bims-mascan Biomed News
on Mass spectrometry in cancer research
Issue of 2023–12–10
fiveteen papers selected by
Giovanny Rodriguez Blanco, University of Edinburgh
  1. MultiPro: DDA-PASEF and diaPASEF acquired cell line proteomic datasets with deliberate batch effects.
  2. IMBAS-MS discovers organ-specific HLA peptide patterns in plasma.
  3. Current Practices in LC-MS Untargeted Metabolomics: A Scoping Review on the Use of Pooled Quality Control Samples.
  4. Interfacial Electromigration for Analysis of Biofluid Lipids in Small Volumes.
  5. Development of targeted hydrophilic interaction liquid chromatography-tandem mass spectrometry method for acyl-Coenzyme A covering short- to long-chain species in a single analytical run.
  6. SCD1 is the critical signaling hub to mediate metabolic diseases: Mechanism and the development of its inhibitors.
  7. Application of Skyline software for detecting prohibited substances in doping control analysis.
  8. Deep Learning-Enabled MS/MS Spectrum Prediction Facilitates Automated Identification Of Novel Psychoactive Substances.
  9. Targeting dysregulated lipid metabolism in the tumor microenvironment.
  10. Recent advances in immunopeptidomic-based tumor neoantigen discovery.
  11. One-Hour Phosphoproteome Analysis with the Orbitrap Astral Mass Spectrometer.
  12. Data independent acquisition for gas chromatographic MS/MS analysis of volatile compounds.
  13. Energy metabolic reprogramming regulates programmed cell death of renal tubular epithelial cells and might serve as a new therapeutic target for acute kidney injury.
  14. Protocol for quantitative proteomic analysis of heterogeneous adipose tissue-residing progenitor subpopulations in mice.
  15. Multi-Omics Analysis Reveals Sphingomyelin Accumulation, Glycerolipids Loss, and Disorders of Lipid Metabolism Regulated by Leucine Deprivation in the Liver of Mice.
  1. Sci Data. 2023 Dec 02. 10(1): 858
    MultiPro: DDA-PASEF and diaPASEF acquired cell line proteomic datasets with deliberate batch effects.
    He Wang, Kai Peng Lim, Weijia Kong, Huanhuan Gao, Bertrand Jern Han Wong, Ser Xian Phua, Tiannan Guo, Wilson Wen Bin Goh.
      Mass spectrometry-based proteomics plays a critical role in current biological and clinical research. Technical issues like data integration, missing value imputation, batch effect correction and the exploration of inter-connections amongst these technical issues, can produce errors but are not well studied. Although proteomic technologies have improved significantly in recent years, this alone cannot resolve these issues. What is needed are better algorithms and data processing knowledge. But to obtain these, we need appropriate proteomics datasets for exploration, investigation, and benchmarking. To meet this need, we developed MultiPro (Multi-purpose Proteome Resource), a resource comprising four comprehensive large-scale proteomics datasets with deliberate batch effects using the latest parallel accumulation-serial fragmentation in both Data-Dependent Acquisition (DDA) and Data Independent Acquisition (DIA) modes. Each dataset contains a balanced two-class design based on well-characterized and widely studied cell lines (A549 vs K562 or HCC1806 vs HS578T) with 48 or 36 biological and technical replicates altogether, allowing for investigation of a multitude of technical issues. These datasets allow for investigation of inter-connections between class and batch factors, or to develop approaches to compare and integrate data from DDA and DIA platforms.
    DOI:  https://doi.org/10.1038/s41597-023-02779-8
  2. Mol Cell Proteomics. 2023 Dec 01. pii: S1535-9476(23)00200-1. [Epub ahead of print] 100689
    IMBAS-MS discovers organ-specific HLA peptide patterns in plasma.
    Maria Wahle, Marvin Thielert, Maximilian Zwiebel, Patricia Skowronek, Wen-Feng Zeng, Matthias Mann.
