Gas-phase Fractionation Research Articles

High Throughput In Situ DDA Analysis of Neuropeptides by Coupling Novel Multiplex Mass Spectrometric Imaging (MSI) with Gas-Phase Fractionation.

Matrix-assisted laser desorption/ionization (MALDI) mass spectrometric imaging (MSI) is a powerful tool to map the spatial distribution of biomolecules on tissue sections. Recent developments of hybrid MS instruments allow combination of different types of data acquisition by various mass analyzers into a single MSI analysis, which reduces experimental time and sample consumptions. Here, using the well-characterized crustacean nervous system as a test-bed, we explore the utility of high resolution and accurate mass (HRAM) MALDI Orbitrap platform for enhanced in situ characterization of the neuropeptidome with improved chemical information. Specifically, we report on a multiplex-MSI method, which combines HRAM MSI with data dependent acquisition (DDA) tandem MS analysis in a single experiment. This method enables simultaneous mapping of neuropeptide distribution, sequence validation, and novel neuropeptide discovery in crustacean neuronal tissues. To enhance the dynamic range and efficiency of in situ DDA, we introduced a novel approach of fractionating full m/z range into several sub-mass ranges and embedding the setup using the multiplex-DDA-MSI scan events to generate pseudo fractionation before MS/MS scans. The division of entire m/z into multiple segments of m/z sub-ranges for MS interrogation greatly decreased the complexity of molecular species from tissue samples and the heterogeneity of the distribution and variation of intensities of m/z peaks. By carefully optimizing the experimental conditions such as the dynamic exclusion, the multiplex-DDA-MSI approach demonstrates better performance with broader precursor coverage, less biased MS/MS scans towards high abundance molecules, and improved quality of tandem mass spectra for low intensity molecular species. Graphical Abstract ᅟ.

Data from a proteomic baseline study of Assemblage A in Giardia duodenalis.

Eight Assemblage A strains from the protozoan parasite Giardia duodenalis were analysed using label-free quantitative shotgun proteomics, to evaluate inter- and intra-assemblage variation and complement available genetic and transcriptomic data. Isolates were grown in biological triplicate in axenic culture, and protein extracts were subjected to in-solution digest and online fractionation using Gas Phase Fractionation (GPF). Recent reclassification of genome databases for subassemblages was evaluated for database-dependent loss of information, and proteome composition of different isolates was analysed for biologically relevant assemblage-independent variation. The data from this study are related to the research article “Quantitative proteomics analysis of Giardia duodenalis Assemblage A – a baseline for host, assemblage and isolate variation” published in Proteomics (Emery et al., 2015 [1]).

Improved data-dependent acquisition for untargeted metabolomics using gas-phase fractionation with staggered mass range.

The inherently limited MS2 rate of the mass spectrometer is still restricting the performance of data-dependent acquisition (DDA) for untargeted metabolomics. When dealing with the complex metabolome ocean, top-n-based DDA is just scratching the surface as only a small fraction of the ions could be selected for MS2. Here, we report an improved DDA method for untargeted metabolomics using gas-phase fractionation with staggered mass range (sGPF). Unlike the single m/z segment for conventional GPF, the m/z segments for sGPF were narrower, multiplex, and discrete to allow more homogeneous selection of precursor ions in low, medium, and high m/z ranges. This was achieved indirectly by predefining an inclusion list containing multiple discontinuous m/z ranges. Five fraction levels (2, 4, 6, 8, and 10) and two staggering strategies (staggered wide and narrow subsegments (sGPFa and sGPFb)) were compared for characterizing the human urinary metabolites. For both targeted and untargeted comparison, the highest MS2 coverage was obtained by sGPFb8. Targeted comparison of 60 metabolites indicated sGPFb performed the best for 2, 4, 6, and 8 fractions with an increased MS2 triggering rate of 15.0-36.6% over GPF and 6.6-11.7% over sGPFa. For untargeted screening of phase II metabolites and carboxylates, the best performance achieved by sGPFb8 exhibited a 46.9% increase over GPF8 with the increase evenly distributed in glucuronides (54 vs 38), sulfates (55 vs 41), and carboxylates (31 vs 16). Such superiority of sGPF over GPF is mainly due to the reduced number of concurrent precursor ions and increased relative ion intensity ranks.

