Correction to "Apoferritin-Encapsulated Jerantinine A for Transferrin Receptor Targeting and Enhanced Selectivity in Breast Cancer Therapy".

[This corrects the article DOI: 10.1021/acsomega.2c00997.].

Positive regulation of oxidative phosphorylation by nuclear myosin 1 protects cells from metabolic reprogramming and tumorigenesis in mice.

Metabolic reprogramming is one of the hallmarks of tumorigenesis. Here, we show that nuclear myosin 1 (NM1) serves as a key regulator of cellular metabolism. NM1 directly affects mitochondrial oxidative phosphorylation (OXPHOS) by regulating mitochondrial transcription factors TFAM and PGC1α, and its deletion leads to underdeveloped mitochondria inner cristae and mitochondrial redistribution within the cell. These changes are associated with reduced OXPHOS gene expression, decreased mitochondrial DNA copy number, and deregulated mitochondrial dynamics, which lead to metabolic reprogramming of NM1 KO cells from OXPHOS to aerobic glycolysis.This, in turn, is associated with a metabolomic profile typical for cancer cells, namely increased amino acid-, fatty acid-, and sugar metabolism, and increased glucose uptake, lactate production, and intracellular acidity. NM1 KO cells form solid tumors in a mouse model, suggesting that the metabolic switch towards aerobic glycolysis provides a sufficient carcinogenic signal. We suggest that NM1 plays a role as a tumor suppressor and that NM1 depletion may contribute to the Warburg effect at the onset of tumorigenesis.

Predicting lameness in dairy cattle using untargeted liquid chromatography-mass spectrometry-based metabolomics and machine learning.

Lameness in dairy cattle is a highly prevalent condition that impacts on the health and welfare of dairy cows. Prompt detection and implementation of effective treatment is important for managing lameness. However, major limitations are associated with visual assessment of lameness, which is the most commonly used method to detect lameness. The aims of this study were to investigate the use of metabolomics and machine learning to develop novel methods to detect lameness. Untargeted metabolomics using liquid chromatography-mass spectrometry (LC-MS) alongside machine learning models and a stability selection method were utilized to evaluate the predictive accuracy of differences in the metabolomics profile of first-lactation dairy cows before (during the transition period) and at the time of lameness (based on visual assessment using the 0-3 scale of the Agriculture and Horticulture Development Board). Urine samples were collected from 2 cohorts of dairy heifers and stored at -86°C before analysis using LC-MS. Cohort 1 (n = 90) cows were recruited as current first-lactation cows with weekly mobility scores recorded over a 4-mo timeframe, from which newly lame and nonlame cows were identified. Cohort 2 (n = 30) cows were recruited within 3 wk before calving, and lameness events (based on mobility score) were recorded through lactation until a minimum of 70 d in milk (DIM). All cows were matched paired by DIM ± 14 d. The median DIM at lameness identification was 187.5 and 28.5 for cohort 1 and 2, respectively. The best performing machine learning models predicted lameness at the time of lameness with an accuracy of between 81 and 82%. Using stability selection, the prediction accuracy at the time of lameness was 80 to 81%. For samples collected before and after calving, the best performing machine learning model predicted lameness with an accuracy of 71 and 75%, respectively. The findings from this study demonstrate that untargeted LC-MS profiling combined with machine learning methods can be used to predict lameness as early as before calving and before observable changes in gait in first-lactation dairy cows. The methods also provide accuracies for detecting lameness at the time of observable changes in gait of up to 82%. The findings demonstrate that these methods could provide substantial advancements in the early prediction and prevention of lameness risk. Further external validation work is required to confirm these findings are generalizable; however, this study provides the basis from which future work can be conducted.

Advantages of using biologically generated 13C-labelled multiple internal standards for stable isotope-assisted LC-MS-based lipidomics.

