MetaboLights: open data repository for metabolomics

Metabolomics and proteomics reveal the inhibitory effect of Lactobacillus crispatus on cervical cancer

Cervical cancer remains a significant global health issue due to its high morbidity and mortality rates. Recently, Lactobacillus crispatus has been recognized for its crucial role in maintaining cervical health. While some studies have explored the use of L. crispatus to mitigate cervical cancer, the underlying mechanisms remain largely unknown. In this study, we employed non-targeted proteomics and metabolomics to investigate how L. crispatus affects the growth of cervical cancer cells (SiHa) and normal cervical cells (Ect1/E6E7). Our findings indicated that the inhibitory effect of L. crispatus on SiHa cells was associated with various biological processes, notably the ferroptosis pathway. Specifically, L. crispatus was found to regulate the expression of proteins such as HMOX1, SLC39A14, VDAC2, ACSL4, and LPCAT3 by SiHa cells, which are closely related to ferroptosis. Additionally, it activated the tricarboxylic acid (TCA) cycle in SiHa cells, leading to increased levels of reactive oxygen species (ROS) and lipid peroxides (LPO). These results revealed the therapeutic potential of L. crispatus in targeting the ferroptosis pathway for cervical cancer treatment, opening new avenues for research and therapy in cervical cancer.

Time-Resolved Multiomics Illustrates Host and Gut Microbe Interactions during Salmonella Infection

Salmonella infection, also known as Salmonellosis, is one of the most common food-borne illnesses. Salmonella infection can trigger host defensive functions, including an inflammatory response. The provoked-host inflammatory response has a significant impact on the bacterial population in the gut. In addition, Salmonella competes with other gut microorganisms for survival and growth within the host. Compositional and functional alterations in gut bacteria occur because of the host immunological response and competition between Salmonella and the gut microbiome. Host variation and the inherent complexity of the gut microbial community make understanding commensal and pathogen interactions particularly difficult during a Salmonella infection. Here, we present metabolomics and lipidomics analyses along with the 16S rRNA sequence analysis, revealing a comprehensive view of the metabolic interactions between the host and gut microbiota during Salmonella infection in a CBA/J mouse model. We found that different metabolic pathways were altered over the four investigated time points of Salmonella infection (days -2, +2, +6, and +13). Furthermore, metatranscriptomics analysis integrated with metabolomics and lipidomics analysis facilitated an understanding of the heterogeneous response of mice, depending on the degree of dysbiosis.

Feature-agnostic metabolomics for determining effective subcytotoxic doses of common pesticides in human cells

Although classical molecular biology assays can provide a measure of cellular response to chemical challenges, they rely on a single biological phenomenon to infer a broader measure of cellular metabolic response. These methods do not always afford the necessary sensitivity to answer questions of subcytotoxic effects, nor do they work for all cell types. Likewise, boutique assays such as cardiomyocyte beat rate may indirectly measure cellular metabolic response, but they too, are limited to measuring a specific biological phenomenon and are often limited to a single cell type. For these reasons, toxicological researchers need new approaches to determine metabolic changes across various doses in differing cell types, especially within the low-dose regime. The data collected herein demonstrate that LC-MS/MS-based untargeted metabolomics with a feature-agnostic view of the data, combined with a suite of statistical methods including an adapted environmental threshold analysis, provides a versatile, robust, and holistic approach to directly monitoring the overall cellular metabolomic response to pesticides. When employing this method in investigating two different cell types, human cardiomyocytes and neurons, this approach revealed separate subcytotoxic metabolomic responses at doses of 0.1 and 1 µM of chlorpyrifos and carbaryl. These findings suggest that this agnostic approach to untargeted metabolomics can provide a new tool for determining effective dose by metabolomics of chemical challenges, such as pesticides, in a direct measurement of metabolomic response that is not cell type-specific or observable using traditional assays.

Microbial transformation of dietary xenobiotics shapes gut microbiome composition

Diet is a major determinant of gut microbiome composition, and variation in diet-microbiome interactions may contribute to variation in their health consequences. To mechanistically understand these relationships, here we map interactions between ∼150 small-molecule dietary xenobiotics and the gut microbiome, including the impacts of these compounds on community composition, the metabolic activities of human gut microbes on dietary xenobiotics, and interindividual variation in these traits. Microbial metabolism can toxify and detoxify these compounds, producing emergent interactions that explain community-specific remodeling by dietary xenobiotics. We identify the gene and enzyme responsible for detoxification of one such dietary xenobiotic, resveratrol, and demonstrate that this enzyme contributes to interindividual variation in community remodeling by resveratrol. Together, these results systematically map interactions between dietary xenobiotics and the gut microbiome and connect toxification and detoxification to interpersonal differences in microbiome response to diet.

