bims-mascan Biomed News
on Mass spectrometry in cancer research
Issue of 2023–05–07
twenty papers selected by
Giovanny Rodríguez Blanco, Uniklinikum Graz
  1. Acetylcarnitine shuttling links mitochondrial metabolism to histone acetylation and lipogenesis.
  2. Sensitive, high-throughput HLA-I and HLA-II immunopeptidomics using parallel accumulation-serial fragmentation mass spectrometry.
  3. Robust and High-Throughput Analytical Flow Proteomics Analysis of Cynomolgus Monkey and Human Matrices with Zeno SWATH Data Independent Acquisition.
  4. Amino acid metabolism, redox balance and epigenetic regulation in cancer.
  5. Rapidly identifying and quantifying of unsaturated lipids with carbon-carbon double bond isomers by photoepoxidation.
  6. Inter-organelle cross-talk supports acetyl-coenzyme A homeostasis and lipogenesis under metabolic stress.
  7. Performance comparison of narrow-bore and capillary liquid-chromatography for non-targeted metabolomics profiling by HILIC-QTOF-MS.
  8. Integration of data-independent acquisition (DIA) with co-fractionation mass spectrometry (CF-MS) to enhance interactome mapping capabilities.
  9. Regions of Interest Multivariate Curve Resolution Liquid Chromatography with Data-Independent Acquisition Tandem Mass Spectrometry.
  10. One Carbon Metabolism and S-Adenosylmethionine in Non-Alcoholic Fatty Liver Disease Pathogenesis and Subtypes.
  11. Amino acid metabolism regulated by lncRNAs: the propellant behind cancer metabolic reprogramming.
  12. Targeting cellular respiration as a therapeutic strategy in glioblastoma.
  13. Mzion enables deep and precise identification of peptides in data-dependent acquisition proteomics.
  14. Targeting serine-glycine-one-carbon metabolism as a vulnerability in cancers.
  15. Peptide-encoding mRNA barcodes for the high-throughput in vivo screening of libraries of lipid nanoparticles for mRNA delivery.
  16. Metabonomic analysis of tumor microenvironments: a mini-review.
  17. Quantitative lipidomics analysis of changes in egg yolk lipids during spray-drying and subsequent accelerated storage.
  18. Kinetic data for modeling the dynamics of the enzymes involved in animal fatty acid synthesis.
  19. Single-cell metabolic fingerprints discover a cluster of circulating tumor cells with distinct metastatic potential.
  20. High sensitivity top-down proteomics captures single muscle cell heterogeneity in large proteoforms.
  1. Sci Adv. 2023 May 03. 9(18): eadf0115
    Acetylcarnitine shuttling links mitochondrial metabolism to histone acetylation and lipogenesis.
    Luke T Izzo, Sophie Trefely, Christina Demetriadou, Jack M Drummond, Takuya Mizukami, Nina Kuprasertkul, Aimee T Farria, Phuong T T Nguyen, Nivitha Murali, Lauren Reich, Daniel S Kantner, Joshua Shaffer, Hayley Affronti, Alessandro Carrer, Andrew Andrews, Brian C Capell, Nathaniel W Snyder, Kathryn E Wellen.
      The metabolite acetyl-CoA is necessary for both lipid synthesis in the cytosol and histone acetylation in the nucleus. The two canonical precursors to acetyl-CoA in the nuclear-cytoplasmic compartment are citrate and acetate, which are processed to acetyl-CoA by ATP-citrate lyase (ACLY) and acyl-CoA synthetase short-chain 2 (ACSS2), respectively. It is unclear whether other substantial routes to nuclear-cytosolic acetyl-CoA exist. To investigate this, we generated cancer cell lines lacking both ACLY and ACSS2 [double knockout (DKO) cells]. Using stable isotope tracing, we show that both glucose and fatty acids contribute to acetyl-CoA pools and histone acetylation in DKO cells and that acetylcarnitine shuttling can transfer two-carbon units from mitochondria to cytosol. Further, in the absence of ACLY, glucose can feed fatty acid synthesis in a carnitine responsive and carnitine acetyltransferase (CrAT)-dependent manner. The data define acetylcarnitine as an ACLY- and ACSS2-independent precursor to nuclear-cytosolic acetyl-CoA that can support acetylation, fatty acid synthesis, and cell growth.
