bims-mascan 2024-06-02 papers

bims-mascan

Biomed News

on Mass spectrometry in cancer research

Issue of 2024–06–02
fourteen papers selected by
Giovanny Rodríguez Blanco, Uniklinikum Graz

Recent additions and access to a multidimensional lipidomic database containing liquid chromatography, ion mobility spectrometry, and tandem mass spectrometry information.
UHPLC-HRMS-based Multiomics to Explore the Potential Mechanisms and Biomarkers for Colorectal Cancer.
A Targeted, Bioinert LC-MS/MS Method for Sensitive, Comprehensive Analysis of Signaling Lipids.
Prognostic potential of lipid profiling in cancer patients: a systematic review of mass spectrometry-based studies.
Oleic acid stimulates proliferation of RMG-1 ovarian cancer cells by activating the pentose phosphate pathway and glutamine metabolism.
Characterization of spironolactone and metabolites derivatized using Girard's reagent P using mass spectrometry and ion mobility spectrometry.
Four-dimensional Lipidomics Profiling in X-linked Adrenoleukodystrophy using Trapped Ion Mobility Mass Spectrometry.
Visualizing 13C-Labeled Metabolites in Maize Root Tips with Mass Spectrometry Imaging.
Statistical Testing for Protein Equivalence Identifies Core Functional Modules Conserved across 360 Cancer Cell Lines and Presents a General Approach to Investigating Biological Systems.
Phospholipid isotope tracing suggests β-catenin-driven suppression of phosphatidylcholine metabolism in hepatocellular carcinoma.
13C metabolite tracing reveals glutamine and acetate as critical in vivo fuels for CD8 T cells.
METLIN-CCS Lipid Database: An authentic standards resource for lipid classification and identification.
High-Throughput Proteomics and Phosphoproteomics of Rat Tissues Using Microflow Zeno SWATH.
Lipidome atlas of the adult human brain.

Anal Bioanal Chem. 2024 May 30.

Recent additions and access to a multidimensional lipidomic database containing liquid chromatography, ion mobility spectrometry, and tandem mass spectrometry information.

Amie M Solosky, Kaylie I Kirkwood-Donelson, Melanie T Odenkirk, Erin S Baker.

  The importance of lipids in biology continues to grow with their recent linkages to more diseases and conditions, microbiome fluctuations, and environmental exposures. These associations have motivated researchers to evaluate lipidomic changes in numerous matrices and studies. Lipidomic analyses, however, present numerous challenges as lipid species have broad chemistries that require different extraction methods and instrumental analyses to evaluate and separate their many isomers and isobars. Increasing knowledge about different lipid characteristics is therefore crucial for improving their separation and identification. Here, we present a multidimensional database for lipids analyzed on a platform combining reversed-phase liquid chromatography, drift tube ion mobility spectrometry, collision-induced dissociation, and mass spectrometry (RPLC-DTIMS-CID-MS). This platform and the different separation characteristics it provides enables more confident lipid annotations when compared to traditional tandem mass spectrometry platforms, especially when analyzing highly isomeric molecules such as lipids. This database expands on our previous publication containing only human plasma and bronchoalveolar lavage fluid lipids and provides experimental RPLC retention times, IMS collision cross section (CCS) values, and m/z information for 877 unique lipids from additional biofluids and tissues. Specifically, the database contains 1504 precursor [M + H]+, [M + NH4]+, [M + Na]+, [M-H]-, [M-2H]2-, [M + HCOO]-, and [M + CH3COO]- ion species and their associated CID fragments which are commonly targeted in clinical and environmental studies, in addition to being present in the chloroform layer of Folch extractions. Furthermore, this multidimensional RPLC-DTIMS-CID-MS database spans 5 lipid categories (fatty acids, sterols, sphingolipids, glycerolipids, and glycerophospholipids) and 24 lipid classes. We have also created a webpage (tarheels.live/bakerlab/databases/) to enhance the accessibility of this resource which will be populated regularly with new lipids as we identify additional species and integrate novel standards.