In comprehensive lipidomics studies, accurate quantification is essential but biological and/or clinical relevance is often hindered due to unwanted variations such as lipid degradation during sample preparation, matrix effects and non-linear responses of analytical instruments. In addition, the wide chemical diversity of lipids can complicate the accurate identification of individual lipids. These analytical limitations can potentially be corrected efficiently by the use of lipid-specific isotopically labelled internal standards (IS) but currently such IS mixtures have limited coverage of the mammalian lipidome. In this study, an in vivo13C labelling strategy was employed to explore four species (Escherichia coli, Arthrospira platensis, Saccharomyces cerevisiae and Pichia pastoris) as a source of 13C-labelled internal standards (13C-ISs) for more accurate and quantitative liquid chromatography (LC)-mass spectrometry (MS)-based lipidomics. Results showed that extracts from 13C-labelled P. pastoris and S. cerevisiae contain the highest percentage of uniformly labelled lipids (both 83% compared to 67% and 69% in A. platensis and E. coli, respectively) and 13C-labelled P. pastoris extract was identified as the optimum source of 13C-ISs for comprehensive data normalisation to correct unwanted variations during sample preparation and LC-MS analysis. Overall, use of a biologically generated 13C-IS lipid mixture of 357 identified lipid ions resulted in significant reduction in the lipid CV% of normalisation compared with other normalisation methods using total ion counts or a commercially available deuterated internal standard mixture. This improved normalisation using 13C-IS was confirmed in a typical lipidomics analysis using a large number of samples (>100+) and long analysis time (>70 h). This study highlights the benefit of an in vivo labelling strategy for reducing technical and analytical variations introduced during sample preparation and analysis in lipidomics studies.

Delivering on sustainable development goals in wastewater reuse for agriculture: Initial prioritization of emerging pollutants in the Tula Valley, Mexico.

Wastewater reuse for agricultural irrigation is a widespread beneficial practice, in line with the sustainable development goals. However, contaminants of emerging concern (CECs) present in wastewater, such as pharmaceuticals, pose an environmental risk. The Tula Valley in Mexico is one of the world's largest agricultural areas reusing wastewater for agriculture. However, no untargeted CEC monitoring has been undertaken there, limiting the information available to prioritise local environmental risk assessment. Furthermore, CEC environmental presence in the Global South remains understudied, compared to the Global North. There is a risk that current research efforts focus on CECs predominantly found in the Global North, leading to strategies that may not be appropriate for the Global South where the pollution profile may be different. To address these knowledge gaps, a sampling campaign at five key sites in the Tula Valley was undertaken and samples analysed using multi-residue targeted and untargeted liquid chromatography mass spectrometry methods. Using the targeted data, ten CECs were found to be of environmental risk for at least one sampling site: 4­tert-octylphenol, acetaminophen, bezafibrate, diclofenac, erythromycin, levonorgestrel, simvastatin, sulfamethoxazole, trimethoprim and tramadol as well as total estrogenicity (combination of three steroid hormones). Six of these have not been previously quantified in the Tula Valley. Over one hundred pollutants never previously measured in the area were identified through untargeted analysis supported by library spectrum match. Examples include diclofenac and carbamazepine metabolites and area-specific pollutants such as the herbicide fomesafen. This research contributes to characterising the presence of CECs in the Global South, as well as providing site-specific data for the Tula Valley.

Potential biomarkers and metabolomics of acetaminophen-induced liver injury during alcohol consumption: A preclinical investigation on C57/BL6 mice.

The toxic effects of alcohol consumption on population health are significant worldwide and the synergistic toxic effects of concurrent intake of Acetaminophen and alcohol is of clinical concern. The understanding of molecular mechanisms beneath such synergism and acute toxicity may be enhanced through assessing underlying metabolomics changes. The molecular toxic activities of the model hereby, is assessed though metabolomics profile with a view to identifying metabolomics targets which could aid in the management of drug-alcohol interactions. In vivo exposure of C57/BL6 mice to APAP (70 mg/kg), single dose of ethanol (6 g/kg of 40%) and APAP after alcohol consumption was employed. Plasma samples were prepared and subjected to biphasic extraction for complete LC-MS profiling, and tandem mass MS2 analysis. Among the detected ions, 174 ions had significant (VIP scores >1 and FDR <0.05) changes between groups and were selected as potential biomarkers and significant variables. The presented metabolomics approach highlighted several affected metabolic pathways, including nucleotide and amino acid metabolism; aminoacyl-tRNA biosynthesis as well as bioenergetics of TCA and Krebs cycle. The impact of APAP on the concurrent administration of alcohol showed great biological interactions in the vital ATP and amino acid producing processes. The metabolomics changes show distinct metabolites which are altered to alcohol-APAP consumption while presenting several unneglectable risks on the vitality of metabolites and cellular molecules which shall be concerned.

