bims-mascan 2022-07-24 papers

bims-mascan

Biomed News

on Mass spectrometry in cancer research

Issue of 2022–07–24
seventeen papers selected by
Giovanny Rodriguez Blanco, University of Edinburgh

Prioritize biologically relevant ions for data-independent acquisition (BRI-DIA) in LC-MS/MS-based lipidomics analysis.
Skin fibroblast metabolomic profiling reveals that lipid dysfunction predicts the severity of Friedreich's ataxia.
Emerging roles of fatty acid metabolism in cancer and their targeted drug development.
Combining data acquisition modes in liquid-chromatography-tandem mass spectrometry for comprehensive determination of acylcarnitines in human serum.
Lipid Analysis of Follicular Fluids by UHPLC-ESI-HRMS Discovers Potential Biomarkers for Ovarian Hyperstimulation Syndrome.
Dataset containing physiological amounts of spike-in proteins into murine C2C12 background as a ground truth quantitative LC-MS/MS reference.
Lipidomic profiling of the hepatic esterified fatty acid composition in diet-induced nonalcoholic fatty liver disease in genetically diverse Collaborative Cross mice.
Potential of atmospheric pressure ionization sources for the analysis of free fatty acids in clinical and biological samples by gas chromatography-mass spectrometry.
Simultaneous quantification of 70 elements in biofluids within 5 min using inductively coupled plasma mass spectrometry to reveal elementomic phenotypes of healthy Chinese adults.
A sensitive UPLC-MS/MS method for simultaneous quantification of one-carbon metabolites & co-factors in human plasma.
Co-regulation of hepatic steatosis by ferritinophagy and unsaturated fatty acid supply.
Sestrin mediates detection of and adaptation to low-leucine diets in Drosophila.
Interplay of Nrf2 and BACH1 in inducing ferroportin expression and enhancing resistance of human macrophages towards ferroptosis.
Bioinformatic Analysis to Investigate Metaproteome Composition Using Trans-Proteomic Pipeline.
Mapping Protein-Protein Interactions Using Data-Dependent Acquisition without Dynamic Exclusion.
Identification of pre-diagnostic metabolites associated with prostate cancer risk by untargeted mass spectrometry-based metabolomics: A case-control study nested in the Northern Sweden Health and Disease Study.
SimPLIT: Simplified Sample Preparation for Large-Scale Isobaric Tagging Proteomics.

Metabolomics. 2022 Jul 16. 18(8): 55

Prioritize biologically relevant ions for data-independent acquisition (BRI-DIA) in LC-MS/MS-based lipidomics analysis.

Likun Duan, Grace Scheidemantle, Mareca Lodge, Magdalina J Cummings, Eva Pham, Xiaoqiu Wang, Arion Kennedy, Xiaojing Liu.

INTRODUCTION: Data-dependent acquisition (DDA) is the most commonly used MS/MS scan method for lipidomics analysis on orbitrap-based instrument. However, MS instrument associated software decide the top N precursors for fragmentation, resulting in stochasticity of precursor selection and compromised consistency and reproducibility. We introduce a novel workflow using biologically relevant lipids to construct inclusion list for data-independent acquisition (DIA), named as BRI-DIA workflow.
OBJECTIVES: To ensure consistent coverage of biologically relevant lipids in LC-MS/MS-based lipidomics analysis.
METHODS: Biologically relevant ion list was constructed based on LIPID MAPS and lipidome atlas in MS-DIAL 4. Lipids were extracted from mouse tissues and used to assess different MS/MS scan workflow (DDA, BRI-DIA, and hybrid mode) on LC-Orbitrap Exploris 480 mass spectrometer.
RESULTS: DDA resulted in more MS/MS events, but the total number of unique lipids identified by three methods (DDA, BRI-DIA, and hybrid MS/MS scan mode) is comparable (580 unique lipids across 44 lipid subclasses in mouse liver). Major cardiolipin molecular species were identified by data generated using BRI-DIA and hybrid methods and allowed calculation of cardiolipin compositions, while identification of the most abundant cardiolipin CL72:8 was missing in data generated using DDA method, leading to wrong calculation of cardiolipin composition.
CONCLUSION: The method of using inclusion list comprised of biologically relevant lipids in DIA MS/MS scan is as efficient as traditional DDA method in profiling lipids, but offers better consistency of lipid identification, compared to DDA method. This study was performed using Orbitrap Exploris 480, and we will further evaluate this workflow on other platforms, and if verified by future work, this biologically relevant ion fragmentation workflow could be routinely used in many studies to improve MS/MS identification capacities.

