high-pH RP-LC Research Articles

A micro-flow, high-pH, reversed-phase peptide fractionation and collection system for targeted and in-depth proteomics of low-abundance proteins in limiting samples

We present a method and a simple system for high-pH RP-LC peptide fractionation of small sample amounts (30–60 µg), at micro-flow rates with micro-liter fraction collection using ammonium bicarbonate as an optimized buffer for system stability and robustness. The method is applicable to targeted mass spectrometry approaches and to in-depth proteomic studies where the amount of sample is limited. Using targeted proteomics with peptide standards, we present the method's analytical parameters, and potential in increasing the detection of low-abundance proteins that are difficult to quantify with direct targeted or global LC-MS analyses. This fractionation system increased peptide signals by up to 18-fold, while maintaining high quantitative precision, with high fractionation reproducibility across varied sample sets. In real applications, it increased the detection of targeted endogenous peptides by two-fold in a 25 cell-cycle-control protein panel, and in-depth MS analyses of nuclear extracts, it allowed the detection of up to 8,896 proteins with 138,417 peptides in 24-concatenated fractions compared to 3,344 proteins with 23,093 peptides without fractionation. In a relevant biological problem of CDK4/6-inhibitors and breast cancer, the method reproduced known information and revealed novel insights, highlighting that it can be successfully applied in studies involving low-abundance proteins and limited samples.•Tested nine high-pH buffer/solvent systems to obtain a robust, effective, and reproducible micro-flow fractionation method which was devoid of commonly encountered LC clogging/pressure issues after months of use.•Peptide enrichment method to improve detection and quantitation of low-abundance proteins in targeted and in-depth proteomic studies.•Can be applied to diverse protein samples where the available amount is limited.

FRACPRED‐2D‐PRM: A Fraction Prediction Algorithm‐Assisted 2D Liquid Chromatography‐Based Parallel Reaction Monitoring‐Mass Spectrometry Approach for Measuring Low‐Abundance Proteins in Human Plasma

Multidimensional fractionation-based enrichment methods improve the sensitivity of proteomic analysis for low-abundance proteins. However, a major limitation of conventional multidimensional proteomics is the extensive labor and instrument time required for analyzing many fractions obtained from the first dimension separation. Here, a fraction prediction algorithm-assisted 2D LC-based parallel reaction monitoring-mass spectrometry (FRACPRED-2D-PRM) approach for measuring low-abundance proteins in human plasma is presented. Plasma digests are separated by the first dimension high-pH RP-LC with data-dependent acquisition (DDA). The FRACPRED algorithm is then usedto predict the retention times of undetectable target peptides according to those of other abundant plasma peptides during the first dimension separation. Fractions predicted to contain target peptides are analyzed by the second dimension low-pH nano RP-LC PRM. The accuracy and robustness of fraction prediction with the FRACPRED algorithm are demonstrated by measuring two low-abundance proteins, aldolase B and carboxylesterase 1, in human plasma. The FRACPRED-2D-PRM proteomics approach demonstrates markedly improved efficiency and sensitivity over conventional 2D-LC proteomics assays. It is expected that this approach will be widely used in the study of low-abundance proteins in plasma and other complex biological samples.

Proteomic Study of Aqueous Humor and Its Application in the Treatment of Neovascular Glaucoma.

Aqueous humor (AH) proteins are involved in many physiological and pathological processes of the eye. The proteome analysis of AH is important to understand its physiological and pathophysiological functions. In the present study, AH samples obtained from 21 cataract volunteers were pooled together. After high-pH RPLC offline separation, the pooled sample was analyzed by LC-MS/MS to provide a comprehensive profile of AH proteome. The function analysis was provided by the GO and IPA annotation. In order to determine whether the AH proteome can reflect the pathophysiological changes of the disease, DIA technology was used to analyze the AH samples obtained from three neovascular glaucoma (NVG) patients (six samples) before and after drug treatment. The differential proteins were validated by PRM technology in an independent group (14 samples). In the AH proteome database, 802 proteins were identified, and 318 proteins were identified for the first time. Furthermore, 480 proteins were quantified based on the peak intensity-based semiquantification (iBAQ), which ranged by approximately 7 orders of magnitude. These proteins are primarily involved in immunity- and inflammation-related pathways. The differential AH proteomic analysis in NVG treatment revealed that the AH proteome can reflect the pathophysiological changes of drug treatment. Angiogenesis and thrombus coagulation progression are deeply involved in NVG treatment. The present experiment provided a comprehensive AH proteome analysis and expanded the profile of human AH proteome. The differential AH proteomic analysis of NVG treatment indicated that AH proteome can reflect the pathophysiological changes in drug intervention.

