "effector hubs" and bacterial core effector interactors, occupy important positions for network organization, as shown by their larger number of protein interactions and centrality. These interactomic data were incorporated in EffectorK, a new graph-oriented knowledge database that allows users to navigate the network, search for homology, or find possible paths between host and/or effector proteins. EffectorK is available at www.effectork.org and allows users to submit their own interactomic data.

Effector Biology of Biotrophic Plant Fungal Pathogens: Current Advances and Future Prospects

The interaction of fungal pathogens with their host requires a novel invading mechanism and the presence of various virulence-associated components responsible for promoting the infection. The small secretory proteins, explicitly known as effector proteins, are one of the prime mechanisms of host manipulation utilized by the pathogen to disarm the host. Several effector proteins are known to translocate from fungus to the plant cell for host manipulation. Many fungal effectors have been identified using genomic, transcriptomic, and bioinformatics approaches. Most of the effector proteins are devoid of any conserved signatures, and their prediction based on sequence homology is very challenging, therefore by combining the sequence consensus based upon machine learning features, multiple tools have also been developed for predicting apoplastic and cytoplasmic effectors. Various post-genomics approaches like transcriptomics of virulent isolates have also been utilized for identifying active consortia of effectors. Significant progress has been made in understanding biotrophic effectors; however, most of it is underway due to their complex interaction with host and complicated recognition and signaling networks. This review discusses advances, and challenges in effector identification and highlighted various features of the potential effector proteins and approaches for understanding their genetics and strategies for regulation.

Envisioning the immune interactome in Arabidopsis

During plant-pathogen interaction, immune targets were regulated by protein-protein interaction events such as ligand-receptor/co-receptor, kinase-substrate, protein sequestration, activation or repression via post-translational modification and homo/oligo/hetro-dimerisation of proteins. A judicious use of molecular machinery requires coordinated protein interaction among defence components. Immune signalling in Arabidopsis can be broadly represented in successive or simultaneous steps; pathogen recognition at cell surface, Ca2+ and reactive oxygen species signalling, MAPK signalling, post-translational modification, transcriptional regulation and phyto-hormone signalling. Proteome wide interaction studies have shown the existence of interaction hubs associated with physiological function. So far, a number of protein interaction events regulating immune targets have been identified, but their understanding in an interactome view is lacking. We focussed specifically on the integration of protein interaction signalling in context to plant-pathogenesis and identified the key targets. The present review focuses towards a comprehensive view of the plant immune interactome including signal perception, progression, integration and physiological response during plant pathogen interaction.

Genome-wide transcriptional response of papain-like cysteine protease-mediated resistance against Xanthomonas oryzae pv. oryzae in rice

Transgenic rice overexpressing PLCP attenuated the virulence of Xanthomonas oryzae pv. oryzae through extensive activation of transduction signal and transcription activities that orchestrate downstream responses including the biosynthesis of secondary metabolites and up-regulation of several pathogenesis-related proteins. High-throughput transcriptome investigations of plant immunity highlight the complexity of gene networks leading to incompatible interaction with the pathogen. Accumulating findings implicate papain-like cysteine proteases (PLCPs) as a central hub in plant defense. While diverse roles of PLCPs in different pathosystems have become more evident, information on gene networks and signaling pathways necessary to orchestrate downstream responses are lacking. To understand the biological significance of cysteine protease against Xanthomonas oryzae pv. oryzae, PLCP overexpression and knockout rice lines were generated. The pathogenicity test revealed the attenuation of Xanthomonas oryzae pv. oryzae race K3a virulence in transgenic lines which is ascribed to high hydrogen peroxide and free salicylic acid accumulation. Next-generation sequencing of RNA from transgenic and wild-type plants identified 1597 combined differentially expressed genes, 1269 of which were exclusively regulated in the transgenic libraries. It was found that PLCP aids rice to circumvent infection through the extensive activation of transduction signal and transcription factors that orchestrate downstream responses, including up-regulation of multiple pathogenesis-related proteins and biosynthesis of secondary metabolites.

Network analysis of host-pathogen protein interactions in microbe induced cardiovascular diseases

Large-scale visualization and analysis of HPIs involved in microbial CVDs can provide crucial insights into the mechanisms of pathogenicity. The comparison of CVD associated HPIs with the entire set of HPIs can identify the pathways specific to CVDs. Therefore, topological properties of HPI networks in CVDs and all pathogens was studied using Cytoscape3.5.1. Ontology and pathway analysis were done using KOBAS 3.0. HPIs of Papilloma, Herpes, Influenza A virus as well as Yersinia pestis and Bacillus anthracis among bacteria were predominant in the whole (wHPI) and the CVD specific (cHPI) network. The central viral and secretory bacterial proteins were predicted virulent. The central viral proteins had higher number of interactions with host proteins in comparison with bacteria. Major fraction of central and essential host proteins interacts with central viral proteins. Alpha-synuclein, Ubiquitin ribosomal proteins, TATA-box-binding protein, and Polyubiquitin-C &B proteins were the top interacting proteins specific to CVDs. Signaling by NGF, Fc epsilon receptor, EGFR and ubiquitin mediated proteolysis were among the top enriched CVD specific pathways. DEXDc and HELICc were enriched host mimicry domains that may help in hijacking of cellular machinery by pathogens. This study provides a system level understanding of cardiac damage in microbe induced CVDs.

