Top PDF Early Interaction of Rhinoviruses with Host Cells

Early Interaction of Rhinoviruses with Host Cells

Early Interaction of Rhinoviruses with Host Cells

The rhinovirus type 2 eclipse product differs from the eluted particles from poliovirus and coxsackievirus in that it is partly stable to CsCl gradient centrifugation and in CsCl produce[r]

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Visualization of Host-Polerovirus Interaction Topologies Using Protein Interaction Reporter Technology

Visualization of Host-Polerovirus Interaction Topologies Using Protein Interaction Reporter Technology

The PIR-defined interaction between the substrate binding do- main of the ER chaperone BiP and the arginine-rich region of PLRV CP monomer uncovered a highly conserved CP peptide domain rich in hydrophobic, neutral residues that was not iden- tified as a putative functional domain in previous predication studies that were based on epitope mapping and sequence align- ments with distantly related, icosahedron-shaped viruses (3, 7, 8, 59, 76). The high degree of conservation of this BiP binding site among the Luteoviridae CP sequences supports the conclusion that the interaction of CP with BiP is beneficial to the virus. In- deed, the VIGS functional data indicate that BiP is a positive reg- ulator of PLRV during early infection. One hypothesis is that CP- BiP interactions in planta act to reduce ER cytotoxicity caused by high levels of viral protein synthesis. BiPs act as sensors of ER stress in plants by inducing the unfolded protein response (UPR) (77). Suppression of the UPR in plants by the virus may have collateral benefits for virus transmission: circulative transmission of PLRV by aphids, which require prolonged feeding on healthy phloem (14). HSP70 family members, including BiP, are known targets of viruses during host infection (55, 56, 78). For example, depletion of BiP in fibroblast cells inhibited human cytomegalo- virus (HCMV) virion formation and cytosolic egress, although viral protein synthesis was unaffected (55). Upon infection with HCMV, BiP becomes relocalized from the ER to cytoplasmic structures that act as assembly compartments for the virus (62). It is possible that a similar mechanism occurs in plant cells infected with poleroviruses, which also replicate in the cytoplasm. Trans- mission electron micrographs of PLRV-infected phloem cells show the formation of virus-induced vesicles within the cyto- plasm, the protein composition and function of which still re- mains unknown (79).
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Adenovirus Early Proteins and Host Sumoylation

Adenovirus Early Proteins and Host Sumoylation

An enigma in the SUMO field has been how sumoylation af- fects the overall function of a protein when, typically, only a small percentage of the population of that protein is sumoylated (68). Several ideas have been proposed to explain this conundrum, in- cluding the idea that protein sumoylation may be required to ini- tiate but not maintain a regulatory event (for example, repression of a transcription factor) or that sumoylation is only needed tran- siently to initiate subsequent processes (68). The studies by Pen- nella et al. pertaining to E1B-55K and p53 sumoylation support a different model (45). E1B-55K and p53 oligomerize themselves and with each other to form a molecular network within cells. Only a small fraction of each of these proteins is sumoylated. This model proposes that once a network of interacting proteins has formed, interactions between sumoylated proteins within the net- work and other proteins with SIMs (SUMO interaction motifs) (for example PML) could have broad effects on the properties of the overall network. Taking PML as an example, sumoylation of a small fraction of E1B-55K and p53 would move the E1B-55K:p53 protein network to PML-NBs. All three of these models may be correct and pertain to specific examples of protein sumoylation.
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Host virus interaction: a new role for microRNAs