Investigating the effect of the probiotic Lactobacillus plantarum and the prebiotic fructooligosaccharides on Pseudomonas aeruginosa metabolome, virulence factors and biofilm formation as potential quorum sensing inhibitors.

Pseudomonas aeruginosa (P. aeruginosa) uses quorum sensing signaling (QS) molecules to control the expression of virulence factors and biofilm formation. In this study, the effects of the probiotic's (Lactobacillus plantarum (L. plantarum)) lysate and cell-free supernatant and the prebiotic (Fructooligosaccharides (FOS)) on the levels of P. aeruginosa QS molecules, virulence factors, biofilm density and metabolites were observed. These effects were investigated using exofactor assays, crystal violet and liquid chromatography-mass spectrometry (LC-MS)-based metabolomics approach. Results showed that in comparison to untreated P. aeruginosa, the L. plantarum cell-free supernatant (5%) and FOS (2%) significantly reduced the levels of the virulence factor pyoverdine (PVD) and several metabolites in the QS pathway including Pseudomonas autoinducer-2 (PAI-2). Metabolomics study revealed that the level of different secondary metabolites involved in the biosynthesis of vitamins, amino acids and the tricarboxylic acid (TCA) cycle were also affected. L. Plantarum was found to have a higher impact on the metabolomics profile of P. aeruginosa and its QS molecules compared to FOS. Lastly, a decrease in the formation of the P. aeruginosa biofilm was observed in a time-dependent pattern upon treatment with either cell-free supernatant of L. plantarum (5%), FOS (2%) or a combination of both treatments (5% + 2%). The latter showed the highest effect with 83% reduction in biofilm density at 72 h incubation. This work highlighted the important role probiotics and prebiotics play as potential QS inhibitors for P. aeruginosa. Moreover, it demonstrated the significant role of LC-MS metabolomics for investigating the altered biochemical and QS pathways in P. aeruginosa.

Micafungin effect on Pseudomonas aeruginosa metabolome, virulence and biofilm: potential quorum sensing inhibitor.

The prevalence of antibiotic resistance in Pseudomonas aeruginosa places a heavy burden on the health care sectors urging the need to find alternative, non-antibiotic strategies. The interference with the P. aeruginosa quorum sensing (QS) system represents a promising alternative strategy to attenuate the bacterial virulency and its ability to form biofilms. Micafungin has been reported to impede the pseudomonal biofilm formation. However, the influences of micafungin on the biochemical composition and metabolites levels of P. aeruginosa have not been explored. In this study, the effect of micafungin (100 µg/mL) on the virulence factors, QS signal molecules and the metabolome of P. aeruginosa was studied using exofactor assay and mass spectrometry-based metabolomics approaches. Furthermore, confocal laser scanning microscopy (CLSM) using the fluorescent dyes ConA-FITC and SYPRO® Ruby was used to visualize micafungin disturbing effects on the pseudomonal glycocalyx and protein biofilm-constituents, respectively. Our findings showed that micafungin significantly decreased the production of various QS-controlled virulence factors (pyocyanin, pyoverdine, pyochelin and rhamnolipid), along with a dysregulation in the level of various metabolites involved in QS system, lysine degradation, tryptophan biosynthesis, TCA cycle, and biotin metabolism. In addition, the CLSM examination showed an altered matrix distribution. The presented findings highlight the promising role of micafungin as a potential quorum sensing inhibitor (QSI) and anti-biofilm agent to attenuate P. aeruginosa pathogenicity. In addition, they point to the promising role of metabolomics study in investigating the altered biochemical pathways in P. aeruginosa.

Lipoprotein Deprivation Reveals a Cholesterol-Dependent Therapeutic Vulnerability in Diffuse Glioma Metabolism.

