Combining amine metabolomics and quantitative proteomics of cancer cells using derivatization with isobaric tags

Spatial amine metabolomics and histopathology reveal localized brain alterations in subacute traumatic brain injury and the underlying mechanism of herbal treatment

INTRODUCTION

Spatial changes of amine metabolites and histopathology of the whole brain help to reveal the mechanism of traumatic brain injury (TBI) and treatment.

METHODS

A newly developed liquid microjunction surface sampling-tandem mass tag-ultra performance liquid chromatography-mass spectrometry technique is applied to profile brain amine metabolites in five brain regions after impact-induced TBI at the subacute stage. H&E, Nissl, and immunofluorescence staining are performed to spatially correlate microscopical changes to metabolic alterations. Then, bioinformatics, molecular docking, ELISA, western blot, and immunofluorescence are integrated to uncover the mechanism of Xuefu Zhuyu decoction (XFZYD) against TBI.

RESULTS

Besides the hippocampus and cortex, the thalamus, caudate-putamen, and fiber tracts also show differentiated metabolic changes between the Sham and TBI groups. Fourteen amine metabolites (including isomers such as L-leucine and L-isoleucine) are significantly altered in specific regions. The metabolic changes are well matched with the degree of neuronal damage, glia activation, and neurorestoration. XFZYD reverses the dysregulation of several amine metabolites, such as hippocampal Lys-Phe/Phe-Lys and dopamine. Also, XFZYD enhances post-TBI angiogenesis in the hippocampus and the thalamus.

CONCLUSION

This study reveals the local amine-metabolite and histological changes in the subacute stage of TBI. XFZYD may promote TBI recovery by normalizing amine metabolites and spatially promoting dopamine production and angiogenesis.

Polarity-regulated derivatization-assisted LC-MS method for amino-containing metabolites profiling in gastric cancer

Amino-containing compounds, including amino acids, aliphatic amines, aromatic amines, small peptides and catecholamines, are involved in various biological processes and play vital roles in multiple metabolic pathways. Previous studies indicated that some amino-containing metabolites are significant diagnostic and prognostic biomarkers of gastric cancer. However, the discovery of precise biomarkers for the preoperative diagnosis of gastric cancer is still in an urgent need. Herein, we established a polarity-regulated derivatization method coupled with liquid chromatography-mass spectrometry (LC-MS) for amino-containing metabolites profiling in the serum samples of patients with gastric cancer and healthy controls, based on our newly designed and synthesized derivatization reagent (S)-3-(1-(diisopropoxyphosphoryl) pyrrolidine-2-carboxamido)-N-hydroxysuccinimidyl ester (3-DP-NHS). Enhanced separation efficiency and detection sensitivity for amino-containing metabolites were achieved after derivatization. This method exhibited good linearity, recovery, intra- and inter-day precision and accuracy. Only 5 μL serum is needed for untargeted analysis, enabling 202 amino-containing metabolites to be detected. Statistical analysis revealed altered amino acid metabolisms in patients with gastric cancer. Furthermore, ultra high performance liquid chromatography coupled with mass spectrometry (UHPLC-MS/MS) analysis quantification revealed increased serum levels of tryptamine and decreased concentrations of arginine and tryptophan in patients with gastric cancer. Receiver operating characteristic (ROC) curves indicated that an increased tryptamine/tryptophan ratio could serve as a potential biomarker for gastric cancer diagnosis. This study demostrated the possibility of using serum amino acid biomarkers for gastric cancer diagnosis, providing new avenues for the treatment of gastric cancer.

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.

Photocatalytic reactive liquid microjunction surface sampling-mass spectrometry for rapid and selective in-situ analysis of alpha-unsubstituted amine metabolites or drugs in brain tissue

