Host-pathogen Interaction Networks Research Articles

Quantification of Adaptive Immune Responses Against Protein-Binding Interfaces in the Streptococcal M1 Protein

Bacterial or viral antigens can contain subdominant protein regions that elicit weak antibody responses upon vaccination or infection although there is accumulating evidence that antibody responses against subdominant regions can enhance the protective immune response. One proposed mechanism for subdominant protein regions is the binding of host proteins that prevent antibody production against epitopes hidden within the protein binding interfaces. Here, we used affinity purification combined with quantitative mass spectrometry (AP-MS) to examine the level of competition between antigen-specific antibodies and host–pathogen protein interaction networks using the M1 protein from Streptococcus pyogenes as a model system. As most humans have circulating antibodies against the M1 protein, we first used AP-MS to show that the M1 protein interspecies protein network formed with human plasma proteins is largely conserved in naïve mice. Immunizing mice with the M1 protein generated a time-dependent increase of anti-M1 antibodies. AP-MS analysis comparing the composition of the M1-plasma protein network from naïve and immunized mice showed significant enrichment of 292 IgG peptides associated with 56 IgG chains in the immune mice. Despite the significant increase of bound IgGs, the levels of interacting plasma proteins were not significantly reduced in the immune mice. The results indicate that the antigen-specific polyclonal IgG against the M1 protein primarily targets epitopes outside the other plasma protein binding interfaces. In conclusion, this study demonstrates that AP-MS is a promising strategy to determine the relationship between antigen-specific antibodies and host-pathogen interaction networks that could be used to define subdominant protein regions of relevance for vaccine development.

Monkeypox virus: phylogenomics, host-pathogen interactome and mutational cascade.

While the world is still recovering from the Covid-19 pandemic, monkeypox virus (MPXV) awaits to cause another global outbreak as a challenge to all of mankind. However, the Covid-19 pandemic has taught us a lesson to speed up the pace of viral genomic research for the implementation of preventive and treatment strategies. One of the important aspects of MPXV that needs immediate insight is its evolutionary lineage based on genomic studies. Utilizing high-quality isolates from the GISAID (Global Initiative on Sharing All Influenza Data) database, primarily sourced from Europe and North America, we employed a SNP-based whole-genome phylogeny method and identified four major clusters among 628 MPXV isolates. Our findings indicate a distinct evolutionary lineage for the first MPXV isolate, and a complex epidemiology and evolution of MPXV strains across various countries. Further analysis of the host-pathogen interaction network revealed key viral proteins, such as E3, SPI-2, K7 and CrmB, that play a significant role in regulating the network and inhibiting the host's cellular innate immune system. Our structural analysis of proteins E3 and CrmB revealed potential disruption of stability due to certain mutations. While this study identified a large number of mutations within the new outbreak clade, it also reflected that we need to move fast with the genomic analysis of newly detected strains from around the world to develop better prevention and treatment methods.

A new framework for host-pathogen interaction research.

COVID-19 often manifests with different outcomes in different patients, highlighting the complexity of the host-pathogen interactions involved in manifestations of the disease at the molecular and cellular levels. In this paper, we propose a set of postulates and a framework for systematically understanding complex molecular host-pathogen interaction networks. Specifically, we first propose four host-pathogen interaction (HPI) postulates as the basis for understanding molecular and cellular host-pathogen interactions and their relations to disease outcomes. These four postulates cover the evolutionary dispositions involved in HPIs, the dynamic nature of HPI outcomes, roles that HPI components may occupy leading to such outcomes, and HPI checkpoints that are critical for specific disease outcomes. Based on these postulates, an HPI Postulate and Ontology (HPIPO) framework is proposed to apply interoperable ontologies to systematically model and represent various granular details and knowledge within the scope of the HPI postulates, in a way that will support AI-ready data standardization, sharing, integration, and analysis. As a demonstration, the HPI postulates and the HPIPO framework were applied to study COVID-19 with the Coronavirus Infectious Disease Ontology (CIDO), leading to a novel approach to rational design of drug/vaccine cocktails aimed at interrupting processes occurring at critical host-coronavirus interaction checkpoints. Furthermore, the host-coronavirus protein-protein interactions (PPIs) relevant to COVID-19 were predicted and evaluated based on prior knowledge of curated PPIs and domain-domain interactions, and how such studies can be further explored with the HPI postulates and the HPIPO framework is discussed.

