bims-mascan Biomed News
on Mass spectrometry in cancer research
Issue of 2024‒01‒14
27 papers selected by
Giovanny Rodriguez Blanco, University of Edinburgh



  1. Anal Chem. 2024 Jan 11.
      Untargeted lipidomics using liquid chromatography (LC) coupled with tandem mass spectrometry (MS) is essential for large cohort studies. Using a fast LC gradient of less than 10 min for the rapid screening of lipids decreases the annotation rate, because of the lower coverage of the MS/MS spectra caused by the narrow peak width. A systematic procedure is proposed in this study to achieve a high annotation rate in fast LC-based untargeted lipidomics by integrating data-dependent acquisition (DDA) and sequential window acquisition of all-theoretical mass spectrometry data-independent acquisition (SWATH-DIA) techniques using the updated MS-DIAL program. This strategy uses variable SWATH-DIA methods for quality control (QC) samples, which are a mixture of biological samples that were analyzed multiple times to correct the MS signal drift. In contrast, biological samples are analyzed using DDA to facilitate the structural elucidation of lipids using the pure spectrum to the maximum extent. The workflow is demonstrated using an 8.6 min LC gradient, where the QC samples are analyzed using five different SWATH-DIA methods. The use of both DDA and SWATH-DIA achieves a 1.7-fold annotation coverage from publicly available benchmark data obtained using a fast LC-DDA-MS technique and offers 95.3% lipid coverage, as compared to the benchmark data set from a 25 min LC gradient. This study demonstrates that harmonized improvements in analytical conditions and informatics tools provide a comprehensive lipidome in fast LC-based untargeted lipidomics, not only for large-scale studies but also for small-scale experiments, contributing to both clinical applications and basic biology.
    DOI:  https://doi.org/10.1021/acs.analchem.3c04400
  2. Mol Cell Proteomics. 2024 Jan 04. pii: S1535-9476(24)00003-3. [Epub ahead of print] 100713
      Optimizing data-independent acquisition (DIA) methods for proteomics applications often requires balancing spectral resolution and acquisition speed. Here we describe a real-time, full mass range implementation of the Phase-constrained Spectrum Deconvolution Method (ΦSDM) for OrbitrapTM mass spectrometry that increases mass resolving power without increasing scan time. Comparing its performance to the standard enhanced Fourier transformation (eFT) signal processing revealed that the increased resolving power of ΦSDM is beneficial in areas of high peptide density and comes with a greater ability to resolve low-abundance signals. In a standard 2-hour analysis of a 200 ng HeLa digest, this resulted in an increase of 16% in the number of quantified peptides. As the acquisition speed becomes even more important when using fast chromatographic gradients, we further applied ΦSDM methods to a range of shorter gradient lengths (21, 12, and 5 min). While ΦSDM improved identification rates and spectral quality in all tested gradients, it proved particularly advantageous for the 5 min gradient. Here the number of identified protein groups and peptides increased by >15% in comparison to eFT processing. In conclusion, ΦSDM is an alternative signal processing algorithm for processing Orbitrap data that can improve spectral quality and benefit quantitative accuracy in typical proteomics experiments, especially when using short gradients.
    Keywords:  Orbitrap; data-independent acquisition; high-throughput; proteomics; ΦSDM
    DOI:  https://doi.org/10.1016/j.mcpro.2024.100713
  3. Anal Sci Adv. 2023 Jul;4(5-6): 181-203
      Top-down proteomics (TDP) identifies, quantifies, and characterizes proteins at the intact proteoform level in complex biological samples to understand proteoform function and cellular mechanisms. However, analyzing complex biological samples using TDP is still challenging due to high sample complexity and wide dynamic range. High-resolution separation methods are often applied prior to mass spectrometry (MS) analysis to decrease sample complexity and increase proteomics throughput. These separation methods, however, may not be efficient enough to characterize low abundance intact proteins in complex samples. As such, multidimensional separation techniques (combination of two or more separation methods with high orthogonality) have been developed and applied that demonstrate improved separation resolution and more comprehensive identification in TDP. A suite of multidimensional separation methods that couple various types of liquid chromatography (LC), capillary electrophoresis (CE), and/or gel electrophoresis-based separation approaches have been developed and applied in TDP to analyze complex biological samples. Here, we reviewed multidimensional separation strategies employed for TDP, summarized current applications, and discussed the gaps that may be addressed in the future.