DOI: https://doi.org/10.1007/s11306-022-01913-8
J Lipid Res. 2022 Jul 15. pii: S0022-2275(22)00088-8. [Epub ahead of print] 100255

Skin fibroblast metabolomic profiling reveals that lipid dysfunction predicts the severity of Friedreich's ataxia.

Dezhen Wang, Elaine S Ho, M Grazia Cotticelli, Peining Xu, Jill S Napierala, Lauren A Hauser, Marek Napierala, Blanca E Himes, Robert B Wilson, David R Lynch, Clementina Mesaros.

  Friedreich's ataxia (FRDA) is an autosomal recessive neurodegenerative disorder caused by a triplet guanine-adenine-adenine (GAA) repeat expansion in intron 1 of the FXN gene, which leads to decreased levels of the frataxin protein. Frataxin is involved in the formation of iron-sulfur (Fe-S) cluster prosthetic groups for various metabolic enzymes. To provide a better understanding of the metabolic status of FRDA patients, here we used patient-derived fibroblast cells as a surrogate tissue for metabolic and lipidomic profiling by liquid-chromatography high resolution-mass spectrometry (LC-HRMS). We found elevated HMG-CoA and β-hydroxybutyrate (BHB)-CoA levels, implying dysregulated fatty acid oxidation, which was further demonstrated by elevated acyl-carnitine levels. Lipidomic profiling identified dysregulated levels of several lipid classes in FRDA fibroblast cells when compared with non-FRDA fibroblast cells. For example, levels of several ceramides were significantly increased in FRDA fibroblast cells; these results positively correlated with the GAA repeat length and negatively correlated with the frataxin protein levels. Furthermore, stable isotope tracing experiments indicated increased ceramide synthesis, especially for long chain fatty acid-ceramides, in FRDA fibroblast cells compared to ceramide synthesis in healthy control fibroblast cells. In addition, PUFA containing triglycerides and phosphatidylglycerols were enriched in FRDA fibroblast cells and negatively correlated with frataxin levels, suggesting lipid remodeling as a result of FXN deficiency. Altogether, we demonstrate patient-derived fibroblast cells exhibited dysregulated metabolic capabilities, and their lipid dysfunction predicted the severity of FRDA, making them a useful surrogate to study the metabolic status in FRDA.

Keywords:  ceramides; fatty acids oxidation; frataxin; lipid remodeling; lipidomics; neurodegenerative disorders; phospholipids; stable isotope tracing; triglycerides; triplet repeat expansion

DOI:  https://doi.org/10.1016/j.jlr.2022.100255
Eur J Med Chem. 2022 Jul 16. pii: S0223-5234(22)00515-3. [Epub ahead of print]240 114613

Emerging roles of fatty acid metabolism in cancer and their targeted drug development.

Qi An, Rui Lin, Dongmei Wang, Chuan Wang.

  Metabolic reprogramming is now considered as one of hallmark of tumor cells and provides them with a selective survival/growth advantage to resist harsh micro-environmental stress. Fatty acid (FA) metabolism of tumor cells supports the biosynthetic needs and provides fuel sources for energy supply. Since FA metabolic reprogramming is a critical link in tumor metabolism, its various roles in tumors have attracted increasing interest. Herein, we review the mechanisms through which cancer cells rewire their FA metabolism with a focus on the pathway of FA metabolism and its targeting drug development. The failure and successful cases of targeting tumor FA metabolism are expected to bypass the metabolic vulnerability and improve the efficacy of targeted therapy.