Keywords:  Collision cross section; Database; Ion mobility spectrometry; Lipidomics; Lipids; Mass spectrometry; Reverse phase liquid chromatography (RPLC)

DOI:  https://doi.org/10.1007/s00216-024-05351-4
BMC Cancer. 2024 May 27. 24(1): 644

UHPLC-HRMS-based Multiomics to Explore the Potential Mechanisms and Biomarkers for Colorectal Cancer.

Xuancheng Wang, Xuan Guan, Ying Tong, Yunxiao Liang, Zongsheng Huang, Mingsen Wen, Jichu Luo, Hongwei Chen, Shanyi Yang, Zhiyong She, Zhijuan Wei, Yun Zhou, Yali Qi, Pingchuan Zhu, Yanying Nong, Qisong Zhang.

   BACKGROUND: Understanding the metabolic changes in colorectal cancer (CRC) and exploring potential diagnostic biomarkers is crucial for elucidating its pathogenesis and reducing mortality. Cancer cells are typically derived from cancer tissues and can be easily obtained and cultured. Systematic studies on CRC cells at different stages are still lacking. Additionally, there is a need to validate our previous findings from human serum.
METHODS: Ultrahigh-performance liquid chromatography tandem high-resolution mass spectrometry (UHPLC-HRMS)-based metabolomics and lipidomics were employed to comprehensively measure metabolites and lipids in CRC cells at four different stages and serum samples from normal control (NR) and CRC subjects. Univariate and multivariate statistical analyses were applied to select the differential metabolites and lipids between groups. Biomarkers with good diagnostic efficacy for CRC that existed in both cells and serum were screened by the receiver operating characteristic curve (ROC) analysis. Furthermore, potential biomarkers were validated using metabolite standards.
RESULTS: Metabolite and lipid profiles differed significantly among CRC cells at stages A, B, C, and D. Dysregulation of glycerophospholipid (GPL), fatty acid (FA), and amino acid (AA) metabolism played a crucial role in the CRC progression, particularly GPL metabolism dominated by phosphatidylcholine (PC). A total of 46 differential metabolites and 29 differential lipids common to the four stages of CRC cells were discovered. Eight metabolites showed the same trends in CRC cells and serum from CRC patients compared to the control groups. Among them, palmitoylcarnitine and sphingosine could serve as potential biomarkers with the values of area under the curve (AUC) more than 0.80 in the serum and cells. Their panel exhibited excellent performance in discriminating CRC cells at different stages from normal cells (AUC = 1.00).
CONCLUSIONS: To our knowledge, this is the first research to attempt to validate the results of metabolism studies of serum from CRC patients using cell models. The metabolic disorders of PC, FA, and AA were closely related to the tumorigenesis of CRC, with PC being the more critical factor. The panel composed of palmitoylcarnitine and sphingosine may act as a potential biomarker for the diagnosis of CRC, aiding in its prevention.

Keywords:  Biomarkers; Colorectal cancer; Lipidomics; Metabolomics; UHPLC-HRMS

DOI:  https://doi.org/10.1186/s12885-024-12321-7
Anal Chem. 2024 May 25.

A Targeted, Bioinert LC-MS/MS Method for Sensitive, Comprehensive Analysis of Signaling Lipids.

Stefanie Rubenzucker, Mailin-Christin Manke, Rainer Lehmann, Alice Assinger, Oliver Borst, Robert Ahrends.

Signaling lipids are key players in cellular processes. Despite their importance, no method currently allows their comprehensive monitoring in one analytical run. Challenges include a wide dynamic range, isomeric and isobaric species, and unwanted interaction along the separation path. Herein, we present a sensitive and robust targeted liquid chromatography-mass spectrometry (LC-MS/MS) approach to overcome these challenges, covering a broad panel of 17 different signaling lipid classes. It involves a simple one-phase sample extraction and lipid analysis using bioinert reversed-phase liquid chromatography coupled to targeted mass spectrometry. The workflow shows excellent sensitivity and repeatability in different biological matrices, enabling the sensitive and robust monitoring of 388 lipids in a single run of only 20 min. To benchmark our workflow, we characterized the human plasma signaling lipidome, quantifying 307 endogenous molecular lipid species. Furthermore, we investigated the signaling lipidome during platelet activation, identifying numerous regulations along important lipid signaling pathways. This highlights the potential of the presented method to investigate signaling lipids in complex biological systems, enabling unprecedentedly comprehensive analysis and direct insight into signaling pathways.

