SpotLink enables sensitive and precise identification of site nonspecific cross-links at the proteome scale.

Nonspecific cross-linker can provide distance restraints between surface residues of any type, which could be used to investigate protein structure construction and protein-protein interaction (PPI). However, the vast number of potential combinations of cross-linked residues or sites obtained with such a cross-linker makes the data challenging to analyze, especially for the proteome-wide applications. Here, we developed SpotLink software for identifying site nonspecific cross-links at the proteome scale. Contributed by the dual pointer dynamic pruning algorithm and the quality control of cross-linking sites, SpotLink identified > 3000 cross-links from human cell samples within a short period of days. We demonstrated that SpotLink outperformed other approaches in terms of sensitivity and precision on the datasets of the simulated succinimidyl 4,4'-azipentanoate dataset and the condensin complexes with known structures. In addition, some valuable PPI were discovered in the datasets of the condensin complexes and the HeLa dataset, indicating the unique identification advantages of site nonspecific cross-linking. These findings reinforce the importance of SpotLink as a fundamental characteristic of site nonspecific cross-linking technologies.

ComMap: a software to perform large-scale structure-based mapping for cross-linking mass spectrometry.

MOTIVATION: Chemical cross-linking combined with mass spectrometry (CXMS) is now a well-established method for profiling existing protein-protein interactions (PPIs) with partially known structures. It is expected to map the results of CXMS with existing structure databases to study the protein dynamic profile in the structure analysis. However, currently available structure-based analysis software suffers from the difficulty of achieving large-scale analysis. Besides, it is infeasible for structure analysis and data mining on a large scale, since of lacking global measurement of dynamic structure mapping results. RESULTS: ComMap (protein complex structure mapping) is a software designed to perform large-scale structure-based mapping by integrating CXMS data with existing structures. It allows complete the distance calculation of PPIs with existing structures in batch within minutes and provides scores for different PPI-structure pairs of testable hypothetical structural dynamism via a global view. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

A Glycosidic-Bond-Based Mass-Spectrometry-Cleavable Cross-linker Enables In Vivo Cross-linking for Protein Complex Analysis.

Chemical cross-linking mass spectrometry (CXMS) has emerged as a powerful technology to analyze protein complexes. However, the progress of in vivo CXMS studies has been limited by cross-linking biocompatibility and data analysis. Herein, a glycosidic bond-based MS-cleavable cross-linker of trehalose disuccinimidyl ester (TDS) was designed and synthesized, which was fragmented in MS under CID/HCD to simplify the cross-linked peptides into conventional single peptides via selective cleavage between glycosidic and peptide bonds under individual MS collision energy. Consequently, the cross-linking identification accuracy and throughput were significantly enhanced, and the popular MS mode of stepped HCD was allowed. In addition, TDS showed proper cell-penetrating properties while being highly water-soluble, making it non-DMSO dependent during solubilization. Collectively, TDS provides a promising toolkit for CXMS characterization of living systems with high biocompatibility and accuracy.

A1 Ions: Peptide-Specific and Intensity-Enhanced Fragment Ions for Accurate and Multiplexed Proteome Quantitation.

Accurate proteome quantitation is of great significance to deeply understand various cellular and physiological processes. Since a1 ions, generated from dimethyl-labeled peptides, exhibited high formation efficiency (up to 99%) and enhanced intensities (2.34-fold by average) in tandem mass spectra, herein, we proposed an a1 ion-based proteome quantitation (APQ) method, which showed high quantitation accuracy (relative errors < 7%) and precision (median coefficients of variation ≤ 11%) even in a 20-fold dynamic range. Notably, due to the mass differences of a1 ions from peptides with different N-terminal amino acids, APQ demonstrated interference-free capacity by distinguishing target peptides from the coisolated ones. By designing an isobaric dimethyl labeling strategy, we achieved simultaneous proteome-wide measurements across up to eight samples. Using APQ to quantify the time-resolved proteomic profiles during a TGF-ß-induced epithelial-mesenchymal transition, we found many differentially expressed proteins associated with fatty acid degradation, indicating that fatty acid metabolism reprogramming occurred during the process. The APQ method combines high quantitation accuracy with multiplexing capacity, which is suitable for deep mining and understanding of dynamic biological processes.

All-Ion Monitoring-Directed Low-Abundance Protein Quantification Reveals CALB2 as a Key Promoter in Hepatocellular Carcinoma Metastasis.