Development of an Online 2D Ultrahigh-Pressure Nano-LC System for High-pH and Low-pH Reversed Phase Separation in Top-Down Proteomics.

The development of novel high-resolution separation techniques is crucial for advancing the complex sample analysis necessary for high-throughput top-down proteomics. Recently, our group developed an offline 2D high-pH RPLC/low-pH RPLC separation method and demonstrated good orthogonality between these two RPLC formats. Specifically, ultrahigh-pressure long capillary column RPLC separation has been applied as the second dimensional low-pH RPLC separation for the improvement of separation resolution. To further improve the throughput and sensitivity of the offline approach, we developed an online 2D ultrahigh-pressure nano-LC system for high-pH and low-pH RPLC separations in top-down proteomics. An online microtrap column with a dilution setup was used to collect eluted proteins from the first dimension high-pH separation and inject the fractions for ultrahigh-pressure long capillary column low-pH RPLC separation in the second dimension. This automatic platform enables the characterization of 1000+ intact proteoforms from 5 μg of intact E. coli cell lysate in 10 online-collected fractions. Here, we have demonstrated that our online 2D pH RP/RPLC system coupled with top-down proteomics holds the potential for deep proteome characterization of mass-limited samples because it allows the identification of hundreds of intact proteoforms from complex biological samples at low microgram sample amounts.

In-depth mapping of the seed phosphoproteome and N-glycoproteome of Tartary buckwheat (Fagopyrum tataricum) using off-line high pH RPLC fractionation and nLC-MS/MS

The seed of Tartary buckwheat (Fagopyrum tataricum) is rich in nutrients and functional ingredients and is recommended as a healthy cereal food. The total proteins of Tartary buckwheat seed (TBS) were extracted and digested; then, the phosphopeptides and glycopeptides were separately enriched and identified by nano liquid chromatography/tandem mass spectrometry. A total of 2613 phosphorylation sites from 1670 phosphoproteins and 404 N-glycosylation sites from 285 N-glycoproteins were identified in TBS. Function and pathway analyses showed that TBS phosphoproteins were significantly enriched in transport, energy metabolism, amino acids biosynthesis/metabolism, and signaling and TBS N-glycoproteins were significantly enriched in modification regulation. The present study reports the first profiles of the phosphoproteome and N-glycoproteome of TBS and provides important post-translational modifications information on the proteins in TBS. The results of this study will aid the understanding of the underlying mechanism of the germination of TBS during cultivation and edible quality changes during storage and processing.

Two-dimensional separation using high-pH and low-pH reversed phase liquid chromatography for top-down proteomics

Advancements in chromatographic separation are critical to in-depth top-down proteomics of complex intact protein samples. Reversed-phase liquid chromatography is the most prevalent technique for top-down proteomics. However, in cases of high complexities and large dynamic ranges, 1D-RPLC may not provide sufficient coverage of the proteome. To address these challenges, orthogonal separation techniques are often combined to improve the coverage and the dynamic range of detection. In this study, a “salt-free” high-pH RPLC was evaluated as an orthogonal dimension of separation to conventional low-pH RPLC with top-down MS. The RPLC separations with low-pH conditions (pH=2) and high-pH conditions (pH=10) were compared to confirm the good orthogonality between high-pH and low-pH RPLC’s. The offline 2D RPLC-RPLC–MS/MS analyses of intact E. coli samples were evaluated for the improvement of intact protein identifications as well as intact proteoform characterizations. Compared to the 163 proteins and 328 proteoforms identified using a 1D RPLC–MS approach, 365 proteins and 886 proteoforms were identified using the 2D RPLC–RPLC top-down MS approach. Our results demonstrate that the 2D RPLC–RPLC top-down approach holds great potential for in-depth top-down proteomics studies by utilizing the high resolving power of RPLC separations and by using mass spectrometry compatible buffers for easy sample handling for online MS analysis.

