Characterisation of glycoproteins using a quadrupole time-of-flight mass spectrometer configured for electron transfer dissociation

RATIONALE

Electron transfer dissociation (ETD) within ion trapping mass spectrometers has proven to be a useful tool for the characterisation of post-translational modifications. In this study, we describe the implementation of ETD upon a modified quadrupole time-of-flight (Q-ToF) system and methods for the analysis of glycoproteins.

METHODS

Liquid chromatography electrospray ionisation mass spectrometry (LC/ESI-MS) was performed using a hybrid quadrupole/ion mobility/oa-ToF mass spectrometer equipped with ETD functionality. 1,4-Dicyanobenzene reagent anions necessary for the ETD reaction were generated from a glow discharge region located within the ESI source block. ETD reactions occurred in the stacked ring travelling wave ion guide (located after the quadrupole mass filter and prior to the oa-ToF mass analyser). LC/ETD was performed upon 'super-charged' tryptic glycopeptide ions produced from the recombinant monoclonal antibody trastuzumab. LC/ETD was also performed on ions from the smaller glycopeptides obtained from erythropoietin.

RESULTS

ETD performed upon the quadruply 'super-charged' N-linked glycopeptide ions of trastuzumab and the triply charged O-linked glycopeptide ions of erythropoietin provided both glycosylation site assignments and full sequence information, respectively. Tandem mass (MS/MS) spectra employing collision-induced dissociation (CID) were dominated by oxonium product ions hampering full peptide sequence characterisation.

CONCLUSIONS

LC/ETD on the Q-ToF system proved effective at characterising a number of different N-linked glyco-forms of the tryptic peptide, EEQYNSTYR, from trastuzumab as well as glyco-forms from the O-linked tryptic peptide, EASIPPDAASAAPLR, from erythropoietin. The data demonstrates that the glycopeptide site heterogeneity of trastuzumab and erythropoietin can be accurately characterised. In addition, the post-column mixing of the super-charging reagent, m-NBA, is an effective method to increase the precursor ion charge state and to improve ETD reaction efficiency.

Design and application of a data-independent precursor and product ion repository

The functional design and application of a data-independent LC-MS precursor and product ion repository for protein identification, quantification, and validation is conceptually described. The ion repository was constructed from the sequence search results of a broad range of discovery experiments investigating various tissue types of two closely related mammalian species. The relative high degree of similarity in protein complement, ion detection, and peptide and protein identification allows for the analysis of normalized precursor and product ion intensity values, as well as standardized retention times, creating a multidimensional/orthogonal queryable, qualitative, and quantitative space. Peptide ion map selection for identification and quantification is primarily based on replication and limited variation. The information is stored in a relational database and is used to create peptide- and protein-specific fragment ion maps that can be queried in a targeted fashion against the raw or time aligned ion detections. These queries can be conducted either individually or as groups, where the latter affords pathway and molecular machinery analysis of the protein complement. The presented results also suggest that peptide ionization and fragmentation efficiencies are highly conserved between experiments and practically independent of the analyzed biological sample when using similar instrumentation. Moreover, the data illustrate only minor variation in ionization efficiency with amino acid sequence substitutions occurring between species. Finally, the data and the presented results illustrate how LC-MS performance metrics can be extracted and utilized to ensure optimal performance of the employed analytical workflows.

A probabilistic framework for peptide and protein quantification from data-dependent and data-independent LC-MS proteomics experiments

A probability-based quantification framework is presented for the calculation of relative peptide and protein abundance in label-free and label-dependent LC-MS proteomics data. The results are accompanied by credible intervals and regulation probabilities. The algorithm takes into account data uncertainties via Poisson statistics modified by a noise contribution that is determined automatically during an initial normalization stage. Protein quantification relies on assignments of component peptides to the acquired data. These assignments are generally of variable reliability and may not be present across all of the experiments comprising an analysis. It is also possible for a peptide to be identified to more than one protein in a given mixture. For these reasons the algorithm accepts a prior probability of peptide assignment for each intensity measurement. The model is constructed in such a way that outliers of any type can be automatically reweighted. Two discrete normalization methods can be employed. The first method is based on a user-defined subset of peptides, while the second method relies on the presence of a dominant background of endogenous peptides for which the concentration is assumed to be unaffected. Normalization is performed using the same computational and statistical procedures employed by the main quantification algorithm. The performance of the algorithm will be illustrated on example data sets, and its utility demonstrated for typical proteomics applications. The quantification algorithm supports relative protein quantification based on precursor and product ion intensities acquired by means of data-dependent methods, originating from all common isotopically-labeled approaches, as well as label-free ion intensity-based data-independent methods.