    Keywords:  CE; LC; Top-down proteomics; gel electrophoresis; multidimensional separation
    DOI:  https://doi.org/10.1002/ansa.202300016
  4. Anal Chem. 2024 Jan 12.
      Hyperplexing approaches have been aimed to meet the demand for large-scale proteomic analyses. Currently, the analysis capacity has expanded to up to 54 samples within a single experiment by utilizing different isotopic and isobaric reagent combinations. In this report, we propose a super multiplexed approach to enable the analysis of up to 102 samples in a single experiment, by the combination of our recently developed TAG-TMTpro and TAG-IBT16 labeling. We systematically investigated the identification and quantification performance of the 102-plex approach using the mixtures of E. coli and HeLa peptides. Our results revealed that all labeling series demonstrated accurate and reliable quantification performance. The combination of TAG-IBT16 and TAG-TMTpro approaches expands the multiplexing capacity to 102 plexes, providing a more multiplexed quantification method for even larger-scale proteomic analysis. Data are available via ProteomeXchange with the identifier PXD042398.
    DOI:  https://doi.org/10.1021/acs.analchem.3c03036
  5. EMBO Rep. 2024 Jan 12.
      Tumor cells reprogram nutrient acquisition and metabolic pathways to meet their energetic, biosynthetic, and redox demands. Similarly, metabolic processes in immune cells support host immunity against cancer and determine differentiation and fate of leukocytes. Thus, metabolic deregulation and imbalance in immune cells within the tumor microenvironment have been reported to drive immune evasion and to compromise therapeutic outcomes. Interestingly, emerging evidence indicates that anti-tumor immunity could modulate tumor heterogeneity, aggressiveness, and metabolic reprogramming, suggesting that immunosurveillance can instruct cancer progression in multiple dimensions. This review summarizes our current understanding of how metabolic crosstalk within tumors affects immunogenicity of tumor cells and promotes cancer progression. Furthermore, we explain how defects in the metabolic cascade can contribute to developing dysfunctional immune responses against cancers and discuss the contribution of immunosurveillance to these defects as a feedback mechanism. Finally, we highlight ongoing clinical trials and new therapeutic strategies targeting cellular metabolism in cancer.
    Keywords:  Cancer Evolution; Immunoediting; Immunometabolism
    DOI:  https://doi.org/10.1038/s44319-023-00038-w
  6. Res Sq. 2023 Dec 23. pii: rs.3.rs-3788683. [Epub ahead of print]
      Lipids play many important physiological roles in mammalian reproduction, being essential for the acquisition of oocyte competence and post-fertilization embryonic development. Lipid profiling in samples of minute size, such as oocytes, is challenging but has been achieved by mass spectrometry technologies such as multiple reaction monitoring (MRM) profiling. With the goals of further simplifying sample workflow and investigating the influence of pre-analytical conditions, we have evaluated how different extraction methods and transportation of lipid extracts in vacuum and at room temperature impacted the lipid profile of bovine oocytes. Using a comprehensive method, 316 MRMs associated with lipids of 10 different classes were screened in oocyte lipid extracts prepared by 2 extraction methods (one-step methanol addition or Bligh and Dyer) and transporting them in dry ice or at room temperature inside vacuum packages. No changes in the multivariate analysis (PCA) were noticeable due to transportation temperature, while lipid profiles were more affected by the lipid extraction protocol. Sample extraction using pure methanol favored the detection of phospholipids uniformly, while Bligh and Dyer favored the detection of neutral intracellular lipids. Triacylglycerol lipids and free fatty acids yielded decreased abundances when samples were transported at room temperature. We conclude that if samples are submitted to the same lipid extraction protocol and same transportation batch at room temperature coupled with vacuum conditions it is possible to analyze lipid extracts of bovine oocytes and still obtain informative lipid profiling results.
    DOI:  https://doi.org/10.21203/rs.3.rs-3788683/v1
  7. Cancers (Basel). 2023 Dec 22. pii: 69. [Epub ahead of print]16(1):
      Amino acids are the building blocks of proteins and essential players in pathways such as the citric acid and urea cycle, purine and pyrimidine biosynthesis, and redox cell signaling. Therefore, it is unsurprising that these molecules have a significant role in cancer metabolism and its metabolic plasticity. As one of the most prevalent malign diseases, colorectal cancer needs biomarkers for its early detection, prognostic, and prediction of response to therapy. However, the available biomarkers for this disease must be more powerful and present several drawbacks, such as high costs and complex laboratory procedures. Metabolomics has gathered substantial attention in the past two decades as a screening platform to study new metabolites, partly due to the development of techniques, such as mass spectrometry or liquid chromatography, which have become standard practice in diagnostic procedures for other diseases. Extensive metabolomic studies have been performed in colorectal cancer (CRC) patients in the past years, and several exciting results concerning amino acid metabolism have been found. This review aims to gather and present findings concerning alterations in the amino acid plasma pool of colorectal cancer patients.
