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Article ; Online: Heterogeneity in IgG-CD16 signaling in infectious disease outcomes.

Gonzalez, Joseph C / Chakraborty, Saborni / Thulin, Natalie K / Wang, Taia T

2022 Volume 309, Issue 1, Page(s) 64–74

Abstract: In this review, we discuss how IgG antibodies can modulate inflammatory signaling during viral infections with a focus on CD16a-mediated functions. We describe the structural heterogeneity of IgG antibody ligands, including subclass and glycosylation ... ...

Abstract	In this review, we discuss how IgG antibodies can modulate inflammatory signaling during viral infections with a focus on CD16a-mediated functions. We describe the structural heterogeneity of IgG antibody ligands, including subclass and glycosylation that impact binding by and downstream activity of CD16a, as well as the heterogeneity of CD16a itself, including allele and expression density. While inflammation is a mechanism required for immune homeostasis and resolution of acute infections, we focus here on two infectious diseases that are driven by pathogenic inflammatory responses during infection. Specifically, we review and discuss the evolving body of literature showing that afucosylated IgG immune complex signaling through CD16a contributes to the overwhelming inflammatory response that is central to the pathogenesis of severe forms of dengue disease and coronavirus disease 2019 (COVID-19).
MeSH term(s)	COVID-19 ; Communicable Diseases ; Humans ; Immunoglobulin G/chemistry ; Immunoglobulin G/metabolism ; Polysaccharides/chemistry ; Polysaccharides/metabolism ; Receptors, IgG
Chemical Substances	Immunoglobulin G ; Polysaccharides ; Receptors, IgG
Language	English
Publishing date	2022-07-03
Publishing country	England
Document type	Journal Article ; Review ; Research Support, N.I.H., Extramural
ZDB-ID	391796-4
ISSN	1600-065X ; 0105-2896
ISSN (online)	1600-065X
ISSN	0105-2896
DOI	10.1111/imr.13109
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Article ; Online: SARS-CoV-2 vaccines in advanced clinical trials: Where do we stand?

Chakraborty, Saborni / Mallajosyula, Vamsee / Tato, Cristina M / Tan, Gene S / Wang, Taia T

Advanced drug delivery reviews

2021 Volume 172, Page(s) 314–338

Abstract: The ongoing SARS-CoV-2 pandemic has led to the focused application of resources and scientific expertise toward the goal of developing investigational vaccines to prevent COVID-19. The highly collaborative global efforts by private industry, governments ... ...

Abstract	The ongoing SARS-CoV-2 pandemic has led to the focused application of resources and scientific expertise toward the goal of developing investigational vaccines to prevent COVID-19. The highly collaborative global efforts by private industry, governments and non-governmental organizations have resulted in a number of SARS-CoV-2 vaccine candidates moving to Phase III trials in a period of only months since the start of the pandemic. In this review, we provide an overview of the preclinical and clinical data on SARS-CoV-2 vaccines that are currently in Phase III clinical trials and in few cases authorized for emergency use. We further discuss relevant vaccine platforms and provide a discussion of SARS-CoV-2 antigens that may be targeted to increase the breadth and durability of vaccine responses.
MeSH term(s)	Animals ; COVID-19/epidemiology ; COVID-19/immunology ; COVID-19/prevention & control ; COVID-19 Vaccines/administration & dosage ; COVID-19 Vaccines/chemistry ; COVID-19 Vaccines/immunology ; Clinical Trials, Phase III as Topic/methods ; Drug Evaluation, Preclinical/methods ; Drug Evaluation, Preclinical/trends ; Humans ; Protein Structure, Secondary ; Protein Structure, Tertiary ; SARS-CoV-2/chemistry ; SARS-CoV-2/drug effects ; SARS-CoV-2/immunology
Chemical Substances	COVID-19 Vaccines
Language	English
Publishing date	2021-01-20
Publishing country	Netherlands
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't ; Review
ZDB-ID	639113-8
ISSN	1872-8294 ; 0169-409X
ISSN (online)	1872-8294
ISSN	0169-409X
DOI	10.1016/j.addr.2021.01.014
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Article ; Online: CD8

Mallajosyula, Vamsee / Ganjavi, Conner / Chakraborty, Saborni / McSween, Alana M / Pavlovitch-Bedzyk, Ana Jimena / Wilhelmy, Julie / Nau, Allison / Manohar, Monali / Nadeau, Kari C / Davis, Mark M

Science immunology

2022 Volume 6, Issue 61

Abstract: A central feature of the SARS-CoV-2 pandemic is that some individuals become severely ill or die, whereas others have only a mild disease course or are asymptomatic. Here we report development of an improved multimeric αβ T cell staining reagent platform, ...

