No abstract available

We first review fundamental insights into anti-ranavirus immunity learned with the Xenopus laevis/ranavirus FV3 model that are generally applicable to ectothermic vertebrates. We then further investigate FV3 genes involved in immune evasion. Focusing on FV3 knockout (KO) mutants defective for a putative viral caspase activation and recruitment domain-containing (CARD)-like protein (Δ64R-FV3), a β-hydroxysteroid dehydrogenase homolog (Δ52L-FV3), and an immediate-early18kDa protein (FV3-Δ18K), we assessed the involvement of these viral genes in replication, dissemination and interaction with peritoneal macrophages in tadpole and adult frogs. Our results substantiate the role of 64R and 52L as critical immune evasion genes, promoting persistence and dissemination in the host by counteracting type III IFN in tadpoles and type I IFN in adult frogs. Comparably, the substantial accumulation of genome copy numbers and exacerbation of type I and III IFN gene expression responses but deficient release of infectious virus suggests that 18K is a viral regulatory gene.

The transcriptome is a powerful proxy for the physiological state of a cell, healthy or diseased. As a result, transcriptome analysis has become a key tool in understanding the molecular changes that accompany bacterial infections of eukaryotic cells. Until recently, such transcriptomic studies have been technically limited to analyzing mRNA expression changes in either the bacterial pathogen or the infected eukaryotic host cell. However, the increasing sensitivity of high-throughput RNA sequencing now enables "dual RNA-seq" studies, simultaneously capturing all classes of coding and noncoding transcripts in both the pathogen and the host. In the five years since the concept of dual RNA-seq was introduced, the technique has been applied to a range of infection models. This has not only led to a better understanding of the physiological changes in pathogen and host during the course of an infection but has also revealed hidden molecular phenotypes of virulence-associated small noncoding RNAs that were not visible in standard infection assays. Here, we use the knowledge gained from these recent studies to suggest experimental and computational guidelines for the design of future dual RNA-seq studies. We conclude this review by discussing prospective applications of the technique.

Protein-protein interactions (PPIs) play a crucial role in initiating infection in a host-pathogen system. Identification of these PPIs is important for understanding the underlying biological mechanism of infection and identifying putative drug targets. Database resources for studying host-pathogen systems are scarce and are either host specific or dedicated to specific pathogens.

The SugarBind Database (SugarBindDB) covers knowledge of glycan binding of human pathogen lectins and adhesins. It is a curated database; each glycan-protein binding pair is associated with at least one published reference. The core data element of SugarBindDB is a set of three inseparable components: the pathogenic agent, a lectin/adhesin and a glycan ligand. Each entity (agent, lectin or ligand) is described by a range of properties that are summarized in an entity-dedicated page. Several search, navigation and visualisation tools are implemented to investigate the functional role of glycans in pathogen binding. The database is cross-linked to protein and glycan-relaled resources such as UniProtKB and UniCarbKB. It is tightly bound to the latter via a substructure search tool that maps each ligand to full structures where it occurs. Thus, a glycan-lectin binding pair of SugarBindDB can lead to the identification of a glycan-mediated protein-protein interaction, that is, a lectin-glycoprotein interaction, via substructure search and the knowledge of site-specific glycosylation stored in UniCarbKB. SugarBindDB is accessible at: http://sugarbind.expasy.org.

