Protein Sequence Database Searches Research Articles

CUDASW++4.0: ultra-fast GPU-based Smith–Waterman protein sequence database search

BackgroundThe maximal sensitivity for local pairwise alignment makes the Smith-Waterman algorithm a popular choice for protein sequence database search. However, its quadratic time complexity makes it compute-intensive. Unfortunately, current state-of-the-art software tools are not able to leverage the massively parallel processing capabilities of modern GPUs with close-to-peak performance. This motivates the need for more efficient implementations.ResultsCUDASW++4.0 is a fast software tool for scanning protein sequence databases with the Smith-Waterman algorithm on CUDA-enabled GPUs. Our approach achieves high efficiency for dynamic programming-based alignment computation by minimizing memory accesses and instructions. We provide both efficient matrix tiling, and sequence database partitioning schemes, and exploit next generation floating point arithmetic and novel DPX instructions. This leads to close-to-peak performance on modern GPU generations (Ampere, Ada, Hopper) with throughput rates of up to 1.94 TCUPS, 5.01 TCUPS, 5.71 TCUPS on an A100, L40S, and H100, respectively. Evaluation on the Swiss-Prot, UniRef50, and TrEMBL databases shows that CUDASW++4.0 gains over an order-of-magnitude performance improvements over previous GPU-based approaches (CUDASW++3.0, ADEPT, SW#DB). In addition, our algorithm demonstrates significant speedups over top-performing CPU-based tools (BLASTP, SWIPE, SWIMM2.0), can exploit multi-GPU nodes with linear scaling, and features an impressive energy efficiency of up to 15.7 GCUPS/Watt.ConclusionCUDASW++4.0 changes the standing of GPUs in protein sequence database search with Smith-Waterman alignment by providing close-to-peak performance on modern GPUs. It is freely available at https://github.com/asbschmidt/CUDASW4.

Rapid multiple protein sequence search by parallel and heterogeneous computation.

Protein sequence database search and multiple sequence alignment generation is a fundamental task in many bioinformatics analyses. As the data volume of sequences continues to grow rapidly, there is an increasing need for efficient and scalable multiple sequence query algorithms for super-large databases without expensive time and computational costs. We introduce Chorus, a novel protein sequence query system that leverages parallel model and heterogeneous computation architecture to enable users to query thousands of protein sequences concurrently against large protein databases on a desktop workstation. Chorus achieves over 100× speedup over BLASTP without sacrificing sensitivity. We demonstrate the utility of Chorus through a case study of analyzing a ∼1.5-TB large-scale metagenomic datasets for novel CRISPR-Cas protein discovery within 30 min. Chorus is open-source and its code repository is available at https://github.com/Bio-Acc/Chorus.

Mistle: bringing spectral library predictions to metaproteomics with an efficient search index.

Deep learning has moved to the forefront of tandem mass spectrometry-driven proteomics and authentic prediction for peptide fragmentation is more feasible than ever. Still, at this point spectral prediction is mainly used to validate database search results or for confined search spaces. Fully predicted spectral libraries have not yet been efficiently adapted to large search space problems that often occur in metaproteomics or proteogenomics. In this study, we showcase a workflow that uses Prosit for spectral library predictions on two common metaproteomes and implement an indexing and search algorithm, Mistle, to efficiently identify experimental mass spectra within the library. Hence, the workflow emulates a classic protein sequence database search with protein digestion but builds a searchable index from spectral predictions as an in-between step. We compare Mistle to popular search engines, both on a spectral and database search level, and provide evidence that this approach is more accurate than a database search using MSFragger. Mistle outperforms other spectral library search engines in terms of run time and proves to be extremely memory efficient with a 4- to 22-fold decrease in RAM usage. This makes Mistle universally applicable to large search spaces, e.g. covering comprehensive sequence databases of diverse microbiomes. Mistle is freely available on GitHub at https://github.com/BAMeScience/Mistle.

A Hybrid Spectral Library and Protein Sequence Database Search Strategy for Bottom-Up and Top-Down Proteomic Data Analysis.