Host virus interaction: a new role for microRNAs

The interest in discovering novel microRNA candidates using both computational tools and experimental valida- tion of the predicted candidates have shown that viruses also encode microRNAs (see Table 1). Most of these pre- dictions have been successfully validated using experi- mental approaches. The current understanding of virus encoded microRNAs is limited mainly to the Herpes virus family, which is a unique class of viruses whose members are implicated in a number of major pathogenic states in humans ranging from mild infections to oncogenesis. Other viruses with miRNA mediated regulation include major pathogens like HIV and Simian Virus 40 (SV40) [41]. SV40 encoded microRNAs which are generated dur- ing the late phase in life cycle could target the early tran- scripts including those coding for viral T antigens and mediate evasion of the virus infected cells from cytotoxic T cells.
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Analysis of interaction between the apicomplexan protozoan Toxoplasma gondii and host cells using label free Raman Spectroscopy

Analysis of interaction between the apicomplexan protozoan Toxoplasma gondii and host cells using label free Raman Spectroscopy

Raman micro-spectroscopy was used to measure label-free molecular properties of T. gondii- infected host cells. Significant increase in protein and lipid concentration was reported associated with development of infection as confirmed by time-course experiments on both paraformaldehyde-fixed and live infected cells. The development of T. gondii cells was also accompanied by an increase in nucleic acids as early as 6 hr PI. While this study demonstrates the potential of Raman spectroscopy to detect molecular changes during host-pathogen interaction, the current method does not provide sufficient specificity to pinpoint the main proteins or lipids that are affected during this biological process. Further studies are currently planned using isotope labelled molecules to improve the specificity and discrimination between biomolecules originating from the T. gondii and host cells. These future experiments are likely to provide further information related to molecular exchange between pathogen and host cells. Understanding the time- and spatially-dependent molecular interactions between pathogens and host cells may provide a useful platform for screening compounds with potential neuro-protective activity for eminent effects of changes in brain infection control practices.
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Transcriptomic insights into the early host pathogen interaction of cat intestine with Toxoplasma gondii

Transcriptomic insights into the early host pathogen interaction of cat intestine with Toxoplasma gondii

evades the immune response in order to facilitate its own growth in the intestine of cats during the first 12 hpi. Host cells, via increasing the expression of HSP70/ 90, PA28, TAP , and TAP1/2 genes, deploy chaperones, immunoproteasomes and transporters to limit infection, through promoting antigen processing and presentation. In the present study, as infection progressed, the expres- sion of MHC I genes was elevated at 72 and 96 hpi, indi- cating that the cats may have mounted a CTL response, mediated by MHC I, to limit replication of the parasite. Infecting cultured rat-intestinal epithelial cells with mature sporozoites, induced an elevated expression of genes associated with tumor necrosis factor alpha (TNFα) signaling, via NF-κB [44]. This transcriptomic change was not observed in our study, suggesting that anti-T. gondii intestinal immunity can vary between different hosts and different parasite stages, and based on whether the infection was established under in vitro or in vivo conditions.
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Host restriction factors in retroviral infection: promises in virus host interaction

Host restriction factors in retroviral infection: promises in virus host interaction

Although Fv1 is only expressed in mice, the N-MLV strains encounter an Fv1-like restriction in non-murine species including humans, and this unknown MLV inhibitor was named restriction factor 1 (Ref-1) [164]. Ref1 also inhibits EIAV replication in human cells [165]. HIV-1 and some SIV strains encounter another Fv1-like restriction when they infect some non-human species. For example, HIV-1 replication is inhibited in the Old World Monkeys (rhesus macaques, African green mon- keys) and New World Monkeys (squirrel monkeys, common marmosets); SIV (SIVmac) infection is blocked in the squirrel monkeys. The unknown HIV-1 and SIV inhibitors were named lentivirus susceptibility factor 1 (Lv1) [166,167]. Fv-1, Ref-1, and Lv-1 share remarkable similarities in their viral inhibition. First, they all target an early post-entry step. Both Ref-1 and Lv-1 act at steps before or after reverse transcription, whereas Fv1 acts at a step after reverse transcription but before integration. Second, they all target viral CA proteins. The same single CA 110 residue that differentiates between N- and B-tropism in mice also determines MLV tropism in human cells. Similarly, HIV-1 and SIVmac restriction in some primate cell lines is determined by sequences within the CA-p2 region of Gag [167-169]. Third, all these restrictions can be released by a high multiplicity of infection (m.o.i.), indicating that they are saturable. In due course, the Lv1 restriction activity was first identi- fied as the TRIM5α protein from rhesus monkey cells and later as the TRIM-Cyp fusion from the owl monkey cells [170,171]. Subsequently, Ref-1 was identified as the human TRIM5α protein [172]. Thus, Ref-1 and Lv1 are specifies-specific TRIM5α proteins that have different activities against different retroviruses.
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Arbovirus Structure and Interaction with Host Cells.