Because of the wide abundance range of the proteome, achieving high-coverage quantification of low-abundance proteins is always a major challenge. In this study, a complete pipeline focused on all-ion monitoring (AIM) is first constructed with the concept of untargeted parallel-reaction monitoring, including the seamless connection of protein sample preparation, liquid chromatography mass spectrometry (LC-MS) acquisition, and algorithm development to enable the in-depth quantitative analysis of low-abundance proteins. This pipeline significantly improves the reproducibility and sensitivity of sample preparation and LC-MS acquisition for low-abundance proteins, enabling all the precursors ions fragmented and collected. Contributed by the advantages of the AIM method with all the target precursor acquisition by the data-dependent acquisition (DDA) approach, together with the ability of data-independent acquisition to fragment all precursor ions, the quantitative accuracy and precision of low-abundance proteins are greatly enhanced. As a proof of concept, this pipeline is employed to discover the key differential proteins in the mechanism of hepatocellular carcinoma (HCC) metastasis. On the basis of the superiority of AIM, an extremely low-abundance protein, CALB2, is proposed to promote HCC metastasis in vitro and in vivo. We also reveal that CALB2 activates the TRPV2-Ca2+-ERK1/2 signaling pathway to induce HCC cell metastasis. In summary, we provide a universal AIM pipeline for the high-coverage quantification of low-abundance functional proteins to seek novel insights into the mechanisms of cancer metastasis.

Carboxypeptidase B-Assisted Charge-Based Fractional Diagonal Chromatography for Deep Screening of C-Terminome.

The determination of protein C-termini is of great significance for protein function annotation and proteolysis research. However, the progress of C-terminomics is still far behind its counterpart, N-terminomics, because of the low reactivity of the carboxyl group. Herein, we developed a negative selection strategy, termed carboxypeptidase B-assisted charge-based fractional diagonal chromatography (CPB-ChaFRADIC), to achieve a global C-terminome analysis. The highly reactive carboxypeptidase B cleavage was utilized to reduce the charge state of non-C-terminal peptides. Together with high-performance charge-based fractional diagonal chromatography, the C-terminal peptides could be isolated. Such a strategy was applied for profiling C-termini from Escherichia coli cell lysates and 441 canonical C-termini and 510 neo-C-termini originating from proteolytic processing were identified. These findings represent 2-fold and 5.8-fold that of identified C-termini via direct analysis, respectively. Using parallel digestion with trypsin and LysC, such a strategy enabled the identification of 604 canonical C-termini and 818 neo-C-termini, representing the largest C-terminome data set of E. coli, and no deficiency in His/Lys/Arg-containing C-terminal peptides was observed. The presented CPB-ChaFRADIC strategy is therefore a highly efficient and unbiased strategy for large-scale C-terminome analysis. Furthermore, using the CPB-ChaFRADIC strategy, we identified 107 cleavage sites and 102 substrates of caspase-3 in Jurkat cells, demonstrating that the CPB-ChaFRADIC strategy shows great promise in promoting proteolysis research. Data are available via ProteomeXchange with identifier PXD018520.

Smart Cutter: An Efficient Strategy for Increasing the Coverage of Chemical Cross-Linking Analysis.

Chemical cross-linking combined with mass spectrometry (CXMS) has emerged as a powerful tool to study protein structure, conformation, and protein-protein interactions (PPIs). Until now, most cross-linked peptides were generated by using commercial cross-linkers, such as DSS, BS3, and DSSO, which react with the primary amino groups of the lysine residues of proteins. However, trypsin, the most commonly used proteolytic enzyme, cannot cleave the C-terminus of a linked lysine, making the obtained cross-linked peptides longer than common peptides and unfavorable for MS identification and data searching. Herein, we propose an in situ sequential digestion strategy using enzymes with distinct cleavage specificity, named as smart cutter, to generate cross-linked peptides with suitable length so that the identification coverage could improve. Through the application of such a strategy to DSS cross-linked E. coli lysates, additional cross-linked sites (1.3-fold increase) obtained in comparison with those obtained by trypsin-trypsin digestion (2879 vs 1255). Among the different digestion combinations, AspN-trypsin performed the best, with 64% (673/1059) of the cross-linked sites complementary to trypsin-trypsin digestion, which is beneficial to ensure the depth for studying protein structure and PPIs. Taking the 60 kDa chaperonin protein as an example, more than twice the cross-linked sites (30 vs 14) were identified to enrich the protein structure information. In addition, compared to the published protein interaction network for E. coli ( http://www.bacteriome.org ), 91 potential PPIs were discovered with our strategy, of which 65 have not covered by trypsin-trypsin digestion. Therefore, these results illustrate the great significance of smart-cutter-based CXMS for the revelation of protein structure as well as finding new PPIs.

