bims-mascan 2023-10-15 papers

bims-mascan

Biomed News

on Mass spectrometry in cancer research

Issue of 2023‒10‒15
29 papers selected by
Giovanny Rodriguez Blanco, University of Edinburgh

Quantitative Analysis of Acetyl-CoA, Malonyl-CoA, and Succinyl-CoA in Myocytes.
A large-scale, targeted metabolomics method for the analysis and quantification of metabolites in human plasma via liquid chromatography-mass spectrometry.
[Advances of peptide-centric data-independent acquisition analysis algorithms and software tools].
Ultrasensitive quantification of estrogens in serum and plasma by liquid chromatography-tandem mass spectrometry.
High sensitivity LC-MS methods for quantitation of hydroxy- and keto-androgens.
Glutamine metabolism in tumor metastasis: Genes, mechanisms and the therapeutic targets.
Sage: An Open-Source Tool for Fast Proteomics Searching and Quantification at Scale.
Proteomics analysis of an individual formalin-fixed paraffin-embedded tissue section using isobaric-tag amplification.
Inclusion of Porous Graphitic Carbon Chromatography Yields Greater Protein Identification and Compartment and Process Coverage and Enables More Reflective Protein-Level Label-Free Quantitation.
Absolute Quantification of Pan-Cancer Plasma Proteomes Reveals Unique Signature in Multiple Myeloma.
Intracellular metabolic profiling of drug resistant cells by surface enhanced Raman scattering.
The Combined Inhibition of Autophagy and Diacylglycerol Acyltransferase-Mediated Lipid Droplet Biogenesis Induces Cancer Cell Death during Acute Amino Acid Starvation.
CancerProteome: a resource to functionally decipher the proteome landscape in cancer.
Parallelized Acquisition of Orbitrap and Astral Analyzers Enables High-Throughput Quantitative Analysis.
Multi-Method Quantification of Acetyl-Coenzyme A and Further Acyl-Coenzyme A Species in Normal and Ischemic Rat Liver.
Quantification of Oligonucleotides Using Tandem Mass Spectrometry with Isobaric Internal Standards.
MsQuality - an interoperable open-source package for the calculation of standardized quality metrics of mass spectrometry data.
A comprehensive spectral assay library to quantify the Halobacterium salinarum NRC-1 proteome by DIA/SWATH-MS.
Clickable Glutathione-Based Identification of Cysteine Glutathionylation.
The yin and yang of itaconate metabolism and its impact on the tumor microenvironment.
Cellular signaling in the hypoxic cancer microenvironment: Implications for drug resistance and therapeutic targeting.
Editorial: The role of one-carbon metabolism in cancer progression, therapy, and resistance.
Database-assisted, globally optimized targeted secondary electrospray ionization high resolution mass spectrometry (dGOT-SESI-HRMS) and spectral stitching enhanced volatilomics analysis of bacterial metabolites.
SWATH-MS Analysis of Blood Plasma and Circulating Small Extracellular Vesicles Enables Detection of Putative Protein Biomarkers of Fertility in Young and Aged Dairy Cows.
Deep Proteomic Compound Profiling with the Orbitrap Ascend Tribrid Mass Spectrometer Using Tandem Mass Tags and Real-Time Search.
[Effect of viral infection on host cell metabolism: a review].
Stearoyl-CoA desaturase 1 inhibition impairs triacylglycerol accumulation and lipid droplet formation in colorectal cancer cells.
Approaches to assessing 3β-hydroxysteroid dehydrogenase-1.
Arginine reprograms metabolism in liver cancer via RBM39.

J Am Soc Mass Spectrom. 2023 Oct 09.

Quantitative Analysis of Acetyl-CoA, Malonyl-CoA, and Succinyl-CoA in Myocytes.

Lin Tan, Sara A Martinez, Philip L Lorenzi, Anja Karlstaedt.

Several analytical challenges make it difficult to accurately measure coenzyme A (CoA) metaboforms, including insufficient stability and a lack of available metabolite standards. Consequently, our understanding of CoA biology and the modulation of human diseases may be nascent. CoA's serve as lipid precursors, energy intermediates, and mediators of post-translational modifications of proteins. Here, we present a liquid chromatography-mass spectrometry (LC-MS) approach to measure malonyl-CoA, acetyl-CoA, and succinyl-CoA in complex biological samples. Additionally, we evaluated workflows to increase sample stability. We used reference standards to optimize CoA assay sensitivity and test CoA metabolite stability as a function of the reconstitution solvent. We show that using glass instead of plastic sample vials decreases CoA signal loss and improves the sample stability. We identify additives that improve CoA stability and facilitate accurate analysis of CoA species across large sample sets. We apply our optimized workflow to biological samples of skeletal muscle cells cultured under hypoxic and normoxia conditions. Together, our workflow improves the detection and identification of CoA species through targeted analysis in complex biological samples.

DOI: https://doi.org/10.1021/jasms.3c00278
Anal Chim Acta. 2023 Oct 23. pii: S0003-2670(23)01012-7. [Epub ahead of print]1279 341791

A large-scale, targeted metabolomics method for the analysis and quantification of metabolites in human plasma via liquid chromatography-mass spectrometry.

Teresa S McMillen, Andrew Leslie, Kenneth Chisholm, Susanne Penny, Jeffrey Gallant, Alejandro Cohen, Arik Drucker, James P Fawcett, Devanand M Pinto.

  Metabolomics is the study of small molecules, primarily metabolites, that are produced during metabolic processes. Analysis of the composition of an organism's metabolome can yield useful information about an individual's health status at any given time. In recent years, the development of large-scale, targeted metabolomic methods has allowed for the analysis of biological samples using analytical techniques such as LC-MS/MS. This paper presents a large-scale metabolomics method for analysis of biological samples, with a focus on quantification of metabolites found in blood plasma. The method comprises a 10-min chromatographic separation using HILIC and RP stationary phases combined with positive and negative electrospray ionization in order to maximize metabolome coverage. Complete analysis of a single sample can be achieved in as little as 40 min using the two columns and dual modes of ionization. With 540 metabolites and the inclusion of over 200 analytical standards, this method is comprehensive and quantitatively robust when compared to current targeted metabolomics methods. This study uses a large-scale evaluation of metabolite recovery from plasma that enables absolute quantification of metabolites by correcting for analyte loss throughout processes such as extraction, handling, or storage. In addition, the method was applied to plasma collected from adjuvant breast cancer patients to confirm the suitability of the method to clinical samples.