A temperature-sensitive metabolic valve and a transcriptional feedback loop drive rapid homeoviscous adaptation in Escherichia coli

All free-living microorganisms homeostatically maintain the fluidity of their membranes by adapting lipid composition to environmental temperatures. Here, we quantify enzymes and metabolic intermediates of the Escherichia coli fatty acid and phospholipid synthesis pathways, to describe how this organism measures temperature and restores optimal membrane fluidity within a single generation after a temperature shock. A first element of this regulatory system is a temperature-sensitive metabolic valve that allocates flux between the saturated and unsaturated fatty acid synthesis pathways via the branchpoint enzymes FabI and FabB. A second element is a transcription-based negative feedback loop that counteracts the temperature-sensitive valve. The combination of these elements accelerates membrane adaptation by causing a transient overshoot in the synthesis of saturated or unsaturated fatty acids following temperature shocks. This strategy is comparable to increasing the temperature of a water bath by adding water that is excessively hot rather than adding water at the desired temperature. These properties are captured in a mathematical model, which we use to show how hard-wired parameters calibrate the system to generate membrane compositions that maintain constant fluidity across temperatures. We hypothesize that core features of the E. coli system will prove to be ubiquitous features of homeoviscous adaptation systems.

The Molecules Gateway: A Homogeneous, Searchable Database of 150k Annotated Molecules from Actinomycetes

Natural products are a sustainable resource for drug discovery, but their identification in complex mixtures remains a daunting task. We present an automated pipeline that compares, harmonizes and ranks the annotations of LC-HRMS data by different tools. When applied to 7,400 extracts derived from 6,566 strains belonging to 86 actinomycete genera, it yielded 150,000 molecules after processing over 50 million MS features. The web-based Molecules Gateway provides a highly interactive access to experimental and calculated data for these molecules, along with the metadata related to extracts and producer strains. We show how the Molecules Gateway can be used to rapidly identify known hard to find microbial products, unreported analogs of known families and not yet described metabolites. The Molecules Gateway, which complements available repositories, contains annotated MS data, both acquired and computationally processed under an identical workflow, making it suitable for global analyses which reveal a large and untapped chemical diversity afforded by actinomycetes.

Annotating full-scan MS data using tandem MS libraries

Full-scan mass spectrometry (MS) data from both liquid chromatography (LC) and MS imaging capture multiple ion forms, including their in-source fragments. Here we leverage such fragments to structurally annotate full-scan data from LC-MS or MS imaging by matching against peak intensity scaled tandem MS spectral libraries using precursor-tolerant reverse match scoring. Applied to inflammatory bowel disease and imaging datasets, we show the approach facilitates re-analyses of data in public repositories.

What is the real value of omics data? Enhancing research outcomes and securing long-term data excellence

A wealth of high-throughput biological data, of which omics constitute a significant fraction, has been made publicly available in repositories over the past decades. These data come in various formats and cover a range of species and research areas providing insights into the complexities of biological systems; the public repositories hosting these data serve as multifaceted resources. The potentially greater value of these data lies in their secondary utilization as the deployment of data science and artificial intelligence in biology advances. Here, we critically evaluate challenges in secondary data use, focusing on omics data of human embryonic kidney cell lines available in public repositories. The emerging issues are obstacles faced by secondary data users across diverse domains as they concern platforms and repositories, which accept deposition of data irrespective of their species type. The evolving landscape of data-driven research in biology prompts re-evaluation of open access data curation and submission procedures to ensure that these challenges do not impede novel research opportunities through data exploitation. This paper aims to draw attention to widespread issues with data reporting and encourages data owners to meticulously curate submissions to maximize not only their immediate research impact but also the long-term legacy of datasets.

