bims-mascan Biomed News
on Mass spectrometry in cancer research
Issue of 2021‒11‒21
23 papers selected by
Giovanny Rodriguez Blanco
University of Edinburgh

  1. Biochim Biophys Acta Mol Cell Biol Lipids. 2021 Nov 15. pii: S1388-1981(21)00210-9. [Epub ahead of print] 159082
      Lung cancer represents one of the leading worldwide causes of cancer death, but the pathobiochemistry of this disease is still not fully understood. Here we characterize the lipidomic and metabolomic profiles of the tumor and surrounding normal tissues for 23 patients with non-small cell lung cancer. In total, 500 molecular species were identified and quantified by a combination of the lipidomic shotgun tandem mass spectrometry (MS/MS) analysis and the targeted metabolomic approach using liquid chromatography (LC) - MS/MS. The statistical evaluation includes multivariate and univariate methods with the emphasis on paired statistical approaches. Our research revealed significant changes in several biochemical pathways related to the central carbon metabolism, acylcarnitines, dipeptides as well as the disruption in the lipid metabolism observed mainly for glycerophospholipids, sphingolipids, and cholesteryl esters.
    Keywords:  Lipidomics; Lung cancer; Mass spectrometry; Metabolism; Metabolomics
  2. Methods Mol Biol. 2022 ;2396 175-186
      Lipids play an important role in the energy storage, cellular signaling, and pathophysiology of diseases such as cancer, neurodegenerative diseases, infections, and diabetes. Due to high importance of diverse lipid classes in human health and disease, manipulating lipid abundance and composition is an important target for metabolic engineering. The extreme structural diversity of lipids in real biological samples is challenging for analytical techniques due to large difference in physicochemical properties of individual lipid species. This chapter describes lipidomic analysis of large sample sets requiring reliable and robust methodology. Rapid and robust methods facilitate the support of longitudinal studies allowing the transfer of methodology between laboratories. We describe a high-throughput reversed-phase LC-MS methodology using Ultra Performance Liquid Chromatography (UPLC®) with charged surface hybrid technology and accurate mass detection for high-throughput non-targeted lipidomics. The methodology showed excellent specificity, robustness, and reproducibility for over 100 LC-MS injections.
    Keywords:  LC-MS; Non-targeted lipidomics
  3. Methods Mol Biol. 2022 ;2396 197-214
      Liquid chromatography-mass spectrometry (LC-MS) provides one of the most popular platforms for untargeted plant lipidomics analysis (Shulaev and Chapman, Biochim Biophys Acta 1862(8):786-791, 2017; Rupasinghe and Roessner, Methods Mol Biol 1778:125-135, 2018; Welti et al., Front Biosci 12:2494-506, 2007; Shiva et al., Plant Methods 14:14, 2018). We have developed SimLipid software in order to streamline the analysis of large-volume datasets generated by LC-MS-based untargeted lipidomics methods. SimLipid contains a customizable library of lipid species; graphical user interfaces (GUIs) for visualization of raw data; the identified lipid molecules and their associated mass spectra annotated with fragment ions and parent ions; and detailed information of each identified lipid species all in a single workbench enabling users to rapidly review the results by examining the data for confident identifications of lipid molecular species. In this chapter, we present the functionality of the software and workflow for automating large-scale LC-MS-based untargeted lipidomics profiling.
    Keywords:  Bioinformatics; Grapes; LC-MS; Lipid identification; Lipidomics
  4. Methods Mol Biol. 2022 ;2396 137-159
      Mass spectrometry (MS)-based metabolomics approaches have been used for characterizing the metabolite content and composition of biological samples in drug discovery and development, as well as in metabolic engineering, and food and plant sciences applications. Here, we describe a protocol routinely used in our laboratory to conduct a metabolic profiling of small polar metabolites from biological samples. Metabolites can be extracted from each sample using a methanol-based single-phase extraction procedure. The combination of LC-based hydrophilic interaction liquid chromatography (HILIC) and a hybrid quadrupole-time of flight (Q-ToF) mass spectrometer allows the comprehensive analysis of small polar metabolites including sugars, phosphorylated compounds, purines and pyrimidines, nucleotides, nucleosides, acylcarnitines, carboxylic acids, hydrophilic vitamins and amino acids. Retention times and accurate masses of metabolites involved in key metabolic pathways are annotated for routine high-throughput screening in both untargeted and targeted metabolomics analyses.