Keywords:  Chromatography; Mass spectrometry; Targeted metabolomics

DOI:  https://doi.org/10.1016/j.aca.2023.341791
Sheng Wu Gong Cheng Xue Bao. 2023 Sep 25. 39(9): 3579-3593

[Advances of peptide-centric data-independent acquisition analysis algorithms and software tools].

Yingying Zhang, Kunxian Shu, Cheng Chang.

  Data-independent acquisition (DIA) is a high-throughput, unbiased mass spectrometry data acquisition method which has good quantitative reproducibility and is friendly to low-abundance proteins. It becomes the preferred choice for clinical proteomic studies especially for large cohort studies in recent years. The mass-spectrometry (MS)/MS spectra generated by DIA is usually heavily mixed with fragment ion information of multiple peptides, which makes the protein identification and quantification more difficult. Currently, DIA data analysis methods fall into two main categories, namely peptide-centric and spectrum-centric. The peptide-centric strategy is more sensitive for identification and more accurate for quantification. Thus, it has become the mainstream strategy for DIA data analysis, which includes four key steps: building a spectral library, extracting ion chromatogram, feature scoring and statistical quality control. This work reviews the peptide-centric DIA data analysis procedure, introduces the corresponding algorithms and software tools, and summarizes the improvements for the existing algorithms. Finally, the future development directions are discussed.

Keywords:  computational proteomics; data-independent acquisition; peptide-centric; quantitative proteomics

DOI:  https://doi.org/10.13345/j.cjb.230079
Methods Enzymol. 2023 ;pii: S0076-6879(23)00135-0. [Epub ahead of print]689 433-452

Ultrasensitive quantification of estrogens in serum and plasma by liquid chromatography-tandem mass spectrometry.

Qingqing Wang, Peining Jimmy Xu, Clementina Mesaros.

  Stable isotope dilution (SID) methodology coupled with liquid chromatography-tandem mass spectrometry (LC-MS) is rapidly becoming the gold standard for measuring estrogens in serum and plasma due to improved specificity, high accuracy, and the ability to conduct a more comprehensive analysis. A general consideration of the problems associated with measuring estrogens and two detailed derivatization methods are described in this chapter. These methods quantify estrogens and their metabolites in serum and plasma samples using this state-of-art technology, which is applicable to the routine clinical laboratory.

Keywords:  Estradiol; Estrone; Liquid chromatography; Mass spectrometry; Multiple reaction monitoring

DOI:  https://doi.org/10.1016/bs.mie.2023.04.011
Methods Enzymol. 2023 ;pii: S0076-6879(23)00133-7. [Epub ahead of print]689 355-376

High sensitivity LC-MS methods for quantitation of hydroxy- and keto-androgens.

Andrea J Detlefsen, Ryan D Paulukinas, Clementina Mesaros.

  The quantitation of androgens is necessary to diagnose and monitor the development of diseases such as prostate cancer and polycystic ovary syndrome. Androgen measurements also support the laboratory-based study of androgen metabolism in cellular and animal models. The methods described in this chapter combine chemical derivatization of hydroxy- and keto-androgens with stable isotope dilution liquid chromatography mass spectrometry (SID-LC-MS). Chemical derivatization of hydroxy-androgens by picolinic acid and keto-androgens by Girard P enhances the ionization and detection sensitivity of androgens, while chromatographic separation and [13C]-labeled internal standards add specificity that allow for simultaneous quantitation of multiple androgens. This chapter describes the materials and protocols necessary for chemical derivatization, enzymatic synthesis of internal standards, and LC-MS detection of keto- and hydroxy-androgens.

Keywords:  Girard P derivatization; Hydroxy-androgens; Keto-androgens; Liquid chromatography mass spectrometry; Picolinic derivatization

DOI:  https://doi.org/10.1016/bs.mie.2023.04.009
Heliyon. 2023 Oct;9(10): e20656

Glutamine metabolism in tumor metastasis: Genes, mechanisms and the therapeutic targets.

Xugang Zhong, Zeju He, Li Yin, Yong Fan, Yu Tong, Yao Kang, Qing Bi.

  Cancer cells frequently change their metabolism from aerobic glycolysis to lipid metabolism and amino acid metabolism to adapt to the malignant biological behaviours of infinite proliferation and distant metastasis. The significance of metabolic substances and patterns in tumour cell metastasis is becoming increasingly prominent. Tumour metastasis involves a series of significant steps such as the shedding of cancer cells from a primary tumour, resistance to apoptosis, and colonisation of metastatic sites. However, the role of glutamine in these processes remains unclear. This review summarises the key enzymes and transporters involved in glutamine metabolism that are related to the pathogenesis of malignant tumour metastasis. We also list the roles of glutamine in resisting oxidative stress and promoting immune escape. Finally, the significance of targeting glutamine metabolism in inhibiting tumour metastasis was proposed, research in this field improving our understanding of amino acid metabolism rewiring and simultaneously bringing about new and exciting therapeutic prospects.

Keywords:  Amino acid metabolism; Cancer metastasis; Glutamine; Metabolic therapy; Precision medicine

DOI:  https://doi.org/10.1016/j.heliyon.2023.e20656
J Proteome Res. 2023 Oct 11.

Sage: An Open-Source Tool for Fast Proteomics Searching and Quantification at Scale.

Michael R Lazear.

  The growing complexity and volume of proteomics data necessitate the development of efficient software tools for peptide identification and quantification from mass spectra. Given their central role in proteomics, it is imperative that these tools are auditable and extensible─requirements that are best fulfilled by open-source and permissively licensed software. This work presents Sage, a high-performance, open-source, and freely available proteomics pipeline. Scalable and cloud-ready, Sage matches the performance of state-of-the-art software tools while running an order of magnitude faster.

Keywords:  bioinformatics; mass spectrometry; open search; peptide identification; peptide quantification; proteomics; search engine

DOI:  https://doi.org/10.1021/acs.jproteome.3c00486
Rapid Commun Mass Spectrom. 2023 Nov 30. 37(22): e9616

Proteomics analysis of an individual formalin-fixed paraffin-embedded tissue section using isobaric-tag amplification.

