Impact of Oxygen Concentration on Metabolic Profile of Human Placenta-Derived Mesenchymal Stem Cells As Determined by Chemical Isotope Labeling LC-MS

Recent advances in LC-MS-based metabolomics for clinical biomarker discovery

The employment of liquid chromatography-mass spectrometry (LC-MS) untargeted and targeted metabolomics has led to the discovery of novel biomarkers and improved the understanding of various disease mechanisms. Numerous strategies have been reported to expand the metabolite coverage in LC-MS-untargeted and targeted metabolomics. To improve the sensitivity of low-abundance or poor-ionized metabolites for reducing the amount of clinical sample, chemical derivatization methods are used to target different functional groups. Proper sample preparation is beneficial for reducing the matrix effect, maintaining the stability of the LC-MS system, and increasing the metabolite coverage. Machine learning has recently been integrated into the workflow of LC-MS metabolomics to accelerate metabolite identification and data-processing automation, and increase the accuracy of disease classification and clinical outcome prediction. Due to the rapidly growing utility of LC-MS metabolomics in discovering disease markers, this review will address the recent advances in the field and offer perspectives on various strategies for expanding metabolite coverage, chemical derivatization, sample preparation, clinical disease markers, and machining learning for disease modeling.

Metabolic perturbations in human hepatocytes induced by bis (2-ethylhexyl)-2,3,4,5-tetrabromophthalate exposure: Insights from high-coverage quantitative metabolomics

Bis (2-ethylhexyl)-2,3,4,5-tetrabromophthalate (TBPH) is an extensively used novel brominated flame retardant that is present ubiquitously in the environment and in biota. However, there is inadequate data on its potential hepatotoxicity to humans. In this study, high-coverage quantitative metabolomics based on ¹²C-/¹³C-dansylation labeling LC-MS was performed for the first time to assess the metabolic perturbations and underlying mechanisms of TBPH on human hepatocytes. HepG2 cells were exposed to TBPH at dosages of 0.1,1,10 μM for 24 or 72 h. Overall, 1887 and 1364 amine/phenol-containing metabolites were relatively quantified in cells and culture supernatant. Our results revealed that exposure to 0.1 μM TBPH showed little adverse effects, whereas exposure to 10 μM TBPH for 24 h enhanced intracellular protein catabolism and disrupted energy and lipid homeostasis-related pathways such as histidine metabolism, pantothenate and CoA biosynthesis, alanine, aspartate and glutamate metabolism. Nevertheless, most of these perturbations returned to the same levels as controls after 72 h of exposure. Additionally, prolonged TBPH exposure increased oxidative stress, as reflected by marked disturbances in taurine metabolism. This study sensitively revealed the dysregulations of intracellular and extracellular metabolome induced by TBPH, providing a comprehensive understanding of metabolic responses of cells to novel brominated flame retardants.

Metabolomic profiling of cerebrospinal fluid reveals an early diagnostic model for central nervous system involvement in acute lymphoblastic leukaemia

The pathogenesis of central nervous system involvement (CNSI) in patients with acute lymphoblastic leukaemia (ALL) remains unclear and a robust biomarker of early diagnosis is missing. An untargeted cerebrospinal fluid (CSF) metabolomics analysis was performed to identify independent risk biomarkers that could diagnose CNSI at the early stage. Thirty-three significantly altered metabolites between ALL patients with and without CNSI were identified, and a CNSI evaluation score (CES) was constructed to predict the risk of CNSI based on three independent risk factors (8-hydroxyguanosine, l-phenylalanine and hypoxanthine). This predictive model could diagnose CNSI with positive prediction values of 95.9% and 85.6% in the training and validation sets respectively. Moreover, CES score increased with the elevated level of central nervous system (CNSI) involvement. In addition, we validated this model by tracking the changes in CES at different stages of CNSI, including before CNSI and during CNSI, and in remission after CNSI. The CES showed good ability to predict the progress of CNSI. Finally, we constructed a nomogram to predict the risk of CNSI in clinical practice, which performed well compared with observed probability. This unique CSF metabolomics study may help us understand the pathogenesis of CNSI, diagnose CNSI at the early stage, and sequentially achieve personalized precision treatment.

