Rule-based knowledge aggregation for large-scale protein sequence analysis of influenza A viruses

Background: The explosive growth of biological data provides opportunities for new statistical and comparative analyses of large information sets, such as alignments comprising tens of thousands of sequences. In such studies, sequence annotations frequently play an essential role, and reliable results depend on metadata quality. However, the semantic heterogeneity and annotation inconsistencies in biological databases greatly increase the complexity of aggregating and cleaning metadata. Manual curation of datasets, traditionally favoured by life scientists, is impractical for studies involving thousands of records. In this study, we investigate quality issues that affect major public databases, and quantify the effectiveness of an automated metadata extraction approach that combines structural and semantic rules. We applied this approach to more than 90,000 influenza A records, to annotate sequences with protein name, virus subtype, isolate, host, geographic origin, and year of isolation. Results: Over 40,000 annotated Influenza A protein sequences were collected by combining information from more than 90,000 documents from NCBI public databases. Metadata values were automatically extracted, aggregated and reconciled from several document fields by applying user-defined structural rules. For each property, values were recovered from ≥88.8% of records, with accuracy exceeding 96% in most cases. Because of semantic heterogeneity, each property required up to six different structural rules to be combined. Significant quality differences between databases were found: GenBank documents yield values more reliably than documents extracted from GenPept. Using a simple set of semantic rules and a reasoner, we reconstructed relationships between sequences from the same isolate, thus identifying 7640 isolates. Validation of isolate metadata against a simple ontology highlighted more than 400 inconsistencies, leading to over 3,000 property value corrections. Conclusion: To overcome the quality issues inherent in public databases, automated knowledge aggregation with embedded intelligence is needed for large-scale analyses. Our results show that user-controlled intuitive approaches, based on combination of simple rules, can reliably automate various curation tasks, reducing the need for manual corrections to approximately 5% of the records. Emerging semantic technologies possess desirable features to support today's knowledge aggregation tasks, with a potential to bring immediate benefits to this field

Intellectual Property Management Strategies to Accelerate the Development and Access of Vaccines and Diagnostics: Case Studies on Pandemic Influenza, Malaria and SARS

Achieving global access to vaccines, diagnostics, and pharmaceuticals remains a challenge. Throughout the developing world, intellectual property (IP) constraints complicate access to critically essential medical technologies and products. Vaccines for malaria and pandemic strains of influenza, as well as diagnostic and vaccine technologies for SARS, are not only relevant to global public health but are particularly critical to the needs of developing countries. A global access solution is urgently needed. This article offers a timely case‐by‐case analysis of preliminary patent landscape surveys and formulates options via patent pools and other forms of creative IP management to accelerate development and access. The analysis of the feasibility of patent pools reveals several impediments to patent pools: these include antitrust considerations, bargaining difficulties caused by asymmetric interests and asymmetric rights among IP holders (e.g. improvement vs. foundational patents), and the difficulties of securing financial support given the significant transaction costs associated with pools. Because of the above conceptual and operational hurdles, patent pools do not appear to be a feasible way to accelerate development. Other mechanisms, however, can ameliorate IP constraints. For example, a key IP constraint related to pandemic influenza vaccines R&D appears to have been resolved when Medimmune secured the assembly of all relevant reverse genetics IP and pledged broad access. Clearly, the landscape is complex and multidimensional. Licensing systems are not the only issue. Measures must also be taken to limit regulatory hurdles and enable the swift, legal production of pandemic influenza vaccines to meet the needs of developing countries. This is why a comprehensive analysis is so necessary. From a strictly legal perspective, IP systems work through the power to exclude. However, as this study’s exploration and formulation of creative licensing strategies reveals, it is also true that IP can be structured and managed to work through the “power to include.