Systematic optimization of long gradient chromatography mass spectrometry for deep analysis of brain proteome.

The development of high-resolution liquid chromatography (LC) is essential for improving the sensitivity and throughput of mass spectrometry (MS)-based proteomics. Here we present systematic optimization of a long gradient LC–MS/MS platform to enhance protein identification from a complex mixture. The platform employed an in-house fabricated, reverse-phase long column (100 μm × 150 cm, 5 μm C18 beads) coupled to Q Exactive MS. The column was capable of achieving a peak capacity of ∼700 in a 720 min gradient of 10–45% acetonitrile. The optimal loading level was ∼6 μg of peptides, although the column allowed loading as many as 20 μg. Gas-phase fractionation of peptide ions further increased the number of peptide identification by ∼10%. Moreover, the combination of basic pH LC prefractionation with the long gradient LC–MS/MS platform enabled the identification of 96 127 peptides and 10 544 proteins at 1% protein false discovery rate in a post-mortem brain sample of Alzheimer’s disease. Because deep RNA sequencing of the same specimen suggested that ∼16 000 genes were expressed, the current analysis covered more than 60% of the expressed proteome. Further improvement strategies of the LC/LC–MS/MS platform were also discussed.

Enhanced detection and identification in metabolomics by use of LC-MS/MS untargeted analysis in combination with gas-phase fractionation.

Liquid chromatography coupled to tandem mass spectrometry is one of the most widely used analytical platforms for profiling analysis in metabolomics. One weakness of untargeted metabolomic analysis, however, is the difficulty of identifying metabolites. In fact, the process typically involves mass-based searching of LC-MS and LC-MS/MS data and requires using MS/MS data for unequivocal identification. Current strategies use LC-MS analysis in the scan mode prior to acquiring MS/MS information about targeted metabolites or the "auto MS/MS" mode to fragment automatically the most intense precursor ions. Therefore, in both cases additional injections are required to obtain MS/MS data after data treatment to identify significant compounds whose signals are not so intense. Because an additional procedure is needed to enhance the fraction of metabolites with MS/MS data, in this work, the effectiveness of utilizing different MS/MS parameters across an analytical batch or repetitions of the same sample by using exclusion or inclusion criteria to select precursor ions is assessed. The procedure, known as "gas-phase fractionation (GPF)", was used here for untargeted analysis of serum. The joint use of four methods with a different mass range for selection of precursor ions each provided useful MS/MS information for at least 80% of all molecular entities detected in the MS scan replicates. By contrast, the conventional "auto MS/MS" mode of data acquisition provided MS/MS data for only 48-57% of entities and was therefore less effective toward identifying metabolites. The additional use of GPF improved the detection and annotation of metabolite families such as phospholipids, amino acids, bile acids, carnitines, and fatty acids and their derivatives.

Peptidomic Analysis of Antimicrobial Peptides in Skin Secretions ofAmolops mantzorum

Amphibian skin secretions contain abundant bioactive peptides that are valuable natural resources for human beings. However, many amphibians are disappearing from the world, making relevant scientific studies even more important. In this study, 24 cDNA sequences encoding antimicrobial peptide (AMP) precursors were initially cloned by screening a cDNA library derived from the skin of the Sichuan torrent frog, Amolops mantzorum. Eighteen mature AMPs belonging to 11 different families were deduced from these cDNA clones. Biological function was confirmed in each family of these AMPs. Some of them were purified from the skin secretions, and their molecular structures were determined by Edman degradation. Liquid chromatography in conjunction with tandem mass spectrometry (LC-MS/MS)-based peptidomics was used to further confirm the actual presence and characteristics of mature AMPs in the skin secretions of A. mantzorum. Incomplete tryptic digestion and gas-phase fractionation (GPF) analysis were used to increase the peptidome coverage and reproducibility of peptide ion selection.

