Isobaric Labeling Strategy Research Articles

6-Plex Tandem Phosphorus Tags (TPT) for Accurate Quantitative Proteomics.

Isobaric chemical labeling is a widely used strategy for high-throughput quantitative proteomics based on mass spectrometry. However, commercially available reagents have high costs in applications as well as the sensitivity limitations for detection of the trace protein samples. Previously, we developed a 2-plex isobaric labeling strategy based on phosphorus chemistry for ultrasensitive proteome quantification with high accuracy. In this work, 6-plex tandem phosphorus tags (TPT) were developed with 3-fold increase in the multiplexing quantitative capacity compared to the 2-plex isobaric phosphorus reagents introduced previously. High isotope enrichment of 18O labeling was incorporated into the phosphoryl group with three exchangeable oxygen atoms by using commercially available H218O. The combinational incorporations of 18O atom in reporter ions and balance group set up the low-cost foundation for development of multiplex TPT reagents. The novel 6-plex TPT reagents could produce phosphoramidate as unique reporter ions with approximately 1 Da mass difference and thus enable 6-plex quantitative analysis in high-resolution ESI-MS/MS analysis. Using HeLa cell tryptic peptides, we concluded that 6-plex TPT reagents could facilitate large-scale accurate quantitative proteomics with very high labeling efficiency.

Lipid Isobaric Mass Tagging for Enhanced Relative Quantification of Unsaturated sn-Positional Isomers.

Changes in the levels of lipid sn-positional isomers are associated with perturbation of the physiological environment within the biological system. Consequently, knowing the concentrations of these lipids holds significant importance for unraveling their involvement in disease diagnosis and pathological mechanisms. However, existing methods for lipid quantification often fall short in accuracy due to the structural diversity and isomeric forms of lipids. To address this challenge, we have developed an aziridine-based isobaric tag labeling strategy that allows (i) differentiation and (ii) enhanced relative quantification of lipid sn-positional isomers from distinct samples in a single run. The methodology enabled by aziridination, isobaric tag labeling, and lithiation has been applied to various phospholipids, enabling the determination of the sn-positions of fatty acyl chains and enhanced relative quantification. The analysis of Escherichia coli lipid extracts demonstrated the enhanced determination of the concentration ratios of lipid isomers by measuring the intensity ratios of mass reporters released from sn-positional diagnostic ions. Moreover, we applied the method to the analysis of human colon cancer plasma. Intriguingly, 17 PC lipid sn-positional isomers were identified and quantified simultaneously, and among them, 7 showed significant abundance changes in the colon cancer plasma, which can be used as potential plasma markers for diagnosis of human colon cancer.

CHRISTMAS: Chiral Pair Isobaric Labeling Strategy for Multiplexed Absolute Quantitation of Enantiomeric Amino Acids.

Amino acids (AAs) in the d-form are involved in multiple pivotal neurological processes, although their l-enantiomers are most commonly found. Mass spectrometry-based analysis of low-abundance d-AAs has been hindered by challenging enantiomeric separation from l-AAs, low sensitivity for detection, and lack of suitable internal standards for accurate quantification. To address these critical gaps, N,N-dimethyl-l-leucine (l-DiLeu) tags are first validated as novel chiral derivatization reagents for chromatographic separation of 20 pairs of d/l-AAs, allowing the construction of a 4-plex isobaric labeling strategy for enantiomer-resolved quantification through single step tagging. Additionally, the creative design of N,N-dimethyl-d-leucine (d-DiLeu) reagents offers an alternative approach to generate analytically equivalent internal references of d-AAs using d-DiLeu-labeled l-AAs. By labeling cost-effective l-AA standards using paired d- and l-DiLeu, this approach not only enables absolute quantitation of both d-AAs and l-AAs from complex biological matrices with enhanced precision but also significantly boosts the combined signal intensities from all isobaric channels, greatly improving the detection and quantitation of low-abundance AAs, particularly d-AAs. We term this quantitative strategy CHRISTMAS, which stands for chiral pair isobaric labeling strategy for multiplexed absolute quantitation. Leveraging the ion mobility collision cross section (CCS) alignment, interferences from coeluting isomers/isobars are effectively filtered out to provide improved quantitative accuracy. From wild-type and Alzheimer's disease (AD) mouse brains, we successfully quantified 20 l-AAs and 5 d-AAs. The significant presence and differential trends of certain d-AAs compared to those of their l-counterparts provide valuable insights into the involvement of d-AAs in aging, AD progression, and neurodegeneration.