    Keywords:  HILIC; LC-MS; Mass spectrometry; Metabolomics; Polar metabolites; qTOF
  5. Lipids Health Dis. 2021 Nov 13. 20(1): 160
      BACKGROUND: The high drug resistance and metabolic reprogramming of clear cell renal cell carcinoma (ccRCC) are considered responsible for poor prognosis. In-depth research at multiple levels is urgently warranted to illustrate the lipid composition, distribution, and metabolic pathways of clinical ccRCC specimens.METHODS: In this project, a leading-edge targeted quantitative lipidomic study was conducted using 10 pairs of cancerous and adjacent normal tissues obtained from ccRCC patients. Accurate lipid quantification was performed according to a linear equation calculated using internal standards. Qualitative and quantitative analyses of lipids were performed with multiple reaction monitoring analysis based on ultra-performance liquid chromatography (UPLC) and mass spectrometry (MS). Additionally, a multivariate statistical analysis was performed using data obtained on lipids.
    RESULTS: A total of 28 lipid classes were identified. Among them, the most abundant were triacylglycerol (TG), diacylglycerol (DG), phosphatidylcholine (PC), and phosphatidylethanolamine (PE). Cholesteryl ester (CE) was the lipid exhibiting the most considerable difference between normal samples and tumor samples. Lipid content, chain length, and chain unsaturation of acylcarnitine (CAR), CE, and DG were found to be significantly increased. Based on screening for variable importance in projection scores ≥1, as well as fold change limits between 0.5 and 2, 160 differentially expressed lipids were identified. CE was found to be the most significantly upregulated lipid, while TG was observed to be the most significantly downregulated lipid.
    CONCLUSION: Based on the absolute quantitative analysis of lipids in ccRCC specimens, it was observed that the content and change trends varied in different lipid classes. Upregulation of CAR, CE, and DG was observed, and analysis of changes in the distribution helped clarify the causes of lipid accumulation in ccRCC and possible carcinogenic molecular mechanisms. The results and methods described herein provide a comprehensive analysis of ccRCC lipid metabolism and lay a theoretical foundation for cancer treatment.
    Keywords:  Clear cell renal cell carcinoma; Differentially expressed lipids; Lipid biomarker; Lipid metabolite; Lipid quantification; Lipidomics; Lipids; UPLC-MS/MS
  6. Front Cell Dev Biol. 2021 ;9 739392
      Ferroptosis is a recently recognized form of non-apoptotic regulated cell death and usually driven by iron-dependent lipid peroxidation and has arisen to play a significant role in cancer biology. Distinct from other types of cell death in morphology, genetics, and biochemistry, ferroptosis is characterized by the accumulation of lipid peroxides and lethal reactive oxygen species controlled by integrated oxidant and antioxidant systems. Increasing evidence indicates that a variety of biological processes, including amino acid, iron, lactate, and lipid metabolism, as well as glutathione, phospholipids, NADPH, and coenzyme Q10 biosynthesis, are closely related to ferroptosis sensitivity. Abnormal ferroptotic response may modulate cancer progression by reprogramming the tumor microenvironment (TME). The TME is widely associated with tumor occurrence because it is the carrier of tumor cells, which interacts with surrounding cells through the circulatory and the lymphatic system, thus influencing the development and progression of cancer. Furthermore, the metabolism processes play roles in maintaining the homeostasis and evolution of the TME. Here, this review focuses on the ferroptosis-mediated crosstalk in the TME, as well as discussing the novel therapeutic strategies for cancer treatment.
    Keywords:  cancer progress; ferroptosis; immunity; metabolism; tumor microenvironment
