Antiviral properties of two trimeric recombinant gp41 proteins

BACKGROUND: As it is the very first step of the HIV replication cycle, HIV entry represents an attractive target for the development of new antiviral drugs. In this context, fusion inhibitors are the third class of anti-HIV drugs to be used for treatment, in combination with nucleoside analogues and antiproteases. But the precise mechanism of HIV fusion mechanism is still unclear. Gp41 ectodomain-derived synthetic peptides represent ideal tools for clarifying this mechanism, in order to design more potent anti-HIV drugs. RESULTS: Two soluble trimeric recombinant gp41 proteins, termed Rgp41B and Rgp41A were designed. Both comprise the N- and C-terminal heptad repeat regions of the ectodomain of HIV-1 gp41, connected by a 7-residue hydrophilic linker, in order to mimic the trimeric fusogenic state of the transmembrane glycoprotein. Both recombinant proteins were found to inhibit HIV-1 entry into target cells in a dose-dependent manner. Rgp41A, the most potent inhibitor, was able to inhibit both X4 and R5 isolates into HeLa cells and primary T lymphocytes. X4 viruses were found to be more susceptible than R5 isolates to inhibition by Rgp41A. In order to elucidate how the trimeric recombinant gp41 protein can interfere with HIV-1 entry into target cells, we further investigated its mode of action. Rgp41A was able to bind gp120 but did not induce gp120-gp41 dissociation. Furthermore, this inhibitor could also interfere with a late step of the fusion process, following the mixing of lipids. CONCLUSION: Taken together, our results suggest that Rgp41A can bind to gp120 and also interfere with a late event of the fusion process. Interestingly, Rgp41A can block membrane fusion without preventing lipid mixing. Although further work will be required to fully understand its mode of action, our results already suggest that Rgp41A can interfere with multiple steps of the HIV entry process

Nonparametric methods for the analysis of single-color pathogen microarrays

<p>Abstract</p> <p>Background</p> <p>The analysis of oligonucleotide microarray data in pathogen surveillance and discovery is a challenging task. Target template concentration, nucleic acid integrity, and host nucleic acid composition can each have a profound effect on signal distribution. Exploratory analysis of fluorescent signal distribution in clinical samples has revealed deviations from normality, suggesting that distribution-free approaches should be applied.</p> <p>Results</p> <p>Positive predictive value and false positive rates were examined to assess the utility of three well-established nonparametric methods for the analysis of viral array hybridization data: (1) Mann-Whitney <it>U</it>, (2) the Spearman correlation coefficient and (3) the chi-square test. Of the three tests, the chi-square proved most useful.</p> <p>Conclusions</p> <p>The acceptance of microarray use for routine clinical diagnostics will require that the technology be accompanied by simple yet reliable analytic methods. We report that our implementation of the chi-square test yielded a combination of low false positive rates and a high degree of predictive accuracy.</p

An Insect Nidovirus Emerging from a Primary Tropical Rainforest

Tropical rainforests show the highest level of terrestrial biodiversity and may be an important contributor to microbial diversity. Exploitation of these ecosystems may foster the emergence of novel pathogens. We report the discovery of the first insect-associated nidovirus, tentatively named Cavally virus (CAVV). CAVV was found with a prevalence of 9.3% during a survey of mosquito-associated viruses along an anthropogenic disturbance gradient in Côte d’Ivoire. Analysis of habitat-specific virus diversity and ancestral state reconstruction demonstrated an origin of CAVV in a pristine rainforest with subsequent spread into agriculture and human settlements. Virus extension from the forest was associated with a decrease in virus diversity (P < 0.01) and an increase in virus prevalence (P < 0.00001). CAVV is an enveloped virus with large surface projections. The RNA genome comprises 20,108 nucleotides with seven major open reading frames (ORFs). ORF1a and -1b encode two large proteins that share essential features with phylogenetically higher representatives of the order Nidovirales, including the families Coronavirinae and Torovirinae, but also with families in a basal phylogenetic relationship, including the families Roniviridae and Arteriviridae. Genetic markers uniquely conserved in nidoviruses, such as an endoribonuclease- and helicase-associated zinc-binding domain, are conserved in CAVV. ORF2a and -2b are predicted to code for structural proteins S and N, respectively, while ORF3a and -3b encode proteins with membrane-spanning regions. CAVV produces three subgenomic mRNAs with 5′ leader sequences (of different lengths) derived from the 5′ end of the genome. This novel cluster of mosquito-associated nidoviruses is likely to represent a novel family within the order Nidovirales

