bims-mascan 2024-05-19 papers

bims-mascan

Biomed News

on Mass spectrometry in cancer research

Issue of 2024–05–19
seventeen papers selected by
Giovanny Rodríguez Blanco, Uniklinikum Graz

Offline Two-Dimensional Liquid Chromatography-Mass Spectrometry for Deep Annotation of the Fecal Metabolome Following Fecal Microbiota Transplantation.
Evaluation of Protein Identification and Quantification by the diaPASEF Method on timsTOF SCP.
High-throughput identification of gut microbiome-dependent metabolites.
mTORC1 regulates cell survival under glucose starvation through 4EBP1/2-mediated translational reprogramming of fatty acid metabolism.
Proteomic Profiling of Samples Derived from a Murine Model Following Cryptococcus neoformans Infection.
Metabolic Pathways of Acylcarnitine Synthesis.
A Mass Spectrometry Strategy for Protein Quantification Based on the Differential Alkylation of Cysteines Using Iodoacetamide and Acrylamide.
High-Throughput Compound Quality Assessment with High-Mass-Resolution Acoustic Ejection Mass Spectrometry: An Automatic Data Processing Toolkit.
One-carbon unit supplementation fuels purine synthesis in tumor-infiltrating T cells and augments checkpoint blockade.
Comprehensive O-Glycan Analysis by Porous Graphitized Carbon Nanoliquid Chromatography-Mass Spectrometry.
The Deep Proteomics Approach Identified Extracellular Vesicular Proteins Correlated to Extracellular Matrix in Type One and Two Endometrial Cancer.
Integration of proteomic and metabolomic analysis reveal distinct metabolic alterations of prostate cancer-associated fibroblasts compared to normal fibroblasts from patient's stroma samples.
The potential of proteomics for in-depth bioanalytical investigations of satellite cell function in applied myology.
The mechanism and clinical application of farnesyl diphosphate farnesyltransferase 1 in cancer metabolism.
Untargeted lipidomics analysis in women with morbid obesity and type 2 diabetes mellitus: A comprehensive study.
A cell-free nutrient-supplemented perfusate allows four-day ex vivo metabolic preservation of human kidneys.
Accelerating ionizable lipid discovery for mRNA delivery using machine learning and combinatorial chemistry.

J Proteome Res. 2024 May 16.

Offline Two-Dimensional Liquid Chromatography-Mass Spectrometry for Deep Annotation of the Fecal Metabolome Following Fecal Microbiota Transplantation.

Brady G Anderson, Alexander Raskind, Rylan Hissong, Michael K Dougherty, Sarah K McGill, Ajay S Gulati, Casey M Theriot, Robert T Kennedy, Charles R Evans.

  Biological interpretation of untargeted LC-MS-based metabolomics data depends on accurate compound identification, but current techniques fall short of identifying most features that can be detected. The human fecal metabolome is complex, variable, incompletely annotated, and serves as an ideal matrix to evaluate novel compound identification methods. We devised an experimental strategy for compound annotation using multidimensional chromatography and semiautomated feature alignment and applied these methods to study the fecal metabolome in the context of fecal microbiota transplantation (FMT) for recurrent C. difficile infection. Pooled fecal samples were fractionated using semipreparative liquid chromatography and analyzed by an orthogonal LC-MS/MS method. The resulting spectra were searched against commercial, public, and local spectral libraries, and annotations were vetted using retention time alignment and prediction. Multidimensional chromatography yielded more than a 2-fold improvement in identified compounds compared to conventional LC-MS/MS and successfully identified several rare and previously unreported compounds, including novel fatty-acid conjugated bile acid species. Using an automated software-based feature alignment strategy, most metabolites identified by the new approach could be matched to features that were detected but not identified in single-dimensional LC-MS/MS data. Overall, our approach represents a powerful strategy to enhance compound identification and biological insight from untargeted metabolomics data.