      Distinction of non-self from self is the major task of the immune system. Immunopeptidomics studies the peptide repertoire presented by the human leukocyte antigen (HLA) protein, usually on tissues. However, HLA peptides are also bound to plasma soluble HLA (sHLA), but little is known about their origin and potential for biomarker discovery in this readily available biofluid. Currently, immunopeptidomics is hampered by complex workflows and limited sensitivity, typically requiring several mL of plasma. Here, we take advantage of recent improvements in the throughput and sensitivity of mass spectrometry (MS)-based proteomics to develop a highly-sensitive, automated and economical workflow for HLA peptide analysis, termed Immunopeptidomics by Biotinylated Antibodies and Streptavidin (IMBAS). IMBAS-MS quantifies more than 5,000 HLA class I peptides from only 200 μL of plasma, in just 30 minutes. Our technology revealed that the plasma immunopeptidome of healthy donors is remarkably stable throughout a year and strongly correlated between individuals with overlapping HLA types. Immunopeptides originating from diverse tissues, including the brain, are proportionately represented. We conclude that sHLAs are a promising avenue for immunology and potentially for precision oncology.
    Keywords:  HLA; IMBAS-MS; immunopeptidomics; plasma immunopeptidomics; sHLA
    DOI:  https://doi.org/10.1016/j.mcpro.2023.100689
  3. Anal Chem. 2023 Dec 06.
    Current Practices in LC-MS Untargeted Metabolomics: A Scoping Review on the Use of Pooled Quality Control Samples.
    Corey D Broeckling, Richard D Beger, Leo L Cheng, Raquel Cumeras, Daniel J Cuthbertson, Surendra Dasari, W Clay Davis, Warwick B Dunn, Anne Marie Evans, Alvaro Fernández-Ochoa, Helen Gika, Royston Goodacre, Kelli D Goodman, Goncalo J Gouveia, Ping-Ching Hsu, Jennifer A Kirwan, Dritan Kodra, Julia Kuligowski, Renny Shang-Lun Lan, María Eugenia Monge, Laura W Moussa, Sindhu G Nair, Nichole Reisdorph, Stacy D Sherrod, Candice Ulmer Holland, Dajana Vuckovic, Li-Rong Yu, Bo Zhang, Georgios Theodoridis, Jonathan D Mosley.
      Untargeted metabolomics is an analytical approach with numerous applications serving as an effective metabolic phenotyping platform to characterize small molecules within a biological system. Data quality can be challenging to evaluate and demonstrate in metabolomics experiments. This has driven the use of pooled quality control (QC) samples for monitoring and, if necessary, correcting for analytical variance introduced during sample preparation and data acquisition stages. Described herein is a scoping literature review detailing the use of pooled QC samples in published untargeted liquid chromatography-mass spectrometry (LC-MS) based metabolomics studies. A literature query was performed, the list of papers was filtered, and suitable articles were randomly sampled. In total, 109 papers were each reviewed by at least five reviewers, answering predefined questions surrounding the use of pooled quality control samples. The results of the review indicate that use of pooled QC samples has been relatively widely adopted by the metabolomics community and that it is used at a similar frequency across biological taxa and sample types in both small- and large-scale studies. However, while many studies generated and analyzed pooled QC samples, relatively few reported the use of pooled QC samples to improve data quality. This demonstrates a clear opportunity for the field to more frequently utilize pooled QC samples for quality reporting, feature filtering, analytical drift correction, and metabolite annotation. Additionally, our survey approach enabled us to assess the ambiguity in the reporting of the methods used to describe the generation and use of pooled QC samples. This analysis indicates that many details of the QC framework are missing or unclear, limiting the reader's ability to determine which QC steps have been taken. Collectively, these results capture the current state of pooled QC sample usage and highlight existing strengths and deficiencies as they are applied in untargeted LC-MS metabolomics.
    DOI:  https://doi.org/10.1021/acs.analchem.3c02924
  4. Anal Chem. 2023 Dec 04.
    Interfacial Electromigration for Analysis of Biofluid Lipids in Small Volumes.
    Madison E Edwards, Dallas P Freitas, Erin A Hirtzel, Nicholas White, Hongying Wang, Laurie A Davidson, Robert S Chapkin, Yuxiang Sun, Xin Yan.