In in-situ mass spectrometry (MS), different on-tissue derivatization methods have been developed to enhance the signals of poorly ionizable primary amines. However, those chemical derivatization methods are laborious and time-consuming, and are usually limited to detection of high-abundance amino acids which suppress the reaction of low-abundance monoamine neurotransmitters and drugs. Herein, A rapid and selective photocatalytic derivatization technique for alpha-unsubstituted primary amine was developed with 5-hydroxyindole as derivatization reagent and TiO₂ as photocatalyst, and was introduced into liquid microjunction surface sampling (LMJSS)-MS system as online derivatization. The results showed that the photocatalytic derivatization method largely enhanced the signals of primary amines by 5-300 fold, and were selective to alpha-unsubstituted primary amines. Thus, the suppression effects from high-abundance amino acids to the reaction of monoamine neurotransmitters and benzylamine drugs proved to be largely reduced in the new method (matrix effect>50%) comparing with those in chemical derivatization method (matrix effect<10%). In addition, the optimal pH of the derivatization reaction was measured to be 7, which indicates the mild and physiologically compatible reaction conditions. By in-situ synthesis of TiO₂ monolith in the transfer capillary of the LMJSS-MS system, rapid on-line photocatalytic derivatization was achieved and completed in 5 s during the transfer of sampling extract from the flow-probe to the MS inlet. With the new photocatalytic reactive LMJSS-MS method, detection limits of three primary amines on glass slides were in the range of 0.031-0.17 ng/mm² with acceptable linearity (r=0.9815-0.9998) and relatively high repeatability (relative standard deviations <22.1%). Finally, endogenous tyramine, serotonin, two dipeptides and one doped benzylamine drug were identified and in-situ analyzed in the mouse cerebrum by the new method with largely enhanced signals comparing with LMJSS-MS without online derivatization. The new method provides a more selective, rapid and automated way to analyze alpha-unsubstituted amine metabolites and drugs in-situ comparing with traditional methods.

Radiation-Induced Intestinal Normal Tissue Toxicity: Implications for Altered Proteome Profile

Radiation-induced toxicity to healthy/normal intestinal tissues, especially during radiotherapy, limits the radiation dose necessary to effectively eradicate tumors of the abdomen and pelvis. Although the pathogenesis of intestinal radiation toxicity is highly complex, understanding post-irradiation alterations in protein profiles can provide crucial insights that make radiotherapy safer and more efficient and allow for increasing the radiation dose during cancer treatment. Recent preclinical and clinical studies have advanced our current understanding of the molecular changes associated with radiation-induced intestinal damage by assessing changes in protein expression with mass spectrometry-based approaches and 2-dimensional difference gel electrophoresis. Studies by various groups have demonstrated that proteins that are involved in the inflammatory response, the apoptotic pathway, reactive oxygen species scavenging, and cell proliferation can be targeted to develop effective radiation countermeasures. Moreover, altered protein profiles serve as a crucial biomarkers for intestinal radiation damage. In this review, we present alterations in protein signatures following intestinal radiation damage as detected by proteomics approaches in preclinical and clinical models with the aim of providing a better understanding of how to accomplish intestinal protection against radiation damage.

Recent advances in isobaric labeling and applications in quantitative proteomics

Mass spectrometry (MS) has emerged at the forefront of quantitative proteomic techniques. Liquid chromatography-mass spectrometry (LC-MS) can be used to determine abundances of proteins and peptides in complex biological samples. Several methods have been developed and adapted for accurate quantification based on chemical isotopic labeling. Among various chemical isotopic labeling techniques, isobaric tagging approaches rely on the analysis of peptides from MS2-based quantification rather than MS1-based quantification. In this review, we will provide an overview of several isobaric tags along with some recent developments including complementary ion tags, improvements in sensitive quantitation of analytes with lower abundance, strategies to increase multiplexing capabilities, and targeted analysis strategies. We will also discuss limitations of isobaric tags and approaches to alleviate these restrictions through bioinformatic tools and data acquisition methods. This review will highlight several applications of isobaric tags, including biomarker discovery and validation, thermal proteome profiling, cross-linking for structural investigations, single-cell analysis, top-down proteomics, along with applications to different molecules including neuropeptides, glycans, metabolites, and lipids, while providing considerations and evaluations to each application.

