PlateletSeq: A novel method for discovery of blood-based biomarkers

IF 4.2 3区 生物学 Q1 BIOCHEMICAL RESEARCH METHODS
Ryan J. Collinson , Darren Boey , Lynne Wilson , Zi Yun Ng , Bob Mirzai , Hun Chuah , Michael F. Leahy , Rebecca Howman , Matthew Linden , Kathy Fuller , Wendy N. Erber , Belinda B. Guo
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Abstract

Platelets are small circulating fragments of cells that play important roles in thrombosis, haemostasis, immune response, inflammation and cancer growth. Although anucleate, they contain a rich RNA repertoire which offers an opportunity to characterise changes in platelet gene expression in health and disease. Whilst this can be achieved with conventional RNA sequencing, a large input of high-quality RNA, and hence blood volume, is required (unless a pre-amplification step is added), along with specialist bioinformatic skills for data analysis and interpretation. We have developed a transcriptomics next-generation sequencing-based approach that overcomes these limitations. Termed PlateletSeq, this method requires very low levels of RNA input and does not require specialist bioinformatic analytical skills. Here we describe the methodology, from sample collection to processing and data analysis. Specifically, blood samples can be stored for up to 8 days at 4 °C prior to analysis. Platelets are isolated using multi-step centrifugation and a purity of ≤ 1 leucocyte per 0.26x106 platelets is optimal for gene expression analysis. We have applied PlateletSeq to normal adult blood samples and show there are no age-associated variations and only minor gender-associated differences. In contrast, platelets from patients with myeloproliferative neoplasms show differences in platelet transcript profiles from normal and between disease subtypes. This illustrates the potential applicability of PlateletSeq for biomarker discovery and studying platelet biology in patient samples. It also opens avenues for assessing platelet quality in other fields such as transfusion research.

血小板序列:一种发现基于血液的生物标志物的新方法。
血小板是细胞的小循环片段,在血栓形成、止血、免疫反应、炎症和癌症生长中发挥重要作用。尽管无核,但它们含有丰富的RNA库,这为表征健康和疾病中血小板基因表达的变化提供了机会。虽然这可以通过传统的RNA测序来实现,但需要大量输入高质量的RNA,因此需要大量的血容量(除非添加了预扩增步骤),以及用于数据分析和解释的专业生物信息学技能。我们开发了一种基于转录组学的下一代测序方法,克服了这些限制。这种方法被称为血小板序列,需要非常低水平的RNA输入,不需要专业的生物信息学分析技能。在这里,我们描述了从样本收集到处理和数据分析的方法。具体而言,在分析之前,血液样本可以在4°C下储存长达8天。使用多步离心分离血小板,并且6个血小板的纯度对于基因表达分析是最佳的。我们将血小板序列应用于正常成人血液样本,结果显示没有年龄相关的变化,只有轻微的性别相关差异。相反,骨髓增生性肿瘤患者的血小板在正常和不同疾病亚型的血小板转录谱上存在差异。这说明了血小板序列在患者样本中发现生物标志物和研究血小板生物学方面的潜在适用性。它还为在输血研究等其他领域评估血小板质量开辟了途径。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Methods
Methods 生物-生化研究方法
CiteScore
9.80
自引率
2.10%
发文量
222
审稿时长
11.3 weeks
期刊介绍: Methods focuses on rapidly developing techniques in the experimental biological and medical sciences. Each topical issue, organized by a guest editor who is an expert in the area covered, consists solely of invited quality articles by specialist authors, many of them reviews. Issues are devoted to specific technical approaches with emphasis on clear detailed descriptions of protocols that allow them to be reproduced easily. The background information provided enables researchers to understand the principles underlying the methods; other helpful sections include comparisons of alternative methods giving the advantages and disadvantages of particular methods, guidance on avoiding potential pitfalls, and suggestions for troubleshooting.
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