Optimization of reversed-phase peptide liquid chromatography ultraviolet mass spectrometry analyses using an automated blending methodology.

The balance between chromatographic performance and mass spectrometric response has been evaluated using an automated series of experiments where separations are produced by the real-time automated blending of water with organic and acidic modifiers. In this work, the concentration effects of two acidic modifiers (formic acid and trifluoroacetic acid) were studied on the separation selectivity, ultraviolet, and mass spectrometry detector response, using a complex peptide mixture. Peptide retention selectivity differences were apparent between the two modifiers, and under the conditions studied, trifluoroacetic acid produced slightly narrower (more concentrated) peaks, but significantly higher electrospray mass spectrometry suppression. Trifluoroacetic acid suppression of electrospray signal and influence on peptide retention and selectivity was dominant when mixtures of the two modifiers were analyzed. Our experimental results indicate that in analyses where the analyzed components are roughly equimolar (e.g., a peptide map of a recombinant protein), the selectivity of peptide separations can be optimized by choice and concentration of acidic modifier, without compromising the ability to obtain effective sequence coverage of a protein. In some cases, these selectivity differences were explored further, and a rational basis for differentiating acidic modifier effects from the underlying peptide sequences is described.     

High sensitivity LC-MS profiling of antibody-drug conjugates with difluoroacetic acid ion pairing

ABSTRACT

Reversed-phase liquid chromatography (RPLC) separations of proteins using optical detection generally use trifluoroacetic acid (TFA) because it is a strong, hydrophobic acid and a very effective ion-pairing agent for minimizing chromatographic secondary interactions. Conversely and in order to avoid ion suppression, analyses entailing mass spectrometry (MS) detection is often performed with a weaker ion-pairing modifier, like formic acid (FA), but resolution quality may be reduced. To gain both the chromatographic advantages of TFA and the enhanced MS sensitivity of FA, we explored the use of an alternative acid, difluoroacetic acid (DFA). This acid modifier is less acidic and less hydrophobic than TFA and is believed to advantageously affect the surface tension of electrospray droplets. Thus, it is possible to increase MS sensitivity threefold by replacing TFA with DFA. Moreover, we have observed DFA ion pairing to concomitantly produce higher chromatographic resolution than FA and even TFA. For this reason, we prepared and used MS-quality DFA in place of FA and TFA in separations involving IdeS digested, reduced NIST mAb and a proprietary antibody-drug conjugate (ADC), aiming to increase sensitivity, resolution and protein recovery. The resulting method using DFA was qualified and applied to two other ADCs and gave heightened sensitivity, resolution and protein recovery versus analyses using TFA. This new method, based on a purified, trace metal free DFA, can potentially become a state-of-the-art liquid chromatography-MS technique for the deep characterization of ADCs.     

Statistical Application and Challenges in Global Gel-Free Proteomic Analysis by Mass Spectrometry

Global gel-free proteomic analysis by mass spectrometry has been widely used as an important tool for exploring complex biological systems at the whole genome level. Simultaneous analysis of a large number of protein species is a complicated and challenging task. The challenges exist throughout all stages of a global gel-free proteomic analysis: experimental design, peptide/protein identification, data preprocessing and normalization, and inferential analysis. In addition to various efforts to improve the analytical technologies, statistical methodologies have been applied in all stages of proteomic analyses to help extract relevant information efficiently from large proteomic datasets. In this review, we summarize current applications of statistics in several stages of global gel-free proteomic analysis by mass spectrometry. We discuss the challenges associated with the applications of various statistical tools. Whenever possible, we also propose potential solutions on how to improve the data collection and interpretation for mass-spectrometry-based global proteomic analysis using more sophisticated and/or novel statistical approaches.     