Bioengineering Outlook on Cultivated Meat Production

Cultured meat (also referred to as cultivated meat or cell-based meat)-CM-is fabricated through the process of cellular agriculture (CA), which entails application of bioengineering, i.e., tissue engineering (TE) principles to the production of food. The main TE principles include usage of cells, grown in a controlled environment provided by bioreactors and cultivation media supplemented with growth factors and other needed nutrients and signaling molecules, and seeded onto the immobilization elements-microcarriers and scaffolds that provide the adhesion surfaces necessary for anchor-dependent cells and offer 3D organization for multiple cell types. Theoretically, many solutions from regenerative medicine and biomedical engineering can be applied in CM-TE, i.e., CA. However, in practice, there are a number of specificities regarding fabrication of a CM product that needs to fulfill not only the majority of functional criteria of muscle and fat TE, but also has to possess the sensory and nutritional qualities of a traditional food component, i.e., the meat it aims to replace. This is the reason that bioengineering aimed at CM production needs to be regarded as a specific scientific discipline of a multidisciplinary nature, integrating principles from biomedical engineering as well as from food manufacturing, design and development, i.e., food engineering. An important requirement is also the need to use as little as possible of animal-derived components in the whole CM bioprocess. In this review, we aim to present the current knowledge on different bioengineering aspects, pertinent to different current scientific disciplines but all relevant for CM engineering, relevant for muscle TE, including different cell sources, bioreactor types, media requirements, bioprocess monitoring and kinetics and their modifications for use in CA, all in view of their potential for efficient CM bioprocess scale-up. We believe such a review will offer a good overview of different bioengineering strategies for CM production and will be useful to a range of interested stakeholders, from students just entering the CA field to experienced researchers looking for the latest innovations in the field.

Metabolomic Applications in Stem Cell Research: a Review

This review describes the use of metabolomics to study stem cell (SC) characteristics and function, excluding SCs in cancer research, suited to a fully dedicated text. The interest in employing metabolomics in SC research has consistently grown and emphasis is, here, given to developments reported in the past five years. This text informs on the existing methodologies and their complementarity regarding the information provided, comprising untargeted/targeted approaches, which couple mass spectrometry or nuclear magnetic resonance spectroscopy with multivariate analysis (and, in some cases, pathway analysis and integration with other omics), and more specific analytical approaches, namely isotope tracing to highlight particular metabolic pathways, or in tandem microscopic strategies to pinpoint characteristics within a single cell. The bulk of this review covers the existing applications in various aspects of mesenchymal SC behavior, followed by pluripotent and neural SCs, with a few reports addressing other SC types. Some of the central ideas investigated comprise the metabolic/biological impacts of different tissue/donor sources and differentiation conditions, including the importance of considering 3D culture environments, mechanical cues and/or media enrichment to guide differentiation into specific lineages. Metabolomic analysis has considered cell endometabolomes and exometabolomes (fingerprinting and footprinting, respectively), having measured both lipid species and polar metabolites involved in a variety of metabolic pathways. This review clearly demonstrates the current enticing promise of metabolomics in significantly contributing towards a deeper knowledge on SC behavior, and the discovery of new biomarkers of SC function with potential translation to in vivo clinical practice.

Comparative Proteomic Investigation of Plasma Reveals Novel Potential Biomarker Groups for Acute Aortic Dissection

Acute aortic dissection (AAD) is a catastrophic cardiovascular disease with high disability and mortality due to multiple fatal complications. However, the molecular changes of the serum proteome after AAD are not very clear. Here, we performed isobaric tags for relative and absolute quantitation- (iTRAQ-) based comparative proteomic analysis to investigate the proteome profile changes after AAD by collecting plasma samples from 20 AAD patients and 20 controls. Out of the 345 identified proteins, 266 were considered as high-quality quantified proteins (95%confident peptides ≥ 2), of which 25 proteins were accumulated and 12 were reduced in AAD samples. Gene ontology enrichment analysis showed that the 25 AAD-accumulated proteins were enriched in high-density lipoprotein particles for the cellular component category and protein homodimerization acidity for the molecular function category. Protein-protein interaction network analysis showed that serum amyloid A proteins (SAAs), complement component proteins, and carboxypeptidase N catalytic chain proteins (CPNs) possessed the key nodes of the network. The expression levels of six selected AAD-accumulated proteins, B2-GP1, CPN1, F9, LBP, SAA1, and SAA2, were validated by ELISA. Moreover, ROC analysis showed that the AUCs of B2-GP1 and CPN1 were 0.808 and 0.702, respectively. Our data provide insights into molecular change profiles in proteome levels after AAD and indicate that B2-GP1 and CPN1 are potential biomarkers for AAD.

