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当前位置: Science » 技术 » Science Advances:瑞士学者发表提高测序准确性方法

Science Advances:瑞士学者发表提高测序准确性方法

摘要 : 3月9日,国际顶尖学术期刊《Science》旗下《Science Advances》杂志上在线发表瑞士苏黎世联邦理工学院的研究人员Sai T. Reddy开发了确保测序质量的有效方法,并在此基础上获得了全面且准确的抗体图谱。

 3月9日,国际顶尖学术期刊《Science》旗下《Science Advances》杂志上在线发表瑞士苏黎世联邦理工学院的研究人员Sai T. Reddy开发了确保测序质量的有效方法,并在此基础上获得了全面且准确的抗体图谱。

为了跟踪免疫系统激活后的抗体生成情况,研究人员对携带抗体生产指令的mRNA进行了测序分析。“近年来测序技术取得了很大的进展,测序速度显著加快,测序成本大幅下降。然而目前的测序方法并不适合分析抗体RNA,”领导这项研究的Sai Reddy教授解释道。机体产生的抗体种类非常多,测序抗体RNA需要很高的灵敏性和准确性。

Reddy及其同事创建了一个使用基因条码的控制系统,对RNA测序进行补充和完善。这个系统与计算机分析结合起来,大大提升了RNA测序的精确性,消除了人为引入突变和RNA分子相对浓度的干扰。“通过这种方式我们能够去除超过98%的测序错误,”Reddy实验室的博士后Tarik Khan说。

研究人员将自己开发的体系命名为分子扩增指纹(MAF)。他们在PCR扩增之前给每个RNA分子随机打上独一无二的“条码”。他们还在扩增过程中添加另一种条码,以记录PCR扩增的偏好。计算机分析可以通过这些条码将原始抗体RNA与测序中发生突变的分子区分开,还能够确定抗体RNA原本所占的比例。

这项研究为人们展示的抗体测序方法,适合多种免疫学研究。Reddy正在与多家制药公司合作,把这一方法用于抗体药物和疫苗的开发。“我们的技术可以精确反映HIV感染者体内的免疫应答过程,”Reddy教授指出。“过去人们只能发现免疫应答中丰度较高的抗体,测序可以准确快速的鉴定那些罕见抗体。”蛋白质分析需要抗体达到较高的浓度,无法检测疾病早期产生的少量抗体分子。这项研究中的测序方法有望帮助人们尽早诊断出癌症和自身免疫疾病。

原文链接:

Accurate and predictive antibody repertoire profiling by molecular amplification fingerprinting

原文摘要:

High-throughput antibody repertoire sequencing (Ig-seq) provides quantitative molecular information on humoral immunity. However, Ig-seq is compromised by biases and errors introduced during library preparation and sequencing. By using synthetic antibody spike-in genes, we determined that primer bias from multiplex polymerase chain reaction (PCR) library preparation resulted in antibody frequencies with only 42 to 62% accuracy. Additionally, Ig-seq errors resulted in antibody diversity measurements being overestimated by up to 5000-fold. To rectify this, we developed molecular amplification fingerprinting (MAF), which uses unique molecular identifier (UID) tagging before and during multiplex PCR amplification, which enabled tagging of transcripts while accounting for PCR efficiency. Combined with a bioinformatic pipeline, MAF bias correction led to measurements of antibody frequencies with up to 99% accuracy. We also used MAF to correct PCR and sequencing errors, resulting in enhanced accuracy of full-length antibody diversity measurements, achieving 98 to 100% error correction. Using murine MAF-corrected data, we established a quantitative metric of recent clonal expansion—the intraclonal diversity index—which measures the number of unique transcripts associated with an antibody clone. We used this intraclonal diversity index along with antibody frequencies and somatic hypermutation to build a logistic regression model for prediction of the immunological status of clones. The model was able to predict clonal status with high confidence but only when using MAF error and bias corrected Ig-seq data. Improved accuracy by MAF provides the potential to greatly advance Ig-seq and its utility in immunology and biotechnology.

来源: Science Advances 浏览次数:0

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