Comprehensive Analysis of Protein N-Terminome by Guanidination of Terminal Amines.

Protein N-termini and their modifications not only represent different protein isoforms but also relate to the functional annotation and proteolytic activities. Currently, negative selection methods, such as terminal amine isotopic labeling of substrates (TAILS), are the most popular strategy to analyze the protein N-terminome, in which dimethylation or acetylation modification is commonly used to block the free amines of proteome samples. However, after tryptic digestion, the generated long peptides, caused by the missing cleavage of blocked lysine, could hardly be identified by MS, which hindered the deep-coverage analysis of N-terminome. Herein, to solve this problem, we developed an approach, named terminal amine guanidination of substrates (TAGS). 1H-Pyrazole-1-carboxamidine was used to effectively guanidinate lysine ε-amines and N-terminal α-amines, followed by tryptic digestion to generate N-terminal peptides without free amines and internal peptides with free amines. Then, the internal peptides with free amines were removed by hyperbranched polyglycerol-aldehyde polymers (HPG-ALDs) to achieve the negative enrichment of N-terminome. By TAGS, not only the cleavage rate of blocked lysine could be improved, but also the ionization efficiency of tryptic peptides was increased. In comparison, 1814 and 1620 protein N-termini were, respectively, identified by TAGS and TAILS in Saccharomyces cerevisiae (S. cerevisiae). Among them, 1012 N-termini were uniquely identified in TAGS. Furthermore, by the combination of TAGS and the stable isotope labeling with amino acids in cell culture (SILAC)/label-free quantitative method, we not only identified the known N-terminal cleavage fragment of gasdermin D but also identified some new cleavage sites during Val-boroPro-induced pyroptosis. All these results demonstrated that our developed approach, TAGS, might be of great promise for the comprehensive analysis of N-terminome and beneficial for promoting the identification of protein isoforms and studying in-depth the proteolytic activity of proteins.

Combination of continuous digestion by peptidase and spectral similarity comparisons for peptide sequencing.

Peptide sequencing is critical to the quality control of peptide drugs and functional studies of active peptides. A combination of peptidase digestion and mass spectrometry technology is common for peptide sequencing. However, such methods often cannot obtain the complete sequence of a peptide due to insufficient amino acid sequence information. Here, we developed a method of generating full peptide ladders and comparing their MS2 spectral similarities. The peptide ladders, of which each component was different from the next component with one residue, were generated by continuous digestion by peptidase (carboxypeptidase Y and aminopeptidase). Then, based on the characteristics of peptide ladders, complete sequencing was realized by comparing MS2 spectral similarity of the generated peptide ladders. The complete amino acid sequences of bivalirudin, adrenocorticotropic hormone, and oxytocin were determined with high accuracy. This approach is beneficial to the quality control of drug peptides as well as the identification of novel bioactive peptides.

Site-Specific Quantification of Persulfidome by Combining an Isotope-Coded Affinity Tag with Strong Cation-Exchange-Based Fractionation.

Protein persulfidation is one of the most important oxidative translational modifications and plays vital roles in various important biological processes. However, the proteome-wide identification of persulfidation sites is a great challenge because of the difficulties in accurately differentiating persulfide groups with disulfide and thiol groups in proteins as well as the extremely low abundance of persulfidated peptides. By current approaches, the persulfidated peptides were often identified by the cleavage of their persulfide groups by reductants prior to MS analysis; therefore, it would bring about a false positive identification and was unable to identify persulfidation sites accurately for a single peptide with multiple cysteine residues. In this study, a novel strategy for the site-specific quantification of persulfidome (SSQPer) was developed. By this strategy, the persulfidated proteins were first labeled with cleavable isotope-coded affinity tag (c-ICAT) reagents. After digestion, the labeled persulfidated peptides were selectively enriched with streptavidin beads and fractionated by strong cation exchange chromatography, followed by LC-MS/MS identification. To evaluate the performance of SSQPer, the persulfidated BSA digests with 20 persulfidation sites identified were used to spike HeLa cell digests with mass ratios of 1:100 and 1:1000, and 16 and 13 persulfidated sites were respectively identified. We applied SSQPer to the site-specific quantification of persulfidome in the epithelial-mesenchymal transition (EMT) process, and 226 endogenous persulfidation sites were identified, of which 74.3% were newly discovered. All of these results demonstrated that the SSQPer strategy would provide a promising tool to profile the site-specific persulfidome and pave the way for future investigation to expand our knowledge of persulfidation.

