Chan et al. BMC Genomics 2011, 12:290 http://www.biomedcentral.com/1471-2164/12/290 complete protein parts list is a key component in designing experiments to expand the understanding of a species. In the last four years a plethora of bee proteomics stu- dies have been published (summarized in [5]) but there is, as yet, no central resource dedicated to integrating all this data. Our group alone has acquired in excess of 5.5 million tandem mass spectra from bee samples, representing a rich source of data with which to validate many bee genes and possibly correct many of the anno- tations. The power of this approach has been demon- strated for the closest model organism, Drosophila [6]. The PeptideAtlas [7] provides a central, stable resource for mass spectrometry data supporting protein identifica- tion information for several species. Raw MS/MS data are processed through a single processing pipeline of sequence searching and post-processing with the Trans- Proteomic Pipeline [8,9] to yield a high quality list of identifications with a low and well-characterized false discovery rate (FDR). The resulting list is mapped onto the genome in order to provide chromosomal coordi- nates for all peptides. PeptideAtlas makes the results of this processing available to the community in a variety of ways, including a browser-based interface for viewing and querying the data [10]. Further, PeptideAtlas enables intra- and inter-species comparisons whose value is further increased by the application of a uniform analytic process across all species supported. Here we present the following resources to the com- munity in order to accelerate honey bee research of all kinds: we describe the building of the Honey Bee Pepti- deAtlas, a compendium of protein identification infor- mation derived from a large set of MS/MS data; we present a set of corrections to the honey bee proteome, a set of functional annotations based on the Gene Ontology classification based on homology to other spe- cies, as well as a comprehensive spectral library and a resource to enable emerging targeted proteomics workflows. Implementation Raw data collection All the MS data were collected using either an LTQ- OrbitrapXL or LTQ-FT between 2005 and 2009. Sam- ples included various organs and life stages, treatment and infection states, and strains selected for various traits such as disease resistance or pollen hoarding sum- marized in Table 1, all from the European honey bee A. mellifera. Some of the datasets have been published previously [5,11-13]. In solution and in gel digestion of samples was performed as described [12] and some were subsequently isotopically labeled to measure rela- tive quantities between different conditions/tissues [5,11,13]. Highly concentrated samples were fractionated Page 2 of 11 by strong cation exchange chromatography in a step gradient [14]; all samples were desalted using STAGE Tips [15] before injected into a nanoflow liquid chroma- tography system with C18 reversed phase material and sprayed into the mass spectrometer as described in [5]. Correction and identification of new proteins In order to detect possible new genes and proteins, as well as to correct incorrect protein predictions, all MS/ MS spectra described above were searched using an automated pipeline built using Proteus (Genologics, http://www.genologics.com/). The pipeline automates submission of MS/MS spectra to an off-site Mascot ser- ver http://www.matrixscience.com/ and the retrieval and filtering of search results. The peak lists were initially searched against the NCBI A. mellifera protein database (plus human contaminants and digestion enzymes) using a Mascot score cutoff of 27, essentially as described [5]. Spectra that did not match any peptides from this search were re-searched against a six-frame translation of the honey bee genome. The six-frame translation was created independently of the built-in function in Mascot, using the eukaryotic genetic code and limiting an open reading frame (ORF) to at least 35 amino acids and spectral hits against this database were considered further if they had an IonsScore of at least 25. For a genomic six-frame translation library this cut- off is not very stringent but this was used simply as an initial filtering step. ORFs that were hit by at least two unique peptides were examined further to see if they could be missed exons of previously annotated genes or if they occurred far from any known genes and thus might be novel genes. ORFs meeting these criteria were then shortened to cover only the region spanned by peptide identifications and added to the protein sequence library used in PeptideAtlas. Links to all of these sequences can be found in Additional File 1, as well as at the honey bee download area at PeptideAtlas at http://www.peptideatlas.org/builds/honeybee/. Creation of a comprehensive protein set In order to process the MS/MS data within PeptideAtlas against the widest array of possible honey bee proteins, we created a comprehensive protein set by assembling the Refseq ftp://ftp.ncbi.nih.gov/genomes/Apis_mellifera/ protein/protein.fa.gz sequences, Official Gene Set 1 [1,16], Genbank [17], and Gnomon predictions ftp://ftp. ncbi.nih.gov/genomes/Apis_mellifera/protein/Gnomon_ prot.fsa.gz. The three protein sets were merged by removing all exact duplicates and keeping the first of the protein in order of the sources as listed above. This was then supplemented with the new protein sequences described in the previous section. Note that only exact duplicates are removed, and many near duplicates