Region-specific mouse brain ganglioside distribution revealed by an improved isobaric aminoxyTMT labeling strategy with automated data processing.

Gangliosides are specialized glycosphingolipids most abundant in the central nervous system. Their complex amphiphilic structure is essential to the formation of membrane lipid rafts and for molecular recognition. Dysfunction of lipid rafts and ganglioside metabolism has been linked to cancer, metabolic disorders, and neurodegenerative disorders. Changes in ganglioside concentration and diversity during the progression of disease have made them potential biomarkers for early detection and shed light on disease mechanisms. Chemical derivatization facilitates whole ion analysis of gangliosides while improving ionization, providing rich fragmentation spectra, and enabling multiplexed analysis schemes such as stable isotope labeling. In this work, we report improvement to our previously reported isobaric labeling methodology for ganglioside analysis by increasing buffer concentration and removing solid-phase extraction desalting for a more complete and quantitative reaction. Identification and quantification of gangliosides are automated through MS-DIAL with an in-house ganglioside derivatives library. We have applied the updated methodology to relative quantification of gangliosides in six mouse brain regions (cerebellum, pons/medulla, midbrain, thalamus/hypothalamus, cortex, and basal ganglia) with 2 mg tissue per sample, and region-specific distributions of 88 ganglioside molecular species are described with ceramide isomers resolved. This method is promising for application to comparative analysis of gangliosides in biological samples.

Isobaric Stable Isotope N-Phosphorylation Labeling (iSIPL) for Ultrasensitive Proteome Quantification.

Stable isotope chemical labeling methods have been widely used for high-throughput mass spectrometry (MS)-based quantitative proteomics in biological and clinical applications. However, the existing methods are far from meeting the requirements for high sensitivity detection. In the present study, a novel isobaric stable isotope N-phosphorylation labeling (iSIPL) strategy was developed for quantitative proteome analysis. The tryptic peptides were selectively labeled with iSIPL tag to generate the novel reporter ions containing phosphoramidate P-N bond with high intensities under lower collision energies. iSIPL strategy are suitable for peptide sequencing and quantitative analysis with high sensitivity and accuracy even for samples of limited quantity. Furthermore, iSIPL coupled with affinity purification and mass spectrometry was applied to measure the dynamics of cyclin dependent kinase 9 (CDK9) interactomes during transactivation of the HIV-1 provirus. The interaction of CDK9 with PARP13 was found to significantly decrease during Tat-induced activation of HIV-1 gene transcription, suggesting the effectiveness of iSIPL strategy in dynamic analysis of protein-protein interaction in vivo. More than that, the proposed iSIPL strategy would facilitate large-scale accurate quantitative proteomics by increasing multiplexing capability.

Quantification of Serum Metabolites in Early Colorectal Adenomas Using Isobaric Labeling Mass Spectrometry.

A major challenge in reducing the death rate of colorectal cancer is to screen patients using low-invasive testing. A blood test shows a high compliance rate with reduced invasiveness. In this work, a multiplex isobaric tag labeling strategy coupled with mass spectrometry is adopted to relatively quantify primary and secondary amine-containing metabolites in serum for the discovery of metabolite level changes of colorectal cancer. Serum samples from patients at different risk statuses and colorectal cancer growth statuses are studied. Metabolite identification is based on accurate mass matching and/or retention time of labeled metabolite standards. We quantify 40 metabolites across all the serum samples, including 18 metabolites validated with standards. We find significantly decreased levels of threonine and asparagine in the patients with growing adenomas or high-risk adenomas (p < 0.05). Glutamine levels decrease in patients with adenomas of unknown growth status or high-risk adenomas. In contrast, arginine levels are elevated in patients with low-risk adenoma. Receiver operating characteristic analysis shows high sensitivity and specificity of these metabolites for detecting growing adenomas. Based on these results, we conclude that a few metabolites identified here might contribute to distinguishing colorectal patients with growing adenomas from normal individuals and patients with unknown growth status of adenomas.