Computational modeling of human-nCoV protein-protein interaction network.

Novel coronavirus (SARS-CoV2) replicates the host cell's genome by interacting with the host proteins. Due to this fact, the identification of virus and host protein–protein interactions could be beneficial in understanding the disease transmission behavior of the virus as well as in potential COVID-19 drug identification. International Committee on Taxonomy of Viruses (ICTV) has declared that nCoV is highly genetically similar to the SARS-CoV epidemic in 2003 (∼89% similarity). With this hypothesis, the present work focuses on developing a computational model for the nCoV-Human protein interaction network, using the experimentally validated SARS-CoV-Human protein interactions. Initially, level-1 and level-2 human spreader proteins are identified in the SARS-CoV-Human interaction network, using Susceptible-Infected-Susceptible (SIS) model. These proteins are considered potential human targets for nCoV bait proteins. A gene-ontology-based fuzzy affinity function has been used to construct the nCoV-Human protein interaction network at a ∼99.98% specificity threshold. This also identifies 37 level-1 human spreaders for COVID-19 in the human protein-interaction network. 2474 level-2 human spreaders are subsequently identified using the SIS model. The derived host-pathogen interaction network is finally validated using six potential FDA-listed drugs for COVID-19 with significant overlap between the known drug target proteins and the identified spreader proteins.

The invasive alien red-eared slider turtle, Trachemys scripta, as a carrier of STEF-disease pathogens

The fungal pathogens Fusarium falciforme and Fusarium keratoplasticum are responsible for the sea turtle egg fusariosis (STEF) throughout main nesting areas of the world. In this study, we investigated whether eggs of the invasive alien red-eared slider turtle, Trachemys scripta, can carry these fungal pathogens. Using multilocus sequence typing of four nuclear DNA regions, we found that eggs of T. scripta naturally can carry these two Fusarium pathogenic species, as well as other Fusarium species belonging to the Fusarium solani species complex. Physiological studies on F. falciforme and F. keratoplasticum isolates revealed that their optimal growth temperature coincided with the pivotal temperature for T. scripta embryos, ca 29.5 ± 0.5 °C, providing an evidence of a potential advantageous biological property for host colonization and virulence. A host-pathogen interaction network analysis of species of the FSSC and their hosts confirmed that F. falciforme and F. keratoplasticum are generalist pathogens in a wide range of animal hosts of worldwide geographical distribution. Finally, we show that nesting areas of this invasive turtle T. scripta in the Mediterranean freshwater marshes can act as chronic reservoirs of these STEF pathogens, and this invasive species can act as a potential vector for the spread of STEF among wild native species and even to humans.

Colored Network Motif Analysis by Dynamic Programming Approach: An Application in Host Pathogen Interaction Network

Network motifs are subgraphs of a network which are found with significantly higher frequency than that expected in similar random networks. Motifs are small building blocks of a network and they have emerged as a way to uncover topological properties of complex networks. A special yet not much explored type of motif is the 'colored motif' where color (type) of each node, and hence the edges, in the motif is distinguishable from each other. A traditional motif is defined as a recurring structure in a network, whereas colored motif introduces detailed information about the color of the nodes. G-trie is a data structure to efficiently store a given set of subgraphs by exploiting the topological overlaps within them. In this article we have implemented a modified g-trie to store colored subgraphs and developed a method to discover colored motifs. Our method uses an approximate enumeration for counting the subgraphs to reduce the runtime. We have applied our method to find colored motifs of size three in a host pathogen protein-protein interaction network having two types of proteins namely HIV-1 and human proteins, and four types of edges. Here, we have discovered eight motifs, six of which contain both HIV-1 and human proteins, while the remaining two contain only human proteins.

Comparative Genomics and Integrated Network Approach Unveiled Undirected Phylogeny Patterns, Co-mutational Hot Spots, Functional Cross Talk, and Regulatory Interactions in SARS-CoV-2.