    DOI:  https://doi.org/10.1126/sciadv.adf0115
  2. Mol Cell Proteomics. 2023 May 02. pii: S1535-9476(23)00073-7. [Epub ahead of print] 100563
    Sensitive, high-throughput HLA-I and HLA-II immunopeptidomics using parallel accumulation-serial fragmentation mass spectrometry.
    Kshiti Meera Phulphagar, Claudia Ctortecka, Alvaro Sebastian Vaca Jacome, Susan Klaeger, Eva K Verzani, Gabrielle M Hernandez, Namrata D Udeshi, Karl R Clauser, Jennifer G Abelin, Steven A Carr.
      Comprehensive, in-depth identification of the human leukocyte antigen HLA-I and HLA-II tumor immunopeptidome can inform the development of cancer immunotherapies. Mass spectrometry (MS) is powerful technology for direct identification of HLA peptides from patient derived tumor samples or cell lines. However, achieving sufficient coverage to detect rare, clinically relevant antigens requires highly sensitive MS-based acquisition methods and large amounts of sample. While immunopeptidome depth can be increased by off-line fractionation prior to MS, its use is impractical when analyzing limited amounts of primary tissue biopsies. To address this challenge, we developed and applied a high throughput, sensitive, single-shot MS-based immunopeptidomics workflow that leverages trapped ion mobility time-of-flight mass spectrometry on the Bruker timsTOF SCP. We demonstrate >2-fold improved coverage of HLA immunopeptidomes relative to prior methods with up to 15,000 distinct HLA-I and HLA-II peptides from 4e7 cells. Our optimized single-shot MS acquisition method on the timsTOF SCP maintains high coverage, eliminates the need for off-line fractionation and reduces input requirements to as few as 1e6 A375 cells for > 800 distinct HLA-I peptides. This depth is sufficient to identify HLA-I peptides derived from cancer-testis antigen, and non-canonical proteins. We also apply our optimized single-shot SCP acquisition methods to tumor derived samples, enabling sensitive, high throughput and reproducible immunopeptidome profiling with detection of clinically relevant peptides from less than 4e7 cells or 15 mg wet weight tissue.
    DOI:  https://doi.org/10.1016/j.mcpro.2023.100563
  3. Mol Cell Proteomics. 2023 May 02. pii: S1535-9476(23)00072-5. [Epub ahead of print] 100562
    Robust and High-Throughput Analytical Flow Proteomics Analysis of Cynomolgus Monkey and Human Matrices with Zeno SWATH Data Independent Acquisition.
    Weiwen Sun, Yuan Lin, Yue Huang, Josolyn Chan, Sonia Terrillon, Anton I Rosenbaum, Kévin Contrepois.
      Modern mass spectrometers routinely allow deep proteome coverage in a single experiment. These methods are typically operated at nano and micro flow regimes, but they often lack throughput and chromatographic robustness, which is critical for large-scale studies. In this context, we have developed, optimized and benchmarked LC-MS methods combining the robustness and throughput of analytical flow chromatography with the added sensitivity provided by the Zeno trap across a wide range of cynomolgus monkey and human matrices of interest for toxicological studies and clinical biomarker discovery. SWATH data independent acquisition (DIA) experiments with Zeno trap activated (Zeno SWATH DIA) provided a clear advantage over conventional SWATH DIA in all sample types tested with improved sensitivity, quantitative robustness and signal linearity as well as increased protein coverage by up to 9-fold. Using a 10-min gradient chromatography, up to 3,300 proteins were identified in tissues at 2 μg peptide load. Importantly, the performance gains with Zeno SWATH translated into better biological pathway representation and improved the ability to identify dysregulated proteins and pathways associated with two metabolic diseases in human plasma. Finally, we demonstrate that this method is highly stable over time with the acquisition of reliable data over the injection of 1,000+ samples (14.2 days of uninterrupted acquisition) without the need for human intervention or normalization. Altogether, Zeno SWATH DIA methodology allows fast, sensitive and robust proteomic workflows using analytical flow and is amenable to large-scale studies. This work provides detailed method performance assessment on a variety of relevant biological matrices and serves as a valuable resource for the proteomics community.
