首页> 外文期刊>Journal of dairy science >Quantitative profiling of bacteriocins present in dairy-free probiotic preparations of Lactobacillus acidophilus by nanoliquid chromatography-tandem mass spectrometry
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Quantitative profiling of bacteriocins present in dairy-free probiotic preparations of Lactobacillus acidophilus by nanoliquid chromatography-tandem mass spectrometry

机译:纳米液相色谱-串联质谱法对嗜酸乳杆菌的无乳益生菌制剂中存在的细菌素进行定量分析

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Bacteriocins are a heterogeneous group of ribosomal-ly synthesized peptides or proteins with antimicrobial activity, produced predominantly by lactic acid bacteria, with potential applications as biopreservatives and probiotics. We describe here a novel strategy based on a bottom-up, shotgun proteomic approach using nanoliquid chromatography-tandem mass spectrometry (nanoLC-MS/MS) with multiple fragmentation techniques for the quantitative profiling of bacteriocins present in the probiotic preparations of Lactobacillus acidophilus. A direct LC-MS/MS analysis with alternate collision-induced dissociation, high-energy collision dissociation, and electron-transfer dissociation fragmentation following a filter-assisted size-exclusion sample prefractionation has resulted in the identification of peptides belonging to 37 bacteriocins or related proteins. Peptides from lactacin F, helveticin J, lysin, avicin A, acidocin M, curvaticin FS47, and carocin D were predominant. The process of freeze drying under vacuum was observed to affect both the diversity and abundance of bacteriocins. Data acquisition using alternating complementary peptide fragmentation modes, especially electron-transfer dissociation, has significantly enhanced the peptide sequence coverage and number of bacteriocin peptides identified. Multi-enzyme proteolytic digestion was observed to increase the sample complexity and dynamic range, lowering the chances of detection of low-abundant bacteriocin peptides by LC-MS/MS. An analytical platform integrating size exclusion prefractionation, nanoLC-MS/MS analysis with multiple fragmentation techniques, and data-dependent decision tree-driven bioinformatic data analysis is novel in bacteriocin research and suitable for the comprehensive bioanalysis of diverse, low-abundant bacteriocins in complex samples.
机译:细菌素是核糖体合成的具有抗微生物活性的肽或蛋白质的异质性组,主要由乳酸菌产生,具有作为生物防腐剂和益生菌的潜在应用。我们在这里描述了一种基于自下而上的shot弹枪蛋白质组学方法的新策略,该方法使用了纳米液相色谱串联质谱法(nanoLC-MS / MS)以及多种片段化技术,用于对嗜酸乳杆菌益生菌制剂中存在的细菌素进行定量分析。直接LC-MS / MS分析以及碰撞辅助解离,高能碰撞解离和电子传递解离碎片化后,通过过滤器辅助的尺寸排阻样品预分离,鉴定出了属于37种细菌素或相关细菌的肽蛋白质。来自内酰胺肽F,helveticin J,溶素,阿维菌素A,嗜酸霉素M,curvaticin FS47和carocin D的肽占主导地位。观察到在真空下冷冻干燥的过程会影响细菌素的多样性和丰度。使用交替互补肽片段化模式(尤其是电子转移解离)的数据采集已显着增强了肽序列的覆盖范围和鉴定出的细菌素肽的数量。观察到多酶蛋白水解增加了样品的复杂性和动态范围,降低了通过LC-MS / MS检测低丰度细菌素肽的机会。结合大小排阻预分离,具有多种片段化技术的nanoLC-MS / MS分析以及数据依赖的决策树驱动的生物信息学数据分析的分析平台在细菌素研究中是一种新颖的方法,适用于对复杂的各种低丰度细菌素进行全面的生物分析样品。

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