Yana Demyanenko, Andrew M. Giltrap, Benjamin G. Davis, Shabaz Mohammed
{"title":"Removal of NHS-labelling by-products in Proteomic Samples","authors":"Yana Demyanenko, Andrew M. Giltrap, Benjamin G. Davis, Shabaz Mohammed","doi":"10.1101/2024.08.15.607975","DOIUrl":null,"url":null,"abstract":"N-Hydroxysuccinimide (NHS) ester chemistry is used extensively across proteomics sample preparation. One of its increasingly prevalent applications is in isobaric reagent-based quantitation such as the iTRAQ (isobaric tags for relative and absolute quantitation) and TMT (tandem mass tag) approaches. In these methods, labelling on the primary amines of lysine residues and N-termini of tryptic peptides via amide formation (N-derivatives) from corresponding NHS ester reagents is the intended reactive outcome. However, the role of NHS esters as activated carboxyls can also drive the formation of serine-, tyrosine-, and threonine- derived esters (O-derivatives). These O-derivative peptides are typically classed as over-labelled and are disregarded for quantification, leading to loss of information and hence potential sensitivity. Their presence also unnecessarily increases sample complexity, which reduces the overall identification rates. One common approach for removing these unwanted labelling events has involved a quench with hydroxylamine. We show here that this approach is not fully efficient and can still leave substantial levels of unwanted over-labelled peptides. Through systematic screening of nucleophilic aminolysis reagents and reaction conditions, we have now developed a robust method to efficiently remove over-labelled peptides. The new method reduces the proportion of over-labelled peptides in the sample to less than 1% without affecting the labelling rate or introducing other modifications, leading to superior identification rates and quantitation precision.","PeriodicalId":501213,"journal":{"name":"bioRxiv - Systems Biology","volume":"4 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"bioRxiv - Systems Biology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1101/2024.08.15.607975","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
N-Hydroxysuccinimide (NHS) ester chemistry is used extensively across proteomics sample preparation. One of its increasingly prevalent applications is in isobaric reagent-based quantitation such as the iTRAQ (isobaric tags for relative and absolute quantitation) and TMT (tandem mass tag) approaches. In these methods, labelling on the primary amines of lysine residues and N-termini of tryptic peptides via amide formation (N-derivatives) from corresponding NHS ester reagents is the intended reactive outcome. However, the role of NHS esters as activated carboxyls can also drive the formation of serine-, tyrosine-, and threonine- derived esters (O-derivatives). These O-derivative peptides are typically classed as over-labelled and are disregarded for quantification, leading to loss of information and hence potential sensitivity. Their presence also unnecessarily increases sample complexity, which reduces the overall identification rates. One common approach for removing these unwanted labelling events has involved a quench with hydroxylamine. We show here that this approach is not fully efficient and can still leave substantial levels of unwanted over-labelled peptides. Through systematic screening of nucleophilic aminolysis reagents and reaction conditions, we have now developed a robust method to efficiently remove over-labelled peptides. The new method reduces the proportion of over-labelled peptides in the sample to less than 1% without affecting the labelling rate or introducing other modifications, leading to superior identification rates and quantitation precision.