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Reviews of "Blood Transcriptomics Analysis Offers Insights into Variant-specific Immune Response to SARS-CoV-2"

Reviewers: R Shankar (Michigan State University) | 📘📘📘📘📘 • A Mentzer (University of Oxford) & B Alamad (University of Oxford) | 📙📙 ◻️◻️◻️

Published onJan 25, 2024
Reviews of "Blood Transcriptomics Analysis Offers Insights into Variant-specific Immune Response to SARS-CoV-2"
key-enterThis Pub is a Review of
Blood transcriptomics analysis offers insights into variant-specific immune response to SARS-CoV-2
Blood transcriptomics analysis offers insights into variant-specific immune response to SARS-CoV-2
Description

Abstract Bulk RNA sequencing (RNA-seq) of blood is typically used for gene expression analysis in biomedical research but is still rarely used in clinical practice. In this study, we argue that RNA-seq should be considered a routine diagnostic tool, as it offers not only insights into aberrant gene expression and splicing but also delivers additional readouts on immune cell type composition as well as B-cell and T-cell receptor (BCR/TCR) repertoires. We demonstrate that RNA-seq offers vital insights into a patient’s immune status via integrative analysis of RNA-seq data from patients infected with various SARS-CoV-2 variants (in total 240 samples with up to 200 million reads sequencing depth). We compare the results of computational cell-type deconvolution methods (e.g., MCP-counter, xCell, EPIC, quanTIseq) to complete blood count data, the current gold standard in clinical practice. We observe varying levels of lymphocyte depletion and significant differences in neutrophil levels between SARS-CoV-2 variants. Additionally, we identify B and T cell receptor (BCR/TCR) sequences using the tools MiXCR and TRUST4 to show that - combined with sequence alignments and pBLAST - they could be used to classify a patient’s disease. Finally, we investigated the sequencing depth required for such analyses and concluded that 10 million reads per sample is sufficient. In conclusion, our study reveals that computational cell-type deconvolution and BCR/TCR methods using bulk RNA-seq analyses can supplement missing CBC data and offer insights into immune responses, disease severity, and pathogen-specific immunity, all achievable with a sequencing depth of 10 million reads per sample.Key Points Computational deconvolution of transcriptomes can estimate immune cell abundances in SARS-CoV-2 patients, supplementing missing CBC data.10 million RNA sequencing reads per sample suffice for analyzing immune responses and disease severity, including BCR/TCR identification.

To read the original manuscript, click the link above.

Summary of Reviews: Both reviewers highlighted the novelty of the proposed deconvolution algorithms and downsampling analysis to simplify bulk RNA-seq data but one reviewer offers criticism on the lack of novelty on the transcriptional patterns found between SARS-CoV-2 positive and seronegative patients. Overall, they both suggest focusing on the  comparison of deconvolution algorithms and exhibit concerns about the practicality of RNA-seq as a routine diagnostic tool due to cost and complexity factors.

Reviewer 1 (Rama S…) | 📘📘📘📘📘

Reviewer 2 (Alex M… & Bana A…) | 📙📙 ◻️◻️◻️

RR:C19 Strength of Evidence Scale Key

📕 ◻️◻️◻️◻️ = Misleading

📙📙 ◻️◻️◻️ = Not Informative

📒📒📒 ◻️◻️ = Potentially Informative

📗📗📗📗◻️ = Reliable

📘📘📘📘📘 = Strong

To read the reviews, click the links below. 

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