  7. Anal Chem. 2021 Nov 18.
      Untargeted metabolomics is an essential component of systems biology research, but it is plagued by a high proportion of detectable features not identified with a chemical structure. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) experiments produce spectra that can be searched against databases to help identify or classify these unknowns, but many features do not generate spectra of sufficient quality to enable successful annotation. Here, we explore alterations to gradient length, mass loading, and rolling precursor ion exclusion parameters for reversed phase liquid chromatography (RPLC) and hydrophilic interaction liquid chromatography (HILIC) that improve compound identification performance for human plasma samples. A manual review of spectral matches from the HILIC data set was used to determine reasonable thresholds for search score and other metrics to enable semi-automated MS/MS data analysis. Compared to typical LC-MS/MS conditions, methods adapted for compound identification increased the total number of unique metabolites that could be matched to a spectral database from 214 to 2052. Following data alignment, 68.0% of newly identified features from the modified conditions could be detected and quantitated using a routine 20-min LC-MS run. Finally, a localized machine learning model was developed to classify the remaining unknowns and select a subset that shared spectral characteristics with successfully identified features. A total of 576 and 749 unidentified features in the HILIC and RPLC data sets were classified by the model as high-priority unknowns or higher-importance targets for follow-up analysis. Overall, our study presents a simple strategy to more deeply annotate untargeted metabolomics data for a modest additional investment of time and sample.
  8. Nat Metab. 2021 Nov;3(11): 1500-1511
      Folate metabolism can be an effective target for cancer treatment. However, standard cell culture conditions utilize folic acid, a non-physiological folate source for most tissues. We find that the enzyme that couples folate and methionine metabolic cycles, methionine synthase, is required for cancer cell proliferation and tumour growth when 5-methyl tetrahydrofolate (THF), the major folate found in circulation, is the extracellular folate source. In such physiological conditions, methionine synthase incorporates 5-methyl THF into the folate cycle to maintain intracellular levels of the folates needed for nucleotide production. 5-methyl THF can sustain intracellular folate metabolism in the absence of folic acid. Therefore, cells exposed to 5-methyl THF are more resistant to methotrexate, an antifolate drug that specifically blocks folic acid incorporation into the folate cycle. Together, these data argue that the environmental folate source has a profound effect on folate metabolism, determining how both folate cycle enzymes and antifolate drugs impact proliferation.
  9. Nat Commun. 2021 Nov 18. 12(1): 6685
      Phosphoproteomics integrating data-independent acquisition (DIA) enables deep phosphoproteome profiling with improved quantification reproducibility and accuracy compared to data-dependent acquisition (DDA)-based phosphoproteomics. DIA data mining heavily relies on a spectral library that in most cases is built on DDA analysis of the same sample. Construction of this project-specific DDA library impairs the analytical throughput, limits the proteome coverage, and increases the sample size for DIA phosphoproteomics. Herein we introduce a deep neural network, DeepPhospho, which conceptually differs from previous deep learning models to achieve accurate predictions of LC-MS/MS data for phosphopeptides. By leveraging in silico libraries generated by DeepPhospho, we establish a DIA workflow for phosphoproteome profiling which involves DIA data acquisition and data mining with DeepPhospho predicted libraries, thus circumventing the need of DDA library construction. Our DeepPhospho-empowered workflow substantially expands the phosphoproteome coverage while maintaining high quantification performance, which leads to the discovery of more signaling pathways and regulated kinases in an EGF signaling study than the DDA library-based approach. DeepPhospho is provided as a web server as well as an offline app to facilitate user access to model training, predictions and library generation.
  10. Mol Cell Proteomics. 2021 Nov 15. pii: S1535-9476(21)00149-3. [Epub ahead of print] 100177
      Single cell transcriptomics has revolutionized our understanding of basic biology and disease. Since transcript levels often do not correlate with protein expression, it is crucial to complement transcriptomics approaches with proteome analyses at single cell resolution. Despite continuous technological improvements in sensitivity, mass spectrometry-based single cell proteomics ultimately faces the challenge of reproducibly comparing the protein expression profiles of thousands of individual cells. Here, we combine two hitherto opposing analytical strategies, DIA and Tandem-Mass-Tag (TMT)-multiplexing, to generate highly reproducible, quantitative proteome signatures from ultra-low input samples. We developed a novel, identification-independent proteomics data-analysis pipeline that allows to quantitatively compare DIA-TMT proteome signatures across hundreds of samples independent of their biological origin to identify cell types and single protein knockouts. These proteome signatures overcome the need to impute quantitative data due to accumulating detrimental amounts of missing data in standard multi-batch TMT experiments. We validate our approach using integrative data analysis of different human cell lines and standard database searches for knockouts of defined proteins. Our data establish a novel and reproducible approach to markedly expand the numbers of proteins one detects from ultra-low input samples.
