...
首页> 外文期刊>Proteomics >Facile removal of high mannose structures prior to extracting complex type N-glycans from de-N-glycosylated peptides retained by C18 solid phase to allow more efficient glycomic mapping
【24h】

Facile removal of high mannose structures prior to extracting complex type N-glycans from de-N-glycosylated peptides retained by C18 solid phase to allow more efficient glycomic mapping

机译:在从由C18固相保留的脱N-糖基化肽中提取复杂的N-聚糖之前,可轻松去除高甘露糖结构,从而实现更有效的糖图分析

获取原文
获取原文并翻译 | 示例
   

获取外文期刊封面封底 >>

       

摘要

The relative amount of high mannose structures within an N-glycomic pool differs from one source to another, but quite often it predominates over the larger size complex type structures carrying biologically important glyco-epitopes. An efficient method to separate these two classes of N-glycans would significantly aid in detecting the lower abundant components by MS. Capitalizing on an initial observation that only high mannose type structures were recovered in the flow-through fraction when peptide-N-glycosidase F digested peptides were passed through a C18 cartridge in 0.1% formic acid, we demonstrated here that native complex type N-glycans can be retained by C18 cartridge and to be efficiently separated from both the smaller high mannose type structures, as well as de-N-glycosylated peptides by stepwise elution with increasing ACN concentration. The weak retention of the largely hydrophilic N-glycans on C18 resin is dependent not only on size but also increased by the presence of α6-fucosylation. This was shown by comparing the resulting N-glycomic profiles of the washed and low-ACN eluted fractions derived from both a human cancer cell line and an insect cell line.
机译:N-糖蛋白库中高甘露糖结构的相对数量因一种来源而异,但通常经常超过携带生物学上重要的糖表位的较大尺寸的复杂类型结构。分离这两类N-聚糖的有效方法将大大有助于通过MS检测较低的丰富成分。利用最初的观察结果,即当肽-N-糖苷酶F消化的肽在0.1%甲酸中通过C18小柱时,流通部分中仅回收了高甘露糖型结构,我们在此证明了天然复杂的N型聚糖可以通过C18柱保留下来,并通过逐步增加ACN的浓度,与较小的高甘露糖型结构以及脱N-糖基化的肽有效地分离。亲水性强的N-聚糖在C18树脂上的弱保留能力不仅取决于大小,还取决于存在α6-岩藻糖基化的程度。通过比较从人类癌细胞系和昆虫细胞系得到的洗涤和低ACN洗脱级分的N-糖类图谱,可以看出这一点。

著录项

相似文献

  • 外文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号