Membrane protein identifications by mass spectrometry using electrocapture-based separation as part of a two-dimensional fractionation system

A two-dimensional (2D) separation method was used to decrease sample complexity in analysis of tryptic peptides from glomerular membrane proteins by tandem mass spectrometry (MS/MS). The first dimension was carried out by electrocapture (EC), which fractionates peptides according to electrophoretic mobility. The second dimension was reverse-phase liquid chromatography (RP-LC), in which EC fractions were further separated and analyzed online by MS/MS. Using this methodology, we now identify 102 glomerular proteins (57 membrane proteins). Many peptides were possible to observe and select for MS/MS only using the 2D approach. Others were detectable in both one-dimensional (1D, without the EC step) and 2D experiments but were selectable for sequence analysis only from the 2D separations because the decrease in complexity then gives time for the mass analyzer to select the peptide and switch to the MS/MS mode. A minority of the peptides were detectable only in the 1D mode (presumably because of handling losses), but at the end this did not decrease the number of proteins identified by the 2D separation. After a database search, the combination of EC and RP-LC MS/MS versus a 1D RP-LC MS/MS separation resulted in a threefold increase in the number of proteins identified and improved the sequence coverage in the identifications, bringing our proteome-identified glomerular proteins to 282.     

Significance of mobile phase composition in enantioseparation of chiral drugs by HPLC on a cellulose-based chiral stationary phase

Eight randomly selected pharmaceuticals, which included ibuprofen, ketoprofen, albuterol, acebutolol, propafenone, betaxolol, methylphenidate, and homatropine, were directly separated on a cellulose tris(4-methylbenzoate) chiral stationary phase (CSP) without derivatization via normal phase mode HPLC. Enantioresolution was achieved by the optimization of the type and the ratio of mobile phase modifiers and additives. The modifiers included alcohols; the mobile phase additives were trifluoroacetic acid (TFA) and triethylamine (TEA). It was found that methanol and ethanol were superior to isopropanol as mobile phase modifiers for enhancing chiral separation of some of the chiral drugs. The results also demonstrated that TFA has a dominant effect on chiral separations for both acidic and basic chiral drugs, although for some basic drug such as homatropine, TEA was more beneficial at improving enantioseparation. The separation of acebutolol enantiomers was achieved for the first time by adding both TFA and TEA to the mobile phase. The purpose of this paper is to demonstrate that the applicability of cellulose based CSPs can be expanded by controlling the mobile phase compositions through the addition of trace amounts of achiral additives and the selection of the appropriate alcoholic modifier. © 1996 Wiley-Liss, Inc.     

Advanced nanoscale separations and mass spectrometry for sensitive high-throughput proteomics

Recent developments in combined separations with mass spectrometry for sensitive and high-throughput proteomic analyses are reviewed herein. These developments primarily involve high-efficiency (separation peak capacities of ~10³) nanoscale liquid chromatography (flow rates extending down to approximately 20 nl/min at optimal liquid mobile-phase separation linear velocities through narrow packed capillaries) in combination with advanced mass spectrometry and in particular, high-sensitivity and high-resolution Fourier transform ion cyclotron resonance mass spectrometry. Such approaches enable analysis of low nanogram level proteomic samples (i.e., nanoscale proteomics) with individual protein identification sensitivity at the low zeptomole level. The resultant protein measurement dynamic range can approach 10⁶ for nanogram-sized proteomic samples, while more abundant proteins can be detected from subpicogram-sized (total) proteome samples. These qualities provide the foundation for proteomics studies of single or small populations of cells. The instrumental robustness required for automation and providing high-quality routine performance nanoscale proteomic analyses is also discussed.     

Optimization of Data-Dependent Acquisition Parameters for Coupling High-Speed Separations with LC-MS/MS for Protein Identifications

Recent developments in chromatography, such as ultra-HPLC and superficially porous particles, offer significantly improved peptide separation. The narrow peak widths, often only several seconds, can permit a 15-min liquid chromatography run to have a similar peak capacity as a 60-min run using traditional HPLC approaches. In theory, these larger peak capacities should provide higher protein coverage and/or more protein identifications when incorporated into a proteomic workflow. We initially observed a decrease in protein coverage when implementing these faster chromatographic approaches, due to data-dependent acquisition (DDA) settings that were not properly set to match the narrow peak widths resulting from newly implemented, fast separation techniques. Oversampling of high-intensity peptides lead to low protein-sequence coverage, and tandem mass spectra (MS/MS) from lower-intensity peptides were of poor quality, as automated MS/MS events were occurring late on chromatographic peaks. These observations led us to optimize DDA settings to use these fast separations. Optimized DDA settings were applied to the analysis of Trypanosome brucei peptides, yielding peptide identifications at a rate almost five times faster than previously used methodologies. The described approach significantly improves protein identification workflows that use typical available instrumentation.     