  11. J Cell Sci. 2021 Nov 15. pii: jcs.258964. [Epub ahead of print]
      Insulin stimulates adipose tissue to extract fatty acids from circulation and sequester them inside adipose cells. How fatty acids are transported across the capillary endothelial barrier, or how this process is regulated, remains unclear. We modeled the relationship of adipocytes and endothelial cells in vitro to test the role of insulin in fatty acid transport. Treatment of endothelial cells with insulin did not affect endothelial fatty acid uptake, but endothelial cells took up more fatty acids when exposed to media conditioned by adipocytes treated with insulin. Manipulations of this conditioned media indicated that the secreted factor is a small, hydrophilic, non-proteinaceous metabolite. Factor activity was correlated with lactate concentration, and inhibition of lactate production in adipocytes abolished the activity. Finally, lactate alone was sufficient to increase endothelial uptake of both free fatty acids and lipids liberated from chylomicrons, and to promote trans-endothelial transport, at physiologically relevant concentrations. Together, these data suggest that insulin drives adipocytes to secrete lactate, which then acts in a paracrine fashion to promote fatty acid uptake and transport across the neighboring endothelial barrier.
    Keywords:  Adipose tissue; Endothelium; Fatty acids; Lactate; Paracrine
  12. Front Cardiovasc Med. 2021 ;8 757022
      Aortic dissection (AD) is a catastrophic cardiovascular emergency with a poor prognosis, and little preceding symptoms. Abnormal lipid metabolism is closely related to the pathogenesis of AD. However, comprehensive lipid alterations related to AD pathogenesis remain unclear. Moreover, there is an urgent need for new or better biomarkers for improved risk assessment and surveillance of AD. Therefore, an untargeted lipidomic approach based on ultra-high-performance liquid chromatograph-mass spectrometry was employed to unveil plasma lipidomic alterations and potential biomarkers for AD patients in this study. We found that 278 of 439 identified lipid species were significantly altered in AD patients (n = 35) compared to normal controls (n = 32). Notably, most lipid species, including fatty acids, acylcarnitines, cholesteryl ester, ceramides, hexosylceramides, sphingomyelins, lysophosphatidylcholines, lysophosphatidylethanolamines, phosphatidylcholines, phosphatidylinositols, diacylglycerols, and triacylglycerols with total acyl chain carbon number ≥54 and/or total double bond number ≥4 were decreased, whereas phosphatidylethanolamines and triacylglycerols with total double bond number <4 accumulated in AD patients. Besides, the length and unsaturation of acyl chains in triacylglycerols and unsaturation of 1-acyl chain in phosphatidylethanolamines were decreased in AD patients. Moreover, lysophosphatidylcholines were the lipids with the largest alterations, at the center of correlation networks of lipid alterations, and had excellent performances in identifying AD patients. The area under the curve of 1.0 and accuracy rate of 100% could be easily obtained by lysophosphatidylcholine (20:0/0:0) or its combination with lysophosphatidylcholine (17:0/0:0) or lysophosphatidylcholine (20:1/0:0). This study provides novel and comprehensive plasma lipidomic signatures of AD patients, identifies lysophosphatidylcholines as excellent potential biomarkers, and would be beneficial to the pathogenetic study, risk assessment and timely diagnosis and treatment of AD.
    Keywords:  aortic dissection; biomarker; fatty acid; lipidomics; phospholipid; plasma; sphingolipid; triglyceride
  13. Curr Protoc. 2021 Nov;1(11): e290
      Multi-isotope imaging mass spectrometry (MIMS) allows the measurement of turnover of molecules within intracellular compartments with a spatial resolution down to 30 nm. We use molecules enriched in stable isotopes administered to animals by diet or injection, or to cells through the culture medium. The stable isotopes used are, in general, 15 N, 13 C, 18 O, and 2 H. For stem cell studies, we essentially use 15 N-thymidine, 13 C-thymidine, and 81 Br from BrdU. This protocol describes the practical use of MIMS with specific reference to applications in stem cell research. This includes choice and administration of stable isotope label(s), sample preparation, best practice for high-resolution imaging, secondary ion mass spectrometry using the Cameca NanoSIMS 50L, and methods for robust statistical analysis of label incorporation in regions of interest (ROI). © 2021 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Stable isotope labeling of DNA in cultured cells Basic Protocol 2: Stable isotope labeling of DNA in animals Basic Protocol 3: Preparation of Si chips, the general sample support for NanoSIMS analysis Basic Protocol 4: Stable isotope analysis of DNA replication in single nuclei in a population of cells with NanoSIMS Basic Protocol 5: Data reduction and processing.