ABSTRACTThe severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has resulted in 92 million cases in a span of 1 year. The study focuses on understanding population-specific variations attributing its high rate of infections in specific geographical regions particularly in the United States. Rigorous phylogenomic network analysis of complete SARS-CoV-2 genomes (245) inferred five central clades named a (ancestral), b, c, d, and e (subtypes e1 and e2). Clade d and subclade e2 were found exclusively comprised of U.S. strains. Clades were distinguished by 10 co-mutational combinations in Nsp3, ORF8, Nsp13, S, Nsp12, Nsp2, and Nsp6. Our analysis revealed that only 67.46% of single nucleotide polymorphism (SNP) mutations were at the amino acid level. T1103P mutation in Nsp3 was predicted to increase protein stability in 238 strains except for 6 strains which were marked as ancestral type, whereas co-mutation (P409L and Y446C) in Nsp13 were found in 64 genomes from the United States highlighting its 100% co-occurrence. Docking highlighted mutation (D614G) caused reduction in binding of spike proteins with angiotensin-converting enzyme 2 (ACE2), but it also showed better interaction with the TMPRSS2 receptor contributing to high transmissibility among U.S. strains. We also found host proteins, MYO5A, MYO5B, and MYO5C, that had maximum interaction with viral proteins (nucleocapsid [N], spike [S], and membrane [M] proteins). Thus, blocking the internalization pathway by inhibiting MYO5 proteins which could be an effective target for coronavirus disease 2019 (COVID-19) treatment. The functional annotations of the host-pathogen interaction (HPI) network were found to be closely associated with hypoxia and thrombotic conditions, confirming the vulnerability and severity of infection. We also screened CpG islands in Nsp1 and N conferring the ability of SARS-CoV-2 to enter and trigger zinc antiviral protein (ZAP) activity inside the host cell.IMPORTANCE In the current study, we presented a global view of mutational pattern observed in SARS-CoV-2 virus transmission. This provided a who-infect-whom geographical model since the early pandemic. This is hitherto the most comprehensive comparative genomics analysis of full-length genomes for co-mutations at different geographical regions especially in U.S. strains. Compositional structural biology results suggested that mutations have a balance of opposing forces affecting pathogenicity suggesting that only a few mutations are effective at the translation level. Novel HPI analysis and CpG predictions elucidate the proof of concept of hypoxia and thrombotic conditions in several patients. Thus, the current study focuses the understanding of population-specific variations attributing a high rate of SARS-CoV-2 infections in specific geographical regions which may eventually be vital for the most severely affected countries and regions for sharp development of custom-made vindication strategies.

Interactions of the Skin Pathogen Haemophilus ducreyi With the Human Host

The obligate human pathogen Haemophilus ducreyi causes both cutaneous ulcers in children and sexually transmitted genital ulcers (chancroid) in adults. Pathogenesis is dependent on avoiding phagocytosis and exploiting the suppurative granuloma-like niche, which contains a myriad of innate immune cells and memory T cells. Despite this immune infiltrate, long-lived immune protection does not develop against repeated H. ducreyi infections—even with the same strain. Most of what we know about infectious skin diseases comes from naturally occurring infections and/or animal models; however, for H. ducreyi, this information comes from an experimental model of infection in human volunteers that was developed nearly three decades ago. The model mirrors the progression of natural disease and serves as a valuable tool to determine the composition of the immune cell infiltrate early in disease and to identify host and bacterial factors that are required for the establishment of infection and disease progression. Most recently, holistic investigation of the experimentally infected skin microenvironment using multiple “omics” techniques has revealed that non-canonical bacterial virulence factors, such as genes involved in central metabolism, may be relevant to disease progression. Thus, the immune system not only defends the host against H. ducreyi, but also dictates the nutrient availability for the invading bacteria, which must adapt their gene expression to exploit the inflammatory metabolic niche. These findings have broadened our view of the host-pathogen interaction network from considering only classical, effector-based virulence paradigms to include adaptations to the metabolic environment. How both host and bacterial factors interact to determine infection outcome is a current focus in the field. Here, we review what we have learned from experimental H. ducreyi infection about host-pathogen interactions, make comparisons to what is known for other skin pathogens, and discuss how novel technologies will deepen our understanding of this infection.

An Integrative Computational Approach for the Prediction of Human-Plasmodium Protein-Protein Interactions.