      Lipids are important biomarkers within the field of disease diagnostics and can serve as indicators of disease progression and predictors of treatment effectiveness. Although lipids can provide important insight into how diseases initiate and progress, mass spectrometric methods for lipid characterization and profiling are limited due to lipid structural diversity, particularly the presence of various lipid isomers. Moreover, the difficulty of handling small-volume samples exacerbates the intricacies of biological analyses. In this work, we have developed a strategy that electromigrates a thin film of a small-volume biological sample directly to the air-liquid interface formed at the tip of a theta capillary. Importantly, we seamlessly integrated in situ biological lipid extraction with accelerated chemical derivatization, enabled by the air-liquid interface, and conducted isomeric structural characterization within a unified platform utilizing theta capillary nanoelectrospray ionization mass spectrometry, all tailored for small-volume sample analysis. We applied this unified platform to the analysis of lipids from small-volume human plasma and Alzheimer's disease mouse serum samples. Accelerated electro-epoxidation of unsaturated lipids at the interface allowed us to characterize lipid double-bond positional isomers. The unique application of electromigration of a thin film to the air-liquid interface in combination with accelerated interfacial reactions holds great potential in small-volume sample analysis for disease diagnosis and prevention.
    DOI:  https://doi.org/10.1021/acs.analchem.3c04309
  5. J Chromatogr A. 2023 Nov 27. pii: S0021-9673(23)00749-5. [Epub ahead of print]1714 464524
    Development of targeted hydrophilic interaction liquid chromatography-tandem mass spectrometry method for acyl-Coenzyme A covering short- to long-chain species in a single analytical run.
    Madhulika Singh, Ligia Akemi Kiyuna, Christoff Odendaal, Barbara M Bakker, Amy C Harms, Thomas Hankemeier.
      Acyl-CoAs play a significant role in numerous physiological and metabolic processes making it important to assess their concentration levels for evaluating metabolic health. Considering the important role of acyl-CoAs, it is crucial to develop an analytical method that can analyze these compounds. Due to the structural variations of acyl-CoAs, multiple analytical methods are often required for comprehensive analysis of these compounds, which increases complexity and the analysis time. In this study, we have developed a method using a zwitterionic HILIC column that enables the coverage of free CoA and short- to long-chain acyl-CoA species in one analytical run. Initially, we developed the method using an LC-QTOF instrument for the identification of acyl-CoA species and optimizing their chromatography. Later, a targeted HILIC-MS/MS method was created in scheduled multiple reaction monitoring mode using a QTRAP MS detector. The performance of the method was evaluated based on various parameters such as linearity, precision, recovery and matrix effect. This method was applied to identify the difference in acyl-CoA profiles in HepG2 cells cultured in different conditions. Our findings revealed an increase in levels of acetyl-CoA, medium- and long-chain acyl-CoA while a decrease in the profiles of free CoA in the starved state, indicating a clear alteration in the fatty acid oxidation process.
    Keywords:  Acyl-CoA; Biomarker; HILIC; HepG2; LC-MS
    DOI:  https://doi.org/10.1016/j.chroma.2023.464524
  6. Biomed Pharmacother. 2023 Nov 30. pii: S0753-3322(23)01384-7. [Epub ahead of print]170 115586
    SCD1 is the critical signaling hub to mediate metabolic diseases: Mechanism and the development of its inhibitors.
    Qin Sun, Xiaorui Xing, Huanyu Wang, Kang Wan, Ruobing Fan, Cheng Liu, Yongjian Wang, Wenyi Wu, Yibing Wang, Ru Wang.