Abstract	A central feature of the SARS-CoV-2 pandemic is that some individuals become severely ill or die, whereas others have only a mild disease course or are asymptomatic. Here we report development of an improved multimeric αβ T cell staining reagent platform, with each maxi-ferritin "spheromer" displaying 12 peptide-MHC complexes. Spheromers stain specific T cells more efficiently than peptide-MHC tetramers and capture a broader portion of the sequence repertoire for a given peptide-MHC. Analyzing the response in unexposed individuals, we find that T cells recognizing peptides conserved amongst coronaviruses are more abundant and tend to have a "memory" phenotype, compared to those unique to SARS-CoV-2. Significantly, CD8
MeSH term(s)	CD8-Positive T-Lymphocytes/immunology ; CD8-Positive T-Lymphocytes/pathology ; COVID-19/immunology ; COVID-19/pathology ; Epitopes, T-Lymphocyte/immunology ; Female ; Humans ; Male ; SARS-CoV-2/immunology ; Severity of Illness Index
Chemical Substances	Epitopes, T-Lymphocyte
Language	English
Publishing date	2022-08-12
Publishing country	United States
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
ISSN	2470-9468
ISSN (online)	2470-9468
DOI	10.1126/sciimmunol.abg5669
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Article ; Online: TNF-α

Cell reports. Medicine

2022 Volume 3, Issue 6, Page(s) 100640

Abstract: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-specific ... ...

Abstract	Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-specific CD4
MeSH term(s)	Antibodies, Neutralizing ; CD4-Positive T-Lymphocytes ; COVID-19 ; Humans ; Outpatients ; SARS-CoV-2 ; T-Lymphocytes ; Tumor Necrosis Factor-alpha
Chemical Substances	Antibodies, Neutralizing ; Tumor Necrosis Factor-alpha
Language	English
Publishing date	2022-05-03
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't ; Research Support, N.I.H., Extramural
ISSN	2666-3791
ISSN (online)	2666-3791
DOI	10.1016/j.xcrm.2022.100640
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Article: Differential Peripheral Blood Glycoprotein Profiles in Symptomatic and Asymptomatic COVID-19

Pickering, Chad / Zhou, Bo / Xu, Gege / Rice, Rachel / Ramachandran, Prasanna / Huang, Hector / Pham, Tho D. / Schapiro, Jeffrey M. / Cong, Xin / Chakraborty, Saborni / Edwards, Karlie / Reddy, Srinivasa T. / Guirgis, Faheem / Wang, Taia T. / Serie, Daniel / Lindpaintner, Klaus

Viruses. 2022 Mar. 07, v. 14, no. 3

2022

Abstract: Glycosylation is the most common form of post-translational modification of proteins, critically affecting their structure and function. Using liquid chromatography and mass spectrometry for high-resolution site-specific quantification of glycopeptides ... ...