Asymmetric proteome equalization of the skeletal muscle proteome using a combinatorial hexapeptide library

Immobilized combinatorial peptide libraries have been advocated as a strategy for equalization of the dynamic range of a typical proteome. The technology has been applied predominantly to blood plasma and other biological fluids such as urine, but has not been used extensively to address the issue of dynamic range in tissue samples. Here, we have applied the combinatorial library approach to the equalization of a tissue where there is also a dramatic asymmetry in the range of abundances of proteins; namely, the soluble fraction of skeletal muscle. We have applied QconCAT and label-free methodology to the quantification of the proteins that bind to the beads as the loading is progressively increased. Although some equalization is achieved, and the most abundant proteins no longer dominate the proteome analysis, at high protein loadings a new asymmetry of protein expression is reached, consistent with the formation of complex assembles of heat shock proteins, cytoskeletal elements and other proteins on the beads. Loading at different ionic strength values leads to capture of different subpopulations of proteins, but does not completely eliminate the bias in protein accumulation. These assemblies may impair the broader utility of combinatorial library approaches to the equalization of tissue proteomes. However, the asymmetry in equalization is manifest at either low and high ionic strength values but manipulation of the solvent conditions may extend the capacity of the method.

Qualitative and quantitative multiplexed proteomic analysis of complex yeast protein fractions that modulate the assembly of the yeast prion Sup35p

Background

The aggregation of the baker's yeast prion Sup35p is at the origin of the transmissible [PSI⁺] trait. We and others have shown that molecular chaperones modulate Sup35p aggregation. However, other protein classes might be involved in [PSI⁺] formation.

Results

We designed a functional proteomic study that combines two techniques to identify modulators of Sup35p aggregation and describe the changes associated to [PSI⁺] formation. The first allows measuring the effect of fractionated Saccharomyces cerevisiae cytosolic extracts from [PSI⁺] and [psi⁻] yeast cells on Sup35p assembly. The second is a multiplex qualitative and quantitative comparison of protein composition of active and inactive fractions using a gel-free and label-free LC-MS approach. We identify changes in proteins involved in translation, folding, degradation, oxido-reduction and metabolic processes.

Conclusion

Our functional proteomic study provides the first inventory list of over 300 proteins that directly or indirectly affect Sup35p aggregation and [PSI⁺] formation. Our results highlight the complexity of the cellular changes accompanying [PSI⁺] formation and pave the way for in vitro studies aimed to document the effect of individual and/or combinations of proteins identified here, susceptible of affecting Sup35p assembly.

Plasma biomarker identification in S-adenosylhomocysteine hydrolase deficiency

S-Adenosylhomocysteine hydrolase (AHCY) deficiency is a rare congenital disorder in methionine metabolism clinically characterized by white matter atrophy, delayed myelination, slowly progressive myopathy, retarded psychomotor development and mildly active chronic hepatitis. In the present study, we utilized a comparative proteomics strategy based on 2-DE/MALDI-MS and LC/ESI-MS to analyze plasma proteins from three AHCY-deficient patients prior to and after receiving dietary treatment designed to alleviate disease symptoms. Obtained results revealed candidate biomarkers for the detection of myopathy specifically associated with AHCY deficiency, such as carbonic anhydrase 3, creatine kinase, and thrombospondin 4. Several proteins mediating T-cell activation and function were identified as well, including attractin and diacylglycerol kinase α. Further validation and functional analysis of identified proteins with clinical value would ensure that these biomarkers make their way into routine diagnosis and management of AHCY deficiency.

Quantitative neuroproteomics: classical and novel tools for studying neural differentiation and function

Mechanisms underlying neural stem cell proliferation, differentiation and maturation play a critical role in the formation and wiring of neuronal connections. This process involves the activation of multiple serial events, which guide the undifferentiated cells to different lineages via distinctive developmental programs, forming neuronal circuits and thus shaping the adult nervous system. Furthermore, alterations within these strictly regulated pathways can lead to severe neurological and psychiatric diseases. In this framework, the investigation of the high dynamic protein expression changes and other factors affecting protein functions, for example post-translational modifications, the alterations of protein interaction networks, is of pivotal importance for the understanding of the molecular mechanisms responsible for cell differentiation. More recently, proteomic studies in neuroscience ("neuroproteomics") are receiving increased interest for the primary understanding of the regulatory networks underlying neuronal differentiation processes. Besides the classical two-dimensional-based proteomic strategies, the emerging platforms for LC-MS shotgun proteomic analysis hold great promise in unraveling the molecular basis of neural stem cell differentiation. In this review, recent advancements in label-free LC-MS quantitative neuroproteomics are highlighted as a new tool for the study of neural differentiation and functions, in comparison to mass spectrometry-based labeling approaches. The more commonly used protein profiling strategies and model systems for the analysis of neural differentiation are also discussed, along with the challenging proteomic approaches aimed to analyze the nervous system-specific organelles, the neural cells secretome and the specific protein interaction networks.

