Multiomic technologies for analyses of inborn errors of immunity: from snapshot of the average cell to dynamic temporal picture at single-cell resolution.

IF 5 3区 医学 Q2 IMMUNOLOGY Inflammation and Regeneration Pub Date : 2021-07-01 DOI:10.1186/s41232-021-00169-4
Yusuke Kawashima, Ryuta Nishikomori, Osamu Ohara
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Abstract

Advances in DNA sequencing technology have significantly impacted human genetics; they have enabled the analysis of genetic causes of rare diseases, which are usually pathogenic variants in a single gene at the nucleotide sequence level. However, since the quantity of data regarding the relationship between genotype and phenotype is insufficient to diagnose some rare immune diseases definitively, genetic information alone cannot help obtain a mechanistic understanding of the disease etiology. For such cases, exploring the molecular phenotype using multiomic analyses could be the approach of choice. In this review, we first overview current technologies for multiomic analysis, particularly focusing on RNA and protein profiling of bulk cell ensembles. We then discuss the measurement modality and granularity issue because it is critical to design multiomic experiments properly. Next, we illustrate the importance of bioimaging by describing our experience with the analysis of an autoinflammatory disease, cryopyrin-associated periodic fever syndrome, which could be caused by low-frequency somatic mosaicism and cannot be well characterized only by multiomic snapshot analyses of an ensemble of many immune cells. We found it powerful to complement the multiomic data with bioimaging data that can provide us with indispensable time-specific dynamic information of every single cell in the "immune cell society." Because we now have many measurement tools in different modalities and granularity to tackle the etiology of rare hereditary immune diseases, we might gain a deeper understanding of the pathogenic mechanisms of these diseases by taking full advantage of these tools in an integrated manner.

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用于分析先天性免疫错误的多组学技术:从平均细胞快照到单细胞分辨率的动态时间图像。
DNA 测序技术的进步对人类遗传学产生了重大影响,使人们能够分析罕见疾病的遗传原因,这些原因通常是单个基因在核苷酸序列水平上的致病变异。然而,由于有关基因型和表型之间关系的数据量不足以明确诊断某些罕见免疫疾病,因此仅靠遗传信息无助于从机理上了解疾病的病因。在这种情况下,利用多组学分析探索分子表型可能是首选方法。在这篇综述中,我们首先概述了当前的多组学分析技术,尤其侧重于体细胞组合的 RNA 和蛋白质分析。然后,我们讨论测量模式和粒度问题,因为这对正确设计多组学实验至关重要。接下来,我们将介绍分析自身炎症性疾病--冰冻蛋白相关周期性发热综合征的经验,以此说明生物成像的重要性。这种疾病可能是由低频体细胞嵌合引起的,仅对许多免疫细胞的集合进行多组学快照分析无法很好地描述其特征。我们发现用生物成像数据来补充多组学数据非常有用,因为生物成像数据可以为我们提供 "免疫细胞社会 "中每个单细胞不可或缺的特定时间动态信息。由于我们现在拥有多种不同模式和粒度的测量工具来解决罕见遗传性免疫疾病的病因问题,因此,通过综合利用这些工具,我们可能会对这些疾病的致病机制有更深入的了解。
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来源期刊
CiteScore
11.10
自引率
1.20%
发文量
45
审稿时长
11 weeks
期刊介绍: Inflammation and Regeneration is the official journal of the Japanese Society of Inflammation and Regeneration (JSIR). This journal provides an open access forum which covers a wide range of scientific topics in the basic and clinical researches on inflammation and regenerative medicine. It also covers investigations of infectious diseases, including COVID-19 and other emerging infectious diseases, which involve the inflammatory responses. Inflammation and Regeneration publishes papers in the following categories: research article, note, rapid communication, case report, review and clinical drug evaluation.
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