    Keywords:  amino acids; biomarkers; colorectal cancer; diagnosis; laboratorial findings; metabolomics; prognosis; treatment response
    DOI:  https://doi.org/10.3390/cancers16010069
  8. Methods. 2024 Jan 05. pii: S1046-2023(23)00218-9. [Epub ahead of print]
      Many of the health-associated impacts of the microbiome are mediated by its chemical activity, producing and modifying small molecules (metabolites). Thus, microbiome metabolite quantification has a central role in efforts to elucidate and measure microbiome function. In this review, we cover general considerations when designing experiments to quantify microbiome metabolites, including sample preparation, data acquisition and data processing, since these are critical to downstream data quality. We then discuss data analysis and experimental steps to demonstrate that a given metabolite feature is of microbial origin. We further discuss techniques used to quantify common microbial metabolites, including short-chain fatty acids (SCFA), secondary bile acids (BAs), tryptophan derivatives, N-acyl amides and trimethylamine N-oxide (TMAO). Lastly, we conclude with challenges and future directions for the field.
    Keywords:  Bile acids; Data processing; Instrumental methods; Mass spectrometry; Microbiome metabolite quantification; Short-chain fatty acids
    DOI:  https://doi.org/10.1016/j.ymeth.2023.12.007
  9. Anal Bioanal Chem. 2024 Jan 12.
      Lipids are a diverse class of molecules involved in many biological functions including cell signaling or cell membrane assembly. Owing to this relevance, LC-MS/MS-based lipidomics emerged as a major field in modern analytical chemistry. Here, we thoroughly characterized the influence of MS and LC settings - of a Q Exactive HF operated in Full MS/data-dependent MS2 TOP N acquisition mode - in order to optimize the semi-quantification of polar lipids. Optimization of MS-source settings improved the signal intensity by factor 3 compared to default settings. Polar lipids were separated on an ACQUITY Premier CSH C18 reversed-phase column (100 × 2.1 mm, 1.7 µm, 130 Å) during an elution window of 28 min, leading to a sufficient number of both data points across the chromatographic peaks, as well as MS2 spectra. Analysis was carried out in positive and negative ionization mode enabling the detection of a broader spectrum of lipids and to support the structural characterization of lipids. Optimal sample preparation of biological samples was achieved by liquid-liquid extraction using MeOH/MTBE resulting in an excellent extraction recovery > 85% with an intra-day and inter-day variability < 15%. The optimized method was applied on the investigation of changes in the phospholipid pattern in plasma from human subjects supplemented with n3-PUFA (20:5 and 22:6). The strongest increase was observed for lipids bearing 20:5, while 22:4 bearing lipids were lowered. Specifically, LPC 20:5_0:0 and PC 16:0_20:5 were found to be strongest elevated, while PE 18:0_22:4 and PC 18:2_18:2 were decreased by n3-PUFA supplementation. These results were confirmed by targeted LC-MS/MS using commercially available phospholipids as standards.
    Keywords:  High-resolution mass spectrometry; Ion suppression; Phospholipids; Reversed-phase liquid chromatography; Untargeted analysis; n3-PUFA supplementation
    DOI:  https://doi.org/10.1007/s00216-023-05080-0
  10. Cancer Cell Int. 2024 Jan 06. 24(1): 15
      Metabolic reprogramming, which is recognized as a hallmark of cancer, refers to the phenomenon by which cancer cells change their metabolism to support their increased biosynthetic demands. Tumor cells undergo substantial alterations in metabolic pathways, such as glycolysis, oxidative phosphorylation, pentose phosphate pathway, tricarboxylic acid cycle, fatty acid metabolism, and amino acid metabolism. Latest studies have revealed that long non-coding RNAs (lncRNAs), a group of non-coding RNAs over 200 nucleotides long, mediate metabolic reprogramming in tumor cells by regulating the transcription, translation and post-translational modification of metabolic-related signaling pathways and metabolism-related enzymes through transcriptional, translational, and post-translational modifications of genes. In addition, lncRNAs are closely related to the tumor microenvironment, and they directly or indirectly affect the proliferation and migration of tumor cells, drug resistance and other processes. Here, we review the mechanisms of lncRNA-mediated regulation of glucose, lipid, amino acid metabolism and tumor immunity in gastrointestinal tumors, aiming to provide more information on effective therapeutic targets and drug molecules for gastrointestinal tumors.