Towards a proteome signature for invasive ductal breast carcinoma derived from label-free nanoscale LC-MS protein expression profiling of tumorous and glandular tissue

As more and more alternative treatments become available for breast carcinoma, there is a need to stratify patients and individual molecular information seems to be suitable for this purpose. In this study, we applied label-free protein quantitation by nanoscale LC-MS and investigated whether this approach could be used for defining a proteome signature for invasive ductal breast carcinoma. Tissue samples from healthy breast and tumor were collected from three patients. Protein identifications were based on LC-MS peptide fragmentation data which were obtained simultaneously to the quantitative information. Hereby, an invasive ductal breast carcinoma proteome signature was generated which contains 60 protein entries. The on-column concentrations for osteoinductive factor, vimentin, GAP-DH, and NDKA are provided as examples. These proteins represent distinctive gene ontology groups of differentially expressed proteins and are discussed as risk markers for primary tumor pathogenesis. The developed methodology has been found well applicable in a clinical environment in which standard operating procedures can be kept; a prerequisite for the definition of molecular parameter sets that shall be capable for stratification of patients.

The detection, correlation, and comparison of peptide precursor and product ions from data independent LC-MS with data dependant LC-MS/MS

The detection, correlation, and comparison of peptide and product ions from a data independent LC-MS acquisition strategy with data dependent LC-MS/MS is described. The data independent mode of acquisition differs from an LC-MS/MS data acquisition since no ion transmission window is applied with the first mass analyzer prior to collision induced disassociation. Alternating the energy applied to the collision cell, between low and elevated energy, on a scan-to-scan basis, provides accurate mass precursor and associated product ion spectra from every ion above the LOD of the mass spectrometer. The method therefore provides a near 100% duty cycle, with an inherent increase in signal intensity due to the fact that both precursor and product ion data are collected on all isotopes of every charge-state across the entire chromatographic peak width. The correlation of product to precursor ions, after deconvolution, is achieved by using reconstructed retention time apices and chromatographic peak shapes. Presented are the results from the comparison of a simple four protein mixture, in the presence and absence of an enzymatically digested protein extract from Escherichia coli. The samples were run in triplicate by both data dependant analysis (DDA) LC-MS/MS and data-independent, alternate scanning LC-MS. The detection and identification of precursor and product ions from the combined DDA search results of the four protein mixture were used for comparison to all other data. Each individual set of data-independent LC-MS data provides a more comprehensive set of detected ions than the combined peptide identifications from the DDA LC-MS/MS experiments. In the presence of the complex E. coli background, over 90% of the monoisotopic masses from the combined LC-MS/MS identifications were detected at the appropriate retention time. Moreover, the fragmentation pattern and number of associated elevated energy product ions in each replicate experiment was found to be very similar to the DDA identifications. In the case of the corresponding individual DDA LC-MS/MS experiment, 43% of the possible detectable peptides of interest were identified. The presented data illustrates that the time-aligned data from data-independent alternate scanning LC-MS experiments is highly comparable to the data obtained via DDA. The obtained information can therefore be effectively and correctly deconvolved to correlate product ions with parent precursor ions. The ability to generate precursor-product ion tables from this information and subsequently identify the correct parent precursor peptide will be illustrated in a companion manuscript.

Nonionic detergent phase extraction for the proteomic analysis of heart membrane proteins using label-free LC-MS

Heart diseases resulting in heart failure are among the leading causes of morbidity and mortality in the Western world and can result from either systemic disease (e.g., hypertensive heart disease, ischemic heart disease) or specific heart muscle disease (e.g., dilated cardiomyopathy/DCM). Subproteome analysis of such disease subsets affords a reduction in sample complexity, potentially revealing biomarkers of cardiac failure that would otherwise remain undiscovered in proteome wide studies. Label-free nanoscale LC-MS has been applied in this study to validate a Triton X-114-based phase enrichment method for cardiac membrane proteins. Annotation of the subcellular location combined with GRAVY score analysis indicates a clear separation between soluble and membrane-bound proteins with an enrichment of over 62% for this protein subset. LC-MS allowed confident identification and annotation of hydrophobic proteins in this control sample pilot study and demonstrates the power of the proposed technique to extract integral membrane-bound proteins. This approach should be applicable to a wider scale study of disease-associated changes in the cardiac membrane subproteome.

