HCD-only fragmentation method balances peptide identification and quantitation of TMT-labeled samples in hybrid linear ion trap/orbitrap mass spectrometers

Identification of candidate genes and residues for improving nitrogen use efficiency in the N-sensitive medicinal plant Panax notoginseng

BACKGROUND

Nitrogen (N) metabolism-related key genes and conserved amino acid sites in key enzymes play a crucial role in improving N use efficiency (NUE) under N stress. However, it is not clearly known about the molecular mechanism of N deficiency-induced improvement of NUE in the N-sensitive rhizomatous medicinal plant Panax notoginseng (Burk.) F. H. Chen. To explore the potential regulatory mechanism, the transcriptome and proteome were analyzed and the three-dimensional (3D) information and molecular docking models of key genes were compared in the roots of P. notoginseng grown under N regimes.

RESULTS

Total N uptake and the proportion of N distribution to roots were significantly reduced, but the NUE, N use efficiency in biomass production (NUEb), the recovery of N fertilizer (RNF) and the proportion of N distribution to shoot were increased in the N0-treated (without N addition) plants. The expression of N uptake- and transport-related genes NPF1.2, NRT2.4, NPF8.1, NPF4.6, AVP, proteins AMT and NRT2 were obviously up-regulated in the N0-grown plants. Meanwhile, the expression of CIPK23, PLC2, NLP6, TCP20, and BT1 related to the nitrate signal-sensing and transduction were up-regulated under the N0 condition. Glutamine synthetase (GS) activity was decreased in the N-deficient plants, while the activity of glutamate dehydrogenase (GDH) increased. The expression of genes GS1-1 and GDH1, and proteins GDH1 and GDH2 were up-regulated in the N0-grown plants, there was a significantly positive correlation between the expression of protein GDH1 and of gene GDH1. Glu192, Glu199 and Glu400 in PnGS1 and PnGDH1were the key amino acid residues that affect the NUE and lead to the differences in GDH enzyme activity. The 3D structure, docking model, and residues of Solanum tuberosum and P. notoginseng was similar.

CONCLUSIONS

N deficiency might promote the expression of key genes for N uptake (genes NPF8.1, NPF4.6, AMT, AVP and NRT2), transport (NPF1.2 and NRT2.4), assimilation (proteins GS1 and GDH1), signaling and transduction (genes CIPK23, PLC2, NLP6, TCP20, and BT1) to enhance NUE in the rhizomatous species. N deficiency might induce Glu192, Glu199 and Glu400 to improve the biological activity of GS1 and GDH, this has been hypothesized to be the main reason for the enhanced ability of N assimilation in N-deficient rhizomatous species. The key genes and residues involved in improving NUE provide excellent candidates for the breeding of medicinal plants.

Collision energies: Optimization strategies for bottom-up proteomics

Mass-spectrometry coupled to liquid chromatography is an indispensable tool in the field of proteomics. In the last decades, more and more complex and diverse biochemical and biomedical questions have arisen. Problems to be solved involve protein identification, quantitative analysis, screening of low abundance modifications, handling matrix effect, and concentrations differing by orders of magnitude. This led the development of more tailored protocols and problem centered proteomics workflows, including advanced choice of experimental parameters. In the most widespread bottom-up approach, the choice of collision energy in tandem mass spectrometric experiments has outstanding role. This review presents the collision energy optimization strategies in the field of proteomics which can help fully exploit the potential of MS based proteomics techniques. A systematic collection of use case studies is then presented to serve as a starting point for related further scientific work. Finally, this article discusses the issue of comparing results from different studies or obtained on different instruments, and it gives some hints on methodology transfer between laboratories based on measurement of reference species.

Optimization of Higher-Energy Collisional Dissociation Fragmentation Energy for Intact Protein-Level Tandem Mass Tag Labeling

Isobaric chemical tag labeling (e.g., TMT) is a commonly used approach in quantitative proteomics, and quantification is enabled through detection of low-mass reporter ions generated after MS2 fragmentation. Recently, we have introduced and optimized an intact protein-level TMT labeling platform that demonstrated >90% labeling efficiency in complex samples with top-down proteomics. Higher-energy collisional dissociation (HCD) is commonly utilized for isobaric tag-labeled peptide fragmentation because it produces accurate reporter ion intensities and avoids loss of low mass ions. HCD energies have been optimized for isobaric tag labeled-peptides but have not been systematically evaluated for isobaric tag-labeled intact proteins. In this study, we report a systematic evaluation of normalized HCD fragmentation energies (NCEs) on TMT-labeled HeLa cell lysate using top-down proteomics. Our results suggested that reporter ions often result in higher ion intensities at higher NCEs. Optimal fragmentation of intact proteins for identification, however, required relatively lower NCE. We further demonstrated that a stepped NCE scheme with energies from 30% to 50% resulted in optimal quantification and identification of TMT-labeled HeLa proteins. These parameters resulted in an average reporter ion intensity of ∼4E4 and average proteoform spectrum matches (PrSMs) of >1000 per RPLC-MS/MS run with a 1% false discovery rate (FDR) cutoff.