      Metabolic diseases, featured with dysregulated energy homeostasis, have become major global health challenges. Patients with metabolic diseases have high probability to manifest multiple complications in lipid metabolism, e.g. obesity, insulin resistance and fatty liver. Therefore, targeting the hub genes in lipid metabolism may systemically ameliorate the metabolic diseases, along with the complications. Stearoyl-CoA desaturase 1(SCD1) is a key enzyme that desaturates the saturated fatty acids (SFAs) derived from de novo lipogenesis or diet to generate monounsaturated fatty acids (MUFAs). SCD1 maintains the metabolic and tissue homeostasis by responding to, and integrating the multiple layers of endogenous stimuli, which is mediated by the synthesized MUFAs. It critically regulates a myriad of physiological processes, including energy homeostasis, development, autophagy, tumorigenesis and inflammation. Aberrant transcriptional and epigenetic activation of SCD1 regulates AMPK/ACC, SIRT1/PGC1α, NcDase/Wnt, etc, and causes aberrant lipid accumulation, thereby promoting the progression of obesity, non-alcoholic fatty liver, diabetes and cancer. This review critically assesses the integrative mechanisms of the (patho)physiological functions of SCD1 in metabolic homeostasis, inflammation and autophagy. For translational perspective, potent SCD1 inhibitors have been developed to treat various types of cancer. We thus discuss the multidisciplinary advances that greatly accelerate the development of SCD1 new inhibitors. In conclusion, besides cancer treatment, SCD1 may serve as the promising target to combat multiple metabolic complications simultaneously.
    Keywords:  Metabolic diseases; Metabolic homeostasis; Monounsaturated fatty acids; Saturated fatty acids; Stearoyl-CoA desaturase 1
    DOI:  https://doi.org/10.1016/j.biopha.2023.115586
  7. PLoS One. 2023 ;18(12): e0295065
    Application of Skyline software for detecting prohibited substances in doping control analysis.
    Hyeon-Jeong Lee, Mijin Jeon, Yoondam Seo, Inseon Kang, Wooyeon Jeong, Junghyun Son, Eugene C Yi, Hophil Min.
      As the number of prohibited drugs has been progressively increasing and analytical methods for detecting such substances are renewed continuously for doping control, the need for more sensitive and accurate doping analysis has increased. To address the urgent need for high throughput and accurate analysis, liquid chromatography with tandem mass spectrometry is actively utilized in case of most of the newly designated prohibited substances. However, because all mass spectrometer vendors provide data processing software that is incapable of handling other instrumental data, it is difficult to cover all doping analysis procedures, from method development to result reporting, on one platform. Skyline is an open-source and vendor-neutral software program invented for the method development and data processing of targeted proteomics. Recently, the utilization of Skyline has been expanding for the quantitative analysis of small molecules and lipids. Herein, we demonstrated Skyline as a simple platform for unifying overall doping control, including the optimization of analytical methods, monitoring of data quality, discovery of suspected doping samples, and validation of analytical methods for detecting newly prohibited substances. For method optimization, we selected the optimal collision energies for 339 prohibited substances. Notably, 195 substances exhibited a signal intensity increase of >110% compared with the signal intensity of the original collision energy. All data related to method validation and quantitative analysis were efficiently visualized, extracted, or calculated using Skyline. Moreover, a comparison of the time consumed and the number of suspicious samples screened in the initial test procedure highlighted the advantages of using Skyline over the commercially available software TraceFinder in doping control.
    DOI:  https://doi.org/10.1371/journal.pone.0295065
  8. Anal Chem. 2023 Dec 04.
    Deep Learning-Enabled MS/MS Spectrum Prediction Facilitates Automated Identification Of Novel Psychoactive Substances.
    Fei Wang, Daniel Pasin, Michael A Skinnider, Jaanus Liigand, Jan-Niklas Kleis, David Brown, Eponine Oler, Tanvir Sajed, Vasuk Gautam, Stephen Harrison, Russell Greiner, Leonard J Foster, Petur Weihe Dalsgaard, David S Wishart.