    Keywords:  Gastrointestinal tract tumors; Long non-coding RNAs; Metabolic enzymes; Metabolic reprogramming; Prognosis; Therapeutic targets; Tumor microenvironment; microRNA
    DOI:  https://doi.org/10.1186/s12935-023-03194-0
  11. bioRxiv. 2023 Dec 24. pii: 2023.12.24.573250. [Epub ahead of print]
      The tumor microenvironment is a determinant of cancer progression and therapeutic efficacy, with nutrient availability playing an important role. Although it is established that the local abundance of specific nutrients defines the metabolic parameters for tumor growth, the factors guiding nutrient availability in tumor compared to normal tissue and blood remain poorly understood. To define these factors in renal cell carcinoma (RCC), we performed quantitative metabolomic and comprehensive lipidomic analyses of tumor interstitial fluid (TIF), adjacent normal kidney interstitial fluid (KIF), and plasma samples collected from patients. TIF nutrient composition closely resembles KIF, suggesting that tissue-specific factors unrelated to the presence of cancer exert a stronger influence on nutrient levels than tumor-driven alterations. Notably, select metabolite changes consistent with known features of RCC metabolism are found in RCC TIF, while glucose levels in TIF are not depleted to levels that are lower than those found in KIF. These findings inform tissue nutrient dynamics in RCC, highlighting a dominant role of non-cancer driven tissue factors in shaping nutrient availability in these tumors.
    DOI:  https://doi.org/10.1101/2023.12.24.573250
  12. Br J Cancer. 2024 Jan 12.
      BACKGROUND: Peroxisomes are central metabolic organelles that have key roles in fatty acid homoeostasis. As prostate cancer (PCa) is particularly reliant on fatty acid metabolism, we explored the contribution of peroxisomal β-oxidation (perFAO) to PCa viability and therapy response.METHODS: Bioinformatic analysis was performed on clinical transcriptomic datasets to identify the perFAO enzyme, 2,4-dienoyl CoA reductase 2 (DECR2) as a target gene of interest. Impact of DECR2 and perFAO inhibition via thioridazine was examined in vitro, in vivo, and in clinical prostate tumours cultured ex vivo. Transcriptomic and lipidomic profiling was used to determine the functional consequences of DECR2 inhibition in PCa.
    RESULTS: DECR2 is upregulated in clinical PCa, most notably in metastatic castrate-resistant PCa (CRPC). Depletion of DECR2 significantly suppressed proliferation, migration, and 3D growth of a range of CRPC and therapy-resistant PCa cell lines, and inhibited LNCaP tumour growth and proliferation in vivo. DECR2 influences cell cycle progression and lipid metabolism to support tumour cell proliferation. Further, co-targeting of perFAO and standard-of-care androgen receptor inhibition enhanced suppression of PCa cell proliferation.
    CONCLUSION: Our findings support a focus on perFAO, specifically DECR2, as a promising therapeutic target for CRPC and as a novel strategy to overcome lethal treatment resistance.
    DOI:  https://doi.org/10.1038/s41416-023-02557-8
  13. Anal Chem. 2024 Jan 08.
      Lipid nanoparticle-encapsulated mRNA (LNP-mRNA) holds great promise as a novel modality for treating a broad range of diseases. The ability to quantify mRNA accurately in therapeutic products helps to ensure consistency and safety. Here, we consider a central aspect of accuracy, measurement traceability, which establishes trueness in quantity. In this study, LNP-mRNA is measured in situ using a novel liquid chromatography-mass spectrometry (LC-MS) approach with traceable quantification. Previous works established that oligonucleotide quantification is possible through the accounting of an oligomer's fundamental nucleobases, with traceability established through common nucleobase calibrators. This sample preparation does not require mRNA extraction, detergents, or enzymes and can be achieved through direct acid hydrolysis of an LNP-mRNA product prior to an isotope dilution strategy. This results in an accurate quantitative analysis of mRNA, independent of time or place. Acid hydrolysis LC-MS is demonstrated to be amenable to measuring mRNA as both an active substance or a formulated mRNA drug product.