Ara Cho, Jinsung Ahn, Andrew Kim, Jeong Hyun Lee, Han Suk Ryu, Kristine M Kim, Eugene C Yi.

RATIONALE: The comprehensive analysis of formalin-fixed paraffin-embedded (FFPE) tissues is essential for retrospective clinical studies. However, detecting low-abundance proteins and obtaining proteome-scale data from FFPE samples pose analytical challenges in mass spectrometry-based proteomics. To overcome this challenge, our study focuses on implementing an isobaric labeling approach to improve the detection of low-abundance target proteins in FFPE tissues, thereby enhancing the qualitative and quantitative analysis.METHODS: We employed an isobaric labeling approach utilizing synthetic peptides or proteins to enable the qualitative and quantitative measurement of target proteins in FFPE tissue samples. To achieve this, we incorporated tandem mass tag (TMT)-labeled recombinant proteins or synthetic peptides into TMT-labeled metastatic breast cancer FFPE tissues. Through this strategy, we successfully detect coexisting CD276 (B7-H3) and CD147 proteins while identifying over 6000 proteins using targeted analysis of individual FFPE tissue sections.
RESULTS: Our findings provide compelling evidence that the incorporation of isobaric labeling, along with the inclusion of TMT-labeled peptides or proteins, greatly enhances the detection of target proteins in FFPE tissue samples. By employing this approach, we were able to obtain robust qualitative measurements of CD276 and CD147 proteins, showcasing its effectiveness in identifying more than 6000 proteins in FFPE samples.
CONCLUSIONS: The integration of an isobaric labeling approach, in conjunction with synthetic peptides or proteins, presents a valuable strategy for enhancing the detection and validation of target proteins in FFPE tissue analysis. This technique holds immense potential in retrospective clinical studies, as it enables comprehensive analysis of low-abundance proteins and facilitating proteome-scale investigations in FFPE samples. By leveraging this methodology, researchers can unlock new insights into disease mechanisms and advance our understanding of complex biological processes.

DOI: https://doi.org/10.1002/rcm.9616
J Proteome Res. 2023 Oct 10.

Inclusion of Porous Graphitic Carbon Chromatography Yields Greater Protein Identification and Compartment and Process Coverage and Enables More Reflective Protein-Level Label-Free Quantitation.

Daniel G Delafield, Hannah N Miles, William A Ricke, Lingjun Li.

  The ubiquity of mass spectrometry-based bottom-up proteomic analyses as a component of biological investigation mandates the validation of methodologies that increase acquisition efficiency, improve sample coverage, and enhance profiling depth. Chromatographic separation is often ignored as an area of potential improvement, with most analyses relying on traditional reversed-phase liquid chromatography (RPLC); this consistent reliance on a single chromatographic paradigm fundamentally limits our view of the observable proteome. Herein, we build upon early reports and validate porous graphitic carbon chromatography (PGC) as a facile means to substantially enhance proteomic coverage without changes to sample preparation, instrument configuration, or acquisition methods. Analysis of offline fractionated cell line digests using both separations revealed an increase in peptide and protein identifications by 43% and 24%, respectively. Increased identifications provided more comprehensive coverage of cellular components and biological processes independent of protein abundance, highlighting the substantial quantity of proteomic information that may go undetected in standard analyses. We further utilize these data to reveal that label-free quantitative analyses using RPLC separations alone may not be reflective of actual protein constituency. Together, these data highlight the value and comprehension offered through PGC-MS proteomic analyses. RAW proteomic data have been uploaded to the MassIVE repository with the primary accession code MSV000091495.

Keywords:  LC-MS; data completeness; liquid chromatography; mass spectrometry; porous graphitic carbon; proteomics

DOI:  https://doi.org/10.1021/acs.jproteome.3c00373
Cancers (Basel). 2023 Sep 28. pii: 4764. [Epub ahead of print]15(19):

Absolute Quantification of Pan-Cancer Plasma Proteomes Reveals Unique Signature in Multiple Myeloma.

David Kotol, Jakob Woessmann, Andreas Hober, María Bueno Álvez, Khue Hua Tran Minh, Fredrik Pontén, Linn Fagerberg, Mathias Uhlén, Fredrik Edfors.

  Mass spectrometry based on data-independent acquisition (DIA) has developed into a powerful quantitative tool with a variety of implications, including precision medicine. Combined with stable isotope recombinant protein standards, this strategy provides confident protein identification and precise quantification on an absolute scale. Here, we describe a comprehensive targeted proteomics approach to profile a pan-cancer cohort consisting of 1800 blood plasma samples representing 15 different cancer types. We successfully performed an absolute quantification of 253 proteins in multiplex. The assay had low intra-assay variability with a coefficient of variation below 20% (CV = 17.2%) for a total of 1013 peptides quantified across almost two thousand injections. This study identified a potential biomarker panel of seven protein targets for the diagnosis of multiple myeloma patients using differential expression analysis and machine learning. The combination of markers, including the complement C1 complex, JCHAIN, and CD5L, resulted in a prediction model with an AUC of 0.96 for the identification of multiple myeloma patients across various cancer patients. All these proteins are known to interact with immunoglobulins.

Keywords:  DIA; multiple myeloma; precision medicine; targeted proteomics

DOI:  https://doi.org/10.3390/cancers15194764
Anal Chim Acta. 2023 Oct 23. pii: S0003-2670(23)01030-9. [Epub ahead of print]1279 341809

Intracellular metabolic profiling of drug resistant cells by surface enhanced Raman scattering.

Fugang Liu, Tingyu Wu, Ao Tian, Chang He, Xinyuan Bi, Yao Lu, Kai Yang, Weiliang Xia, Jian Ye.