Poor outcomes associated with diffuse high-grade gliomas occur in both adults and children, despite substantial progress made in the molecular characterisation of the disease. Targeting the metabolic requirements of cancer cells represents an alternative therapeutic strategy to overcome the redundancy associated with cell signalling. Cholesterol is an integral component of cell membranes and is required by cancer cells to maintain growth and may also drive transformation. Here, we show that removal of exogenous cholesterol in the form of lipoproteins from culture medium was detrimental to the growth of two paediatric diffuse glioma cell lines, KNS42 and SF188, in association with S-phase elongation and a transcriptomic program, indicating dysregulated cholesterol homeostasis. Interrogation of metabolic perturbations under lipoprotein-deficient conditions revealed a reduced abundance of taurine-related metabolites and cholesterol ester species. Pharmacological reduction in intracellular cholesterol via decreased uptake and increased export was simulated using the liver X receptor agonist LXR-623, which reduced cellular viability in both adult and paediatric models of diffuse glioma, although the mechanism appeared to be cholesterol-independent in the latter. These results provide proof-of-principle for further assessment of liver X receptor agonists in paediatric diffuse glioma to complement the currently approved therapeutic regimens and expand the options available to clinicians to treat this highly debilitating disease.

Metabolic Signatures of Surface-Modified Poly(lactic-co-glycolic acid) Nanoparticles in Differentiated THP-1 Cells Derived with Liquid Chromatography-Mass Spectrometry-based Metabolomics.

Polymeric nanoparticles (NPs) are widely used in preclinical drug delivery investigations, and some formulations are now in the clinic. However, the detailed effects of many NPs at the subcellular level have not been fully investigated. In this study, we used differentiated THP-1 macrophage cells, as a model, to investigate the metabolic changes associated with the use of poly (lactic-co-glycolic acid) (PLGA) NPs with different surface coating or conjugation chemistries. Liquid chromatography-mass spectrometry-based metabolic profiling was performed on the extracts (n = 6) of the differentiated THP-1 cells treated with plain, Pluronic (F-127, F-68, and P-85)-coated and PEG-PLGA NPs and control (no treatment). Principal component analysis and orthogonal partial least squares-discriminant analysis (OPLS-DA) in conjunction with univariate and pathway analyses were performed to identify significantly changed metabolites and pathways related to exposure of the cells to NPs. OPLS-DA of each class in the study compared to the control showed clear separation and clustering with cross-validation values of R 2 and Q 2 > 0.5. A total of 105 metabolites and lipids were found to be significantly altered in the differentiated THP-1 cell profiles due to the NP exposure, whereas more than 20 metabolic pathways were found to be affected. These pathways included glycerophospholipid, sphingolipid, linoleic acid, arginine and proline, and alpha-linolenic acid metabolisms. PLGA NPs were found to perturb some amino acid metabolic pathways and altered membrane lipids to a different degree. The metabolic effect of the PLGA NPs on the cells were comparable to those caused by silver oxide NPs and other inorganic nanomaterials. However, PEG-PLGA NPs demonstrated a reduced impact on the cellular metabolism compared to Pluronic copolymer-coated PLGA and plain PLGA NPs.

Apoferritin-Encapsulated Jerantinine A for Transferrin Receptor Targeting and Enhanced Selectivity in Breast Cancer Therapy.