Tandem mass spectrometry (MS/MS) is widely employed for the analysis of complex proteomic samples. While protein sequence database searching and spectral library searching are both well-established peptide identification methods, each has shortcomings. Protein sequence databases lack fragment peak intensity information, which can result in poor discrimination between correct and incorrect spectrum assignments. Spectral libraries usually contain fewer peptides than protein sequence databases, which limits the number of peptides that can be identified. Notably, few post-translationally modified peptides are represented in spectral libraries. This is because few search engines can both identify a broad spectrum of PTMs and create corresponding spectral libraries. Also, programs that generate spectral libraries using deep learning approaches are not yet able to accurately predict spectra for the vast majority of PTMs. Here, we address these limitations through use of a hybrid search strategy that combines protein sequence database and spectral library searches to improve identification success rates and sensitivity. This software uses Global PTM Discovery (G-PTM-D) to produce spectral libraries for a wide variety of different PTMs. These features, along with a new spectrum annotation and visualization tool, have been integrated into the freely available and open-source search engine MetaMorpheus.

Conformational change following conversion of inactive rhinophrynin-33 to bioactive rhinophrynin-27 in the skin of the frog Rhinophrynus dorsalis

Skin secretions of the Mexican burrowing toad Rhinophrynus dorsalis (Rhinophrynidae) contain the proline-arginine-rich peptide, rhinophrynin-27 (RP-27; ELRLPEIARPVPEVLPARLPLPALPRN) with insulinotropic and immunomodulatory properties, together with a higher concentration of the biologically inactive form, rhinophrynin-33 (RP-33) that constitutes RP-27 extended from its C-terminus by the hexapeptide KMAKNQ. Determination of the conformation of RP-33 by NMR demonstrates that in both water and in a solvent that promotes protein folding (50% trifluoroethanol-water), the majority of the proline residues are found in a polyproline type II helical region. The peptide adopts a horseshoe (U-shaped) conformation with pronounced bends in the molecule of around 100°–120° at Glu13 and Arg18. The hexapeptide extension adopts a α-helical conformation. When the hexapeptide is excised to generate RP-27, the molecule adopts an L-shaped conformation with a single bend at Glu13. A search of protein sequence databases indicated the P-X-P-XXX-P-XXX-P-X-P motif found in RP-27 and RP-33 occurs in a number of proteins although its functional implications are unclear. The data suggest that RP-33 represents a biosynthetic precursor of RP-27 that is activated by a protease cleaving at a single lysine residue of the type previously identified in Xenopus laevis skin secretions.

Using Bioinformatics to Understand Genetic Diseases

This Practical Guide in the Bringing Bioinformatics into the Classroom series outlines a number of basic bioinformatics approaches that can be used to understand the molecular basis of genetic diseases. A rare variation in the insulin gene is discussed, and the impact of the variation on the gene product, and how this results in disease, is explored. Specifically, this Guide introduces a range of commonly used bioinformatics tools and databases with which to analyse both DNA and protein sequences, and protein structures. On reading the Guide and completing the exercises, users will be able to: investigate the locations of genes on the human genome using a genome browser; compare DNA sequences using an alignment tool; translate a DNA sequence into its protein product; search a protein structure database, and visualise the 3D structure of insulin; and infer whether insulin is specific to humans by using protein sequence database search tools.

Protein Identification from Tandem Mass Spectra by Database Searching.

Protein identification from tandem mass spectra is one of the most versatile and widely used proteomics workflows, able to identify proteins, characterize post-translational modifications, and provide semiquantitative measurements of relative protein abundance. This manuscript describes the concepts, prerequisites, and methods required to analyze a tandem mass spectrometry dataset in order to identify its proteins, by using a tandem mass spectrometry search engine to search protein sequence databases. The discussion includes instructions for extraction, preparation, and formatting of spectral datafiles, selection of appropriate search parameter settings, and basic interpretation of the results.

ReSpect: software for identification of high and low abundance ion species in chimeric tandem mass spectra.

Most shotgun proteomics data analysis workflows are based on the assumption that each fragment ion spectrum is explained by a single species of peptide ion isolated by the mass spectrometer; however, in reality mass spectrometers often isolate more than one peptide ion within the window of isolation that contribute to additional peptide fragment peaks in many spectra. We present a new tool called reSpect, implemented in the Trans-Proteomic Pipeline (TPP), which enables an iterative workflow whereby fragment ion peaks explained by a peptide ion identified in one round of sequence searching or spectral library search are attenuated based on the confidence of the identification, and then the altered spectrum is subjected to further rounds of searching. The reSpect tool is not implemented as a search engine, but rather as a post-search engine processing step where only fragment ion intensities are altered. This enables the application of any search engine combination in the iterations that follow. Thus, reSpect is compatible with all other protein sequence database search engines as well as peptide spectral library search engines that are supported by the TPP. We show that while some datasets are highly amenable to chimeric spectrum identification and lead to additional peptide identification boosts of over 30% with as many as four different peptide ions identified per spectrum, datasets with narrow precursor ion selection only benefit from such processing at the level of a few percent. We demonstrate a technique that facilitates the determination of the degree to which a dataset would benefit from chimeric spectrum analysis. The reSpect tool is free and open source, provided within the TPP and available at the TPP website. Graphical Abstract ᅟ.