    DOI:  https://doi.org/10.1021/acs.analchem.3c04406
  14. Anal Chem. 2024 Jan 08.
      The accuracy of the structural annotation of unidentified peaks obtained in metabolomic analysis using liquid chromatography/tandem mass spectrometry (LC/MS/MS) can be enhanced using retention time (RT) information as well as precursor and product ions. Unified-hydrophilic-interaction/anion-exchange liquid chromatography high-resolution tandem mass spectrometry (unified-HILIC/AEX/HRMS/MS) has been recently developed as an innovative method ideal for nontargeted polar metabolomics. However, the RT prediction for unified-HILIC/AEX has not been developed because of the complex separation mechanism characterized by the continuous transition of the separation modes from HILIC to AEX. In this study, we propose an RT prediction model of unified-HILIC/AEX/HRMS/MS, which enables the comprehensive structural annotation of polar metabolites. With training data for 203 polar metabolites, we ranked the feature importance using a random forest among 12,420 molecular descriptors (MDs) and constructed an RT prediction model with 26 selected MDs. The accuracy of the RT model was evaluated using test data for 51 polar metabolites, and 86.3% of the ΔRTs (difference between measured and predicted RTs) were within ±1.50 min, with a mean absolute error of 0.80 min, indicating high RT prediction accuracy. Nontargeted metabolomic data from the NIST SRM 1950-Metabolites in frozen human plasma were analyzed using the developed RT model and in silico MS/MS prediction, resulting in a successful structural estimation of 216 polar metabolites, in addition to the 62 identified based on standards. The proposed model can help accelerate the structural annotation of unknown hydrophilic metabolites, which is a key issue in metabolomic research.
    DOI:  https://doi.org/10.1021/acs.analchem.3c04618
  15. Food Funct. 2024 Jan 10.
      The biological functions of fatty acids and the lipids in which they are esterified are determined by their chain length, double bond position and geometry and other structural motifs such as the presence of methyl branches. Unusual isomeric features in fatty acids of human foods such as conjugated double bonds or chain branching found in dairy products, some seeds and nuts, and marine foods potentially have important effects on human health. Recent advancements in identifying fatty acids with unusual double bond positions and pinpointing the position of methyl branches have empowered the study of their biological functions. We present recent advances in fatty acid structural elucidation by mass spectrometry in comparison with the more traditional methods. The double bond position can be determined by purely instrumental methods, specifically solvent-mediated covalent adduct chemical ionization (SM-CACI) and ozone induced dissociation (OzID), with charge inversion methods showing promise. Prior derivatization using the Paternò-Büchi (PB) reaction to yield stable structures that, upon collisional activation, yield the double bond position has emerged. The chemical ionization (CI) based three ion monitoring (MRM) method has been developed to simultaneously identify and quantify low-level branched chain fatty acids (BCFAs), unattainable by electron ionization (EI) based methods. Accurate identification and quantification of unusual fatty acid isomers has led to research progress in the discovery of biomarkers for cancer, diabetes, nonalcoholic fatty liver disease (NAFLD) and atherosclerosis. Modulation of eicosanoids, weight loss and the health significance of BCFAs are also presented. This review clearly shows that the improvement of analytical capacity is critical in the study of fatty acid biological functions, and stronger coupling of the methods discussed here with fatty acid mechanistic research is promising in generating more refined outcomes.
    DOI:  https://doi.org/10.1039/d3fo03716a
  16. Anal Chem. 2024 Jan 09.
      Ion mobility mass spectrometry (IM-MS) is a rapid, gas-phase separation technology that can resolve ions on the basis of their size-to-charge and mass-to-charge ratios. Since each class of biomolecule has a unique relationship between size and mass, IM-MS spectra of complex biological samples are organized into trendlines that each contain one type of biomolecule (i.e., lipid, peptide, metabolite). These trendlines can aid in the identification of unknown ions by providing a general classification, while more specific identifications require the conversion of IM arrival times to collision cross section (CCS) values to minimize instrument-to-instrument variability. However, the process of converting IM arrival times to CCS values varies between the different IM devices. Arrival times from traveling wave ion mobility (TWIM) devices must undergo a calibration process to obtain CCS values, which can impart biases if the calibrants are not structurally similar to the analytes. For multiomic mixtures, several different types of calibrants must be used to obtain the most accurate CCS values from TWIM platforms. Here we describe the development of a multiomic CCS calibration tool, MOCCal, to automate the assignment of unknown features to the power law calibration that provides the most accurate CCS value. MOCCal calibrates every experimental arrival time with up to three class-specific calibration curves and uses the difference (in Å2) between the calibrated TWCCSN2 value and DTCCSN2 vs m/z regression lines to determine the best calibration curve. Using real and simulated multiomic samples, we demonstrate that MOCCal provides accurately calibrated TWCCSN2 values for small molecules, lipids, and peptides.