The O-acetyl (or acetate) derivative of the Aspidosperma alkaloid Jerantinine A (JAa) elicits anti-tumor activity against cancer cell lines including mammary carcinoma cell lines irrespective of receptor status (0.14 < GI50 < 0.38 µM), targeting microtubule dynamics. By exploiting breast cancer cells' upregulated transferrin receptor 1 (TfR1) expression and apoferritin (AFt) recognition, we sought to develop an AFt JAa-delivery vehicle to enhance tumor-targeting and reduce systemic toxicity. Optimizing pH-mediated reassembly, ∼120 JAa molecules were entrapped within AFt. Western blot and flow cytometry demonstrate TfR1 expression in cancer cells. Enhanced internalization of 5-carboxyfluorescein-conjugated human AFt in SKBR3 and MDA-MB-231 cancer cells is observed compared to MRC5 fibroblasts. Accordingly, AFt-JAa delivers significantly greater intracellular JAa levels to SKBR3 and MDA-MB-231 cells than naked JAa (0.2 µM) treatment alone. Compared to naked JAa (0.2 µM), AFt-JAa achieves enhanced growth inhibition (2.5-14-fold; <0.02 µM < GI50 < 0.15 µM) in breast cancer cells; AFt-JAa treatment results in significantly reduced clonal survival, more profound cell cycle perturbation including G2/M arrest, greater reduction in cell numbers, and increased apoptosis compared to the naked agent (p < 0.01). Decreased PLK1 and Mcl-1 expression, together with the appearance of cleaved poly (ADP-ribose)-polymerase, corroborate the augmented potency of AFt-JAa. Hence, we demonstrate that AFt represents a biocompatible vehicle for targeted delivery of JAa, offering potential to minimize toxicity and enhance JAa activity in TfR1-expressing tumors.

Vegetable oils composition affects the intestinal lymphatic transport and systemic bioavailability of co-administered lipophilic drug cannabidiol.

Although natural sesame oil has been shown to facilitate the lymphatic delivery and oral bioavailability of the highly lipophilic drug cannabidiol (CBD), considerable variability remains an unresolved challenge. Vegetable oils differ substantially in composition, which could lead to differences in promotion of intestinal lymphatic transport of lipophilic drugs. Therefore, the differences in composition of sesame, sunflower, peanut, soybean, olive and coconut oils and their corresponding role as vehicles in promoting CBD lymphatic targeting and bioavailability were investigated in this study. The comparative analysis suggests that the fatty acids profile of vegetable oils is overall similar to the fatty acids profile in the corresponding chylomicrons in rat lymph. However, arachidonic acid (C20:4), was introduced to chylomicrons from endogenous nondietary sources. Overall, fatty acid composition of natural vegetable oils vehicles affected the intestinal lymphatic transport and bioavailability of CBD following oral administration in this work. Olive oil led to the highest concentration of CBD in the lymphatic system and in the systemic circulation in comparison to the other natural vegetable oils following oral administration in rats.

Intratumour heterogeneity in microRNAs expression regulates glioblastoma metabolism.

While specific microRNA (miRNA) signatures have been identified in glioblastoma (GBM), the intratumour heterogeneity in miRNA expression has not yet been characterised. In this study, we reveal significant alterations in miRNA expression across three GBM tumour regions: the core, rim, and invasive margin. Our miRNA profiling analysis showed that miR-330-5p and miR-215-5p were upregulated in the invasive margin relative to the core and the rim regions, while miR-619-5p, miR-4440 and miR-4793-3p were downregulated. Functional analysis of newly identified miRNAs suggests their involvement in regulating lipid metabolic pathways. Subsequent liquid chromatography-mass spectrometry (LC-MS) and tandem mass spectroscopy (LC-MS/MS) profiling of the intracellular metabolome and the lipidome of GBM cells with dysregulated miRNA expression confirmed the alteration in the metabolite levels associated with lipid metabolism. The identification of regional miRNA expression signatures may underlie the metabolic heterogeneity within the GBM tumour and understanding this relationship may open new avenues for the GBM treatment.

Engineering improved ethylene production: Leveraging systems biology and adaptive laboratory evolution.

Ethylene is a small hydrocarbon gas widely used in the chemical industry. Annual worldwide production currently exceeds 150 million tons, producing considerable amounts of CO2 contributing to climate change. The need for a sustainable alternative is therefore imperative. Ethylene is natively produced by several different microorganisms, including Pseudomonas syringae pv. phaseolicola via a process catalyzed by the ethylene-forming enzyme (EFE), subsequent heterologous expression of EFE has led to ethylene production in non-native bacterial hosts including Escherichia coli and cyanobacteria. However, solubility of EFE and substrate availability remain rate-limiting steps in biological ethylene production. We employed a combination of genome-scale metabolic modelling, continuous fermentation, and protein evolution to enable the accelerated development of a high efficiency ethylene producing E. coli strain, yielding a 49-fold increase in production, the most significant improvement reported to date. Furthermore, we have clearly demonstrated that this increased yield resulted from metabolic adaptations that were uniquely linked to EFE (wild type versus mutant). Our findings provide a novel solution to deregulate metabolic bottlenecks in key pathways, which can be readily applied to address other engineering challenges.