Keywords:  C. diff; Clostridioides difficile; HILIC; LC × LC; LC-MS; MS/MS; RPLC; bile acids; compound identification; untargeted metabolomics

DOI:  https://doi.org/10.1021/acs.jproteome.4c00022
J Am Soc Mass Spectrom. 2024 May 16.

Evaluation of Protein Identification and Quantification by the diaPASEF Method on timsTOF SCP.

Ju Wang, Haiyan Tan, Yingxue Fu, Ashutosh Mishra, Huan Sun, Zhen Wang, Zhiping Wu, Xusheng Wang, Geidy E Serrano, Thomas G Beach, Junmin Peng, Anthony A High.

  Accurate and precise quantification is crucial in modern proteomics, particularly in the context of exploring low-amount samples. While the innovative 4D-data-independent acquisition (DIA) quantitative proteomics facilitated by timsTOF mass spectrometers gives enhanced sensitivity and selectivity for protein identification, the diaPASEF (parallel accumulation-serial fragmentation combined with data-independent acquisition) parameters have not been systematically optimized, and a comprehensive evaluation of the quantification is currently lacking. In this study, we conducted a thorough optimization of key parameters on a timsTOF SCP instrument, including sample loading amount (50 ng), ramp/accumulation time (140 ms), isolation window width (20 m/z), and gradient time (60 min). To further improve the identification of proteins in low-amount samples, we utilized different column settings and introduced 0.02% n-dodecyl-β-d-maltoside (DDM) in the sample reconstitution solution, resulting in a remarkable 19-fold increase in protein identification at the single-cell-equivalent level. Moreover, a comprehensive comparison of protein quantification using a tandem mass tag reporter (TMT-reporter), complement TMT ions (TMTc), and diaPASEF revealed a strong correlation between these methods. Both diaPASEF and TMTc have effectively addressed the issue of ratio compression, highlighting the diaPASEF method's effectiveness in achieving accurate quantification data compared to TMT reporter quantification. Additionally, an in-depth analysis of in-group variation positioned diaPASEF between the TMT-reporter and TMTc methods. Therefore, diaPASEF quantification on the timsTOF SCP instrument emerges as a precise and accurate methodology for quantitative proteomics, especially for samples with small amounts.

Keywords:  TMT; TMTc; diaPASEF; proteomics; ratio compression; sensitivity; timsTOF SCP

DOI:  https://doi.org/10.1021/jasms.4c00067
Nat Protoc. 2024 May 13.

High-throughput identification of gut microbiome-dependent metabolites.

Shuo Han, Emma R Guiberson, Yuxin Li, Justin L Sonnenburg.

A significant hurdle that has limited progress in microbiome science has been identifying and studying the diverse set of metabolites produced by gut microbes. Gut microbial metabolism produces thousands of difficult-to-identify metabolites, which present a challenge to study their roles in host biology. In recent years, mass spectrometry-based metabolomics has become one of the core technologies for identifying small metabolites. However, metabolomics expertise, ranging from sample preparation to instrument use and data analysis, is often lacking in academic labs. Most targeted metabolomics methods provide high levels of sensitivity and quantification, while they are limited to a panel of predefined molecules that may not be informative to microbiome-focused studies. Here we have developed a gut microbe-focused and wide-spectrum metabolomic protocol using liquid chromatography-mass spectrometry and bioinformatic analysis. This protocol enables users to carry out experiments from sample collection to data analysis, only requiring access to a liquid chromatography-mass spectrometry instrument, which is often available at local core facilities. By applying this protocol to samples containing human gut microbial metabolites, spanning from culture supernatant to human biospecimens, our approach enables high-confidence identification of >800 metabolites that can serve as candidate mediators of microbe-host interactions. We expect this protocol will lower the barrier to tracking gut bacterial metabolism in vitro and in mammalian hosts, propelling hypothesis-driven mechanistic studies and accelerating our understanding of the gut microbiome at the chemical level.