DOI: https://doi.org/10.1021/acs.analchem.4c01388
Lipids Health Dis. 2024 May 25. 23(1): 154

Prognostic potential of lipid profiling in cancer patients: a systematic review of mass spectrometry-based studies.

Yusuke Takanashi, Tomoaki Kahyo, Keigo Sekihara, Akikazu Kawase, Mitsutoshi Setou, Kazuhito Funai.

  Cancer prognosis remains a critical clinical challenge. Lipidomic analysis via mass spectrometry (MS) offers the potential for objective prognostic prediction, leveraging the distinct lipid profiles of cancer patient-derived specimens. This review aims to systematically summarize the application of MS-based lipidomic analysis in prognostic prediction for cancer patients. Our systematic review summarized 38 studies from the past decade that attempted prognostic prediction of cancer patients through lipidomics. Commonly analyzed cancers included colorectal, prostate, and breast cancers. Liquid (serum and urine) and tissue samples were equally used, with liquid chromatography-tandem MS being the most common analytical platform. The most frequently evaluated prognostic outcomes were overall survival, stage, and recurrence. Thirty-eight lipid markers (including phosphatidylcholine, ceramide, triglyceride, lysophosphatidylcholine, sphingomyelin, phosphatidylethanolamine, diacylglycerol, phosphatidic acid, phosphatidylserine, lysophosphatidylethanolamine, lysophosphatidic acid, dihydroceramide, prostaglandin, sphingosine-1-phosphate, phosphatidylinosito, fatty acid, glucosylceramide and lactosylceramide) were identified as prognostic factors, demonstrating potential for clinical application. In conclusion, the potential for developing lipidomics in cancer prognostic prediction was demonstrated. However, the field is still nascent, necessitating future studies for validating and establishing lipid markers as reliable prognostic tools in clinical practice.

Keywords:  Cancer; Lipid; Lipidomics; Mass spectrometry; Prognostic prediction

DOI:  https://doi.org/10.1186/s12944-024-02121-0
Biochem Biophys Res Commun. 2024 May 24. pii: S0006-291X(24)00698-3. [Epub ahead of print]722 150162

Oleic acid stimulates proliferation of RMG-1 ovarian cancer cells by activating the pentose phosphate pathway and glutamine metabolism.

Takeru Tamaki, Nobuyuki Fukushima.

  Extracellular fatty acids (FAs) play an important role in regulating cellular functions such as cell proliferation, survival, and migration. The effects of oleic acid (OA) on cancer cells vary depending on the cell type. Our prior study showed that two distinct ovarian cancer cell lines, RMG-1 and HNOA, proliferate in response to OA, but they differ with respect to glucose utilization. Here, we aimed to elucidate the mechanism(s) by which OA stimulates proliferation of RMG-1 cells. We found that OA stimulates RMG-1 proliferation by activating the FA transporter CD36. OA also increases uptake of glucose and glutamine, which subsequently activate the pentose phosphate pathway (PPP) and glutamine metabolism, respectively. Given that ribose 5-phosphate derived from the PPP is utilized for glutamine metabolism and the subsequent de novo nucleotide synthesis, our findings suggest that OA affects the PPP associated with Gln metabolism, rather than glycolysis associated with glutaminolysis; this leads ultimately to activation of DNA synthesis, which is required for cell proliferation. This selective activation by OA contrasts with the mechanisms observed in HNOA cells, in which OA-induced cell proliferation is driven by transcriptional regulation of the GLUT gene. The diverse responses of cancer cells to OA may be attributed to distinct mechanisms of OA reception and/or different metabolic pathways activated by OA.