Identification and analysis of host-pathogen interactions (HPI) is essential to study infectious diseases. However, HPI data are sparse in existing molecular interaction databases, especially for agricultural host-pathogen systems. Therefore, resources that annotate, predict and display the HPI that underpin infectious diseases are critical for developing novel intervention strategies. HPIDB 2.0 (http://www.agbase.msstate.edu/hpi/main.html) is a resource for HPI data, and contains 45, 238 manually curated entries in the current release. Since the first description of the database in 2010, multiple enhancements to HPIDB data and interface services were made that are described here. Notably, HPIDB 2.0 now provides targeted biocuration of molecular interaction data. As a member of the International Molecular Exchange consortium, annotations provided by HPIDB 2.0 curators meet community standards to provide detailed contextual experimental information and facilitate data sharing. Moreover, HPIDB 2.0 provides access to rapidly available community annotations that capture minimum molecular interaction information to address immediate researcher needs for HPI network analysis. In addition to curation, HPIDB 2.0 integrates HPI from existing external sources and contains tools to infer additional HPI where annotated data are scarce. Compared to other interaction databases, our data collection approach ensures HPIDB 2.0 users access the most comprehensive HPI data from a wide range of pathogens and their hosts (594 pathogen and 70 host species, as of February 2016). Improvements also include enhanced search capacity, addition of Gene Ontology functional information, and implementation of network visualization. The changes made to HPIDB 2.0 content and interface ensure that users, especially agricultural researchers, are able to easily access and analyse high quality, comprehensive HPI data. All HPIDB 2.0 data are updated regularly, are publically available for direct download, and are disseminated to other molecular interaction resources.Database URL: http://www.agbase.msstate.edu/hpi/main.html.

For image-based infection biology, accurate unbiased quantification of host-pathogen interactions is essential, yet often performed manually or using limited enumeration employing simple image analysis algorithms based on image segmentation. Host protein recruitment to pathogens is often refractory to accurate automated assessment due to its heterogeneous nature. An intuitive intelligent image analysis program to assess host protein recruitment within general cellular pathogen defense is lacking. We present HRMAn (Host Response to Microbe Analysis), an open-source image analysis platform based on machine learning algorithms and deep learning. We show that HRMAn has the capacity to learn phenotypes from the data, without relying on researcher-based assumptions. Using Toxoplasma gondii and Salmonella enterica Typhimurium we demonstrate HRMAn's capacity to recognize, classify and quantify pathogen killing, replication and cellular defense responses. HRMAn thus presents the only intelligent solution operating at human capacity suitable for both single image and high content image analysis.

Menaquinone (vitamin K2) shuttles electrons between membrane-bound respiratory complexes under microaerophilic conditions. In photosynthetic eukaryotes and cyanobacteria, phylloquinone (vitamin K1) participates in photosystem I function. Here we elucidate the evolutionary history of vitamin K metabolism in algae and plants. We show that Chlamydiales intracellular pathogens made major genetic contributions to the synthesis of the naphthoyl ring core and the isoprenoid side-chain of these quinones. Production of the core in extremophilic red algae is under control of a menaquinone (Men) gene cluster consisting of 7 genes that putatively originated via lateral gene transfer (LGT) from a chlamydial donor to the plastid genome. In other green and red algae, functionally related nuclear genes also originated via LGT from a non-cyanobacterial, albeit unidentified source. In addition, we show that 3-4 of the 9 required steps for synthesis of the isoprenoid side chains are under control of genes of chlamydial origin. These results are discussed in the light of the hypoxic response experienced by the cyanobacterial endosymbiont when it gained access to the eukaryotic cytosol.

During bacterial pathogenesis extensive contacts between the human and the bacterial extracellular proteomes take place. The identification of novel host-pathogen interactions by standard methods using a case-by-case approach is laborious and time consuming. To overcome this limitation, we took advantage of large libraries of human and bacterial recombinant proteins. We applied a large-scale protein microarray-based screening on two important human pathogens using two different approaches: (I) 75 human extracellular proteins were tested on 159 spotted Staphylococcus aureus recombinant proteins and (II) Neisseria meningitidis adhesin (NadA), an important vaccine component against serogroup B meningococcus, was screened against ≈2300 spotted human recombinant proteins. The approach presented here allowed the identification of the interaction between the S. aureus immune evasion protein FLIPr (formyl-peptide receptor like-1 inhibitory protein) and the human complement component C1q, key players of the offense-defense fighting; and of the interaction between meningococcal NadA and human LOX-1 (low-density oxidized lipoprotein receptor), an endothelial receptor. The novel interactions between bacterial and human extracellular proteins here presented might provide a better understanding of the molecular events underlying S. aureus and N. meningitidis pathogenesis.