Keywords:  Fatty acid; Metabolic reprograming; Targeted drug; Tumor metabolism

DOI:  https://doi.org/10.1016/j.ejmech.2022.114613
Metabolomics. 2022 Jul 21. 18(8): 59

Combining data acquisition modes in liquid-chromatography-tandem mass spectrometry for comprehensive determination of acylcarnitines in human serum.

D Luque-Córdoba, M Calderón-Santiago, F Priego-Capote.

  Acylcarnitines (ACs) are metabolites involved in fatty acid β-oxidation and organic acid metabolism. Metabolic disorders associated to these two processes can be evaluated by determining the complete profile of ACs. In this research, we present an overall strategy for identification, confirmation, and quantitative determination of acylcarnitines in human serum. By this strategy we identified the presence of 47 ACs from C2 to C24 with detection of the unsaturation degree by application of a data-independent acquisition (DIA) liquid chromatography-tandem mass spectrometry (LC-MS/MS) method. Complementary, quantitative determination of ACs is based on a high-throughput and fully automated method consisting of solid-phase extraction on-line coupled to LC-MS/MS in data-dependent acquisition (DDA) to improve analytical features avoiding the errors associated to sample processing. Quantitation limits were at pg mL-1 level, the intra-day and between-day variability were below 15-20%, respectively; and the accuracy, expressed as bias, was always within ± 25%. The proposed method was tested with 40 human volunteers to determine the relative concentration of ACs in serum and identify predominant forms. Significant differences were detected by comparing the ACs profile of obese versus non-obese individuals.

Keywords:  Acylcarnitines; Data-dependent acquisition; Data-independent acquisition; Multiple reaction monitoring; SPE–LC–MS/MS; Serum

DOI:  https://doi.org/10.1007/s11306-022-01916-5
Front Endocrinol (Lausanne). 2022 ;13 895116

Lipid Analysis of Follicular Fluids by UHPLC-ESI-HRMS Discovers Potential Biomarkers for Ovarian Hyperstimulation Syndrome.

Yue Gao, Jingjie Li, Shicheng Fan, Pan Chen, Min Huang, Huichang Bi.

  Ovarian hyperstimulation syndrome (OHSS) is a serious iatrogenic complication during ovarian stimulation. Even though the incidence of OHSS was relatively low in clinical practice, the consequence can be potentially devastating and life-threatening. Abnormal lipid metabolism may relate to the pathological development of OHSS, but there is still a research gap in the lipidomic research. So here in our study, an ultra-high-performance liquid chromatography coupled with electrospray ionization high-resolution mass spectrometry (UHPLC-ESI-HRMS) based lipidomic analysis was performed using follicular fluid samples obtained from 17 patients undergoing OHSS. The lipid profiles of OHSS patients were characterized by increased cholesterol ester (ChE) and decreased lysophosphatidylcholine (LPC), phosphatidylinositol (PI), sphingomyelin (SM), dimethylphosphatidylethanolamine (dMePE) and lysodimethylphosphatidylethanolamine (LdMePE). Totally 10 lipids including LPC(18:0), SM(d18:1/16:0), PC(18:0/18:1), PC(20:2/20:5), PC(16:0/18:1), TG(16:0/18:1/18:1), TG(16:0/18:2/18:2), TG(16:0/16:1/18:1), ChE(20:4) and TG(8:0/8:0/10:0) were selected as differential lipids. In conclusion, this study demonstrated the alteration of various lipids in OHSS patients, which suggested the key role of lipids during the development of OHSS and shed light on the further pathophysiological research of OHSS.

Keywords:  UHPLC-ESI-HRMS; biomarkers; follicular fluids; lipidomics; ovarian hyperstimulation syndrome

DOI:  https://doi.org/10.3389/fendo.2022.895116
Data Brief. 2022 Aug;43 108435

Dataset containing physiological amounts of spike-in proteins into murine C2C12 background as a ground truth quantitative LC-MS/MS reference.

Julian Uszkoreit, Katalin Barkovits, Sandra Pacharra, Kathy Pfeiffer, Simone Steinbach, Katrin Marcus, Martin Eisenacher.