Insights into predicting small molecule retention times in liquid chromatography using deep learning

In untargeted metabolomics, structures of small molecules are annotated using liquid chromatography-mass spectrometry by leveraging information from the molecular retention time (RT) in the chromatogram and m/z (formerly called ''mass-to-charge ratio'') in the mass spectrum. However, correct identification of metabolites is challenging due to the vast array of small molecules. Therefore, various in silico tools for mass spectrometry peak alignment and compound prediction have been developed; however, the list of candidate compounds remains extensive. Accurate RT prediction is important to exclude false candidates and facilitate metabolite annotation. Recent advancements in artificial intelligence (AI) have led to significant breakthroughs in the use of deep learning models in various fields. Release of a large RT dataset has mitigated the bottlenecks limiting the application of deep learning models, thereby improving their application in RT prediction tasks. This review lists the databases that can be used to expand training datasets and concerns the issue about molecular representation inconsistencies in datasets. It also discusses the application of AI technology for RT prediction, particularly in the 5 years following the release of the METLIN small molecule RT dataset. This review provides a comprehensive overview of the AI applications used for RT prediction, highlighting the progress and remaining challenges. SCIENTIFIC CONTRIBUTION: This article focuses on the advancements in small molecule retention time prediction in computational metabolomics over the past five years, with a particular emphasis on the application of AI technologies in this field. It reviews the publicly available datasets for small molecule retention time, the molecular representation methods, the AI algorithms applied in recent studies. Furthermore, it discusses the effectiveness of these models in assisting with the annotation of small molecule structures and the challenges that must be addressed to achieve practical applications.

Characterization of a colistin resistant, hypervirulent hospital isolate of Acinetobacter courvalinii from Canada

Non-baumannii Acinetobacter spp. are becoming more prevalent in clinical settings including those that present resistance to last-resort antibiotics such as colistin. AB222-IK40 is an Acinetobacter courvalinii strain isolated from the Ottawa Hospital Research Institute located in Ottawa, Canada. To our knowledge, it is the first report of clinical A. courvalinii in Canada. Based on the susceptibility profile, AB222-IK40 is resistant to colistin and non-susceptible to ertapenem. Whole-genome sequencing allowed for genomic investigation into colistin resistance mechanisms. No previously identified mechanism(s) were observed, but a mobile colistin resistance (mcr)-like gene and a UDP-glucose dehydrogenase gene were identified. Based on phylogenomic analyses, the mcr-like gene is an intrinsic phosphoethanolamine transferase. This gene family is implicated in one of the many mechanisms responsible for colistin resistance in Acinetobacter baumannii as well as Acinetobacter modestus. UDP-glucose dehydrogenase is involved in colistin resistance in Enterobacterales and has been shown to be involved in capsule formation in A. baumannii. Global lipidomics revealed greater abundance of phosphatidyl-myo-inositol and lyso-phosphatidyl ethanolamine moieties in the membrane of A. courvalinii than in A. baumannii. Lipidomic profiles showed differences that were probably responsible for the colistin resistance phenotype in AB222-IK40. This isolate was also hypervirulent based on survival assays in Galleria mellonella. As this is the first report of A. courvalinii from a hospital in Canada, this species may be an emerging clinical pathogen, and therefore, it is important to understand this mechanism of its colistin resistance and hypervirulence.

Modulation of liver metabolism and gut microbiota by Alhagi-honey alleviated heat stress-induced liver damage

Alhagi-honey (AH) is a well-established traditional ethnic medicine with advantageous effects against diarrhea and headaches. We aimed to explore the preventive effect of AH on liver damage induced by heat stress (HS) and its underlying mechanism. HS models were established by thermostat, and mice were treated at 39 ℃ for 10 h, lasting for 7 days. Hematoxylin-eosin (H&E) staining and Periodic Acid-Schiff (PAS) staining were used for histological observation, and transmission electron microscopy (TEM) was used for ultrastructure examination of hepatocytes. Gut microbiota (GM) composition and liver metabolites were respectively analyzed by 16S rRNA sequencing and non-targeted metabolome sequencing. AH pretreatment alleviated liver damage caused by heat stress in mice. The main manifestation was that AH alleviated serum aspartate transferase (AST) and aspartate transaminase (ALT). It was found that AH improved symptoms of hepatocyte damage. In addition, the relative abundance of f_Rikenellaceae, g_Incertae_Sedis and s_Staphylococcus_Orisratti, g_Lachnoclostridium, g_GCA-900066575, and s_Alistipes_inops were modified by AH and these bacterial genera showed association with 6 metabolites (2- (3,4-dihydroxyphenyl) acetamide, 3-hydroxy-3-methylpentanedioic acid, PC (17:0/17:1), Y-L-Glutamy-L-glutamic acid, L-Isoleucine, 5-Methyluridine, 8,8-dimethyl-2-phenyl-4H,8H-pyrano [2, 3-h] chromen-4-one). The Pearson analysis also showed a strong correlation between these microbes and 2 risk indicators (AST and ALT) of liver damage. AH alleviated HS-induced liver damage by regulating liver metabolism and maintaining normal GM. It demonstrated that AH held potential as a prophylactic drug for the prevention of HS-induced liver damage.