Boost-DiLeu: Enhanced Isobaric N,N-Dimethyl Leucine Tagging Strategy for a Comprehensive Quantitative Glycoproteomic Analysis.

Intact glycopeptide analysis has been of great interest because it can elucidate glycosylation site information and glycan structural composition at the same time. However, mass spectrometry (MS)-based glycoproteomic analysis is hindered by the low abundance and poor ionization efficiency of glycopeptides. Relatively large amounts of starting materials are needed for the enrichment, which makes the identification and quantification of intact glycopeptides from samples with limited quantity more challenging. To overcome these limitations, we developed an improved isobaric labeling strategy with an additional boosting channel to enhance N,N-dimethyl leucine (DiLeu) tagging-based quantitative glycoproteomic analysis, termed as Boost-DiLeu. With the integration of a one-tube sample processing workflow and high-pH fractionation, 3514 quantifiable N-glycopeptides were identified from 30 μg HeLa cell tryptic digests with reliable quantification performance. Furthermore, this strategy was applied to human cerebrospinal fluid (CSF) samples to differentiate N-glycosylation profiles between Alzheimer's disease (AD) patients and non-AD donors. The results revealed processes and pathways affected by dysregulated N-glycosylation in AD, including platelet degranulation, cell adhesion, and extracellular matrix, which highlighted the involvement of N-glycosylation aberrations in AD pathogenesis. Moreover, weighted gene coexpression network analysis (WGCNA) showed nine modules of glycopeptides, two of which were associated with the AD phenotype. Our results demonstrated the feasibility of using this strategy for in-depth glycoproteomic analysis of size-limited clinical samples. Taken together, we developed and optimized a strategy for the enhanced comprehensive quantitative intact glycopeptide analysis with DiLeu labeling, showing significant promise for identifying novel therapeutic targets or biomarkers in biological systems with a limited sample quantity.

29‐Plex tandem mass tag mass spectrometry enabling accurate quantification by interference correction

Tandem mass tag (TMT) mass spectrometry is a mainstream isobaric chemical labeling strategy for profiling proteomes. Here we present a 29-plex TMT method to combine the 11-plex and 18-plex labeling strategies. The 29-plex method was examined with a pooled sample composed of 1×, 3×, and 10× Escherichia coli peptides with 100× human background peptides, which generated two E. coli datasets (TMT11 and TMT18), displaying the distorted ratios of 1.0:1.7:4.2 and 1.0:1.8:4.9, respectively. This ratio compression from the expected 1:3:10 ratios was caused by co-isolated TMT-labeled ions (i.e., noise). Interestingly, the mixture of two TMT sets produced MS/MS spectra with unique features for the noise detection: (i) in TMT11-labeled spectra, TMT18-specific reporter ions (e.g., 135N) were shown as the noise; (ii) in TMT18-labeled spectra, the TMT11/TMT18-shared reporter ions (e.g., 131C) typically exhibited higher intensities than TMT18-specific reporter ions, due to contaminated TMT11-labeled ions in these shared channels. We further estimated the noise levels contributed by both TMT11- and TMT18-labeled peptides, and corrected reporter ion intensities in every spectrum. Finally, the anticipated 1:3:10 ratios were largely restored. This strategy was also validated using another 29-plex sample with 1:5 ratios. Thus the 29-plex method expands the TMT throughput and enhances the quantitative accuracy.

Predicting fragment intensities and retention time of iTRAQ- and TMTPro-labeled peptides with Prosit-TMT.