Detection of zoonotic pathogens and characterization of novel viruses carried by commensal Rattus norvegicus in New York City

Norway rats (Rattus norvegicus) are globally distributed and concentrate in urban environments, where they live and feed in closer proximity to human populations than most other mammals. Despite the potential role of rats as reservoirs of zoonotic diseases, the microbial diversity present in urban rat populations remains unexplored. In this study, we used targeted molecular assays to detect known bacterial, viral, and protozoan human pathogens and unbiased high-throughput sequencing to identify novel viruses related to agents of human disease in commensal Norway rats in New York City. We found that these rats are infected with bacterial pathogens known to cause acute or mild gastroenteritis in people, including atypical enteropathogenic Escherichia coli, Clostridium difficile, and Salmonella enterica, as well as infectious agents that have been associated with undifferentiated febrile illnesses, including Bartonella spp., Streptobacillus moniliformis, Leptospira interrogans, and Seoul hantavirus. We also identified a wide range of known and novel viruses from groups that contain important human pathogens, including sapoviruses, cardioviruses, kobuviruses, parechoviruses, rotaviruses, and hepaciviruses. The two novel hepaciviruses discovered in this study replicate in the liver of Norway rats and may have utility in establishing a small animal model of human hepatitis C virus infection. The results of this study demonstrate the diversity of microbes carried by commensal rodent species and highlight the need for improved pathogen surveillance and disease monitoring in urban environments. Importance: The observation that most emerging infectious diseases of humans originate in animal reservoirs has led to wide-scale microbial surveillance and discovery programs in wildlife, particularly in the developing world. Strikingly, less attention has been focused on commensal animals like rats, despite their abundance in urban centers and close proximity to human populations. To begin to explore the zoonotic disease risk posed by urban rat populations, we trapped and surveyed Norway rats collected in New York City over a 1-year period. This analysis revealed a striking diversity of known pathogens and novel viruses in our study population, including multiple agents associated with acute gastroenteritis or febrile illnesses in people. Our findings indicate that urban rats are reservoirs for a vast diversity of microbes that may affect human health and indicate a need for increased surveillance and awareness of the disease risks associated with urban rodent infestation

Novel Borna Virus in Psittacine Birds with Proventricular Dilatation Disease

Pyrosequencing of cDNA from brains of parrots with proventricular dilatation disease (PDD), an unexplained fatal inflammatory central, autonomic, and peripheral nervous system disease, showed 2 strains of a novel Borna virus. Real-time PCR confirmed virus presence in brain, proventriculus, and adrenal gland of 3 birds with PDD but not in 4 unaffected birds

Panmicrobial Oligonucleotide Array for Diagnosis of Infectious Diseases

To facilitate rapid, unbiased, differential diagnosis of infectious diseases, we designed GreeneChipPm, a panmicrobial microarray comprising 29,455 sixty-mer oligonucleotide probes for vertebrate viruses, bacteria, fungi, and parasites. Methods for nucleic acid preparation, random primed PCR amplification, and labeling were optimized to allow the sensitivity required for application with nucleic acid extracted from clinical materials and cultured isolates. Analysis of nasopharyngeal aspirates, blood, urine, and tissue from persons with various infectious diseases confirmed the presence of viruses and bacteria identified by other methods, and implicated Plasmodium falciparum in an unexplained fatal case of hemorrhagic feverlike disease during the Marburg hemorrhagic fever outbreak in Angola in 2004–2005

Detection of Respiratory Viruses and Subtype Identification of Influenza A Viruses by GreeneChipResp Oligonucleotide Microarray

