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本文引用的文献

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SCoPE-MS: mass spectrometry of single mammalian cells quantifies proteome heterogeneity during cell differentiation.SCoPE-MS:单细胞哺乳动物细胞的质谱分析定量了细胞分化过程中的蛋白质组异质性。
Genome Biol. 2018 Oct 22;19(1):161. doi: 10.1186/s13059-018-1547-5.
2
Quality control of single amino acid variations detected by tandem mass spectrometry.串联质谱法检测的单个氨基酸变异的质量控制。
J Proteomics. 2018 Sep 15;187:144-151. doi: 10.1016/j.jprot.2018.07.004. Epub 2018 Jul 23.
3
Nanodroplet processing platform for deep and quantitative proteome profiling of 10-100 mammalian cells.用于对10-100个哺乳动物细胞进行深度和定量蛋白质组分析的纳米液滴处理平台。
Nat Commun. 2018 Feb 28;9(1):882. doi: 10.1038/s41467-018-03367-w.
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Large Scale Identification of Variant Proteins in Glioma Stem Cells.大规模鉴定脑肿瘤干细胞中的变异蛋白。
ACS Chem Neurosci. 2018 Jan 17;9(1):73-79. doi: 10.1021/acschemneuro.7b00362. Epub 2017 Dec 21.
5
Proteogenomic analysis prioritises functional single nucleotide variants in cancer samples.蛋白质基因组分析确定癌症样本中功能性单核苷酸变异的优先级。
Oncotarget. 2017 Sep 27;8(56):95841-95852. doi: 10.18632/oncotarget.21339. eCollection 2017 Nov 10.
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Gentle Introduction to the Statistical Foundations of False Discovery Rate in Quantitative Proteomics.定量蛋白质组学中错误发现率统计基础的简要介绍。
J Proteome Res. 2018 Jan 5;17(1):12-22. doi: 10.1021/acs.jproteome.7b00170. Epub 2017 Nov 14.
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Decoding the Effect of Isobaric Substitutions on Identifying Missing Proteins and Variant Peptides in Human Proteome.解码同位取代对鉴定人类蛋白质组中缺失蛋白质和变异肽的影响。
J Proteome Res. 2017 Dec 1;16(12):4415-4424. doi: 10.1021/acs.jproteome.7b00342. Epub 2017 Sep 29.
8
Detecting protein variants by mass spectrometry: a comprehensive study in cancer cell-lines.通过质谱法检测蛋白质变体:在癌细胞系中的综合研究
Genome Med. 2017 Jul 18;9(1):62. doi: 10.1186/s13073-017-0454-9.
9
Functional analysis of human cytochrome P450 21A2 variants involved in congenital adrenal hyperplasia.参与先天性肾上腺皮质增生的人细胞色素P450 21A2变体的功能分析。
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10
Single-cell RNA-seq enables comprehensive tumour and immune cell profiling in primary breast cancer.单细胞 RNA 测序可全面分析原发性乳腺癌中的肿瘤和免疫细胞。
Nat Commun. 2017 May 5;8:15081. doi: 10.1038/ncomms15081.

单细胞中单个氨基酸变异的发现。

Single Amino Acid Variant Discovery in Small Numbers of Cells.

机构信息

Department of Surgery , University of Michigan , Ann Arbor , Michigan 48109 , United States.

NCMIS, RCSDS, Academy of Mathematics and Systems Science , Chinese Academy of Sciences , Beijing 100190 , China.

出版信息

J Proteome Res. 2019 Jan 4;18(1):417-425. doi: 10.1021/acs.jproteome.8b00694. Epub 2018 Nov 21.

DOI:10.1021/acs.jproteome.8b00694
PMID:30404448
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6465122/
Abstract

We have performed deep proteomic profiling down to as few as 9 Panc-1 cells using sample fractionation, TMT multiplexing, and a carrier/reference strategy. Off line fractionation of the TMT-labeled sample pooled with TMT-labeled carrier Panc-1 whole cell proteome was achieved using alkaline reversed phase spin columns. The fractionation in conjunction with the carrier/reference (C/R) proteome allowed us to detect 47 414 unique peptides derived from 6261 proteins, which provided a sufficient coverage to search for single amino acid variants (SAAVs) related to cancer. This high sample coverage is essential in order to detect a significant number of SAAVs. In order to verify genuine SAAVs versus false SAAVs, we used the SAVControl pipeline and found a total of 79 SAAVs from the 9-cell Panc-1 sample and 174 SAAVs from the 5000-cell Panc-1 C/R proteome. The SAAVs as sorted into high confidence and low confidence SAAVs were checked manually. All the high confidence SAAVs were found to be genuine SAAVs, while half of the low confidence SAAVs were found to be false SAAVs mainly related to PTMs. We identified several cancer-related SAAVs including KRAS, which is an important oncoprotein in pancreatic cancer. In addition, we were able to detect sites involved in loss or gain of glycosylation due to the enhanced coverage available in these experiments where we can detect both sites of loss and gain of glycosylation.

摘要

我们使用样品分馏、TMT 多重标记和载体/参考策略,对少至 9 个 Panc-1 细胞进行了深度蛋白质组学分析。使用碱性反相旋转柱对 TMT 标记的样品与 TMT 标记的载体 Panc-1 全细胞蛋白质组混合液进行离线分馏。分馏与载体/参考(C/R)蛋白质组相结合,使我们能够检测到 47414 个独特的肽段,来自 6261 种蛋白质,这为寻找与癌症相关的单个氨基酸变异(SAAV)提供了足够的覆盖度。这种高样品覆盖率对于检测大量 SAAV 至关重要。为了验证真正的 SAAV 与假 SAAV,我们使用了 SAVControl 管道,从 9 个细胞的 Panc-1 样本中总共发现了 79 个 SAAV,从 5000 个细胞的 Panc-1 C/R 蛋白质组中发现了 174 个 SAAV。SAAV 被分类为高可信度和低可信度 SAAV,然后手动检查。所有高可信度的 SAAV 都被证实是真正的 SAAV,而一半的低可信度 SAAV 被发现是假 SAAV,主要与 PTM 有关。我们鉴定了几个与癌症相关的 SAAV,包括 KRAS,它是胰腺癌中的一种重要癌蛋白。此外,我们还能够检测到由于这些实验中提供的增强覆盖度而导致的糖基化丢失或获得的位点,在这些实验中,我们可以检测到糖基化的丢失和获得位点。