Analysis and quantification of diagnostic serum markers and protein signatures for Gaucher disease

Novel approaches for the qualitative and quantitative proteomics analysis by nanoscale LC-MS applied to the study of protein expression response in depleted and undepleted serum of Gaucher patients undergoing enzyme replacement therapy are presented. Particular emphasis is given to the method reproducibility of these LC-MS experiments without the use of isotopic labels. The level of chitotriosidase, an established Gaucher biomarker, was assessed by means of an absolute concentration determination technique for alternate scanning LC-MS generated data. Disease associated proteins, including fibrinogens, complement cascade proteins, and members of the high density lipoprotein serum content, were recognized by various clustering methods and sorting and intensity profile grouping of identified peptides. Condition-unique LC-MS protein signatures could be generated utilizing the measured serum protein concentrations and are presented for all investigated conditions. The clustering results of the study were also used as input for gene ontology searches to determine the correlation between the molecular functions of the identified peptides and proteins.

Alignment and statistical difference analysis of complex peptide data sets generated by multidimensional LC-MS

A method for high-resolution proteomics analyses of complex protein mixtures is presented using multidimensional HPLC coupled to MS (MDLC-MS). The method was applied to identify proteins that are differentially expressed during fruit ripening of tomato. Protein extracts from red and green tomato fruits were digested by trypsin. The resulting highly complex peptide mixtures were separated by strong cation exchange chromatography (SCX), and subsequently analyzed by RP nano-LC coupled to quadrupole-TOF MS. For detailed quantitative comparison, triplicate RP-LC-MS runs were performed for each SCX fraction. The resulting data sets were analyzed using MetAlign software for noise and data reduction, multiple alignment and statistical variance analysis. For each RP-LC-MS chromatogram, up to 7000 mass components were detected. Peak intensity data were compared by multivariate and statistical analysis. This revealed a clear separation between the green and red tomato samples, and a clear separation of the different SCX fractions. MS/MS spectra were collected using the data-dependent acquisition mode from a selected set of differentially detected peptide masses, enabling the identification of proteins that were differentially expressed during ripening of tomato fruits. Our approach is a highly sensitive method to analyze proteins in complex mixtures without the need of isotope labeling.

Absolute quantification of proteins by LCMSE: a virtue of parallel MS acquisition

Relative quantification methods have dominated the quantitative proteomics field. There is a need, however, to conduct absolute quantification studies to accurately model and understand the complex molecular biology that results in proteome variability among biological samples. A new method of absolute quantification of proteins is described. This method is based on the discovery of an unexpected relationship between MS signal response and protein concentration: the average MS signal response for the three most intense tryptic peptides per mole of protein is constant within a coefficient of variation of less than +/-10%. Given an internal standard, this relationship is used to calculate a universal signal response factor. The universal signal response factor (counts/mol) was shown to be the same for all proteins tested in this study. A controlled set of six exogenous proteins of varying concentrations was studied in the absence and presence of human serum. The absolute quantity of the standard proteins was determined with a relative error of less than +/-15%. The average MS signal responses of the three most intense peptides from each protein were plotted against their calculated protein concentrations, and this plot resulted in a linear relationship with an R(2) value of 0.9939. The analyses were applied to determine the absolute concentration of 11 common serum proteins, and these concentrations were then compared with known values available in the literature. Additionally within an unfractionated Escherichia coli lysate, a subset of identified proteins known to exist as functional complexes was studied. The calculated absolute quantities were used to accurately determine their stoichiometry.