DOI: https://doi.org/10.1038/s41596-024-00980-6
Nat Commun. 2024 May 14. 15(1): 4083

mTORC1 regulates cell survival under glucose starvation through 4EBP1/2-mediated translational reprogramming of fatty acid metabolism.

Tal Levy, Kai Voeltzke, Laura Hruby, Khawla Alasad, Zuelal Bas, Marteinn Snaebjörnsson, Ran Marciano, Katerina Scharov, Mélanie Planque, Kim Vriens, Stefan Christen, Cornelius M Funk, Christina Hassiepen, Alisa Kahler, Beate Heider, Daniel Picard, Jonathan K M Lim, Anja Stefanski, Katja Bendrin, Andres Vargas-Toscano, Ulf D Kahlert, Kai Stühler, Marc Remke, Moshe Elkabets, Thomas G P Grünewald, Andreas S Reichert, Sarah-Maria Fendt, Almut Schulze, Guido Reifenberger, Barak Rotblat, Gabriel Leprivier.

Energetic stress compels cells to evolve adaptive mechanisms to adjust their metabolism. Inhibition of mTOR kinase complex 1 (mTORC1) is essential for cell survival during glucose starvation. How mTORC1 controls cell viability during glucose starvation is not well understood. Here we show that the mTORC1 effectors eukaryotic initiation factor 4E binding proteins 1/2 (4EBP1/2) confer protection to mammalian cells and budding yeast under glucose starvation. Mechanistically, 4EBP1/2 promote NADPH homeostasis by preventing NADPH-consuming fatty acid synthesis via translational repression of Acetyl-CoA Carboxylase 1 (ACC1), thereby mitigating oxidative stress. This has important relevance for cancer, as oncogene-transformed cells and glioma cells exploit the 4EBP1/2 regulation of ACC1 expression and redox balance to combat energetic stress, thereby supporting transformation and tumorigenicity in vitro and in vivo. Clinically, high EIF4EBP1 expression is associated with poor outcomes in several cancer types. Our data reveal that the mTORC1-4EBP1/2 axis provokes a metabolic switch essential for survival during glucose starvation which is exploited by transformed and tumor cells.

DOI: https://doi.org/10.1038/s41467-024-48386-y
Methods Mol Biol. 2024 ;2775 127-137

Proteomic Profiling of Samples Derived from a Murine Model Following Cryptococcus neoformans Infection.

Ben Muselius, Antoine Bodein, Florence Roux-Dalvai, Arnaud Droit, Jennifer Geddes-McAlister.

  Proteomic profiling provides in-depth information about the regulation of diverse biological processes, activation of and communication across signaling networks, and alterations to protein production, modifications, and interactions. For infectious disease research, mass spectrometry-based proteomics enables detection of host defenses against infection and mechanisms used by the pathogen to evade such responses. In this chapter, we outline protein extraction from organs, tissues, and fluids collected following intranasal inoculation of a murine model with the human fungal pathogen Cryptococcus neoformans. We describe sample preparation, followed by purification, processing on the mass spectrometer, and a robust bioinformatics analysis. The information gleaned from proteomic profiling of fungal infections supports the detection of novel biomarkers for diagnostic and prognostic purposes.

Keywords:  Bioinformatics; Cryptococcosis; Cryptococcus neoformans; Mass spectrometry-based proteomics; Murine model

DOI:  https://doi.org/10.1007/978-1-0716-3722-7_9
Physiol Res. 2024 May 15.

Metabolic Pathways of Acylcarnitine Synthesis.

J Brejchova, K Brejchova, O Kuda.