A Multiplex Fragment-Ion-Based Method for Accurate Proteome Quantification.

Multiplex proteome quantification with high accuracy is urgently required to achieve a comprehensive understanding of dynamic cellular and physiological processes. Among the existing quantification strategies, fragment-ion-based methods can provide highly accurate results, but the multiplex capacity is limited to 3-plex. Herein, we developed a multiplex pseudo-isobaric dimethyl labeling (m-pIDL) method to extend the capacity of the fragment-ion-based method to 6-plex by one-step dimethyl labeling with several millidalton and dalton mass differences between precursor ions and enlarging the isolation window of precursor ions to 10 m/ z during data acquisition. m-pIDL showed high quantification accuracy within the 20-fold dynamic range. Notably, the ratio compression was 1.13-fold in a benchmark two-proteome model (5:1 mixed E. coli proteins with HeLa proteins as interference), indicating that by m-pIDL, the ratio distortion of isobaric labeling approaches and the approximate 40% ratio shift of the label-free quantification strategy could be effectively eliminated. Additionally, m-pIDL did not show ratio variation among post-translational modifications (CV = 6.66%), which could benefit the measurement of universal protein properties for proteomic atlases. We further employed m-pIDL to monitor the time-resolved responses of the TGF-ß-induced epithelial-mesenchymal transition (EMT) in lung adenocarcinoma A549 cell lines, which facilitated the finding of new potential regulatory proteins. Therefore, the 6-plex quantification of m-pIDL with the remarkably high accuracy might create new prospects for comprehensive proteome analysis.

In-Depth Proteome Coverage by Improving Efficiency for Membrane Proteome Analysis.

Although great achievement has been made in the mapping of human proteome, the efficiency of sample preparation still needs to be improved, especially for membrane proteins. Herein, we presented a novel method to deepen proteome coverage by the sequential extraction of proteins using urea and 1-dodecyl-3- methylimidazolium chloride (C12Im-Cl). With such a strategy, the commonly lost hydrophobic proteins by 8 M urea extraction could be further recovered by C12Im-Cl, as well as the suppression effect of high abundance soluble proteins could be decreased. Followed by the in situ sample preparation and separation with different stationary phases, more than 9810 gene products could be identified, covering 8 orders of magnitude in abundance, which was, to the best of our knowledge, the largest data set of HeLa cell proteome. Compared with previous work, not only the number of proteins identified was obviously increased, but also the analysis time was shortened to a few days. Therefore, we expect that such a strategy has great potential applications to achieve unprecedented coverage for proteome analysis.

In-Depth Proteomic Quantification of Cell Secretome in Serum-Containing Conditioned Medium.

Secreted proteins play key roles during cellular communication, proliferation, and migration. The comprehensive profiling of secreted proteins in serum-containing culture media is technically challenging. Most studies have been performed under serum-free conditions. However, these conditions might alter the status of the cells. Herein, we describe an efficient strategy that avoids the disturbance of serum by combining metabolic labeling, protein "equalization," protein fractionation, and filter-aided sample preparation, called MLEFF, enabling the identification of 534 secreted proteins from HeLa conditioned media, including 31 cytokines, and growth factors. This MLEFF strategy was also successfully applied during a comparative secretome analysis of two human hepatocellular carcinoma cell lines with differentially metastatic potentials, enabling the quantification of 61 significantly changed proteins involved in tumor invasion and metastasis.

Hydrophobic Tagging-Assisted N-Termini Enrichment for In-Depth N-Terminome Analysis.

The analysis of protein N-termini is of great importance for understanding the protein function and elucidating the proteolytic processing. Herein, we develop a negative enrichment strategy, termed as hydrophobic tagging-assisted N-termini enrichment (HYTANE) to achieve a global N-terminome analysis. The HYTANE strategy showed a high efficiency in hydrophobic tagging and C18 material-assisted depletion using bovine serum albumin (BSA) as the sample. This strategy was applied to N-termini profiling from S. cerevisiae cell lysates and enabled the identification of 1096 protein N-termini, representing the largest N-terminome data set of S. cerevisiae. The identified N-terminal peptides accounted for 99% of all identified peptides, and no deficiency in acidic, histidine (His)-containing, and His-free N-terminal peptides was observed. The presented HYTANE strategy is therefore a highly selective, efficient, and unbiased strategy for the large scale N-terminome analysis. Furthermore, using the HYTANE strategy, we identified 329 cleavage sites and 291 substrates of caspases in Jurkat cells, demonstrating the great promise of HYTANE strategy for protease research. Data are available via ProteomeXchange with identifier PXD004690.