  BACKGROUND: Intracellular metabolic profiling reveals real-time metabolic information useful for the study of underlying mechanisms of cells in particular conditions such as drug resistance. However, mass spectrometry (MS), one of the leading metabolomics technologies, usually requires a large number of cells and complex pretreatments. Surface enhanced Raman scattering (SERS) has an ultrahigh detection sensitivity and specificity, favorable for metabolomics analysis. However, some targeted SERS methods focus on very limited metabolite without global bioprofiling, and some label-free approaches try to fingerprint the metabolic response based on whole SERS spectral classification, but comprehensive interpretation of biological mechanisms was lacking. (95) RESULTS: We proposed a label-free SERS technique for intracellular metabolic profiling in complex cellular lysates within 3 min. We first compared three kinds of cellular lysis methods and sonication lysis shows the highest extraction efficiency of metabolites. To obtain comprehensive metabolic information, we collected a spectral set for each sample and further qualified them by the Pearson correlation coefficient (PCC) to calculate how many spectra should be acquired at least to gain the adequate information from a statistical and global view. In addition, according to our measurements with 10 pure metabolites, we can understand the spectra acquired from complex cellular lysates of different cell lines more precisely. Finally, we further disclosed the variations of 22 SERS bands in enzalutamide-resistant prostate cancer cells and some are associated with the androgen receptor signaling activity and the methionine salvage pathway in the drug resistance process, which shows the same metabolic trends as MS. (149) SIGNIFICANCE: Our technique has the capability to capture the intracellular metabolic fingerprinting with the optimized lysis approach and spectral set collection, showing high potential in rapid, sensitive and global metabolic profiling in complex biosamples and clinical liquid biopsy. This gives a new perspective to the study of SERS in insightful understanding of relevant biological mechanisms. (54).

Keywords:  Drug resistance; Metabolic profiling; Nanoparticles; Surface enhanced Raman scattering

DOI:  https://doi.org/10.1016/j.aca.2023.341809
Cancers (Basel). 2023 Oct 05. pii: 4857. [Epub ahead of print]15(19):

The Combined Inhibition of Autophagy and Diacylglycerol Acyltransferase-Mediated Lipid Droplet Biogenesis Induces Cancer Cell Death during Acute Amino Acid Starvation.

Maida Jusović, Pia Starič, Eva Jarc Jovičić, Toni Petan.

  Lipid droplets (LDs) are dynamic organelles involved in the management of fatty acid trafficking and metabolism. Recent studies suggest that autophagy and LDs serve complementary roles in the protection against nutrient stress, but the autophagy-LD interplay in cancer cells is not well understood. Here, we examined the relationship between autophagy and LDs in starving HeLa cervical cancer- and MDA-MB-231 breast cancer cells. We found that acute amino acid depletion induces autophagy and promotes diacylglycerol acyltransferase 1 (DGAT1)-mediated LD accumulation in HeLa cells. Inhibition of autophagy via late-stage autophagy inhibitors, or by knocking down autophagy-related 5 (ATG5), reduced LD accumulation in amino acid-starved cancer cells, suggesting that autophagy contributes to LD biogenesis. On the contrary, knockdown of adipose triglyceride lipase (ATGL) increased LD accumulation, suggesting that LD breakdown is mediated by lipolysis under these conditions. Concurrent inhibition of autophagy by silencing ATG5 and of LD biogenesis using DGAT inhibitors was effective in killing starving HeLa cells, whereas cell survival was not compromised by suppression of ATGL-mediated lipolysis. Autophagy-dependent LD biogenesis was also observed in the aggressive triple-negative MDA-MB-231 breast cancer cells deprived of amino acids, but these cells were not sensitized to starvation by the combined inhibition of LD biogenesis and autophagy. These findings reveal that while targeting autophagy-driven and DGAT-mediated LD biogenesis reduces the resilience of HeLa cervical cancer cells to amino acid deprivation, this strategy may not be successful in other cancer cell types.

Keywords:  autophagy; cancer; cell death; diacylglycerol acyltransferase; lipid droplets; nutrient starvation

DOI:  https://doi.org/10.3390/cancers15194857
Nucleic Acids Res. 2023 Oct 12. pii: gkad824. [Epub ahead of print]

CancerProteome: a resource to functionally decipher the proteome landscape in cancer.

Dezhong Lv, Donghao Li, Yangyang Cai, Jiyu Guo, Sen Chu, Jiaxin Yu, Kefan Liu, Tiantongfei Jiang, Na Ding, Xiyun Jin, Yongsheng Li, Juan Xu.

Advancements in mass spectrometry (MS)-based proteomics have greatly facilitated the large-scale quantification of proteins and microproteins, thereby revealing altered signalling pathways across many different cancer types. However, specialized and comprehensive resources are lacking for cancer proteomics. Here, we describe CancerProteome (http://bio-bigdata.hrbmu.edu.cn/CancerProteome), which functionally deciphers and visualizes the proteome landscape in cancer. We manually curated and re-analyzed publicly available MS-based quantification and post-translational modification (PTM) proteomes, including 7406 samples from 21 different cancer types, and also examined protein abundances and PTM levels in 31 120 proteins and 4111 microproteins. Six major analytical modules were developed with a view to describe protein contributions to carcinogenesis using proteome analysis, including conventional analyses of quantitative and the PTM proteome, functional enrichment, protein-protein associations by integrating known interactions with co-expression signatures, drug sensitivity and clinical relevance analyses. Moreover, protein abundances, which correlated with corresponding transcript or PTM levels, were evaluated. CancerProteome is convenient as it allows users to access specific proteins/microproteins of interest using quick searches or query options to generate multiple visualization results. In summary, CancerProteome is an important resource, which functionally deciphers the cancer proteome landscape and provides a novel insight for the identification of tumor protein markers in cancer.

DOI: https://doi.org/10.1093/nar/gkad824
Anal Chem. 2023 Oct 10.

Parallelized Acquisition of Orbitrap and Astral Analyzers Enables High-Throughput Quantitative Analysis.

Hamish I Stewart, Dmitry Grinfeld, Anastassios Giannakopulos, Johannes Petzoldt, Toby Shanley, Matthew Garland, Eduard Denisov, Amelia C Peterson, Eugen Damoc, Martin Zeller, Tabiwang N Arrey, Anna Pashkova, Santosh Renuse, Amirmansoor Hakimi, Andreas Kühn, Matthias Biel, Arne Kreutzmann, Bernd Hagedorn, Immo Colonius, Adrian Schütz, Arne Stefes, Ankit Dwivedi, Daniel Mourad, Max Hoek, Bastian Reitemeier, Philipp Cochems, Alexander Kholomeev, Robert Ostermann, Gregor Quiring, Maximilian Ochmann, Sascha Möhring, Alexander Wagner, André Petker, Sebastian Kanngiesser, Michael Wiedemeyer, Wilko Balschun, Daniel Hermanson, Vlad Zabrouskov, Alexander A Makarov, Christian Hock.