Quantitative Bioreactor Monitoring of Intracellular Bacterial Metabolites in Clostridium autoethanogenum Using Liquid Chromatography-Isotope Dilution Mass Spectrometry.

We report a liquid chromatography-isotope dilution mass spectrometry method for the simultaneous quantification of 131 intracellular bacterial metabolites of Clostridium autoethanogenum. A comprehensive mixture of uniformly 13C-labeled internal standards (U-13C IS) was biosynthesized from the closely related bacterium Clostridium pasteurianum using 4% 13C-glucose as a carbon source. The U-13C IS mixture combined with 12C authentic standards was used to validate the linearity, precision, accuracy, repeatability, limits of detection, and quantification for each metabolite. A robust-fitting algorithm was employed to reduce the weight of the outliers on the quantification data. The metabolite calibration curves were linear with R 2 ≥ 0.99, limits of detection were ≤1.0 µM, limits of quantification were ≤10 µM, and precision/accuracy was within RSDs of 15% for all metabolites. The method was subsequently applied for the daily monitoring of the intracellular metabolites of C. autoethanogenum during a CO gas fermentation over 40 days as part of a study to optimize biofuel production. The concentrations of the metabolites were estimated at steady states of different pH levels using the robust-fitting mathematical approach, and we demonstrate improved accuracy of results compared to conventional regression. Metabolic pathway analysis showed that reactions of the incomplete (branched) tricarboxylic acid "cycle" were the most affected pathways associated with the pH shift in the bioreactor fermentation of C. autoethanogenum and the concomitant changes in ethanol production.

Integrated Metabolomics and Transcriptomics Using an Optimised Dual Extraction Process to Study Human Brain Cancer Cells and Tissues.

The integration of untargeted metabolomics and transcriptomics from the same population of cells or tissue enhances the confidence in the identified metabolic pathways and understanding of the enzyme-metabolite relationship. Here, we optimised a simultaneous extraction method of metabolites/lipids and RNA from ependymoma cells (BXD-1425). Relative to established RNA (mirVana kit) or metabolite (sequential solvent addition and shaking) single extraction methods, four dual-extraction techniques were evaluated and compared (methanol:water:chloroform ratios): cryomill/mirVana (1:1:2); cryomill-wash/Econospin (5:1:2); rotation/phenol-chloroform (9:10:1); Sequential/mirVana (1:1:3). All methods extracted the same metabolites, yet rotation/phenol-chloroform did not extract lipids. Cryomill/mirVana and sequential/mirVana recovered the highest amounts of RNA, at 70 and 68% of that recovered with mirVana kit alone. sequential/mirVana, involving RNA extraction from the interphase of our established sequential solvent addition and shaking metabolomics-lipidomics extraction method, was the most efficient approach overall. Sequential/mirVana was applied to study a) the biological effect caused by acute serum starvation in BXD-1425 cells and b) primary ependymoma tumour tissue. We found (a) 64 differentially abundant metabolites and 28 differentially expressed metabolic genes, discovering four gene-metabolite interactions, and (b) all metabolites and 62% lipids were above the limit of detection, and RNA yield was sufficient for transcriptomics, in just 10 mg of tissue.

Metabolic signatures of osteoarthritis in urine using liquid chromatography-high resolution tandem mass spectrometry.