Non-canonical metabolic and molecular effects of calorie restriction are revealed by varying temporal conditions

Calorie restriction (CR) extends lifespan and healthspan in diverse species. Comparing ad libitum- and CR-fed mice is challenging due to their significantly different feeding patterns, with CR-fed mice consuming their daily meal in 2 h and then subjecting themselves to a prolonged daily fast. Here, we examine how ad libitum- and CR-fed mice respond to tests performed at various times and fasting durations and find that the effects of CR-insulin sensitivity, circulating metabolite levels, and mechanistic target of rapamycin 1 (mTORC1) activity-result from the specific temporal conditions chosen, with CR-induced improvements in insulin sensitivity observed only after a prolonged fast, and the observed differences in mTORC1 activity between ad libitum- and CR-fed mice dependent upon both fasting duration and the specific tissue examined. Our results demonstrate that much of our understanding of the effects of CR are related to when, relative to feeding, we choose to examine the mice.

Enhanced fatty acid biosynthesis by Sigma28 in stringent responses contributes to multidrug resistance and biofilm formation in Helicobacter pylori

The metabolic state of bacteria significantly contributes to their resistance to antibiotics; however, the specific metabolic mechanisms conferring antimicrobial resistance in Helicobacter pylori remain largely understudied. Employing transcriptomic and non-targeted metabolomics, we characterized the metabolic reprogramming of H. pylori when challenged with antibiotic agents. We observed a notable increase in both genetic and key proteomic components involved in fatty acid biosynthesis. Inhibition of this pathway significantly enhanced the antibiotic susceptibility of the sensitive and multidrug-resistant H. pylori strains while also disrupting their biofilm-forming capacities. Further analysis revealed that antibiotic treatment induced a stringent response, triggering the expression of the hp0560-hp0557 operon regulated by Sigma28 (σ28). This activation in turn stimulated the fatty acid biosynthetic pathway, thereby enhancing the antibiotic tolerance of H. pylori. Our findings reveal a novel adaptive strategy employed by H. pylori to withstand antibiotic stress.

Isotope dilution with isotopically labeled biomass: An effective alternative for quantitative metabolomics

BACKGROUND

State-of-the-art quantitative metabolomics relies on isotope dilution using internal standards (IS) derived from fully 13C labeled biomass. By spiking samples and external standards with known amounts of IS, the spike characterization demands are kept to a minimum. In fact, it is sufficient to experimentally assess the isotopic enrichment of the IS. This study develops the yeast derived IS toolbox further, (1) by characterizing the concentration levels of hydrophilic metabolites in a yeast fermentation batch and (2) by exploring the analytical figures of merit of one-point IS versus multipoint external calibration using IS, the established gold-standard for quantitative metabolomics.

RESULTS

Independent reverse isotope dilution experiments using different chromatographic methods over a period of several months, delivered a list of 83 13C-labeled metabolites with fully characterized concentration and their uncertainty, covering 5 orders of magnitude, from the nanomolar to the low millimolar range. The 13C-labeled yeast-derived IS showed excellent intermediate stability with 92 % of molecules showing inter-method RSDs ≤30 % (75 % of molecules showed RSDs ≤15 %) over a timeframe of five months. One-point internal standardization with the characterized labeled biomass achieved figures of merit equivalent to multipoint calibrations for the majority of metabolites.

SIGNIFICANCE

The proposed calibration workflow rationalizes time and standard expenditure and is particularly beneficial for laboratories dealing with wide-target assays and small analysis batches. The present assessment serves as a seminal study for further developments of the concept towards absolute quantification from archive high-resolution MS data of U13C-biomass-spiked samples and the implementation of quick biomass recalibration with each experiment, promising seamless transition between internal standards derived from different fermentation batches.