    DOI:  https://doi.org/10.1016/j.mcpro.2023.100562
  4. FEBS J. 2023 May 02.
    Amino acid metabolism, redox balance and epigenetic regulation in cancer.
    Xiang Li, Hong-Sheng Zhang.
      Amino acids act as the versatile nutrients driving cell growth and survival, especially in cancer cells. Amino acid metabolism comprises numerous metabolic networks and is closely linked with intracellular redox balance and epigenetic regulation. Reprogrammed amino acid metabolism has been recognized as a ubiquitous feature in tumor cells. This review outlines the metabolism of several primary amino acids in cancer cells and highlights the pivotal role of amino acid metabolism in sustaining redox homeostasis and regulating epigenetic modification in response to oxidative and genetic stress in cancer cells.
    Keywords:  amino acids; cancer; epigenetic regulation; metabolism; redox balance
    DOI:  https://doi.org/10.1111/febs.16803
  5. Talanta. 2023 Apr 29. pii: S0039-9140(23)00326-0. [Epub ahead of print]260 124575
    Rapidly identifying and quantifying of unsaturated lipids with carbon-carbon double bond isomers by photoepoxidation.
    Jian Zhang, Zesen Zhang, Ting Jiang, Zhenyu Zhang, Wenjing Zhang, Wei Xu.
      Unsaturated lipids play an essential role in life activities. Identifying and quantifying their carbon-carbon double bond (CC) isomers have become a hot topic in recent years. In lipidomics, the analysis of unsaturated lipids in complex biological samples usually requires high-throughput methods, which puts forward the requirements of rapid response and simple operation for identification. In this paper, we proposed a photoepoxidation strategy, which uses benzoin to open the double bonds of unsaturated lipids to form epoxides under ultraviolet light and aerobic conditions. Photoepoxidation is controlled by light and has a fast response. After 5 min, the derivatization yield can reach 80% with no side reaction products. Besides, the method has the advantages of high quantitation accuracy and a high yield of diagnostic ions. It was successfully applied to rapidly identify the double bond locations of various unsaturated lipids in both positive and negative ion modes, and to rapidly identify and quantitatively analyze the various isomers of unsaturated lipids in mouse tissue extract. So the method has the potential for large-scale analysis of unsaturated lipids in complex biological samples.
    Keywords:  Carbon-carbon double bond; Derivative reactions; Mass spectrometry; Photoepoxidation; Unsaturated lipid
    DOI:  https://doi.org/10.1016/j.talanta.2023.124575
  6. Sci Adv. 2023 May 03. 9(18): eadf0138
    Inter-organelle cross-talk supports acetyl-coenzyme A homeostasis and lipogenesis under metabolic stress.
    Ramya S Kuna, Avi Kumar, Karl A Wessendorf-Rodriguez, Hector Galvez, Courtney R Green, Grace H McGregor, Thekla Cordes, Reuben J Shaw, Robert U Svensson, Christian M Metallo.
      Proliferating cells rely on acetyl-CoA to support membrane biogenesis and acetylation. Several organelle-specific pathways are available for provision of acetyl-CoA as nutrient availability fluctuates, so understanding how cells maintain acetyl-CoA homeostasis under such stresses is critically important. To this end, we applied 13C isotope tracing cell lines deficient in these mitochondrial [ATP-citrate lyase (ACLY)]-, cytosolic [acetyl-CoA synthetase (ACSS2)]-, and peroxisomal [peroxisomal biogenesis factor 5 (PEX5)]-dependent pathways. ACLY knockout in multiple cell lines reduced fatty acid synthesis and increased reliance on extracellular lipids or acetate. Knockout of both ACLY and ACSS2 (DKO) severely stunted but did not entirely block proliferation, suggesting that alternate pathways can support acetyl-CoA homeostasis. Metabolic tracing and PEX5 knockout studies link peroxisomal oxidation of exogenous lipids as a major source of acetyl-CoA for lipogenesis and histone acetylation in cells lacking ACLY, highlighting a role for inter-organelle cross-talk in supporting cell survival in response to nutrient fluctuations.
    DOI:  https://doi.org/10.1126/sciadv.adf0138
  7. Talanta. 2023 Apr 22. pii: S0039-9140(23)00329-6. [Epub ahead of print]260 124578
    Performance comparison of narrow-bore and capillary liquid-chromatography for non-targeted metabolomics profiling by HILIC-QTOF-MS.