Abstract	Glycosylation is the most common form of post-translational modification of proteins, critically affecting their structure and function. Using liquid chromatography and mass spectrometry for high-resolution site-specific quantification of glycopeptides coupled with high-throughput artificial intelligence-powered data processing, we analyzed differential protein glycoisoform distributions of 597 abundant serum glycopeptides and nonglycosylated peptides in 50 individuals who had been seriously ill with COVID-19 and in 22 individuals who had recovered after an asymptomatic course of COVID-19. As additional comparison reference phenotypes, we included 12 individuals with a history of infection with a common cold coronavirus, 16 patients with bacterial sepsis, and 15 healthy subjects without history of coronavirus exposure. We found statistically significant differences, at FDR < 0.05, for normalized abundances of 374 of the 597 peptides and glycopeptides interrogated between symptomatic and asymptomatic COVID-19 patients. Similar statistically significant differences were seen when comparing symptomatic COVID-19 patients to healthy controls (350 differentially abundant peptides and glycopeptides) and common cold coronavirus seropositive subjects (353 differentially abundant peptides and glycopeptides). Among healthy controls and sepsis patients, 326 peptides and glycopeptides were found to be differentially abundant, of which 277 overlapped with biomarkers that showed differential expression between symptomatic COVID-19 cases and healthy controls. Among symptomatic COVID-19 cases and sepsis patients, 101 glycopeptide and peptide biomarkers were found to be statistically significantly abundant. Using both supervised and unsupervised machine learning techniques, we found specific glycoprotein profiles to be strongly predictive of symptomatic COVID-19 infection. LASSO-regularized multivariable logistic regression and K-means clustering yielded accuracies of 100% in an independent test set and of 96% overall, respectively. Our findings are consistent with the interpretation that a majority of glycoprotein modifications observed which are shared among symptomatic COVID-19 and sepsis patients likely represent a generic consequence of a severe systemic immune and inflammatory state. However, there are glycoisoform changes that are specific and particular to severe COVID-19 infection. These may be representative of either COVID-19-specific consequences or susceptibility to or predisposition for a severe course of the disease. Our findings support the potential value of glycoproteomic biomarkers in the biomedical understanding and, potentially, the clinical management of serious acute infectious conditions.
Keywords	COVID-19 infection ; Orthocoronavirinae ; biomarkers ; blood serum ; common cold ; gene expression regulation ; glycopeptides ; glycoproteins ; glycosylation ; liquid chromatography ; mass spectrometry ; regression analysis ; seroprevalence
Language	English
Dates of publication	2022-0307
Publishing place	Multidisciplinary Digital Publishing Institute
Document type	Article
ZDB-ID	2516098-9
ISSN	1999-4915
ISSN	1999-4915
DOI	10.3390/v14030553
Database	NAL-Catalogue (AGRICOLA)

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Article ; Online: Differential Peripheral Blood Glycoprotein Profiles in Symptomatic and Asymptomatic COVID-19.

Pickering, Chad / Zhou, Bo / Xu, Gege / Rice, Rachel / Ramachandran, Prasanna / Huang, Hector / Pham, Tho D / Schapiro, Jeffrey M / Cong, Xin / Chakraborty, Saborni / Edwards, Karlie / Reddy, Srinivasa T / Guirgis, Faheem / Wang, Taia T / Serie, Daniel / Lindpaintner, Klaus

Viruses

2022 Volume 14, Issue 3

Abstract	Glycosylation is the most common form of post-translational modification of proteins, critically affecting their structure and function. Using liquid chromatography and mass spectrometry for high-resolution site-specific quantification of glycopeptides coupled with high-throughput artificial intelligence-powered data processing, we analyzed differential protein glycoisoform distributions of 597 abundant serum glycopeptides and nonglycosylated peptides in 50 individuals who had been seriously ill with COVID-19 and in 22 individuals who had recovered after an asymptomatic course of COVID-19. As additional comparison reference phenotypes, we included 12 individuals with a history of infection with a common cold coronavirus, 16 patients with bacterial sepsis, and 15 healthy subjects without history of coronavirus exposure. We found statistically significant differences, at FDR < 0.05, for normalized abundances of 374 of the 597 peptides and glycopeptides interrogated between symptomatic and asymptomatic COVID-19 patients. Similar statistically significant differences were seen when comparing symptomatic COVID-19 patients to healthy controls (350 differentially abundant peptides and glycopeptides) and common cold coronavirus seropositive subjects (353 differentially abundant peptides and glycopeptides). Among healthy controls and sepsis patients, 326 peptides and glycopeptides were found to be differentially abundant, of which 277 overlapped with biomarkers that showed differential expression between symptomatic COVID-19 cases and healthy controls. Among symptomatic COVID-19 cases and sepsis patients, 101 glycopeptide and peptide biomarkers were found to be statistically significantly abundant. Using both supervised and unsupervised machine learning techniques, we found specific glycoprotein profiles to be strongly predictive of symptomatic COVID-19 infection. LASSO-regularized multivariable logistic regression and K-means clustering yielded accuracies of 100% in an independent test set and of 96% overall, respectively. Our findings are consistent with the interpretation that a majority of glycoprotein modifications observed which are shared among symptomatic COVID-19 and sepsis patients likely represent a generic consequence of a severe systemic immune and inflammatory state. However, there are glycoisoform changes that are specific and particular to severe COVID-19 infection. These may be representative of either COVID-19-specific consequences or susceptibility to or predisposition for a severe course of the disease. Our findings support the potential value of glycoproteomic biomarkers in the biomedical understanding and, potentially, the clinical management of serious acute infectious conditions.
MeSH term(s)	Artificial Intelligence ; COVID-19/diagnosis ; Chromatography, Liquid/methods ; Glycopeptides/analysis ; Glycopeptides/chemistry ; Glycopeptides/metabolism ; Glycoproteins ; Humans
Chemical Substances	Glycopeptides ; Glycoproteins
Language	English
Publishing date	2022-03-07
Publishing country	Switzerland
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
ZDB-ID	2516098-9
ISSN	1999-4915 ; 1999-4915
ISSN (online)	1999-4915
ISSN	1999-4915
DOI	10.3390/v14030553
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Article: Early immune responses have long-term associations with clinical, virologic, and immunologic outcomes in patients with COVID-19.