Multiplexed analysis of amino acids in mice brain microdialysis samples using isobaric labeling and liquid chromatography-high resolution tandem mass spectrometry

We developed a new multiplexed reversed phase liquid chromatography-high resolution tandem mass spectrometric (LC-MS/MS) method. The method is based on isobaric labeling with a tandem mass tag (TMT10-plex) and stable isotope-labeled internal standards, and was used to analyze amino acids in mouse brain microdialysis samples. The TMT10-plex labeling of amino acids allowed analysis of ten samples in one LC-MS/MS run, significantly increasing the sample throughput. The method provides good chromatographic performance (peak half-width between 0.04-0.12 min), allowing separation of all TMT-labeled amino acids with acceptable resolution and high sensitivity (limits of detection typically around 10 nM). The use of stable isotope-labeled internal standards, together with TMT10-plex labeling, ensured good repeatability (relative standard deviation ≤ 12.1 %) and linearity (correlation coefficient > 0.994), indicating good quantitative performance of the multiplexed method. The method was applied to study the effect of d-amphetamine microdialysis perfusion on amino acid concentrations in the mouse brain. All amino acids were reliably detected and quantified, indicating that the method is sensitive enough to detect low concentrations of amino acids in brain microdialysis samples.

Tryptophan metabolism is inversely regulated in the tumor and blood of patients with glioblastoma

Tryptophan (Trp)-catabolic enzymes (TCEs) produce metabolites that activate the aryl hydrocarbon receptor (AHR) and promote tumor progression and immunosuppression in glioblastoma. As therapies targeting TCEs or AHR become available, a better understanding of Trp metabolism is required. Methods: The combination of LC-MS/MS with chemical isobaric labeling enabled the simultaneous quantitative comparison of Trp and its amino group-bearing metabolites in multiple samples. We applied this method to the sera of a cohort of 43 recurrent glioblastoma patients and 43 age- and sex-matched healthy controls. Tumor volumes were measured in MRI data using an artificial neural network-based approach. MALDI MSI visualized Trp and its direct metabolite N-formylkynurenine (FK) in glioblastoma tissue. Analysis of scRNA-seq data was used to detect the presence of Trp metabolism and AHR activity in different cell types in glioblastoma. Results: Compared to healthy controls, glioblastoma patients showed decreased serum Trp levels. Surprisingly, the levels of Trp metabolites were also reduced. The decrease became smaller with more enzymatic steps between Trp and its metabolites, suggesting that Trp availability controls the levels of its systemic metabolites. High tumor volume associated with low systemic metabolite levels and low systemic kynurenine levels associated with worse overall survival. MALDI MSI demonstrated heterogeneity of Trp catabolism across glioblastoma tissues. Analysis of scRNA-seq data revealed that genes involved in Trp metabolism were expressed in almost all the cell types in glioblastoma and that most cell types, in particular macrophages and T cells, exhibited AHR activation. Moreover, high AHR activity associated with reduced overall survival in the glioblastoma TCGA dataset. Conclusion: The novel techniques we developed could support the identification of patients that may benefit from therapies targeting TCEs or AHR activation.

JUMPt: Comprehensive Protein Turnover Modeling of In Vivo Pulse SILAC Data by Ordinary Differential Equations

Recent advances in mass spectrometry (MS)-based proteomics allow the measurement of turnover rates of thousands of proteins using dynamic labeling methods, such as pulse stable isotope labeling by amino acids in cell culture (pSILAC). However, when applying the pSILAC strategy to multicellular animals (e.g., mice), the labeling process is significantly delayed by native amino acids recycled from protein degradation in vivo, raising a challenge of defining accurate protein turnover rates. Here, we report JUMPt, a software package using a novel ordinary differential equation (ODE)-based mathematical model to determine reliable rates of protein degradation. The uniqueness of JUMPt is to consider amino acid recycling and fit the kinetics of the labeling amino acid (e.g., Lys) and whole proteome simultaneously to derive half-lives of individual proteins. Multiple settings in the software are designed to enable simple to comprehensive data inputs for precise analysis of half-lives with flexibility. We examined the software by studying the turnover of thousands of proteins in the pSILAC brain and liver tissues. The results were largely consistent with the proteome turnover measurements from previous studies. The long-lived proteins are enriched in the integral membrane, myelin sheath, and mitochondrion in the brain. In summary, the ODE-based JUMPt software is an effective proteomics tool for analyzing large-scale protein turnover, and the software is publicly available on GitHub (https://github.com/JUMPSuite/JUMPt) to the research community.