    Sylvia K Neef, Ute Hofmann, Thomas E Mürdter, Matthias Schwab, Mathias Haag.
      Clinical metabolomics studies often have to cope with limited sample amounts, thus miniaturized liquid chromatography (LC) systems are a promising alternative. Their applicability has already been demonstrated in various fields, including a few metabolomics studies that mainly used reversed-phase chromatography. However, hydrophilic interaction chromatography (HILIC), which is widely used in metabolomics due to its particular suitability for the analysis of polar molecules, has rarely been tested for miniaturized LC-MS analysis of small molecules. In the present work, the suitability of a capillary HILIC (CapHILIC)-QTOF-MS system for non-targeted metabolomics was evaluated based on extracts of porcine formalin-fixed, paraffin-embedded (FFPE) tissue samples. The performance was assessed with respect to the number and retention time span of metabolic features as well as the analytical repeatability, the signal-to-noise ratio and the signal intensity of 16 annotated metabolites from different compound classes. The results were compared with a well established narrow-bore HILIC-QTOF-MS system. Both platforms have detected a similar number of features and performed excellent with respect to retention time stability (median RT span <0.05 min) and analytical repeatability (>75% of features with CV < 20%). The signal areas of all metabolites assessed were increased up to 18-fold by the use of CapHILIC, although the signal-to-noise ratio was only improved for 50% of the metabolites. An even better reproducibility (median CV = 5.2%) and up to 80-fold increase in signal intensity were observed after optimization of CapHILIC conditions for analysis of bile acid standard solutions. Even though the observed improvement for specific bile acids (e.g. taurocholic acid) in biological matrix needs to be evaluated, the platform comparison indicates, that the tested CapHILIC system is particularly suitable for analyses of a less broad metabolite spectrum, and specifically optimized chromatography.
    Keywords:  Hydrophilic interaction chromatography; LC miniaturization; LC-MS; Metabolomics; Platform comparison; Q-TOF
    DOI:  https://doi.org/10.1016/j.talanta.2023.124578
  8. Proteomics. 2023 May 05. e2200278
    Integration of data-independent acquisition (DIA) with co-fractionation mass spectrometry (CF-MS) to enhance interactome mapping capabilities.
    Brenna N Hay, Mopelola O Akinlaja, Teesha C Baker, Aicha Asma Houfani, R Greg Stacey, Leonard J Foster.
      Proteomics technologies are continually advancing, providing opportunities to develop stronger and more robust protein interaction networks (PINs). In part, this is due to the ever-growing number of high-throughput proteomics methods that are available. This review discusses how data-independent acquisition (DIA) and co-fractionation mass spectrometry (CF-MS) can be integrated to enhance interactome mapping abilities. Furthermore, integrating these two techniques can improve data quality and network generation through extended protein coverage, less missing data, and reduced noise. CF-DIA-MS shows promise in expanding our knowledge of interactomes, notably for non-model organisms (NMOs). CF-MS is a valuable technique on its own, but upon the integration of DIA, the potential to develop robust PINs increases, offering a unique approach for researchers to gain an in-depth understanding into the dynamics of numerous biological processes.
    Keywords:  co-fractionation mass spectrometry (CF-MS); data-independent acquisition (DIA); interactomics; protein interaction networks (PINs); protein-protein interactions (PPIs)
    DOI:  https://doi.org/10.1002/pmic.202200278
  9. Anal Chem. 2023 May 05.
    Regions of Interest Multivariate Curve Resolution Liquid Chromatography with Data-Independent Acquisition Tandem Mass Spectrometry.
    Carlos Pérez-López, Bernat Oró-Nolla, Silvia Lacorte, Romà Tauler.