Keywords:  CD36; Glutamine metabolism; Oleic acid; Ovarian cancer cell; Pentose phosphate pathway; de novo nucleotide synthesis

DOI:  https://doi.org/10.1016/j.bbrc.2024.150162
Rapid Commun Mass Spectrom. 2024 Aug 15. 38(15): e9775

Characterization of spironolactone and metabolites derivatized using Girard's reagent P using mass spectrometry and ion mobility spectrometry.

Stephanie M Jones, Kaylie I Kirkwood-Donelson, Georgia M Alexander, Lalith Perera, Serena M Dudek, Alan K Jarmusch.

RATIONALE: Spironolactone is a steroidal drug prescribed for a variety of medical conditions and is extensively metabolized quickly after administration. Measurement of spironolactone and its metabolites remains challenging using mass spectrometry (MS) due to in-source fragmentation and relatively poor ionization using electrospray ionization. Therefore, improved methods of measurements are needed, particularly in the case of small sample volumes.
METHODS: Girard's reagent P (GP) derivatization of spironolactone was employed to improve response and provide an MS-based solution to the measurement of spironolactone and its metabolites. We performed ultra-high-performance liquid chromatography-electrospray ionization-tandem mass spectrometry (UHPLC-ESI-MS/MS) and ion mobility spectrometry (IMS)-high-resolution mass spectrometry (HRMS) to fully characterize the GP derivatization products. Analytes were studied in positive ionization mode, and MS/MS was performed using nonresonance and resonance excitation collision-induced dissociation.
RESULTS: We observed the successful GP derivatization of spironolactone and its metabolites using authentic chemical standards. A signal enhancement of 1-2 orders of magnitude was observed for GP-derivatized versions of spironolactone and its metabolites. Further, GP derivatization eliminated in-source fragmentation. Finally, we performed GP derivatization and ultra-high-performance liquid chromatography-high-resolution mass spectrometry (UHPLC-HRMS) in a small volume of murine serum (20 μL) from spironolactone-treated and control animals and observed multiple spironolactone metabolites only in the spironolactone-treated group.
CONCLUSIONS: GP derivatization was proven to have advantageous mass spectral performance (e.g., limiting in-source fragmentation, enhancing signals, and eliminating isobaric analytes) for spironolactone and its metabolites. This work and the detailed characterization using ultra-high-performance liquid chromatography-high-resolution tandem mass spectrometry (UHPLC-HRMS/MS) and IMS serve as the foundation for future developments in reaction optimization and/or quantitative assay development.

DOI: https://doi.org/10.1002/rcm.9775
J Lipid Res. 2024 May 23. pii: S0022-2275(24)00072-5. [Epub ahead of print] 100567

Four-dimensional Lipidomics Profiling in X-linked Adrenoleukodystrophy using Trapped Ion Mobility Mass Spectrometry.

Yorrick R J Jaspers, Sven W Meyer, Mia L Pras-Raves, Inge M E Dijkstra, Eric J M Wever, Adrie D Dane, Jan-Bert van Klinken, Gajja S Salomons, Riekelt H Houtkooper, Marc Engelen, Stephan Kemp, Michel Van Weeghel, Frédéric M Vaz.