    DOI:  https://doi.org/10.1021/acs.analchem.3c04290
  17. Chem Res Toxicol. 2024 Jan 10.
      Pyridone-containing adenine dinucleotides, ox-NAD, are formed by overoxidation of nicotinamide adenine dinucleotide (NAD+) and exist in three distinct isomeric forms. Like the canonical nucleosides, the corresponding pyridone-containing nucleosides (PYR) are chemically stable, biochemically versatile, and easily converted to nucleotides, di- and triphosphates, and dinucleotides. The 4-PYR isomer is often reported with its abundance increasing with the progression of metabolic diseases, age, cancer, and oxidative stress. Yet, the pyridone-derived nucleotides are largely under-represented in the literature. Here, we report the efficient synthesis of the series of ox-NAD and pyridone nucleotides and measure the abundance of ox-NAD in biological specimens using liquid chromatography coupled with mass spectrometry (LC-MS). Overall, we demonstrate that all three forms of PYR and ox-NAD are found in biospecimens at concentrations ranging from nanomolar to midmicromolar and that their presence affects the measurements of NAD(H) concentrations when standard biochemical redox-based assays are applied. Furthermore, we used liver extracts and 1H NMR spectrometry to demonstrate that each ox-NAD isomer can be metabolized to its respective PYR isomer. Together, these results suggest a need for a better understanding of ox-NAD in the context of human physiology since these species are endogenous mimics of NAD+, the key redox cofactor in metabolism and bioenergetics maintenance.
    DOI:  https://doi.org/10.1021/acs.chemrestox.3c00264
  18. Int J Mol Sci. 2023 Dec 20. pii: 75. [Epub ahead of print]25(1):
      Ferroptosis is a newly discovered form of regulated cell death. The main feature of ferroptosis is excessive membrane lipid peroxidation caused by iron-mediated chemical and enzymatic reactions. In normal cells, harmful lipid peroxides are neutralized by glutathione peroxidase 4 (GPX4). When GPX4 is inhibited, ferroptosis occurs. In mammalian cells, ferroptosis serves as a tumor suppression mechanism. Not surprisingly, in recent years, ferroptosis induction has gained attention as a potential anticancer strategy, alone or in combination with other conventional therapies. However, sensitivity to ferroptosis inducers depends on the metabolic state of the cell. Endometrial cancer (EC) is the sixth most common cancer in the world, with more than 66,000 new cases diagnosed every year. Out of all gynecological cancers, carcinogenesis of EC is mostly dependent on metabolic abnormalities. Changes in the uptake and catabolism of iron, lipids, glucose, and glutamine affect the redox capacity of EC cells and, consequently, their sensitivity to ferroptosis-inducing agents. In addition to this, in EC cells, ferroptosis-related genes are usually mutated and overexpressed, which makes ferroptosis a promising target for EC prediction, diagnosis, and therapy. However, for a successful application of ferroptosis, the connection between metabolic rewiring and ferroptosis in EC needs to be deciphered, which is the focus of this review.
    Keywords:  endometrial cancer; ferroptosis; metabolism; resistance
    DOI:  https://doi.org/10.3390/ijms25010075
  19. bioRxiv. 2023 Dec 18. pii: 2023.12.17.572088. [Epub ahead of print]
      Aging is accompanied by multiple molecular changes that contribute to aging-associated pathologies, such as accumulation of cellular damage and mitochondrial dysfunction. Tissue metabolism can also change with age, in part because mitochondria are central to cellular metabolism. Moreover, the co-factor NAD+, which is reported to decline across multiple tissue types during aging, plays a central role in metabolic pathways such as glycolysis, the tricarboxylic acid cycle, and the oxidative synthesis of nucleotides, amino acids, and lipids. To further characterize how tissue metabolism changes with age, we intravenously infused [U-13C]-glucose into young and old C57BL/6J, WSB/EiJ, and Diversity Outbred mice to trace glucose fate into downstream metabolites within plasma, liver, gastrocnemius muscle, and brain tissues. We found that glucose incorporation into central carbon and amino acid metabolism was robust during healthy aging across these different strains of mice. We also observed that levels of NAD+, NADH, and the NAD+/NADH ratio were unchanged in these tissues with healthy aging. However, aging tissues, particularly brain, exhibited evidence of up-regulated fatty acid and sphingolipid metabolism reactions that regenerate NAD+ from NADH. Because mitochondrial respiration, a major source of NAD+ regeneration, is reported to decline with age, our data supports a model where NAD+-generating lipid metabolism reactions may buffer against changes in NAD+/NADH during healthy aging.
    DOI:  https://doi.org/10.1101/2023.12.17.572088
  20. Mol Neurobiol. 2024 Jan 06.
      AIMS: Ischemic stroke (IS) is the most common subtype of stroke. The risk factors and pathogenesis of IS are complex and varied due to different subtypes. Therefore, we used metabolomics technology to investigate the biomarkers and potential pathophysiological mechanisms of different subtypes of IS.METHODS: We included 126 IS patients and divided them into two groups based on the TOAST classification: large-artery atherosclerosis (LAA) group (n = 87) and small-vessel occlusion (SVO) group (n = 39). Plasma metabolomics analysis was performed using liquid chromatography-high-resolution mass spectrometry (LC-HRMS) to identify metabolic profiles in LAA and SVO subtype IS patients and to determine metabolic differences between patients with the two subtypes of IS.