Host-pathogen molecular cross-talks are critical in determining the pathophysiology of a specific infection. Most of these cross-talks are mediated via protein-protein interactions between the host and the pathogen (HP-PPI). Thus, it is essential to know how some pathogens interact with their hosts to understand the mechanism of infections. Malaria is a life-threatening disease caused by an obligate intracellular parasite belonging to the Plasmodium genus, of which P. falciparum is the most prevalent. Several previous studies predicted human-plasmodium protein-protein interactions using computational methods have demonstrated their utility, accuracy, and efficiency to identify the interacting partners and therefore complementing experimental efforts to characterize host-pathogen interaction networks. To predict potential putative HP-PPIs, we use an integrative computational approach based on the combination of multiple OMICS-based methods including human red blood cells (RBC) and Plasmodium falciparum 3D7 strain expressed proteins, domain-domain based PPI, similarity of gene ontology terms, structure similarity method homology identification, and machine learning prediction. Our results reported a set of 716 protein interactions involving 302 human proteins and 130 Plasmodium proteins. This work provides a list of potential human-Plasmodium interacting proteins. These findings will contribute to better understand the mechanisms underlying the molecular determinism of malaria disease and potentially to identify candidate pharmacological targets.

MiR-4334-5p Facilitates Foot and Mouth Disease Virus Propagation by Suppressing Interferon Pathways via Direct Targeting ID1.

Emerging evidence indicates that the host microRNAs (miRNAs) are important intracellular regulators and play pivotal roles in intricate host-pathogen interaction networks. In our previous studies, ssc-microRNA-4334-5p (miR-4334-5p) was identified as a differentially expressed miRNA in microarray-based miRNAs profiling experiment, but whether miR-4334-5p regulates foot and mouth disease virus (FMDV) propagation is less understood. Here, we demonstrated that miR-4334-5p expression level was up-regulated shortly after FMDV infection, transfection of miR-4334-5p mimics promoted, while inhibitor transfection suppressed FMDV replication correspondingly. Further bioinformatic analysis and experimental study suggested ID1 was the direct target of miR-4334-5p, suppressing FMDV replication by regulating interferon (IFN) pathways. These findings shed light on microRNAs-ID1-interferon axis in regulating FMDV replication.

Comprehensive host-pathogen protein-protein interaction network analysis

BackgroundInfectious diseases are a cruel assassin with millions of victims around the world each year. Understanding infectious mechanism of viruses is indispensable for their inhibition. One of the best ways of unveiling this mechanism is to investigate the host-pathogen protein-protein interaction network. In this paper we try to disclose many properties of this network. We focus on human as host and integrate experimentally 32,859 interaction between human proteins and virus proteins from several databases. We investigate different properties of human proteins targeted by virus proteins and find that most of them have a considerable high centrality scores in human intra protein-protein interaction network. Investigating human proteins network properties which are targeted by different virus proteins can help us to design multipurpose drugs.ResultsAs host-pathogen protein-protein interaction network is a bipartite network and centrality measures for this type of networks are scarce, we proposed seven new centrality measures for analyzing bipartite networks. Applying them to different virus strains reveals unrandomness of attack strategies of virus proteins which could help us in drug design hence elevating the quality of life. They could also be used in detecting host essential proteins. Essential proteins are those whose functions are critical for survival of its host. One of the proposed centralities named diversity of predators, outperforms the other existing centralities in terms of detecting essential proteins and could be used as an optimal essential proteins’ marker.ConclusionsDifferent centralities were applied to analyze human protein-protein interaction network and to detect characteristics of human proteins targeted by virus proteins. Moreover, seven new centralities were proposed to analyze host-pathogen protein-protein interaction network and to detect pathogens’ favorite host protein victims. Comparing different centralities in detecting essential proteins reveals that diversity of predator (one of the proposed centralities) is the best essential protein marker.