The growing trend toward high-throughput proteomics demands rapid liquid chromatography-mass spectrometry (LC-MS) cycles that limit the available time to gather the large numbers of MS/MS fragmentation spectra required for identification. Orbitrap analyzers scale performance with acquisition time and necessarily sacrifice sensitivity and resolving power to deliver higher acquisition rates. We developed a new mass spectrometer that combines a mass-resolving quadrupole, the Orbitrap, and the novel Asymmetric Track Lossless (Astral) analyzer. The new hybrid instrument enables faster acquisition of high-resolution accurate mass (HRAM) MS/MS spectra compared with state-of-the-art mass spectrometers. Accordingly, new proteomics methods were developed that leverage the strengths of each HRAM analyzer, whereby the Orbitrap analyzer performs full scans with a high dynamic range and resolution, synchronized with the Astral analyzer's acquisition of fast and sensitive HRAM MS/MS scans. Substantial improvements are demonstrated over previous methods using current state-of-the-art mass spectrometers.

DOI: https://doi.org/10.1021/acs.analchem.3c02856
Int J Mol Sci. 2023 Oct 06. pii: 14957. [Epub ahead of print]24(19):

Multi-Method Quantification of Acetyl-Coenzyme A and Further Acyl-Coenzyme A Species in Normal and Ischemic Rat Liver.

Malgorzata Tokarska-Schlattner, Nour Zeaiter, Valérie Cunin, Stéphane Attia, Cécile Meunier, Laurence Kay, Amel Achouri, Edwige Hiriart-Bryant, Karine Couturier, Cindy Tellier, Abderrafek El Harras, Bénédicte Elena-Herrmann, Saadi Khochbin, Audrey Le Gouellec, Uwe Schlattner.

  Thioesters of coenzyme A (CoA) carrying different acyl chains (acyl-CoAs) are central intermediates of many metabolic pathways and donor molecules for protein lysine acylation. Acyl-CoA species largely differ in terms of cellular concentrations and physico-chemical properties, rendering their analysis challenging. Here, we compare several approaches to quantify cellular acyl-CoA concentrations in normal and ischemic rat liver, using HPLC and LC-MS/MS for multi-acyl-CoA analysis, as well as NMR, fluorimetric and spectrophotometric techniques for the quantification of acetyl-CoAs. In particular, we describe a simple LC-MS/MS protocol that is suitable for the relative quantification of short and medium-chain acyl-CoA species. We show that ischemia induces specific changes in the short-chain acyl-CoA relative concentrations, while mild ischemia (1-2 min), although reducing succinyl-CoA, has little effects on acetyl-CoA, and even increases some acyl-CoA species upstream of the tricarboxylic acid cycle. In contrast, advanced ischemia (5-6 min) also reduces acetyl-CoA levels. Our approach provides the keys to accessing the acyl-CoA metabolome for a more in-depth analysis of metabolism, protein acylation and epigenetics.

Keywords:  HPLC; NMR; acetyl-CoA; acyl-CoA; fluorometric assay; liver ischemia; mass spectrometry; metabolomics; spectrophotometric assay; succinyl-CoA

DOI:  https://doi.org/10.3390/ijms241914957
Int J Mol Sci. 2023 Sep 28. pii: 14691. [Epub ahead of print]24(19):

Quantification of Oligonucleotides Using Tandem Mass Spectrometry with Isobaric Internal Standards.

Christopher Gawlig, Güngör Hanci, Michael Rühl.

  In recent years, oligonucleotides have become more important in research, drug approvals and medical therapies. Due to this growing interest in pharmaceutical applications, it is essential to develop reliable analytical methods for this substance class. In this work, we present a quantification method using liquid chromatography coupled with tandem mass spectrometry by applying an isobaric oligonucleotide standard. In addition to a proof of principle, we perform a method qualification to assess its readiness for validation according to ICH Q2 guidelines. In addition to good linearity, sensitivity, accuracy and recovery, the method showed no significant matrix effects. Furthermore, we demonstrated the application of the method by applying the quantification in a biological matrix, as well as an exemplary degradation of an oligonucleotide in bovine plasma.

Keywords:  HPLC-MS/MS; bioanalytic; biological matrix; fragmentation reaction; internal standard; isobaric standard; method validation; multiple reaction monitoring; oligonucleotides

DOI:  https://doi.org/10.3390/ijms241914691
Bioinformatics. 2023 Oct 09. pii: btad618. [Epub ahead of print]

MsQuality - an interoperable open-source package for the calculation of standardized quality metrics of mass spectrometry data.

Thomas Naake, Johannes Rainer, Wolfgang Huber.

  MOTIVATION: Multiple factors can impact accuracy and reproducibility of mass spectrometry data. There is a need to integrate quality assessment and control into data analytic workflows.RESULTS: The MsQuality package calculates 43 low-level quality metrics based on the controlled mzQC vocabulary defined by the HUPO-PSI on a single mass spectrometry-based measurement of a sample. It helps to identify low-quality measurements and track data quality. Its use of community-standard quality metrics facilitates comparability of quality assessment and control (QA/QC) criteria across datasets.
AVAILABILITY: The R package MsQuality is available through Bioconductor at https://bioconductor.org/packages/MsQuality.
SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Keywords:  R; mass spectrometry; metabolomics; proteomics; quality control

DOI:  https://doi.org/10.1093/bioinformatics/btad618
Sci Data. 2023 Oct 13. 10(1): 697

A comprehensive spectral assay library to quantify the Halobacterium salinarum NRC-1 proteome by DIA/SWATH-MS.

Ulrike Kusebauch, Alan P R Lorenzetti, David S Campbell, Min Pan, David Shteynberg, Charu Kapil, Mukul K Midha, Adrián López García de Lomana, Nitin S Baliga, Robert L Moritz.