  Lipids play pivotal roles in an extensive range of metabolic and physiological processes. In recent years, the convergence of trapped ion mobility (TIMS) and mass spectrometry (MS) has enabled 4D-lipidomics, a highly promising technology for comprehensive lipid analysis. 4D-lipidomics assesses lipid annotations across four distinct dimensions-retention time, collisional cross section, m/z (mass-to-charge ratio), and MS/MS spectra-providing a heightened level of confidence in lipid annotation. These advantages prove particularly valuable when investigating complex disorders involving lipid metabolism, such as adrenoleukodystrophy (ALD). ALD is characterized by the accumulation of very-long-chain fatty acids (VLCFA) due to pathogenic variants in the ABCD1 gene. A comprehensive 4D-lipidomics strategy of ALD fibroblasts demonstrated significant elevations of various lipids from multiple classes. This indicates that the changes observed in ALD are not confined to a single lipid class and likely impacts a broad spectrum of lipid-mediated physiological processes. Our findings highlight the incorporation of mainly saturated and monounsaturated VLCFA variants into a range of lipid classes, encompassing phosphatidylcholines, triacylglycerols, and cholesterol esters. These include ultra-long-chain fatty acids with a length of up to thirty carbon atoms. Lipid species containing C26:0, C26:1 were the most frequently detected VLCFA lipids in our study. Furthermore, we report a panel of 121 new candidate biomarkers in fibroblasts, exhibiting significant differentiation between controls and individuals with ALD. In summary, this study demonstrates the capabilities of a 4D-lipid profiling workflow in unraveling novel insights into the intricate lipid modifications associated with metabolic disorders like ALD.

Keywords:  4D-Lipidomics; PASEF; VLCFA; adrenoleukodystrophy; mass spectrometry; trapped ion mobility spectrometry; very long-chain fatty acids

DOI:  https://doi.org/10.1016/j.jlr.2024.100567
J Am Soc Mass Spectrom. 2024 May 31.

Visualizing 13C-Labeled Metabolites in Maize Root Tips with Mass Spectrometry Imaging.

Young Jin Lee, Pubudu Nuwan Perera Hapuarachchige, Evan A Larson, Ngoc Le, Trevor T Forsman.

  Tracing in vivo isotope-labeled metabolites has been used to study metabolic pathways or flux analysis. However, metabolic differences between the cells have been often ignored in these studies due to the limitation of solvent-based extraction. Here we demonstrate that the mass spectrometry imaging of in vivo isotope-labeled metabolites, referred to as MSIi, can provide important insights into metabolic dynamics with cellular resolution that may supplement the traditional metabolomics and flux analysis. Developing maize root tips are adopted as a model system for MSIi by supplementing 200 mM [U-13C]glucose in 0.1x Hoagland medium. MSIi data sets were acquired for longitudinal sections of newly grown maize root tips after growing 5 days in the medium. A total of 56 metabolite features were determined to have been 13C-labeled based on accurate mass and the number of carbon matching with the metabolite databases. Simple sugars and their derivatives were fully labeled, but some small metabolites were partially labeled with a significant amount of fully unlabeled metabolites still present, suggesting the recycling of "old" metabolites in the newly grown tissues. Some distinct localizations were found, including the low abundance of hexose and its derivatives in the meristem, the high abundance of amino acids in the meristem, and the localization to epidermal and endodermal cells for lipids and their intermediates. Fatty acids and lipids were slow in metabolic turnover and showed various isotopologue distributions with intermediate building blocks, which may provide flux information for their biosynthesis.

Keywords:  13C-labeling; MALDI; in vivo isotope labeling; maize; mass spectrometry imaging; root tip

DOI:  https://doi.org/10.1021/jasms.4c00042
J Proteome Res. 2024 May 28.

Statistical Testing for Protein Equivalence Identifies Core Functional Modules Conserved across 360 Cancer Cell Lines and Presents a General Approach to Investigating Biological Systems.

Enes K Ergin, Junia J K Myung, Philipp F Lange.

  Quantitative proteomics has enhanced our capability to study protein dynamics and their involvement in disease using various techniques, including statistical testing, to discern the significant differences between conditions. While most focus is on what is different between conditions, exploring similarities can provide valuable insights. However, exploring similarities directly from the analyte level, such as proteins, genes, or metabolites, is not a standard practice and is not widely adopted. In this study, we propose a statistical framework called QuEStVar (Quantitative Exploration of Stability and Variability through statistical hypothesis testing), enabling the exploration of quantitative stability and variability of features with a combined statistical framework. QuEStVar utilizes differential and equivalence testing to expand statistical classifications of analytes when comparing conditions. We applied our method to an extensive data set of cancer cell lines and revealed a quantitatively stable core proteome across diverse tissues and cancer subtypes. The functional analysis of this set of proteins highlighted the molecular mechanism of cancer cells to maintain constant conditions of the tumorigenic environment via biological processes, including transcription, translation, and nucleocytoplasmic transport.