Identification of cellular microRNA miR-188-3p with broad-spectrum anti-influenza A virus activity

BackgroundInfluenza A virus (IAV) continues to pose serious threats to public health. The current prophylaxis and therapeutic interventions for IAV requires frequent changes due to the continuous antigenic drift and antigenic shift of IAV. Emerging evidence indicates that the host microRNAs (miRNAs) play critical roles in intricate host-pathogen interaction networks. Cellular miRNAs may directly target virus to inhibit its infection and be developed as potential anti-virus drugs.MethodsIn this study, we established a broad-spectrum anti-IAV miRNA screening method using miRanda software. The screened miRNAs were further verified by luciferase assay, viral protein expression assay and virus replication assay.ResultsFive cellular miRNAs (miR-188-3p, miR-345-5p, miR-3183, miR-15-3p and miR-769-3p), targeting 99.96, 95.31, 92.9, 94.58 and 97.24% of human IAV strains recorded in NCBI, respectively, were chosen for further experimental verification. Finally, we found that miR-188-3p downregulated PB2 expression at both mRNA and protein levels by directly targeted the predicted sites on PB2 and effectively inhibited the replication of IAV (H1N1, H5N6 and H7N9) in A549 cells.ConclusionsThis is the first report screening cellular miRNAs that broad-spectrum inhibiting IAV infection. These findings suggested that cellular miR-188-3p could be used for RNAi-mediated anti-IAV therapeutic strategies.

The Inducible microRNA-21 Negatively Modulates the Inflammatory Response in Teleost Fish via Targeting IRAK4

Eradication of bacterial infection requires timely and appropriate immune and inflammatory responses, but excessive induction of inflammatory cytokines can cause acute or chronic inflammatory disorders. Thus, various layers of negative regulators and mechanisms are needed to ensure maintenance of the homeostasis for the immune system. miRNAs are a family of small non-coding RNAs that emerged as significant and versatile regulators involved in regulation of immune responses. Recently, the molecular mechanisms of miRNA in host-pathogen interaction networks have been extensively studied in mammals, whereas the underlying regulatory mechanisms in fish are still poorly understood. In this study, we identify miR-21 as a negative regulator of the teleost inflammatory response. We found that lipopolysaccharide and Vibrio anguillarum significantly upregulated the expression of fish miR-21. Upregulated miR-21 suppresses LPS-induced inflammatory cytokine expression by targeting IL-1 receptor-associated kinase 4 (IRAK4), thereby avoiding excessive inflammatory responses. Furthermore, we demonstrated that miR-21 regulates inflammatory responses through NF-κB signaling pathways. The collective findings indicate that miR-21 plays a regulatory role in host-pathogen interactions through IRAK4-mediated NF-κB signaling pathway.

The inducible MicroRNA-21 negatively modulates the inflammatory response in teleost fish via targeting IRAK4

Eradication of bacterial infection requires timely and appropriate immune and inflammatory responses, but excessive induction of inflammatory cytokines can cause acute or chronic inflammatory disorders. Thus, various layers of negative regulators and mechanisms are needed to ensure maintenance of the homeostasis for the immune system. miRNAs are a family of small non-coding RNAs that emerged as significant and versatile regulators involved in regulation of immune responses. Recently, the molecular mechanisms of miRNA in host-pathogen interaction networks have been extensively studied in mammals, whereas the underlying regulatory mechanisms in fish are still poorly understood. In this study, we identify miR-21 as a negative regulator of the teleost inflammatory response. We found that lipopolysaccharide and Vibrio anguillarum significantly upregulated the expression of fish miR-21. Upregulated miR-21 suppresses LPS-induced inflammatory cytokine expression by targeting IL-1 receptor-associated kinase 4 (IRAK4), thereby avoiding excessive inflammatory responses. Furthermore, we demonstrated that miR-21 regulates inflammatory responses through NF-κB signaling pathways. The collective findings indicate that miR-21 plays a regulatory role in host-pathogen interactions through IRAK4-mediated NF-κB signaling pathway.