  In this article, we present a data dependent acquisition (DDA) dataset which was generated as a reference and ground truth quantitative dataset. While initially used to compare samples measured with DDA and data independent acquisition (DIA) (Barkovits et al., 2020), the presented dataset holds potential value as a benchmark reference for any workflows working on DDA data. The entire dataset consists of 15 LC-MS/MS measurements composed of five distinct spike-in-states, each with three replicates. To generate the data set, a C2C12 (immortalized mouse myoblast) cell lysate was used as a complex background for five different states which were simulated by spiking 13 defined proteins at different concentrations. For this purpose, the cell lysate was used in a constant amount of 20 µg for all samples and different amounts of the 13 selected proteins ranging from 0.1 to 10 pmol were added, reflecting physiological amounts of proteins. Afterwards, all samples were tryptically digested using the same method. From each sample 200 ng tryptic peptides were measured in triplicates on a Q Exactive HF (Thermo Fisher Scientific). The mass range for MS1 was set to 350-1400 m/z with a resolution of 60,000 at 200 m/z. HCD fragmentation of the Top10 abundant precursor ions was performed at 27% NCE. The fragment analysis (MS2) was performed with a resolution of 30,000 at 200 m/z. Additionally to the raw files, the dataset contains centroided mzML files and spectrum identification results for peptide identifications performed by Mascot (Perkins et al., 1999), MS-GF+ (Kim et al., 2010) and X!Tandem (Craig and Beavis, 2004) for each separate MS analysis. The corresponding FASTA containing protein sequences as well as a combination of all identification runs performed by PIA (Uszkoreit et al., 2019, 2015) and a peptide and protein quantification performed by OpenMS (Pfeuffer et al., 2017) is included. All data have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository (Perez-Riverol et al., 2018) with the dataset identifier PXD012986.

Keywords:  C2C12 cell line; Complex proteomics standard; Mass spectrometry; Protein spike-in dataset; Proteomics; Quantitative ground truth dataset

DOI:  https://doi.org/10.1016/j.dib.2022.108435
J Nutr Biochem. 2022 Jul 17. pii: S0955-2863(22)00176-0. [Epub ahead of print] 109108

Lipidomic profiling of the hepatic esterified fatty acid composition in diet-induced nonalcoholic fatty liver disease in genetically diverse Collaborative Cross mice.

Suresh K Nagumalli, Rose A Willett, Aline de Conti, Volodymyr P Tryndyak, Mark I Avigan, Gonçalo Gamboa da Costa, Frederick A Beland, Ivan Rusyn, Igor P Pogribny.

  Nonalcoholic fatty liver disease (NAFLD), one of the most common forms of chronic liver disease, is characterized by the excessive accumulation of lipid species in hepatocytes. Recent studies have indicated that in addition to the total lipid quantities, changes in lipid composition are a determining factor in hepatic lipotoxicity. Using ultra-high performance liquid chromatography coupled with electrospray tandem mass spectrometry, we analyzed the esterified fatty acid composition in 24 strains of male and female Collaborative Cross (CC) mice fed a high fat/high sucrose (HF/HS) diet for 12 weeks. Changes in lipid composition were found in all strains after the HF/HS diet, most notably characterized by increases in monounsaturated fatty acids (MUFA) and decreases in polyunsaturated fatty acids (PUFA). Similar changes in MUFA and PUFA were observed in a choline- and folate-deficient (CFD) mouse model of NAFLD, as well as in hepatocytes treated in vitro with free fatty acids. Analysis of fatty acid composition revealed that alterations were accompanied by an increase in the estimated activity of MUFA generating SCD1 enzyme and an estimated decrease in the activity of PUFA generating FADS1 and FADS2 enzymes. PUFA/MUFA ratios were inversely correlated with lipid accumulation in male and female CC mice fed the HF/HS diet and with morphological markers of hepatic injury in CFD diet-fed mouse model of NAFLD. These results demonstrate that different models of NAFLD are characterized by similar changes in the esterified fatty acid composition and that alterations in PUFA/MUFA ratios may serve as a diagnostic marker for NAFLD severity.

Keywords:  Nonalcoholic fatty liver disease; diet and dietary lipids; fatty acids; fatty liver; lipidomics; mouse genetics

DOI:  https://doi.org/10.1016/j.jnutbio.2022.109108
Anal Bioanal Chem. 2022 Jul 18.