    Keywords:  BrdU; MIMS; NanoSIMS; OpenMIMS; stable isotopes; thymidine
  14. J Pharm Biomed Anal. 2021 Oct 29. pii: S0731-7085(21)00561-6. [Epub ahead of print]208 114450
      Carboxylic acid containing compounds (R-COOH) are involved in a large number of biological processes and they are relevant for several pathological processes such as neurodegeneration or cancer. Comprehensive methodologies for the quantitative determination of R-COOH in biological samples are required. In this study we have developed a LC-MS/MS method for the quantification of 20 endogenous R-COOH belonging to different pathways such as kynurenine metabolism, serotoninergic pathway, glycolysis, tricarboxylic acid cycle, dopaminergic pathway, short chain fatty acids and glycine metabolism. The approach included derivatization with o-benzylhydroxylamine (reaction time 1 h), liquid-liquid extraction with ethyl acetate and LC-MS/MS detection (run time 10 min). The method was optimized and validated in 5 different matrices (urine, plasma, saliva, brain and liver) following two different approaches: (i) using surrogate matrices and (ii) using actual human samples by standard additions. A suitable linearity was obtained in the endogenous range of the analytes. Adequate intra and inter-assay accuracies (80-120%) and intra- and inter-assay precisions (<20%) were achieved for almost all analytes in all studied matrices. The method was applied in several scenarios to confirm (i) human urinary changes produced in glycolysis after exercise, (ii) metabolic changes produced in rat brain and plasma by methamphetamine administration and (iii) metabolic alterations in human plasma caused by vitamin B6 deficiency. Additionally, the application of the method allowed for establishing previously unreported alterations in R-COOH metabolites under these conditions. Due to the comprehensive analyte and matrix coverage and the wide applicability of the developed methodology, it can be considered as a suitable tool for the study of R-COOH status in health and disease by targeted metabolomics.
    Keywords:  Carboxylic acids; Derivatization; LC–MS/MS; O-benzylhydroxylamine; Targeted metabolomics; Tricarboxylic acid cycle
  15. Proteomics. 2021 Nov 20. e2100147
      Prostate cancer is the most common cancer in male worldwide. Mass spectrometry-based targeted proteomics has demonstrated great potential in quantifying proteins from formalin-fixed paraffin-embedded (FFPE) and (fresh) frozen biopsy tissues. Here we provide a comprehensive tissue-specific spectral library for targeted proteomic analysis of prostate tissue samples. Benign and malignant FFPE prostate tissue samples were processed into peptide samples by pressure cycling technology (PCT)-assisted sample preparation, and fractionated with high-pH reversed phase chromatography (RPLC). Based on data-dependent acquisition (DDA) MS analysis using a TripleTOF 6600, we built a library containing 108,533 precursors, 84,198 peptides and 9384 unique proteins (1% FDR). The applicability of the library was demonstrated with prostate specimens. This article is protected by copyright. All rights reserved.
    Keywords:  SWATH-MS spectral library; high-pH fractionation; prostate cancer; targeted proteomics
  16. Biochem Biophys Res Commun. 2021 Nov 12. pii: S0006-291X(21)01545-X. [Epub ahead of print]585 61-67
      Leucine, isoleucine and valine, known as branched chain amino acids (BCAAs), have been reported to be degraded by different cancer cells, and their biodegradation pathways have been suggested as anticancer targets. However, the mechanisms by which the degradation of BCAAs could support the growth of cancer cells remains unclear. In this work, 13C experiments have been carried out in order to elucidate the metabolic role of BCAA degradation in two breast cancer cell lines (MCF-7 and BCC). The results revealed that up to 36% of the energy production via respiration by MCF-7 cells was supported by the degradation of BCAAs. Also, 67% of the mevalonate (the precursor of cholesterol) synthesized by the cells was coming from the degradation of leucine. The results were lower for BCC cells (14 and 30%, respectively). The non-tumorigenic epythelial cell line MCF-10A was used as a control, showing that 10% of the mitochondrial acetyl-CoA comes from the degradation of BCAAs and no mevalonate production. Metabolic flux analysis around the mevalonate node, also revealed that significant amounts of acetoacetate are being produced from BCAA derived carbon, which could be at the source of lipid synthesis. From these results we can conclude that the degradation of BCAAs is an important energy and carbon source for the proliferation of some cancer cells and its therapeutic targeting could be an interesting option.