Acute respiratory infections are significant causes of morbidity, mortality, and economic burden worldwide. An accurate, early differential diagnosis may alter individual clinical management as well as facilitate the recognition of outbreaks that have implications for public health. Here we report on the establishment and validation of a comprehensive and sensitive microarray system for detection of respiratory viruses and subtyping of influenza viruses in clinical materials. Implementation of a set of influenza virus enrichment primers facilitated subtyping of influenza A viruses through the differential recognition of hemagglutinins 1 through 16 and neuraminidases 1 through 9. Twenty-one different respiratory virus species were accurately characterized, including a recently identified novel genetic clade of rhinovirus.Fil: Quan, Phenix-Lan. Columbia University. Jerome L. and Dawn Greene Infectious Disease Laboratory; Estados Unidos.Fil: Palacios, Gustavo. Columbia University. Jerome L. and Dawn Greene Infectious Disease Laboratory; Estados Unidos.Fil: Jabado, Omar J. Columbia University. Jerome L. and Dawn Greene Infectious Disease Laboratory; Estados Unidos.Fil: Conlan, Sean. Columbia University. Jerome L. and Dawn Greene Infectious Disease Laboratory; Estados Unidos.Fil: Hirschberg, David L. Stanford School of Medicine; Estados Unidos.Fil: Pozo, Francisco. Instituto de Salud Carlos III. Centro Nacional de Microbiología; España.Fil: Jack, Philippa J. M. Australian Animal Health Laboratory. CSIRO Livestock Industries; Australia.Fil: Cisterna, Daniel. ANLIS Dr.C.G.Malbrán. Instituto Nacional de Enfermedades Infecciosas; Argentina.Fil: Renwick, Neil. Columbia University. Jerome L. and Dawn Greene Infectious Disease Laboratory; Estados Unidos.Fil: Hui, Jeffrey. Columbia University. Jerome L. and Dawn Greene Infectious Disease Laboratory; Estados Unidos.Fil: Drysdale, Andrew. Columbia University. Jerome L. and Dawn Greene Infectious Disease Laboratory; Estados Unidos.Fil: Amos-Ritchie, Rachel. Australian Animal Health Laboratory. CSIRO Livestock Industries; Australia.Fil: Baumeister, Elsa. ANLIS Dr.C.G.Malbrán. Instituto Nacional de Enfermedades Infecciosas; Argentina.Fil: Savy, Vilma. ANLIS Dr.C.G.Malbrán. Instituto Nacional de Enfermedades Infecciosas; Argentina.Fil: Lager, Kelly M. USDA. National Animal Disease Center; Estados Unidos.Fil: Richt, Jürgen A. USDA. National Animal Disease Center; Estados Unidos.Fil: Boyle, David B. Australian Animal Health Laboratory. CSIRO Livestock Industries; Australia.Fil: García-Sastre, Adolfo. Mount Sinai School of Medicine. Department of Microbiology and Emerging Pathogens Institute; Estados Unidos.Fil: Casas, Inmaculada. Instituto de Salud Carlos III. Centro Nacional de Microbiología; España.Fil: Perez-Breña, Pilar. Instituto de Salud Carlos III. Centro Nacional de Microbiología; España.Fil: Briese, Thomas. Columbia University. Jerome L. and Dawn Greene Infectious Disease Laboratory; Estados Unidos.Fil: Lipkin, W. Ian. Columbia University. Jerome L. and Dawn Greene Infectious Disease Laboratory; Estados Unidos

Detection of Respiratory Viruses and Subtype Identification of Influenza A Viruses by GreeneChipResp Oligonucleotide Microarray

