bims-mascan Biomed News
on Mass spectrometry in cancer research
Issue of 2022‒07‒03
twenty-six papers selected by
Giovanny Rodriguez Blanco
University of Edinburgh

  1. Nat Metab. 2022 Jun;4(6): 693-710
      Elevated production of collagen-rich extracellular matrix is a hallmark of cancer-associated fibroblasts (CAFs) and a central driver of cancer aggressiveness. Here we find that proline, a highly abundant amino acid in collagen proteins, is newly synthesized from glutamine in CAFs to make tumour collagen in breast cancer xenografts. PYCR1 is a key enzyme for proline synthesis and highly expressed in the stroma of breast cancer patients and in CAFs. Reducing PYCR1 levels in CAFs is sufficient to reduce tumour collagen production, tumour growth and metastatic spread in vivo and cancer cell proliferation in vitro. Both collagen and glutamine-derived proline synthesis in CAFs are epigenetically upregulated by increased pyruvate dehydrogenase-derived acetyl-CoA levels. PYCR1 is a cancer cell vulnerability and potential target for therapy; therefore, our work provides evidence that targeting PYCR1 may have the additional benefit of halting the production of a pro-tumorigenic extracellular matrix. Our work unveils new roles for CAF metabolism to support pro-tumorigenic collagen production.
  2. Mol Metab. 2022 Jun 22. pii: S2212-8778(22)00101-6. [Epub ahead of print] 101532
      Bone marrow mesenchymal stromal cells (MSCs) have immunomodulatory and regenerative potential. However, culture conditions govern their metabolic processes and therapeutic efficacy. Here we show that culturing donor-derived MSCs in Plasmax™, a physiological medium with the concentrations of nutrients found in human plasma, supports their proliferation and stemness, and prevents the nutritional stress induced by the conventional medium DMEM. The quantification of the exchange rates of metabolites between cells and medium, untargeted metabolomics, stable isotope tracing and transcriptomic analysis, performed at physiologically relevant oxygen concentrations (1%O2), reveal that MSCs rely on high rate of glucose to lactate conversion, coupled with parallel anaplerotic fluxes from glutamine and glutamate to support citrate synthesis and secretion. These distinctive traits of MSCs shape the metabolic microenvironment of bone marrow niche and can influence nutrient cross-talks under physiological and pathological conditions.
    Keywords:  Citrate; Glutamate; Glutamine; Hypoxia; Mesenchymal stromal cells; Metabolism; Physiological medium; Plasmax; Primary cells; Stable isotope tracing
  3. Cancer Res. 2022 Jun 30. pii: can.22.0917. [Epub ahead of print]
      Metabolic reprogramming is a hallmark of cancer progression. Metabolic activity supports tumorigenesis and tumor progression, allowing cells to uptake essential nutrients from the environment and use the nutrients to maintain viability and support proliferation. The metabolic pathways of malignant cells are altered to accommodate increased demand for energy, reducing equivalents, and biosynthetic precursors. Activated oncogenes coordinate with altered metabolism to control cell-autonomous pathways, which can lead to tumorigenesis when abnormalities accumulate. Clinical and preclinical studies have shown that targeting metabolic features of hematological malignancies is an appealing therapeutic approach. This review provides a comprehensive overview of the mechanisms of metabolic reprogramming in hematologic malignancies and potential therapeutic strategies to target cancer metabolism.
  4. Mol Cell. 2022 Jun 24. pii: S1097-2765(22)00544-5. [Epub ahead of print]
      Bicarbonate (HCO3-) ions maintain pH homeostasis in eukaryotic cells and serve as a carbonyl donor to support cellular metabolism. However, whether the abundance of HCO3- is regulated or harnessed to promote cell growth is unknown. The mechanistic target of rapamycin complex 1 (mTORC1) adjusts cellular metabolism to support biomass production and cell growth. We find that mTORC1 stimulates the intracellular transport of HCO3- to promote nucleotide synthesis through the selective translational regulation of the sodium bicarbonate cotransporter SLC4A7. Downstream of mTORC1, SLC4A7 mRNA translation required the S6K-dependent phosphorylation of the translation factor eIF4B. In mTORC1-driven cells, loss of SLC4A7 resulted in reduced cell and tumor growth and decreased flux through de novo purine and pyrimidine synthesis in human cells and tumors without altering the intracellular pH. Thus, mTORC1 signaling, through the control of SLC4A7 expression, harnesses environmental bicarbonate to promote anabolic metabolism, cell biomass, and growth.
