国自然申报卷创新？DRUG-seq2技术藏着N大应用，还能牵手AI放大招！

2026年国自然申报指南新鲜出炉，又到了拼创新的时刻！想让课题脱颖而出？DRUG-seq2技术来助力啦！它不仅能搞定药物筛选、靶点发现、中药解析等多个科研场景，还能和AI强强联手，智能预测药物活性、评估毒性。低样本量、高通量的优势拉满，妥妥的国自然申报加分利器。下面的文档可以直接“抄作业”。

DRUG-seq2简介

DRUG-seq2是一种针对少量细胞高通量的批量化转录组测序方法。该方法通过将特定的Barcode序列引入到反转录引物中作为cDNA第一链的反转录引物——即标记cDNA，测序后可根据不同的Barcode序列进行孔板拆分，可以做到孔板之间几乎0污染。同时由于随机UMI的加入，可以根据UMI是否相同，以识别其原始转录本的来源，提升了样本的平行性和数据的准确性。检测基因数达到10000-12000个。与传统的RNA-seq相比，该方法需要的细胞数量只需要1000个以上，样本用量降低100-1000倍，支持稀有细胞、类器官或高价值药物扰动样本分析。并且无需提取RNA，操作便捷，单次实验样本通量提升4倍以上，满足大规模药物筛选的需求。

DRUG-seq工作原理图（Nature Communications  2018）

技术特色

（1）操作便捷，无需提取RNA；

（2）节约细胞，每个孔1000个以上细胞就可以，类器官样本适配；

（3）批量化建库，通量高，96/384体系均可；

（4）产生多维度、高精准度的转录组数据。

应用拓展

参考文献&发表文章情况

（1）2018年诺华公司技术开发：Ye C et al. DRUG-seq for miniaturized high-throughput transcriptome profiling in drug discovery. Nat Commun. 2018；

（2）昕瑞再生开发技术并应用：Li J, et al. Transcriptome-based chemical screens identify CDK8 as a common barrier in multiple cell reprogramming systems. Cell Rep. 2023

（3）临床样本应用：Zuo W et al. The persistence of SARS-CoV-2 in tissues and its association with long COVID symptoms: a cross-sectional cohort study in China. Lancet Infect Dis. 2024

（4）中药筛选应用：Quality and composition control of complex TCM preparations through a novel "Herbs-in vivo Compounds-Targets-Pathways" network methodology: The case of Lianhuaqingwen capsules. Pharmacol Res. 2025

（5）构建完类器官做药筛：Generation of iPSC-derived human venous endothelial cells for the modeling of vascular malformations and drug discovery. Cell Stem Cell. 2025 

（6）细胞命运重编程体系分化：Li, S. et al. Chemical reprogramming of fibroblasts into retinal pigment epithelium cells for vision restoration. Nat Commun 2025

文章撰写关于DRUG-seq2供稿

DRUG-seq2 data were processed to obtain expression matrix of gene counts according to drop-seq analysis protocol (https://github.com/broadinstitute/Drop-seq). Briefly, reads for each well were split through 10-base well and 10-base plate barcodes and then mapped to the human transcriptome with the GRCh38 reference index and Ensembl gene references by STAR.39 The unique alignments were further demultiplexed based on the transcript UMI for each gene. The UMIs of each gene were counted as its raw counts. CPM (counts of exon model per million mapped reads) matrix was transferred from the raw count matrix and used for hierarchical clustering, cluster heatmap, and PCA analysis,Our method for normalization with VST (default): first, use loess to fit a straight line to log (variance) and log (mean), then use the observed mean and expected variance to normalize the gene expression, and finally calculate the variance according to the normalized expression with the largest reservation.

DRUG-seq2 experiments were conducted by Plastech Pharmaceutical Technology Co. LTD with a reported protocol (Li et al. 2023).

联系方式

官网：www.xremed.com

南京昕瑞再生医药科技有限公司

官方技术支持

关于昕瑞再生

南京昕瑞再生医药科技有限公司成立于2019年，先后获中科创星、红杉资本两轮融资，依托北京大学分子医学南京转化研究院软硬件支持。公司核心团队源自北京大学，承载创始团队在干细胞、再生医学及小分子创新药领域20余年经验，搭建了世界领先的细胞表型药筛平台——整合细胞疾病模型、表型组学定量、AI技术，聚焦“细胞疾病/衰老表型逆转”研发新药。

公司拥有自主知识产权的DRUG-seq2、PHDs-seq高通量测序技术，已在早期药物开发、靶点发现、人工智能大模型建立等场景见效，既服务自研项目，也为科研领域提供高质量技术解决方案。