What do you mean, Supply Chain Security? A Taxonomy and Framework for Knowledge Sharing

Supply chain security is a hot topic for research, but the specific phrase supply chain security has different definitions for different groups. This paper presents a brief taxonomy for both the terms supply chain and security, and then explores a basic framework to help describe areas of research in supply chain security. Security is broken down into confidentiality, integrity, and availability; supply chain is detailed as the networks, processes, and elements. By creating a method for describing the research, we can begin to create a framework of the research in supply chain security. This framework allows us to see where prior work has been done and allows us to focus on less-explored areas. It also allows us to compare and translate the supply chain research being performed in one field (electronics), to other fields (e.g. food production, clothing manufacturing)

Coupled transcriptome and proteome analysis of human lymphotropic tumor viruses: insights on the detection and discovery of viral genes

<p>Abstract</p> <p>Background</p> <p>Kaposi's sarcoma-associated herpesvirus (KSHV) and Epstein-Barr virus (EBV) are related human tumor viruses that cause primary effusion lymphomas (PEL) and Burkitt's lymphomas (BL), respectively. Viral genes expressed in naturally-infected cancer cells contribute to disease pathogenesis; knowing which viral genes are expressed is critical in understanding how these viruses cause cancer. To evaluate the expression of viral genes, we used high-resolution separation and mass spectrometry coupled with custom tiling arrays to align the viral proteomes and transcriptomes of three PEL and two BL cell lines under latent and lytic culture conditions.</p> <p>Results</p> <p>The majority of viral genes were efficiently detected at the transcript and/or protein level on manipulating the viral life cycle. Overall the correlation of expressed viral proteins and transcripts was highly complementary in both validating and providing orthogonal data with latent/lytic viral gene expression. Our approach also identified novel viral genes in both KSHV and EBV, and extends viral genome annotation. Several previously uncharacterized genes were validated at both transcript and protein levels.</p> <p>Conclusions</p> <p>This systems biology approach coupling proteome and transcriptome measurements provides a comprehensive view of viral gene expression that could not have been attained using each methodology independently. Detection of viral proteins in combination with viral transcripts is a potentially powerful method for establishing virus-disease relationships.</p

COVID19 Disease Map, a computational knowledge repository of virus-host interaction mechanisms.

Funder: Bundesministerium für Bildung und ForschungFunder: Bundesministerium für Bildung und Forschung (BMBF)We need to effectively combine the knowledge from surging literature with complex datasets to propose mechanistic models of SARS-CoV-2 infection, improving data interpretation and predicting key targets of intervention. Here, we describe a large-scale community effort to build an open access, interoperable and computable repository of COVID-19 molecular mechanisms. The COVID-19 Disease Map (C19DMap) is a graphical, interactive representation of disease-relevant molecular mechanisms linking many knowledge sources. Notably, it is a computational resource for graph-based analyses and disease modelling. To this end, we established a framework of tools, platforms and guidelines necessary for a multifaceted community of biocurators, domain experts, bioinformaticians and computational biologists. The diagrams of the C19DMap, curated from the literature, are integrated with relevant interaction and text mining databases. We demonstrate the application of network analysis and modelling approaches by concrete examples to highlight new testable hypotheses. This framework helps to find signatures of SARS-CoV-2 predisposition, treatment response or prioritisation of drug candidates. Such an approach may help deal with new waves of COVID-19 or similar pandemics in the long-term perspective

Sialic Acid on Herpes Simplex Virus Type 1 Envelope Glycoproteins Is Required for Efficient Infection of Cells

Herpes simplex virus type 1 (HSV-1) envelope proteins are posttranslationally modified by the addition of sialic acids to the termini of the glycan side chains. Although gC, gD, and gH are sialylated, it is not known whether sialic acids on these envelope proteins are functionally important. Digestion of sucrose gradient purified virions for 4 h with neuraminidases that remove both α2,3 and α2,6 linked sialic acids reduced titers by 1,000-fold. Digestion with a α2,3-specific neuraminidase had no effect, suggesting that α2,6-linked sialic acids are required for infection. Lectins specific for either α2,3 or α2,6 linkages blocked attachment and infection to the same extent. In addition, the mobility of gH, gB, and gD in sodium dodecyl sulfate-polyacrylamide gel electrophoresis gels was altered by digestion with either α2,3 specific neuraminidase or nonspecific neuraminidases, indicating the presence of both linkages on these proteins. The infectivity of a gC-1-null virus, ΔgC2-3, was reduced to the same extent as wild-type virus after neuraminidase digestion, and attachment was not altered. Neuraminidase digestion of virions resulted in reduced VP16 translocation to the nucleus, suggesting that the block occurred between attachment and entry. These results show for the first time that sialic acids on HSV-1 virions play an important role in infection and suggest that targeting virion sialic acids may be a valid antiviral drug development strategy

Addition of a C-Terminal Cysteine Improves the Anti-Herpes Simplex Virus Activity of a Peptide Containing the Human Immunodeficiency Virus Type 1 TAT Protein Transduction Domain

Previous studies have shown that peptides containing the protein transduction domain (PTD) of the human immunodeficiency virus tat protein (GRKKRRQRRR) were effective inhibitors of herpes simplex virus type 1 (HSV-1) entry (H. Bultmann and C. R. Brandt, J. Biol. Chem. 277:36018-36023, 2002). We now show that the addition of a single cysteine residue to the C terminus of the TAT PTD (TAT-C peptide) improves the antiviral activity against HSV-1 and HSV-2. The principle effect of adding the cysteine was to enable the peptide to inactivate virions and to induce a state of resistance to infection in cells pretreated with peptide. The TAT-C peptide acted extracellularly, immediately blocked entry of adsorbed virus, prevented VP16 translocation to the nucleus, and blocked syncytium formation and cell-cell spread. Thus, TAT-C peptides are fusion inhibitors. The induction of the resistance of cells to infection was rapid, recovered with a half-life of 5 to 6 h, and could be reinduced by peptide treatment. TAT-C bound to heparan sulfate but was a poor competitor for viral attachment. The antiviral activity depended on the net positive charge of the peptide but not on chirality, and a free sulfhydryl group was not essential for antiviral activity because TAT-C dimers were at least as effective as monomers. The unique combination of antiviral activities and low toxicity combine to make TAT-C a strong candidate for further development as a drug to block HSV infection

COVID19 Disease Map, a computational knowledge repository of virus–host interaction mechanisms

We need to effectively combine the knowledge from surging literature with complex datasets to propose mechanistic models of SARS-CoV-2 infection, improving data interpretation and predicting key targets of intervention. Here, we describe a large-scale community effort to build an open access, interoperable and computable repository of COVID-19 molecular mechanisms. The COVID-19 Disease Map (C19DMap) is a graphical, interactive representation of disease-relevant molecular mechanisms linking many knowledge sources. Notably, it is a computational resource for graph-based analyses and disease modelling. To this end, we established a framework of tools, platforms and guidelines necessary for a multifaceted community of biocurators, domain experts, bioinformaticians and computational biologists. The diagrams of the C19DMap, curated from the literature, are integrated with relevant interaction and text mining databases. We demonstrate the application of network analysis and modelling approaches by concrete examples to highlight new testable hypotheses. This framework helps to find signatures of SARS-CoV-2 predisposition, treatment response or prioritisation of drug candidates. Such an approach may help deal with new waves of COVID-19 or similar pandemics in the long-term perspective