Mass Measurement Errors of Fourier-Transform Mass Spectrometry (FTMS): Distribution, Recalibration, and Application

In-depth proteomic analysis of boar spermatozoa through shotgun and gel-based methods

Background

Mature spermatozoa contain numerous epididymal and seminal plasma proteins, which full identification through high-throughput technologies may allow for a better understanding of the sperm biology. Therefore, we conducted a global proteomic analysis of boar spermatozoa through shotgun and gel-based methodologies.

Results

The total proteins were extracted from mature spermatozoa and subjecsted to proteome analyses. Functional analyses of gene ontology representations and pathway enrichments were conducted on the shotgun dataset, followed by immunology and gene expression validations. Shotgun and gel-based approaches allowed the detection of 2728 proteins and 2123 spots, respectively. Approximately 38% and 59% of total proteins were respectively fully and partially annotated, and 3% were unknown. Gene ontology analysis indicated high proportions of proteins associated with intracellular and cytoplasm localizations, protein and nucleic acid binding, hydrolase and transferase activities, and cellular, metabolic, and regulation of biological processes. Proteins associated with phosphorylation processes and mitochondrial membranes, nucleic acid binding, and phosphate and phosphorous metabolics represented 77% of the dataset. Pathways associated with oxidative phosphorylation, citrate cycle, and extra-cellular matrix-receptor interaction were significantly enriched. Protein complex, intracellular organelle, cytoskeletal parts, fertilization and reproduction, and gap junction pathway were significantly enriched within the top 116 highly abundant proteins. Nine randomly selected protein candidates were confirmed with gel-based identification, immunofluorescence detection, and mRNA expression.

Conclusions

This study offers an in-depth proteomic mapping of mature boar spermatozoa that will enable comparative and discovery research for the improvement of male fertility.

Electronic supplementary material

The online version of this article (10.1186/s12864-018-4442-2) contains supplementary material, which is available to authorized users.

Mass recalibration of FT-ICR mass spectrometry imaging data using the average frequency shift of ambient ions

Achieving and maintaining high mass measurement accuracy (MMA) throughout a mass spectrometry imaging (MSI) experiment is vital to the identification of the observed ions. However, when using FTMS instruments, fluctuations in the total ion abundance at each pixel due to inherent biological variation in the tissue section can introduce space charge effects that systematically shift the observed mass. Herein we apply a recalibration based on the observed cyclotron frequency shift of ions found in the ambient laboratory environment, polydimethylcyclosiloxanes (PDMS). This calibration method is capable of achieving part per billion (ppb) mass accuracy with relatively high precision for an infrared matrix-assisted laser desorption electrospray ionization (IR-MALDESI) MSI dataset. Comparisons with previously published mass calibration approaches are also presented.

An improved calibration method for the matrix-assisted laser desorption/ionization-Fourier transform ion cyclotron resononance analysis of 15N-metabolically- labeled proteome digests using a mass difference approach

High mass measurement accuracy of peptides in enzymatic digests is critical for confident protein identification and characterization in proteomics research. Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS) can provide low or sub-ppm mass accuracy and ultrahigh resolving power. While for ESI-FT-ICR-MS, the mass accuracy is generally 1 ppm or better, with matrix-assisted laser desorption/ionization (MALDI)-FT-ICR-MS, the mass errors can vary from sub-ppm with internal calibration to over 100 ppm with conventional external calibration. A novel calibration method for (15)N-metabolically labeled peptides from a batch digest of a proteome is described which corrects for space charge induced frequency shifts in FT-ICR spectra without using an internal calibrant. This strategy utilizes the information from the mass difference between the (14)N/(15)N peptide peak pairs to correct for space charge induced mass shifts after data collection. A procedure for performing the mass correction has been written into a computer program and has been successfully applied to high-performance liquid chromatography-MALDI-FT- ICR-MS measurement of (15)N-metabolic labeled proteomes. We have achieved an average measured mass error of 1.0 ppm and a standard deviation of 3.5 ppm for 900 peptides from 68 MALDI-FT-ICR mass spectra of the proteolytic digest of a proteome from Methanococcus maripaludis.

DtaRefinery, a software tool for elimination of systematic errors from parent ion mass measurements in tandem mass spectra data sets

Hybrid two-stage mass spectrometers capable of both highly accurate mass measurement and high throughput MS/MS fragmentation have become widely available in recent years, allowing for significantly better discrimination between true and false MS/MS peptide identifications by the application of a relatively narrow window for maximum allowable deviations of measured parent ion masses. To fully gain the advantage of highly accurate parent ion mass measurements, it is important to limit systematic mass measurement errors. Based on our previous studies of systematic biases in mass measurement errors, here, we have designed an algorithm and software tool that eliminates the systematic errors from the peptide ion masses in MS/MS data. We demonstrate that the elimination of the systematic mass measurement errors allows for the use of tighter criteria on the deviation of measured mass from theoretical monoisotopic peptide mass, resulting in a reduction of both false discovery and false negative rates of peptide identification. A software implementation of this algorithm called DtaRefinery reads a set of fragmentation spectra, searches for MS/MS peptide identifications using a FASTA file containing expected protein sequences, fits a regression model that can estimate systematic errors, and then corrects the parent ion mass entries by removing the estimated systematic error components. The output is a new file with fragmentation spectra with updated parent ion masses. The software is freely available.