About: Dynamics of B-cell repertoires and emergence of cross-reactive responses in COVID-19 patients with different disease severity

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About: Dynamics of B-cell repertoires and emergence of cross-reactive responses in COVID-19 patients with different disease severity Goto Sponge NotDistinct Permalink

An Entity of Type : schema:ScholarlyArticle, within Data Space : wasabi.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Dynamics of B-cell repertoires and emergence of cross-reactive responses in COVID-19 patients with different disease severity
Creator	Lv, Huibin Peiris, J Wilson, Ian Wu, Nicholas Tak, Owen Tsang, Yin Yip, Garrick Yuan, Meng Ka, Chris Mok, Pun Isacchini, Giulio Liu, Hejun Montague, Zachary Ng, Wilson Nourmohammad, Armita Otwinowski, Jakub Dewitt, William
Source	MedRxiv; Medline; PMC
abstract	COVID-19 patients show varying severity of the disease ranging from asymptomatic to requiring intensive care. Although a number of monoclonal antibodies against SARS-CoV-2 have been identified, we still lack an understanding of the overall landscape of B-cell receptor (BCR) repertoires in COVID-19 patients. Here, we used high-throughput sequencing of BCR repertoires collected over multiple time points during an infection to characterize statistical and dynamical signatures of the B-cell response to SARS-CoV-2 in 19 patients with different disease severities. Based on principled statistical approaches, we determined differential sequence features of BCRs associated with different disease severity. We identified 34 significantly expanded rare clonal lineages shared among patients as candidates for a specific response to SARS-CoV-2. Moreover, we identified natural emergence of a BCR with cross-reactivity to SARS-CoV and SARS-CoV-2 in a number of patients. Overall, our results provide important insights for development of rational therapies and vaccines against COVID-19.
has issue date	2020-07-15(xsd:dateTime)
bibo:doi	10.1101/2020.07.13.20153114
bibo:pmid	32699862
has license	cc-by-nc-nd
sha1sum (hex)	5edd0b8d2e4aad4927bef804dbfa08a73527ac0a
schema:url	https://doi.org/10.1101/2020.07.13.20153114
resource representing a document's title	Dynamics of B-cell repertoires and emergence of cross-reactive responses in COVID-19 patients with different disease severity
has PubMed Central identifier	PMC7373151
has PubMed identifier	32699862
schema:publication	medRxiv
resource representing a document's body	covid:5edd0b8d2e4aad4927bef804dbfa08a73527ac0a#body_text
is schema:about of	named entity 'high-throughput sequencing' named entity 'patients' named entity 'specific' named entity 'infection' named entity 'responses' named entity 'DIFFERENT' named entity 'SEVERITY' named entity 'sequence' named entity 'SARS-CoV-2' named entity 'intensive care' named entity 'development' named entity 'patients' named entity 'B-cell receptor' named entity 'intensive care' named entity 'Bcell' named entity 'B-cell' named entity 'COVID-19' named entity 'false discovery rate' named entity 'mAbs' named entity 'BCR' named entity 'recombination' named entity 'GenBank' named entity 'BCR' named entity 'BCR' named entity 'SARS-CoV-2' named entity 'sample size' named entity 'Hamming distance' named entity 'probability' named entity 'heavy chain' named entity 'SARS-CoV-2' named entity 'SONIA' named entity 'stop codons' named entity 'COVID' named entity 'BCR' named entity 'dashed' named entity 'primer' named entity 'antibody' named entity 'probability' named entity 'SARS-CoV-2' named entity 'mRNA' named entity 'cysteine' named entity 'antibodies in the blood' named entity 'medRxiv' named entity 'probability' named entity 'COVID' named entity 'p-value' named entity 'Hong Kong West Cluster' named entity 'dashed' named entity 'PCR' named entity 'gene' named entity 'nucleoprotein' named entity 'medRxiv' named entity 'infection' named entity 'Pall Corporation' named entity 'molecular mechanism' named entity 'paratope' named entity 'medRxiv' named entity 'probability' named entity 'infectious diseases' named entity 'clusterable' named entity 'human plasma' named entity 'single-linkage clustering' named entity 'COVID-19' named entity 'complementarity-determining regions' named entity 'RBD'

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