    Keywords:  SLC4A7/NBCn1; bicarbonate metabolism; mTOR signaling; purine metabolism; pyrimidine metabolism
  5. Klin Onkol. 2022 ;35(3): 195-207
      BACKGROUND: A general characteristic of cancer metabolism is the skill to gain the essential nutrients from a relatively poor environment and use them effectively to maintain viability and create new bio-mass. The changes in intracellular and extracellular metabolites that accompany metabolic reprogramming associated with tumor growth subsequently affect gene expression, cell differentiation, and tumor microenvironment. During carcinogenesis, cancer cells face huge selection pressures that force them to constantly optimize dominant metabolic pathways and undergo major metabolic reorganizations. In general, greater flexibility of metabolic pathways increases the ability of tumor cells to satisfy their metabolic needs in a changing environment.PURPOSE: In this review, we discuss the metabolic properties of cancer cells and describe the tumor promoting effect of the transformed metabolism. We assume that changes in metabolism are significant enough to facilitate tumorigenesis and may provide interesting targets for cancer therapy.
    Keywords:  Krebs cycle; Metabolism; Warburg effect; anaplerosis; cancer; glutaminolysis; malignancy; oncogenesis; oncometabolite
  6. Cell Rep. 2022 Jun 28. pii: S2211-1247(22)00801-4. [Epub ahead of print]39(13): 111012
      Ovarian cancer (OC) is the most lethal gynecological malignancy, with aggressive metastatic disease responsible for the majority of OC-related deaths. In particular, OC tumors preferentially metastasize to and proliferate rapidly in the omentum. Here, we show that metastatic OC cells experience increased oxidative stress in the omental microenvironment. Metabolic reprogramming, including upregulation of the pentose phosphate pathway (PPP), a key cellular redox homeostasis mechanism, allows OC cells to compensate for this challenge. Inhibition of glucose-6-phosphate dehydrogenase (G6PD), the rate-limiting enzyme of the PPP, reduces tumor burden in pre-clinical models of OC, suggesting that this adaptive metabolic dependency is important for OC omental metastasis.
    Keywords:  CP: Cancer; CP: Metabolism; metabolism; metastasis; ovarian cancer
  7. J Chromatogr B Analyt Technol Biomed Life Sci. 2022 Jun 02. pii: S1570-0232(22)00218-5. [Epub ahead of print]1205 123314
      The methionine transsulfuration pathway plays an important role in some fundamental biological processes, such as redox and methylation reactions. However, quantitative analysis of the majority of intracellular metabolites is rather challenging. In this study, we developed a simple, fast and reliable method using liquid chromatography-tandem mass spectrometry (LC-MS/MS) for the simultaneous detection of 14 methionine-related metabolites, including methionine, S-adenosylmethionine (SAM), S-adenosylhomocysteine (SAH), homocysteine (HCY), cystathionine (Cysta), cysteine (CYS), glutathione (GSH), dimethylglycine (DMG), betaine, serine, folic acid (FA), dihydrofolic acid (DHF), tetrahydrofolic acid (THF) and 5-methyltetrahydrofolic acid (5-MTHF), in MCF-7 and MDA-MB-231 breast cancer cells. By taking advantage of a surrogate matrix, the linearity, sensitivity, precision, accuracy, stability, matrix effect, recovery, dilution integrity and carryover of the established method were evaluated and validated. This method enabled the precise measurement of methionine-related metabolites both in cells and in the medium and was successfully applied to profile these metabolites involved in the methionine transsulfuration pathway. The data showed that cystine deprivation or excessive supplementation with cystine had a marked impact on methionine metabolism, in addition to its effects on intracellular CYS and GSH levels, indicating that the methionine transsulfuration pathway was dependent on intracellular cystine levels. The established method provides a reliable way to target metabolomics for the quantitative determination of intracellular metabolites in the methionine transsulfuration pathway, which can greatly facilitate the understanding of the mechanisms involved in methylation and redox homeostasis in cellular metabolomic studies.