    RESULTS: We identified 26 differential metabolites between LAA and SVO subtype IS. A multiple prediction model based on the plasm metabolites had good predictive ability for IS subtyping (AUC = 0.822, accuracy = 77.8%), with 12,13-DHOME being the most important differential metabolite in the model. The differential metabolic pathways between the two subtypes of IS patients included tricarboxylic acid (TCA) cycle, alanine, aspartate and glutamate metabolism, and pyruvate metabolism, mainly focused on energy metabolism.
    CONCLUSION: 12,13-DHOME emerged as the primary discriminatory metabolite between LAA and SVO subtypes of IS. In LAA subtype IS patients, energy metabolism, encompassing pyruvate metabolism and the TCA cycle, exhibited lower activity levels when compared to patients with the SVO subtype IS. The utilization of targeted metabolomics holds the potential to improve diagnostic accuracy for distinguishing stroke subtypes.
    Keywords:  12, 13-DHOME; Ischemic stroke; Large-artery atherosclerosis; Metabolomics; Small-vessel occlusion
    DOI:  https://doi.org/10.1007/s12035-023-03884-w
  21. Trends Endocrinol Metab. 2024 Jan 10. pii: S1043-2760(23)00250-3. [Epub ahead of print]
      Tumours are heterogeneous tissues containing diverse populations of cells and an abundant extracellular matrix (ECM). This tumour microenvironment prompts cancer cells to adapt their metabolism to survive and grow. Besides epigenetic factors, the metabolism of cancer cells is shaped by crosstalk with stromal cells and extracellular components. To date, most experimental models neglect the complexity of the tumour microenvironment and its relevance in regulating the dynamics of the metabolism in cancer. We discuss emerging strategies to model cellular and extracellular aspects of cancer metabolism. We highlight cancer models based on bioengineering, animal, and mathematical approaches to recreate cell-cell and cell-matrix interactions and patient-specific metabolism. Combining these approaches will improve our understanding of cancer metabolism and support the development of metabolism-targeting therapies.
    Keywords:  cancer metabolism; cancer models; mathematical models; tumour microenvironment
    DOI:  https://doi.org/10.1016/j.tem.2023.12.005
  22. Zhonghua Yu Fang Yi Xue Za Zhi. 2023 Dec 06. 57(12): 2073-2085
    Grassroots Inspection Technology Standardization Branch of China International Exchange and Promotive Association for Medical and Health Care
      Liquid chromatography-tandem mass spectrometry (LC-MS/MS) combines the advantages of high separation ability of chromatography and high selectivity, specificity and sensitivity of mass spectrometry, making it one of the most vibrant new technologies in the field of clinical testing. However, the analytical performance is often limited by the characteristics of the sample to be measured. Due to the limited anti-contamination capability of the mass spectrometer, biological samples need to be properly pre-processed to effectively improve the detection performance and achieve accurate detection. The main function of pre-treatment is to selectively separate the target analyte from the biological matrix to reduce interference from other matrix components. At the same time, the target analytes can be concentrated and enriched to improve the analytical sensitivity. At present, there are many kinds of clinical sample pre-treatment methods, and several methods are time-consuming and cumbersome, which brings difficulties to laboratory personnel in method selection, development and standardized operation. Therefore, the purpose of this consensus is to provide guidance for the establishment of laboratory methods and facilitate the standardized development of clinical mass spectrometry measurement.
    DOI:  https://doi.org/10.3760/cma.j.cn112150-20230906-00160
  23. mSystems. 2024 Jan 11. e0035623
      IMPORTANCE: Systems biology research on host-associated microbiota focuses on two fundamental questions: which microbes are present and how do they interact with each other, their host, and the broader host environment? Metagenomics provides us with a direct answer to the first part of the question: it unveils the microbial inhabitants, e.g., on our skin, and can provide insight into their functional potential. Yet, it falls short in revealing their active role. Metabolomics shows us the chemical composition of the environment in which microbes thrive and the transformation products they produce. In particular, untargeted metabolomics has the potential to observe a diverse set of metabolites and is thus an ideal complement to metagenomics. However, this potential often remains underexplored due to the low annotation rates in MS-based metabolomics and the necessity for multiple experimental chromatographic and mass spectrometric conditions. Beyond detection, prospecting metabolites' functional role in the host/microbiome metabolome requires identifying the biological processes and entities involved in their production and biotransformations. In the present study of the human scalp, we developed a strategy to achieve comprehensive structural and functional annotation of the metabolites in the human scalp environment, thus diving one step deeper into the interpretation of "omics" data. Leveraging a collection of openly accessible software tools and integrating microbiome data as a source of functional metabolite annotations, we finally identified the specific metabolic niche of Staphylococcus epidermidis, one of the key players of the human skin microbiome.