      The market for illicit drugs has been reshaped by the emergence of more than 1100 new psychoactive substances (NPS) over the past decade, posing a major challenge to the forensic and toxicological laboratories tasked with detecting and identifying them. Tandem mass spectrometry (MS/MS) is the primary method used to screen for NPS within seized materials or biological samples. The most contemporary workflows necessitate labor-intensive and expensive MS/MS reference standards, which may not be available for recently emerged NPS on the illicit market. Here, we present NPS-MS, a deep learning method capable of accurately predicting the MS/MS spectra of known and hypothesized NPS from their chemical structures alone. NPS-MS is trained by transfer learning from a generic MS/MS prediction model on a large data set of MS/MS spectra. We show that this approach enables a more accurate identification of NPS from experimentally acquired MS/MS spectra than any existing method. We demonstrate the application of NPS-MS to identify a novel derivative of phencyclidine (PCP) within an unknown powder seized in Denmark without the use of any reference standards. We anticipate that NPS-MS will allow forensic laboratories to identify more rapidly both known and newly emerging NPS. NPS-MS is available as a web server at https://nps-ms.ca/, which provides MS/MS spectra prediction capabilities for given NPS compounds. Additionally, it offers MS/MS spectra identification against a vast database comprising approximately 8.7 million predicted NPS compounds from DarkNPS and 24.5 million predicted ESI-QToF-MS/MS spectra for these compounds.
    DOI:  https://doi.org/10.1021/acs.analchem.3c02413
  9. Arch Pharm Res. 2023 Dec 07.
    Targeting dysregulated lipid metabolism in the tumor microenvironment.
    Do-Hee Kim, Na-Young Song, Hyungshin Yim.
      The reprogramming of lipid metabolism and its association with oncogenic signaling pathways within the tumor microenvironment (TME) have emerged as significant hallmarks of cancer. Lipid metabolism is defined as a complex set of molecular processes including lipid uptake, synthesis, transport, and degradation. The dysregulation of lipid metabolism is affected by enzymes and signaling molecules directly or indirectly involved in the lipid metabolic process. Regulation of lipid metabolizing enzymes has been shown to modulate cancer development and to avoid resistance to anticancer drugs in tumors and the TME. Because of this, understanding the metabolic reprogramming associated with oncogenic progression is important to develop strategies for cancer treatment. Recent advances provide insight into fundamental mechanisms and the connections between altered lipid metabolism and tumorigenesis. In this review, we explore alterations to lipid metabolism and the pivotal factors driving lipid metabolic reprogramming, which exacerbate cancer progression. We also shed light on the latest insights and current therapeutic approaches based on small molecular inhibitors and phytochemicals targeting lipid metabolism for cancer treatment. Further investigations are worthwhile to fully understand the underlying mechanisms and the correlation between altered lipid metabolism and carcinogenesis.
    Keywords:  Cholesterol transport; Lipid uptake; Lipogenesis; Lipolysis; Phytochemical; Tumor microenvironment
    DOI:  https://doi.org/10.1007/s12272-023-01473-y
  10. Adv Immunol. 2023 ;pii: S0065-2776(23)00031-7. [Epub ahead of print]160 1-36
    Recent advances in immunopeptidomic-based tumor neoantigen discovery.
    Wei Meng, Robert D Schreiber, Cheryl F Lichti.
      The role of aberrantly expressed proteins in tumors in driving immune-mediated control of cancer has been well documented for more than five decades. Today, we know that both aberrantly expressed normal proteins as well as mutant proteins (neoantigens) can function as tumor antigens in both humans and mice. Next-generation sequencing (NGS) and high-resolution mass spectrometry (MS) technologies have made significant advances since the early 2010s, enabling detection of rare but clinically relevant neoantigens recognized by T cells. MS profiling of tumor-specific immunopeptidomes remains the most direct method to identify mutant peptides bound to cellular MHC. However, the need for use of large numbers of cells or significant amounts of tumor tissue to achieve neoantigen detection has historically limited the application of MS. Newer, more sensitive MS technologies have recently demonstrated the capacities to detect neoantigens from fewer cells. Here, we highlight recent advancements in immunopeptidomics-based characterization of tumor-specific neoantigens. Various tumor antigen categories and neoantigen identification approaches are also discussed. Furthermore, we summarize recent reports that achieved successful tumor neoantigen detection by MS using a variety of starting materials, MS acquisition modes, and novel ion mobility devices.