Potential of atmospheric pressure ionization sources for the analysis of free fatty acids in clinical and biological samples by gas chromatography-mass spectrometry.

Paul E Görs, Pia Wittenhofer, Juan F Ayala-Cabrera, Sven W Meckelmann.

  Because of the central role of fatty acids in biological systems, their accurate quantification is still important. However, the impact of the complex matrix of biologically and clinically relevant samples such as plasma, serum, or cells makes the analysis still challenging, especially, when free non-esterified fatty acids have to be quantified. Here we developed and characterized a novel GC-MS method using pentafluorobenzyl bromide as a derivatization agent and compared different ionization techniques such as atmospheric pressure chemical ionization (APCI), atmospheric pressure chemical photoionization (APPI), and negative ion chemical ionization (NICI). The GC-APCI-MS showed the lowest limits of detection from 30 to 300 nM for a broad range of fatty acids and a similar response for various fatty acids from a chain length of 10 to 20 carbon atoms. This allows the number of internal standards necessary for accurate quantification to be reduced. Moreover, the use of pentafluorobenzyl bromide allows the direct derivatization of free fatty acids making them accessible for GC-MS analysis without labor-intense sample pretreatment.

Keywords:  Fatty acids; Gas chromatography; Lipidomics; Non-esterified fatty acids; Pentafluorobenzyl bromide; Systems biology

DOI:  https://doi.org/10.1007/s00216-022-04223-z
Talanta. 2022 Jul 08. pii: S0039-9140(22)00516-1. [Epub ahead of print]250 123720

Simultaneous quantification of 70 elements in biofluids within 5 min using inductively coupled plasma mass spectrometry to reveal elementomic phenotypes of healthy Chinese adults.

Jiahui Liu, Lan Peng, Qi Wang, Xu-Dong Wang, Huiru Tang.

  High-throughput quantification of the composition of all chemical elements (elementome) in biological samples is essential for understanding their diverse functions in large cohort studies. We, here, established an ICP-MS method to simultaneously quantify 70 elements in 50 μL biofluids within 5 min. This validated method had excellent quantification linearity (R2 > 0.998), sensitivity (with LOD as low as 1.0 ng/L), precision (CV<15%), accuracy (|RE|<20% except Hg), recovery (80-120%), throughput and coverage with minute samples. The method also showed good applicability to multiple biofluids including human serum, plasma, urine and goat serum samples. By using this method, we furture measured 70 elements in blood plasma samples from 758 Chinese adult participants and established the first reference intervals for the concentration of these elements from 127 healthy adults in this population. This offers a high-throughput quantitative elementomics method to define population elementomic phenotypes and for investigating the diverse biological functions of many elements in multiple biological matrices.

Keywords:  Elementomics; ICP-MS; Reference intervals; Serum and plasma; Simultaneous quantification

DOI:  https://doi.org/10.1016/j.talanta.2022.123720
J Pharm Biomed Anal. 2022 Jul 16. pii: S0731-7085(22)00365-X. [Epub ahead of print]219 114944

A sensitive UPLC-MS/MS method for simultaneous quantification of one-carbon metabolites & co-factors in human plasma.

Ping Chen, Yun Tang, Qiangqiang He, Lishun Liu, Ziyi Zhou, Yun Song, Nan Zhang, Binyan Wang, Houqing Zhou, Hanping Shi, Jie Jiang.