Isobaric labeling increases the throughput of proteomics by enabling the parallel identification and quantification of peptides and proteins. Over the past decades, a variety of isobaric tags have been developed allowing the multiplexed analysis of up to 18 samples. However, experiments utilizing such tags often exhibit reduced identification rates and thus show decreased analytical depth. Re-scoring has been shown to rescue otherwise missed identifications but was not yet systematically applied on isobarically labeled data. Because iTRAQ 4/8-plex and the recently released TMTpro 16/18-plex share similar characteristics with TMT 6/10/11-plex, we hypothesized that Prosit-TMT, trained exclusively on 6/10/11-plex labeled peptides, may be applicable to these isobaric labeling strategies as well. To investigate this, we re-analyzed nine publicly available datasets covering iTRAQ and TMTpro labeling for samples with human and mouse origin. We highlight that Prosit-TMT shows remarkably good performance when comparing experimentally acquired and predicted fragmentation spectra (R of 0.84 - 0.9) and retention times (ΔRT95% of 3% - 10% gradient time) of peptides. Furthermore, re-scoring substantially increases the number of confidently identified spectra, peptides, and proteins.

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-β-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.

Three-dimensional feature matching improves coverage for single-cell proteomics based on ion mobility filtering.

SUMMARYSingle-cell proteomics (scProteomics) promises to advance our understanding of cell functions within complex biological systems. However, a major challenge of current methods is their inability to identify and provide accurate quantitative information for low-abundance proteins. Herein, we describe an ion-mobility-enhanced mass spectrometry acquisition and peptide identification method, transferring identification based on FAIMS filtering (TIFF), to improve the sensitivity and accuracy of label-free scProteomics. TIFF extends the ion accumulation times for peptide ions by filtering out singly charged ions. The peptide identities are assigned by a three-dimensional MS1 feature matching approach (retention time, accurate mass, and FAIMS compensation voltage). The TIFF method enabled unbiased proteome analysis to a depth of >1,700 proteins in single HeLa cells, with >1,100 proteins consistently identified. As a demonstration, we applied the TIFF method to obtain temporal proteome profiles of >150 single murine macrophage cells during lipopolysaccharide stimulation and identified time-dependent proteome changes. A record of this paper’s transparent peer review process is included in the supplemental information.

Isobaric Peptide Labeling on Digital Microfluidics for Quantitative Low Cell Number Proteomics.

Digital microfluidics (DMF) is a technology suitable for bioanalytical applications requiring miniaturized, automated, and multiplexed liquid handling. Its use in LC-MS-based proteomics, however, has so far been limited to qualitative proteome analyses. This is mainly due to the need for detergents that enable facile, reproducible droplet movement, which are compatible with organic solvents commonly used in targeted chemical modifications of peptides. Aiming to implement isobaric peptide labeling, a widely applied technique allowing multiplexed quantitative proteome studies, on DMF devices, we tested different commercially available detergents. We identified the maltoside-based detergent 3-dodecyloxypropyl-1-β-d-maltopyranoside (DDOPM) to enable facile droplet movement and show micelle formation even in the presence of organic solvent, which is necessary for isobaric tandem mass tag (TMT) labeling. The detergent is fully compatible with reversed phase LC-MS, not interfering with peptide identification. Tryptic digestion in the presence of DDOPM was more efficient than without detergent, resulting in more protein identifications. Using this detergent, we report the first on-DMF chip isobaric labeling strategy, with TMT-labeling efficiency comparable to conventional protocols. The newly developed labeling protocol was evaluated in the multiplexed analyses of a protein standard digest spiked into 25 cells. Finally, using only 75 cells per biological replicate, we were able to identify 39 proteins being differentially abundant after treatment of Jurkat T cells with the anticancer drug doxorubicin. In summary, we demonstrate an important step toward multiplexed quantitative proteomics on DMF, which, in combination with larger chip arrays and optimized hardware, could enable high throughput low cell number proteomics.

Quantitative Proteome Data Analysis of Tandem Mass Tags Labeled Samples.