Acylcarnitines are important markers in metabolic studies of many diseases, including metabolic, cardiovascular, and neurological disorders. We reviewed analytical methods for analyzing acylcarnitines with respect to the available molecular structural information, the technical limitations of legacy methods, and the potential of new mass spectrometry-based techniques to provide new information on metabolite structure. We summarized the nomenclature of acylcarnitines based on historical common names and common abbreviations, and we propose the use of systematic abbreviations derived from the shorthand notation for lipid structures. The transition to systematic nomenclature will facilitate acylcarnitine annotation, reporting, and standardization in metabolomics. We have reviewed the metabolic origins of acylcarnitines important for the biological interpretation of human metabolomic profiles. We identified neglected isomers of acylcarnitines and summarized the metabolic pathways involved in the synthesis and degradation of acylcarnitines, including branched-chain lipids and amino acids. We reviewed the primary literature, mapped the metabolic transformations of acyl-CoAs to acylcarnitines, and created a freely available WikiPathway WP5423 to help researchers navigate the acylcarnitine field. The WikiPathway was curated, metabolites and metabolic reactions were annotated, and references were included. We also provide a table for conversion between common names and abbreviations and systematic abbreviations linked to the LIPID MAPS or Human Metabolome Database.
Int J Mol Sci. 2024 Apr 25. pii: 4656. [Epub ahead of print]25(9):

A Mass Spectrometry Strategy for Protein Quantification Based on the Differential Alkylation of Cysteines Using Iodoacetamide and Acrylamide.

Dávid Virág, Gitta Schlosser, Adina Borbély, Gabriella Gellén, Dávid Papp, Zoltán Kaleta, Borbála Dalmadi-Kiss, István Antal, Krisztina Ludányi.

  Mass spectrometry has become the most prominent yet evolving technology in quantitative proteomics. Today, a number of label-free and label-based approaches are available for the relative and absolute quantification of proteins and peptides. However, the label-based methods rely solely on the employment of stable isotopes, which are expensive and often limited in availability. Here we propose a label-based quantification strategy, where the mass difference is identified by the differential alkylation of cysteines using iodoacetamide and acrylamide. The alkylation reactions were performed under identical experimental conditions; therefore, the method can be easily integrated into standard proteomic workflows. Using high-resolution mass spectrometry, the feasibility of this approach was assessed with a set of tryptic peptides of human serum albumin. Several critical questions, such as the efficiency of labeling and the effect of the differential alkylation on the peptide retention and fragmentation, were addressed. The concentration of the quality control samples calculated against the calibration curves were within the ±20% acceptance range. It was also demonstrated that heavy labeled peptides exhibit a similar extraction recovery and matrix effect to light ones. Consequently, the approach presented here may be a viable and cost-effective alternative of stable isotope labeling strategies for the quantification of cysteine-containing proteins.

Keywords:  acrylamide; alkylation; high-resolution mass spectrometry; human serum albumin; iodoacetamide; protein quantification

DOI:  https://doi.org/10.3390/ijms25094656
Anal Chem. 2024 May 15.

High-Throughput Compound Quality Assessment with High-Mass-Resolution Acoustic Ejection Mass Spectrometry: An Automatic Data Processing Toolkit.

Alandra Quinn, Gordana Ivosev, Jefferson Chin, Robert Mongillo, Cristiano Veiga, Thomas R Covey, Brendon Kapinos, Bhagyashree Khunte, Hui Zhang, Matthew D Troutman, Chang Liu.

Pharmacological screening heavily relies on the reliability of compound libraries. To ensure the accuracy of screening results, fast and reliable quality control (QC) of these libraries is essential. While liquid chromatography (LC) with ultraviolet (UV) or mass spectrometry (MS) detection has been employed for molecule QC on small sample sets, the analytical throughput becomes a bottleneck when dealing with large libraries. Acoustic ejection mass spectrometry (AEMS) is a high-throughput analytical platform that covers a broad range of chemical structural space. In this study, we present the utilization of an AEMS system equipped with a high-resolution MS analyzer for high-throughput compound QC. To facilitate efficient data processing, which is a key challenge for such a high-throughput application, we introduce an automatic data processing toolkit that allows for the high-throughput assessment of the sample standards' quantitative and qualitative characteristics, including purity calculation with the background processing option. Moreover, the toolkit includes a module for quantitatively comparing spectral similarity with the reference library. Integrating the described high-resolution AEMS system with the data processing toolkit effectively eliminates the analytical bottleneck, enabling a rapid and reliable compound quality assessment of large-scale compound libraries.