Development of Tandem Mass Tag Labeling Method for Lipid Molecules Containing Carboxy and Phosphate Groups, and Their Stability in Human Serum

In clinical lipidomics, it is a challenge to measure a large number of samples and to reproduce the quantitative results. We expanded the range of application of the tandem mass tag (TMT) method, which is widely used in proteomics, to lipidomic fields. There are various types of lipid molecule, for example, eicosanoids have a carboxyl group and phosphatidic acid has a phosphate group. We modified these functional groups simultaneously with TMT. This approach allows for a single analysis by mixing six samples and using one of the six samples as a bridging sample; the quantitative data can be easily normalized even if the number of measurements increases. To accommodate a large number of samples, we utilize a pooled serum sample of 300 individuals as a bridging sample. The stability of these lipid molecules in serum was examined as an analytical validation for the simultaneous TMT labeling. It was found that the stability of these lipid molecules in serum differs greatly depending on the lipid species. These findings reaffirmed the importance of proper sample preparation and storage to obtain reliable data. The TMT labeling method is expected to be a useful method for lipidomics with high-throughput and reliable reproducibility.

Deep Profiling of Microgram-Scale Proteome by Tandem Mass Tag Mass Spectrometry

Tandem mass tag (TMT)-based mass spectrometry (MS) enables deep proteomic profiling of more than 10,000 proteins in complex biological samples but requires up to 100 μg protein in starting materials during a standard analysis. Here, we present a streamlined protocol to quantify more than 9000 proteins with 0.5 μg protein per sample by 16-plex TMT coupled with two-dimensional liquid chromatography and tandem mass spectrometry (LC/LC-MS/MS). In this protocol, we optimized multiple conditions to reduce sample loss, including processing each sample in a single tube to minimize surface adsorption, increasing digestion enzymes to shorten proteolysis and function as carriers, eliminating a desalting step between digestion and TMT labeling, and developing miniaturized basic pH LC for prefractionation. By profiling 16 identical human brain tissue samples of Alzheimer's disease (AD), vascular dementia (VaD), and non-dementia controls, we directly compared this new microgram-scale protocol to the standard-scale protocol, quantifying 9116 and 10,869 proteins, respectively. Importantly, bioinformatics analysis indicated that the microgram-scale protocol had adequate sensitivity and reproducibility to detect differentially expressed proteins in disease-related pathways. Thus, this newly developed protocol is of general application for deep proteomics analysis of biological and clinical samples at sub-microgram levels.

Serine-dependent redox homeostasis regulates glioblastoma cell survival

Background

The amino acid serine is an important substrate for biosynthesis and redox homeostasis. We investigated whether glioblastoma (GBM) cells are dependent on serine for survival under conditions of the tumour microenvironment.

Methods

Serine availability in GBM cells was modulated pharmacologically, genetically and by adjusting serine and glycine concentrations in the culture medium. Cells were investigated for regulation of serine metabolism, proliferation, sensitivity to hypoxia-induced cell death and redox homeostasis.

Results

Hypoxia-induced expression of phosphoglycerate dehydrogenase (PHGDH) and the mitochondrial serine hydroxymethyltransferase (SHMT2) was observed in three of five tested glioma cell lines. Nuclear factor erythroid 2-related factor (Nrf) 2 activation also induced PHGDH and SHMT2 expression in GBM cells. Low levels of endogenous PHGDH as well as PHGDH gene suppression resulted in serine dependency for cell growth. Pharmacological inhibition of PHGDH with CBR-5884 reduced proliferation and sensitised cells profoundly to hypoxia-induced cell death. This effect was accompanied by an increase in reactive oxygen species and a decrease in the NADPH/NADP⁺ ratio. Similarly, hypoxia-induced cell death was enhanced by PHGDH gene suppression and reduced by PHGDH overexpression.

Conclusions

Serine facilitates adaptation of GBM cells to conditions of the tumour microenvironment and its metabolism could be a plausible therapeutic target.

