EpiSurf: metadata-driven search server for analyzing amino acid changes within epitopes of SARS-CoV-2 and other viral species

Bernasconi, Anna; Cilibrasi, Luca; Khalaf, Ruba Al; Alfonsi, Tommaso; Ceri, Stefano; Pinoli, Pietro; Canakoglu, Arif

doi:10.1093/database/baab059

Cited by 13 publications

(12 citation statements)

References 33 publications

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“…The VCM focuses on such structuring function for the purposes of characterizing viral genomic sequences. The model has already being successfully used for designing several search and visualization systems [14][15][16] and has been linked to a Phenotype Data Dictionary [17] and a knowledge base of SARS-CoV-2 mutations' impacts [18,19]. A broader application and adoption of the VCM within the context of virology research (by both life science domain experts and information systems' developers), however, requires that a more ontology-oriented approach is embraced, allowing the unambiguous identification of entities in the context of heterogeneous information.…”

Section: Introductionmentioning

confidence: 99%

Semantic interoperability: ontological unpacking of a viral conceptual model

2022

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Background Genomics and virology are unquestionably important, but complex, domains being investigated by a large number of scientists. The need to facilitate and support work within these domains requires sharing of databases, although it is often difficult to do so because of the different ways in which data is represented across the databases. To foster semantic interoperability, models are needed that provide a deep understanding and interpretation of the concepts in a domain, so that the data can be consistently interpreted among researchers. Results In this research, we propose the use of conceptual models to support semantic interoperability among databases and assess their ontological clarity to support their effective use. This modeling effort is illustrated by its application to the Viral Conceptual Model (VCM) that captures and represents the sequencing of viruses, inspired by the need to understand the genomic aspects of the virus responsible for COVID-19. For achieving semantic clarity on the VCM, we leverage the “ontological unpacking” method, a process of ontological analysis that reveals the ontological foundation of the information that is represented in a conceptual model. This is accomplished by applying the stereotypes of the OntoUML ontology-driven conceptual modeling language.As a result, we propose a new OntoVCM, an ontologically grounded model, based on the initial VCM, but with guaranteed interoperability among the data sources that employ it. Conclusions We propose and illustrate how the unpacking of the Viral Conceptual Model resolves several issues related to semantic interoperability, the importance of which is recognized by the “I” in FAIR principles. The research addresses conceptual uncertainty within the domain of SARS-CoV-2 data and knowledge.The method employed provides the basis for further analyses of complex models currently used in life science applications, but lacking ontological grounding, subsequently hindering the interoperability needed for scientists to progress their research.

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Section: Introductionmentioning

confidence: 99%

Semantic interoperability: ontological unpacking of a viral conceptual model

2022

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“…CCP is the only antibody therapy that keeps up with the variants since every variant elicits a response that neutralizes it during convalescence: Not by chance the fold‐reductions in neutralization ability of CCP are usually below 10‐fold, while for monoclonal antibodies are often higher than 100‐fold. In particular, the recently recognized Omicron VOC, with its huge mutation load disrupting Spike conformation and evading most monoclonal antibody therapies developed to date [21, 22], is a serious quest for polyclonal therapies.…”

Section: Figurementioning

confidence: 99%

Are convalescent plasma stocks collected during former COVID‐19 waves still effective against current SARS‐CoV‐2 variants?

Focosi¹,

Franchini

Joyner

et al. 2022

Vox Sanguinis

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COVID-19 convalescent plasma (CCP) was among the few frontline therapies used to treat COVID-19. After large randomized controlled trials (RCTs) relying on late use in hospitalized patients and/or low antibody titres failed to meet their predefined primary endpoint, the infectious disease community reduced usage of CCP in favour of monoclonal antibodies. Consequently, there are CCP stocks at most transfusion centres worldwide, although scattered usage continues. Further, better designed RCTs are also being launched. The urgent question here is: should we use CCP units collected months before given the largely changed viral variant landscape? We review here in vitro evidence that discourages usage of such CCP units against Delta and other variants of concern. CCP collections should be continued in order to update the armamentarium of therapeutics against vaccine breakthrough infections or in unvaccinated patients and is especially relevant in next-generation RCTs.

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“…Different conditions can be built on the presence of specific mutational patterns (predicating on either nucleotides or amino acid residues). EpiSurf and EpiSurf-GISAID [10] are companion systems for analyzing sequences mutations in the context of specific viral genomic regions, i.e., epitopes. Epitopes, extracted from the Immune Epitope Database (https://www.iedb.org/, last accessed 26 January, 2022), are strings of amino acid residues from a virus protein that can be recognized by antibodies or other host's receptors.…”

Section: Introductionmentioning

confidence: 99%

Interoperability of COVID-19 Clinical Phenotype Data with Host and Viral Genetics Data

Bernasconi

Ceri

2022

BioMed

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The outbreak of the COVID-19 epidemic has focused enormous attention on the genetics of viral infection and related disease. Since the beginning of the pandemic, we focused on the collection and integration of SARS-CoV-2 databases, which contain information on the structure of the virus and on its ability to spread, mutate, and evolve; data are made available from several open-source databases. In the past, we gathered experience on human genomics data by building models and integrated databases of genomic datasets (representing, e.g., mutations, gene expression profiles, epigenetic signals). We also coordinated the development of a data dictionary describing the clinical phenotype of the COVID19 disease, in the context of a very large consortium. The main objective of this paper is to describe the content of the data dictionary and the process of data collection and organization. We also argue that—in the context of the COVID-19 disease—interoperability between the three domains of viral genomics, clinical phenotype, and human host genomics is essential for empowering important analysis processes and results. We call for actions that could be performed to link these data.

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EpiSurf: metadata-driven search server for analyzing amino acid changes within epitopes of SARS-CoV-2 and other viral species

Cited by 13 publications

References 33 publications

Semantic interoperability: ontological unpacking of a viral conceptual model

Semantic interoperability: ontological unpacking of a viral conceptual model

Are convalescent plasma stocks collected during former COVID‐19 waves still effective against current SARS‐CoV‐2 variants?

Interoperability of COVID-19 Clinical Phenotype Data with Host and Viral Genetics Data

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