The Role of miRNA in Differentiation, Cell Proliferation, and Pathogenesis of Poultry Diseases

To date, several noncoding RNAs are known that play a prominent role in the processes of transcription, translation, and structural conformation of RNA. By binding miRNA to 3'-untranslated regions, mRNA regulates gene expression in animals through inhibition of translation initiation, elongation, and other mechanisms. There is evidence for the differential expression of miRNA that regulates transcription with the inclusion of several stages of myoblast proliferation, differentiation, and apoptosis. These molecules play a significant role in cell differentiation, proliferation, apoptosis, and tumorigenesis. Some miRNAs are known to target 100–200 genes. Polymorphisms of miRNA genes, especially in the competent regions of the genome, can be biomarkers for phenotypic traits important for breeding birds. The findings confirm the key role of miRNA in controlling the metabolic switch that occurs between the embryo development and the chick hatching. Differentially expressed miRNAs and their possible target genes are involved in egg production functions. The available miRNA data complement our understanding of the molecular genetic control underlying abdominal fat accumulation and myogenesis in chickens. Hundreds of differentially expressed miRNAs from individuals differing in body weight were found. A new understanding into the functions of miRNA during chicken gonads’ rapid development is being formed. Hundreds of miRNAs expressed by hypothalamic genes and involved in the initial phase of rapid gonad growth have been identified. There is increasingly clear evidence that miRNA play a major role in regulating the innate immune response and are important effectors in complex host–pathogen interaction networks for salmonellosis, Marek’s disease, carcinogenic, and other diseases. Many of the miRNAs are associated with cell proliferation, apoptosis, and tumorigenesis. Bacterial pathogens are able to modulate the expression of the host miRNAs and affect the regulation of miRNAs and the outcome of infection. Several miRNAs are induced by TLR activation in innate immune cells and target the 3′-untranslated regions of the mRNA encoding the components of the TLR signaling system. Modern genome-editing tools suggest an artificial increase in the diversity of miRNAs and an increased use of miRNAs for directional action. Structure determination of RNA, RNA–RNA, RNA–DNA, and ribonucleoprotein complexes is becoming a rapidly developing area requiring the development of new technologies.

Understanding the role of interactions between host and Mycobacterium tuberculosis under hypoxic condition: an in silico approach

BackgroundMycobacterium tuberculosis infection in humans is often associated with extended period of latency. To adapt to the hostile hypoxic environment inside a macrophage, M. tuberculosis cells undergo several physiological and metabolic changes. Previous studies have mostly focused on inspecting individual facets of this complex process. In order to gain deeper insights into the infection process and to understand the coordination among different regulatory/ metabolic pathways in the pathogen, the current in silico study investigates three aspects, namely, (i) host-pathogen interactions (HPIs) between human and M. tuberculosis proteins, (ii) gene regulatory network pertaining to adaptation of M. tuberculosis to hypoxia and (iii) alterations in M. tuberculosis metabolism under hypoxic condition. Subsequently, cross-talks between these components have been probed to evaluate possible gene-regulatory events as well as HPIs which are likely to drive metabolic changes during pathogen’s adaptation to the intra-host hypoxic environment.ResultsThe newly identified HPIs suggest the pathogen’s ability to subvert host mediated reactive oxygen intermediates/ reactive nitrogen intermediates (ROI/ RNI) stress as well as their potential role in modulating host cell cycle and cytoskeleton structure. The results also indicate a significantly pronounced effect of HPIs on hypoxic metabolism of M. tuberculosis. Findings from the current study underscore the necessity of investigating the infection process from a systems-level perspective incorporating different facets of intra-cellular survival of the pathogen.ConclusionsThe comprehensive host-pathogen interaction network, a Boolean model of M. tuberculosis H37Rv (Mtb) hypoxic gene-regulation, as well as a genome scale metabolic model of Mtb, built for this study are expected to be useful resources for future studies on tuberculosis infection.

Leveraging Experimental Details for an Improved Understanding of Host-Pathogen Interactome.

An increasing proportion of curated host-pathogen interaction (HPI) information is becoming available in interaction databases. These data represent detailed, experimentally-verified, molecular interaction data, which may be used to better understand infectious diseases. By their very nature, HPIs are context dependent, where the outcome of two proteins as interacting or not depends on the precise biological conditions studied and approaches used for identifying these interactions. The associated biology and the technical details of the experiments identifying interacting protein molecules are increasing being curated using defined curation standards but are overlooked in current HPI network modeling. Given the increase in data size and complexity, awareness of the process and variables included in HPI identification and curation, and their effect on data analysis and interpretation is crucial in understanding pathogenesis. We describe the use of HPI data for network modeling, aspects of curation that can help researchers to more accurately model specific infection conditions, and provide examples to illustrate these principles. © 2018 by John Wiley & Sons, Inc.