Comparative study of five different amine-derivatization methods for metabolite analyses by liquid chromatography-tandem mass spectrometry

Current metabolomics research utilizes liquid chromatography-tandem mass spectrometry (LC-MS/MS) analyses to handle biological samples that contain thousands of quantifiable metabolites. However, no LC-MS/MS condition is suitable for directly analyzing all metabolites. An alternative approach is to derivatize metabolites to impart desirable properties such as better chromatographic separation, enhanced ionization efficiency, or fluorescence detection. An important category of metabolites is amine-containing compounds, which includes amino acids, neurotransmitters, alkaloids, biogenic amines, etc. Various derivatization methods have been developed for amine groups, but few studies have compared their relative strengths and weaknesses. We chose Dansyl-Cl, o-phthalaldehyde (OPA), Fmoc-Cl, Dabsyl-Cl, and Marfey's reagent to systematically compare their reactivity, absorbance, fluorescence, chromatographic separation, and ionization efficiencies under three pH conditions-2.6, 5.0, and 8.0. Their MS/MS fragmentation patterns were also examined under different collision energies. Overall, Dansyl-Cl is a very versatile derivatization method, generating products with fluorescence and high ionization efficiency. Fmoc-Cl is similarly useful under highly acidic chromatography conditions. Dabsyl-Cl may be a good alternative at weakly acidic and weakly basic conditions. OPA is a versatile fluorogenic reagent and its chemistry may be fine-tuned by incorporating different thiol molecules. Marfey's reagent is suboptimal in general, but its chiral property is useful for the separation of enantiomers. All five were applied to the analyses of Coptis chinensis, a Chinese medical herb, identifying hundreds of amine-containing metabolites through MS/MS analyses. None of the five methods is clearly superior, and their compound coverage profiles are rather distinct. A combination of multiple derivatization reagents is required for comprehensive coverage. Our comparative data provide useful guidelines for designing more efficient metabolomics experiments for different analytical goals.

Detecting single amino acids and small peptides by combining isobaric tags and peptidomics

Single amino acids and small endogenous peptides play important roles in maintaining a properly functioning organism. These molecules are however currently only routinely identified in targeted approaches. In a small proof-of-concept mass spectrometry experiment, we found that by combining isobaric tags and peptidomics, and by targeting singly charged molecules, we were able to identify a significant amount of single amino acids and small endogenous peptides using a basic mass-based identification approach. While there is still room for improvement, our simple test indicates that a limited amount of extra work when setting up the mass spectrometry experiment could potentially lead to a wealth of additional information.

Barocycler-Based Concurrent Multiomics Method To Assess Molecular Changes Associated with Atherosclerosis Using Small Amounts of Arterial Tissue from a Single Mouse

Atherosclerosis is a complex, multifactorial disease characterized by the buildup of plaque in the arterial wall. Apolipoprotein E gene deficient (Apoe^-/-) mice serve as a commonly used tool to elucidate the pathophysiology of atherosclerosis because of their propensity to spontaneously develop arterial lesions. To date, however, an integrated omics assessment of atherosclerotic lesions in individual Apoe^-/- mice has been challenging because of the small amount of diseased and nondiseased tissue available. To address this current limitation, we developed a multiomics method (Multi-ABLE) based on the proteomic method called accelerated Barocycler lysis and extraction (ABLE) to assess the depth of information that can be obtained from arterial tissue derived from a single mouse by splitting ABLE to allow for a combined proteomics-metabolomics-lipidomics analysis (Multi-ABLE). The new method includes tissue lysis via pressure cycling technology (PCT) in a Barocycler, followed by proteomic analysis of half the sample by nanoLC-MS and sequential extraction of lipids (organic extract) and metabolites (aqueous extract) combined with HILIC and reversed phase chromatography and time-of-flight mass spectrometry on the other half. Proteomic analysis identified 845 proteins, 93 of which were significantly altered in lesion-containing arteries. Lipidomic and metabolomic analyses detected 851 lipid and 362 metabolite features, which included 215 and 65 identified lipids and metabolites, respectively. The Multi-ABLE method is the first to apply a concurrent multiomics pipeline to cardiovascular disease using small (<5 mg) tissue samples, and it is applicable to other diseases where limited size samples are available at specific points during disease progression.