Knowledge of the pathogen-host interactions between the species is essentialin order to develop a solution strategy against infectious diseases. In vitro methods take extended periods of time to detect interactions and provide very few of the possible interaction pairs. Hence, modelling interactions between proteins has necessitated the development of computational methods. The main scope of this paper is integrating the known protein interactions between thehost and pathogen organisms to improve the prediction success rate of unknown pathogen-host interactions. Thus, the truepositive rate of the predictions was expected to increase.In order to perform this study extensively, encoding methods and learning algorithms of several proteins were tested. Along with human as the host organism, two different pathogen organisms were used in the experiments. For each combination of protein-encoding and prediction method, both the original prediction algorithms were tested using only pathogen-host interactions and the same methodwas testedagain after integrating the known protein interactions within each organism. The effect of merging the networks of pathogen-host interactions of different species on the prediction performance of state-of-the-art methods was also observed. Successwas measured in terms of Matthews correlation coefficient, precision, recall, F1 score, and accuracy metrics. Empirical results showed that integrating the host and pathogen interactions yields better performance consistently in almost all experiments.

Infections are one of the major selective pressures acting on humans, and host-pathogen interactions contribute to shaping the genetic diversity of both organisms. Evolutionary genomic studies take advantage of experiments that natural selection has been performing over millennia. In particular, inter-species comparative genomic analyses can highlight the genetic determinants of infection susceptibility or severity. Recent examples show how evolution-guided approaches can provide new insights into host-pathogen interactions, ultimately clarifying the basis of host range and explaining the emergence of different diseases. We describe the latest developments in comparative immunology and evolutionary genetics, showing their relevance for understanding the molecular determinants of infection susceptibility in mammals.

Vibrio cholerae, which causes the diarrheal disease cholera, is a species of bacteria commonly found in aquatic habitats. Within such environments, the bacterium must defend itself against predatory protozoan grazers. Amoebae are prominent grazers, with Acanthamoeba castellanii being one of the best-studied aquatic amoebae. We previously showed that V. cholerae resists digestion by A. castellanii and establishes a replication niche within the host's osmoregulatory organelle. In this study, we decipher the molecular mechanisms involved in the maintenance of V. cholerae's intra-amoebal replication niche and its ultimate escape from the succumbed host. We demonstrate that minor virulence features important for disease in mammals, such as extracellular enzymes and flagellum-based motility, have a key role in the replication and transmission of V. cholerae in its aqueous environment. This work, therefore, describes new mechanisms that provide the pathogen with a fitness advantage in its primary habitat, which may have contributed to the emergence of these minor virulence factors in the species V. cholerae.

Here we describe the use of synthetic genetic elements to improve the predictability and tunability of episomal protein production in Salmonella. We used a multi-pronged approach, in which a series of variable-strength synthetic promoters were combined with a synthetic transcriptional terminator, and plasmid copy number variation. This yielded a series of plasmids that drive uniform production of fluorescent and endogenous proteins, over a wide dynamic range. We describe several examples where this system is used to fine-tune constitutive expression in Salmonella, providing an efficient means to titrate out toxic effects of protein production.

Coxiella burnetii is a Gram-negative, intracellular bacterium that causes the zoonosis Q fever. Among the many natural isolates of C. burnetii recovered from various sources, the Dugway group exhibits unique genetic characteristics, including the largest C. burnetii genomes. These strains were isolated during 1954-1958 from wild rodents from the Utah, USA desert. Despite retaining phase I lipopolysaccharide and the type 4B secretion system, two critical virulence factors, avirulence has been reported in a guinea pig infection model. Using guinea pig models, we evaluated the virulence, whole-cell vaccine (WCV) efficacy, and post-vaccination hypersensitivity (PVH) potential of a representative Dugway strain. Consistent with prior reports, Dugway appeared to be highly attenuated compared to a virulent strain. Indeed, Dugway-infected animals showed similarly low levels of fever, body weight loss, and splenomegaly like Nine Mile II-infected animals. When compared to a human Q fever vaccine, QVax®, Dugway WCV exhibited analogous protection against a heterologous Nine Mile I challenge. PVH was investigated in a skin-testing model which revealed significantly decreased maximum erythema in Dugway Δdot/icm WCV-skin-tested animals compared to that of QVax®. These data provide insight into this unique bacterial strain and implicate its potential use as a mutated WCV candidate.