    Keywords:  Breast cancer cells; Cystine; LC–MS/MS; Methionine metabolism; Oxidative stress
  8. J Cell Sci. 2022 Jul 01. pii: jcs.259090. [Epub ahead of print]
      Accelerated aerobic glycolysis is a distinctive metabolic property of cancer cells that confers dependency on glucose for survival. However, the therapeutic strategies targeting this vulnerability are still inefficient and have unacceptable side effects in clinical trials. Therefore, developing biomarkers to predict therapeutic efficacy would be essential to improve the selective targeting of cancer cells. Here, we found that the cell lines sensitive to glucose deprivation have high expression of cystine/glutamate antiporter xCT. We found that cystine uptake and glutamate export through xCT contributed to rapid NADPH depletion under glucose deprivation. This collapse of the redox system oxidized and inactivated AMPK, a major regulator of metabolic adaptation, resulting in a metabolic catastrophe and cell death. While this phenomenon was prevented by pharmacological or genetic inhibition of xCT, overexpression of xCT sensitized resistant cancer cells to glucose deprivation. Taken together, these findings suggest a novel cross-talk between AMPK and xCT for the metabolism and signal transduction and reveal a metabolic vulnerability in xCT-high expressing cancer cells to glucose deprivation.
    Keywords:  AMPK; Cystine; Glucose starvation; NADPH; SLC7A11; xCT
  9. J Anal Toxicol. 2022 Jun 29. pii: bkac046. [Epub ahead of print]
      Liquid chromatography-electrospray ionization-tandem mass spectrometry (LC-ESI-MS/MS) with stable isotope labeled internal standards (SIL-IS) is the gold standard for quantitative analysis of drugs and metabolites in complex biological samples. Significant isotopic effects associated with deuterium labeling often causes the deuterated IS to elute at a different retention time from the target analyte, diminishing its capability to compensate for matrix effects. In this study, we systematically compared the analytical performance of deuterated (2H) SIL-IS to non-deuterated (13C and 15N) SIL-ISs for quantifying urinary 2-methylhippuric acid (2MHA) and 4-methylhippuric acid (4MHA), biomarkers of xylenes exposure, with an LC-ESI-MS/MS assay. Analytical method comparison between IS demonstrated a quantitative bias for urinary 2MHA results, with concentrations generated with 2MHA-[2H7] on average 59.2% lower than concentrations generated by 2MHA-[13C6]. Spike accuracy, measured by quantifying analyte-spiked urine matrix and comparing the result to the known spike concentration, determined that 2MHA-[2H7] generated negatively biased urinary results of -38.4% whereas no significant bias was observed for 2MHA-[13C6]. Post-column infusion demonstrated that ion suppression experienced by 2MHA and 2MHA-[13C6] was not equally experienced by 2MHA-[2H7], explaining the negatively biased 2MHA results. Quantitation of urinary 4MHA results between IS exhibited no significant quantitative bias. These results underscore the importance of careful selection of internal standards for targeted quantitative analysis in complex biological samples.
    Keywords:  2-methylhippuric acid; 4-methylhippuric acid; accuracy; biomonitoring; deuterated; internal standard; liquid chromatography-mass spectrometry; matrix effects; xylenes
  10. Chem Sci. 2022 Jun 07. 13(22): 6687-6695
      Cell-cell interactions are critical for transmitting signals among cells and maintaining their normal functions from the single-cell level to tissues. In cancer studies, interactions between drug-resistant and drug-sensitive cells play an important role in the development of chemotherapy resistance of tumors. As metabolites directly reflect the cell status, metabolomics studies provide insight into cell-cell communication. Mass spectrometry (MS) is a powerful tool for metabolomics studies, and single cell MS (SCMS) analysis can provide unique information for understanding interactions among heterogeneous cells. In the current study, we utilized a direct co-culture system (with cell-cell contact) to study metabolomics of single cells affected by cell-cell interactions in their living status. A fluorescence microscope was utilized to distinguish these two types of cells for SCMS metabolomics studies using the Single-probe SCMS technique under ambient conditions. Our results show that through interactions with drug-resistant cells, drug-sensitive cancer cells acquired significantly increased drug resistance and exhibited drastically altered metabolites. Further investigation found that the increased drug resistance was associated with multiple metabolism regulations in drug-sensitive cells through co-culture such as the upregulation of sphingomyelins lipids and lactic acid and the downregulation of TCA cycle intermediates. The method allows for direct MS metabolomics studies of individual cells labeled with fluorescent proteins or dyes among heterogeneous populations.