Metandem: An online software tool for mass spectrometry-based isobaric labeling metabolomics

Mass spectrometry-based stable isotope labeling provides the advantages of multiplexing capability and accurate quantification but requires tailored bioinformatics tools for data analysis. Despite the rapid advancements in analytical methodology, it is often challenging to analyze stable isotope labeling-based metabolomics data, particularly for isobaric labeling using MS/MS reporter ions for quantification. We report Metandem, a novel online software tool for isobaric labeling-based metabolomics, freely available at http://metandem.com/web/. Metandem provides a comprehensive data analysis pipeline integrating feature extraction, metabolite quantification, metabolite identification, batch processing of multiple data files, online parameter optimization for custom datasets, data normalization, and statistical analysis. Systematic evaluation of the Metandem tool was demonstrated on UPLC-MS/MS, nanoLC-MS/MS, CE-MS/MS and MALDI-MS platforms, via duplex, 4-plex, 10-plex, and 12-plex isobaric labeling experiments and the application to various biological samples.

Breast cancer subtype dictates DNA methylation and ALDH1A3-mediated expression of tumor suppressor RARRES1

Breast cancer subtyping, based on the expression of hormone receptors and other genes, can determine patient prognosis and potential options for targeted therapy. Among breast cancer subtypes, tumors of basal-like and claudin-low subtypes are typically associated with worse patient outcomes, are primarily classified as triple-negative breast cancers (TNBC), and cannot be treated with existing hormone-receptor-targeted therapies. Understanding the molecular basis of these subtypes will lead to the development of more effective treatment options for TNBC. In this study, we focus on retinoic acid receptor responder 1 (RARRES1) as a paradigm to determine if breast cancer subtype dictates protein function and gene expression regulation. Patient tumor dataset analysis and gene expression studies of a 26 cell-line panel, representing the five breast cancer subtypes, demonstrate that RARRES1 expression is greatest in basal-like TNBCs. Cell proliferation and tumor growth assays reveal that RARRES1 is a tumor suppressor in TNBC. Furthermore, gene expression studies, Illumina HumanMethylation450 arrays, and chromatin immunoprecipitation demonstrate that expression of RARRES1 is retained in basal-like breast cancers due to hypomethylation of the promoter. Additionally, expression of the cancer stem cell marker, aldehyde dehydrogenase 1A3, which provides the required ligand (retinoic acid) for RARRES1 transcription, is also specific to the basal-like subtype. We functionally demonstrate that the combination of promoter methylation and retinoic acid signaling dictates expression of tumor suppressor RARRES1 in a subtype-specific manner. These findings provide a precedent for a therapeutically-inducible tumor suppressor and suggest novel avenues of therapeutic intervention for patients with basal-like breast cancer.

Mass Defect-Based N,N-Dimethyl Leucine Labels for Quantitative Proteomics and Amine Metabolomics of Pancreatic Cancer Cells

Mass spectrometry-based stable isotope labeling has become a key technology for protein and small-molecule analyses. We developed a multiplexed quantification method for simultaneous proteomics and amine metabolomics analyses via nano reversed-phase liquid chromatography-tandem mass spectrometry (nanoRPLC-MS/MS), called mass defect-based N,N-dimethyl leucine (mdDiLeu) labeling. The duplex mdDiLeu reagents were custom-synthesized with a mass difference of 20.5 mDa, arising from the subtle variation in nuclear binding energy between the two DiLeu isotopologues. Optimal MS resolving powers were determined to be 240K for labeled peptides and 120K for labeled metabolites on the Orbitrap Fusion Lumos instrument. The mdDiLeu labeling does not suffer from precursor interference and dynamic range compression, providing excellent accuracy for MS¹-centric quantification. Quantitative information is only revealed at high MS resolution without increasing spectrum complexity and overlapping isotope distribution. Chromatographic performance of polar metabolites was dramatically improved by mdDiLeu labeling with modified hydrophobicity, enhanced ionization efficiency, and picomole levels of detection limits. Paralleled proteomics and amine metabolomics analyses using mdDiLeu were systematically evaluated and then applied to pancreatic cancer cells.