DOI: https://doi.org/10.1021/acs.analchem.3c05435
Cell Chem Biol. 2024 May 16. pii: S2451-9456(24)00169-7. [Epub ahead of print]31(5): 932-943.e8

One-carbon unit supplementation fuels purine synthesis in tumor-infiltrating T cells and augments checkpoint blockade.

Xincheng Xu, Zihong Chen, Caroline R Bartman, Xi Xing, Kellen Olszewski, Joshua D Rabinowitz.

Nucleotides perform important metabolic functions, carrying energy and feeding nucleic acid synthesis. Here, we use isotope tracing-mass spectrometry to quantitate contributions to purine nucleotides from salvage versus de novo synthesis. We further explore the impact of augmenting a key precursor for purine synthesis, one-carbon (1C) units. We show that tumors and tumor-infiltrating T cells (relative to splenic or lymph node T cells) synthesize purines de novo. Shortage of 1C units for T cell purine synthesis is accordingly a potential bottleneck for anti-tumor immunity. Supplementing 1C units by infusing formate drives formate assimilation into purines in tumor-infiltrating T cells. Orally administered methanol functions as a formate pro-drug, with deuteration enabling kinetic control of formate production. Safe doses of methanol raise formate levels and augment anti-PD-1 checkpoint blockade in MC38 tumors, tripling durable regressions. Thus, 1C deficiency can gate antitumor immunity and this metabolic checkpoint can be overcome with pharmacological 1C supplementation.

DOI: https://doi.org/10.1016/j.chembiol.2024.04.007
Anal Chem. 2024 May 17.

Comprehensive O-Glycan Analysis by Porous Graphitized Carbon Nanoliquid Chromatography-Mass Spectrometry.

Tao Zhang, Wenjun Wang, Manfred Wuhrer, Noortje de Haan.

The diverse and unpredictable structures of O-GalNAc-type protein glycosylation present a challenge for its structural and functional characterization in a biological system. Porous graphitized carbon (PGC) liquid chromatography (LC) coupled to mass spectrometry (MS) has become one of the most powerful methods for the global analysis of glycans in complex biological samples, mainly due to the extensive chromatographic separation of (isomeric) glycan structures and the information delivered by collision induced fragmentation in negative mode MS for structural elucidation. However, current PGC-based methodologies fail to detect the smaller glycan species consisting of one or two monosaccharides, such as the Tn (single GalNAc) antigen, which is broadly implicated in cancer biology. This limitation is caused by the loss of small saccharides during sample preparation and LC. Here, we improved the conventional PGC nano-LC-MS/MS-based strategy for O-glycan analysis, enabling the detection of truncated O-glycan species and improving isomer separation. This was achieved by the implementation of 2.7 μm PGC particles in both the trap and analytical LC columns, which provided an enhanced binding capacity and isomer separation for O-glycans. Furthermore, a novel mixed-mode PGC-boronic acid-solid phase extraction during sample preparation was established to purify a broad range of glycans in an unbiased manner, including the previously missed mono- and disaccharides. Taken together, the optimized PGC nano-LC-MS/MS platform presents a powerful component of the toolbox for comprehensive O-glycan characterization.

DOI: https://doi.org/10.1021/acs.analchem.3c05826
Int J Mol Sci. 2024 Apr 24. pii: 4650. [Epub ahead of print]25(9):

The Deep Proteomics Approach Identified Extracellular Vesicular Proteins Correlated to Extracellular Matrix in Type One and Two Endometrial Cancer.

Valeria Capaci, Feras Kharrat, Andrea Conti, Emanuela Salviati, Manuela Giovanna Basilicata, Pietro Campiglia, Nour Balasan, Danilo Licastro, Federica Caponnetto, Antonio Paolo Beltrami, Lorenzo Monasta, Federico Romano, Giovanni Di Lorenzo, Giuseppe Ricci, Blendi Ura.