      New data-independent acquisition (DIA) modes coupled to chromatographic separations are opening new perspectives in the processing of massive mass spectrometric (MS) data using chemometric methods. In this work, the application of the regions of interest multivariate curve resolution (ROIMCR) method is shown for the simultaneous analysis of MS1 and MS2 DIA raw data obtained by liquid chromatography coupled to quadrupole-time-of-flight MS analysis. The ROIMCR method proposed in this work relies on the intrinsic bilinear structure of the MS1 and MS2 experimental data which allows us for the fast direct resolution of the elution and spectral profiles of all sample constituents giving measurable MS signals, without needing any further data pretreatment such as peak matching, alignment, or modeling. Compound annotation and identification can be achieved directly by the comparison of the ROIMCR-resolved MS1 and MS2 spectra with those from standards or from mass spectral libraries. ROIMCR elution profiles of the resolved components can be used to build calibration curves for the prediction of their concentrations in complex unknown samples. The application of the proposed procedure is shown for the analysis of mixtures of per- and polyfluoroalkyl substances in standard mixtures, spiked hen eggs, and gull egg samples, where these compounds tend to accumulate.
    DOI:  https://doi.org/10.1021/acs.analchem.2c05704
  10. Livers. 2022 Dec;2(4): 243-257
    One Carbon Metabolism and S-Adenosylmethionine in Non-Alcoholic Fatty Liver Disease Pathogenesis and Subtypes.
    David Fernández-Ramos, Fernando Lopitz-Otsoa, Oscar Millet, Cristina Alonso, Shelly C Lu, José M Mato.
      One carbon metabolism (1CM) can be defined as the transfer of a carbon unit from one metabolite to another and its replenishment by different sources of labile methyl-group nutrients: primarily choline, methionine, betaine, and serine. This flow of carbon units allows the biosynthesis of nucleotides, amino acids, formylated methionyl-tRNA, polyamines, glutathione, phospholipids, detoxification reactions, maintenance of the redox status and the concentration of NAD, and methylation reactions including epigenetic modifications. That is, 1CM functions as a nutrient sensor and integrator of cellular metabolism. A critical process in 1CM is the synthesis of S-adenosylmethionine (SAMe), the source of essentially all the hundreds of millions of daily methyl transfer reactions in a cell. This versatility of SAMe imposes a tight control in its synthesis and catabolism. Much of our knowledge concerning 1CM has been gained from studies in the production and prevention of nonalcoholic fatty liver disease (NAFLD). Here, we discuss in detail the function of the most important enzymes for their quantitative contribution to maintaining the flux of carbon units through 1CM in the liver and discuss how alterations in their enzymatic activity contribute to the development of NAFLD. Next, we discuss NAFLD subtypes based on serum lipidomic profiles with different risk of cardiovascular disease. Among the latter, we highlight the so-called subtype A for its serum lipidomic profile phenocopying that of mice deficient in SAMe synthesis and because its high frequency (about 50% of the NAFLD patients).
    Keywords:  S-adenosylmethionine; lipidomics; non-alcoholic fatty liver disease subtypes
    DOI:  https://doi.org/10.3390/livers2040020
  11. Cell Commun Signal. 2023 May 01. 21(1): 87
    Amino acid metabolism regulated by lncRNAs: the propellant behind cancer metabolic reprogramming.
    Qifan Hu, Yutong Li, Dan Li, Yi Yuan, Keru Wang, Lu Yao, Zhujun Cheng, Tianyu Han.
      Metabolic reprogramming is one of the main characteristics of cancer cells and plays pivotal role in the proliferation and survival of cancer cells. Amino acid is one of the key nutrients for cancer cells and many studies have focused on the regulation of amino acid metabolism, including the genetic alteration, epigenetic modification, transcription, translation and post-translational modification of key enzymes in amino acid metabolism. Long non-coding RNAs (lncRNAs) are composed of a heterogeneous group of RNAs with transcripts of more than 200 nucleotides in length. LncRNAs can bind to biological molecules such as DNA, RNA and protein, regulating the transcription, translation and post-translational modification of target genes. Now, the functions of lncRNAs in cancer metabolism have aroused great research interest and significant progress has been made. This review focuses on how lncRNAs participate in the reprogramming of amino acid metabolism in cancer cells, especially glutamine, serine, arginine, aspartate, cysteine metabolism. This will help us to better understand the regulatory mechanism of cancer metabolic reprogramming and provide new ideas for the development of anti-cancer drugs. Video Abstract.
    Keywords:  Amino acid metabolism; Cancer; Long non-coding RNA; Metabolic reprogramming
    DOI:  https://doi.org/10.1186/s12964-023-01116-1
  12. Oncotarget. 2023 May 04. 14 419-425
    Targeting cellular respiration as a therapeutic strategy in glioblastoma.