    Keywords:  Branched chain amino-acids; Cancer metabolism; Metabolic flux analysis
  17. Lipids Health Dis. 2021 Nov 14. 20(1): 163
      Reprogramming of lipid metabolism has received increasing recognition as a hallmark of cancer cells because lipid dysregulation and the alteration of related enzyme profiles are closely correlated with oncogenic signals and malignant phenotypes, such as metastasis and therapeutic resistance. In this review, we describe recent findings that support the importance of lipids, as well as the transcription factors involved in cancer lipid metabolism. With recent advances in transcription factor analysis, including computer-modeling techniques, transcription factors are emerging as central players in cancer biology. Considering the limited number and the crucial role of transcription factors associated with lipid rewiring in cancers, transcription factor targeting is a promising potential strategy for cancer therapy.
    Keywords:  Cancer; Lipid metabolism; Transcription factor
  18. Nat Metab. 2021 Nov;3(11): 1512-1520
      Mammalian cells require activated folates to generate nucleotides for growth and division. The most abundant circulating folate species is 5-methyl tetrahydrofolate (5-methyl-THF), which is used to synthesize methionine from homocysteine via the cobalamin-dependent enzyme methionine synthase (MTR). Cobalamin deficiency traps folates as 5-methyl-THF. Here, we show using isotope tracing that MTR is only a minor source of methionine in cell culture, tissues or xenografted tumours. Instead, MTR is required for cells to avoid folate trapping and assimilate 5-methyl-THF into other folate species. Under conditions of physiological extracellular folates, genetic MTR knockout in tumour cells leads to folate trapping, purine synthesis stalling, nucleotide depletion and impaired growth in cell culture and as xenografts. These defects are rescued by free folate but not one-carbon unit supplementation. Thus, MTR plays a crucial role in liberating THF for use in one-carbon metabolism.
  19. Mol Metab. 2021 Nov 13. pii: S2212-8778(21)00248-9. [Epub ahead of print] 101393
      BACKGROUND: Obesity develops due to an imbalance in energy homeostasis, wherein energy intake exceeds energy expenditure. Increasing evidence shows that manipulations of dietary protein and their component amino acids affect the energy balance, resulting in changes in fat mass and body weight. Amino acids are not only the building blocks of proteins but also serve as signals regulating multiple biological pathways.SCOPE OF REVIEW: We present the current available knowledge regarding the effects of dietary alterations of a single essential amino acid (EAA) on energy balance and relevant signaling mechanisms at both the central and peripheral levels. We also summarize the association between EAAs and obesity in humans and the clinical use of modifying the dietary EAA composition for therapeutic intervention in obesity. Finally, we describe similar mechanisms underlying diets varying in protein levels and diets altered of a single EAA. This review will expand the understanding of the contribution of protein and amino acids to energy balance control, which could be helpful in the discovery of new therapeutic approaches for obesity and related diseases.
    MAJOR CONCLUSIONS: Changes in circulating EAA levels, particularly increased branched-chain amino acids (BCAAs), have been observed in obese human and animal models. Alterations in dietary EAA intake can lead to improvements in fat and weight loss in rodents, and each has its distinct mechanism. For example, leucine deprivation increases energy expenditure and reduces food intake and fat mass, primarily through regulation of the general control nonderepressible 2 (GCN2) and mammalian target of rapamycin (mTOR) signaling. Methionine restriction by 80 % decreases fat mass and body weight while developing hyperphagia, mainly via fibroblast growth factor (FGF) 21 signaling. Some effects of diets with different protein levels on energy homeostasis are mediated by similar mechanisms. However, reports on the effects and underlying mechanisms of dietary EAA imbalances on human body weight are few, and more investigations are needed.