Keywords:  bioinformatics; cancer cell lines; equivalence testing; proteomics; statistics

DOI:  https://doi.org/10.1021/acs.jproteome.4c00131
Biochim Biophys Acta Mol Cell Biol Lipids. 2024 May 23. pii: S1388-1981(24)00064-7. [Epub ahead of print]1869(6): 159514

Phospholipid isotope tracing suggests β-catenin-driven suppression of phosphatidylcholine metabolism in hepatocellular carcinoma.

Chad VanSant-Webb, Hayden K Low, Junko Kuramoto, Claire E Stanley, Hantao Qiang, Audrey Y Su, Alexis N Ross, Chad G Cooper, James E Cox, Scott A Summers, Kimberley J Evason, Gregory S Ducker.

  Activating mutations in the CTNNB1 gene encoding β-catenin are among the most frequently observed oncogenic alterations in hepatocellular carcinoma (HCC). Profound alterations in lipid metabolism, including increases in fatty acid oxidation and transformation of the phospholipidome, occur in HCC with CTNNB1 mutations, but it is unclear what mechanisms give rise to these changes. We employed untargeted lipidomics and targeted isotope tracing to measure phospholipid synthesis activity in an inducible human liver cell line expressing mutant β-catenin, as well as in transgenic zebrafish with activated β-catenin-driven HCC. In both models, activated β-catenin expression was associated with large changes in the lipidome including conserved increases in acylcarnitines and ceramides and decreases in triglycerides. Lipid isotope tracing analysis in human cells revealed a reduction in phosphatidylcholine (PC) production rates as assayed by choline incorporation. We developed lipid isotope tracing analysis for zebrafish tumors and observed reductions in phosphatidylcholine synthesis by both the CDP-choline and PEMT pathways. The observed changes in the β-catenin-driven HCC phospholipidome suggest that zebrafish can recapitulate conserved features of HCC lipid metabolism and may serve as a model for identifying future HCC-specific lipid metabolic targets.

Keywords:  Ceramides; Hepatocellular carcinoma; Isotope tracing; Lipid metabolism; Phospholipids; Zebrafish

DOI:  https://doi.org/10.1016/j.bbalip.2024.159514
Sci Adv. 2024 May 31. 10(22): eadj1431

13C metabolite tracing reveals glutamine and acetate as critical in vivo fuels for CD8 T cells.

Eric H Ma, Michael S Dahabieh, Lisa M DeCamp, Irem Kaymak, Susan M Kitchen-Goosen, Brandon M Oswald, Joseph Longo, Dominic G Roy, Mark J Verway, Radia M Johnson, Bozena Samborska, Lauren R Duimstra, Catherine A Scullion, Mya Steadman, Matthew Vos, Thomas P Roddy, Connie M Krawczyk, Kelsey S Williams, Ryan D Sheldon, Russell G Jones.

Infusion of 13C-labeled metabolites provides a gold standard for understanding the metabolic processes used by T cells during immune responses in vivo. Through infusion of 13C-labeled metabolites (glucose, glutamine, and acetate) in Listeria monocytogenes-infected mice, we demonstrate that CD8 T effector (Teff) cells use metabolites for specific pathways during specific phases of activation. Highly proliferative early Teff cells in vivo shunt glucose primarily toward nucleotide synthesis and leverage glutamine anaplerosis in the tricarboxylic acid (TCA) cycle to support adenosine triphosphate and de novo pyrimidine synthesis. In addition, early Teff cells rely on glutamic-oxaloacetic transaminase 1 (Got1)-which regulates de novo aspartate synthesis-for effector cell expansion in vivo. CD8 Teff cells change fuel preference over the course of infection, switching from glutamine- to acetate-dependent TCA cycle metabolism late in infection. This study provides insights into the dynamics of Teff metabolism, illuminating distinct pathways of fuel consumption associated with CD8 Teff cell function in vivo.