Research square

2022

Abstract: The great majority of SARS-CoV-2 infections are mild and uncomplicated, but some individuals with initially mild COVID-19 progressively develop more severe symptoms. Furthermore, there is substantial heterogeneity in SARS-CoV-2-specific memory immune ... ...

Abstract	The great majority of SARS-CoV-2 infections are mild and uncomplicated, but some individuals with initially mild COVID-19 progressively develop more severe symptoms. Furthermore, there is substantial heterogeneity in SARS-CoV-2-specific memory immune responses following infection. There remains a critical need to identify host immune biomarkers predictive of clinical and immunologic outcomes in SARS-CoV-2-infected patients. Leveraging longitudinal samples and data from a clinical trial in SARS-CoV-2 infected outpatients, we used host proteomics and transcriptomics to characterize the trajectory of the immune response in COVID-19 patients within the first 2 weeks of symptom onset. We identify early immune signatures, including plasma RIG-I levels, early interferon signaling, and related cytokines (CXCL10, MCP1, MCP-2 and MCP-3) associated with subsequent disease progression, control of viral shedding, and the SARS-CoV-2 specific T cell and antibody response measured up to 7 months after enrollment. We found that several biomarkers for immunological outcomes are shared between individuals receiving BNT162b2 (Pfizer-BioNTech) vaccine and COVID-19 patients. Finally, we demonstrate that machine learning models using 7-10 plasma protein markers measured early within the course of infection are able to accurately predict disease progression, T cell memory, and the antibody response post-infection in a second, independent dataset.
Language	English
Publishing date	2022-02-02
Publishing country	United States
Document type	Preprint
DOI	10.21203/rs.3.rs-847082/v1
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Article ; Online: Antibodies elicited by SARS-CoV-2 infection or mRNA vaccines have reduced neutralizing activity against Beta and Omicron pseudoviruses.

Science translational medicine

2022 Volume 14, Issue 634, Page(s) eabn7842

Abstract: Multiple severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants that have mutations associated with increased transmission and antibody escape have arisen over the course of the current pandemic. Although the current vaccines have largely ... ...