  11. Science. 2022 Jul;377(6601): 47-56
      The mechanistic target of rapamycin complex 1 (mTORC1) kinase controls growth in response to nutrients, including the amino acid leucine. In cultured cells, mTORC1 senses leucine through the leucine-binding Sestrin proteins, but the physiological functions and distribution of Sestrin-mediated leucine sensing in mammals are unknown. We find that mice lacking Sestrin1 and Sestrin2 cannot inhibit mTORC1 upon dietary leucine deprivation and suffer a rapid loss of white adipose tissue (WAT) and muscle. The WAT loss is driven by aberrant mTORC1 activity and fibroblast growth factor 21 (FGF21) production in the liver. Sestrin expression in the liver lobule is zonated, accounting for zone-specific regulation of mTORC1 activity and FGF21 induction by leucine. These results establish the mammalian Sestrins as physiological leucine sensors and reveal a spatial organization to nutrient sensing by the mTORC1 pathway.
  12. J Am Soc Mass Spectrom. 2022 Jun 28.
      Short-chain fatty acids are difficult to analyze with high sensitivity using liquid chromatography-electrospray ionization-mass spectrometry (LC-ESI-MS) owing to the high polarity of their carboxyl groups. Various derivatization methods have been developed; however, most are effective only for monocarboxylic acids and not for those having multiple carboxyl groups. Therefore, we successfully attempted to synthesize a derivatization reagent that could analyze both mono- and poly(carboxylic acid)s with high sensitivity. We optimized our derivatization reagent by modifying the structure of the reaction site, hydrophobicity of the derivatized compound, and linker structure connecting the reaction site to the permanently charged substructure. The reactivity toward carboxyl groups was improved by employing a piperidine moiety as the reaction site, and the ESI efficiency was improved by the highly hydrophobic and permanently charged triphenylpyridinium group. Furthermore, the incorporation of an alkyl linker enabled polylabeling. When the optimized reagent was applied to mono-, di-, tri-, and tetracarboxylic acids, the ESI efficiency increased with polylabeling; thus, our derivatization reagent outperforms existing derivatization methods and enables the analysis of poly(carboxylic acid)s with high sensitivity. Since this derivatization reagent can be applied to most carboxyl-containing compounds, it can be widely used for lipidomics, proteomics, and metabolomics.
  13. Bioinformatics. 2022 06 24. 38(Suppl 1): i342-i349
      MOTIVATION: Untargeted metabolomics experiments rely on spectral libraries for structure annotation, but these libraries are vastly incomplete; in silico methods search in structure databases, allowing us to overcome this limitation. The best-performing in silico methods use machine learning to predict a molecular fingerprint from tandem mass spectra, then use the predicted fingerprint to search in a molecular structure database. Predicted molecular fingerprints are also of great interest for compound class annotation, de novo structure elucidation, and other tasks. So far, kernel support vector machines are the best tool for fingerprint prediction. However, they cannot be trained on all publicly available reference spectra because their training time scales cubically with the number of training data.RESULTS: We use the Nyström approximation to transform the kernel into a linear feature map. We evaluate two methods that use this feature map as input: a linear support vector machine and a deep neural network (DNN). For evaluation, we use a cross-validated dataset of 156 017 compounds and three independent datasets with 1734 compounds. We show that the combination of kernel method and DNN outperforms the kernel support vector machine, which is the current gold standard, as well as a DNN on tandem mass spectra on all evaluation datasets.
