In-Depth, Comprehensive Mapping of the Human Seminal Plasma Proteome by a Novel, Iterative LC-MS/MS Analysis and Database Search Workflow

Apart from its obvious role in transporting male gametes, seminal plasma provides a protective environment for ejaculated spermatozoa and improves their fertilizing potential. Compositional changes can alter these properties and cause reproductive disorders. Thus, characterization of seminal plasma has the potential to provide biomarkers of reproductive disorders in males. Seminal plasma is a highly complex fluid that contains proteins secreted from several glands of the male reproductive tract: prostate, seminal vesicle, epididymis, and testis (Figure 1). However, like most body fluids, seminal plasma presents a wide range of protein concentrations that renders low-abundance proteins very difficult to identify and quantify. Few studies have been performed to investigate the protein composition of seminal plasma. Several proteins were identified in the seminal plasma of healthy donors using a 2D gel-mass spectrometry approach.1, 2 More recent studies were performed using a combination of 1D gel electrophoresis and LC-MS/MS analysis. In 2006, 923 proteins were identified by Mann and co-workers using this strategy with mass analysis performed by an LTQ FT instrument.3 However, this study failed to identify known markers in the seminal plasma such as epididymis-specific defensins that may have been lost during the fractionation step, demonstrating the complexity of this biological fluid. Mass spectrometers have a limited dynamic range where peptide analyte ions of interest can be fragmented efficiently for confident identification by database search. Due to sample preparation, chromatographic, and mass spectro metric constraints, a limited number of peptides can be analyzed in any given LC-MS/MS experiment. On-the-fly strategies involve the selection of the most intense peptides for fragmentation in a data-dependent manner. Very complex samples like seminal plasma thus require an optimized data acquisition strategy to achieve a thorough analysis of the sample. Here we describe a method for extensive protein identification in complex samples that involves iterative nanoflow LC-MS/MS analysis, exclusion list generation, and iterative database searching with Thermo Scientific Proteome Discoverer software, leading to the identification of numerous low-copy-number proteins in the seminal plasma proteome.