Shotgun proteome analysis utilising mixed mode (reversed phase‐anion exchange chromatography) in conjunction with reversed phase liquid chromatography mass spectrometry analysis

The 2‐D peptide separations employing mixed mode reversed phase anion exchange (MM (RP‐AX)) HPLC in the first dimension in conjunction with RP chromatography in the second dimension were developed and utilised for shotgun proteome analysis. Compared with strong cation exchange (SCX) typically employed for shotgun proteomic analysis, peptide separations using MM (RP‐AX) revealed improved separation efficiency and increased peptide distribution across the elution gradient. In addition, improved sample handling, with no significant reduction in the orthogonality of the peptide separations was observed. The shotgun proteomic analysis of a mammalian nuclear cell lysate revealed additional proteome coverage (2818 versus 1125 unique peptides and 602 versus 238 proteins) using the MM (RP‐AX) compared with the traditional SCX hyphenated to RP‐LC‐MS/MS. The MM analysis resulted in approximately 90% of the unique peptides identified present in only one fraction, with a heterogeneous peptide distribution across all fractions. No clustering of the predominant peptide charge states was observed during the gradient elution. The application of MM (RP‐AX) for 2‐D LC proteomic studies was also extended in the analysis of iTRAQ‐labelled HeLa and cyanobacterial proteomes using nano‐flow chromatography interfaced to the MS/MS. We demonstrate MM (RP‐AX) HPLC as an alternative approach for shotgun proteomic studies that offers significant advantages over traditional SCX peptide separations.     

Performance metrics for evaluating system suitability in liquid chromatography—Mass spectrometry peptide mass mapping of protein therapeutics and monoclonal antibodies

The use of liquid chromatography – mass spectrometry (LC-MS) for the characterization of proteins can provide a plethora of information related to their structure, including amino acid sequence determination and analysis of posttranslational modifications. The variety of LC-MS based applications has led to the use of LC-MS characterization of therapeutic proteins and monoclonal antibodies as an integral part of the regulatory approval process. However, the improper use of an LC-MS system, related to intrinsic instrument limitations, improper tuning parameters, or poorly optimized methods may result in the production of low quality data. Improper system performance may arise from subtle changes in operating conditions that limit the ability to detect low abundance species. To address this issue, we systematically evaluated LC-MS/MS operating parameters to identify a set of metrics that can be used in a workflow to determine if a system is suitable for its intended purpose. Development of this workflow utilized a bovine serum albumin (BSA) digest standard spiked with synthetic peptides present at 0.1% to 100% of the BSA digest peptide concentration to simulate the detection of low abundance species using a traditional bottom-up workflow and data-dependent MS² acquisition. BSA sequence coverage, a commonly used indicator for instrument performance did not effectively identify settings that led to limited dynamic range or poorer absolute mass accuracy on 2 separate LC-MS systems. Additional metrics focusing on the detection limit and sensitivity for peptide identification were determined to be necessary to establish system suitability for protein therapeutic characterization by LC-MS.     

