Deep analysis of total serum N-glycome suggests glyco-signatures for phospholipase A2 receptor 1-related idiopathic membranous nephropathy diagnosis.

Idiopathic membranous nephropathy (IMN) is an antibody-mediated and kidney-specific autoimmune disease, with the antigen phospholipase A2 receptor 1 (PLA2R1) accounting for approximately 70% of IMN cases. Although a variety of new podocyte target antigens and their autoantibodies have been identified, they are still of limited diagnostic and therapeutic value due to lack of high specificity and sensitivity. N-glycans play vital roles in renal system and their pathobiological relevance has become increasingly recognized in many kidney diseases, but not fully explored in IMN. To find possible glyco-signatures for PLA2R1-related IMN diagnosis, we herein established a comprehensive workflow for total serum N-glycome analysis based on our recently developed mass spectrometry (MS)-based N-glycan purification method, named Ultrafast Glycoprotein Immobilization for Glycan extraction (UltraGIG). A total of 191 N-glycans were identified from IMN patients, representing the largest N-glycome dataset in IMN. Compared to healthy controls, up-regulation of sialylation and core-fucosylation as well as down-regulation of galactosylation were observed in PLA2R1-positive IMN patients, and up-regulation of hyper-galactosylation was specific for PLA2R1-negative IMN patients. A six-glycan marker panel consisting of H4N3S1, H4N3F1, H6N4S2, H6H5F1S2, H6N5 and H6N6F1S1, was proposed to aid in the accurate diagnosis of PLA2R1-related IMN, which provided new insights into IMN biomarker study. SIGNIFICANCE: PLA2R1-related IMN is a kidney-specific autoimmune disease with a high risk of developing end-stage renal disease (ESRD) and even kidney failure. Current biomarkers are still of limited diagnostic and therapeutic value due to lack of high specificity and sensitivity. An in-depth MS analysis of total serum N-glycome of PLA2R1-related IMN patients was conducted for the first time. We generated the largest dataset of serum N-glycome for IMN to date, and proposed a novel six-glycan marker panel that may help the accurate diagnosis of PLA2R1-related IMN.

An efficient, amine-specific iTRAQ labeling method improves the peptide and protein identification rates.

Isotope tags for relative and absolute quantification (iTRAQ) are among the most widely used proteomics quantification techniques. These tags can be rapidly coupled to the primary amines of proteins/peptides through chemical reactions under mild conditions, making this technique universally applicable to any kind of sample. However, iTRAQ reagents also partially react with the hydroxyl groups of serine, threonine and tyrosine residues, particularly when these residues coexist with a histidine residue in the same peptide. This overlabeling of peptides causes systematic biases and significantly compromises protein/peptide identification rates. In this study, we report a novel iTRAQ labeling method that overcomes the detrimental overlabeling while providing high amine labeling efficiency. The impacts of reaction temperature, reactant concentrations, reaction time, buffer compositions, and pH on iTRAQ labeling performance were investigated in-depth. In a comparison experiment between our method and the standard labeling method provided by the iTRAQ manufacturer, our method reduced the number of overlabeled peptides by 55-fold while achieving comparable amine labeling efficiency. This improvement allowed our method to eliminates the systematic bias against histidyl- and hydroxyl-containing peptides, and more importantly, enabled the identification of 23.9% more peptides and 9.8% more proteins. SIGNIFICANCE: In addition to amines, the hydroxyl groups in serine, threonine, and tyrosine residues can also partially labeled by iTRAQ reagents, which leads to systematic biases and significantly compromises the analytical sensitivity. To address this issue, we developed a novel iTRAQ labeling method that overcomes the detrimental overlabeling while providing high labeling efficiency of amines. When benchmarking our method against the standard method provided by the reagent manufacturer, our method achieved comparable labeling efficiency but reduced the overlabeled species by 55-fold. This significant improvement eliminated the systematic biases, and more importantly, enabled the identification of 23.9% more peptides and 9.8% more proteins, demonstrating its superior performance and potential to enhance proteome quantification using iTRAQ labeling.

Overcoming the detrimental O-acylation in TMTpro labeling improves the proteome depth and quantification precision.

BACKGROUND: With the advent of proline-based reporter isobaric Tandem Mass Tag (TMTpro) reagents, the sample multiplexing capacity of tandem mass tags (TMTs) has been expanded, and up to 18 samples can be quantified in a multiplexed manner. Like classic TMT reagents, TMTpro reagents contain a tertiary amine group, which markedly enhances their reactivity toward hydroxyl groups and results in O-acylation of serine, threonine and tyrosine residues. This overlabeling significantly compromises proteome analysis in terms of depth and precision. In particular, the reactivity of hydroxyl-containing residues can be dramatically enhanced when coexisting with a histidine in the same peptides, leading to a severe systematic bias against the analysis of these peptides. Although some protocols using a reduced molar excess of TMT under alkaline conditions can alleviate overlabeling of histidine-free peptides to some extent, they have a limited effect on histidyl- and hydroxyl-containing peptides. RESULTS: Here, we report a novel TMTpro labeling method that overcomes detrimental overlabeling while providing high labeling efficiency of amines. Additionally, our method is cost-effective, as it requires only half the amount of TMTpro reagents recommended by the reagent manufacturer. In a deep-scale analysis of a yeast/human two-proteome model sample, we compared our method with a typical alkaline labeling method using a reduced molar excess of TMTpro. Even at a depth of over 10,000 proteins, our method detected 23.7% more unique peptides and 8.7% more protein groups compared to the alkaline labeling method. Moreover, our method significantly improved the quantitative precision due to the reduced variability in labeling and increased protein sequence coverage. This substantially enhanced the statistical power of our method for detecting differentially abundant proteins, providing an average of 13% more yeast proteins that reached statistical significance. SIGNIFCANCE: We presented a novel TMTpro labeling method that overcomes the detrimental O-acylation and thus significantly improves the depth and quantitative precision for proteome analysis.