INTRODUCTION: Osteoarthritis (OA) is a common cause of disability in older people, but its aetiology is not yet fully understood. Biomarkers of OA from metabolomics studies have shown potential use in understanding the progression and pathophysiology of OA. OBJECTIVES: To investigate possible surrogate biomarkers of knee OA in urine using metabolomics to contribute towards a better understanding of OA progression and possible targeted treatment. METHOD: Liquid chromatography-high resolution mass spectrometry (LC-HRMS) was applied in a case-control approach to explore the possible metabolic differences between the urinary profiles of symptomatic knee OA patients (n = 74) (subclassified into inflammatory OA, n = 22 and non-inflammatory OA, n = 52) and non-OA controls (n = 68). Univariate, multivariate and pathway analyses were performed with a rigorous validation including cross-validation, permutation test, prediction and receiver operating characteristic curve to identify significantly altered metabolites and pathways in OA. RESULTS: OA datasets generated 7405 variables and multivariate analysis showed clear separation of inflammatory OA, but not non-inflammatory OA, from non-OA controls. Adequate cross-validation (R2Y = 0.874, Q2 = 0.465) was obtained. The prediction model and the ROC curve showed satisfactory results with a sensitivity of 88%, specificity of 71% and accuracy of 77%. 26 metabolites were identified as potential biomarkers of inflammatory OA using HMDB, authentic standards and/or MS/MS database. CONCLUSION: Urinary metabolic profiles were altered in inflammatory knee OA subjects compared to those with non-inflammatory OA and non-OA controls. These altered profiles associated with perturbed activity of the TCA cycle, pyruvate and amino acid metabolism linked to inflammation, oxidative stress and collagen destruction. Of note, 2-keto-glutaramic acid level was > eightfold higher in the inflammatory OA patients compared to non-OA control, signalling a possible perturbation in glutamine metabolism related to OA progression.

Designing topographically textured microparticles for induction and modulation of osteogenesis in mesenchymal stem cell engineering.

Mesenchymal stem cells are the focus of intense research in bone development and regeneration. The potential of microparticles as modulating moieties of osteogenic response by utilizing their architectural features is demonstrated herein. Topographically textured microparticles of varying microscale features are produced by exploiting phase-separation of a readily soluble sacrificial component from polylactic acid. The influence of varying topographical features on primary human mesenchymal stem cell attachment, proliferation and markers of osteogenesis is investigated. In the absence of osteoinductive supplements, cells cultured on textured microparticles exhibit notably increased expression of osteogenic markers relative to conventional smooth microparticles. They also exhibit varying morphological, attachment and proliferation responses. Significantly altered gene expression and metabolic profiles are observed, with varying histological characteristics in vivo. This study highlights how tailoring topographical design offers cell-instructive 3D microenvironments which allow manipulation of stem cell fate by eliciting the desired downstream response without use of exogenous osteoinductive factors.

Metabolic characterisation of Magnetospirillum gryphiswaldense MSR-1 using LC-MS-based metabolite profiling.

Magnetosomes are nano-sized magnetic nanoparticles with exquisite properties that can be used in a wide range of healthcare and biotechnological applications. They are biosynthesised by magnetotactic bacteria (MTB), such as Magnetospirillum gryphiswaldense MSR-1 (Mgryph). However, magnetosome bioprocessing yields low quantities compared to chemical synthesis of magnetic nanoparticles. Therefore, an understanding of the intracellular metabolites and metabolic networks related to Mgryph growth and magnetosome formation are vital to unlock the potential of this organism to develop improved bioprocesses. In this work, we investigated the metabolism of Mgryph using untargeted metabolomics. Liquid chromatography-mass spectrometry (LC-MS) was performed to profile spent medium samples of Mgryph cells grown under O2-limited (n = 6) and O2-rich conditions (n = 6) corresponding to magnetosome- and non-magnetosome producing cells, respectively. Multivariate, univariate and pathway enrichment analyses were conducted to identify significantly altered metabolites and pathways. Rigorous metabolite identification was carried out using authentic standards, the Mgryph-specific metabolite database and MS/MS mzCloud database. PCA and OPLS-DA showed clear separation and clustering of sample groups with cross-validation values of R2X = 0.76, R2Y = 0.99 and Q2 = 0.98 in OPLS-DA. As a result, 50 metabolites linked to 45 metabolic pathways were found to be significantly altered in the tested conditions, including: glycine, serine and threonine; butanoate; alanine, aspartate and glutamate metabolism; aminoacyl-tRNA biosynthesis and; pyruvate and citric acid cycle (TCA) metabolisms. Our findings demonstrate the potential of LC-MS to characterise key metabolites in Mgryph and will contribute to further understanding the metabolic mechanisms that affect Mgryph growth and magnetosome formation.