Mining the human plasma proteome with three-dimensional strategies by high-resolution Quadrupole Orbitrap Mass Spectrometry

Human plasma is a readily available clinical sample that reflects the status of the body in normal physiological and disease states. Although the wide dynamic range and immense complexity of plasma proteins are obstacles, comprehensive proteomic analysis of human plasma is necessary for biomarker discovery and further verification. Various methods such as immunodepletion, protein equalization and hyper fractionation have been applied to reduce the influence of high-abundance proteins (HAPs) and to reduce the high level of complexity. However, the depth at which the human plasma proteome has been explored in a relatively short time frame has been limited, which impedes the transfer of proteomic techniques to clinical research. Development of an optimal strategy is expected to improve the efficiency of human plasma proteome profiling.Here, five three-dimensional strategies combining HAP depletion (the 1st dimension) and protein fractionation (the 2nd dimension), followed by LC-MS/MS analysis (the 3rd dimension) were developed and compared for human plasma proteome profiling. Pros and cons of the five strategies are discussed for two issues: HAP depletion and complexity reduction. Strategies A and B used proteome equalization and tandem Seppro IgY14 immunodepletion, respectively, as the first dimension. Proteome equalization (strategy A) was biased toward the enrichment of basic and low-molecular weight proteins and had limited ability to enrich low-abundance proteins. By tandem removal of HAPs (strategy B), the efficiency of HAP depletion was significantly increased, whereas more off-target proteins were subtracted simultaneously. In the comparison of complexity reduction, strategy D involved a deglycosylation step before high-pH RPLC separation. However, the increase in sequence coverage did not increase the protein number as expected. Strategy E introduced SDS-PAGE separation of proteins, and the results showed oversampling of HAPs and identification of fewer proteins. Strategy C combined single Seppro IgY14 immunodepletion, high-pH RPLC fractionation and LC-MS/MS analysis. It generated the largest dataset, containing 1544 plasma protein groups and 258 newly identified proteins in a 30-h-machine-time analysis, making it the optimum three-dimensional strategy in our study. Further analysis of the integrated data from the five strategies showed identical distribution patterns in terms of sequence features and GO functional analysis with the 1929-plasma-protein dataset, further supporting the reliability of our plasma protein identifications. The characterization of 20 cytokines in the concentration range from sub-nanograms/milliliter to micrograms/milliliter demonstrated the sensitivity of the current strategies.

In this issue

PROTEOMICSVolume 11, Issue 10 In this issue In this issue First published: 11 May 2011 https://doi.org/10.1002/pmic.201190043AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat Abstract Been workin' on the concatenation gang, all the live-long day Givin' the man 15 for 1 throughput as I sweat away… I hope you aren't working too far from the air conditioner because this proteomic 2-D LC procedure is smokin' hot. In brief, Wang et al. re-examined the selection of first-dimension RPLC buffers to come up with one with markedly improved resolution properties. In particular, it was the pH that mattered most – substituting a high pH RPLC (pH 7.5) identified 30% more phosphopeptides than conventionally detected with a strong cation exchanger. Then they found that they could concatenate first-dimension fractions with second-dimension buffers for more efficient use for chromatography space. Plus, there's a fringe benefit – no sample desalting is required for the high pH RPLC buffer – a great time-saver for shotgun proteome researchers. pp. 2019–2026 A self-starting, spot-spotting, mixture-modeling package released It sounds ominous, but there are no reports of terabytes terrorizing the people of Athens. There is some talk among the petabytes of picketing the pedestrian path from the port to the Parthenon – the pickpockets can't keep up with the parade of passengers seeking Drs Tsakanikas and Manolakos. These two have taken a different approach to matching spots from 2-DE gels – a protocol that, after initialization, does not require manual calibration or adjustment for successive scans – it teaches itself in an unsupervised learning mode. (Warning: equations ahead.) An intensity histogram identifies the number of mixture models required. Pixels are sorted by mode level and Bayes thresholding. This eliminates local background streaks and non-informative pixels and, after agglomerative hierarchical clustering (!), yields a dendrogram that is then trimmed and pruned. Unique is the use of random sampling of model data rather than raw peak data for analysis. This new procedure was tested against PDQuest. pp. 2038–2050 Raw, raw, raw. Sis, boom, bah… (basketball cheer, ca. 1918) Cheering for one's favorite team is thought to improve performance. It would be interesting to test the hypothesis...on someone else's nickel. Here we have a technical brief on a software package from Holenya et al. that conveniently accepts .raw data for analysis. Where does the data come from? From a multiplex array procedure for analysis of protein phosphorylation sites, using a very sensitive modified kinetic ELISA procedure. With a 1 pg lower limit of detection and 20 000 pg upper limit of detection (depending on the protein), the detection curve was non-linear. The non-parametric regression model Gaussian Random Process Regression was applied for calibration surface generation. pp. 2129–2133 Volume11, Issue10May 2011 RelatedInformation