Characterizing the effects of hypoxia on the metabolic profiles of mesenchymal stromal cells derived from three tissue sources using chemical isotope labeling liquid chromatography-mass spectrometry

Microenvironmental factors such as oxygen concentration mediate key effects on the biology of mesenchymal stromal cells (MSCs). Herein, we performed an in-depth characterization of the metabolic behavior of MSCs derived from the placenta, umbilical cord, and adipose tissue (termed hPMSCs, UC-MSCs, and AD-MSCs, respectively) at physiological (hypoxic; 5% oxygen [O₂]) and standardized (normoxic; 21% O₂) O₂ concentrations using chemical isotope labeling liquid chromatography-mass spectrometry. ¹²C- and ¹³C-isotope dansylation (Dns) labeling was used to analyze the amine/phenol submetabolome, and 2574 peak pairs or metabolites were detected and quantified, from which 52 metabolites were positively identified using a library of 275 Dns-metabolite standards; 2189 metabolites were putatively identified. Next, we identified six metabolites using the Dns library, as well as 14 hypoxic biomarkers from the human metabolome database out of 96 altered metabolites. Ultimately, metabolic pathway analyses were performed to evaluate the associated pathways. Based on pathways identified using the Kyoto Encyclopedia of Genes and Genomes, we identified significant changes in the metabolic profiles of MSCs in response to different O₂ concentrations. These results collectively suggest that O₂ concentration has the strongest influence on hPMSCs metabolic characteristics, and that 5% O₂ promotes arginine and proline metabolism in hPMSCs and UC-MSCs but decreases gluconeogenesis (alanine-glucose) rates in hPMSCs and AD-MSCs. These changes indicate that MSCs derived from different sources exhibit distinct metabolic profiles.

Metabolic profiling associated with autophagy of human placenta-derived mesenchymal stem cells by chemical isotope labeling LC-MS

Autophagy has been reported to have a pivotal role in maintaining stemness, regulating immunomodulation and enhancing the survival of mesenchymal stem cells (MSCs). However, the effect of autophagy on MSC metabolism is largely unknown. Here, we report a workflow for examining the impact of autophagy on human placenta-derived MSC (hPMSC) metabolome profiling with chemical isotope labeling (CIL) LC-MS. Rapamycin or 3-methyladenine was successfully used to induce or inhibit autophagy, respectively. Then, ¹²C- and ¹³C-dansylation labeling LC-MS were used to profile the amine/phenol submetabolome. A total of 935 peak pairs were detected and 50 metabolites were positively identified using the dansylation metabolite standards library, and 669 metabolites were putatively identified based on an accurate mass match in metabolome databases. ¹²C/¹³C-p-dimethylaminophenacyl bromide labeling LC-MS was used to analyze the carboxylic acid submetabolome; 4736 peak pairs were detected, among which 33 metabolites were positively identified in the dimethylaminophenacyl metabolite standards library, and 3007 metabolites were putatively identified. PCA/OPLS-DA analysis combined with volcano plots and Venn diagrams was used to determine the significant metabolites. Metabolites pathway analysis demonstrated that hPMSCs appeared to generate more ornithine with the arginine and proline metabolism pathway and utilized more pantothenic acid to synthesize acetyl-CoA in the beta-alanine metabolism pathway when autophagy was activated. Meanwhile, acetyl-CoA conversion to fatty acids led to accumulation in the fatty acid biosynthesis pathway. In contrast, when autophagy was suppressed, a reduction in metabolites demonstrated weakened metabolic activity in these metabolic pathways. Our research provides a more comprehensive understanding of hPMSC metabolism associated with autophagy.