DOI: https://doi.org/10.1126/sciadv.adj1431
Nat Metab. 2024 May 27.

METLIN-CCS Lipid Database: An authentic standards resource for lipid classification and identification.

Erin S Baker, Winnie Uritboonthai, Aries Aisporna, Corey Hoang, Heino M Heyman, Lisa Connell, Damien Olivier-Jimenez, Martin Giera, Gary Siuzdak.

DOI: https://doi.org/10.1038/s42255-024-01058-z
J Proteome Res. 2024 May 31.

High-Throughput Proteomics and Phosphoproteomics of Rat Tissues Using Microflow Zeno SWATH.

Erin M Humphries, Dylan Xavier, Keith Ashman, Peter G Hains, Phillip J Robinson.

  High-throughput tissue proteomics has great potential in the advancement of precision medicine. Here, we investigated the combined sensitivity of trap-elute microflow liquid chromatography with a ZenoTOF for DIA proteomics and phosphoproteomics. Method optimization was conducted on HEK293T cell lines to determine the optimal variable window size, MS2 accumulation time and gradient length. The ZenoTOF 7600 was then compared to the previous generation TripleTOF 6600 using eight rat organs, finding up to 23% more proteins using a fifth of the sample load and a third of the instrument time. Spectral reference libraries generated from Zeno SWATH data in FragPipe (MSFragger-DIA/DIA-NN) contained 4 times more fragment ions than the DIA-NN only library and quantified more proteins. Replicate single-shot phosphopeptide enrichments of 50-100 μg of rat tryptic peptide were analyzed by microflow HPLC using Zeno SWATH without fractionation. Using Spectronaut we quantified a shallow phosphoproteome containing 1000-3000 phosphoprecursors per organ. Promisingly, clear hierarchical clustering of organs was observed with high Pearson correlation coefficients >0.95 between replicate enrichments and median CV of 20%. The combined sensitivity of microflow HPLC with Zeno SWATH allows for the high-throughput quantitation of an extensive proteome and shallow phosphoproteome from small tissue samples.

Keywords:  Zeno SWATH; microflow; phosphoproteomics; proteomics; shallow phosphoproteome

DOI:  https://doi.org/10.1021/acs.jproteome.4c00010
Nat Commun. 2024 May 25. 15(1): 4455

Lipidome atlas of the adult human brain.

Maria Osetrova, Anna Tkachev, Waltraud Mair, Patricia Guijarro Larraz, Olga Efimova, Ilia Kurochkin, Elena Stekolshchikova, Nickolay Anikanov, Juat Chin Foo, Amaury Cazenave-Gassiot, Aleksandra Mitina, Polina Ogurtsova, Song Guo, Daria M Potashnikova, Alexander A Gulin, Alexander A Vasin, Anastasia Sarycheva, Gleb Vladimirov, Maria Fedorova, Yury Kostyukevich, Evgeny Nikolaev, Markus R Wenk, Ekaterina E Khrameeva, Philipp Khaitovich.

Lipids are the most abundant but poorly explored components of the human brain. Here, we present a lipidome map of the human brain comprising 75 regions, including 52 neocortical ones. The lipidome composition varies greatly among the brain regions, affecting 93% of the 419 analyzed lipids. These differences reflect the brain's structural characteristics, such as myelin content (345 lipids) and cell type composition (353 lipids), but also functional traits: functional connectivity (76 lipids) and information processing hierarchy (60 lipids). Combining lipid composition and mRNA expression data further enhances functional connectivity association. Biochemically, lipids linked with structural and functional brain features display distinct lipid class distribution, unsaturation extent, and prevalence of omega-3 and omega-6 fatty acid residues. We verified our conclusions by parallel analysis of three adult macaque brains, targeted analysis of 216 lipids, mass spectrometry imaging, and lipidome assessment of sorted murine neurons.

DOI: https://doi.org/10.1038/s41467-024-48734-y