    Keywords:  FGF21; GCN2; body weight; energy balance; essential amino acid; mTOR; protein
  20. Nat Metab. 2021 Nov;3(11): 1521-1535
      Eukaryotic cells can survive the loss of their mitochondrial genome, but consequently suffer from severe growth defects. 'Petite yeasts', characterized by mitochondrial genome loss, are instrumental for studying mitochondrial function and physiology. However, the molecular cause of their reduced growth rate remains an open question. Here we show that petite cells suffer from an insufficient capacity to synthesize glutamate, glutamine, leucine and arginine, negatively impacting their growth. Using a combination of molecular genetics and omics approaches, we demonstrate the evolution of fast growth overcomes these amino acid deficiencies, by alleviating a perturbation in mitochondrial iron metabolism and by restoring a defect in the mitochondrial tricarboxylic acid cycle, caused by aconitase inhibition. Our results hence explain the slow growth of mitochondrial genome-deficient cells with a partial auxotrophy in four amino acids that results from distorted iron metabolism and an inhibited tricarboxylic acid cycle.
  21. Analyst. 2021 Nov 17.
      This review paper highlights the recent research on liquid-phase microscale separation techniques for lipidome analysis over the last 10 years, mainly focusing on capillary liquid chromatography (LC) and capillary electrophoresis (CE) coupled with mass spectrometry (MS). Lipids are one of the most important classes of biomolecules which are involved in the cell membrane, energy storage, signal transduction, and so on. Since lipids include a variety of hydrophobic compounds including numerous structural isomers, lipidomes are a challenging target in bioanalytical chemistry. MS is the key technology that comprehensively identifies lipids; however, separation techniques like LC and CE are necessary prior to MS detection in order to avoid ionization suppression and resolve structural isomers. Separation techniques using μm-scale columns, such as a fused silica capillary and microfluidic device, are effective at realizing high-resolution separation. Microscale separation usually employs a nL-scale flow, which is also compatible with nanoelectrospray ionization-MS that achieves high sensitivity. Owing to such analytical advantages, microscale separation techniques like capillary/microchip LC and CE have been employed for more than 100 lipidome studies. Such techniques are still being evolved and achieving further higher resolution and wider coverage of lipidomes. Therefore, microscale separation techniques are promising as the fundamental technology in next-generation lipidome analysis.
  22. J Hepatol. 2021 Nov 15. pii: S0168-8278(21)02181-4. [Epub ahead of print]
      Lipid droplets (LDs) are complex and metabolically active organelles. They are composed of a neutral lipid core surrounded by a monolayer of phospholipids and proteins. LD accumulation in hepatocytes is the distinctive characteristic of non-alcoholic fatty liver disease (NAFLD). NAFLD is a chronic, heterogeneous liver condition that can progress to liver fibrosis and hepatocellular carcinoma. Though recent research has improved our understanding of the mechanisms linking LDs accumulation to NAFLD progression, numerous aspects of LD biology are either poorly understood or unknown. In this review, we provide a description of several key mechanisms that contribute to LDs accumulation in the hepatocytes, favouring NAFLD progression. First, we highlight the importance of LD architecture and describe how the dysregulation of LD biogenesis leads to endoplasmic reticulum stress and inflammation. This is followed by an analysis of the causal nexus that exists between LD proteome composition and LD degradation. Finally, we describe how the increase in size of LDs causes activation of hepatic stellate cells, leading to liver fibrosis and hepatocellular carcinoma. We conclude that acquiring a more sophisticated understanding of LD biology will provide crucial insights into the heterogeneity of NAFLD and assist in the development of therapeutic approaches for this liver disease.
    Keywords:  Autophagy; Endoplasmic reticulum stress; Hypoxia; Lipid droplets (LDs); Non-alcoholic fatty liver disease (NAFLD); Non-alcoholic steatohepatitis (NASH)
  23. Nat Metab. 2021 Nov;3(11): 1445-1465
      The perception that intracellular lipolysis is a straightforward process that releases fatty acids from fat stores in adipose tissue to generate energy has experienced major revisions over the last two decades. The discovery of new lipolytic enzymes and coregulators, the demonstration that lipophagy and lysosomal lipolysis contribute to the degradation of cellular lipid stores and the characterization of numerous factors and signalling pathways that regulate lipid hydrolysis on transcriptional and post-transcriptional levels have revolutionized our understanding of lipolysis. In this review, we focus on the mechanisms that facilitate intracellular fatty-acid mobilization, drawing on canonical and noncanonical enzymatic pathways. We summarize how intracellular lipolysis affects lipid-mediated signalling, metabolic regulation and energy homeostasis in multiple organs. Finally, we examine how these processes affect pathogenesis and how lipolysis may be targeted to potentially prevent or treat various diseases.