    AVAILABILITY AND IMPLEMENTATION: The deep kernel learning method for fingerprint prediction is part of the SIRIUS software, available at
  14. Methods Mol Biol. 2022 ;2515 203-225
      The immuno-MALDI-MS method can be used to quantify low-abundance proteins from clinical samples that offer only a limited amount of material for analysis. An internal standard, in the form of a stable isotope-labeled peptide, is used to ensure reproducible and absolute quantitation. The protocol described here was optimized for the quantitation of AKT1 and AKT2, but we offer instructions on how to adapt the method to target other proteins. The described workflow is compatible with automation via a liquid handling robot for high-throughput applications.
    Keywords:  Absolute protein quantitation; Immunoenrichment; Internal peptide standard; MALDI; Proteomics; TOF mass spectrometry (MS); iMALDI
  15. Proteomics. 2022 Jul 01. e2100253
      In mass spectrometry (MS)-based quantitative proteomics, labeling with isobaric mass tags such as iTRAQ and TMT can substantially improve sample throughput and reduce peptide missing values. Nonetheless, the quantification of labeled peptides tends to suffer from reduced accuracy due to the co-isolation of co-eluting precursors of similar mass-to-charge. Acquisition approaches such as multistage MS3 or ion mobility separation address this problem, yet are difficult to audit and limited to expensive instrumentation. Here we introduce IsobaricQuant, an open-source software tool for quantification, visualization, and filtering of peptides labeled with isobaric mass tags, with specific focus on precursor interference. IsobaricQuant is compatible with MS2 and MS3 acquisition strategies, has a viewer that allows assessing interference, and provides several scores to aid the filtering of scans with compression. We demonstrate that IsobaricQuant quantifications are accurate by comparing it with commonly used software. We further show that its QC scores can successfully filter out scans with reduced quantitative accuracy at MS2 and MS3 levels, removing inaccurate peptide quantifications and decreasing protein CVs. Finally, we apply IsobaricQuant to a PISA dataset and show that QC scores improve the sensitivity of the identification of protein targets of a kinase inhibitor. IsobaricQuant is available at This article is protected by copyright. All rights reserved.
    Keywords:  isobaric mass tag; protein quantification; quantification software
  16. Cell Commun Signal. 2022 Jun 25. 20(1): 97
      Cancer progression involves several biological steps where angiogenesis is a key tumorigenic phenomenon. Extracellular vesicles (EVs) derived from tumor cells and other cells in the tumor microenvironment (TME) help modulate and maintain favorable microenvironments for tumors. Endothelial cells (ECs) activated by cancer-derived EVs have important roles in tumor angiogenesis. Interestingly, EVs from ECs activate tumor cells, i.e. extracellular matrix (ECM) remodeling and provide more supplements for tumor cells. Thus, EV communications between cancer cells and ECs may be effective therapeutic targets for controlling cancer progression. In this review, we describe the current knowledge on EVs derived from ECs and we examine how these EVs affect TME remodeling. Video abstract.
    Keywords:  Angiogenesis; Extracellular vesicles; Remodeling; Targeted therapy; Tumor microenvironment
  17. Immunooncol Technol. 2021 Oct;11 100042
      Quantitative mass-spectrometry-based methods to perform relative and absolute quantification of peptides in the immunopeptidome are growing in popularity as researchers aim to measure the dynamic nature of the peptide major histocompatibility complex repertoire and make copies-per-cell estimations of target antigens of interest. Multiple methods to carry out these experiments have been reported, each with unique advantages and limitations. This article describes existing methods and recent applications, offering guidance for improving quantitative accuracy and selecting an appropriate experimental set-up to maximize data quality and quantity.