Citral reduces breast tumor growth by inhibiting the cancer stem cell marker ALDH1A3

Breast cancer stem cells (CSCs) can be identified by increased Aldefluor fluorescence caused by increased expression of aldehyde dehydrogenase 1A3 (ALDH1A3), as well as ALDH1A1 and ALDH2. In addition to being a CSC marker, ALDH1A3 regulates gene expression via retinoic acid (RA) signaling and plays a key role in the progression and chemotherapy resistance of cancer. Therefore, ALDH1A3 represents a druggable anti-cancer target of interest. Since to date, there are no characterized ALDH1A3 isoform inhibitors, drugs that were previously described as inhibiting the activity of other ALDH isoforms were tested for anti-ALDH1A3 activity. Twelve drugs (3-hydroxy-dl-kynurenine, benomyl, citral, chloral hydrate, cyanamide, daidzin, DEAB, disulfiram, gossypol, kynurenic acid, molinate, and pargyline) were compared for their efficacy in inducing apoptosis and reducing ALDH1A3, ALDH1A1 and ALDH2-associated Aldefluor fluorescence in breast cancer cells. Citral was identified as the best inhibitor of ALDH1A3, reducing the Aldefluor fluorescence in breast cancer cell lines and in a patient-derived tumor xenograft. Nanoparticle encapsulated citral specifically reduced the enhanced tumor growth of MDA-MB-231 cells overexpressing ALDH1A3. To determine the potential mechanisms of citral-mediated tumor growth inhibition, we performed cell proliferation, clonogenic, and gene expression assays. Citral reduced ALDH1A3-mediated colony formation and expression of ALDH1A3-inducible genes. In conclusion, citral is an effective ALDH1A3 inhibitor and is able to block ALDH1A3-mediated breast tumor growth, potentially via blocking its colony forming and gene expression regulation activity. The promise of ALDH1A3 inhibitors as adjuvant therapies for patients with tumors that have a large population of high-ALDH1A3 CSCs is discussed.

Differential Glutamate Metabolism in Proliferating and Quiescent Mammary Epithelial Cells

Mammary epithelial cells transition between periods of proliferation and quiescence during development, menstrual cycles, and pregnancy, and as a result of oncogenic transformation. Utilizing an organotypic 3D tissue culture model coupled with quantitative metabolomics and proteomics, we identified significant differences in glutamate utilization between proliferating and quiescent cells. Relative to quiescent cells, proliferating cells catabolized more glutamate via transaminases to couple non-essential amino acid (NEAA) synthesis to α-ketoglutarate generation and tricarboxylic acid (TCA) cycle anaplerosis. As cells transitioned to quiescence, glutamine consumption and transaminase expression were reduced, while glutamate dehydrogenase (GLUD) was induced, leading to decreased NEAA synthesis. Highly proliferative human tumors display high transaminase and low GLUD expression, suggesting that proliferating cancer cells couple glutamine consumption to NEAA synthesis to promote biosynthesis. These findings describe a competitive and partially redundant relationship between transaminases and GLUD, and they reveal how coupling of glutamate-derived carbon and nitrogen metabolism can be regulated to support cell proliferation.

Biomarker discovery in mass spectrometry-based urinary proteomics

Urinary proteomics has become one of the most attractive topics in disease biomarker discovery. MS-based proteomic analysis has advanced continuously and emerged as a prominent tool in the field of clinical bioanalysis. However, only few protein biomarkers have made their way to validation and clinical practice. Biomarker discovery is challenged by many clinical and analytical factors including, but not limited to, the complexity of urine and the wide dynamic range of endogenous proteins in the sample. This article highlights promising technologies and strategies in the MS-based biomarker discovery process, including study design, sample preparation, protein quantification, instrumental platforms, and bioinformatics. Different proteomics approaches are discussed, and progresses in maximizing urinary proteome coverage and standardization are emphasized in this review. MS-based urinary proteomics has great potential in the development of noninvasive diagnostic assays in the future, which will require collaborative efforts between analytical scientists, systems biologists, and clinicians.