Arbovirus Structure and Interaction with Host Cells.

60 MicroRNAs (miRNA) are small (20-22 bases) single-stranded RNAs that regulate protein expression post-transcriptionally by preventing translation and/or promoting target mRNA degradation. Hepatitis C (Hep C), DENV and Eastern Equine Encephalitis virus (EEEV) all have single stranded +RNA genomes and have been shown to use miRNA to modify the host cell response to viral infection (Jopling et al., 2005; Trobaugh et al., 2014; Trobaugh & Klimstra, 2017; Wu et al., 2013). During HepC infection, liver specific miR122 binds to viral RNA, stabilizing the RNA and enhancing in vivo viral replication (Jopling et al., 2005; Shimakami et al., 2012). miR-146a facilitates replication of DENV by targeting the TRAF6 gene and thereby suppressing interferon induction (Wu et al., 2013). In the case of EEEV, haematopoietic-cell specific miR-142-3p restricts the replication of the virus in myeloid-lineage cells (Trobaugh et al., 2014). We hypothesize that the evolution from pre-epidemic to epidemic ZIKV involves a change in the miRNA profile induced by these two strains. This may correlate with the altered pathogenesis. It is also hypothesized that the pathogenesis of ZIKV is more pronounced when the miRNAs are expressed early during infection in cells, such as in cells of the monocyte lineage, the “first responders” of the innate immune system. The miRNA profile of ZIKV infected human macrophages (MФ) is not known.
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Extension of Flavivirus Protein C Differentially Affects Early RNA Synthesis and Growth in Mammalian and Arthropod Host Cells

Extension of Flavivirus Protein C Differentially Affects Early RNA Synthesis and Growth in Mammalian and Arthropod Host Cells

and the mutant when a high number of naked RNA molecules were introduced by electroporation. This suggests that the C-2A protein of the incoming virions impaired uncoating and/or early viral RNA synthesis, highlighting a previously undetected role of protein C in these processes. Given that TBEV-2A replicated extremely poorly in vector tick cells, it appears that this previously undetected role of protein C de- pends on the interaction with factors present in the host cell. The observed defects in unpackaging and RNA replication must derive from the changes in the properties of the C ter- minus of protein C. Indeed, the 19-amino-acid 2A extension introduces 15 uncharged, mainly hydrophobic residues that may interfere with the known RNA binding ability of basic residues (14). Ma et al. (24) and Dokland et al. (7) have shown for protein C of dengue virus and WNV, respectively, that protein C occurs as a dimer with the two C-terminal helices lying close together and forming a broad interface for interac- tion with RNA. It seems possible that the 19-amino-acid 2A extension may interfere with the accessibility of the basic res- idues or hinder dimer formation, or both. These structural changes may be detrimental to the correct release of the RNA during uncoating or to the state of the RNA at the start of the replication process. Alternatively, the 2A sequences could af- fect the intracellular location of protein C during early RNA synthesis or its interaction with other components of the as- sembling replication complex. Notably, the C proteins of Kun- jin virus and Japanese encephalitis virus have been shown to translocate to the nucleus during infection (28, 41).
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Persistent Gammaherpesvirus Replication and Dynamic Interaction with the Host In Vivo

Persistent Gammaherpesvirus Replication and Dynamic Interaction with the Host In Vivo