    Keywords:  HLA; MHC; antigen presentation; immunopeptidomics; mass spectometry
  18. J Proteome Res. 2022 Jun 30.
      Data-independent acquisition (DIA) allows comprehensive proteome coverage, while it also potentially works as a unified protocol to determine a multitude of proteins found in blood. Because of its high specificity, mass spectrometry may greatly reduce the interference observed in other assays to evaluate blood markers. Here, we combined DIA with volumetric absorptive microsampling (VAMS) and automated proteomics sample processing in a platform to assess clinical markers. As a proof of concept, we evaluated two hemoglobin-related biomarkers: the glycated hemoglobin (HbA1c) and hemoglobin (Hb) variants. HbA1c by DIA showed good correlation with the reference method, but method imprecision did not meet the quality requirement for this biomarker. We developed a strategy to identify Hb variants based on a customized database combined with a workflow for DIA data extraction and rigorous peptide evaluation. Data are available via ProteomeXchange with identifier PXD029918.
    Keywords:  data-independent acquisition; glycated hemoglobin; hemoglobin variants; proteomics; volumetric absorptive microsampling
  19. Anal Chem. 2022 Jun 29.
      Despite advances in proteomic technologies, clinical translation of plasma biomarkers remains low, partly due to a major bottleneck between the discovery of candidate biomarkers and costly clinical validation studies. Due to a dearth of multiplexable assays, generally only a few candidate biomarkers are tested, and the validation success rate is accordingly low. Previously, mass spectrometry-based approaches have been used to fill this gap but feature poor quantitative performance and were generally limited to hundreds of proteins. Here, we demonstrate the capability of an internal standard triggered-parallel reaction monitoring (IS-PRM) assay to greatly expand the numbers of candidates that can be tested with improved quantitative performance. The assay couples immunodepletion and fractionation with IS-PRM and was developed and implemented in human plasma to quantify 5176 peptides representing 1314 breast cancer biomarker candidates. Characterization of the IS-PRM assay demonstrated the precision (median % CV of 7.7%), linearity (median R2 > 0.999 over 4 orders of magnitude), and sensitivity (median LLOQ < 1 fmol, approximately) to enable rank-ordering of candidate biomarkers for validation studies. Using three plasma pools from breast cancer patients and three control pools, 893 proteins were quantified, of which 162 candidate biomarkers were verified in at least one of the cancer pools and 22 were verified in all three cancer pools. The assay greatly expands capabilities for quantification of large numbers of proteins and is well suited for prioritization of viable candidate biomarkers.
  20. Anal Chem. 2022 Jun 27.
      Urine sample storage after collection at ultra-low-temperature (e.g., -80 °C) is normally required for comparative metabolome analysis of many samples, and therefore, freeze-thaw cycles (FTCs) are unavoidable. However, the reported effects of FTCs on the urine metabolome are controversial. Moreover, there is no report on the study of how urine FTCs affect biomarker discovery. Herein, we present our study of the FTC effects on the urine metabolome and biomarker discovery using a high-coverage quantitative metabolomics platform. Our study involved two centers located in Hangzhou, China, and Edmonton, Canada, to perform metabolome analysis of two separate cohorts of urine samples. The same workflow of sample preparation and dansylation isotope labeling LC-MS was used for in-depth analysis of the amine/phenol submetabolome. The analysis of 320 samples from the Hangzhou cohort consisting of 80 healthy subjects with each urine being subjected to four FTCs resulted in relative quantification of 3682 metabolites with 3307 identified or mass-matched. The analysis of 176 samples from the Edmonton cohort of 44 subjects with four FTCs quantified 3516 metabolites with 3166 identified or mass-matched. Multivariate and univariate analyses indicated that significant variations (fold change ≥ 1.5 with q-value ≤ 0.05) from FTCs were only observed in a very small fraction of the metabolites (<0.3%). Moreover, various metabolites did not show a consistent pattern of concentration changes from one to four FTCs, allowing the use of two separate cohorts of samples to remove these randomly changed metabolites. Three metabolite biomarkers for separating males and females were discovered, and FTC did not influence their discovery.