A proteome approach defines protective functions of tobacco leaf trichomes

The leaf surface of most terrestrial plants is covered with plant hairs called trichomes. These epidermal appendages are thought to contribute to many aspects of plant defense against biotic and abiotic stresses in a variety of species. Trichome development has been intensively studied in Arabidopsis, and the phytochemical composition of trichomes was analyzed in a number of plant species. However, comparatively little is known of the proteins expressed. We therefore initiated a proteome approach to better define the cellular mechanisms operating in plant trichomes using two-dimensional gel electrophoresis to separate proteins of whole leaves and isolated trichomes. Tobacco was chosen due to the presence of glandular trichomes involved in the secretion of defense compounds. Comparative image analysis of the protein patterns indicated a number of spots, which were highly enriched in trichomes relative to leaves. These spots were excised for identification by mass spectrometry. The results showed that among the proteins specifically enriched in trichomes, the components of stress defense responses were strongly represented. The high expression of stress-related proteins was verified by Western blotting. Superoxide dismutase isoforms were additionally analyzed by activity staining. Our results demonstrate feasibility of the proteome approach to elucidate the cell biology of plant trichomes.

Survey of bacterial proteins released in cheese: a proteomic approach

During the ripening of Emmental cheese, the bacterial ecosystem confers its organoleptic characteristics to the evolving curd both by the action of the living cells, and through the release of numerous proteins, including various types of enzymes into the cheese when the cells lyse. In Emmental cheese these proteins can be released from thermophilic lactic acid bacteria used as starters like Lactobacillus helveticus, Lb delbruecki subsp. lactis and Streptococcus salivarius subsp. thermophilus and ripening bacteria such as Propionibacterium freudenreichii. The aim of this study was to obtain a proteomic view of the different groups of proteins within the cheese using proteomic tools to create a reference map. A methodology was therefore developed to reduce the complexity of cheese matrix prior to 2D-PAGE analysis. The aqueous phase of cheese was prefractionated by size exclusion chromatography, bacterial and milk proteins were separated and subsequently characterised by mass spectrometry, prior to peptide mass fingerprint and sequence homology database search. Five functional groups of proteins were identified involved in: (i) proteolysis, (ii) glycolysis, (iii) stress response, (iv) DNA and RNA repair and (v) oxidoreduction. The results revealed stress responses triggered by thermophilic lactic acid bacteria and Propionibacterium strains at the end of ripening. Information was also obtained regarding the origin and nature of the peptidases released into the cheese, thus providing a greater understanding of casein degradation mechanisms during ripening. Different peptidases arose from St thermophilus and Lb helveticus, suggesting that streptococci are involved in peptide degradation in addition to the proteolytic activity of lactobacilli.

Mass spectrometry proteomic analysis of stress adaptation reveals both common and distinct response pathways in Propionibacterium freudenreichii

Microorganisms used in food technology and probiotics are exposed to technological and digestive stresses, respectively. Traditionally used as Swiss-type cheese starters, propionibacteria also constitute promising human probiotics. Stress tolerance and cross-protection in Propionibacterium freudenreichii were thus examined after exposure to heat, acid, or bile salts stresses. Adapted cells demonstrated acquired homologous tolerance. Cross-protection between bile salts and heat adaptation was demonstrated. By contrast, bile salts pretreatment sensitized cells to acid challenge and vice versa. Surprisingly, heat and acid responses did not present significant cross-protection in P. freudenreichii. During adaptations, important changes in cellular protein synthesis were observed using two-dimensional electrophoresis. While global protein synthesis decreased, several proteins were overexpressed during stress adaptations. Thirty-four proteins were induced by acid pretreatment, 34 by bile salts pretreatment, and 26 by heat pretreatment. Six proteins are common to all stresses and represent general stress-response components. Among these polypeptides, general stress chaperones, and proteins involved in energetic metabolism, oxidative stress response, or SOS response were identified. These results bring new insight into the tolerance of P. freudenreichii to heat, acid, and bile salts, and should be taken into consideration in the development of probiotic preparations.

Binding of the AVR4 elicitor of Cladosporium fulvum to chitotriose units is facilitated by positive allosteric protein-protein interactions: the chitin-binding site of AVR4 represents a novel binding site on the folding scaffold shared between the invertebrate and the plant chitin-binding domain

The attack of fungal cell walls by plant chitinases is an important plant defense response to fungal infection. Anti-fungal activity of plant chitinases is largely restricted to chitinases that contain a noncatalytic, plant-specific chitin-binding domain (ChBD) (also called Hevein domain). Current data confirm that the race-specific elicitor AVR4 of the tomato pathogen Cladosporium fulvum can protect fungi against plant chitinases, which is based on the presence of a novel type of ChBD in AVR4 that was first identified in invertebrates. Although these two classes of ChBDs (Hevein and invertebrate) are sequentially unrelated, they share structural homology. Here, we show that the chitin-binding sites of these two classes of ChBDs have different topologies and characteristics. The K(D), DeltaH, and DeltaS values obtained for the interaction between AVR4 and chito-oligomers are comparable with those obtained for Hevein. However, the binding site of AVR4 is larger than that of Hevein, i.e. AVR4 interacts strictly with chitotriose, whereas Hevein can also interact with the monomer N-acetylglucosamine. Moreover, binding of additional AVR4 molecules to chitin occurs through positive cooperative protein-protein interactions. By this mechanism AVR4 is likely to effectively shield chitin on the fungal cell wall, preventing the cell wall from being degraded by plant chitinases.