In silico drug design for Staphylococcus aureus and development of host-pathogen interaction network

Abstract Staphylococcus aureus, a member of Staphylococcacea has been considered as an opportunistic pathogen in humans and livestock. Thus, the suggestion has been made to discover a potential drug to address Staphylococcus aureus infections. In the present study, drug designing of natural antistaphylococcal compounds, comprised of docking study of acetylated abietane quinone against ClfA (clumping factor A) using the AutoDock tool, was performed and the formed hydrogen bonds in the docked complex were analyzed using Pymol software. A drug library of 86 natural antistaphylococcal compounds was generated and screened with Lipinski and ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) filters using Molinspiration and PreADMET tools. A host-pathogen interaction network of Staphylococcus aureus and humans was developed using Cytoscape tool. After applying filters and performing an analysis, acetylated abietane quinone, which is a natural antistaphylococcal compound and a component of mint, was obtained. The binding energy of the docked complex of ligand acetylated abietane quinone against receptor ClfA was estimated to be −7.52 kcal/mol, which showed good binding affinity. Thus, acetylated abietane quinone could serve as a drug for treating staphylococcal infections in humans. A total of 40 interactions between S. aureus and humans were identified and represented using the developed host-pathogen interaction network, which should provide a significant target-based drug discovery for treating S. aureus infections in humans.

Mechanisms of action of Coxiella burnetii effectors inferred from host-pathogen protein interactions.

Coxiella burnetii is an obligate Gram-negative intracellular pathogen and the etiological agent of Q fever. Successful infection requires a functional Type IV secretion system, which translocates more than 100 effector proteins into the host cytosol to establish the infection, restructure the intracellular host environment, and create a parasitophorous vacuole where the replicating bacteria reside. We used yeast two-hybrid (Y2H) screening of 33 selected C. burnetii effectors against whole genome human and murine proteome libraries to generate a map of potential host-pathogen protein-protein interactions (PPIs). We detected 273 unique interactions between 20 pathogen and 247 human proteins, and 157 between 17 pathogen and 137 murine proteins. We used orthology to combine the data and create a single host-pathogen interaction network containing 415 unique interactions between 25 C. burnetii and 363 human proteins. We further performed complementary pairwise Y2H testing of 43 out of 91 C. burnetii-human interactions involving five pathogen proteins. We used the combined data to 1) perform enrichment analyses of target host cellular processes and pathways, 2) examine effectors with known infection phenotypes, and 3) infer potential mechanisms of action for four effectors with uncharacterized functions. The host-pathogen interaction profiles supported known Coxiella phenotypes, such as adapting cell morphology through cytoskeletal re-arrangements, protein processing and trafficking, organelle generation, cholesterol processing, innate immune modulation, and interactions with the ubiquitin and proteasome pathways. The generated dataset of PPIs—the largest collection of unbiased Coxiella host-pathogen interactions to date—represents a rich source of information with respect to secreted pathogen effector proteins and their interactions with human host proteins.

Technologies for Proteome-Wide Discovery of Extracellular Host-Pathogen Interactions.

Pathogens have evolved unique mechanisms to breach the cell surface barrier and manipulate the host immune response to establish a productive infection. Proteins exposed to the extracellular environment, both cell surface-expressed receptors and secreted proteins, are essential targets for initial invasion and play key roles in pathogen recognition and subsequent immunoregulatory processes. The identification of the host and pathogen extracellular molecules and their interaction networks is fundamental to understanding tissue tropism and pathogenesis and to inform the development of therapeutic strategies. Nevertheless, the characterization of the proteins that function in the host-pathogen interface has been challenging, largely due to the technical challenges associated with detection of extracellular protein interactions. This review discusses available technologies for the high throughput study of extracellular protein interactions between pathogens and their hosts, with a focus on mammalian viruses and bacteria. Emerging work illustrates a rich landscape for extracellular host-pathogen interaction and points towards the evolution of multifunctional pathogen-encoded proteins. Further development and application of technologies for genome-wide identification of extracellular protein interactions will be important in deciphering functional host-pathogen interaction networks, laying the foundation for development of novel therapeutics.