Effective isolation of exosomes with polyethylene glycol from cell culture supernatant for in-depth proteome profiling.

Exosomes are secreted nanovesicles shed by almost all kinds of cells. Recently, increased interest has been focused on these extracellular vesicles as natural carriers transporting biological contents for intercellular communication. However, current isolation techniques, such as ultracentrifugation, are not convenient and often require specialized equipment. Herein, we describe a polyethylene glycol (PEG)-based approach, which could permit facile, low-cost and effective isolation of exosomes from cell culture supernatant. High-resolution electron microscopes clearly visualized the size and morphology of isolated exosome aggregates, implying the mechanism of PEG-based precipitation. Combined with tandem mass spectrometry analysis, 6299 protein groups encoded by 5120 genes were successfully characterized from HeLa cell culture supernatant, including numerous exosome proteins which could overlap 97% of the Top 100 exosome marker proteins recorded in the ExoCarta database, as well as a series of low-abundance cytokines and biomarkers. Furthermore, we found a higher ratio of neo-cleavage sites in proteins identified from exosomes compared with cellular proteins, revealing the potential roles of exosomes in accumulation and transportation of protein degradation intermediates.

Pseudo isobaric peptide termini labelling for relative proteome quantification by SWATH MS acquisition.

The pseudo isobaric peptide termini labeling (IPTL) method is a remarkable strategy in quantitative proteomics, and has been efficiently applied in biological studies due to its high quantitative accuracy. However, irreproducible precursor ion selection caused by data dependent acquisition and the chromatographic shift caused by isotope effects limit the wide application of this method. Herein, we expand the use of pseudo IPTL to SWATH MS application and develop a novel quantitative strategy, termed SWATH-pseudo-IPTL, by which the relative quantification could be achieved by comparing the "complete" extracted ion chromatogram (XIC) intensity of MS/MS scan instead of a single intensity measurement in DDA-pseudo-IPTL which only reflected the peptide abundances at that given time. The quantitative analysis of various proportions of mixed HeLa samples revealed the strong accuracy and precision of our SWATH-pseudo-IPTL method, both of which were better than that of the DDA-pseudo-IPTL strategy. SWATH-pseudo-IPTL was also applied to the quantitative profiling of the proteome from human hepatocellular carcinoma cell lines with high and low metastatic potential, and most of the differentially expressed proteins were related to tumorigenesis and tumor metastasis, demonstrating the feasibility of this methodology for biological applications.

Depletion of internal peptides by site-selective blocking, phosphate labeling, and TiO2 adsorption for in-depth analysis of C-terminome.

The analysis of protein C-termini is of great importance, because it not only provides valuable information about protein function, but also facilitates the elucidation of proteolytic processing. However, even with the recent methods for the global profiling of protein C-termini, the identification of C-termini is still far behind that of N-termini due to the lack of basic residue and low reactive carboxyl group. Therefore, an unbiased and complementary method for C-termini profiling is imperative. In this work, we developed a negative enrichment strategy to achieve the in-depth analysis of C-terminome. Proteins were firstly amidated to block carboxyl groups, followed by lysyl endoproteinase (LysC) digestion to generate C-terminal peptides with α-amines and internal peptides bearing both α- and ε-amines. After the α-amines were blocked by site-selective dimethylation or succinylation, the remaining ε-amines on internal peptides were labeled with phosphate groups. Finally, internal peptides were depleted by TiO2, leaving exclusively the fraction of C-terminal peptides for LC-MS/MS analysis. With Escherichia coli (E. coli) digests as the sample, the efficiency of amidation, dimethylation/succinylation, phosphate labeling and TiO2 depletion was proved high. With the combination of dimethyl and succinic blocking strategy, our method enabled the identification of 477 unique C-terminal peptides in E. coli. In comparison with the C-terminal amine-based isotope labeling of substrates (C-TAILS) method, 83 C-termini were identified by both methods, whereas 369 C-termini were unique to C-TAILS and 394 to our dataset. The method proposed is therefore efficient and possibly promotes the comprehensive profiling of C-termini. Graphical Abstract Negative isolation of C-terminal peptides with combination of site-selective blocking, phosphate labeling, and TiO2 adsorption.