An assessment of current bioinformatic solutions for analyzing LC-MS data acquired by selected reaction monitoring technology

Selected reaction monitoring (SRM) is an accurate quantitative technique, typically used for small-molecule mass spectrometry (MS). SRM has emerged as an important technique for targeted and hypothesis-driven proteomic research, and is becoming the reference method for protein quantification in complex biological samples. SRM offers high selectivity, a lower limit of detection and improved reproducibility, compared to conventional shot-gun-based tandem MS (LC-MS/MS) methods. Unlike LC-MS/MS, which requires computationally intensive informatic postanalysis, SRM requires preacquisition bioinformatic analysis to determine proteotypic peptides and optimal transitions to uniquely identify and to accurately quantitate proteins of interest. Extensive arrays of bioinformatics software tools, both web-based and stand-alone, have been published to assist researchers to determine optimal peptides and transition sets. The transitions are oftentimes selected based on preferred precursor charge state, peptide molecular weight, hydrophobicity, fragmentation pattern at a given collision energy (CE), and instrumentation chosen. Validation of the selected transitions for each peptide is critical since peptide performance varies depending on the mass spectrometer used. In this review, we provide an overview of open source and commercial bioinformatic tools for analyzing LC-MS data acquired by SRM.     

Performance metrics for evaluating system suitability in liquid chromatography—Mass spectrometry peptide mass mapping of protein therapeutics and monoclonal antibodies

The use of liquid chromatography – mass spectrometry (LC-MS) for the characterization of proteins can provide a plethora of information related to their structure, including amino acid sequence determination and analysis of posttranslational modifications. The variety of LC-MS based applications has led to the use of LC-MS characterization of therapeutic proteins and monoclonal antibodies as an integral part of the regulatory approval process. However, the improper use of an LC-MS system, related to intrinsic instrument limitations, improper tuning parameters, or poorly optimized methods may result in the production of low quality data. Improper system performance may arise from subtle changes in operating conditions that limit the ability to detect low abundance species. To address this issue, we systematically evaluated LC-MS/MS operating parameters to identify a set of metrics that can be used in a workflow to determine if a system is suitable for its intended purpose. Development of this workflow utilized a bovine serum albumin (BSA) digest standard spiked with synthetic peptides present at 0.1% to 100% of the BSA digest peptide concentration to simulate the detection of low abundance species using a traditional bottom-up workflow and data-dependent MS² acquisition. BSA sequence coverage, a commonly used indicator for instrument performance did not effectively identify settings that led to limited dynamic range or poorer absolute mass accuracy on 2 separate LC-MS systems. Additional metrics focusing on the detection limit and sensitivity for peptide identification were determined to be necessary to establish system suitability for protein therapeutic characterization by LC-MS.     

One-dimensional proteomic mapping of human liver cytochromes P450

A method for constructing one-dimensional proteomic maps (1D-PM) based on mass spectrometric identification of proteins from adjacent slices of one-dimensional electrophoregram has been developed. For the proteomic mapping, gel lanes were sectioned into slices less than 0.2 mm thick and each slice was subjected to enzymatic hydrolysis. The resultant mixture of peptide fragments was analyzed by matrix-assisted laser desorption time-of-flight mass spectrometry (MALDI-TOF) and liquid chromatography electrospray ionization tandem mass spectrometry (LC-MS/MS). Proteins were identified by the mass spectra obtained. Data on peptide fragments and corresponding identified proteins were presented as a 1D-PM. Proteomic maps were constructed by assigning individual proteins to gel slices based on number of matching peptides in a corresponding MS-data. On 1D-PM of human liver microsomal fraction, 18 proteins were identified in the region of 40–65 kDa. These included 12 membrane proteins belonging to the superfamily of cytochromes P450. Pooling of mass spectrometric data, obtained from several adjacent gel slices (molecular zooming) increased sequence coverage of CYP2A (cytochrome P450 family 2A). The maximal coverage of 66% significantly exceeded the level of 48% that could be obtained using one (even the most informative) slice. This method can be applied to the proteomic profiling of membrane-bound proteins.     