    Enyuan Shang, Trang Thi Thu Nguyen, Mike-Andrew Westhoff, Georg Karpel-Massler, Markus D Siegelin.
      While glycolysis is abundant in malignancies, mitochondrial metabolism is significant as well. Mitochondria harbor the enzymes relevant for cellular respiration, which is a critical pathway for both regeneration of reduction equivalents and energy production in the form of ATP. The oxidation of NADH2 and FADH2 are fundamental since NAD and FAD are the key components of the TCA-cycle that is critical to entertain biosynthesis in cancer cells. The TCA-cycle itself is predominantly fueled through carbons from glucose, glutamine, fatty acids and lactate. Targeting mitochondrial energy metabolism appears feasible through several drug compounds that activate the CLPP protein or interfere with NADH-dehydrogenase, pyruvate-dehydrogenase, enzymes of the TCA-cycle and mitochondrial matrix chaperones. While these compounds have demonstrated anti-cancer effects in vivo, recent research suggests which patients most likely benefit from such treatments. Here, we provide a brief overview of the status quo of targeting mitochondrial energy metabolism in glioblastoma and highlight a novel combination therapy.
    Keywords:  carbon tracing; central carbon metabolism; glioblastoma; lactate; metabolism
    DOI:  https://doi.org/10.18632/oncotarget.28424
  13. Sci Rep. 2023 Apr 29. 13(1): 7056
    Mzion enables deep and precise identification of peptides in data-dependent acquisition proteomics.
    Qiang Zhang.
      Sensitive and reliable identification of proteins and peptides pertains the basis of proteomics. We introduce Mzion, a new database search tool for data-dependent acquisition (DDA) proteomics. Our tool utilizes an intensity tally strategy and achieves generally a higher performance in terms of depth and precision across 20 datasets, ranging from large-scale to single-cell proteomics. Compared to several other search engines, Mzion matches on average 20% more peptide spectra at tryptic enzymatic specificity and 80% more at no enzymatic specificity from six large-scale, global datasets. Mzion also identifies more phosphopeptide spectra that can be explained by fewer proteins, demonstrated by six large-scale, local datasets corresponding to the global data. Our findings highlight the potential of Mzion for improving proteomic analysis and advancing our understanding of protein biology.
    DOI:  https://doi.org/10.1038/s41598-023-34323-4
  14. Biomark Res. 2023 May 05. 11(1): 48
    Targeting serine-glycine-one-carbon metabolism as a vulnerability in cancers.
    Wei Sun, Ruochen Liu, Xinyue Gao, Zini Lin, Hongao Tang, Hongjuan Cui, Erhu Zhao.
      The serine-glycine-one-carbon (SGOC) metabolic pathway is critical for DNA methylation, histone methylation, and redox homeostasis, in addition to protein, lipid, and nucleotide biosynthesis. The SGOC pathway is a crucial metabolic network in tumorigenesis, wherein the outputs are required for cell survival and proliferation and are particularly likely to be co-opted by aggressive cancers. SGOC metabolism provides an integration point in cell metabolism and is of crucial clinical significance. The mechanism of how this network is regulated is the key to understanding tumor heterogeneity and overcoming the potential mechanism of tumor recurrence. Herein, we review the role of SGOC metabolism in cancer by focusing on key enzymes with tumor-promoting functions and important products with physiological significance in tumorigenesis. In addition, we introduce the ways in which cancer cells acquire and use one-carbon unit, and discuss the recently clarified role of SGOC metabolic enzymes in tumorigenesis and development, as well as their relationship with cancer immunotherapy and ferroptosis. The targeting of SGOC metabolism may be a potential therapeutic strategy to improve clinical outcomes in cancers.
    Keywords:  Ferroptosis; Immunotherapy; Metabolic enzyme inhibitors; Serine-glycine-one-carbon metabolism; Vulnerability
    DOI:  https://doi.org/10.1186/s40364-023-00487-4
  15. Nat Biomed Eng. 2023 May 01.
    Peptide-encoding mRNA barcodes for the high-throughput in vivo screening of libraries of lipid nanoparticles for mRNA delivery.
    Luke H Rhym, Rajith S Manan, Antonius Koller, Georgina Stephanie, Daniel G Anderson.