An Efficient, Amine-Specific, and Cost-Effective Method for TMT 6/11-plex Labeling Improves the Proteome Coverage, Quantitative Accuracy and Precision.

Tandem mass tags (TMT) are widely used in proteomics to simultaneously quantify multiple samples in a single experiment. The tags can be easily added to the primary amines of peptides/proteins through chemical reactions. In addition to amines, TMT reagents also partially react with the hydroxyl groups of serine, threonine, and tyrosine residues under alkaline conditions, which significantly compromises the analytical sensitivity and precision. Under alkaline conditions, reducing the TMT molar excess can partially mitigate overlabeling of histidine-free peptides, but has a limited effect on peptides containing histidine and hydroxyl groups. Here, we present a method under acidic conditions to suppress overlabeling while efficiently labeling amines, using only one-fifth of the TMT amount recommended by the manufacturer. In a deep-scale analysis of a yeast/human two-proteome sample, we systematically evaluated our method against the manufacturer's method and a previously reported TMT-reduced method. Our method reduced overlabeled peptides by 9-fold and 6-fold, respectively, resulting in the substantial enhancement in peptide/protein identification rates. More importantly, the quantitative accuracy and precision were improved as overlabeling was reduced, endowing our method with greater statistical power to detect 42% and 12% more statistically significant yeast proteins compared to the standard and TMT-reduced methods, respectively. Mass spectrometric data have been deposited in the ProteomeXchange Consortium via the iProX partner repository with the data set identifier PXD047052.

LINC02454-CCT complex interaction is essential for telomerase activity and cell proliferation in head and neck squamous cell carcinoma.

Telomerase activity is upregulated in head and neck squamous cell carcinoma (HNSCC), yet its regulatory mechanisms remain unclear. Here, we identified a cancer-specific lncRNA (LINC02454) associated with poor prognosis by using LncRNA chip of our HNSCC cohorts and external datasets. Through employing negative-stain transmission electron microscopy (NS-TEM), we discovered an interaction between LINC02454 and CCT complex which would augment telomerase activity for maintaining telomere homeostasis. Supporting this, in the telomerase repeat amplification protocol (TRAP) assay and quantitative fluorescence in situ hybridization (Q-FISH) analysis, LINC02454 depletion significantly reduced telomerase activity and shortened telomere length. Consistently, pathways related to telomerase, mitosis, and apoptosis were significantly impacted upon LINC02454 knockdown in RNAseq analysis. Functionally, LINC02454-deficient cells exhibited a more significant senescence phenotype in ß-galactosidase staining, cell cycle, and apoptosis assays. We further confirmed the role of LINC02454 in HNSCC proliferation through a combination of in vitro and in vivo experiments. The therapeutic potential of targeting LINC02454 was verified by adenovirus-shRNA approach in HNSCC patient-derived xenograft (PDX) models. In summary, our findings provided valuable insights into the molecular mechanisms of HNSCC tumorigenesis and potential targets for future treatment modalities.

A simplified protocol for deep quantitative proteomic analysis of gingival crevicular fluid for skeletal maturity indicators.

Assessment of craniofacial skeletal maturity is of great importance in orthodontic diagnosis and treatment planning. Traditional radiographic methods suffer from clinician subjectivity and low reproducibility. Recent biochemical methods, such as the use of gingival crevicular fluid (GCF) protein biomarkers involved in bone metabolism, have provided new opportunities to assess skeletal maturity. However, mass spectrometry (MS)-based GCF proteomic analysis still faces significant challenges, including the interference of high abundance proteins, laborious sample prefractionation and relatively limited coverage of GCF proteome. To improve GCF sample processing and further discover novel biomarkers, we herein developed a single-pot, solid-phase-enhanced sample-preparation (SP3)-based high-field asymmetric waveform ion mobility spectrometry (FAIMS)-MS protocol for deep quantitative analysis of the GCF proteome for skeletal maturity indicators. SP3 combined with FAIMS could minimize sample loss and eliminate tedious and time-consuming offline fractionation, thereby simplifying GCF sample preparation and improving analytical coverage and reproducibility of the GCF proteome. A total of 5407 proteins were identified in GCF samples from prepubertal and circumpubertal groups, representing the largest dataset of human GCF proteome to date. Compared to the prepubertal group, 61 proteins were differentially expressed (31 up-regulated, 30 down-regulated) in the circumpubertal group. The six-protein marker panel, including ATP5D, CLTA, CLTB, DNM2, HSPA8 and NCK1, showed great potential to predict the circumpubertal stage (ROC-AUC 0.937), which provided new insights into skeletal maturity assessment.