The Transcriptomics to Proteomics of Hair Cell Regeneration: Looking for a Hair Cell in a Haystack.

Michael E Smith, Gopinath Rajadinakaran
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引用次数: 6

Abstract

Mature mammals exhibit very limited capacity for regeneration of auditory hair cells, while all non-mammalian vertebrates examined can regenerate them. In an effort to find therapeutic targets for deafness and balance disorders, scientists have examined gene expression patterns in auditory tissues under different developmental and experimental conditions. Microarray technology has allowed the large-scale study of gene expression profiles (transcriptomics) at whole-genome levels, but since mRNA expression does not necessarily correlate with protein expression, other methods, such as microRNA analysis and proteomics, are needed to better understand the process of hair cell regeneration. These technologies and some of the results of them are discussed in this review. Although there is a considerable amount of variability found between studies owing to different species, tissues and treatments, there is some concordance between cellular pathways important for hair cell regeneration. Since gene expression and proteomics data is now commonly submitted to centralized online databases, meta-analyses of these data may provide a better picture of pathways that are common to the process of hair cell regeneration and lead to potential therapeutics. Indeed, some of the proteins found to be regulated in the inner ear of animal models (e.g., IGF-1) have now gone through human clinical trials.

Abstract Image

毛细胞再生的转录组学到蛋白质组学:在大海捞针中寻找毛细胞。
成熟哺乳动物的听觉毛细胞再生能力非常有限,而所有非哺乳动物的脊椎动物都可以再生。为了寻找耳聋和平衡障碍的治疗靶点,科学家们研究了不同发育和实验条件下听觉组织的基因表达模式。微阵列技术允许在全基因组水平上对基因表达谱(转录组学)进行大规模研究,但由于mRNA表达不一定与蛋白质表达相关,因此需要其他方法,如microRNA分析和蛋白质组学,以更好地了解毛细胞再生过程。本文就这些技术及其取得的一些成果作一综述。尽管由于不同的物种、组织和处理,研究之间存在相当大的差异,但在毛细胞再生的重要细胞途径之间存在一些一致性。由于基因表达和蛋白质组学数据现在通常提交给集中的在线数据库,因此对这些数据进行荟萃分析可能会更好地了解毛细胞再生过程中常见的途径,并导致潜在的治疗方法。事实上,在动物模型的内耳中发现的一些被调节的蛋白质(例如,IGF-1)现在已经通过了人体临床试验。
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来源期刊
自引率
0.00%
发文量
0
审稿时长
11 weeks
期刊介绍: High-Throughput (formerly Microarrays, ISSN 2076-3905) is a multidisciplinary peer-reviewed scientific journal that provides an advanced forum for the publication of studies reporting high-dimensional approaches and developments in Life Sciences, Chemistry and related fields. Our aim is to encourage scientists to publish their experimental and theoretical results based on high-throughput techniques as well as computational and statistical tools for data analysis and interpretation. The full experimental or methodological details must be provided so that the results can be reproduced. There is no restriction on the length of the papers. High-Throughput invites submissions covering several topics, including, but not limited to: Microarrays, DNA Sequencing, RNA Sequencing, Protein Identification and Quantification, Cell-based Approaches, Omics Technologies, Imaging, Bioinformatics, Computational Biology/Chemistry, Statistics, Integrative Omics, Drug Discovery and Development, Microfluidics, Lab-on-a-chip, Data Mining, Databases, Multiplex Assays.
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