In mass spectrometry-based proteomics, relative quantitative approaches enable differential protein abundance analysis. Isobaric labeling strategies, such as tandem mass tags (TMT), provide simultaneous quantification of several samples (e.g., up to 16 using 16plex TMTpro) owing to its multiplexing capability. This technology improves sample throughput and thereby minimizes both measurement time and overall experimental variation. However, TMT-based MS data processing and statistical analysis are probably the crucial parts of this pipeline to obtain reliable, plausible, and significantly quantified results. Here, we provide a step-by-step guide to the analysis and evaluation of TMT quantitative proteomics data.

Plant Proteomics and Systems Biology.

Proteome analysis of model and non-model plants is a genuine scientific field in expansion. Several technological advances have contributed to the implementation of different proteomics approaches for qualitative and quantitative analysis of the dynamics of cellular responses at the protein level. The design of time-resolved experiments and the emergent use of multiplexed proteome analysis using chemical or isotopic and isobaric labeling strategies as well as label-free approaches are generating a vast amount of proteomics data that is going to be essential for analysis of protein posttranslational modifications and implementation of systems biology approaches. Through the target proteomics analysis, especially the ones that combine the untargeted methods, we should expect an improvement in the completeness of the identification of proteome and reveal nuances of regulatory cellular mechanisms related to plant development and responses to environmental stresses. Both genomic sequencing and proteomic advancements in the last decades coupled to integrative data analysis are enriching biological information that was once confined to model plants. Therewith, predictions of a changing environment places proteomics as an especially useful tool for crops performance.

Abstract 2856: An intelligent boosting to amplify signal with isobaric labeling (iBASIL) strategy for precise quantitative single-cell proteomics analysis

Abstract Mass spectrometry (MS)-based proteomics has great potential for overcoming the limitations of antibody-based immunoassays for antibody-independent, comprehensive, and quantitative proteomic analysis of single cells. Indeed, recent advances in nanoscale sample preparation have enabled effective processing of single cells. In particular, the concept of using boosting/carrier channels in isobaric labeling to increase the sensitivity in MS detection (e.g., our recent boosting to amplify signal with isobaric labeling (BASIL) approach) has also been increasingly used for quantitative proteomic analysis of small-sized samples including single cells. However, the full potential of such boosting/carrier approaches has not been significantly explored, nor has the resulting quantitation quality been carefully evaluated. Herein, we have systematically evaluated and optimized the BASIL approach, originally developed for quantifying phosphorylation in small number of cells, for highly effective analysis of single cells. This improved, intelligent BASIL (iBASIL) approach enables comprehensive and quantitative single-cell proteomics analysis by carefully controlling the boosting-to-sample ratio and optimizing MS automatic gain control and ion injection time settings. Using standard LC-MS platforms, iBASIL enabled precise quantification of 800-1,200 proteins from single FACS-isolated cells (depending on the cell type). Moreover, coupling iBASIL to nanoscale fractionation enabled identification of &amp;gt;3,000 proteins and reliable quantification of &amp;gt;2,000 proteins while readily separating single cells from 3 different acute myeloid leukemia cell lines. We believe iBASIL has broad utility for comprehensive and precise quantitative single-cell proteomics for systems biology and biomedical research, as well as for comprehensive proteomic analysis of size-limited clinical specimens that cannot be readily accessed by regular proteomics platforms. It also has the potential to be adapted for phosphoproteome analysis of as few as 100 cells. Citation Format: Chia-Feng Tsai, Rui Zhao, Ronald Moore, Sarah Williams, Kendall Schultz, Paul Piehowski, Ljiljana Pasa-Tolic, Karin Rodland, Richard Smith, Tujin Shi, Ying Zhu, Ying Zhu, Tao Liu. An intelligent boosting to amplify signal with isobaric labeling (iBASIL) strategy for precise quantitative single-cell proteomics analysis [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 2856.