A fast and simple assay for busulfan in serum or plasma by liquid chromatography-tandem mass spectrometry using turbulent flow online extraction technology

Busulfan is used in myeloablative preparation regimens for hematopoietic bone marrow transplantation. Due to its narrow therapeutic range therapeutic drug monitoring of busulfan is recommended. In this study a fast and simple method for measuring busulfan in serum or plasma by liquid chromatography-tandem mass spectrometry (LC-MS/MS) has been developed utilizing turbulent flow online extraction technology. Serum or plasma was mixed with acetonitrile containing d(8)-busulfan. After centrifugation the supernatant was injected onto a turbulent flow preparatory column then transferred to a C18 analytical column monitored by a tandem mass spectrometer set at positive electrospray ionization. The analytical cycle time was 4.0min. The method was linear from 0.15 to 41.90μmol/L with an accuracy of 87.9-103.0%. Inter- and intra-assay CVs across four concentration levels were 2.1-7.8%. No significant carryover or ion suppression was observed. No interference was observed from commercial control materials containing more than 100 compounds. Comparison with a well established LC-MS/MS method using patient specimens (n=45) showed a mean bias 1.3% with Deming regression of slope 1.02, intercept -0.02μmol/L, and a linear correlation coefficient 0.9883. The LC-MS/MS method coupled with turbulent flow online sample cleaning technology described here offers reliable busulfan quantitation in serum or plasma with minimum manual sample preparation and was fully validated for clinical use.     

Improving large-scale proteomics by clustering of mass spectrometry data

Tandem mass spectrometry (MS/MS), coupled with liquid chromatography (LC), is a powerful tool for the analysis and comparison of complex protein and peptide mixtures. However, the extremely large amounts of data that result from the process are very complex and difficult to analyze. We show how the clustering of similar spectra from multiple LC-MS/MS runs can help in data management and improve the analysis of complex peptide mixtures. The major effect of spectrum clustering is the reduction of the huge amounts of data to a manageable size. As a result, analysis time is shorter and more data can be stored for further analysis. Furthermore, spectrum quality improvement allows the identification of more peptides with greater confidence, the comparison of complex peptide mixtures is facilitated, and the entire proteomics project is presented in concise form. Pep-Miner is an advanced software tool that implements these clustering-based applications. It proved useful in several comparative proteomics projects involving lung cancer cells and various other cell types. In one of these projects, Pep-Miner reduced 517 000 spectra to 20 900 clusters and identified 2518 peptides derived from 830 proteins. Clustering and identification lasted less than two hours on an IBM Thinkpad T23 computer (laptop). Pep-Miner's unique properties make it a very useful tool for large-scale shotgun proteomics projects.     

Evaluation of strong cation exchange versus isoelectric focusing of peptides for multidimensional liquid chromatography-tandem mass spectrometry

Shotgun proteome analysis platforms based on multidimensional liquid chromatography-tandem mass spectrometry (LC-MS/MS) provide a powerful means to discover biomarker candidates in tissue specimens. Analysis platforms must balance sensitivity for peptide detection, reproducibility of detected peptide inventories and analytical throughput for protein amounts commonly present in tissue biospecimens (< 100 microg), such that platform stability is sufficient to detect modest changes in complex proteomes. We compared shotgun proteomics platforms by analyzing tryptic digests of whole cell and tissue proteomes using strong cation exchange (SCX) and isoelectric focusing (IEF) separations of peptides prior to LC-MS/MS analysis on a LTQ-Orbitrap hybrid instrument. IEF separations provided superior reproducibility and resolution for peptide fractionation from samples corresponding to both large (100 microg) and small (10 microg) protein inputs. SCX generated more peptide and protein identifications than did IEF with small (10 microg) samples, whereas the two platforms yielded similar numbers of identifications with large (100 microg) samples. In nine replicate analyses of tryptic peptides from 50 microg colon adenocarcinoma protein, overlap in protein detection by the two platforms was 77% of all proteins detected by both methods combined. IEF more quickly approached maximal detection, with 90% of IEF-detectable medium abundance proteins (those detected with a total of 3-4 peptides) detected within three replicate analyses. In contrast, the SCX platform required six replicates to detect 90% of SCX-detectable medium abundance proteins. High reproducibility and efficient resolution of IEF peptide separations make the IEF platform superior to the SCX platform for biomarker discovery via shotgun proteomic analyses of tissue specimens.     