Identification of multiple antimicrobial peptides from the skin of fine-spined frog, Hylarana spinulosa (Ranidae)

In this study, peptidomics and genomics analyses were used to study antimicrobial peptides from the skin of Hylarana spinulosa. Twenty-nine different antimicrobial peptide precursors were characterized from the skin of H.spinulosa, which produce 23 mature antimicrobial peptides belonging to 12 different families. To confirm the actual presence and characteristics of these antimicrobial peptides in the skin tissue extractions from H.spinulosa, we used two distinct methods, one was peptide purification method that combined gel filtration chromatography and reversed-phase high performance liquid chromatography (RP-HPLC), and the other was peptidomics approach based on liquid chromatography in conjunction with tandem mass spectrometry (LC-MS/MS). In the peptidomics approach, incomplete tryptic digestion and gas-phase fractionation (GPF) analysis were used to increase peptidome coverage and reproducibility of peptide ion selection. Multiple species of microorganisms were chosen to test and analyze the antimicrobial activities and spectrum of these antimicrobial peptides.

Combination of Gas-Phase Fractionation and MS3 Acquisition Modes for Relative Protein Quantification with Isobaric Tagging

Relative quantification of peptides and proteins with isobaric tags such as iTRAQ or TMT is commonly used in comparative quantitative proteomics based on tandem mass spectrometry (MS/MS). Nonetheless, isobaric tagging inherently suffers from the cofragmentation/interference phenomenon that may compromise the quality of the quantitative data. An MS(3) acquisition mode has been recently proposed to address this issue. Because of the additional ion isolation and fragmentation step, the MS(3) acquisition mode significantly alleviates this interference effect. However, MS(3) acquisition exhibits a lower sensitivity and a higher duty cycle, both of which reduce the number of identified and quantified proteins. In the present study, we evaluated the combination of gas-phase fractionation (GPF) and MS(3) acquisition modes to optimize both identification and quantification of tryptic peptides labeled with TMT using a hybrid ion trap-orbitrap (LTQ-OT) instrument. An interference model was used where TMT-labeled human plasma proteolytic digests were spiked with TMT-labeled E. coli proteolytic digests. When combined with GPF, the MS(3) acquisition mode was compared with MS(2) modes such as high-energy collision dissociation (HCD) and combined collision-induced dissociation (CID)/HCD. We demonstrated the benefit of using both GPF and MS(3) to analyze tryptic peptides labeled with TMT in terms of quantification precision and accuracy as well as proteome coverage. We further explored parameters such as the influence of automatic gain control and additional MS(3) scans. The TMT-GPF-MS(3) workflow was shown to be a powerful alternative for quantitative proteomic studies that offers improved identification/quantification accuracy and enhanced proteome coverage without the need for extensive sample fractionation before MS analysis.

Molecular cloning and characterization of antimicrobial peptides from skin of the broad-folded frog, Hylarana latouchii

Seven cDNA sequences encoding antimicrobial peptide (AMP) precursors were cloned by screening the skin-derived cDNA library of the broad-folded frog, Hylarana latouchii. Seven of the deduced peptides are highly similar to AMPs in five families of brevinin-2 (brevinin-2LTa, brevinin-2LTb, and brevinin-2LTc), esculentin-1 (esculentin-1LTa), esculentin-2 (esculentin-2LTa), palustrin-2 (palustrin-2LTa), and temporin (temporin-LTe). The actual sequences and characteristics of mature AMPs were analyzed by RP-HPLC and LC–MS/MS-based proteomics approaches in combination of four different protein digestion processes and by LTQ XL in combination of gas-phase fractionation (GPF) analysis. Moreover, most of the peptides found in this study hardly display hemolytic activity in vitro, suggesting they are promising antimicrobial drug candidates.