ZNF322A-mediated protein phosphorylation induces autophagosome formation through modulation of IRS1-AKT glucose uptake and HSP-elicited UPR in lung cancer

BackgroundZNF322A is an oncogenic transcription factor that belongs to the Cys2His2-type zinc-finger protein family. Accumulating evidence suggests that ZNF322A may contribute to the tumorigenesis of lung cancer, however, the ZNF322A-mediated downstream signaling pathways remain unknown.MethodsTo uncover ZNF322A-mediated functional network, we applied phosphopeptide enrichment and isobaric labeling strategies with mass spectrometry-based proteomics using A549 lung cancer cells, and analyzed the differentially expressed proteins of phosphoproteomic and proteomic profiles to determine ZNF322A-modulated pathways.ResultsZNF322A highlighted a previously unidentified insulin signaling, heat stress, and signal attenuation at the post-translational level. Consistently, protein-phosphoprotein-kinase interaction network analysis revealed phosphorylation of IRS1 and HSP27 were altered upon ZNF322A-silenced lung cancer cells. Thus, we further investigated the molecular regulation of ZNF322A, and found the inhibitory transcriptional regulation of ZNF322A on PIM3, which was able to phosphorylate IRS1 at serine1101 in order to manipulate glucose uptake via the PI3K/AKT/mTOR signaling pathway. Moreover, ZNF322A also affects the unfolded protein response by phosphorylation of HSP27S82 and eIF2aS51, and triggers autophagosome formation in lung cancer cells.ConclusionsThese findings not only give new information about the molecular regulation of the cellular proteins through ZNF322A at the post-translational level, but also provides a resource for the study of lung cancer therapy.

Isobaric Labeling Strategy Utilizing 4-Plex N,N-Dimethyl Leucine (DiLeu) Tags Reveals Proteomic Changes Induced by Chemotherapy in Cerebrospinal Fluid of Children with B-Cell Acute Lymphoblastic Leukemia.

The use of mass spectrometry for protein identification and quantification in cerebrospinal fluid (CSF) is at the forefront of research efforts to identify and explore biomarkers for the early diagnosis and prognosis of neurologic disorders. Here we implemented a 4-plex N,N-dimethyl leucine (DiLeu) isobaric labeling strategy in a longitudinal study aiming to investigate protein dynamics in children with B-cell acute lymphoblastic leukemia (B-cell ALL) undergoing chemotherapy. The temporal profile of CSF proteome during chemotherapy treatment at weeks 5, 10-14, and 24-28 highlighted many differentially expressed proteins, such as neural cell adhesion molecule, neuronal growth regulator 1, and secretogranin-3, all of which play important roles in neurodegenerative diseases. A total of 63 proteins were significantly altered across all of the time points investigated. The most over-represented biological processes from gene ontology analysis included platelet degranulation, complement activation, cell adhesion, fibrinolysis, neuron projection, regeneration, and regulation of neuron death. We expect that results from this and future studies will provide a means to monitor neurotoxicity and develop strategies to prevent central nervous system injury in response to chemotherapy in children.

An Improved Boosting to Amplify Signal with Isobaric Labeling (iBASIL) Strategy for Precise Quantitative Single-cell Proteomics

Mass spectrometry (MS)-based proteomics has great potential for overcoming the limitations of antibody-based immunoassays for antibody-independent, comprehensive, and quantitative proteomic analysis of single cells. Indeed, recent advances in nanoscale sample preparation have enabled effective processing of single cells. In particular, the concept of using boosting/carrier channels in isobaric labeling to increase the sensitivity in MS detection has also been increasingly used for quantitative proteomic analysis of small-sized samples including single cells. However, the full potential of such boosting/carrier approaches has not been significantly explored, nor has the resulting quantitation quality been carefully evaluated. Herein, we have further evaluated and optimized our recent boosting to amplify signal with isobaric labeling (BASIL) approach, originally developed for quantifying phosphorylation in small number of cells, for highly effective analysis of proteins in single cells. This improved BASIL (iBASIL) approach enables reliable quantitative single-cell proteomics analysis with greater proteome coverage by carefully controlling the boosting-to-sample ratio (e.g. in general <100×) and optimizing MS automatic gain control (AGC) and ion injection time settings in MS/MS analysis (e.g. 5E5 and 300 ms, respectively, which is significantly higher than that used in typical bulk analysis). By coupling with a nanodroplet-based single cell preparation (nanoPOTS) platform, iBASIL enabled identification of ∼2500 proteins and precise quantification of ∼1500 proteins in the analysis of 104 FACS-isolated single cells, with the resulting protein profiles robustly clustering the cells from three different acute myeloid leukemia cell lines. This study highlights the importance of carefully evaluating and optimizing the boosting ratios and MS data acquisition conditions for achieving robust, comprehensive proteomic analysis of single cells.