  Among gynecological cancers, endometrial cancer is the most common in developed countries. Extracellular vesicles (EVs) are cell-derived membrane-surrounded vesicles that contain proteins involved in immune response and apoptosis. A deep proteomic approach can help to identify dysregulated extracellular matrix (ECM) proteins in EVs correlated to key pathways for tumor development. In this study, we used a proteomics approach correlating the two acquisitions-data-dependent acquisition (DDA) and data-independent acquisition (DIA)-on EVs from the conditioned medium of four cell lines identifying 428 ECM proteins. After protein quantification and statistical analysis, we found significant changes in the abundance (p < 0.05) of 67 proteins. Our bioinformatic analysis identified 26 pathways associated with the ECM. Western blotting analysis on 13 patients with type 1 and type 2 EC and 13 endometrial samples confirmed an altered abundance of MMP2. Our proteomics analysis identified the dysregulated ECM proteins involved in cancer growth. Our data can open the path to other studies for understanding the interaction among cancer cells and the rearrangement of the ECM.

Keywords:  extracellular matrix; mass spectrometry; proteomics

DOI:  https://doi.org/10.3390/ijms25094650
Biochim Biophys Acta Mol Basis Dis. 2024 May 10. pii: S0925-4439(24)00218-7. [Epub ahead of print]1870(6): 167229

Integration of proteomic and metabolomic analysis reveal distinct metabolic alterations of prostate cancer-associated fibroblasts compared to normal fibroblasts from patient's stroma samples.

Guillermo Bordanaba-Florit, Félix Royo, Oihane E Albóniga, Aled Clayton, Juan Manuel Falcón-Pérez, Jason Webber.

  The prostate gland is a complex and heterogeneous organ composed of epithelium and stroma. Whilst many studies into prostate cancer focus on epithelium, the stroma is known to play a key role in disease with the emergence of a cancer-associated fibroblasts (CAF) phenotype associated upon disease progression. In this work, we studied the metabolic rewiring of stromal fibroblasts following differentiation to a cancer-associated, myofibroblast-like, phenotype. We determined that CAFs were metabolically more active compared to normal fibroblasts. This corresponded with a heightened lipogenic metabolism, as both reservoir species and building block compounds. Interestingly, lipid metabolism affects mitochondria functioning yet the mechanisms of lipid-mediated functions are unclear. Data showing oxidised fatty acids and glutathione system are elevated in CAFs, compared to normal fibroblasts, strengthens the hypothesis that increased metabolic activity is related to mitochondrial activity. This manuscript describes mechanisms responsible for the altered metabolic flux and shows that prostate cancer-derived extracellular vesicles can increase basal respiration in normal fibroblasts, mirroring that of the disease-like phenotype. This indicates that extracellular vesicles derived from prostate cancer cells may drive an altered oxygen-dependent metabolism associated to mitochondria in CAFs.

Keywords:  Extracellular vesicles; Human primary fibroblasts; Mass spectrometry; Metabolism; Prostate cancer

DOI:  https://doi.org/10.1016/j.bbadis.2024.167229
Expert Rev Proteomics. 2024 May 16.

The potential of proteomics for in-depth bioanalytical investigations of satellite cell function in applied myology.

Paul Dowling, Capucine Trollet, Laura Muraine, Elisa Negroni, Dieter Swandulla, Kay Ohlendieck.