    Keywords:  Immunogenomic; Immunopeptidomics; Ion mobility spectrometry; Mass spectrometry; Neoantigens; Tumor antigens
    DOI:  https://doi.org/10.1016/bs.ai.2023.10.001
  11. bioRxiv. 2023 Nov 21. pii: 2023.11.21.568149. [Epub ahead of print]
    One-Hour Phosphoproteome Analysis with the Orbitrap Astral Mass Spectrometer.
    Noah M Lancaster, Pavel Sinitcyn, Patrick Forny, Trenton M Peters-Clarke, Caroline Fecher, Andrew J Smith, Evgenia Shishkova, Tabiwang N Arrey, Anna Pashkova, Margaret Lea Robinson, Nicholas Arp, Jing Fan, Juli Hansen, Andrea Galmozzi, Lia R Serrano, Michael S Westphall, Hamish Stewart, Christian Hock, Eugen Damoc, David J Pagliarini, Vlad Zabrouskov, Joshua J Coon.
      As a key mechanism for cellular signal transduction, protein phosphorylation plays critical roles in myriad cellular processes. This modification, however, is highly dynamic and occurs at sub-stoichiometric levels. Mass spectrometry is an essential tool for studying this modification on a global scale; however, the technology's impact suffers from four main limitations: need for site localization, dynamic range, reproducibility, and throughput. Here we describe the use of a novel mass spectrometer (Orbitrap Astral) coupled with data-independent acquisition (DIA) to achieve detection of close to 40,000 unique phosphorylation sites within one hour of analysis. We applied this approach to generate a phosphoproteome atlas of the mouse. Altogether, we detected 81,120 unique phosphorylation sites within 12 hours of measurement. With this unique dataset, we examine the sequence and structural context of protein phosphorylation. Finally, we highlight the discovery potential of this resource with multiple examples of novel phosphorylation events relevant to mitochondrial and brain biology.
    DOI:  https://doi.org/10.1101/2023.11.21.568149
  12. J Chromatogr A. 2023 Nov 23. pii: S0021-9673(23)00752-5. [Epub ahead of print]1714 464527
    Data independent acquisition for gas chromatographic MS/MS analysis of volatile compounds.
    Premkamol Karapakdee, Prapin Wilairat, Sirirat Kokpol, Yada Nolvachai, Chadin Kulsing.
      This study presents a novel tandem mass spectrometry (MS/MS) approach utilizing a data independent acquisition (DIA) concept specifically designed with gas chromatography-electron ionization-triple quadrupole mass spectrometry (GC-EI-QqQMS). This allows compound identification based on comparison between all the experimental MS/MS product ion spectra and the simulated library data of >1,000 MS/MS transitions of 71 compounds. The simulation data were generated by using the Competitive Fragmentation Modeling (CFM-ID) 3.0 program. The approach for calculation of the DIA MS/MS library match scores was then established and applied for identification of a range of terpenoids and oxygenated compounds in perfume. The identity of each peak was confirmed using 4-241 MS/MS transitions. The established data collection and analysis methods are expected to be useful for increased confidence in volatile compound analysis.
    Keywords:  DIA-based MS/MS analysis on GC (DIMS/MS); Improved compound identification; Tandem mass spectrometry approach; Untargeted GC−MS/MS analysis; Volatile compound analysis
    DOI:  https://doi.org/10.1016/j.chroma.2023.464527
  13. Front Cell Dev Biol. 2023 ;11 1276217
    Energy metabolic reprogramming regulates programmed cell death of renal tubular epithelial cells and might serve as a new therapeutic target for acute kidney injury.
    Limei Zhao, Yajie Hao, Shuqin Tang, Xiutao Han, Rongshan Li, Xiaoshuang Zhou.