Protein-protein interactions: network analysis and applications in drug discovery

Physical interactions among proteins constitute the backbone of cellular function, making them an attractive source of therapeutic targets. Although the challenges associated with targeting protein-protein interactions (PPIs) -in particular with small molecules are considerable, a growing number of functional PPI modulators is being reported and clinically evaluated. An essential starting point for PPI inhibitor screening or design projects is the generation of a detailed map of the human interactome and the interactions between human and pathogen proteins. Different routes to produce these biological networks are being combined, including literature curation and computational methods. Experimental approaches to map PPIs mainly rely on the yeast two-hybrid (Y2H) technology, which have recently shown to produce reliable protein networks. However, other genetic and biochemical methods will be essential to increase both coverage and resolution of current protein networks in order to increase their utility towards the identification of novel disease-related proteins and PPIs, and their potential use as therapeutic targets

Aggregation of biological knowledge for immunological and virological applications

Ph.DDOCTOR OF PHILOSOPH

Evolutionarily Conserved Protein Sequences of Influenza A Viruses, Avian and Human, as Vaccine Targets

10.1371/journal.pone.0001190PLoS ONE21

Complete-Proteome Mapping of Human Influenza A Adaptive Mutations: Implications for Human Transmissibility of Zoonotic Strains

BACKGROUND: There is widespread concern that H5N1 avian influenza A viruses will emerge as a pandemic threat, if they become capable of human-to-human (H2H) transmission. Avian strains lack this capability, which suggests that it requires important adaptive mutations. We performed a large-scale comparative analysis of proteins from avian and human strains, to produce a catalogue of mutations associated with H2H transmissibility, and to detect their presence in avian isolates. METHODOLOGY/PRINCIPAL FINDINGS: We constructed a dataset of influenza A protein sequences from 92,343 public database records. Human and avian sequence subsets were compared, using a method based on mutual information, to identify characteristic sites where human isolates present conserved mutations. The resulting catalogue comprises 68 characteristic sites in eight internal proteins. Subtype variability prevented the identification of adaptive mutations in the hemagglutinin and neuraminidase proteins. The high number of sites in the ribonucleoprotein complex suggests interdependence between mutations in multiple proteins. Characteristic sites are often clustered within known functional regions, suggesting their functional roles in cellular processes. By isolating and concatenating characteristic site residues, we defined adaptation signatures, which summarize the adaptive potential of specific isolates. Most adaptive mutations emerged within three decades after the 1918 pandemic, and have remained remarkably stable thereafter. Two lineages with stable internal protein constellations have circulated among humans without reassorting. On the contrary, H5N1 avian and swine viruses reassort frequently, causing both gains and losses of adaptive mutations. CONCLUSIONS: Human host adaptation appears to be complex and systemic, involving nearly all influenza proteins. Adaptation signatures suggest that the ability of H5N1 strains to infect humans is related to the presence of an unusually high number of adaptive mutations. However, these mutations appear unstable, suggesting low pandemic potential of H5N1 in its current form. In addition, adaptation signatures indicate that pandemic H1N1/09 strain possesses multiple human-transmissibility mutations, though not an unusually high number with respect to swine strains that infected humans in the past. Adaptation signatures provide a novel tool for identifying zoonotic strains with the potential to infect humans

The role of influenza neuraminidase transmembrane domain on budding and virus morphology

Influenza A virus neuraminidase (NA), a type II transmembrane glycoprotein plays a role in the cleavage of sialic acids and facilitating the release of mature virions from the surface of infected cells. NA has also previously been shown to play a role in virion formation during influenza A virus budding, although the exact mechanisms by which NA contributes to influenza virion formation and morphology is currently unknown. Previous research has shown that mutations within the transmembrane domain (TMD) of NA can result in alteration in virion morphology, particularly in the production of filament like influenza virions. In this research project we examined if the TMD does indeed play a role in influenza virus budding and morphology. We utilised both full and partial mutations of the TMD of NA from A/WSN/33, a primarily spherical lab adapted influenza strain, with the TMD of a primarily filamentous strain A/California/09. To evaluate the effects of TMD on the morphology of a primarily spherical strain with that of filamentous strain. This study used a transfection based virus like particle (VLP) system to examine the effects of TMD alterations on morphology, utilising various biochemical and microscopy methods. Our findings show that as previously indicated mutations within the TMD do result in alterations to virion morphology, as well as showing that despite previous theories both NA and NA’s TMD may play a more active role in in budding and morphology than previously though