Deciphering signalling network in broad spectrum Near Isogenic Lines of rice resistant to Magnaporthe oryzae

Disease resistance (R) genes like Pi9, Pita, Pi21, Pi54 are playing important role for broad spectrum blast resistance in rice. Development of near isogenic lines (NILs) using these type of broad spectrum genes and understanding their signalling networks is essential to cope up with highly evolving Magnaporthe oryzae strains for longer duration. Here, transcriptional-level changes were studied in three near-isogenic lines (PB1 + Pi1, PB1 + Pi9 and PB1 + Pi54) of rice resistant to blast infection, to find the loci that are unique to resistant lines developed in the background of Pusa Basmati 1 (PB1). The pathway analysis of loci, unique to resistant NILs compared to susceptible control revealed that plant secondary metabolite synthesis was the common mechanism among all NILs to counter against M. oryzae infection. Comparative transcriptome analysis helped to find out common clusters of co-expressed significant differentially expressed loci (SDEL) in both PB1 + Pi9 and PB1 + Pi54 NILs. SDELs from these clusters were involved in the synthesis and degradation of starch; synthesis and elongation of fatty acids; hydrolysis of phospholipids; synthesis of phenylpropanoid; and metabolism of ethylene and jasmonic acid. Through detailed analysis of loci specific to each resistant NIL, we identified a network of signalling pathways mediated by each blast resistance gene. The study also offers insights into transcriptomic dynamics, points to a set of important candidate genes that serve as module to regulate the changes in resistant NILs. We suggest that pyramiding of the blast resistance gene Pi9 with Pi54 will lead to maximum broad spectrum resistance to M. oryzae.

PlaD: A Transcriptomics Database for Plant Defense Responses to Pathogens, Providing New Insights into Plant Immune System

High-throughput transcriptomics technologies have been widely used to study plant transcriptional reprogramming during the process of plant defense responses, and a large quantity of gene expression data have been accumulated in public repositories. However, utilization of these data is often hampered by the lack of standard metadata annotation. In this study, we curated 2444 public pathogenesis-related gene expression samples from the model plant Arabidopsis and three major crops (maize, rice, and wheat). We organized the data into a user-friendly database termed as PlaD. Currently, PlaD contains three key features. First, it provides large-scale curated data related to plant defense responses, including gene expression and gene functional annotation data. Second, it provides the visualization of condition-specific expression profiles. Third, it allows users to search co-regulated genes under the infections of various pathogens. Using PlaD, we conducted a large-scale transcriptome analysis to explore the global landscape of gene expression in the curated data. We found that only a small fraction of genes were differentially expressed under multiple conditions, which might be explained by their tendency of having more network connections and shorter network distances in gene networks. Collectively, we hope that PlaD can serve as an important and comprehensive knowledgebase to the community of plant sciences, providing insightful clues to better understand the molecular mechanisms underlying plant immune responses. PlaD is freely available at http://systbio.cau.edu.cn/plad/index.php or http://zzdlab.com/plad/index.php.

Large Scale Proteomic Data and Network-Based Systems Biology Approaches to Explore the Plant World

The investigation of plant organisms by means of data-derived systems biology approaches based on network modeling is mainly characterized by genomic data, while the potential of proteomics is largely unexplored. This delay is mainly caused by the paucity of plant genomic/proteomic sequences and annotations which are fundamental to perform mass-spectrometry (MS) data interpretation. However, Next Generation Sequencing (NGS) techniques are contributing to filling this gap and an increasing number of studies are focusing on plant proteome profiling and protein-protein interactions (PPIs) identification. Interesting results were obtained by evaluating the topology of PPI networks in the context of organ-associated biological processes as well as plant-pathogen relationships. These examples foreshadow well the benefits that these approaches may provide to plant research. Thus, in addition to providing an overview of the main-omic technologies recently used on plant organisms, we will focus on studies that rely on concepts of module, hub and shortest path, and how they can contribute to the plant discovery processes. In this scenario, we will also consider gene co-expression networks, and some examples of integration with metabolomic data and genome-wide association studies (GWAS) to select candidate genes will be mentioned.

Integrative network analyses of wilt transcriptome in chickpea reveal genotype dependent regulatory hubs in immunity and susceptibility

Host specific resistance and non-host resistance are two plant immune responses to counter pathogen invasion. Gene network organizing principles leading to quantitative differences in resistant and susceptible host during host specific resistance are poorly understood. Vascular wilt caused by root pathogen Fusarium species is complex and governed by host specific resistance in crop plants, including chickpea. Here, we temporally profiled two contrasting chickpea genotypes in disease and immune state to better understand gene expression switches in host specific resistance. Integrative gene-regulatory network elucidated tangible insight into interaction coordinators leading to pathway determination governing distinct (disease or immune) phenotypes. Global network analysis identified five major hubs with 389 co-regulated genes. Functional enrichment revealed immunome containing three subnetworks involving CTI, PTI and ETI and wilt diseasome encompassing four subnetworks highlighting pathogen perception, penetration, colonization and disease establishment. These subnetworks likely represent key components that coordinate various biological processes favouring defence or disease. Furthermore, we identified core 76 disease/immunity related genes through subcellular analysis. Our regularized network with robust statistical assessment captured known and unexpected gene interaction, candidate novel regulators as future biomarkers and first time showed system-wide quantitative architecture corresponding to genotypic characteristics in wilt landscape.