   INTRODUCTION: Regenerative myogenesis plays a crucial role in mature myofibers to counteract muscular injury or dysfunction due to neuromuscular disorders. The activation of specialized myogenic stem cells, called satellite cells, is intrinsically involved in proliferation and differentiation, followed by myoblast fusion and the formation of multi-nucleated myofibers.
AREAS COVERED: This report provides an overview of the role of satellite cells in the neuromuscular system and the potential future impact of proteomic analyses for biomarker discovery, as well as the identification of novel therapeutic targets in muscle disease. The article reviews the ways in which the systematic analysis of satellite cells, myoblasts and myocytes by single cell proteomics can help to better understand the process of myofiber regeneration.
EXPERT OPINION: In order to better comprehend satellite cell dysfunction in neuromuscular disorders, mass spectrometry-based proteomics is an excellent large-scale analytical tool for the systematic profiling of pathophysiological processes. The optimized isolation of muscle-derived cells can be routinely performed by mechanical/enzymatic dissociation protocols, followed by fluorescence-activated cell sorting in specialized flow cytometers. Ultrasensitive single cell proteomics using label-free quantitation methods or approaches that utilize tandem mass tags are ideal bioanalytical approaches to study the pathophysiological role of stem cells in neuromuscular disease.

Keywords:  Biomarker; muscle stem cell; muscular dystrophy; neuromuscular disease; regenerative medicine; single cell proteomics

DOI:  https://doi.org/10.1080/14789450.2024.2356578
Biochem Biophys Res Commun. 2024 May 06. pii: S0006-291X(24)00582-5. [Epub ahead of print]719 150046

The mechanism and clinical application of farnesyl diphosphate farnesyltransferase 1 in cancer metabolism.

Nanxin Li, Guojuan Wang, Min Guo, Naicheng Zhu, Wenyan Yu.

  Cancer poses a significant risk to human well-being. Among the crucial characteristics of cancer is metabolic reprogramming. To meet the relentless metabolic needs, cancer cells enhance cholesterol metabolism within the adverse tumor microenvironment. Reprograming cholesterol metabolism includes a series of modifications in the synthesis, absorption, esterification, and metabolites associated with cholesterol. These adjustments have a strong correlation with the proliferation, invasion, metastasis, and other characteristics of malignant tumors. FDFT1, also known as farnesyl diphosphate farnesyltransferase 1, is an enzyme crucial in the process of cholesterol biosynthesis. Its significant involvement in tumor metabolism has garnered considerable interest. The significance of FDFT1 in cancer metabolism cannot be overstated, as it actively interacts with cancer cells. This paper aims to analyze and consolidate the mechanism of FDFT1 in cancer metabolism and explore its clinical application. The goal is to contribute new strategies and targets for the prevention and treatment of cancer metabolism.

Keywords:  Cancer metabolism; Cell metastasis; Cell proliferation; Farnesyl diphosphate farnesyltransferase 1

DOI:  https://doi.org/10.1016/j.bbrc.2024.150046
PLoS One. 2024 ;19(5): e0303569

Untargeted lipidomics analysis in women with morbid obesity and type 2 diabetes mellitus: A comprehensive study.

Laia Bertran, Jordi Capellades, Sonia Abelló, Carmen Aguilar, Teresa Auguet, Cristóbal Richart.

There is a phenotype of obese individuals termed metabolically healthy obese that present a reduced cardiometabolic risk. This phenotype offers a valuable model for investigating the mechanisms connecting obesity and metabolic alterations such as Type 2 Diabetes Mellitus (T2DM). Previously, in an untargeted metabolomics analysis in a cohort of morbidly obese women, we observed a different lipid metabolite pattern between metabolically healthy morbid obese individuals and those with associated T2DM. To validate these findings, we have performed a complementary study of lipidomics. In this study, we assessed a liquid chromatography coupled to a mass spectrometer untargeted lipidomic analysis on serum samples from 209 women, 73 normal-weight women (control group) and 136 morbid obese women. From those, 65 metabolically healthy morbid obese and 71 with associated T2DM. In this work, we find elevated levels of ceramides, sphingomyelins, diacyl and triacylglycerols, fatty acids, and phosphoethanolamines in morbid obese vs normal weight. Conversely, decreased levels of acylcarnitines, bile acids, lyso-phosphatidylcholines, phosphatidylcholines (PC), phosphatidylinositols, and phosphoethanolamine PE (O-38:4) were noted. Furthermore, comparing morbid obese women with T2DM vs metabolically healthy MO, a distinct lipid profile emerged, featuring increased levels of metabolites: deoxycholic acid, diacylglycerol DG (36:2), triacylglycerols, phosphatidylcholines, phosphoethanolamines, phosphatidylinositols, and lyso-phosphatidylinositol LPI (16:0). To conclude, analysing both comparatives, we observed decreased levels of deoxycholic acid, PC (34:3), and PE (O-38:4) in morbid obese women vs normal-weight. Conversely, we found elevated levels of these lipids in morbid obese women with T2DM vs metabolically healthy MO. These profiles of metabolites could be explored for the research as potential markers of metabolic risk of T2DM in morbid obese women.