      Developing safe and effective nanoparticles for the delivery of messenger RNA (mRNA) is slow and expensive, partly due to the lack of predictive power of in vitro screening methods and the low-throughput nature of in vivo screening. While DNA barcoding and batch analysis present methods for increasing in vivo screening throughput, they can also result in incomplete or misleading measures of efficacy. Here, we describe a high-throughput and accurate method for the screening of pooled nanoparticle formulations within the same animal. The method uses liquid chromatography with tandem mass spectrometry to detect peptide barcodes translated from mRNAs in nanoparticle-transfected cells. We show the method's applicability by evaluating a library of over 400 nanoparticle formulations with 384 unique ionizable lipids using only nine mice to optimize the formulation of a biodegradable lipid nanoparticle for mRNA delivery to the liver. Barcoding lipid nanoparticles with peptide-encoding mRNAs may facilitate the rapid development of nanoparticles for mRNA delivery to specific cells and tissues.
    DOI:  https://doi.org/10.1038/s41551-023-01030-4
  16. Front Oncol. 2023 ;13 1164266
    Metabonomic analysis of tumor microenvironments: a mini-review.
    Zeng Zeng, Cong-Xian Chen.
      Metabolomic analysis is a vital part of studying cancer progression. Metabonomic crosstalk, such as nutrient availability, physicochemical transformation, and intercellular interactions can affect tumor metabolism. Many original studies have demonstrated that metabolomics is important in some aspects of tumor metabolism. In this mini-review, we summarize the definition of metabolomics and how it can help change a tumor microenvironment, especially in pathways of three metabonomic tumors. Just as non-invasive biofluids have been identified as early biomarkers of tumor development, metabolomics can also predict differences in tumor drug response, drug resistance, and efficacy. Therefore, metabolomics is important for tumor metabolism and how it can affect oncology drugs in cancer therapy.
    Keywords:  drug resistance; metabolism; metabolomic; metabonomic; tumor
    DOI:  https://doi.org/10.3389/fonc.2023.1164266
  17. Curr Res Food Sci. 2023 ;6 100503
    Quantitative lipidomics analysis of changes in egg yolk lipids during spray-drying and subsequent accelerated storage.
    Wei Luo, Xialei Liu, Beibei Wang, Di Wu, Jinqiu Wang, Fang Geng.
      Egg yolks are rich in lipids that are easily altered during processing and storage. In this study, a liquid chromatography-tandem mass spectrometry strategy was used for quantitative lipidomics analysis of egg yolk after spray-drying processing and accelerated storage. Spray-drying treatment caused lipid oxidation (especially the oxidation of free fatty acids), potential hydrolysis of phospholipids, and alteration of the form of certain polyunsaturated fatty acids (docosahexaenoic acid, eicosapentaenoic acid, linolenic acid, and eicosatetraenoic acid) in egg yolk. These lipid alterations caused by the spray-drying process were further aggravated by the accelerated storage process. In detail, following storage, the abundance of free fatty acids, phosphatidic acid and phosphatidylethanolamine decreased further; and the abundance of polyunsaturated fatty acids in the form of triglycerides increased significantly. These results provide new insight into the mechanism underlying egg yolk property changes during spray-drying and storage, and offer valuable reference data for egg yolk powder promotion and application in food processing.
    Keywords:  Egg yolk; Lipid oxidation; Phospholipids; Spray-drying; Storage
    DOI:  https://doi.org/10.1016/j.crfs.2023.100503
  18. Biosci Rep. 2023 May 03. pii: BSR20222496. [Epub ahead of print]
    Kinetic data for modeling the dynamics of the enzymes involved in animal fatty acid synthesis.
    Chilperic Armel Foko Kuate, Oliver Ebenhöh, Barbara Marleen Bakker, Adélaïde Raguin.
