利用多重离子活化和质子转移电荷还原对重组腺相关病毒的囊膜蛋白进行自上而下的质谱分析。

IF 3.4 4区 生物学 Q2 BIOCHEMICAL RESEARCH METHODS Proteomics Pub Date : 2024-09-05 DOI:10.1002/pmic.202400223
Jake T Kline, Jingjing Huang, Linda B Lieu, Kristina Srzentić, David Bergen, Christopher Mullen, Graeme C McAlister, Kenneth R Durbin, Rafael D Melani, Luca Fornelli
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引用次数: 0

摘要

腺相关病毒(AAV)对人类无致病性,是新兴基因疗法的常用载体。在此,我们通过自上而下的质谱法(MS)研究了 AAV 病毒外壳的病毒蛋白(即 VP1、VP2 和 VP3)。利用亲水相互作用液相色谱法对这些分子量在 59 至 81 kDa 之间的蛋白质进行色谱分离,并利用高分辨率 Orbitrap 傅立叶变换质谱对其气相特征进行表征。利用互补离子解离法提高了整体序列覆盖率。在 Orbitrap Ascend BioPharma Tribrid 质谱仪上通过质子转移电荷还原减少了产物离子信号的重叠,从而显著提高了每个 VP 的序列覆盖率,其中 VP3 的覆盖率高达 40%。这些结果表明,通过气相反应操纵产物离子以获得易于解释的碎片质谱,可以改善大于 30 kDa 蛋白质的测序。
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Top-down mass spectrometry analysis of capsid proteins of recombinant adeno-associated virus using multiple ion activations and proton transfer charge reduction.

Adeno-associated viruses (AAVs) are common vectors for emerging gene therapies due to their lack of pathogenicity in humans. Here, we present our investigation of the viral proteins (i.e., VP1, VP2, and VP3) of the capsid of AAVs via top-down mass spectrometry (MS). These proteins, ranging from 59 to 81 kDa, were chromatographically separated using hydrophilic interaction liquid chromatography and characterized in the gas-phase by high-resolution Orbitrap Fourier transform MS. Complementary ion dissociation methods were utilized to improve the overall sequence coverage. By reducing the overlap of product ion signals via proton transfer charge reduction on the Orbitrap Ascend BioPharma Tribrid mass spectrometer, the sequence coverage of each VP was significantly increased, reaching up to ∼40% in the case of VP3. These results showcase the improvements in the sequencing of proteins >30 kDa that can be achieved by manipulating product ions via gas-phase reactions to obtain easy-to-interpret fragmentation mass spectra.

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来源期刊
Proteomics
Proteomics 生物-生化研究方法
CiteScore
6.30
自引率
5.90%
发文量
193
审稿时长
3 months
期刊介绍: PROTEOMICS is the premier international source for information on all aspects of applications and technologies, including software, in proteomics and other "omics". The journal includes but is not limited to proteomics, genomics, transcriptomics, metabolomics and lipidomics, and systems biology approaches. Papers describing novel applications of proteomics and integration of multi-omics data and approaches are especially welcome.
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