Abstract
The model organism zebrafish (Danio rerio) is particularly amenable to studies deciphering regulatory genetic networks in vertebrate development, biology, and pharmacology. Unraveling the functional dynamics of such networks requires precise quantitation of protein expression during organismal growth, which is incrementally challenging with progressive complexity of the systems. In an approach toward such quantitative studies of dynamic network behavior, we applied mass spectrometric methodology and rigorous statistical analysis to create comprehensive, high quality profiles of proteins expressed at two stages of zebrafish development. Proteins of embryos 72 and 120 h postfertilization (hpf) were isolated and analyzed both by two-dimensional (2D) LC followed by ESI-MS/MS and by 2D PAGE followed by MALDI-TOF/TOF protein identification. We detected 1384 proteins from 327,906 peptide sequence identifications at 72 and 120 hpf with false identification rates of less than 1% using 2D LC-ESI-MS/MS. These included only approximately 30% of proteins that were identified by 2D PAGE-MALDI-TOF/TOF. Roughly 10% of all detected proteins were derived from hypothetical or predicted gene models or were entirely unannotated. Comparison of proteins expression by 2D DIGE revealed that proteins involved in energy production and transcription/translation were relatively more abundant at 72 hpf consistent with faster synthesis of cellular proteins during organismal growth at this time compared with 120 hpf. The data are accessible in a database that links protein identifications to existing resources including the Zebrafish Information Network database. This new resource should facilitate the selection of candidate proteins for targeted quantitation and refine systematic genetic network analysis in vertebrate development and biology.
Highlights
The model organism zebrafish (Danio rerio) is amenable to studies deciphering regulatory genetic networks in vertebrate development, biology, and pharmacology
Peptide sequence identifications generated from both search algorithms for each replicate were combined in an integrated analysis using the Empirical Bayes Protein Identifier (EBP) algorithm for protein assignment to augment sensitivity and error control [30]
Sequencing of the genome has fostered various initiatives to catalog the proteome of genetic model organisms such as yeast [37], Caenorhabditis elegans [38], Drosophila [39, 40], and the mouse [41]
Summary
Sample Preparation—Methods for breeding and raising zebrafish embryos were followed as described previously [33]. EBP analyses were run on combined SEQUEST and MASCOT results and biological replicates for each developmental stage using its default settings except for the calculation of the number of trypsin digests per protein, which specified peptides with at least one tryptic terminus. A minimum of two monoisotopic trypsin peaks were required to calibrate each spectrum to a mass accuracy within 20 ppm Failure to meet these criteria resulted in the application of the external plate calibration that was performed prior to each run and required matching of six standard peptide ion masses (m/z 904.468, 1296.685, 1570.677, 2093.087, 2465.199, and 3657.929) from six calibration spots (4700 Mass Standard kit, catalog number 4333604, Applied Biosystems). The zebrafish proteomics database can be accessed on line (see supplemental data for the URL database link under Instructions for Downloading)
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