    Keywords:  metabolite annotation; metabolomics; multi-omics integration; scalp; skin microbiome
    DOI:  https://doi.org/10.1128/msystems.00356-23
  24. Nucleic Acids Res. 2024 Jan 09. pii: gkad1249. [Epub ahead of print]
      The RNA-interacting proteome is commonly characterized by UV-crosslinking followed by RNA purification, with protein recovery quantified using SILAC labeling followed by data-dependent acquisition (DDA) of proteomic data. However, the low efficiency of UV-crosslinking, combined with limited sensitivity of the DDA approach often restricts detection to relatively abundant proteins, necessitating multiple mass spec injections of fractionated peptides for each biological sample. Here we report an application of data-independent acquisition (DIA) with SILAC in a total RNA-associated protein purification (TRAPP) UV-crosslinking experiment. This gave 15% greater protein detection and lower inter-replicate variation relative to the same biological materials analyzed using DDA, while allowing single-shot analysis of the sample. As proof of concept, we determined the effects of arsenite treatment on the RNA-bound proteome of HEK293T cells. The DIA dataset yielded similar GO term enrichment for RNA-binding proteins involved in cellular stress responses to the DDA dataset while detecting extra proteins unseen by DDA. Overall, the DIA SILAC approach improved detection of proteins over conventional DDA SILAC for generating RNA-interactome datasets, at a lower cost due to reduced machine time. Analyses are described for TRAPP data, but the approach is suitable for proteomic analyses following essentially any RNA-binding protein enrichment technique.
    DOI:  https://doi.org/10.1093/nar/gkad1249
  25. Methods Mol Biol. 2024 ;2752 215-226
      Laser ablation inductively coupled plasma-mass spectrometry (LA-ICP-MS) is a well-established and sensitive analytical technique, which provides high-resolution imaging of endogenous elements, element tagged-markers, metal-containing nanoparticles, and metallodrugs within cells. Here we describe a protocol for imaging the subcellular distribution of platinum within A549 cells, following their incubation with the platinum-based anticancer agent, Oxaliplatin. We outline the essential steps in sample preparation and instrumental setup and discuss how the current generation of low-dispersion instruments facilitates new approaches to data acquisition and image processing. The protocol described herein can be easily adapted for other cell lines and metal-containing labeling agents.
    Keywords:  A549 cells; ICP-MS; Imaging; Laser ablation; Oxaliplatin
    DOI:  https://doi.org/10.1007/978-1-0716-3621-3_14
  26. J Invest Dermatol. 2024 Jan 05. pii: S0022-202X(23)03211-6. [Epub ahead of print]
      A substantial part of cutaneous malignant melanomas develops from benign nevi. However, the precise molecular events driving the transformation from benign to malignant melanoma are not well understood. We used laser microdissection and mass spectrometry to analyze the proteomes of melanoma subtypes, including superficial spreading melanomas (SSM, n=17), nodular melanomas (NM, n=17), and acral melanomas (AM, n=15). Furthermore, we compared the proteomes of nevi cells and melanoma cells within the same specimens (nevus-associated melanoma (NAM, n=14)). In total, we quantified 7,935 proteins. Despite the genomic and clinical differences of the melanoma subtypes, our analysis revealed relatively similar proteomes, except for the upregulation of proteins involved in immune activation in NM vs AM. Examining NAM versus nevi, we found 1,725 differentially expressed proteins (FDR < 0.05). Among these proteins were 140 that overlapped with cancer hallmarks, tumor suppressors, and regulators of metabolism and cell cycle. Pathway analysis indicated aberrant activation of the PI3K-AKT-mTOR pathways and the Hippo-YAP pathway. Using a classifier, we identified six proteins capable of distinguishing melanoma from nevi samples. Our study represents a comprehensive comparative analysis of the proteome in melanoma subtypes and associated nevi, offering, to our knowledge, previously unreported insights into the biological behavior of these distinct entities.
    Keywords:  cancer; mass spectrometry; melanoma; proteomics; skin
    DOI:  https://doi.org/10.1016/j.jid.2023.12.011