GPCRtm: An amino acid substitution matrix for the transmembrane region of class A G Protein-Coupled Receptors.

BackgroundProtein sequence alignments and database search methods use standard scoring matrices calculated from amino acid substitution frequencies in general sets of proteins. These general-purpose matrices are not optimal to align accurately sequences with marked compositional biases, such as hydrophobic transmembrane regions found in membrane proteins. In this work, an amino acid substitution matrix (GPCRtm) is calculated for the membrane spanning segments of the G protein-coupled receptor (GPCR) rhodopsin family; one of the largest transmembrane protein family in humans with great importance in health and disease.ResultsThe GPCRtm matrix reveals the amino acid compositional bias distinctive of the GPCR rhodopsin family and differs from other standard substitution matrices. These membrane receptors, as expected, are characterized by a high content of hydrophobic residues with regard to globular proteins. On the other hand, the presence of polar and charged residues is higher than in average membrane proteins, displaying high frequencies of replacement within themselves.ConclusionsAnalysis of amino acid frequencies and values obtained from the GPCRtm matrix reveals patterns of residue replacements different from other standard substitution matrices. GPCRs prioritize the reactivity properties of the amino acids over their bulkiness in the transmembrane regions. A distinctive role is that charged and polar residues seem to evolve at different rates than other amino acids. This observation is related to the role of the transmembrane bundle in the binding of ligands, that in many cases involve electrostatic and hydrogen bond interactions. This new matrix can be useful in database search and for the construction of more accurate sequence alignments of GPCRs.Electronic supplementary materialThe online version of this article (doi:10.1186/s12859-015-0639-4) contains supplementary material, which is available to authorized users.

SANSparallel: interactive homology search against Uniprot.

Proteins evolve by mutations and natural selection. The network of sequence similarities is a rich source for mining homologous relationships that inform on protein structure and function. There are many servers available to browse the network of homology relationships but one has to wait up to a minute for results. The SANSparallel webserver provides protein sequence database searches with immediate response and professional alignment visualization by third-party software. The output is a list, pairwise alignment or stacked alignment of sequence-similar proteins from Uniprot, UniRef90/50, Swissprot or Protein Data Bank. The stacked alignments are viewed in Jalview or as sequence logos. The database search uses the suffix array neighborhood search (SANS) method, which has been re-implemented as a client-server, improved and parallelized. The method is extremely fast and as sensitive as BLAST above 50% sequence identity. Benchmarks show that the method is highly competitive compared to previously published fast database search programs: UBLAST, DIAMOND, LAST, LAMBDA, RAPSEARCH2 and BLAT. The web server can be accessed interactively or programmatically at http://ekhidna2.biocenter.helsinki.fi/cgi-bin/sans/sans.cgi. It can be used to make protein functional annotation pipelines more efficient, and it is useful in interactive exploration of the detailed evidence supporting the annotation of particular proteins of interest.

Prediction of Peptide Fragment Ion Mass Spectra by Data Mining Techniques

Accurate prediction of peptide fragment ion mass spectra is one of the critical factors to guarantee confident peptide identification by protein sequence database search in bottom-up proteomics. In an attempt to accurately and comprehensively predict this type of mass spectra, a framework named MS(2)PBPI is proposed. MS(2)PBPI first extracts fragment ions from large-scale MS/MS spectra data sets according to the peptide fragmentation pathways and uses binary trees to divide the obtained bulky data into tens to more than 1000 regions. For each adequate region, stochastic gradient boosting tree regression model is constructed. By constructing hundreds of these models, MS(2)PBPI is able to predict MS/MS spectra for unmodified and modified peptides with reasonable accuracy. Moreover, high consistency between predicted and experimental MS/MS spectra derived from different ion trap instruments with low and high resolving power is achieved. MS(2)PBPI outperforms existing algorithms MassAnalyzer and PeptideART.

Enhancing HMM-based protein profile-profile alignment with structural features and evolutionary coupling information.

