An efficient approach based on basic strong cation exchange chromatography for enriching methylated peptides with high specificity for methylproteomics analysis

Hydrophobic Derivatization Strategy Facilitates Comprehensive Profiling of Protein Methylation

Protein methylation is receiving more and more attention due to its essential role in diverse biological processes. Large-scale analysis of protein methylation requires the efficient identification of methylated peptides at the proteome level; unfortunately, a significant number of methylated peptides are highly hydrophilic and hardly retained during reversed-phase chromatography, making it difficult to be identified by conventional approaches. Herein, we report the development of a novel strategy by combining hydrophobic derivatization and high pH strong cation exchange enrichment, which significantly expands the identification coverage of the methylproteome. Noteworthily, the total number of identified methylated short peptides was improved by more than 2-fold. By this strategy, we identified 492 methylation sites from NCI-H460 cells compared to only 356 sites identified in native forms. The identification of methylation sites before and after derivatization was highly complementary. Approximately 2-fold the methylation sites were obtained by combining the results identified in both approaches (native and derivatized) as compared with the only analysis in native forms. Therefore, this novel chemical derivatization strategy is a promising approach for the comprehensive identification of protein methylation by improving the identification of methylated short peptides.

Nanoproteomics deciphers the prognostic value of EGFR family proteins-based liquid biopsy

Monitoring tumor-associated protein status in serum can effectively track tumors and avoid time-consuming, costly, and invasive tissue biopsy. Epidermal growth factor receptor (EGFR) family proteins are often recommended in the clinical management of multiple solid tumors. However, the low-abundance of serum EGFR (sEGFR) family proteins hinders the depth-understanding of their function and tumor management. Herein, a nanoproteomics approach coupling with aptamer-modified MOFs (NMOFs-Apt) with mass spectrometry was developed for the enrichment and quantitative analysis of sEGFR family proteins. This nanoproteomics approach exhibited high sensitivity and specificity for sEGFR family protein quantification, with the limit of quantification as low as 1.00 nM. After detecting 626 patients' sEGFR family proteins with various malignant tumors, we concluded that the levels of serum proteins had a moderate concordance with tissue counterparts. Metastatic breast cancer patients with a high level of serum human epidermal growth factor receptor 2 (sHER2) and a low level of sEGFR had a poor prognosis, and patients with a sHER2 decrease of more than 20% had longer disease-free time after receiving chemotherapy. This nanoproteomics method provided a simple and effective approach for low-abundant serum protein detection and our results clarified the potential of sHER2 and sEGFR as cancer markers.

Global lysine methylome profiling using systematically characterized affinity reagents

Lysine methylation modulates the function of histone and non-histone proteins, and the enzymes that add or remove lysine methylation-lysine methyltransferases (KMTs) and lysine demethylases (KDMs), respectively-are frequently mutated and dysregulated in human diseases. Identification of lysine methylation sites proteome-wide has been a critical barrier to identifying the non-histone substrates of KMTs and KDMs and for studying functions of non-histone lysine methylation. Detection of lysine methylation by mass spectrometry (MS) typically relies on the enrichment of methylated peptides by pan-methyllysine antibodies. In this study, we use peptide microarrays to show that pan-methyllysine antibodies have sequence bias, and we evaluate how the differential selectivity of these reagents impacts the detection of methylated peptides in MS-based workflows. We discovered that most commercially available pan-Kme antibodies have an in vitro sequence bias, and multiple enrichment approaches provide the most comprehensive coverage of the lysine methylome. Overall, global lysine methylation proteomics with multiple characterized pan-methyllysine antibodies resulted in the detection of 5089 lysine methylation sites on 2751 proteins from two human cell lines, nearly doubling the number of reported lysine methylation sites in the human proteome.

Proteomics of post-translational modifications in colorectal cancer: Discovery of new biomarkers

Colorectal cancer (CRC) is one of the costliest health problems and ranks second in cancer-related mortality in developed countries. With the aid of proteomics, many protein biomarkers for the diagnosis, prognosis, and precise management of CRC have been identified. Furthermore, some protein biomarkers exhibit structural diversity after modifications. Post-translational modifications (PTMs), most of which are catalyzed by a variety of enzymes, extensively increase protein diversity and are involved in many complex and dynamic cellular processes through the regulation of protein function. Accumulating evidence suggests that abnormal PTM events are associated with a variety of human diseases, such as CRC, thus highlighting the need for studying PTMs to discover both the molecular mechanisms and therapeutic targets of CRC. In this review, we begin with a brief overview of the importance of protein PTMs, discuss the general strategies for proteomic profiling of several key PTMs (including phosphorylation, acetylation, glycosylation, ubiquitination, methylation, and citrullination), shift the emphasis to describing the specific methods used for delineating the global landscapes of each of these PTMs, and summarize the recent applications of these methods to explore the potential roles of the PTMs in CRC. Finally, we discuss the current status of PTM research on CRC and provide future perspectives on how PTM regulation can play an essential role in translational medicine for early diagnosis, prognosis stratification, and therapeutic intervention in CRC.

Automated ion exchange chromatography screening combined with in silico multifactorial simulation for efficient method development and purification of biopharmaceutical targets

Bioprocess development of increasingly challenging therapeutics and vaccines requires a commensurate level of analytical innovation to deliver critical assays across functional areas. Chromatography hyphenated to numerous choices of detection has undeniably been the preferred analytical tool in the pharmaceutical industry for decades to analyze and isolate targets (e.g., APIs, intermediates, and byproducts) from multicomponent mixtures. Among many techniques, ion exchange chromatography (IEX) is widely used for the analysis and purification of biopharmaceuticals due to its unique selectivity that delivers distinctive chromatographic profiles compared to other separation modes (e.g., RPLC, HILIC, and SFC) without denaturing protein targets upon isolation process. However, IEX method development is still considered one of the most challenging and laborious approaches due to the many variables involved such as elution mechanism (via salt, pH, or salt-mediated-pH gradients), stationary phase's properties (positively or negatively charged; strong or weak ion exchanger), buffer type and ionic strength as well as pH choices. Herein, we introduce a new framework consisting of a multicolumn IEX screening in conjunction with computer-assisted simulation for efficient method development and purification of biopharmaceuticals. The screening component integrates a total of 12 different columns and 24 mobile phases that are sequentially operated in a straightforward automated fashion for both cation and anion exchange modes (CEX and AEX, respectively). Optimal and robust operating conditions are achieved via computer-assisted simulation using readily available software (ACD Laboratories/LC Simulator), showcasing differences between experimental and simulated retention times of less than 0.5%. In addition, automated fraction collection is also incorporated into this framework, illustrating the practicality and ease of use in the context of separation, analysis, and purification of nucleotides, peptides, and proteins. Finally, we provide examples of the use of this IEX screening as a framework to identify efficient first dimension (¹D) conditions that are combined with MS-friendly RPLC conditions in the second dimension (²D) for two-dimensional liquid chromatography experiments enabling purity analysis and identification of pharmaceutical targets.