Data-Independent Acquisition (DIA) is a mass spectrometry-based method to reliably identify and reproducibly quantify large fractions of a target proteome. The peptide-centric data analysis strategy employed in DIA requires a priori generated spectral assay libraries. Such assay libraries allow to extract quantitative data in a targeted approach and have been generated for human, mouse, zebrafish, E. coli and few other organisms. However, a spectral assay library for the extreme halophilic archaeon Halobacterium salinarum NRC-1, a model organism that contributed to several notable discoveries, is not publicly available yet. Here, we report a comprehensive spectral assay library to measure 2,563 of 2,646 annotated H. salinarum NRC-1 proteins. We demonstrate the utility of this library by measuring global protein abundances over time under standard growth conditions. The H. salinarum NRC-1 library includes 21,074 distinct peptides representing 97% of the predicted proteome and provides a new, valuable resource to confidently measure and quantify any protein of this archaeon. Data and spectral assay libraries are available via ProteomeXchange (PXD042770, PXD042774) and SWATHAtlas (SAL00312-SAL00319).

DOI: https://doi.org/10.1038/s41597-023-02590-5
Curr Protoc. 2023 Oct;3(10): e907

Clickable Glutathione-Based Identification of Cysteine Glutathionylation.

Nadee N J Matarage Don, Dhanushika S K Kukulage, Young-Hoon Ahn.

  Clickable glutathione is a glutathione-derived chemical probe designed to identify and analyze protein S-glutathionylation, a major cysteine oxidation in redox signaling. An engineered glutathione synthetase mutant (GS M4) is used to synthesize clickable glutathione in cells or in vitro, which affords utility via click chemistry to detect, identify, and quantify glutathionylation on individual or global proteins in biochemical and mass spectrometric analyses. The clickable glutathione approach is valuable for the unequivocal identification of glutathionylated cysteines, among many reversible cysteine oxoforms, via the direct enrichment and detection of glutathionylated proteins or peptides. Clickable glutathione, in combination with GS M4, has demonstrated utility in the mass-spectrometry-based discovery and profiling of new proteins and cysteines for glutathionylation in cell lines in response to physiologic and oxidative stress. The approach is versatile and applicable to validating the glutathionylation of proteins and cysteines in other biochemical analysis beside mass spectrometry. Here, we describe the applications of clickable glutathione and provide detailed protocols for the identification, profiling, and detection of glutathionylated proteins and cysteines. © 2023 Wiley Periodicals LLC. Basic Protocol 1: Identification of glutathionylated cysteine in individual proteins in vitro Basic Protocol 2: Proteomic identification and quantification of glutathionylation Basic Protocol 3: Biochemical validation of glutathionylation in cells.

Keywords:  S-glutathionylation; clickable glutathione; cysteine; proteomics; reactive oxygen species; redox signaling

DOI:  https://doi.org/10.1002/cpz1.907
Curr Opin Biotechnol. 2023 Oct 06. pii: S0958-1669(23)00106-4. [Epub ahead of print]84 102996

The yin and yang of itaconate metabolism and its impact on the tumor microenvironment.

Fangfang Chen, Birte Dowerg, Thekla Cordes.

The tumor microenvironment (TME) consists of a network of metabolically interconnected tumor and immune cell types. Macrophages influence the metabolic composition within the TME, which directly impacts the metabolic state and drug response of tumors. The accumulation of oncometabolites, such as succinate, fumarate, and 2-hydroxyglutarate, represents metabolic vulnerabilities in cancer that can be targeted therapeutically. Immunometabolites are emerging as metabolic regulators of the TME impacting immune cell functions and cancer cell growth. Here, we discuss recent discoveries on the potential impact of itaconate on the TME. We highlight how itaconate influences metabolic pathways relevant to immune responses and cancer cell proliferation. We also consider the therapeutic implications of manipulating itaconate metabolism as an immunotherapeutic strategy to constrain tumor growth.

DOI: https://doi.org/10.1016/j.copbio.2023.102996
Cell Signal. 2023 Oct 05. pii: S0898-6568(23)00326-1. [Epub ahead of print] 110911

Cellular signaling in the hypoxic cancer microenvironment: Implications for drug resistance and therapeutic targeting.

Hamid A Bakshi, Michella Mkhael, Hakkim L Faruck, Asad Ullah Khan, Alaa A A Aljabali, Vijay Mishra, Mohamed El-Tanani, Nitin B Charbe, Murtaza M Tambuwala.

  The rewiring of cellular metabolism is a defining characteristic of cancer, as tumor cells adapt to acquire essential nutrients from a nutrient-poor environment to sustain their viability and biomass. While hypoxia has been identified as a major factor depriving cancer cells of nutrients, recent studies have revealed that cancer cells distant from supporting blood vessels also face nutrient limitations. To overcome this challenge, hypoxic cancer cells, which heavily rely on glucose as an energy source, employ alternative pathways such as glycogen metabolism and reductive carboxylation of glutamine to meet their energy requirements for survival. Our preliminary studies, alongside others in the field, have shown that under glucose-deficient conditions, hypoxic cells can utilize mannose and maltose as alternative energy sources. This review aims to comprehensively examine the hypoxic cancer microenvironment, its association with drug resistance, and potential therapeutic strategies for targeting this unique niche. Furthermore, we will critically evaluate the current literature on hypoxic cancer microenvironments and explore state-of-the-art techniques used to analyze alternate carbohydrates, specifically mannose and maltose, in complex biological fluids. We will also propose the most effective analytical methods for quantifying mannose and maltose in such biological samples. By gaining a deeper understanding of the hypoxic cancer cell microenvironment and its role in drug resistance, novel therapeutic approaches can be developed to exploit this knowledge.

Keywords:  Drug Resistance; Hypoxia; alternate carbohydrate; cancer metabolism; microenvironment

DOI:  https://doi.org/10.1016/j.cellsig.2023.110911
Front Oncol. 2023 ;13 1286790

Editorial: The role of one-carbon metabolism in cancer progression, therapy, and resistance.

Abhimanyu Thakur, Xin Hu, Erhu Zhao, Chunwan Lu, Yanqing Liu, Yashika Rustagi, Kui Zhang.



Keywords:  cancer diagnosis and treatment; chemotherapy; folic acid; metabolic pathways; nucleic acid synthesis

DOI:  https://doi.org/10.3389/fonc.2023.1286790
Analyst. 2023 Oct 11.

Database-assisted, globally optimized targeted secondary electrospray ionization high resolution mass spectrometry (dGOT-SESI-HRMS) and spectral stitching enhanced volatilomics analysis of bacterial metabolites.