  One-carbon metabolism is an important metabolic pathway involved in many diseases, such as congenital malformations, tumours, cardiovascular diseases, anaemia, depression, cognitive diseases and liver disease. However, the current methods have specific defects in detecting and qualifying the related compounds of one-carbon metabolism. In this study, a validated method was established to simultaneously quantify 22 one-carbon metabolites & co-factors in human plasma and applied to the study of correlation between one-carbon metabolism and colorectal cancer in human plasma samples, which were from 44 healthy subjects and 55 colorectal cancer patients. The method used ultra-high performance liquid chromatography coupled with triple quadrupole mass spectrometry (UPLC-MS/MS), and the analytes included betaine, L-carnitine, L-cystathionine, L-cysteine, dimethylglycine, DL-homocysteic acid, homocysteine, methionine, pyridoxal hydrochloride, pyridoxamine dihydrochloride, pyridoxine dihydrochloride, S-(5'-Adenosyl)-L-homocysteine, serine, choline chloride, folic acid, glycine, pyridoxal phosphate monohydrate, riboflavin, taurine, 5-methyltetrahydrofolate, S-(5'-adenosyl)-L-methionine disulfate salt, trimethylamine oxide. The developed method was successfully applied to the quantification of 22 one-carbon metabolites & co-factors in human plasma from colorectal cancer patients and healthy individuals. The plasma concentrations of dimethylglycine was significantly decreased in the patients compared with the healthy individuals, while L-cystathionine was increased.

Keywords:  Folic acid; Homocysteine; Human plasma; LC-MS/MS; One-carbon metabolism

DOI:  https://doi.org/10.1016/j.jpba.2022.114944
Hepatol Commun. 2022 Jul 21.

Co-regulation of hepatic steatosis by ferritinophagy and unsaturated fatty acid supply.

Ning Li, Yilie Liao, Haipeng Huang, Suneng Fu.

Both iron overload and iron deficiency have been reported in obesity and metabolic syndromes. Due to the presence of multiple intracellular iron pools and the dynamic nature of iron mobilization and use, the actual status and contribution of free and metabolically active iron toward metabolic syndrome remain to be established. The discovery of nuclear receptor coactivator 4 (NCOA4) as a ferritinophagy receptor provides an opening to address the connection between iron and metabolic diseases. This study aims to specifically dissect the role of hepatic ferritinophagy in lipid metabolism and hepatic steatosis. We conducted a series of Ncoa4 gain- and loss-of-function experiments to examine how ferritinophagy affects lipid metabolism through phenotypic and lipidomic analyses both in vitro and in vivo. We show that ferritinophagy is required to release iron from ferritin cages for biological use, and is induced by lipid loading in vitro and during the development of obesity in vivo. Ncoa4 knockdown impairs mitochondrial morphology and reduces palmitate-induced lipid droplet formation in cultured cells and the development of hepatic steatosis in obese mice models. Importantly, the effect of Ncoa4 deficiency on mitochondrial morphology and lipid accumulation is specifically linked to lipidomic reductions in unsaturated fatty acid content in triglycerides and cardiolipins, and an external supply of unsaturated fatty acids reverses these phenotypes. Conclusion: This study shows that ferritinophagy-derived iron supports fatty acid desaturation and the synthesis of unsaturated fatty acid-rich lipids to reduce lipotoxicity. However, the continuous activation of ferritinophagy contributes to the development of hepatic steatosis and liver damage in obesity.

DOI: https://doi.org/10.1002/hep4.2040
Nature. 2022 Jul 20.

Sestrin mediates detection of and adaptation to low-leucine diets in Drosophila.

Xin Gu, Patrick Jouandin, Pranav V Lalgudi, Rich Binari, Max L Valenstein, Michael A Reid, Annamarie E Allen, Nolan Kamitaki, Jason W Locasale, Norbert Perrimon, David M Sabatini.

Mechanistic target of rapamycin complex 1 (mTORC1) regulates cell growth and metabolism in response to multiple nutrients, including the essential amino acid leucine1. Recent work in cultured mammalian cells established the Sestrins as leucine-binding proteins that inhibit mTORC1 signalling during leucine deprivation2,3, but their role in the organismal response to dietary leucine remains elusive. Here we find that Sestrin-null flies (Sesn-/-) fail to inhibit mTORC1 or activate autophagy after acute leucine starvation and have impaired development and a shortened lifespan on a low-leucine diet. Knock-in flies expressing a leucine-binding-deficient Sestrin mutant (SesnL431E) have reduced, leucine-insensitive mTORC1 activity. Notably, we find that flies can discriminate between food with or without leucine, and preferentially feed and lay progeny on leucine-containing food. This preference depends on Sestrin and its capacity to bind leucine. Leucine regulates mTORC1 activity in glial cells, and knockdown of Sesn in these cells reduces the ability of flies to detect leucine-free food. Thus, nutrient sensing by mTORC1 is necessary for flies not only to adapt to, but also to detect, a diet deficient in an essential nutrient.

