Jenni Viitaharju, Lauri Polari, Otto Kauko, Johannes Merilahti, Anne Rokka, Diana M. Toivola, Kirsi Laitinen
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引用次数: 0
摘要
母乳的成分包括多种生物活性因子,如活细胞、脂类和蛋白质。由于蛋白质浓度的动态范围很大,而且存在干扰物质,因此测量母乳血浆中特定蛋白质的水平具有挑战性。因此,大多数母乳蛋白质组学研究只能鉴定出不到 1000 种蛋白质。母乳蛋白质组研究中使用的优化程序和最新分离技术可以更精确地了解母乳蛋白质组。本研究(n = 53)采用了三种不同的蛋白质定量方法,包括直接 DIA 法、基于文库的 DIA 法以及一种结合了直接 DIA 法和基于文库的 DIA 法的混合方法。通过混合方法,我们平均鉴定了 2400 个蛋白质。通过应用这些方法,我们量化了母乳蛋白质组中与体重指数(BMI)相关的变化。在比较肥胖母亲和超重母亲的母乳蛋白质组时,有 210 种蛋白质存在明显差异。此外,我们还利用高场非对称波形离子迁移谱法(FAIMS)分析了一个小型群组(n = 5,从 53 个样本中随机抽取)。FAIMS 与 Orbitrap Fusion Lumos 质谱仪联用,与 Q Exactive HF 质谱仪相比,蛋白质鉴定率提高了 41.7%。
Improved breast milk proteome coverage by DIA based LC-MS/MS method
The breast milk composition includes a multitude of bioactive factors such as viable cells, lipids and proteins. Measuring the levels of specific proteins in breast milk plasma can be challenging because of the large dynamic range of protein concentrations and the presence of interfering substances. Therefore, most proteomic studies of breast milk have been able to identify under 1000 proteins. Optimised procedures and the latest separation technologies used in milk proteome research could lead to more precise knowledge of breast milk proteome. This study (n = 53) utilizes three different protein quantification methods, including direct DIA, library-based DIA method and a hybrid method combining direct DIA and library-based DIA. On average we identified 2400 proteins by hybrid method. By applying these methods, we quantified body mass index (BMI) associated variation in breast milk proteomes. There were 210 significantly different proteins when comparing the breast milk proteome of obese and overweight mothers. In addition, we analysed a small cohort (n = 5, randomly selected from 53 samples) by high field asymmetric waveform ion mobility spectrometry (FAIMS). FAIMS coupled with the Orbitrap Fusion Lumos mass spectrometer, which led to 41.7% higher number of protein identifications compared to Q Exactive HF mass spectrometer.
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.