The beauty of being (label)-free: sample preparation methods for SWATH-MS and next-generation targeted proteomics

Abstract

<ns4:p>The combination of qualitative analysis with label-free quantification has greatly facilitated the throughput and flexibility of novel proteomic techniques. However, such methods rely heavily on robust and reproducible sample preparation procedures. Here, we benchmark a selection of <ns4:italic>in gel</ns4:italic>, <ns4:italic>on filter</ns4:italic>, and <ns4:italic>in solution</ns4:italic> digestion workflows for their application in label-free proteomics. Each procedure was associated with differing advantages and disadvantages. The <ns4:italic>in gel </ns4:italic>methods interrogated were cost effective, but were limited in throughput and digest efficiency. <ns4:italic>Filter-aided</ns4:italic> sample preparations facilitated reasonable processing times and yielded a balanced representation of membrane proteins, but led to a high signal variation in quantification experiments. Two <ns4:italic>in solution</ns4:italic> digest protocols, however, gave optimal performance for label-free proteomics. A protocol based on the detergent <ns4:italic>RapiGest</ns4:italic> led to the highest number of detected proteins at second-best signal stability, while a protocol based on acetonitrile-digestion, <ns4:italic>RapidACN</ns4:italic>, scored best in throughput and signal stability but came second in protein identification. In addition, we compared label-free data dependent (DDA) and data independent (SWATH) acquisition. While largely similar in protein detection, SWATH outperformed DDA in quantification, reducing signal variation and markedly increasing the number of precisely quantified peptides.</ns4:p>