Fouad Choueiry, Rui Xu, Kelly Meyrath, Jiangjiang Zhu.

Secondary electrospray ionization high-resolution mass spectrometry (SESI-HRMS) is an innovative analytical technique for the rapid and non-invasive analysis of volatile organic compounds (VOCs). However, compound annotation and ion suppression in the SESI source has hindered feature detection, stability and reproducibility of SESI-HRMS in untargeted volatilomics. To address this, we have developed and optimized a novel pseudo-targeted approach, database-assisted globally optimized targeted (dGOT)-SESI-HRMS using the microbial-VOC (mVOC) database, and spectral stitching methods to enhance metabolite detection in headspace of anaerobic bacterial cultures. Headspace volatiles from representative bacteria strains were assessed using full scan with data dependent acquisition (DDA), conventional globally optimized targeted (GOT) method, and spectral stitching supported dGOT experiments based on a MS peaks list derived from mVOC. Our results indicate that spectral stitching supported dGOT-SESI-HRMS can proportionally fragment peaks with respect to different analysis windows, with a total of 109 VOCs fragmented from 306 targeted compounds. Of the collected spectra, 88 features were confirmed as culture derived volatiles with respect to media blanks. Annotation was also achieved with a total of 25 unique volatiles referenced to standard databases allowing for biological interpretation. Principal component analysis (PCA) summarizing the headspace volatile demonstrated improved separation of clusters when data was acquired using the dGOT method. Collectively, our dGOT-SESI-HRMS method afforded robust capability of capturing unique VOC profiles from different bacterial strains and culture conditions when compared to conventional GOT and DDA modes, suggesting the newly developed approach can serve as a more reliable analytical method for the sensitive monitoring of gut microbial metabolism.

DOI: https://doi.org/10.1039/d3an01487h
J Proteome Res. 2023 Oct 13.

SWATH-MS Analysis of Blood Plasma and Circulating Small Extracellular Vesicles Enables Detection of Putative Protein Biomarkers of Fertility in Young and Aged Dairy Cows.

Natalie Turner, Pevindu Abeysinghe, Holly Flay, Susanne Meier, Pawel Sadowski, Murray D Mitchell.

  The development of biomarkers of fertility could provide benefits for the genetic improvement of dairy cows. Circulating small extracellular vesicles (sEVs) show promise as diagnostic or prognostic markers since their cargo reflects the metabolic state of the cell of origin; thus, they mirror the physiological status of the host. Here, we employed data-independent acquisition mass spectrometry to survey the plasma and plasma sEV proteomes of two different cohorts of Young (Peripubertal; n = 30) and Aged (Primiparous; n = 20) dairy cows (Bos taurus) of high- and low-genetic merit of fertility and known pregnancy outcomes (ProteomeXchange data set identifier PXD042891). We established predictive models of fertility status with an area under the curve of 0.97 (sEV; p value = 3.302e-07) and 0.95 (plasma; p value = 6.405e-08). Biomarker candidates unique to high-fertility Young cattle had a sensitivity of 0.77 and specificity of 0.67 (*p = 0.0287). Low-fertility biomarker candidates uniquely identified in sEVs from Young and Aged cattle had a sensitivity and specificity of 0.69 and 1.0, respectively (***p = 0.0005). Our bioinformatics pipeline enabled quantification of plasma and circulating sEV proteins associated with fertility phenotype. Further investigations are warranted to validate this research in a larger population, which may lead to improved classification of fertility status in cattle.

Keywords:  Bos taurus; SWATH; bioinformatics; biomarker; dairy cow; data-independent acquisition; exosome; extracellular vesicle; fertility; plasma

DOI:  https://doi.org/10.1021/acs.jproteome.3c00406
Anal Chem. 2023 Oct 09.

Deep Proteomic Compound Profiling with the Orbitrap Ascend Tribrid Mass Spectrometer Using Tandem Mass Tags and Real-Time Search.

Steven R Shuken, Graeme C McAlister, William D Barshop, Jesse D Canterbury, David Bergen, Jingjing Huang, Romain Huguet, João A Paulo, Vlad Zabrouskov, Steven P Gygi, Qing Yu.

Tandem mass tags (TMT) and tribrid mass spectrometers are a powerful combination for high-throughput proteomics with high quantitative accuracy. Increasingly, this technology is being used to map the effects of drugs on the proteome. However, the depth of proteomic profiling is still limited by sensitivity and speed. The new Orbitrap Ascend mass spectrometer was designed to address these limitations with a combination of hardware and software improvements. We evaluated the performance of the Ascend in multiple contexts including deep proteomic profiling. We found that the Ascend exhibited increased sensitivity, yielding higher signal-to-noise ratios than the Orbitrap Eclipse with shorter injection times. As a result, higher numbers of peptides and proteins were identified and quantified, especially with low sample input. TMT measurements had significantly improved signal-to-noise ratios, improving quantitative precision. In a fractionated 16plex sample that profiled proteomic differences across four human cell lines, the Ascend was able to quantify hundreds more proteins than the Eclipse, many of them low-abundant proteins, and the Ascend was able to quantify >8000 proteins in 30% less instrument time. We used the Ascend to analyze 8881 proteins in HCT116 cancer cells treated with covalent sulfolane/sulfolene inhibitors of peptidyl-prolyl cis-trans isomerase NIMA-interacting 1 (PIN1), a phosphorylation-specific peptidyl-prolyl cis-trans isomerase implicated in several cancers. We characterized these PIN1 inhibitors' effects on the proteome and identified discrepancies among the different compounds, which will facilitate a better understanding of the structure-activity relationship of this class of compounds. The Ascend was able to quantify statistically significant, potentially therapeutically relevant changes in proteins that the Eclipse could not detect.

DOI: https://doi.org/10.1021/acs.analchem.3c01701
Sheng Wu Gong Cheng Xue Bao. 2023 Sep 25. 39(9): 3566-3578

[Effect of viral infection on host cell metabolism: a review].

Yanmei Li, Yunlin Wei, Haiyan Li, Xiuling Ji.

