MOESM1 of Antigen 85B peptidomic analysis allows species-specific mycobacterial identification

Additional file 1: Table S1. Ag85B target peptide identification and quantification by LC-MS/MS PRM mode

Profiling and Relative Quantitation of Phosphoinositides by Multiple Precursor Ion Scanning Based on Phosphate Methylation and Isotopic Labeling

Phosphoinositides, the phosphorylated derivatives of phosphatidylinositol (PtdIns), are key regulators of many fundamental biological processes, including cell growth, proliferation, and motility. Here, we present a novel method for rapid, sensitive, and simultaneous profiling of phosphatidylinositol trisphosphate (PtdInsP₃), phosphatidylinositol bisphosphate (PtdInsP₂), and phosphatidylinositol phosphate (PtdInsP) of different fatty acid compositions. This method is based on a technique called “charged diacylglycerol fragment ion-specific multiple precursor ion scanning” (DAG⁺-specific MPIS), coupled with prior phosphate methylation. Using DAG⁺-specific MPIS, we were able to identify 32 PtdIns, 28 PtdInsP, 30 PtdInsP₂, and 3 PtdInsP₃ molecular species from bovine brain extracts or prostatic cancer cell lines in an efficient and time-saving manner. Our analysis revealed a large range of fatty acyl compositions in phosphoinositides not obtained previously from mammalian samples. We also developed a method that involves isotopic labeling of endogenous phosphoinositides with deuterated diazomethane (CD₂N₂) for quantitation of phosphoinositides. CD₂N₂ was generated in situ through acid-catalyzed H/D exchange and methanolysis of trimethylsilyl diazomethane (TMS-diazomethane). Phosphoinositides, extracted from a PC3 prostatic cancer cell line, were labeled either with CH₂N₂ or CD₂N₂ and mixed in known proportions for DAG⁺-specific MPIS-based mass spectrometry (MS) analysis. The results indicate that isotopic labeling is capable of providing accurate quantitation of PtdInsP₃, PtdInsP₂, and PtdInsP with adequate linearity as well as high reproducibility with an average coefficient variation of 18.9%. More importantly, this new methods excluded the need for multiple phosphoinositide internal standards. DAG⁺-specific MPIS and isotopic labeling based MS analysis of phosphoinositides offers unique advantages over existing approaches and presents a powerful tool for research of phosphoinositide metabolism

Evaluation of Different N‑Glycopeptide Enrichment Methods for N‑Glycosylation Sites Mapping in Mouse Brain

N-Glycosylation of proteins plays a critical role in many biological pathways. Because highly heterogeneous N-glycopeptides are present in biological sources, the enrichment procedure is a crucial step for mass spectrometry analysis. Five enrichment methods, including IP-ZIC-HILIC, hydrazide chemistry, lectin affinity, ZIC-HILIC-FA, and TiO₂ affinity were evaluated and compared in the study of mapping N-glycosylation sites in mouse brain. On the basis of our results, the identified N-glycosylation sites were 1891, 1241, 891, 869, and 710 and the FDR values were 3.29, 5.62, 9.54, 9.54, and 20.02%, respectively. Therefore, IP-ZIC-HILIC enrichment method displayed the highest sensitivity and specificity. In this work, we identified a total of 3446 unique glycosylation sites conforming to the N-glycosylation consensus motif (N-X-T/S/C; X ≠ P) with ¹⁸O labeling in 1597 N-glycoproteins. N-glycosylation site information was used to confirm or correct the transmembrane topology of the 57 novel transmembrane N-glycoproteins

Proteomic Comparison and MRM-Based Comparative Analysis of Metabolites Reveal Metabolic Shift in Human Prostate Cancer Cell Lines

