Curated DIA assay for consistent ecological proteomics of threespine sticklebacks (Gasterosteus aculeatus)
J. Li, B.B. Levitan, S. Gomez-Jimenez and D. Kültz (2018) Development of a gill assay library for ecological proteomics of threespine sticklebacks (Gasterosteus aculeatus). Mol. Cell. Proteomics, in press. (2018, doi: 10.1074/mcp.RA118.000973
- Organism: Gasterosteus aculeatus
- Instrument: ImpactHD UHR-QTOF
A curated data-independent acquisition (cDIA) assay for consistent quantitative analyses of proteome dynamics has been developed for threespine stickleback gill. The assay utilizes a spectral library generated by data-dependent acquisition (DDA) and annotation of tryptic peptides to MSMS spectra and to protein database identifiers by multiple search engines. The cDIA target set has been curated to remove low-quality, ambiguous, and low-signal entries. It only includes only unique proteins that are represented by at least two proteotypic peptides. The resulting cDIA target set consists of 1506 proteins, 5,074 peptides, 5,104 precursors, and 25,322 transitions. This assay was used to identify biochemical differences in the gill proteome of four populations representing different eco- and morpho-types of threespine sticklebacks. This approach represents a model for cDIA assay development in other tissues, which will pave the way for accurate and reproducible analyses of environmental context-dependent proteome network dynamics in whole organisms.
Three independent search engines (Mascot 2.2.7, X!Tandem Cyclone, PEAKS 8.0) were used and identical parameters and settings as previously described were applied for experiment 1 DDA data (Kültz et al., 2015, Proteomics 15, 3980-3992; Kültz et al., 2016, J Proteomics 135, 112-131). Data and metadata for these analyses have been submitted to MassIVE (MSV000081795) and ProteomeXchange (PXD008395). Additional DDA results for the experiment 1 dataset, including PEAKSQ 8 (Bioinformatics Solutions Inc.) MS1 quantitative surveys and Scaffold (Proteome Systems) analyses are available at CAMP proteome under accession number CAMPDDA00023 (https://kueltzlab.ucdavis.edu/CAMP_dda_profiles.cfm?AC=CAMPDDA00023).
A G. aculeatus gill spectral library was generated using the peptide-to-spectrum matches and protein annotation information generated from experiment 1 DDA data. DDA was used to identify peptide-to-spectrum matches and corresponding protein entries in the threespine stickleback (G. aculeatus) UniProt reference proteome. This information was exported in pepxml and Mascot dat formats followed by spectral library construction with Skyline 3.6 (MacCoss Lab) (Pino et al, 2017, Mass Spectrom Rev DOI: 10.1002/mas.21540, 1-16). Validation of gill proteins with significantly and at least 2-fold different abundances in a single population relative to the other populations was accomplished by repeating experiment 1 three additional times. Independent population samplings were performed and different fish (representing independent biological replicates) for experiments 2 to 4 (n=6 for each population in each experiment). All samples for experiments 1 to 4 were analyzed by the novel cDIA assay.
Each sample was collected from a different fish. Gill tissue was excised after sacrificing fish and samples prepared as previously described (Kültz et al., 2013, Mol Cell Proteomics 12, 3962-3975). Six samples were collected from 4 populations in four experiments. Each experiment consisted of an independent population sampling. For each experiment six fish were sampled from each population (24 total samples in each experiment). Only samples in experiment 1 were analyzed by DDA to generate a spectral libary for cDIA assay development. All samples from all four experiments were then analyzed by the newly developed cDIA assay. Unique gill proteome signatures were identified for the four populations: warm-adapted, low-plated, brackish-water (LaBoRo), cold-adapted, fully-plated, brackish-water (WesLag), cold-adapted, low-plated, freshwater (LakSol), and cold-adapted, fully-plated, marine (BodHar) fish.
Created on 12/18/17, 2:50 PM