Subgroup Discovery trhough Evolutionary Fuzzy Systems applied to Bioinformatic problems

Subgroup discovery is a descriptive data mining technique using supervised learning. This paper presents a summary about the main properties and elements about subgroup discovery task. In addition, we will focus on the suitability and potential of the search performed by evolutionary algorithms in order to apply in the development of subgroup discovery algorithms, and in the use of fuzzy logic which is a soft computing technique very close to the human reasoning. The hybridisation of both techniques are well known as evolutionary fuzzy system. The most relevant applications of evolutionary fuzzy systems for subgroup discovery in the bioinformatics domains are outlined in this work. Specifically, these algorithms are applied to a problem based on the Influenza A virus and the accute sore throat problem

Virus purification, detection and removal

The biopharmaceutical industry has a growing demand and an increasing need to improve the current virus purification technologies, especially as more and more vaccines are produced from cell-culture derived virus particles. Downstream purification strategies can be expensive and account for 70% of the overall manufacturing costs. The economic pressure and purification processes can be particularly challenging when the virus to be purified is small, as in our model virus, porcine parvovirus (PPV). Our efforts are focused on designing an easy, economical, scalable and efficient system for virus purification, and we focused on aqueous two-phase systems. Industry acceptable standards for virus vaccine recovery can be as low as 30% due to demand of high final titer, virus transduction inhibitors and presence of empty or defective virus capsids as impurities. We have overcome these shortcomings by recovering a high 64% of infectious virus using an aqueous two-phase system. We used high molecular weight polymer and citrate salt to achieve a good yield and eliminated the major contaminant bovine serum albumin. Viruses are also studied for ensuring pure and safe drinking water. Low pressure microfiltrations are continuously being investigated for water filters as they allow high permeate flux and low fouling. Viruses such as PPV are small enough to pass through the microporous membranes. Control of viruses in water is crucial for public health and we have designed an affinity based membrane filter to capture virus. Nanofibers have a high surface to volume ratio providing a highly accessible surface area for virus adsorption. Chitosan an insoluble, biocompatible and biodegradable polymer was used for adsorbing trimer peptide WRW. About 0.2 μmoles of cysteine terminal WRW peptide was conjugated to amine terminal chitosan using maleimide conjugation chemistry. We achieved 90-99% virus removal from water adjusted to a neutral pH. The virus removal from affinity based chitosan was attributed to electrostatic and hydrophobic driven binding effect

A genome-wide CRISPR/Cas9 screen reveals the requirement of host sphingomyelin synthase 1 for infection with Pseudorabies virus mutant gD–Pass

Herpesviruses are large DNA viruses, which encode up to 300 different proteins including enzymes enabling efficient replication. Nevertheless, they depend on a multitude of host cell proteins for successful propagation. To uncover cellular host factors important for replication of pseudorabies virus (PrV), an alphaherpesvirus of swine, we performed an unbiased genome-wide CRISPR/Cas9 forward screen. To this end, a porcine CRISPR-knockout sgRNA library (SsCRISPRko.v1) targeting 20,598 genes was generated and used to transduce porcine kidney cells. Cells were then infected with either wildtype PrV (PrV-Ka) or a PrV mutant (PrV-gD–Pass) lacking the receptor-binding protein gD, which regained infectivity after serial passaging in cell culture. While no cells survived infection with PrV-Ka, resistant cell colonies were observed after infection with PrV-gD–Pass. In these cells, sphingomyelin synthase 1 (SMS1) was identified as the top hit candidate. Infection efficiency was reduced by up to 90% for PrV-gD–Pass in rabbit RK13-sgms1KO cells compared to wildtype cells accompanied by lower viral progeny titers. Exogenous expression of SMS1 partly reverted the entry defect of PrV-gD–Pass. In contrast, infectivity of PrV-Ka was reduced by 50% on the knockout cells, which could not be restored by exogenous expression of SMS1. These data suggest that SMS1 plays a pivotal role for PrV infection, when the gD-mediated entry pathway is blocked