DOI: https://doi.org/10.1038/s41586-022-04960-2
Cell Death Discov. 2022 Jul 19. 8(1): 327

Interplay of Nrf2 and BACH1 in inducing ferroportin expression and enhancing resistance of human macrophages towards ferroptosis.

Dmitry Namgaladze, Dominik C Fuhrmann, Bernhard Brüne.

Compared to cancer cells, macrophages are inert to lipid peroxidation-triggered, iron-dependent cell death known as ferroptosis. Mechanisms underlying macrophage resistance towards ferroptosis are largely obscure. Here, we show that human primary macrophages respond to RSL3, a ferroptosis-inducing inhibitor of glutathione peroxidase 4, by upregulating mRNA expression of the iron transporter ferroportin. RSL3 induces lipid peroxidation, and both, lipid peroxidation as well as ferroportin induction were attenuated by liproxstatin-1, an inhibitor of lipid peroxidation and ferroptosis blocker. At the same time, system xc- inhibitor erastin fails to elicit lipid peroxidation or ferroportin expression. Ferroportin induction in response to RSL3 demands nuclear accumulation of the redox-sensitive transcription factor Nrf2 and downregulation of the transcriptional repressor BACH1. Silencing ferroportin or Nrf2 increases the cellular labile iron pool and lipid peroxidation, thereby sensitizing cells towards ferroptosis following RSL3 treatments. In contrast, silencing BACH1 decreases the labile iron pool and lipid peroxidation, enhancing macrophage resistance towards ferroptosis. Our findings reveal Nrf2, BACH1, and ferroportin as important regulators, protecting human macrophages against ferroptosis.

DOI: https://doi.org/10.1038/s41420-022-01117-y
Curr Protoc. 2022 Jul;2(7): e506

Bioinformatic Analysis to Investigate Metaproteome Composition Using Trans-Proteomic Pipeline.

Steven He, Shoba Ranganathan.

  With evidence emerging that the microbiome has a role in the onset of many human diseases, including cancer, analyzing these microbial communities and their proteins (i.e., the metaproteome) has become a powerful research tool. The Trans-Proteomic Pipeline (TPP) is a free, comprehensive software suite that facilitates the analysis of mass spectrometry (MS) data. By utilizing available microbial proteomes, TPP can identify microbial proteins and species, with an acceptable peptide false-discovery rate (FDR). An application to a publicly available oral cancer dataset is presented as an example to identify the viral metaproteome on the oral cancer invasive tumor front. © 2022 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Collection of data and resources Basic Protocol 2: Analysis of MS data using TPP Basic Protocol 3: Analysis of TPP output using R in RStudio.

Keywords:  mass spectrometry; metaproteomics; microbial species

DOI:  https://doi.org/10.1002/cpz1.506
Anal Chem. 2022 Jul 18.

Mapping Protein-Protein Interactions Using Data-Dependent Acquisition without Dynamic Exclusion.

Shen Zhang, Brett Larsen, Karen Colwill, Cassandra J Wong, Ji-Young Youn, Anne-Claude Gingras.

Systematic analysis of affinity-purified samples by liquid chromatography coupled to mass spectrometry (LC-MS) requires high coverage, reproducibility, and sensitivity. While data-independent acquisition (DIA) approaches improve the reproducibility of protein-protein interaction detection as compared to standard data-dependent acquisition approaches, the need for library generation reduces their throughput, and analysis pipelines are still being optimized. In this study, we report the development of a simple and robust approach, termed turboDDA, to improve interactome analysis using spectral counting and data-dependent acquisition (DDA) by eliminating the dynamic exclusion (DE) step and optimizing the acquisition parameters. Using representative interaction and proximity proteomics samples, we detected increases in identified interactors of 18-71% compared to all samples analyzed by standard DDA with dynamic exclusion and for most samples analyzed by DIA with the MSPLIT-DIA spectral counting approach. In summary, turboDDA provides better sensitivity and identifies more high-confident interactors than the optimized DDA with DE and comparable or better sensitivity than DIA spectral counting approaches.