LC-MS/MS based proteomic analysis and functional inference of hypothetical proteins in Desulfovibrio vulgaris

High efficiency capillary liquid chromatography-tandem mass spectrometry (LC-MS/MS) was used to examine the proteins extracted from Desulfovibrio vulgaris cells across six treatment conditions. While our previous study provided a proteomic overview of the cellular metabolism based on proteins with known functions [W. Zhang, M.A. Gritsenko, R.J. Moore, D.E. Culley, L. Nie, K. Petritis, E.F. Strittmatter, D.G. Camp II, R.D. Smith, F.J. Brockman, A proteomic view of the metabolism in Desulfovibrio vulgaris determined by liquid chromatography coupled with tandem mass spectrometry, Proteomics 6 (2006) 4286-4299], this study describes the global detection and functional inference for hypothetical D. vulgaris proteins. Using criteria that a given peptide of a protein is identified from at least two out of three independent LC-MS/MS measurements and that for any protein at least two different peptides are identified among the three measurements, 129 open reading frames (ORFs) originally annotated as hypothetical proteins were found to encode expressed proteins. Functional inference for the conserved hypothetical proteins was performed by a combination of several non-homology based methods: genomic context analysis, phylogenomic profiling, and analysis of a combination of experimental information, including peptide detection in cells grown under specific culture conditions and cellular location of the proteins. Using this approach we were able to assign possible functions to 20 conserved hypothetical proteins. This study demonstrated that a combination of proteomics and bioinformatics methodologies can provide verification of the expression of hypothetical proteins and improve genome annotation.     

Tissue proteomics using capillary isoelectric focusing-based multidimensional separations

The capabilities of capillary isoelectric focusing-based multidimensional separations for performing proteome analysis from minute samples create new opportunities in the pursuit of biomarker discovery using enriched and selected cell populations procured from tissue specimens. In this article, recent advances in online integration of capillary isoelectric focusing with nano-reversed phase liquid chromatography for achieving high-resolution peptide and protein separations prior to mass spectrometry analysis are reviewed, along with its potential application to tissue proteomics. These proteome technological advances combined with recently developed tissue microdissection techniques, provide powerful tools for those seeking to gain a greater understanding at the global level of the cellular machinery associated with human diseases such as cancer.     

Proteome analysis in thyroid pathology

The incidence of thyroid cancer has continuously increased due to its detection in the preclinical stage. Clinical research in thyroid pathology is focusing on the development of new diagnostic tools to improve the stratification of nodules that have biological, practical and economic consequences on the management of patients. Several clinical questions related to thyroid carcinoma remain open and the use of proteomic research in the hunt for new targets with potential diagnostic applications has an important role in the solutions. Many different proteomic approaches are used to investigate thyroid lesions, including mass spectrometry profiling and imaging technologies. These approaches have been applied to different human tissues (cytological specimens, frozen sections, formalin-fixed paraffin embedded tissue or Tissue Micro Arrays). Moreover, other specimens are used for biomarker discovery, such as cell lines and the secretome. Alternative approaches, such as metabolomics and lipidomics, are also used and integrated within proteomics.     

Advanced nanoscale separations and mass spectrometry for sensitive high-throughput proteomics

Recent developments in combined separations with mass spectrometry for sensitive and high-throughput proteomic analyses are reviewed herein. These developments primarily involve high-efficiency (separation peak capacities of approximately 10(3)) nanoscale liquid chromatography (flow rates extending down to approximately 20 nl/min at optimal liquid mobile-phase separation linear velocities through narrow packed capillaries) in combination with advanced mass spectrometry and in particular, high-sensitivity and high-resolution Fourier transform ion cyclotron resonance mass spectrometry. Such approaches enable analysis of low nanogram level proteomic samples (i.e., nanoscale proteomics) with individual protein identification sensitivity at the low zeptomole level. The resultant protein measurement dynamic range can approach 10(6) for nanogram-sized proteomic samples, while more abundant proteins can be detected from subpicogram-sized (total) proteome samples. These qualities provide the foundation for proteomics studies of single or small populations of cells. The instrumental robustness required for automation and providing high-quality routine performance nanoscale proteomic analyses is also discussed.