The multistep growth curve assay was performed to investi- gate the growth of M3FL and the parental wild-type MHV-68 during multiple rounds of replication in mouse fibroblast NIH FIG. 1. Construction of recombinant MHV-68 for bioluminescent imaging. (A) Schematic diagram of M3FL. Viral M3 promoter-driven firefly luciferase (FL) gene cassette was inserted between genomic coordinates 746 and 747 of MHV-68 WUMS (GenBank no. U97553). Nucleotide 1882 is the insertion site of the bacterial artificial chromosome vector sequence. TR, terminal repeat. (B) Genomic integrity of M3FL. BAC DNA from wild-type MHV-68 (WT) and M3FL was digested with EcoRI, HindIII, and SmaI and analyzed by agarose gel electrophoresis. Small white circles indicate the shift of digested fragment due to the insertion of the M3 promoter-driven FL gene cassette. The white triangle indicates the heterogenous fragment in the EcoRI-digested pattern, which includes the 40-bp repeat region. (C) Expression of FL from M3FL virus. The lysate of the cells infected with either WT or M3FL was resolved by sodium dodecyl sulfate-polyacrylamide gel electrophoresis, and the expression of FL was analyzed by Western blotting using anti-FL (sc-57603; Santa Cruz). A Western blot using antibodies against viral structural proteins (ORF26 and M9) was included as a control for viral replication. (D) Multistep growth curve of wild-type MHV-68 and M3FL in NIH 3T12 cells. The data were compiled from three independent experiments, and standard deviations are shown as error bars. (E) In vitro correlation of FL activity with viral replication. NIH 3T12 cells were infected with M3FL at multiple MOIs, and the titer of infectious virus and the relative luciferase units (R.L.U.)/ ␮ g of protein in the whole-cell lysate were determined as described in Materials and Methods. (F) In vivo correlation of FL activity with viral replication. Mice were infected intranasally with 5 ⫻ 10 5 PFU of M3FL, and the titer of infectious virus and the number of RLU in the
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Reassortment of NS Segments Modifies Highly Pathogenic Avian Influenza Virus Interaction with Avian Hosts and Host Cells

Reassortment of NS Segments Modifies Highly Pathogenic Avian Influenza Virus Interaction with Avian Hosts and Host Cells

Highly pathogenic avian influenza viruses (HPAIV) of subtypes H5 and H7 have caused numerous outbreaks in diverse poultry species and rising numbers of human infections. Both HPAIV subtypes support a growing concern of a pandemic outbreak, spe- cifically via the avian-human link. Natural reassortment of both HPAIV subtypes is a possible event with unpredictable outcome for virulence and host specificity of the progeny virus for avian and mammalian species. NS reassortment of H5N1 HPAIV vi- ruses in the background of A/FPV/Rostock/1934 (H7N1) HPAIV has been shown to change virus replication kinetics and host cell responses in mammalian cells. However, not much is known about the virus-host interaction of such viruses in avian species. In the present study, we show that the NS segment of A/Vietnam/1203/2004 (FPV NS VN, H5N1) HPAIV significantly altered the characteristics of the H7 prototype HPAIV in tracheal organ cultures (TOC) of chicken and turkey in vitro, with decreased repli- cation efficiency accompanied by increased induction of type I interferon (IFN) and apoptosis. Furthermore, species-specific differences between chicken and turkey were demonstrated. Interestingly, NS-reassortant FPV NS VN showed an overall highly pathogenic phenotype, with increased virulence and replication potential compared to the wild-type virus after systemic infec- tion of chicken and turkey embryos. Our data demonstrate that single reassortment of an H5-type NS into an H7-type HPAIV significantly changed virus replication abilities and influenced the avian host cell response without prior adaptation.
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Human rhinoviruses: coming in from the cold