A paired ions scoring algorithm based on Morpheus for simultaneous identification and quantification of proteome samples prepared by isobaric peptide termini labeling strategies.

The isobaric peptide termini labeling (IPTL) method is a promising strategy in quantitative proteomics for its high accuracy, while the increased complexity of MS2 spectra originated from the paired b, y ions has adverse effect on the identification and the coverage of quantification. Here, a paired ions scoring algorithm (PISA) based on Morpheus, a database searching algorithm specifically designed for high-resolution MS2 spectra, was proposed to address this issue. PISA was first tested on two 1:1 mixed IPTL datasets, and increases in peptide to spectrum matchings, distinct peptides and protein groups compared to Morpheus itself and MASCOT were shown. Furthermore, the quantification is simultaneously performed and 100% quantification coverage is achieved by PISA since each of the identified peptide to spectrum matchings has several pairs of fragment ions which could be used for quantification. Then the PISA was applied to the relative quantification of human hepatocellular carcinoma cell lines with high and low metastatic potentials prepared by an IPTL strategy.

Improved accuracy for label-free absolute quantification of proteome by combining the Absolute Protein EXpression profiling algorithm and summed tandem mass spectrometric total ion current.

Proteome scale absolute quantification is fundamental for the quantitative understanding of an organism. The unsatisfactory accuracy for protein abundance estimation of current algorithms has been partially improved by the Absolute Protein EXpression profiling (APEX) algorithm, which implements the prior expectations of peptides' appearances in the calculation of protein abundances. However, the abundance feature (AF) in APEX is the spectral count (SC); an AF suffers from a narrow dynamic range, thus, unsatisfactory accuracy. Therefore, we adopted another tandem mass spectrometric (MS/MS) level AF called Summed MS/MS Total ion current (SMT), which cumulates the MS/MS fragment intensities rather than simply counting the MS/MS spectra, to surmount this particular deficiency. The combination of APEX and SMT (abbreviated as APEX-SMT) is capable of improving the accuracy of absolute quantification by reducing the average relative deviation by ~55-85% compared to that of APEX, through a series of tests on the Universal Proteomics Standard sample with a dynamic range of 5 orders of magnitude (UPS2). The algorithm could also be used for relative quantification. When applied to the relative quantification of a publicly available benchmark dataset, APEX-SMT could provide comparable accuracy to APEX. All these results suggest that APEX-SMT is a promising alternative to APEX for proteome quantification.

[An enrichment strategy based on hydrophobic tagging and reversed-phase chromatographic separation for the analysis of lysine-containing peptides].

Lysine (K) is widely used in the design of lysine-targeted crosslinkers, structural elucidation of protein complexes, and analysis of protein-protein interactions. In "shotgun" proteomics, which is based on liquid chromatography-tandem mass spectrometry (LC-MS/MS), proteins from complex samples are enzymatically digested, generating thousands of peptides and presenting significant challenges for the direct analysis of K-containing peptides. In view of the lack of effective methods for the enrichment of K-containing peptides, this work developed a method which based on a hydrophobic-tag-labeling reagent C10-S-S-NHS and reversed-phase chromatography (termed as HYTARP) to achieve the efficient enrichment and identification of K-containing peptides from complex samples. The C10-S-S-NHS synthesized in this work successfully labeled standard peptides containing various numbers of K and the labeling efficiency achieved up to 96% for HeLa cell protein tryptic digests. By investigating the retention behavior of these labeled peptides in C18 RP column, we found that most K-labeled peptides were eluted once when acetonitrile percentage reached 57.6% (v/v). Further optimization of the elution gradient enabled the efficient separation and enrichment of the K-labeled peptides in HeLa digests via a stepwise elution gradient. The K-labeled peptides accounted for 90% in the enriched peptides, representing an improvement of 35% compared with the number of peptides without the enrichment. The dynamic range of proteins quantified from the enriched K-containing peptides spans 5-6 orders of magnitude, and realized the detection of low-abundance proteins in the complex sample. In summary, the HYTARP strategy offers a straightforward and effective approach for reducing sample complexity and improving the identification coverage of K-containing peptides and low-abundance proteins.