BackgroundProtein sequence profile-profile alignment is an important approach to recognizing remote homologs and generating accurate pairwise alignments. It plays an important role in protein sequence database search, protein structure prediction, protein function prediction, and phylogenetic analysis.ResultsIn this work, we integrate predicted solvent accessibility, torsion angles and evolutionary residue coupling information with the pairwise Hidden Markov Model (HMM) based profile alignment method to improve profile-profile alignments. The evaluation results demonstrate that adding predicted relative solvent accessibility and torsion angle information improves the accuracy of profile-profile alignments. The evolutionary residue coupling information is helpful in some cases, but its contribution to the improvement is not consistent.ConclusionIncorporating the new structural information such as predicted solvent accessibility and torsion angles into the profile-profile alignment is a useful way to improve pairwise profile-profile alignment methods.

XGlycScan: An Open-source Software For N-linked Glycosite Assignment, Quantification and Quality Assessment of Data from Mass Spectrometry-based Glycoproteomic Analysis.

Mass spectrometry based glycoproteomics has become a major means of identifying and characterizing previously N-linked glycan attached loci (glycosites). In the bottom-up approach, several factors which include but not limited to sample preparation, mass spectrometry analyses, and protein sequence database searches result in previously N-linked peptide spectrum matches (PSMs) of varying lengths. Given that multiple PSM scan map to a glycosite, we reason that identified PSMs are varying length peptide species of a unique set of glycosites. Because associated spectra of these PSMs are typically summed separately, true glycosite associated spectra counts are lost or complicated. Also, these varying length peptide species complicate protein inference as smaller sized peptide sequences are more likely to map to more proteins than larger sized peptides or actual glycosite sequences. Here, we present XGlycScan. XGlycScan maps varying length peptide species to glycosites to facilitate an accurate quantification of glycosite associated spectra counts. We observed that this reduced the variability in reported identifications of mass spectrometry technical replicates of our sample dataset. We also observed that mapping identified peptides to glycosites provided an assessment of search-engine identification. Inherently, XGlycScan reported glycosites reduce the complexity in protein inference. We implemented XGlycScan in the platform independent Java programing language and have made it available as open source. XGlycScan's source code is freely available at https://bitbucket.org/paiyetan/xglycscan/src and its compiled binaries and documentation can be freely downloaded at https://bitbucket.org/paiyetan/xglycscan/downloads. The graphical user interface version can also be found at https://bitbucket.org/paiyetan/xglycscangui/src and https://bitbucket.org/paiyetan/xglycscangui/downloads respectively.

CUDASW++ 3.0: accelerating Smith-Waterman protein database search by coupling CPU and GPU SIMD instructions

BackgroundThe maximal sensitivity for local alignments makes the Smith-Waterman algorithm a popular choice for protein sequence database search based on pairwise alignment. However, the algorithm is compute-intensive due to a quadratic time complexity. Corresponding runtimes are further compounded by the rapid growth of sequence databases.ResultsWe present CUDASW++ 3.0, a fast Smith-Waterman protein database search algorithm, which couples CPU and GPU SIMD instructions and carries out concurrent CPU and GPU computations. For the CPU computation, this algorithm employs SSE-based vector execution units as accelerators. For the GPU computation, we have investigated for the first time a GPU SIMD parallelization, which employs CUDA PTX SIMD video instructions to gain more data parallelism beyond the SIMT execution model. Moreover, sequence alignment workloads are automatically distributed over CPUs and GPUs based on their respective compute capabilities. Evaluation on the Swiss-Prot database shows that CUDASW++ 3.0 gains a performance improvement over CUDASW++ 2.0 up to 2.9 and 3.2, with a maximum performance of 119.0 and 185.6 GCUPS, on a single-GPU GeForce GTX 680 and a dual-GPU GeForce GTX 690 graphics card, respectively. In addition, our algorithm has demonstrated significant speedups over other top-performing tools: SWIPE and BLAST+.ConclusionsCUDASW++ 3.0 is written in CUDA C++ and PTX assembly languages, targeting GPUs based on the Kepler architecture. This algorithm obtains significant speedups over its predecessor: CUDASW++ 2.0, by benefiting from the use of CPU and GPU SIMD instructions as well as the concurrent execution on CPUs and GPUs. The source code and the simulated data are available at http://cudasw.sourceforge.net.