One of the major challenges in prostate cancer therapy remains the development of effective treatments for castration-resistant prostate cancer (CRPC), as the underlying mechanisms for its progression remain elusive. Previous studies showed that androgen receptor (AR) is crucially involved in regulation of metabolism in prostate cancer (PCa) cells throughout the transition from early stage, androgen-sensitive PCa to androgen-independent CRPC. AR achieves such metabolic rewiring directively either via its transcriptional activity or via interactions with AMP-activated protein kinase (AMPK). However, due to the heterogeneous expression and activity status of AR in PCa cells, it remains a challenge to investigate the links between AR status and metabolic alterations. To this end, we compared the proteomes of three pairs of androgen-sensitive (AS) and androgen-independent (AI) PCa cell lines, namely, PC3-AR⁺/PC3, 22Rv1/Du145, and LNCaP/C42B, using an iTRAQ labeling approach. Our results revealed that most of the differentially expressed proteins between each pair function in metabolism, indicating a metabolic shift between AS and AI cells, as further validated by multiple reaction monitoring (MRM)-based quantification of nucleotides and relative comparison of fatty acids between these cell lines. Furthermore, increased adenylate kinase isoenzyme 1 (AK1) in AS relative to AI cells may result in activation of AMPK, representing a major regulatory factor involved in the observed metabolic shift in PCa cells

Proteomic Comparison and MRM-Based Comparative Analysis of Metabolites Reveal Metabolic Shift in Human Prostate Cancer Cell Lines

One of the major challenges in prostate cancer therapy remains the development of effective treatments for castration-resistant prostate cancer (CRPC), as the underlying mechanisms for its progression remain elusive. Previous studies showed that androgen receptor (AR) is crucially involved in regulation of metabolism in prostate cancer (PCa) cells throughout the transition from early stage, androgen-sensitive PCa to androgen-independent CRPC. AR achieves such metabolic rewiring directively either via its transcriptional activity or via interactions with AMP-activated protein kinase (AMPK). However, due to the heterogeneous expression and activity status of AR in PCa cells, it remains a challenge to investigate the links between AR status and metabolic alterations. To this end, we compared the proteomes of three pairs of androgen-sensitive (AS) and androgen-independent (AI) PCa cell lines, namely, PC3-AR⁺/PC3, 22Rv1/Du145, and LNCaP/C42B, using an iTRAQ labeling approach. Our results revealed that most of the differentially expressed proteins between each pair function in metabolism, indicating a metabolic shift between AS and AI cells, as further validated by multiple reaction monitoring (MRM)-based quantification of nucleotides and relative comparison of fatty acids between these cell lines. Furthermore, increased adenylate kinase isoenzyme 1 (AK1) in AS relative to AI cells may result in activation of AMPK, representing a major regulatory factor involved in the observed metabolic shift in PCa cells

Proteomic Comparison and MRM-Based Comparative Analysis of Metabolites Reveal Metabolic Shift in Human Prostate Cancer Cell Lines

One of the major challenges in prostate cancer therapy remains the development of effective treatments for castration-resistant prostate cancer (CRPC), as the underlying mechanisms for its progression remain elusive. Previous studies showed that androgen receptor (AR) is crucially involved in regulation of metabolism in prostate cancer (PCa) cells throughout the transition from early stage, androgen-sensitive PCa to androgen-independent CRPC. AR achieves such metabolic rewiring directively either via its transcriptional activity or via interactions with AMP-activated protein kinase (AMPK). However, due to the heterogeneous expression and activity status of AR in PCa cells, it remains a challenge to investigate the links between AR status and metabolic alterations. To this end, we compared the proteomes of three pairs of androgen-sensitive (AS) and androgen-independent (AI) PCa cell lines, namely, PC3-AR⁺/PC3, 22Rv1/Du145, and LNCaP/C42B, using an iTRAQ labeling approach. Our results revealed that most of the differentially expressed proteins between each pair function in metabolism, indicating a metabolic shift between AS and AI cells, as further validated by multiple reaction monitoring (MRM)-based quantification of nucleotides and relative comparison of fatty acids between these cell lines. Furthermore, increased adenylate kinase isoenzyme 1 (AK1) in AS relative to AI cells may result in activation of AMPK, representing a major regulatory factor involved in the observed metabolic shift in PCa cells