Peptidomic analysis of hippocampal tissue for explore leptin neuroprotective effect on the preterm ischemia-hypoxia brain damage model rats

The most common injury of preterm infants is periventricular leukomalacia (PVL) and to date there is still no safe and effective treatment. In our previous studies, leptin has been found to have neuroprotective effects on the preterm ischemia-hypoxia brain damage model rats in animal behavior. To gain insight into the neuroprotective mechanisms of leptin on preterm brain damage model rats, we constructed a comparative peptidomic profiling of hippocampal tissue between leptin-treated after model and preterm ischemia-hypoxia brain damage model rats using a stable isobaric labeling strategy involving tandem mass tag reagents, followed by nano liquid chromatography tandem mass spectrometry. We identified and quantified 4164 peptides, 238 of which were differential expressed in hippocampal tissue in the two groups. A total of 150 peptides were up regulated and 88 peptides were down regulated. These peptides were imported into the Ingenuity Pathway Analysis (IPA) and identified putative roles in nervous system development, function and diseases. We concluded that the preterm ischemia-hypoxia brain damage model with leptin treatment induced peptides changes in hippocampus, and these peptides, especially for the peptides associated “microtubule-associated protein 1b (MAP1b), Elastin (Eln), Piccolo presynaptic cytomatrix protein (Pclo), Zinc finger homeobox 3(Zfhx3), Alpha-kinase 3(Alpk3) and Myosin XVA(Myo15a) ”, could be candidate bio-active peptides and participate in neuroprotection of leptin. These may advance our current understanding of the mechanism of leptin's neuroprotective effect on preterm brain damage and may be involved in the etiology of preterm brain damage. Meanwhile, we found that repression of ILK signaling pathway plays a significant role in neuroprotection of leptin. A better understanding of the role of ILK signaling pathway in neuroprotective mechanisms will help scientists and researchers to develop selective, safe and efficacious drug for therapy against human nervous system disorders.

Boosting to Amplify Signal with Isobaric Labeling (BASIL) Strategy for Comprehensive Quantitative Phosphoproteomic Characterization of Small Populations of Cells.

Comprehensive phosphoproteomic analysis of small populations of cells remains a daunting task due primarily to the insufficient MS signal intensity from low concentrations of enriched phosphopeptides. Isobaric labeling has a unique multiplexing feature where the "total" peptide signal from all channels (or samples) triggers MS/MS fragmentation for peptide identification, while the reporter ions provide quantitative information. In light of this feature, we tested the concept of using a "boosting" sample (e.g., a biological sample mimicking the study samples but available in a much larger quantity) in multiplexed analysis to enable sensitive and comprehensive quantitative phosphoproteomic measurements with <100 000 cells. This simple boosting to amplify signal with isobaric labeling (BASIL) strategy increased the overall number of quantifiable phosphorylation sites more than 4-fold. Good reproducibility in quantification was demonstrated with a median CV of 15.3% and Pearson correlation coefficient of 0.95 from biological replicates. A proof-of-concept experiment demonstrated the ability of BASIL to distinguish acute myeloid leukemia cells based on the phosphoproteome data. Moreover, in a pilot application, this strategy enabled quantitative analysis of over 20 000 phosphorylation sites from human pancreatic islets treated with interleukin-1β and interferon-γ. Together, this signal boosting strategy provides an attractive solution for comprehensive and quantitative phosphoproteome profiling of relatively small populations of cells where traditional phosphoproteomic workflows lack sufficient sensitivity.