  21. Mol Cell. 2022 Jun 18. pii: S1097-2765(22)00541-X. [Epub ahead of print]
      Cancer mortality is primarily a consequence of its metastatic spread. Here, we report that methionine sulfoxide reductase A (MSRA), which can reduce oxidized methionine residues, acts as a suppressor of pancreatic ductal adenocarcinoma (PDA) metastasis. MSRA expression is decreased in the metastatic tumors of PDA patients, whereas MSRA loss in primary PDA cells promotes migration and invasion. Chemoproteomic profiling of pancreatic organoids revealed that MSRA loss results in the selective oxidation of a methionine residue (M239) in pyruvate kinase M2 (PKM2). Moreover, M239 oxidation sustains PKM2 in an active tetrameric state to promote respiration, migration, and metastasis, whereas pharmacological activation of PKM2 increases cell migration and metastasis in vivo. These results demonstrate that methionine residues can act as reversible redox switches governing distinct signaling outcomes and that the MSRA-PKM2 axis serves as a regulatory nexus between redox biology and cancer metabolism to control tumor metastasis.
    Keywords:  PKM2; cancer metabolism; glucose oxidation; metastasis; methionine oxidation; pancreatic cancer; redox signaling
  22. Anal Chem. 2022 Jun 30.
      Nanospray desorption electrospray mass spectrometry imaging (nano-DESI MSI) enables quantitative mapping of hundreds of molecules in biological samples with minimal sample pretreatment. We have recently developed an integrated microfluidic probe (iMFP) for nano-DESI MSI. Herein, we describe an improved design of the iMFP for the high-throughput imaging of tissue sections. We increased the dimensions of the primary and spray channels and optimized the spray voltage and solvent flow rate to obtain a stable operation of the iMFP at both low and high scan rates. We observe that the sensitivity, molecular coverage, and spatial resolution obtained using the iMFP do not change to a significant extent as the scan rate increases. Using a scan rate of 0.4 mm/s, we obtained high-quality images of mouse uterine tissue sections (scan area: 3.2 mm × 2.3 mm) in only 9.5 min and of mouse brain tissue (scan area: 7.0 mm × 5.4 mm) in 21.7 min, which corresponds to a 10-15-fold improvement in the experimental throughput. We have also developed a quantitative metric for evaluating the quality of ion images obtained at different scan rates. Using this metric, we demonstrate that the quality of nano-DESI MSI data does not degrade substantially with an increase in the scan rate. The ability to image biological tissues with high throughput using iMFP-based nano-DESI MSI will substantially speed up tissue mapping efforts.
  23. Nat Metab. 2022 Jun;4(6): 775-790
      Obesity induces chronic inflammation resulting in insulin resistance and metabolic disorders. Cold exposure can improve insulin sensitivity in humans and rodents, but the mechanisms have not been fully elucidated. Here, we find that cold resolves obesity-induced inflammation and insulin resistance and improves glucose tolerance in diet-induced obese mice. The beneficial effects of cold exposure on improving obesity-induced inflammation and insulin resistance depend on brown adipose tissue (BAT) and liver. Using targeted liquid chromatography with tandem mass spectrometry, we discovered that cold and β3-adrenergic stimulation promote BAT to produce maresin 2 (MaR2), a member of the specialized pro-resolving mediators of bioactive lipids that play a role in the resolution of inflammation. Notably, MaR2 reduces inflammation in obesity in part by targeting macrophages in the liver. Thus, BAT-derived MaR2 could contribute to the beneficial effects of BAT activation in resolving obesity-induced inflammation and may inform therapeutic approaches to combat obesity and its complications.
  24. iScience. 2022 Jun 17. 104612
      The coronavirus disease-19 (COVID-19) pandemic has ravaged global healthcare with previously unseen levels of morbidity and mortality. In this study, we performed large-scale integrative multi-omics analyses of serum obtained from COVID-19 patients with the goal of uncovering novel pathogenic complexities of this disease and identifying molecular signatures that predict clinical outcomes. We assembled a network of protein-metabolite interactions through targeted metabolomic and proteomic profiling in 330 COVID-19 patients compared to 97 non-COVID, hospitalized controls. Our network identified distinct protein-metabolite cross talk related to immune modulation, energy and nucleotide metabolism, vascular homeostasis, and collagen catabolism. Additionally, our data linked multiple proteins and metabolites to clinical indices associated with long-term mortality and morbidity. Finally, we developed a novel composite outcome measure for COVID-19 disease severity based on metabolomics data. The model predicts severe disease with a concordance index of around 0.69, and shows high predictive power of 0.83-0.93 in two independent datasets.