      The synthesis and modification of fatty acids from carbohydrates are paramount for the production of lipids. Simultaneously, lipids are pivotal energy storage in human health. They are associated with various metabolic diseases and their production pathways are for instance candidate therapeutic targets for cancer treatments. The fatty acid de novo synthesis (FADNS) occurs in the cytoplasm, while the microsomal modification of fatty acids (MMFA) happens at the surface of the endoplasmic reticulum. The kinetics and regulation of these complex processes involve several enzymes. In mammals, those are the acetyl-CoA carboxylase (ACC), the fatty acid synthase (FAS), the very-long-chain fatty acid elongases (ELOVL 1-7), and the desaturases (delta family). Their mechanisms and expression in different organs have been studied for more than 50 years. However, modeling them in the context of complex metabolic pathways is still a challenge. Distinct modeling approaches can be implemented. Here we focus on dynamic modeling using ordinary differential equations based on kinetic rate laws. This requires a combination of knowledge on the enzymatic mechanisms and their kinetics, as well as the interactions between the metabolites, and between enzymes and metabolites. In this review, after recalling the modeling framework, we support the development of such a mathematical approach by reviewing the available kinetic information of the enzymes involved.
    Keywords:  Enzyme kinetics; Fatty acid synthesis; Mathematical modeling; Metabolism
    DOI:  https://doi.org/10.1042/BSR20222496
  19. Nat Commun. 2023 04 29. 14(1): 2485
    Single-cell metabolic fingerprints discover a cluster of circulating tumor cells with distinct metastatic potential.
    Wenjun Zhang, Feifei Xu, Jiang Yao, Changfei Mao, Mingchen Zhu, Moting Qian, Jun Hu, Huilin Zhong, Junsheng Zhou, Xiaoyu Shi, Yun Chen.
      Circulating tumor cells (CTCs) are recognized as direct seeds of metastasis. However, CTC count may not be the "best" indicator of metastatic risk because their heterogeneity is generally neglected. In this study, we develop a molecular typing system to predict colorectal cancer metastasis potential based on the metabolic fingerprints of single CTCs. After identification of the metabolites potentially related to metastasis using mass spectrometry-based untargeted metabolomics, setup of a home-built single-cell quantitative mass spectrometric platform for target metabolite analysis in individual CTCs and use of a machine learning method composed of non-negative matrix factorization and logistic regression, CTCs are divided into two subgroups, C1 and C2, based on a 4-metabolite fingerprint. Both in vitro and in vivo experiments demonstrate that CTC count in C2 subgroup is closely associated with metastasis incidence. This is an interesting report on the presence of a specific population of CTCs with distinct metastatic potential at the single-cell metabolite level.
    DOI:  https://doi.org/10.1038/s41467-023-38009-3
  20. Proc Natl Acad Sci U S A. 2023 May 09. 120(19): e2222081120
    High sensitivity top-down proteomics captures single muscle cell heterogeneity in large proteoforms.
    Jake A Melby, Kyle A Brown, Zachery R Gregorich, David S Roberts, Emily A Chapman, Lauren E Ehlers, Zhan Gao, Eli J Larson, Yutong Jin, Justin R Lopez, Jared Hartung, Yanlong Zhu, Sean J McIlwain, Daojing Wang, Wei Guo, Gary M Diffee, Ying Ge.
      Single-cell proteomics has emerged as a powerful method to characterize cellular phenotypic heterogeneity and the cell-specific functional networks underlying biological processes. However, significant challenges remain in single-cell proteomics for the analysis of proteoforms arising from genetic mutations, alternative splicing, and post-translational modifications. Herein, we have developed a highly sensitive functionally integrated top-down proteomics method for the comprehensive analysis of proteoforms from single cells. We applied this method to single muscle fibers (SMFs) to resolve their heterogeneous functional and proteomic properties at the single-cell level. Notably, we have detected single-cell heterogeneity in large proteoforms (>200 kDa) from the SMFs. Using SMFs obtained from three functionally distinct muscles, we found fiber-to-fiber heterogeneity among the sarcomeric proteoforms which can be related to the functional heterogeneity. Importantly, we detected multiple isoforms of myosin heavy chain (~223 kDa), a motor protein that drives muscle contraction, with high reproducibility to enable the classification of individual fiber types. This study reveals single muscle cell heterogeneity in large proteoforms and establishes a direct relationship between sarcomeric proteoforms and muscle fiber types, highlighting the potential of top-down proteomics for uncovering the molecular underpinnings of cell-to-cell variation in complex systems.
    Keywords:  mass spectrometry; proteoform; proteomics; single cell; single muscle fiber
    DOI:  https://doi.org/10.1073/pnas.2222081120
This page is being maintained by Thomas Krichel. It was last updated on 2024‒12‒09 at 5:53.