Abstract	Multiple severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants that have mutations associated with increased transmission and antibody escape have arisen over the course of the current pandemic. Although the current vaccines have largely been effective against past variants, the number of mutations found on the Omicron (B.1.1.529) spike protein appear to diminish the protection conferred by preexisting immunity. Using vesicular stomatitis virus (VSV) pseudoparticles expressing the spike protein of several SARS-CoV-2 variants, we evaluated the magnitude and breadth of the neutralizing antibody response over time in individuals after infection and in mRNA-vaccinated individuals. We observed that boosting increases the magnitude of the antibody response to wild-type (D614), Beta, Delta, and Omicron variants; however, the Omicron variant was the most resistant to neutralization. We further observed that vaccinated healthy adults had robust and broad antibody responses, whereas responses may have been reduced in vaccinated pregnant women, underscoring the importance of learning how to maximize mRNA vaccine responses in pregnant populations. Findings from this study show substantial heterogeneity in the magnitude and breadth of responses after infection and mRNA vaccination and may support the addition of more conserved viral antigens to existing SARS-CoV-2 vaccines.
MeSH term(s)	Adult ; Antibodies, Neutralizing/immunology ; Antibodies, Viral/immunology ; COVID-19/immunology ; COVID-19/prevention & control ; COVID-19/virology ; COVID-19 Vaccines/immunology ; Female ; Humans ; Pregnancy ; Pregnancy Complications, Infectious/immunology ; Pregnancy Complications, Infectious/prevention & control ; Pregnancy Complications, Infectious/virology ; SARS-CoV-2/immunology ; Spike Glycoprotein, Coronavirus/immunology ; Vaccines, Synthetic/immunology ; mRNA Vaccines/immunology
Chemical Substances	Antibodies, Neutralizing ; Antibodies, Viral ; COVID-19 Vaccines ; Spike Glycoprotein, Coronavirus ; Vaccines, Synthetic ; mRNA Vaccines ; spike protein, SARS-CoV-2
Language	English
Publishing date	2022-03-02
Publishing country	United States
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
ZDB-ID	2518854-9
ISSN	1946-6242 ; 1946-6234
ISSN (online)	1946-6242
ISSN	1946-6234
DOI	10.1126/scitranslmed.abn7842
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Article ; Online: Differential Peripheral Blood Glycoprotein Profiles in Symptomatic and Asymptomatic COVID-19

Pickering, Chad / Zhou, Bo / Xu, Gege / Rice, Rachel / Huang, Hector / Pham, Tho / Shapiro, Jeffrey / Cong, Xin / Chakraborty, Saborni / Edwards, Karlie / Reddy, Srinavasa / Giurgis, Faheem / Wang, Taia T. / Serie, Daniel / Lindpaintner, Klaus

medRxiv

Abstract	Glycosylation is the most common form of post-translational modification of proteins, critically affecting their structure and function. Using liquid chromatography and mass spectrometry for high-resolution site-specific quantification of glycopeptides coupled with high-throughput artificial intelligence-powered data processing, we analyzed differential protein glyco-isoform distributions of 597 abundant serum glycopeptides and non-glycosylated peptides in 50 individuals who had been seriously ill with COVID-19 and in 22 individuals who had recovered after an asymptomatic course of COVID-19. As additional comparison reference phenotypes, we included 12 individuals with a history of infection with a common cold coronavirus, 16 patients with bacterial sepsis, and 15 healthy subjects without history of coronavirus exposure. We found statistically significant differences, at FDR<0.05, for normalized abundances of 374 of the 597 peptides and glycopeptides interrogated, between symptomatic and asymptomatic COVID-19 patients. Similar statistically significant differences were seen when comparing symptomatic COVID-19 patients to healthy controls (350 differentially abundant peptides and glycopeptides) and common cold coronavirus seropositive subjects (353 differentially abundant peptides and glycopeptides). Among healthy controls and sepsis patients, 326 peptides and glycopeptides were found to be differentially abundant, of which 277 overlapped with biomarkers that showed differential expression between symptomatic COVID-19 cases and healthy controls. Among symptomatic COVID-19 cases and sepsis patients, 101 glycopeptide and peptide biomarkers were found to be statistically significantly abundant. Using both supervised and unsupervised machine learning techniques, we found specific glycoprotein profiles to be strongly predictive of symptomatic COVID-19 infection. LASSO-regularized multivariable logistic regression and K-means clustering yielded accuracies of 100% in an independent test set and of 96% overall, respectively. Our findings are consistent with the interpretation that a majority of glycoprotein modifications observed which are shared among symptomatic COVID-19 and sepsis patients likely represent a generic consequence of a severe systemic immune and inflammatory state. However, there are glyco-isoform changes that are specific and particular to severe COVID-19 infection. These may be representative of either COVID-19-specific consequences or of susceptibility to or predisposition for a severe course of the disease. Our findings support the potential value of glycoproteomic biomarkers in the biomedical understanding, and, potentially, the clinical management of serious acute infectious conditions.
Keywords	covid19
Language	English
Publishing date	2022-01-08
Publisher	Cold Spring Harbor Laboratory Press
Document type	Article ; Online
DOI	10.1101/2022.01.07.21267956
Database	COVID19

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Article ; Online: Early immune markers of clinical, virological, and immunological outcomes in patients with COVID-19: a multi-omics study.