Human enteroids-epithelial spheroids derived from primary gastrointestinal tissue-are a promising model to study pathogen-epithelial interactions. However, accessing the apical enteroid surface is challenging because it is enclosed within the spheroid. We developed a technique to reverse enteroid polarity such that the apical surface everts to face the media. Apical-out enteroids maintain proper polarity and barrier function, differentiate into the major intestinal epithelial cell (IEC) types, and exhibit polarized absorption of nutrients. We used this model to study host-pathogen interactions and identified distinct polarity-specific patterns of infection by invasive enteropathogens. Salmonella enterica serovar Typhimurium targets IEC apical surfaces for invasion via cytoskeletal rearrangements, and Listeria monocytogenes, which binds to basolateral receptors, invade apical surfaces at sites of cell extrusion. Despite different modes of entry, both pathogens exit the epithelium within apically extruding enteroid cells. This model will enable further examination of IECs in health and disease.

Burkholderia pathogenicity relies on protein virulence factors to control and promote bacterial internalization, survival, and replication within eukaryotic host cells. We recently used yeast two-hybrid (Y2H) screening to identify a small set of novel Burkholderia proteins that were shown to attenuate disease progression in an aerosol infection animal model using the virulent Burkholderia mallei ATCC 23344 strain. Here, we performed an extended analysis of primarily nine B. mallei virulence factors and their interactions with human proteins to map out how the bacteria can influence and alter host processes and pathways. Specifically, we employed topological analyses to assess the connectivity patterns of targeted host proteins, identify modules of pathogen-interacting host proteins linked to processes promoting infectivity, and evaluate the effect of crosstalk among the identified host protein modules. Overall, our analysis showed that the targeted host proteins generally had a large number of interacting partners and interacted with other host proteins that were also targeted by B. mallei proteins. We also introduced a novel Host-Pathogen Interaction Alignment (HPIA) algorithm and used it to explore similarities between host-pathogen interactions of B. mallei, Yersinia pestis, and Salmonella enterica. We inferred putative roles of B. mallei proteins based on the roles of their aligned Y. pestis and S. enterica partners and showed that up to 73% of the predicted roles matched existing annotations. A key insight into Burkholderia pathogenicity derived from these analyses of Y2H host-pathogen interactions is the identification of eukaryotic-specific targeted cellular mechanisms, including the ubiquitination degradation system and the use of the focal adhesion pathway as a fulcrum for transmitting mechanical forces and regulatory signals. This provides the mechanisms to modulate and adapt the host-cell environment for the successful establishment of host infections and intracellular spread.

Chlamydia trachomatis (Ct) causes the most prevalent bacterial sexually transmitted disease leading to ectopic pregnancy and infertility. Swine not only have many similarities to humans, but they are also susceptible to Ct. Despite these benefits and the ease of access to primary tissue from this food animal, in vitro research in swine has been underutilized. This study will provide basic understanding of the Ct host-pathogen interactions in porcine oviduct epithelial cells (pOECs)-the counterparts of human Fallopian tube epithelial cells. Using NanoString technology, flow cytometry, and confocal and transmission-electron microscopy, we studied the Ct developmental cycle in pOECs, the cellular immune response, and the expression and location of the tight junction protein claudin-4. We show that Ct productively completes its developmental cycle in pOECs and induces an immune response to Ct similar to human cells: Ct mainly induced the upregulation of interferon regulated genes and T-cell attracting chemokines. Furthermore, Ct infection induced an accumulation of claudin-4 in the Ct inclusion with a coinciding reduction of membrane-bound claudin-4. Downstream effects of the reduced membrane-bound claudin-4 expression could potentially include a reduction in tight-junction expression, impaired epithelial barrier function as well as increased susceptibility to co-infections. Thereby, this study justifies the investigation of the effect of Ct on tight junctions and the mucosal epithelial barrier function. Taken together, this study demonstrates that primary pOECs represent an excellent in vitro model for research into Ct pathogenesis, cell biology and immunity.