Relative quantification of amine-containing metabolites using isobaric N,N-dimethyl leucine (DiLeu) reagents via LC-ESI-MS/MS and CE-ESI-MS/MS

Tandem mass spectrometry (MS/MS)-based relative quantification by isobaric labeling is a useful technique to compare different metabolic expression levels in biological systems. For the first time, we have labeled primary and secondary amine-containing small molecules using 4-plex isobaric N,N-dimethyl leucine (DiLeu) to perform relative quantification. Good labeling efficiency and quantification accuracy were demonstrated with a mixture of 12 metabolite standards including amino acids and small molecule neurotransmitters. Labeling amine-containing metabolites with DiLeu reagents also enabled the separation of polar metabolites by nanoRPLC and improved the detection sensitivity by CE-ESI-MS. The 4-plex DiLeu labeling technique combined with LC-MS/MS and CE-MS/MS platforms were applied to profile and quantify amine-containing metabolites in mouse urine. The variability of concentrations of identified metabolites in urine samples from different mouse individuals was illustrated by the ratios of reporter ion intensities acquired from online data-dependent analysis.

Analytical strategies used to identify the readers of histone modifications: A review

The so-called "readers" of histone post-translational modifications (HPTMs) refer to proteins or complexes that are recruited to HPTMs thus eventually regulate gene transcription. To identify these "readers", mass spectrometry plays an essential role following various enriching strategies. These enriching methods include the use of modified histone peptides/proteins or chemically synthesized histones/nucleosomes containing desired HPTMs to enrich the readers of HPTMs. Despite the peptide- or protein-based assay is straightforward and easy to perform for most labs, this strategy has limited applications for those weak or combinational interactions among various HPTMs and false-positive results are a potential big problem. While the results derived from synthesized histone proteins/nucleosomes is more reliable as it mimics the real chromatic conditions thus is able to analyze the binders of those cross-talked HPTMs, usually the synthesis is so difficult that their applications are impeded for high throughput analysis. In this review, an overview of these analytical techniques is provided and their advantages and disadvantages are discussed.

Development and characterization of novel 8-plex DiLeu isobaric labels for quantitative proteomics and peptidomics

RATIONALE

Relative quantification of proteins via their enzymatically digested peptide products determines disease biomarker candidate lists in discovery studies. Isobaric label-based strategies using TMT and iTRAQ allow for up to 10 samples to be multiplexed in one experiment, but their expense limits their use. The demand for cost-effective tagging reagents capable of multiplexing many samples led us to develop an 8-plex version of our isobaric labeling reagent, DiLeu.

METHODS

The original 4-plex DiLeu reagent was extended to an 8-plex set by coupling isotopic variants of dimethylated leucine to an alanine balance group designed to offset the increasing mass of the label's reporter group. Tryptic peptides from a single protein digest, a protein mixture digest, and Saccharomyces cerevisiae lysate digest were labeled with 8-plex DiLeu and analyzed via nanospray liquid chromatography/tandem mass spectrometry (nanoLC/MS(2) ) on a Q-Exactive Orbitrap mass spectrometer. Characteristics of 8-plex DiLeu-labeled peptides, including quantitative accuracy and fragmentation, were examined.

RESULTS

An 8-plex set of DiLeu reagents with 1 Da spaced reporters was synthesized at a yield of 36%. The average cost to label eight 100 µg peptide samples was calculated to be approximately $15. Normalized collision energy tests on the Q-Exactive revealed that a higher-energy collisional dissociation value of 27 generated the optimum number of high-quality spectral matches. Relative quantification of DiLeu-labeled peptides yielded normalized median ratios accurate to within 12% of their expected values.

CONCLUSIONS

Cost-effective 8-plex DiLeu reagents can be synthesized and applied to relative peptide and protein quantification. These labels increase the multiplexing capacity of our previous 4-plex implementation without requiring high-resolution instrumentation to resolve reporter ion signals.

From pathways to networks: connecting dots by establishing protein-protein interaction networks in signaling pathways using affinity purification and mass spectrometry

Signal transductions are the basis of biological activities in all living organisms. Studying the signaling pathways, especially under physiological conditions, has become one of the most important facets of modern biological research. During the last decade, MS has been used extensively in biological research and is proven to be effective in addressing important biological questions. Here, we review the current progress in the understanding of signaling networks using MS approaches. We will focus on studies of protein-protein interactions that use affinity purification followed by MS approach. We discuss obstacles to affinity purification, data processing, functional validation, and identification of transient interactions and provide potential solutions for pathway-specific proteomics analysis, which we hope one day will lead to a comprehensive understanding of signaling networks in humans.