Advancing Target Identification of Nitrated Phospholipids in Biological Systems by HCD Specific Fragmentation Fingerprinting in Orbitrap Platforms

Nitrated phospholipids have recently been detected in vitro and in vivo and associated with beneficial health effects. They were identified and quantified in biological samples by lipidomics methodologies using liquid chromatography-collision-induced dissociation (CID) tandem mass spectrometry (MS/MS) acquired with the linear ion trap mass spectrometer. Only a few studies have used higher-energy collision dissociation (HCD)-MS/MS in high-resolution Orbitraps to characterize nitrated phosphatidylserines and nitrated cardiolipins, highlighting the marked differences in the fragmentation patterns when using CID or HCD fragmentation methods. In this study, we aimed to evaluate the fragmentation of nitrated phosphatidylcholine and nitrated phosphatidylethanolamine species under HCD-MS/MS. We studied the effect of normalized collision energy (NCE) in the fragmentation pattern to identify the best acquisition conditions and reporter ions to detect nitrated phospholipids. The results showed that the intensity of the typical neutral loss of nitrous acid (HNO₂) diminishes with increasing NCE, becoming non-detectable for a higher NCE. Thus, the loss of HNO₂ could not be the most suitable ion/fragment for the characterization of nitrated phospholipids under HCD. In HCD-MS/MS new fragment ions were identified, corresponding to the nitrated fatty acyl chains, NO₂-RCOO⁻, (NO₂-RCOOH-H₂O + H)⁺, and (NO₂-RCOOH + H)⁺, suggested as potential reporter ions to detect nitrated phospholipids when using the HCD-MS/MS lipidomics analysis.

Quantitative Peptidomics with Isotopic and Isobaric Tags

In differential peptidomics, peptide profiles are compared between biological samples and the resulting expression levels are correlated to a phenotype of interest. This, in turn, allows us insight into how peptides may affect the phenotype of interest. In quantitative differential peptidomics, both label-based and label-free techniques are often employed. Label-based techniques have several advantages over label-free methods, primarily that labels allow for various samples to be pooled prior to liquid chromatography-mass spectrometry (LC-MS) analysis, reducing between-run variation. Here, we detail a method for performing quantitative peptidomics using stable amine-binding isotopic and isobaric tags.

High-resolution enabled 12-plex DiLeu isobaric tags for quantitative proteomics

Multiplex isobaric tags (e.g., tandem mass tags (TMT) and isobaric tags for relative and absolute quantification (iTRAQ)) are a valuable tool for high-throughput mass spectrometry based quantitative proteomics. We have developed our own multiplex isobaric tags, DiLeu, that feature quantitative performance on par with commercial offerings but can be readily synthesized in-house as a cost-effective alternative. In this work, we achieve a 3-fold increase in the multiplexing capacity of the DiLeu reagent without increasing structural complexity by exploiting mass defects that arise from selective incorporation of ¹³C, ¹⁵N, and ²H stable isotopes in the reporter group. The inclusion of eight new reporter isotopologues that differ in mass from the existing four reporters by intervals of 6 mDa yields a 12-plex isobaric set that preserves the synthetic simplicity and quantitative performance of the original implementation. We show that the new reporter variants can be baseline-resolved in high-resolution higher-energy C-trap dissociation (HCD) spectra, and we demonstrate accurate 12-plex quantitation of a DiLeu-labeled Saccharomyces cerevisiae lysate digest via high-resolution nano liquid chromatography–tandem mass spectrometry (nanoLC–MS²) analysis on an Orbitrap Elite mass spectrometer.

Isobaric labeling-based relative quantification in shotgun proteomics

Mass spectrometry plays a key role in relative quantitative comparisons of proteins in order to understand their functional role in biological systems upon perturbation. In this review, we review studies that examine different aspects of isobaric labeling-based relative quantification for shotgun proteomic analysis. In particular, we focus on different types of isobaric reagents and their reaction chemistry (e.g., amine-, carbonyl-, and sulfhydryl-reactive). Various factors, such as ratio compression, reporter ion dynamic range, and others, cause an underestimation of changes in relative abundance of proteins across samples, undermining the ability of the isobaric labeling approach to be truly quantitative. These factors that affect quantification and the suggested combinations of experimental design and optimal data acquisition methods to increase the precision and accuracy of the measurements will be discussed. Finally, the extended application of isobaric labeling-based approach in hyperplexing strategy, targeted quantification, and phosphopeptide analysis are also examined.