  As specialized intracellular parasite, viruses have no ability to metabolize independently, so they completely depend on the metabolic mechanism of host cells. Viruses use the energy and precursors provided by the metabolic network of the host cells to drive their replication, assembly and release. Namely, viruses hijack the host cells metabolism to achieve their own replication and proliferation. In addition, viruses can also affect host cell metabolism by the expression of auxiliary metabolic genes (AMGs), affecting carbon, nitrogen, phosphorus, and sulfur cycles, and participate in microbial-driven biogeochemical cycling. This review summarizes the effect of viral infection on the host's core metabolic pathway from four aspects: cellular glucose metabolism, glutamine metabolism, fatty acid metabolism, and viral AMGs on host metabolism. It may facilitate in-depth understanding of virus-host interactions, and provide a theoretical basis for the treatment of viral diseases through metabolic intervention.

Keywords:  auxiliary metabolic genes (AMGs); fatty acid metabolism; glutamine metabolism; glycolysis; viral infections

DOI:  https://doi.org/10.13345/j.cjb.220888
J Cell Physiol. 2023 Oct 10.

Stearoyl-CoA desaturase 1 inhibition impairs triacylglycerol accumulation and lipid droplet formation in colorectal cancer cells.

Zuzanna Tracz-Gaszewska, Adrian Sowka, Pawel Dobrzyn.

  Increases in fatty acid (FA) biosynthesis meet the higher lipid demand by intensely proliferating cancer cells and promoting their progression. Stearoyl-CoA desaturase 1 (SCD1) is the key enzyme in FA biosynthesis, converting saturated FA (SFA) into monounsaturated FA (MUFA). Increases in the MUFA/SFA ratio and SCD1 expression have been observed in cancers of various origins and correlate with their aggressiveness. However, much is still unknown about the SCD1-dependent molecular mechanisms that promote specific changes in metabolic pathways of cancer cells. The present study investigated the involvement of SCD1 in shaping glucose and lipid metabolism in colorectal cancer (CRC) cells. Excess FAs that derive from de novo lipogenesis are stored in organelles, called lipid droplets (LDs), mainly in the form of triacylglycerol (TAG) and cholesteryl esters. LD accumulation is associated with key features of cancer development and progression. Consistent with our findings, the pharmacological inhibition of SCD1 activity affects CRC cell viability and impairs TAG accumulation and LD formation in these cells through the activation of lipolytic and lipophagic pathways. We showed that SCD1 suppression affects crucial lipogenic processes that promote lipid accumulation in CRC cells but in a sterol regulatory element-binding protein 1-independent manner. We propose that adenosine monophosphate-activated protein kinase contributes to these changes through the activation of lipolysis and inhibition of TAG synthesis. We also provide evidence of the involvement of SCD1 in the regulation of glucose uptake and utilization in CRC cells. These findings underscore the importance of SCD1 in regulating cellular processes that promote cancer development and progression.

Keywords:  SCD1; energetic metabolism; fatty acids; lipid droplets; lipolysis; lipophagy

DOI:  https://doi.org/10.1002/jcp.31137
Methods Enzymol. 2023 ;pii: S0076-6879(23)00126-X. [Epub ahead of print]689 89-119

Approaches to assessing 3β-hydroxysteroid dehydrogenase-1.

Mohammad Alyamani, Jeff McManus, Mona Patel, Nima Sharifi.

  The enzyme 3β-hydroxysteroid dehydrogenase-1 (3βHSD1), encoded by the gene HSD3B1, plays an essential role in the peripheral conversion of 3β-OH, Δ5-steroids to 3-keto, Δ4-steroids. In human physiology, the adrenal produces dehydroepiandrosterone (DHEA) and DHEA-sulfate, which are major precursors for the biosynthesis of potent androgens and estrogens. DHEA is converted by 3βHSD1 and subsequently is converted by steroid-5α-reductase to potent androgens or by aromatase to estrogens. Assessment of 3βHSD1 is therefore critical under various conditions. In this chapter, we detail several approaches to assessing 3βHSD1. First, we describe a genotyping protocol for the identification of a common missense-encoding variation that regulates 3βHSD1 cellular metabolic activity. This protocol distinguishes between the HSD3B1(1245A) and the HSD3B1(1245C) allele which have lower and higher metabolic activity, respectively. Second, we detail mass spectrometry approaches to determining 3βHSD1 activity using stable isotope dilution. Third, we describe methods for using tritiated DHEA and high performance liquid chromatography coupled with a beta-RAM to also determine 3βHSD1 activity. Together, we provide multiple methods of directly assessing 3βHSD1 activity or anticipated 3βHSD1 activity.

Keywords:  Androgen; Genotype; HPLC; HSD3B1; LC–MS; Metabolism; Prostate cancer

DOI:  https://doi.org/10.1016/bs.mie.2023.04.002
Cell. 2023 Sep 26. pii: S0092-8674(23)01032-2. [Epub ahead of print]

Arginine reprograms metabolism in liver cancer via RBM39.

Dirk Mossmann, Christoph Müller, Sujin Park, Brendan Ryback, Marco Colombi, Nathalie Ritter, Diana Weißenberger, Eva Dazert, Mairene Coto-Llerena, Sandro Nuciforo, Lauriane Blukacz, Caner Ercan, Veronica Jimenez, Salvatore Piscuoglio, Fatima Bosch, Luigi M Terracciano, Uwe Sauer, Markus H Heim, Michael N Hall.

  Metabolic reprogramming is a hallmark of cancer. However, mechanisms underlying metabolic reprogramming and how altered metabolism in turn enhances tumorigenicity are poorly understood. Here, we report that arginine levels are elevated in murine and patient hepatocellular carcinoma (HCC), despite reduced expression of arginine synthesis genes. Tumor cells accumulate high levels of arginine due to increased uptake and reduced arginine-to-polyamine conversion. Importantly, the high levels of arginine promote tumor formation via further metabolic reprogramming, including changes in glucose, amino acid, nucleotide, and fatty acid metabolism. Mechanistically, arginine binds RNA-binding motif protein 39 (RBM39) to control expression of metabolic genes. RBM39-mediated upregulation of asparagine synthesis leads to enhanced arginine uptake, creating a positive feedback loop to sustain high arginine levels and oncogenic metabolism. Thus, arginine is a second messenger-like molecule that reprograms metabolism to promote tumor growth.

Keywords:  AGMAT; ARG1; ASNS; RBM39; arginine; hepatocellular carcinoma; indisulam; metabolism

DOI:  https://doi.org/10.1016/j.cell.2023.09.011