DOI: https://doi.org/10.1021/acs.analchem.2c00755
Int J Cancer. 2022 Jul 22.

Identification of pre-diagnostic metabolites associated with prostate cancer risk by untargeted mass spectrometry-based metabolomics: A case-control study nested in the Northern Sweden Health and Disease Study.

Johnny R Östman, Rui C Pinto, Timothy Md Ebbels, Elin Thysell, Göran Hallmans, Ali A Moazzami.

  Prostate cancer (PCa) is the most common cancer form in males in many European and American countries, but there are still open questions regarding its etiology. Untargeted metabolomics can produce an unbiased global metabolic profile, with the opportunity for uncovering new plasma metabolites prospectively associated with risk of PCa, providing insights into disease etiology. We conducted a prospective untargeted liquid chromatography-mass spectrometry (LC-MS) metabolomics analysis using pre-diagnostic fasting plasma samples from 752 PCa case-control pairs nested within the Northern Sweden Health and Disease Study (NSHDS). The pairs were matched by age, BMI, and sample storage time. Discriminating features were identified by a combination of orthogonal projection to latent structures-effect projections (OPLS-EP) and Wilcoxon signed-rank tests. Their prospective associations with PCa risk were investigated by conditional logistic regression. Subgroup analyses based on stratification by disease aggressiveness and baseline age were also conducted. Various free fatty acids and phospholipids were positively associated with overall risk of PCa and in various stratification subgroups. Aromatic amino acids were positively associated with overall risk of PCa. Uric acid was positively, and glucose negatively, associated with risk of PCa in the older subgroup. This is the largest untargeted LC-MS based metabolomics study to date on plasma metabolites prospectively associated with risk of developing PCa. Different subgroups of disease aggressiveness and baseline age showed different associations with metabolites. The findings suggest that shifts in plasma concentrations of metabolites in lipid, aromatic amino acid, and glucose metabolism are associated with risk of developing PCa during following two decades. This article is protected by copyright. All rights reserved.

Keywords:  Liquid chromatography-mass spectrometry; Nested case-control study; Prostate cancer; Risk biomarkers; Untargeted metabolomics

DOI:  https://doi.org/10.1002/ijc.34223
J Proteome Res. 2022 Jul 18.

SimPLIT: Simplified Sample Preparation for Large-Scale Isobaric Tagging Proteomics.

Fernando J Sialana, Theodoros I Roumeliotis, Habib Bouguenina, Laura Chan Wah Hak, Hannah Wang, John Caldwell, Ian Collins, Rajesh Chopra, Jyoti S Choudhary.

  Large scale proteomic profiling of cell lines can reveal molecular signatures attributed to variable genotypes or induced perturbations, enabling proteogenomic associations and elucidation of pharmacological mechanisms of action. Although isobaric labeling has increased the throughput of proteomic analysis, the commonly used sample preparation workflows often require time-consuming steps and costly consumables, limiting their suitability for large scale studies. Here, we present a simplified and cost-effective one-pot reaction workflow in a 96-well plate format (SimPLIT) that minimizes processing steps and demonstrates improved reproducibility compared to alternative approaches. The workflow is based on a sodium deoxycholate lysis buffer and a single detergent cleanup step after peptide labeling, followed by quick off-line fractionation and MS2 analysis. We showcase the applicability of the workflow in a panel of colorectal cancer cell lines and by performing target discovery for a set of molecular glue degraders in different cell lines, in a 96-sample assay. Using this workflow, we report frequently dysregulated proteins in colorectal cancer cells and uncover cell-dependent protein degradation profiles of seven cereblon E3 ligase modulators (CRL4CRBN). Overall, SimPLIT is a robust method that can be easily implemented in any proteomics laboratory for medium-to-large scale TMT-based studies for deep profiling of cell lines.

Keywords:  CELMoDs; IMiDs; TMTpro; cancer cell lines; isobaric labeling; targeted protein degradation

DOI:  https://doi.org/10.1021/acs.jproteome.2c00092