Quantitative proteomics of heavy metal stress responses in Sydney rock oysters

Currently, there are few predictive biomarkers in key biomonitoring species, such as oysters, that can detect heavy metal pollution in coastal waterways. Several attributes make oysters superior to other organisms for positive biomonitoring of heavy metal pollution. In particular, they are filter feeders with a high capacity for bioaccumulation. In this study, we used two proteomics approaches, namely label-free shotgun proteomics based on SDS-PAGE gel separation and gas phase fractionation, to investigate the heavy metal stress responses of Sydney rock oysters. Protein samples were prepared from haemolymph of oysters exposed to 100 μg/L of PbCl(2), CuCl(2), or ZnCl(2) for 4 days in closed aquaria. Peptides were identified using a Bivalvia protein sequence database, due to the unavailability of a complete oyster genome sequence. Statistical analysis revealed 56 potential biomarker proteins, as well as several protein biosynthetic pathways to be greatly impacted by metal stress. These have the potential to be incorporated into bioassays for prevention and monitoring of heavy metal pollution in Australian oyster beds. The study confirms that proteomic analysis of biomonitoring species is a promising approach for assessing the effects of environmental pollution, and our experiments have provided insights into the molecular mechanisms underlying oyster stress responses.

Data-independent Proteomic Screen Identifies Novel Tamoxifen Agonist that Mediates Drug Resistance

A label-free quantitative variation of the recently developed data-independent shotgun proteomic method precursor acquisition independent from ion count (PAcIFIC) was used to identify novel proteins implicated in cancer progression and resistance. Specifically, this screen identified the pro-metastatic protein anterior gradient 2 (AGR2) as significantly up-regulated in tamoxifen-treated cells. Highlighting the need for direct proteome profiling methods like PAcIFIC, neither data-dependent gas-phase fractionation nor a transcriptomic screen detected AGR2 protein/transcript at significantly up-regulated levels. Further cell-based experiments using human cancer cell lines and in vivo xenografts confirmed the PAcIFIC hypothesis that AGR2 is up-regulated in MCF-7 cells post tamoxifen treatment and that it is implicated in drug resistance mediation.

A new versatile peptide‐based size exclusion chromatography platform for global profiling and quantitation of candidate biomarkers in hepatocellular carcinoma specimens

Disease biomarkers are predicted to be in low abundance; thus, the most crucial step of biomarker discovery is the efficient fractionation of clinical samples into protein sets that define disease stages and/or predict disease development. For this purpose, we developed a new platform that uses peptide-based size exclusion chromatography (pep-SEC) to quantify disease biomarker candidates. This new platform has many advantages over previously described biomarker profiling platforms, including short run time, high resolution, and good reproducibility, which make it suitable for large-scale analysis. We combined this platform with isotope labeling and label-free methods to identify and quantitate differentially expressed proteins in hepatocellular carcinoma (HCC) tissues. When we combined pep-SEC with a gas phase fractionation method, which broadens precursor ion selection, the protein coverage was significantly increased, which is critical for the global profiling of HCC specimens. Furthermore, pep-SEC-LC-MS/MS analysis enhanced the detection of low-abundance proteins (e.g. insulin receptor substrate 2 and carboxylesterase 1) and glycopeptides in HCC plasma. Thus, our pep-SEC platform is an efficient and versatile pre-fractionation system for the large-scale profiling and quantitation of candidate biomarkers in complex disease proteomes.

Urinary proteomics evaluation in interstitial cystitis/painful bladder syndrome: a pilot study

Interstitial cystitis/painful bladder syndrome (IC/PBS) is characterized by chronic pain, pressure and discomfort felt in the pelvis or bladder. An in-depth shotgun proteomics study was carried out to profile the urinary proteome of women with IC/PBS to identify possible specific proteins and networks associated with IC%PBS. Urine samples from ten female IC/PBS patients and ten female asymptomatic, healthy control subjects were analyzed in quadruplicate by liquid chromatography-tandem mass spectrometry (LC-MS/MS) on a hybrid linear ion trap-orbitrap mass spectrometer. Gas-phase fractionation (GPF) was used to enhance protein identification. Differences in protein quantity were determined by peptide spectral counting. alpha-1B-glycoprotein (A1BG) and orosomucoid-1 (ORM1) were detected in all IC%PBS patients, and > or = 60% of these patients had elevated expression of these two proteins compared to control subjects. Transthyretin (TTR) and hemopexin (HPX) were detected in all control individuals, but > or = 60% of the IC/PBS patients had decreased expression levels of these two proteins. Enrichment functional analysis showed cell adhesion and response to stimuli were down-regulated whereas response to inflammation, wounding, and tissue degradation were up-regulated in IC/PBS. Activation of neurophysiological processes in synaptic inhibition, and lack of DNA damage repair may also be key components of IC%PBS. There are qualitative and quantitative differences between the urinary proteomes of women with and without IC%PBS. We identified a number of proteins as well as pathways%networks that might contribute to the pathology of IC%PBS or result from perturbations induced by this condition.