PfsearchV3: a code acceleration and heuristic to search PROSITE profiles

Summary: The PROSITE resource provides a rich and well annotated source of signatures in the form of generalized profiles that allow protein domain detection and functional annotation. One of the major limiting factors in the application of PROSITE in genome and metagenome annotation pipelines is the time required to search protein sequence databases for putative matches. We describe an improved and optimized implementation of the PROSITE search tool pfsearch that, combined with a newly developed heuristic, addresses this limitation. On a modern x86_64 hyper-threaded quad-core desktop computer, the new pfsearchV3 is two orders of magnitude faster than the original algorithm.Availability and implementation: Source code and binaries of pfsearchV3 are freely available for download at http://web.expasy.org/pftools/#pfsearchV3, implemented in C and supported on Linux. PROSITE generalized profiles including the heuristic cut-off scores are available at the same address.Contact: pftools@isb-sib.ch

Impact of the antiproliferative agent ciclopirox olamine treatment on stem cells proteome

To investigate the proteome changes of stem cells due to ciclopirox olamine (CPX) treatment compared to control and retinoic acid treated cells. Stem cells (SCs) are cells, which have the ability to continuously divide and differentiate into various other kinds of cells. Murine embryonic stem cells (ESCs) and multipotent adult germline stem cells (maGSCs) were treated with CPX, which has been shown to have an antiproliferative effect on stem cells, and compared to stem cells treated with retinoic acid (RA), which is known to have a differentiating effect on stem cells. Classical proteomic techniques like 2-D gel electrophoresis and differential in-gel electrophoresis (DIGE) were used to generate 2D protein maps from stem cells treated with RA or CPX as well as from non-treated stem cells. The resulting 2D gels were scanned and the digitalized images were collated with the help of Delta 2D software. The differentially expressed proteins were analyzed by a MALDI-TOF-TOF mass spectrometer, and the identified proteins were investigated and categorized using bioinformatics. Treatment of stem cells with CPX, a synthetic antifungal clinically used to treat superficial mycoses, resulted in an antiproliferative effect in vitro, without impairment of pluripotency. To understand the mechanisms induced by CPX treatments which results in arrest of cell cycle without any marked effect on pluripotency, a comparative proteomics study was conducted. The obtained data revealed that the CPX impact on cell proliferation was accompanied with a significant alteration in stem cell proteome. By peptide mass fingerprinting and tandem mass spectrometry combined with searches of protein sequence databases, a set of 316 proteins was identified, corresponding to a library of 125 non-redundant proteins. With proteomic analysis of ESCs and maGSCs treated with CPX and RA, we could identify more than 90 single proteins, which were differently expressed in both cell lines. We could highlight, that CPX treatment of stem cells, with subsequent proliferation inhibition, resulted in an alteration of the expression of 56 proteins compared to non-treated cells, and 54 proteins compared to RA treated cells. Bioinformatics analysis of the regulated proteins demonstrated their involvement in various biological processes. To our interest, a number of proteins have potential roles in the regulation of cell proliferation either directly or indirectly. Furthermore the classification of the altered polypeptides according to their main known/postulated functions revealed that the majority of these proteins are involved in molecular functions like nucleotide binding and metal ion binding, and biological processes like nucleotide biosynthetic processes, gene expression, embryonic development, regulation of transcription, cell cycle processes, RNA and mRNA processing. Proteins, which are involved in nucleotide biosynthetic process and proteolysis, were downregulated in CPX treated cells compared to control, as well as in RA treated cells, which may explain the cell cycle arrest. Moreover, proteins which were involved in cell death, positive regulation of biosynthetic process, response to organic substance, glycolysis, anti-apoptosis, and phosphorylation were downregulated in RA treated cells compared to control and CPX treated cells. The CPX treatment of SCs results in downregulation of nucleotide binding proteins and leads to cell cycle stop without impairment of pluripotency.

Phylogenetic Analysis of the Thylakoid ATP/ADP Carrier Reveals New Insights into Its Function Restricted to Green Plants

ATP is the common energy currency of cellular metabolism in all living organisms. Most of them synthesize ATP in the cytosol or on the mitochondrial inner membrane, whereas land plants, algae, and cyanobacteria also produce it on the thylakoid membrane during the light-dependent reactions of photosynthesis. From the site of synthesis, ATP is transported to the site of utilization via intracellular membrane transporters. One major type of ATP transporters is represented by the mitochondrial ADP/ATP carrier family. Here we review a recently characterized member, namely the thylakoid ATP/ADP carrier from Arabidopsis thaliana (AtTAAC). Thus far, no orthologs of this carrier have been characterized in other organisms, although similar sequences can be recognized in many sequenced genomes. Protein Sequence database searches and phylogenetic analyses indicate the absence of TAAC in cyanobacteria and its appearance early in the evolution of photosynthetic eukaryotes. The TAAC clade is composed of carriers found in land plants and some green algae, but no proteins from other photosynthetic taxa, such as red algae, brown algae, and diatoms. This implies that TAAC-like sequences arose only once before the divergence of green algae and land plants. Based on these findings, it is proposed that TAAC may have evolved in response to the need of a new activity in higher photosynthetic eukaryotes. This activity may provide the energy to drive reactions during biogenesis and turnover of photosynthetic complexes, which are heterogeneously distributed in a thylakoid membrane system composed of appressed and non-appressed regions.