We consider the problem of building a model to predict protein-protein interactions (PPIs) between the bacterial species Salmonella Typhimurium and the plant host Arabidopsis thaliana which is a host-pathogen pair for which no known PPIs are available. To achieve this, we present approaches, which use homology and statistical learning methods called "transfer learning." In the transfer learning setting, the task of predicting PPIs between Arabidopsis and its pathogen S. Typhimurium is called the "target task." The presented approaches utilize labeled data i.e., known PPIs of other host-pathogen pairs (we call these PPIs the "source tasks"). The homology based approaches use heuristics based on biological intuition to predict PPIs. The transfer learning methods use the similarity of the PPIs from the source tasks to the target task to build a model. For a quantitative evaluation we consider Salmonella-mouse PPI prediction and some other host-pathogen tasks where known PPIs exist. We use metrics such as precision and recall and our results show that our methods perform well on the target task in various transfer settings. We present a brief qualitative analysis of the Arabidopsis-Salmonella predicted interactions. We filter the predictions from all approaches using Gene Ontology term enrichment and only those interactions involving Salmonella effectors. Thereby we observe that Arabidopsis proteins involved e.g., in transcriptional regulation, hormone mediated signaling and defense response may be affected by Salmonella.

Fungal infections, ranging from superficial to life-threatening infections, represent a major public health problem that affects 25% of the worldwide population. In this context, the study of host-pathogen interactions within the host is crucial to advance antifungal therapy. However, since fungal cells are usually outnumbered by host cells, the fungal transcriptome frequently remains uncovered. We compared three different methods to selectively lyse human cells from in vitro mixes, composed of Candida cells and peripheral blood mononuclear cells. In order to prevent transcriptional modification, the mixes were stored in RNAlater. We evaluated the enrichment of fungal cells through cell counting using microscopy and aimed to further enrich fungal nucleic acids by centrifugation and by reducing contaminant nucleic acids from the host. We verified the enrichment of fungal DNA and RNA through qPCR and RT-qPCR respectively and confirmed that the resulting RNA has high integrity scores, suitable for downstream applications. The enrichment method provided here, i.e., lysis with Buffer RLT followed by centrifugation, may contribute to increase the proportion of nucleic acids from fungi in clinical samples, thus promoting more comprehensive analysis of fungal transcriptional profiles. Although we focused on C. albicans, the enrichment may be applicable to other fungal pathogens.

The identification of host / pathogen interactions is essential to both understanding the molecular biology of infection and developing rational intervention strategies to overcome disease. Alphaviruses, such as Sindbis virus, Chikungunya virus, and Venezuelan Equine Encephalitis virus are medically relevant positive-sense RNA viruses. As such, they must interface with the host machinery to complete their infectious lifecycles. Nonetheless, exhaustive RNA:Protein interaction discovery approaches have not been reported for any alphavirus species. Thus, the breadth and evolutionary conservation of host interactions on alphaviral RNA function remains a critical gap in the field. Herein we describe the application of the Cross-Link Assisted mRNP Purification (CLAMP) strategy to identify conserved alphaviral interactions. Through comparative analyses, conserved alphaviral host / pathogen interactions were identified. Approximately 100 unique host proteins were identified as a result of these analyses. Ontological assessments reveal enriched Molecular Functions and Biological Processes relevant to alphaviral infection. Specifically, as anticipated, Poly(A) RNA Binding proteins are significantly enriched in virus specific CLAMP data sets. Moreover, host proteins involved in the regulation of mRNA stability, proteasome mediated degradation, and a number of 14-3-3 proteins were identified. Importantly, these data expand the understanding of alphaviral host / pathogen interactions by identifying conserved interactants.