Hu, Zicheng / van der Ploeg, Kattria / Chakraborty, Saborni / Arunachalam, Prabhu S / Mori, Diego A M / Jacobson, Karen B / Bonilla, Hector / Parsonnet, Julie / Andrews, Jason R / Holubar, Marisa / Subramanian, Aruna / Khosla, Chaitan / Maldonado, Yvonne / Hedlin, Haley / de la Parte, Lauren / Press, Kathleen / Ty, Maureen / Tan, Gene S / Blish, Catherine /

Takahashi, Saki / Rodriguez-Barraquer, Isabel / Greenhouse, Bryan / Butte, Atul J / Singh, Upinder / Pulendran, Bali / Wang, Taia T / Jagannathan, Prasanna

eLife

2022 Volume 11

Abstract: Background: The great majority of severe acute respiratory syndrome-related coronavirus 2 (SARS-CoV-2) infections are mild and uncomplicated, but some individuals with initially mild COVID-19 progressively develop more severe symptoms. Furthermore, ... ...

Abstract	Background: The great majority of severe acute respiratory syndrome-related coronavirus 2 (SARS-CoV-2) infections are mild and uncomplicated, but some individuals with initially mild COVID-19 progressively develop more severe symptoms. Furthermore, there is substantial heterogeneity in SARS-CoV-2-specific memory immune responses following infection. There remains a critical need to identify host immune biomarkers predictive of clinical and immunological outcomes in SARS-CoV-2-infected patients. Methods: Leveraging longitudinal samples and data from a clinical trial (N=108) in SARS-CoV-2-infected outpatients, we used host proteomics and transcriptomics to characterize the trajectory of the immune response in COVID-19 patients. We characterized the association between early immune markers and subsequent disease progression, control of viral shedding, and SARS-CoV-2-specific T cell and antibody responses measured up to 7 months after enrollment. We further compared associations between early immune markers and subsequent T cell and antibody responses following natural infection with those following mRNA vaccination. We developed machine-learning models to predict patient outcomes and validated the predictive model using data from 54 individuals enrolled in an independent clinical trial. Results: We identify early immune signatures, including plasma RIG-I levels, early IFN signaling, and related cytokines (CXCL10, MCP1, MCP-2, and MCP-3) associated with subsequent disease progression, control of viral shedding, and the SARS-CoV-2-specific T cell and antibody response measured up to 7 months after enrollment. We found that several biomarkers for immunological outcomes are shared between individuals receiving BNT162b2 (Pfizer-BioNTech) vaccine and COVID-19 patients. Finally, we demonstrate that machine-learning models using 2-7 plasma protein markers measured early within the course of infection are able to accurately predict disease progression, T cell memory, and the antibody response post-infection in a second, independent dataset. Conclusions: Early immune signatures following infection can accurately predict clinical and immunological outcomes in outpatients with COVID-19 using validated machine-learning models. Funding: Support for the study was provided from National Institute of Health/National Institute of Allergy and Infectious Diseases (NIH/NIAID) (U01 AI150741-01S1 and T32-AI052073), the Stanford's Innovative Medicines Accelerator, National Institutes of Health/National Institute on Drug Abuse (NIH/NIDA) DP1DA046089, and anonymous donors to Stanford University. Peginterferon lambda provided by Eiger BioPharmaceuticals.
MeSH term(s)	Humans ; Antibodies, Viral ; Biomarkers ; BNT162 Vaccine ; COVID-19 ; Cytokines/metabolism ; Disease Progression ; RNA, Messenger ; SARS-CoV-2 ; Clinical Trials as Topic
Chemical Substances	Antibodies, Viral ; Biomarkers ; BNT162 Vaccine ; Cytokines ; RNA, Messenger
Language	English
Publishing date	2022-10-14
Publishing country	England
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
ZDB-ID	2687154-3
ISSN	2050-084X ; 2050-084X
ISSN (online)	2050-084X
ISSN	2050-084X
DOI	10.7554/eLife.77943
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