Precursor Ion Independent Algorithm for Top-Down Shotgun Proteomics

We present a precursor ion independent top-down algorithm (PIITA) for use in automated assignment of protein identifications from tandem mass spectra of whole proteins. To acquire the data, we utilize data-dependent acquisition to select protein precursor ions eluting from a C4-based HPLC column for collision induced dissociation in the linear ion trap of an LTQ-Orbitrap mass spectrometer. Gas-phase fractionation is used to increase the number of acquired tandem mass spectra, all of which are recorded in the Orbitrap mass analyzer. To identify proteins, the PIITA algorithm compares deconvoluted, deisotoped, observed tandem mass spectra to all possible theoretical tandem mass spectra for each protein in a genomic sequence database without regard for measured parent ion mass. Only after a protein is identified, is any difference in measured and theoretical precursor mass used to identify and locate post-translation modifications. We demonstrate the application of PIITA to data generated via our wet-lab approach on a Salmonella typhimurium outer membrane extract and compare these results to bottom-up analysis. From these data, we identify 154 proteins by top-down analysis, 73 of which were not identified in a parallel bottom-up analysis. We also identify 201 unique isoforms of these 154 proteins at a false discovery rate (FDR) of <1%.

Cell Surface and Secreted Protein Profiles of Human Thyroid Cancer Cell Lines Reveal Distinct Glycoprotein Patterns

Cell surface proteins have been shown to be effective therapeutic targets. In addition, shed forms of these proteins and secreted proteins can serve as biomarkers for diseases, including cancer. Thus, identification of cell surface and secreted proteins has been a prime area of interest in the proteomics field. Most cell surface and secreted proteins are known to be glycosylated, and therefore, a proteomics strategy targeting these proteins was applied to obtain proteomic profiles from various thyroid cancer cell lines that represent the range of thyroid cancers of follicular cell origin. In this study, we oxidized the carbohydrates of secreted proteins and those on the cell surface with periodate and isolated them via covalent coupling to hydrazide resin. The glycoproteins obtained were identified from tryptic peptides and N-linked glycopeptides released from the hydrazide resin using two-dimensional liquid chromatography-tandem mass spectrometry in combination with the gas phase fractionation. Thyroid cancer cell lines derived from papillary thyroid cancer (TPC-1), follicular thyroid cancer (FTC-133), Hurthle cell carcinoma (XTC-1), and anaplastic thyroid cancer (ARO and DRO-1) were evaluated. An average of 150 glycoproteins were identified per cell line, of which more than 57% are known cell surface or secreted glycoproteins. The usefulness of the approach for identifying thyroid cancer associated biomarkers was validated by the identification of glycoproteins (e.g., CD44, galectin 3 and metalloproteinase inhibitor 1) that have been found to be useful markers for thyroid cancer. In addition to glycoproteins that are commonly expressed by all of the cell lines, we identified others that are only expressed in the more well-differentiated thyroid cancer cell lines (follicular, Hurthle cell and papillary), or by cell lines derived from undifferentiated tumors that are uniformly fatal forms of thyroid cancer (i.e., anaplastic). On the basis of the results obtained, a set of glycoprotein biomarker candidates for thyroid cancer is proposed.