An efficient parallelization of phosphorylated peptide and protein identification

Protein sequence database search based on tandem mass spectrometry is an essential method for protein identification. As the computational demand increases, parallel computing has become an important technique for accelerating proteomics data analysis. In this paper, we discuss several factors which could affect the runtime of the pFind search engine and build an estimation model. Based on this model, effective on-line and off-line scheduling methods were developed. An experiment on the public dataset from PhosphoPep consisting of 100 RAW files of phosphopeptides shows that the speedup on 100 processors is 83.7. The parallel version can complete the identification task within 9 min, while a stand-alone process on a single PC takes more than 10 h. On another larger dataset consisting of 1,366,471 spectra, the speedup on 320 processors is 258.9 and the efficiency is 80.9%. Our approach can be applied to other similar search engines.

MS/MS/MS Reveals False Positive Identification of Histone Serine Methylation

Methylation of lysine and arginine residues is known to play a key role in regulating histone structure and function. However, methylation of other amino acid residues in histones has not been previously described. Using exhaustive nano-HPLC/MS/MS and blind protein sequence database searches, we tentatively assigned methylation to serine 28 of histone H3 from calf thymus. The assignment was in agreement with our stringent manual verification rules, coelution in HPLC/MS/MS with its corresponding synthetic peptide, the dynamic nature of such methylation in distinct cell lines, and isotopic labeling. However, careful inspection of the MS/MS and MS/MS/MS spectra of a series of synthetic peptides confirmed that methylation actually occurs on K27 rather than on S28. The misassignment was caused by the fact that the (y(9) + 14) of the putative S28-methylated peptide and (b(9) + 18) ions of the K27 methylated peptide share the same m/z value (m/z 801). This MS/MS peak was used as the major evidence to assign methylation to S28 (consecutive y(8) and (y(9) + 14) ions). MS/MS/MS analysis revealed the false positive nature of serine methylation: the ambiguous ion at m/z 801 is indeed (b(9) + 18), an ion resulting from an in vitro reaction in the gas phase during collisionally activated dissociation (CAD). When lysine (K27) was acetylated, the degree of such in vitro reactions was greatly reduced, and such reactions were completely eliminated when the C-terminus was blocked by carboxylic group derivatization. Moreover, such side-chain assisted C-terminal rearrangement was found to be charge dependent. In aggregate, these results suggest that extra caution should be taken in interpretation of post-translational modification (PTM) data and that MS/MS as well as MS/MS/MS of synthetic peptides are needed for verifying the identity of peptides bearing a novel PTM.

Multipotent Adult Germline Stem Cells and Embryonic Stem Cells: Comparative Proteomic Approach

Spermatogonial stem cells isolated from the adult mouse testis acquire under certain culture conditions pluripotency and become so-called multipotent adult germline stem cells (maGSCs). They can be differentiated into somatic cells of the three germ layers. We investigated a subset of the maGSCs and ESCs proteomes using cell lines derived from two different mouse strains, narrow range immobilized pH gradients to favor the detection of less abundant proteins, and DIGE to ensure confident comparison between the two cell types. 2-D reference maps of maGSCs and ESCs in the pI ranges 3-6 and 5-8 were created, and protein entities were further processed for protein identification. By peptide mass fingerprinting and tandem mass spectrometry combined with searches of protein sequence databases, a set of 409 proteins was identified, corresponding to a library of 166 nonredundant stem cell-associated proteins. The identified proteins were classified according to their main known/postulated functions using bioinformatics. Furthermore, we used DIGE to highlight the ESC-like nature of maGSCs on the proteome scale. We concluded that the proteome of maGSCs is highly similar to that of ESCs as we could identify only a small subset of 18 proteins to be differentially expressed between the two cell types. Moreover, comparative analysis of the cell line proteomes from two different mouse strains showed that the interindividual differences in maGSCs proteomes are minimal. With our study, we created for the first time a proteomic map for maGSCs and compared it to the ESCs proteome from the same mouse. We confirmed on the proteome level the ESC-like nature of maGSCs.