Human rhinoviruses: coming in from the cold

Although HRVs have increasingly become thought of as a single viral supergroup, now residing alongside their cousins in the genus Enterovirus, there may be important, discriminating antigenic, immunogenic, epidemic, clinical [20,46] and now genomic features that support the treat- ment of some strains, clades or species as discrete viral entities, deserving targeted antiviral interventions and virological, clinical and epidemiological characterization [21]. The rhinoviruses, known for decades, but often considered less of a public health and research priority than other viruses, may at last be facing the modern molecular, epidemiological and clinical research onslaught due such an intriguing group of pathogens.
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Training host pathogen protein–protein interaction predictors

Training host pathogen protein–protein interaction predictors

Detection of protein-protein interactions (PPIs) plays a vital role in molecular biology. Particularly, pathogenic infections are caused by interactions of host and pathogen proteins. It is important to identify host-pathogen interactions (HPIs) to discover new drugs to counter infectious diseases. Conventional wet lab PPI detection techniques have limitations in terms of cost and large-scale application. Hence, computational approaches are developed to predict PPIs. This study aims to develop machine learning models to predict inter-species PPIs with a special interest HPIs. Specifically, we focus on seeking answers to three questions that arise while developing an HPI predictor: 1) How should negative training examples be selected? 2) Does assigning sample weights to individual negative examples based on their similarity to positive examples improve generalization performance? and, 3) What should be the size of negative samples as compared to the positive samples during training and evaluation? We compare two available methods for negative sampling: random vs. de novo sampling and our experiments show that de novo sampling offers better accuracy. However, our experiments also show that generalization performance can be improved further by using a soft de novo approach that assigns sample weights to negative examples inversely proportional to their similarity to known positive examples during training. Based on our findings, we have also developed an HPI predictor called HOPITOR (Host-Pathogen Interaction Predictor) that can predict interactions between human and viral proteins. The HOPITOR web server can be accessed at the URL: http://faculty.pieas.edu.pk/fayyaz/software.html#HoPItor.
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Managing Early Aspects Interaction

Managing Early Aspects Interaction

So we can reason about concerns (base and aspect) as a use case that each of them specifies a set of condition. Then requirement of any concern (scenario, step of scenario) has to satisfy their first level conditions (concern level). And could refine their concern conditions or could add specific requirement conditions that relate to specific requirements. Finally, each of analysis unit inherits all conditions of concerns and requirement that implement. Conditions specified on analysis artifact then have to refine the previous level constraints and specify them based on the units involved to each concern and requirement. For example let suppose that A1, A2 two aspect concern that crosscut the Base concern (B). in concern level it is specified that A1 and A2 has to be weaved before the base B a constraint of priority has be identified ( A1 prior than A2). Then we can refine in requirement level to specify for example all requirement off aspect A1 are prior to all requirement of aspect A2 and in last in analysis artifact we specify that method invocation which start A1 execution ( is captured as advice) is prior than the method invocation that start execution of A 2 . This is the simpler case of interaction other complex case can occur.
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Host-vector interaction in dengue: a simple mathematical model

Host-vector interaction in dengue: a simple mathematical model

Similarly, the first term of (2) accounts for the interaction between infected humans and healthy mosquitoes in transferring the infection to the mosquitoes and b is the biting r[r]

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Antiviral Effects of Pyrrolidine Dithiocarbamate on Human Rhinoviruses

Antiviral Effects of Pyrrolidine Dithiocarbamate on Human Rhinoviruses

that readily kill normal mice (63). However, NF-␬B activation is not essential for virus multiplication in cell culture but is required for the inhibition of apoptosis and for prevention of premature cell death, thus affecting virulence in mice (60). In contrast, no significant apoptosis and/or cell death was de- tected when NF-␬B activation by HRV was inhibited by PDTC treatment (Fig. 10D and F). PDTC was also shown to be involved in activation of pleiotropic transcription factors, e.g., AP-1 (41), transactivator C/EBP␤ (9), and heat shock factor 1 (29). Activation of genes regulated by these factors may ac- count for the stimulatory effect of PDTC on uninfected cells as observed in our experiments. Another biological property of PDTC is its activity as a chelator of Zn and Cu (42, 43). As many enzymatic functions are dependent on essential ions, chelation of these ions could lead to inhibition of enzyme function.
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COMPUTATIONAL BINDING STUDIES FOR HOST-GUEST INTERACTION OF MOSCS