      Acute kidney injury (AKI) induces significant energy metabolic reprogramming in renal tubular epithelial cells (TECs), thereby altering lipid, glucose, and amino acid metabolism. The changes in lipid metabolism encompass not only the downregulation of fatty acid oxidation (FAO) but also changes in cell membrane lipids and triglycerides metabolism. Regarding glucose metabolism, AKI leads to increased glycolysis, activation of the pentose phosphate pathway (PPP), inhibition of gluconeogenesis, and upregulation of the polyol pathway. Research indicates that inhibiting glycolysis, promoting the PPP, and blocking the polyol pathway exhibit a protective effect on AKI-affected kidneys. Additionally, changes in amino acid metabolism, including branched-chain amino acids, glutamine, arginine, and tryptophan, play an important role in AKI progression. These metabolic changes are closely related to the programmed cell death of renal TECs, involving autophagy, apoptosis, necroptosis, pyroptosis, and ferroptosis. Notably, abnormal intracellular lipid accumulation can impede autophagic clearance, further exacerbating lipid accumulation and compromising autophagic function, forming a vicious cycle. Recent studies have demonstrated the potential of ameliorating AKI-induced kidney damage through calorie and dietary restriction. Consequently, modifying the energy metabolism of renal TECs and dietary patterns may be an effective strategy for AKI treatment.
    Keywords:  acute kidney injury; energy metabolism; programmed cell death; renal tubular epithelial cells; therapeutic
    DOI:  https://doi.org/10.3389/fcell.2023.1276217
  14. STAR Protoc. 2023 Dec 03. pii: S2666-1667(23)00643-3. [Epub ahead of print]4(4): 102676
    Protocol for quantitative proteomic analysis of heterogeneous adipose tissue-residing progenitor subpopulations in mice.
    Bo Shan, Clive S Barker, Harry Theraulaz, Xiaoli Zhang, Yan Ping, Rana K Gupta, Mengle Shao, Yibo Wu.
      Recent studies have revealed cellular heterogeneity of mesenchymal stromal cells and immune cells in adipose tissue and emphasized the need for quantitative analysis of small numbers of functionally distinct cells using state-of-the-art "omics" technologies. Here, we present an optimized protocol for precise protein quantification from minute amounts of samples. We describe steps for isolation of mouse adipose progenitor cells, proteomics sample preparation, mass spectrometry measurement, and computational analysis. This protocol can be adapted to other samples with limited amounts. For complete details on the use and execution of this protocol, please refer to Shan et al. (2022).1.
    Keywords:  Proteomics; Stem Cells; Systems Biology
    DOI:  https://doi.org/10.1016/j.xpro.2023.102676
  15. Mol Nutr Food Res. 2023 Dec 07. e2300567
    Multi-Omics Analysis Reveals Sphingomyelin Accumulation, Glycerolipids Loss, and Disorders of Lipid Metabolism Regulated by Leucine Deprivation in the Liver of Mice.
    Haonan Yu, Yaorong Niu, Xinyu Lei, Chunlin Xie, Xianghua Yan.
       SCOPE: Branched-chain amino acids, especially leucine, have been reported to play a role in regulating lipid metabolism. This study aims to examine the effects of leucine deprivation on hepatic lipid metabolism.
    METHODS AND RESULTS: C57BL/6 mice are fed with a chow diet (control group, n = 8) or a leucine-free diet (-Leu group, n = 8) for 7 days. Histology, lipidomics, targeted metabolomics, and transcriptomics are performed to analyze the liver tissue. Compared to control group, -Leu group exhibits a notably reduced liver weight, accompanied by hepatic injury, and disorders of lipid metabolism. The level of sphingomyelin (SM) is significantly increased in the liver of -Leu group, while the glycerolipids (GL) level is significantly decreased. The expression of sphingomyelin synthase 1 (SGMS1) is upregulated by leucine deprivation in a time-dependent manner, leading to hepatic SM accumulation. Moreover, leucine deprivation results in hepatic GL loss via suppressing fatty acid synthase (FASN) and acetyl-CoA carboxylase 1 (ACC1) expression.
    CONCLUSION: The findings demonstrate that leucine deprivation results in abnormal lipid metabolism in the liver, mainly manifested as SM accumulation and GL loss. These results provide insights into the role of leucine in regulating lipid metabolism.
    Keywords:  glycerolipids; leucine; lipid metabolism; multi-omics analysis; sphingomyelin
    DOI:  https://doi.org/10.1002/mnfr.202300567
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