Use of machine learning to identify a T cell response to SARS-CoV-2

Shoukat, M S; Foers, Andrew D; Woodmansey, Stephen; Evans, Shelley; Fowler, Anna; Soilleux, Elizabeth

doi:10.1016/j.xcrm.2021.100192

“…Notably, the fact that younger patients in our cohort had significantly higher CD8-to-CD4 T cell ratios might have contributed to reduced symptom duration relative to older patients. In this context, we predict that methods for the identification of CD8-derived SARS-CoV-2-specific TCRs including functional assays 54,55 and the application of motif clustering 56 or machine learning 57 to TCR repertoire data, as well as methods for the identification of their corresponding epitopes 58,59 will become increasingly important tools for monitoring SARS-CoV-2 immunity.…”

Section: Discussionmentioning

confidence: 99%

A single-cell atlas of lymphocyte adaptive immune repertoires and transcriptomes reveals age-related differences in convalescent COVID-19 patients

Bieberich

¹

,

Vazquez-Lombardi

²

,

Yermanos

³

et al. 2021

Preprint

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COVID-19 disease outcome is highly dependent on adaptive immunity from T and B lymphocytes, which play a critical role in the control, clearance and long-term protection against SARS-CoV-2. To date, there is limited knowledge on the composition of the T and B cell immune receptor repertoires [T cell receptors (TCRs) and B cell receptors (BCRs)] and transcriptomes in convalescent COVID-19 patients of different age groups. Here, we utilize single-cell sequencing (scSeq) of lymphocyte immune repertoires and transcriptomes to quantitatively profile the adaptive immune response in COVID-19 patients of varying age. We discovered highly expanded T and B cells in multiple patients, with the most expanded clonotypes coming from the effector CD8+ T cell population. Highly expanded CD8+ and CD4+ T cell clones show elevated markers of cytotoxicity (CD8: PRF1, GZMH, GNLY; CD4: GZMA), whereas clonally expanded B cells show markers of transition into the plasma cell state and activation across patients. By comparing young and old convalescent COVID-19 patients (mean ages = 31 and 66.8 years, respectively), we found that clonally expanded B cells in young patients were predominantly of the IgA isotype and their BCRs had incurred higher levels of somatic hypermutation than elderly patients. In conclusion, our scSeq analysis defines the adaptive immune repertoire and transcriptome in convalescent COVID-19 patients and shows important age-related differences implicated in immunity against SARS-CoV-2.

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“…Notably, the fact that younger patients in our cohort had significantly higher CD8-to-CD4 T cell ratios might have contributed to reduced symptom duration relative to older patients. In this context, we predict that methods for the identification of CD8-derived SARS-CoV-2-specific TCRs including functional assays ( 57 , 58 ) and the application of motif clustering ( 59 ) or machine learning ( 60 ) to TCR repertoire data, as well as methods for the identification of their corresponding epitopes ( 61 , 62 ) will become increasingly important tools for monitoring SARS-CoV-2 immunity.…”

Section: Discussionmentioning

confidence: 99%

A Single-Cell Atlas of Lymphocyte Adaptive Immune Repertoires and Transcriptomes Reveals Age-Related Differences in Convalescent COVID-19 Patients

Bieberich

¹

,

Vazquez-Lombardi

²

,

Yermanos

³

et al. 2021

View full text Add to dashboard Cite

COVID-19 disease outcome is highly dependent on adaptive immunity from T and B lymphocytes, which play a critical role in the control, clearance and long-term protection against SARS-CoV-2. To date, there is limited knowledge on the composition of the T and B cell immune receptor repertoires [T cell receptors (TCRs) and B cell receptors (BCRs)] and transcriptomes in convalescent COVID-19 patients of different age groups. Here, we utilize single-cell sequencing (scSeq) of lymphocyte immune repertoires and transcriptomes to quantitatively profile the adaptive immune response in COVID-19 patients of varying age. We discovered highly expanded T and B cells in multiple patients, with the most expanded clonotypes coming from the effector CD8+ T cell population. Highly expanded CD8+ and CD4+ T cell clones show elevated markers of cytotoxicity (CD8: PRF1, GZMH, GNLY; CD4: GZMA), whereas clonally expanded B cells show markers of transition into the plasma cell state and activation across patients. By comparing young and old convalescent COVID-19 patients (mean ages = 31 and 66.8 years, respectively), we found that clonally expanded B cells in young patients were predominantly of the IgA isotype and their BCRs had incurred higher levels of somatic hypermutation than elderly patients. In conclusion, our scSeq analysis defines the adaptive immune repertoire and transcriptome in convalescent COVID-19 patients and shows important age-related differences implicated in immunity against SARS-CoV-2.

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“…To demonstrate an example usage of the Rep-seq analysis platform, we analysed the antibody repertoires generated in response to Coronavirus disease 2019 (COVID-19), which results from infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Since the start of the COVID-19 outbreak, many studies have been conducted to discover SARS-CoV-2-neutralizing antibodies (39) and to characterize the convergent signatures of T and B cell receptor repertoires for diagnosis and therapy (40,41). We downloaded five Rep-seq datasets containing B cell receptor repertoires from COVID-19 patients from the NCBI SRA database (SRR12190252, SRR12190293, SRR12326739, SRR13518454, SRR13518456) and compared their features to those of 32 references whose Rep-seq datasets were obtained before the COVID-19 pandemic.…”

Section: Rep-seq Dataset Analysis Platformmentioning

confidence: 99%

RAPID: A Rep-Seq Dataset Analysis Platform With an Integrated Antibody Database

Zhang

¹

,

Chen

²

,

Zeng

³

et al. 2021

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The antibody repertoire is a critical component of the adaptive immune system and is believed to reflect an individual’s immune history and current immune status. Delineating the antibody repertoire has advanced our understanding of humoral immunity, facilitated antibody discovery, and showed great potential for improving the diagnosis and treatment of disease. However, no tool to date has effectively integrated big Rep-seq data and prior knowledge of functional antibodies to elucidate the remarkably diverse antibody repertoire. We developed a Rep-seq dataset Analysis Platform with an Integrated antibody Database (RAPID; https://rapid.zzhlab.org/), a free and web-based tool that allows researchers to process and analyse Rep-seq datasets. RAPID consolidates 521 WHO-recognized therapeutic antibodies, 88,059 antigen- or disease-specific antibodies, and 306 million clones extracted from 2,449 human IGH Rep-seq datasets generated from individuals with 29 different health conditions. RAPID also integrates a standardized Rep-seq dataset analysis pipeline to enable users to upload and analyse their datasets. In the process, users can also select set of existing repertoires for comparison. RAPID automatically annotates clones based on integrated therapeutic and known antibodies, and users can easily query antibodies or repertoires based on sequence or optional keywords. With its powerful analysis functions and rich set of antibody and antibody repertoire information, RAPID will benefit researchers in adaptive immune studies.

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Use of machine learning to identify a T cell response to SARS-CoV-2

Cited by 32 publications

References 19 publications

A single-cell atlas of lymphocyte adaptive immune repertoires and transcriptomes reveals age-related differences in convalescent COVID-19 patients

A single-cell atlas of lymphocyte adaptive immune repertoires and transcriptomes reveals age-related differences in convalescent COVID-19 patients

A Single-Cell Atlas of Lymphocyte Adaptive Immune Repertoires and Transcriptomes Reveals Age-Related Differences in Convalescent COVID-19 Patients

RAPID: A Rep-Seq Dataset Analysis Platform With an Integrated Antibody Database

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