Surface and wastewater quality monitoring: combination of liquid chromatography with (geno)toxicity detection, diode array detection and tandem mass spectrometry for identification of pollutants

Identification of unknown water pollutants with liquid chromatography and tandem mass spectrometry (LC-MS-MS) is often more complex and time consuming than identification with gas chromatography and mass spectrometry (GC-MS). In order to focus the identification effort on relevant compounds, unknown peaks need to be selected carefully. Based on its frequency of occurrence in the LC-Diode Array Detection (LC-DAD) chromatograms of surface and infiltrated waters, an unknown peak was selected for identification with LC-MS-MS. This compound was identified as hexamethoxymethylmelamine (HMMM), a chemical often used in the coating industry. This is the first time the presence of this chemical in surface waters has been reported. In addition to HMMM, two other structurally related compounds were found to be present in the investigated surface water. A standard mixture of HMMM and its by-products did not exhibit (geno)toxicity under the test conditions applied in this study. In another example, a genotoxic fraction of an industrial wastewater was isolated and examined by LC-MS-MS using a modern quadrupole-orthogonal acceleration-time-of-flight mass spectrometer (Q-TOF). Four compounds were detected. The structures of two compounds present are proposed to be 9-amino-2-hydroxy-acridine and 9-hydroxy-acridine-N-oxide or its structural isomer dihydroxy-acridine. Confirmation with standards could not be carried out, as pure compounds are not available. The other two compounds (structural isomers) could not be identified based on the data available within this study.

A novel precursor ion discovery method on a hybrid quadrupole orthogonal acceleration time-of-flight (Q-TOF) mass spectrometer for studying protein phosphorylation

A tandem quadrupole time-of-flight (Q-TOF) mass spectrometer has been programmed such that phosphorylated peptides can automatically be discovered and identified in a way similar to that of the use of precursor ion or neutral loss scanning, but without the need to scan the quadrupole mass filter. Instead, the method capitalizes on the innate capability of the Q-TOF to record mass spectra and product ion spectra quickly, with good sensitivity and with good mass accuracy. Alternate mass spectra, with and without fragmentation, are recorded at high and low collision energy with the quadrupole operating in wideband mode. The method of analysis is both compatible with and dependant on liquid chromatography for separation of complex mixtures. The method has been demonstrated by searching for the neutral loss of 98 Da (H3PO4) from phosphoserine and phosphothreonine residues, or for the phosphorylated immonium ion at m/z 216 from phosphotyrosine. The method also incorporates acquisition of the product ion spectrum from any candidate precursor ions, thereby allowing confirmation of the neutral loss or product ion and providing additional sequence information to assist identification of the protein and assign the site of phosphorylation.

A novel interface for variable flow nanoscale LC/MS/MS for improved proteome coverage

A variable flow "peak trapping" liquid chromatography (LC) interface has been developed for the coupling of nanoscale LC to electrospray ionization mass spectrometry (ESI-MS). The presented peak trapping LC interface allows for the extended analysis time of co-eluting compounds and has been employed for the identification of proteins via tandem mass spectrometry (MS/MS). The variable flow process can be controlled either manually or in a completely automated manner where the mass spectrometer status determines the status of the variable flow interface. When the mass spectrometer operates in MS survey mode, the interface is operated in a so-called "high-flow" mode. Alternatively, the interface is operated in a "low-flow" mode during MS/MS analysis. In the "high-flow" mode of the variable flow process the column flow rate is typically around 200 nL/min, whereas in the "low-flow" mode the column effluent is introduced into the source of the mass spectrometer at 25 nL/min. In addition to the flow reduction during MS/MS analysis, the gradient is paused to preserve the peptide separation on the analytical nanoscale LC column. The performance of the variable flow nanoscale LC/MS/MS interface is demonstrated by the automated analysis of standard peptide mixtures and protein digests utilizing variable flow, data-dependent scanning MS/MS techniques, and automated database searching.