Single-cell analytical technologies: uncovering the mechanisms behind variations in immune responses

Yukie Kashima, Patrick Reteng, Yasuhiko Haga, Junya Yamagishi, Yutaka Suzuki*

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review


The immune landscape varies among individuals. It determines the immune response and results in surprisingly diverse symptoms, even in response to similar external stimuli. However, the detailed mechanisms underlying such diverse immune responses have remained mostly elusive. The utilization of recently developed single-cell multimodal analysis platforms has started to answer this question. Emerging studies have elucidated several molecular networks that may explain diversity with respect to age or other factors. An elaborate interplay between inherent physical conditions and environmental conditions has been demonstrated. Furthermore, the importance of modifications by the epigenome resulting in transcriptome variation among individuals is gradually being revealed. Accordingly, epigenomes and transcriptomes are direct indicators of the medical history and dynamic interactions with environmental factors. Coronavirus disease 2019 (COVID-19) has recently become one of the most remarkable examples of the necessity of in-depth analyses of diverse responses with respect to various factors to improve treatment in severe cases and to prevent viral transmission from asymptomatic carriers. In fact, determining why some patients develop serious symptoms is still a pressing issue. Here, we review the current “state of the art” in single-cell analytical technologies and their broad applications to healthy individuals and representative diseases, including COVID-19.

Original languageEnglish
JournalFEBS Journal
Publication statusAccepted/In press - 9 Sept 2022
Externally publishedYes


  • B cell receptor
  • immune response
  • individual variations
  • influenza vaccination
  • personalized medication
  • SARS-CoV-2 vaccination
  • single-cell analysis
  • T cell receptor


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