AspSnFR: A genetically encoded biosensor for real-time monitoring of aspartate in live cells

Aspartate is crucial for nucleotide synthesis, ammonia detoxification, and maintaining redox balance via the malate-aspartate-shuttle (MAS). To disentangle these multiple roles of aspartate metabolism, tools are required that measure aspartate concentrations in real time and in live cells. We introduce AspSnFR, a genetically encoded green fluorescent biosensor for intracellular aspartate, engineered through displaying and screening biosensor libraries on mammalian cells. In live cells, AspSnFR is able to precisely and quantitatively measure cytosolic aspartate concentrations and dissect its production from glutamine. Combining high-content imaging of AspSnFR with pharmacological perturbations exposes differences in metabolic vulnerabilities of aspartate levels based on nutrient availability. Further, AspSnFR facilitates tracking of aspartate export from mitochondria through SLC25A12, the MAS' key transporter. We show that SLC25A12 is a rapidly responding and direct route to couple Ca2+ signaling with mitochondrial aspartate export. This establishes SLC25A12 as a crucial link between cellular signaling, mitochondrial respiration, and metabolism.

Fungicide Metabolite MS2 Spectral Libraries for Comprehensive Human Biomonitoring

Fungicides undergo rapid metabolism and are excreted in the urine. There are few methods for screening these ubiquitous compounds, which have a high potential for human exposure. High-resolution mass spectrometry (HRMS) is a suitable technique to assess fungicide exposures; however, there is a lack of spectral libraries for fungicide annotation and in particular for downstream metabolites. We created spectral libraries for 32 fungicides for suspect screening. Fungicide standards were administered to mice, and 24-h urine was analyzed using hydrophilic interaction and reversed-phase chromatography coupled to hybrid quadrupole-orbitrap mass spectrometry. Suspect metabolite MS2 spectra for library creation were selected based on the ratio of exposed-to-control mouse urine. MS2 libraries were applied to urine collected from female university students (n = 73). Several tetraconazole and tebuconazole metabolites were detected in 3% (2/73) of the samples. The creation of comprehensive suspect screening MS2 libraries is a useful tool to detect fungicide exposure for human biomonitoring.

Functional implications of glycans and their curation: insights from the workshop held at the 16th Annual International Biocuration Conference in Padua, Italy

Dynamic changes in protein glycosylation impact human health and disease progression. However, current resources that capture disease and phenotype information focus primarily on the macromolecules within the central dogma of molecular biology (DNA, RNA, proteins). To gain a better understanding of organisms, there is a need to capture the functional impact of glycans and glycosylation on biological processes. A workshop titled "Functional impact of glycans and their curation" was held in conjunction with the 16th Annual International Biocuration Conference to discuss ongoing worldwide activities related to glycan function curation. This workshop brought together subject matter experts, tool developers, and biocurators from over 20 projects and bioinformatics resources. Participants discussed four key topics for each of their resources: (i) how they curate glycan function-related data from publications and other sources, (ii) what type of data they would like to acquire, (iii) what data they currently have, and (iv) what standards they use. Their answers contributed input that provided a comprehensive overview of state-of-the-art glycan function curation and annotations. This report summarizes the outcome of discussions, including potential solutions and areas where curators, data wranglers, and text mining experts can collaborate to address current gaps in glycan and glycosylation annotations, leveraging each other's work to improve their respective resources and encourage impactful data sharing among resources. Database URL: https://wiki.glygen.org/Glycan_Function_Workshop_2023.

Anoectochilus roxburghii Extract Extends the Lifespan of Caenorhabditis elegans through Activating the daf-16/FoxO Pathway