Acute respiratory infections are significant causes of morbidity, mortality, and economic burden worldwide. An accurate, early differential diagnosis may alter individual clinical management as well as facilitate the recognition of outbreaks that have implications for public health. Here we report on the establishment and validation of a comprehensive and sensitive microarray system for detection of respiratory viruses and subtyping of influenza viruses in clinical materials. Implementation of a set of influenza virus enrichment primers facilitated subtyping of influenza A viruses through the differential recognition of hemagglutinins 1 through 16 and neuraminidases 1 through 9. Twenty-one different respiratory virus species were accurately characterized, including a recently identified novel genetic clade of rhinovirus.Fil: Quan, Phenix-Lan. Columbia University. Jerome L. and Dawn Greene Infectious Disease Laboratory; Estados Unidos.Fil: Palacios, Gustavo. Columbia University. Jerome L. and Dawn Greene Infectious Disease Laboratory; Estados Unidos.Fil: Jabado, Omar J. Columbia University. Jerome L. and Dawn Greene Infectious Disease Laboratory; Estados Unidos.Fil: Conlan, Sean. Columbia University. Jerome L. and Dawn Greene Infectious Disease Laboratory; Estados Unidos.Fil: Hirschberg, David L. Stanford School of Medicine; Estados Unidos.Fil: Pozo, Francisco. Instituto de Salud Carlos III. Centro Nacional de Microbiología; España.Fil: Jack, Philippa J. M. Australian Animal Health Laboratory. CSIRO Livestock Industries; Australia.Fil: Cisterna, Daniel. ANLIS Dr.C.G.Malbrán. Instituto Nacional de Enfermedades Infecciosas; Argentina.Fil: Renwick, Neil. Columbia University. Jerome L. and Dawn Greene Infectious Disease Laboratory; Estados Unidos.Fil: Hui, Jeffrey. Columbia University. Jerome L. and Dawn Greene Infectious Disease Laboratory; Estados Unidos.Fil: Drysdale, Andrew. Columbia University. Jerome L. and Dawn Greene Infectious Disease Laboratory; Estados Unidos.Fil: Amos-Ritchie, Rachel. Australian Animal Health Laboratory. CSIRO Livestock Industries; Australia.Fil: Baumeister, Elsa. ANLIS Dr.C.G.Malbrán. Instituto Nacional de Enfermedades Infecciosas; Argentina.Fil: Savy, Vilma. ANLIS Dr.C.G.Malbrán. Instituto Nacional de Enfermedades Infecciosas; Argentina.Fil: Lager, Kelly M. USDA. National Animal Disease Center; Estados Unidos.Fil: Richt, Jürgen A. USDA. National Animal Disease Center; Estados Unidos.Fil: Boyle, David B. Australian Animal Health Laboratory. CSIRO Livestock Industries; Australia.Fil: García-Sastre, Adolfo. Mount Sinai School of Medicine. Department of Microbiology and Emerging Pathogens Institute; Estados Unidos.Fil: Casas, Inmaculada. Instituto de Salud Carlos III. Centro Nacional de Microbiología; España.Fil: Perez-Breña, Pilar. Instituto de Salud Carlos III. Centro Nacional de Microbiología; España.Fil: Briese, Thomas. Columbia University. Jerome L. and Dawn Greene Infectious Disease Laboratory; Estados Unidos.Fil: Lipkin, W. Ian. Columbia University. Jerome L. and Dawn Greene Infectious Disease Laboratory; Estados Unidos

Pathosphere.org: pathogen detection and characterization through a web-based, open source informatics platform

Background The detection of pathogens in complex sample backgrounds has been revolutionized by wide access to next-generation sequencing (NGS) platforms. However, analytical methods to support NGS platforms are not as uniformly available. Pathosphere (found at Pathosphere.org) is a cloud - based open - sourced community tool that allows for communication, collaboration and sharing of NGS analytical tools and data amongst scientists working in academia, industry and government. The architecture allows for users to upload data and run available bioinformatics pipelines without the need for onsite processing hardware or technical support. Results The pathogen detection capabilities hosted on Pathosphere were tested by analyzing pathogen-containing samples sequenced by NGS with both spiked human samples as well as human and zoonotic host backgrounds. Pathosphere analytical pipelines developed by Edgewood Chemical Biological Center (ECBC) identified spiked pathogens within a common sample analyzed by 454, Ion Torrent, and Illumina sequencing platforms. ECBC pipelines also correctly identified pathogens in human samples containing arenavirus in addition to animal samples containing flavivirus and coronavirus. These analytical methods were limited in the detection of sequences with limited homology to previous annotations within NCBI databases, such as parvovirus. Utilizing the pipeline-hosting adaptability of Pathosphere, the analytical suite was supplemented by analytical pipelines designed by the United States Army Medical Research Insititute of Infectious Diseases and Walter Reed Army Institute of Research (USAMRIID-WRAIR). These pipelines were implemented and detected parvovirus sequence in the sample that the ECBC iterative analysis previously failed to identify. Conclusions By accurately detecting pathogens in a variety of samples, this work demonstrates the utility of Pathosphere and provides a platform for utilizing, modifying and creating pipelines for a variety of NGS technologies developed to detect pathogens in complex sample backgrounds. These results serve as an exhibition for the existing pipelines and web-based interface of Pathosphere as well as the plug-in adaptability that allows for integration of newer NGS analytical software as it becomes available