High-resolution mass spectrometry analysis of protein oxidations and resultant loss of function

MS, with or without pre-analysis peptide fractionation, can be used to decipher the residues on proteins where oxidative modifications caused by peroxynitrite, singlet oxygen or electrophilic lipids have occurred. Peroxynitrite nitrates tyrosine and tryptophan residues on the surface of actin. Singlet oxygen, formed by the interaction of UVA light with tryptophan, can oxidize neighbouring cysteine, histidine, methionine, tyrosine and tryptophan residues. Dose-response inactivation by 4HNE (4-hydroxynonenal) of hBAT (human bile acid CoA:amino acid N-acyltransferase) and CKBB (cytosolic brain isoform of creatine kinase) is associated with site-specific modifications. FT-ICR (Fourier-transform ion cyclotron resonance)-MS using nanoLC (nano-liquid chromatography)-ESI (electrospray ionization)-MS or direct-infusion ESI-MS with gas-phase fractionation identified 14 4HNE adducts on hBAT and 17 on CKBB respectively. At 4HNE concentrations in the physiological range, one member of the catalytic triad of hBAT (His362) was modified; for CKBB, although all four residues in the active site that were modifiable by 4HNE were ultimately modified, only one, Cys283, occurred at physiological concentrations of 4HNE. These results suggest that future in vivo studies should carefully assess the critical sites that are modified rather than using antibodies that do not distinguish between different modified sites.

Genome-Specific Gas-Phase Fractionation Strategy for Improved Shotgun Proteomic Profiling of Proteotypic Peptides

Gas-phase fractionation (GPF) is an efficient and straightforward method to increase proteome coverage. In this report, optimal m/z ranges were calculated based on genomic complexity and experimental data. Then, theoretical precursor ion densities were calculated in silico from various organisms' genomes and found to corroborate the empirical selection of m/z ranges based on ion density mapping. According to both calculations, the choice of m/z range for most efficient GPF coverage in the lower m/z range should be very narrow and increase as m/z value increases. Next, a systematic LC-MS/MS analysis was performed to confirm this observation. The behavior of data-dependent precursor ion selection and the origin of the observed variability was investigated under three different scan modes of an LTQ-Orbitrap hybrid mass spectrometer. Finally, GPF combined with data-dependent analysis was compared to a targeted, pseudo-multiple reaction monitoring analysis of proteotypic peptides that should be, based on empirical observation of LC-ESI-MS/MS data, detectable. The result of the latter experiment supported our conclusion that data-dependent analysis using rational gas-phase fractionation was sufficient for comprehensive proteomic analysis of the proteotypic peptides in an unfractionated cell lysate.

Toward a global characterization of the phosphoproteome in prostate cancer cells: Identification of phosphoproteins in the LNCaP cell line

Protein phosphorylation plays a major role in most cell-signaling pathways in all eukaryotic cells. Disruptions in phosphorylation-mediated cell-signaling events are associated with various diseases, including cancer. Here, we applied a fully non-gel-based methodology to obtain an initial panel of phosphoproteins from the LNCaP human prostate cancer cell line. The analytical strategy involved enrichment of phosphopeptides by immobilized metal ion affinity chromatography, the use of POROS Oligo R3 to capture phosphopeptides that were not retained with a C18 packing, and gas-phase fractionation in the m/z dimension to extend the dynamic range of the LC-MS/MS analysis. In this pilot investigation, 137 phosphorylation sites in 81 phosphoproteins were identified. The characterized phosphoproteins include kinases, co-regulators of steroid receptors, and a number of cancer-related proteins.

Improved Validation of Peptide MS/MS Assignments Using Spectral Intensity Prediction