As a significant global issue, aging is prompting people's interest in the potential anti-aging properties of Anoectochilus roxburghii (A. roxburghii), a plant traditionally utilized in various Asian countries for its purported benefits in treating diabetes and combating aging. However, the specific anti-aging components and mechanisms of A. roxburghii remain unclear. This study aims to investigate the anti-aging effects and mechanisms of A. roxburghii extract E (ARE). Caenorhabditis elegans (C. elegans) were exposed to media containing different concentrations of ARE whose superior in vitro radical scavenging capacity was thus identified. Lifespan assays, stress resistance tests, and RT-qPCR analyses were conducted to evaluate anti-aging efficacy, reactive oxygen species (ROS) levels, antioxidant enzyme activity, and daf-16, sod-3, and gst-4 levels. Additionally, transcriptomic and metabolomic analyses were performed to elucidate the potential anti-aging mechanisms of ARE. Fluorescence protein assays and gene knockout experiments were employed to validate the impacts of ARE on anti-aging mechanisms. Our results revealed that ARE not only prolonged the lifespan of C. elegans but also mitigated ROS and lipofuscin accumulation, and boosted resistance to UV and heat stress. Furthermore, ARE modulated the expression of pivotal anti-aging genes including daf-16, sod-3, and gst-4, facilitating the nuclear translocation of DAF-16. Significantly, ARE failed to extend the lifespan of daf-16-deficient C. elegans (CF1038), indicating its dependency on the daf-16/FoxO signaling pathway. These results underscored the effectiveness of ARE as a natural agent for enhancing longevity and stress resilience to C. elegans, potentially to human.

Comparing the Extraction Performance in Mouse Plasma of Different Biphasic Methods for Polar and Nonpolar Compounds

Many metabolomic studies are interested in both polar and nonpolar analyses. However, the available sample volume often precludes multiple separate extractions. Therefore, there are major advantages in performing a biphasic extraction and retaining both phases for subsequent separate analyses. To be successful, such approaches require the method to be robust and repeatable for both phases. Hence, we determined the performance of three extraction protocols, plus two variant versions, using 25 μL of commercially available mouse plasma. The preferred option for nonpolar lipids was a modified diluted version of a method employing methyl tert-butyl ether (MTBE) suggested by Matyash and colleagues due to its high repeatability for nonpolar compounds. For polar compounds, the Bligh-Dyer method performs best for sensitivity but with consequentially poorer lipid performance. Overall, the scaled-down version of the MTBE method gave the best overall performance, with high sensitivity for both polar and nonpolar compounds and good repeatability for polar compounds in particular.

Overview and limitations of database in global traditional medicines: A narrative review

The study of traditional medicine has garnered significant interest, resulting in various research areas including chemical composition analysis, pharmacological research, clinical application, and quality control. The abundance of available data has made databases increasingly essential for researchers to manage the vast amount of information and explore new drugs. In this article we provide a comprehensive overview and summary of 182 databases that are relevant to traditional medicine research, including 73 databases for chemical component analysis, 70 for pharmacology research, and 39 for clinical application and quality control from published literature (2000-2023). The review categorizes the databases by functionality, offering detailed information on websites and capacities to facilitate easier access. Moreover, this article outlines the primary function of each database, supplemented by case studies to aid in database selection. A practical test was conducted on 68 frequently used databases using keywords and functionalities, resulting in the identification of highlighted databases. This review serves as a reference for traditional medicine researchers to choose appropriate databases and also provides insights and considerations for the function and content design of future databases.

Multiomic profiling of medulloblastoma reveals subtype-specific targetable alterations at the proteome and N-glycan level

Medulloblastomas (MBs) are malignant pediatric brain tumors that are molecularly and clinically heterogenous. The application of omics technologies-mainly studying nucleic acids-has significantly improved MB classification and stratification, but treatment options are still unsatisfactory. The proteome and their N-glycans hold the potential to discover clinically relevant phenotypes and targetable pathways. We compile a harmonized proteome dataset of 167 MBs and integrate findings with DNA methylome, transcriptome and N-glycome data. We show six proteome MB subtypes, that can be assigned to two main molecular programs: transcription/translation (pSHHt, pWNT and pG3myc), and synapses/immunological processes (pSHHs, pG3 and pG4). Multiomic analysis reveals different conservation levels of proteome features across MB subtypes at the DNA methylome level. Aggressive pGroup3myc MBs and favorable pWNT MBs are most similar in cluster hierarchies concerning overall proteome patterns but show different protein abundances of the vincristine resistance-associated multiprotein complex TriC/CCT and of N-glycan turnover-associated factors. The N-glycome reflects proteome subtypes and complex-bisecting N-glycans characterize pGroup3myc tumors. Our results shed light on targetable alterations in MB and set a foundation for potential immunotherapies targeting glycan structures.