COMPUTATIONAL BINDING STUDIES FOR HOST-GUEST INTERACTION OF MOSCS

(e.g. aspirin) non-covalently binding to the building blocks of MOSCs can be determined. ESP maps allow us to predict possible binding sites on host molecules. Specifically, we were testing the hypothesis that negatively charged sites of the host preferentially bind with positively charged sites of guest, which accounts for the experimentally observed binding selectivity. 6c In addition, the strongest adsorption on both sulfonylcalix[4]arene and the tetranuclear complex is observed for two configurations: ϕ=ϴ=180˚, d=3 Å, and ϕ=180˚, ϴ=0˚, d=3 Å.
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Mothers and infants : early interaction and consequences

Mothers and infants : early interaction and consequences

Permission is given for a copy to be downloaded by an individual for the purpose of research and private study only.. The thesis may not be reproduced elsewhere without the permission of[r]

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Adaptive immunity to rhinoviruses: sex and age matter

Adaptive immunity to rhinoviruses: sex and age matter

PBMC were isolated from heparinised blood by density gradient centrifugation as previously described [11], and cultured at 1 × 10 6 PBMC in 24 well culture plates at a final concentration of 2 × 10 6 cells per/ml together with RV16 at a multiplicity of infection (MOI) of one; i.e. one virion per cell. Control cultures contained medium alone. RPMI media was supplemented with antibiotics, 2-mercaptoethanol and either 10% foetal calf serum (FCS; innate immune studies) or 5% autologous plasma (adaptive immune studies). Extensive comparative experiments showed that both FCS and autologous plasma supplemented media induced identical innate immune responses, though autologous plasma was pre- ferred for adaptive immune studies in order to minimise foreign antigen exposure and because autologous plasma supplemented media was associated with consistently higher adaptive IFNg synthesis (data not shown). The experiments that required depletion of antigen experi- enced/memory T cells from PBMC were performed using CD45R0+ immuno-magnetic beads (Miltenyi Bio- tech), according to the manufacturer’s directions. Cul- tures were incubated at 37°C with 5% CO 2 and
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Colonization Induced Host Gut Microbial Metabolic Interaction

Colonization Induced Host Gut Microbial Metabolic Interaction

In this context, we characterized in a previous study the meta- bolic phenotypes of germfree and conventional C3H mice to serve as a basis for the following studies on the same germfree mouse model. We demonstrated that the microbiota status affects the systemic metabolism of the host, modulating the metabolic fin- gerprint of topographically remote organs such as the liver and the kidney (6). Here, we explore the adaptive mechanisms of gut col- onization by microbiota using a similar systems biology approach in the same mouse strain. In addition to the nuclear magnetic resonance (NMR)-based metabolic profiling of the animals, as performed in the previous work, we also monitored here the gut microbial establishment by 16S rRNA gene pyrosequencing in or- der to review the composition of the microbial ecosystem simul- taneously with the modifications of the host metabolism induced by the colonization process. In particular, we focused our atten- tion on the evolution of liver metabolism, where important mod- ifications of energy metabolism in conjunction with changes in the expression level of cytochrome P450 (CYP) involved in bile acid and drug detoxification pathways were observed in response to the colonization process. We also highlight a strong correlation between microbial families, such as the Coriobacteriaceae (includ- ing the genus Eggerthella), and both the hepatic concentrations of glucose, glycogen, and triglycerides and the activity of Cyp3a11, one of the most active cytochromes in drug metabolism in the mouse.
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