A major limitation in identifying peptides from complex mixtures by shotgun proteomics is the ability of search programs to accurately assign peptide sequences using mass spectrometric fragmentation spectra (MS/MS spectra). Manual analysis is used to assess borderline identifications; however, it is error-prone and time-consuming, and criteria for acceptance or rejection are not well defined. Here we report a Manual Analysis Emulator (MAE) program that evaluates results from search programs by implementing two commonly used criteria: 1) consistency of fragment ion intensities with predicted gas phase chemistry and 2) whether a high proportion of the ion intensity (proportion of ion current (PIC)) in the MS/MS spectra can be derived from the peptide sequence. To evaluate chemical plausibility, MAE utilizes similarity (Sim) scoring against theoretical spectra simulated by MassAnalyzer software (Zhang, Z. (2004) Prediction of low-energy collision-induced dissociation spectra of peptides. Anal. Chem. 76, 3908-3922) using known gas phase chemical mechanisms. The results show that Sim scores provide significantly greater discrimination between correct and incorrect search results than achieved by Sequest XCorr scoring or Mascot Mowse scoring, allowing reliable automated validation of borderline cases. To evaluate PIC, MAE simplifies the DTA text files summarizing the MS/MS spectra and applies heuristic rules to classify the fragment ions. MAE output also provides data mining functions, which are illustrated by using PIC to identify spectral chimeras, where two or more peptide ions were sequenced together, as well as cases where fragmentation chemistry is not well predicted.

Analysis of Complex Protein Mixtures with Improved Sequence Coverage Using (CE−MS/MS)n

Identification of proteins, in a complex protein mixture, using one-dimensional high-performance liquid chromatography tandem mass spectrometry (HPLC-MS/MS) analysis of its digest, usually suffers from low sequence coverage. There are several reasons for the low coverage including undersampling, wide concentration dynamic range of the proteins in a complex protein mixture, and wide range of electrospray ionization efficiency of peptides under each mobile-phase composition. To address this low sequence coverage, we introduce a novel technique, (CE-MS/MS)n, which utilizes the most significant advantages of CE-MS/MS, including economy of sample size, fast analysis time, and high separation efficiency, to increase the sequence coverage of a complex protein mixture. Based on these characteristics, (CE-MS/MS)n can be performed in which multiple CE-MS/MS subanalyses (injections followed by analyses) are analyzed and experimental variables are manipulated during each CE-MS/MS subanalysis in order to maximize sequence coverage. (CE-MS/MS)n is a practical technique since each CE-MS/MS subanalysis consumes <10 nL, and each CE-MS/MS subanalysis takes approximately 10 min; therefore, several subanalyses can be performed in approximately 1 h consuming only nanoliters of the sample. Two techniques have been introduced to address the undersampling: (1) (CE-MS/MS)n using dynamic exclusion. In this technique, several CE-MS/MS analyses (injection followed by separation) were performed in one run using the dynamic exclusion capability of the mass spectrometer until all peptide peaks were analyzed by MS/MS. (2) Gas-phase fractionation. In this technique, (CE-MS/MS)n is performed by scanning a narrow mass range (every approximately 100 m/z) during each CE-MS/MS subanalysis without using dynamic exclusion. Under this condition, in each subanalysis, the number of peptides available for MS/MS analysis is significantly reduced, and peptides with the same nominal masses are analyzed, thereby increasing sequence coverage. Additionally, to address the lack of detection of low-level peptides in a mixture containing a wide concentration dynamic range, the concentration of the sample was systematically increased in each subanalysis (while utilizing dynamic exclusion) so that low-intensity peptides would rise above the mass spectrometer threshold and, consequently, undergo MS/MS analysis. Moreover, to alter the ionization efficiency of peptides with low electrospray ionization efficiency, and to change the migration behavior of comigrating peptides under a specific liquid composition, the CE background electrolyte was modified in several subanalyses to further improve sequence coverage. The combination of the above-mentioned techniques was applied to the analysis of the tryptic digests of three well-characterized protein mixtures: a six-protein mixture with average MW of approximately 26,000 (standard I), a six-protein mixture with an average MW approximately 49,000 (standard II), and a more complex protein mixture containing 55 proteins (E. coli ribosomal proteins). In approximately 1 h, when the MS/MS of the peptides were manually checked, all peptides that produced peaks under electrospray ionization in the scanned range of the analysis (500-2000 m/z) and within the practical fragmentation capability of the MS (peptides with MW <3500) were identified for standard I by consuming only 200 fmol of each protein. When searched against a Swissprot database, the average sequence coverage for the standard I, II, and E. coli's ribosomal proteins were 57, 34, and 15%, respectively.