DOI: https://doi.org/10.1371/journal.pone.0303569
Nat Commun. 2024 May 13. 15(1): 3818

A cell-free nutrient-supplemented perfusate allows four-day ex vivo metabolic preservation of human kidneys.

Marlon J A de Haan, Marleen E Jacobs, Franca M R Witjas, Annemarie M A de Graaf, Elena Sánchez-López, Sarantos Kostidis, Martin Giera, Francisco Calderon Novoa, Tunpang Chu, Markus Selzner, Mehdi Maanaoui, Dorottya K de Vries, Jesper Kers, Ian P J Alwayn, Cees van Kooten, Bram Heijs, Gangqi Wang, Marten A Engelse, Ton J Rabelink.

The growing disparity between the demand for transplants and the available donor supply, coupled with an aging donor population and increasing prevalence of chronic diseases, highlights the urgent need for the development of platforms enabling reconditioning, repair, and regeneration of deceased donor organs. This necessitates the ability to preserve metabolically active kidneys ex vivo for days. However, current kidney normothermic machine perfusion (NMP) approaches allow metabolic preservation only for hours. Here we show that human kidneys discarded for transplantation can be preserved in a metabolically active state up to 4 days when perfused with a cell-free perfusate supplemented with TCA cycle intermediates at subnormothermia (25 °C). Using spatially resolved isotope tracing we demonstrate preserved metabolic fluxes in the kidney microenvironment up to Day 4 of perfusion. Beyond Day 4, significant changes were observed in renal cell populations through spatial lipidomics, and increases in injury markers such as LDH, NGAL and oxidized lipids. Finally, we demonstrate that perfused kidneys maintain functional parameters up to Day 4. Collectively, these findings provide evidence that this approach enables metabolic and functional preservation of human kidneys over multiple days, establishing a solid foundation for future clinical investigations.

DOI: https://doi.org/10.1038/s41467-024-47106-w
Nat Mater. 2024 May 13.

Accelerating ionizable lipid discovery for mRNA delivery using machine learning and combinatorial chemistry.

Bowen Li, Idris O Raji, Akiva G R Gordon, Lizhuang Sun, Theresa M Raimondo, Favour A Oladimeji, Allen Y Jiang, Andrew Varley, Robert S Langer, Daniel G Anderson.

To unlock the full promise of messenger (mRNA) therapies, expanding the toolkit of lipid nanoparticles is paramount. However, a pivotal component of lipid nanoparticle development that remains a bottleneck is identifying new ionizable lipids. Here we describe an accelerated approach to discovering effective ionizable lipids for mRNA delivery that combines machine learning with advanced combinatorial chemistry tools. Starting from a simple four-component reaction platform, we create a chemically diverse library of 584 ionizable lipids. We screen the mRNA transfection potencies of lipid nanoparticles containing those lipids and use the data as a foundational dataset for training various machine learning models. We choose the best-performing model to probe an expansive virtual library of 40,000 lipids, synthesizing and experimentally evaluating the top 16 lipids flagged. We identify lipid 119-23, which outperforms established benchmark lipids in transfecting muscle and immune cells in several tissues. This approach facilitates the creation and evaluation of versatile ionizable lipid libraries, advancing the formulation of lipid nanoparticles for precise mRNA delivery.

DOI: https://doi.org/10.1038/s41563-024-01867-3