NAD+ precursors prolong survival and improve cardiac phenotypes in a mouse model of Friedreich's Ataxia

Friedreich's ataxia (FRDA) is a progressive disorder caused by insufficient expression of frataxin, which plays a critical role in assembly of iron-sulfur centers in mitochondria. Individuals are cognitively normal but display a loss of motor coordination and cardiac abnormalities. Many ultimately develop heart failure. Administration of nicotinamide adenine dinucleotide-positive (NAD+) precursors has shown promise in human mitochondrial myopathy and rodent models of heart failure, including mice lacking frataxin in cardiomyocytes. We studied mice with systemic knockdown of frataxin (shFxn), which display motor deficits and early mortality with cardiac hypertrophy. Hearts in these mice do not "fail" per se but become hyperdynamic with small chamber sizes. Data from an ongoing natural history study indicate that hyperdynamic hearts are observed in young individuals with FRDA, suggesting that the mouse model could reflect early pathology. Administering nicotinamide mononucleotide or riboside to shFxn mice increases survival, modestly improves cardiac hypertrophy, and limits increases in ejection fraction. Mechanistically, most of the transcriptional and metabolic changes induced by frataxin knockdown are insensitive to NAD+ precursor administration, but glutathione levels are increased, suggesting improved antioxidant capacity. Overall, our findings indicate that NAD+ precursors are modestly cardioprotective in this model of FRDA and warrant further investigation.

Characterization of Electrospray Ionization Complexity in Untargeted Metabolomic Studies

The annotation of metabolites detected in LC-MS-based untargeted metabolomics studies routinely applies accurate m/z of the intact metabolite (MS1) as well as chromatographic retention time and MS/MS data. Electrospray ionization and transfer of ions through the mass spectrometer can result in the generation of multiple "features" derived from the same metabolite with different m/z values but the same retention time. The complexity of the different charged and neutral adducts, in-source fragments, and charge states has not been previously and deeply characterized. In this paper, we report the first large-scale characterization using publicly available data sets derived from different research groups, instrument manufacturers, LC assays, sample types, and ion modes. 271 m/z differences relating to different metabolite feature pairs were reported, and 209 were annotated. The results show a wide range of different features being observed with only a core 32 m/z differences reported in >50% of the data sets investigated. There were no patterns reporting specific m/z differences that were observed in relation to ion mode, instrument manufacturer, LC assay type, and mammalian sample type, although some m/z differences were related to study group (mammal, microbe, plant) and mobile phase composition. The results provide the metabolomics community with recommendations of adducts, in-source fragments, and charge states to apply in metabolite annotation workflows.

Illuminating the dark space of neutral glycosphingolipidome by selective enrichment and profiling at multi-structural levels

Glycosphingolipids (GSLs) are essential components of cell membranes, particularly enriched in the nervous system. Altered molecular distributions of GSLs are increasingly associated with human diseases, emphasizing the significance of lipidomic profiling. Traditional GSL analysis methods are hampered by matrix effect from phospholipids and the difficulty in distinguishing structural isomers. Herein, we introduce a highly sensitive workflow that harnesses magnetic TiO2 nanoparticle-based selective enrichment, charge-tagging Paternò-Büchi reaction, and liquid chromatography-tandem mass spectrometry. This approach enables mapping over 300 distinct GSLs in brain tissues by defining sugar types, long chain bases, N-acyl chains, and the locations of desaturation and hydroxylation. Relative quantitation of GSLs across multiple structural levels provides evidence of dysregulated gene and protein expressions of FA2H and CerS2 in human glioma tissue. Based on the structural features of GSLs, our method accurately differentiates human glioma with/without isocitrate dehydrogenase genetic mutation, and normal brain tissue.

Evaluation of metabolomics-based urinary biomarker models for recognizing major depression disorder and bipolar disorder

BACKGROUND

Major depressive disorder (MDD) and bipolar disorder (BD) are psychiatric disorders with overlapping symptoms, leading to high rates of misdiagnosis due to the lack of biomarkers for differentiation. This study aimed to identify metabolic biomarkers in urine samples for diagnosing MDD and BD, as well as to establish unbiased differential diagnostic models.

METHODS

We utilized a metabolomics approach employing ultra-high performance liquid chromatography-mass spectrometry (UHPLC-MS) to analyze the metabolic profiles of urine samples from individuals with MDD (n = 50), BD (n = 12), and healthy controls (n = 50). The identification of urine metabolites was verified using MS data analysis tools and online metabolite databases.

RESULTS

Two diagnostic panels consisting of a combination of metabolites and clinical indicators were identified-one for MDD and another for BD. The discriminative capacity of these panels was assessed using the area under the receiver operating characteristic (ROC) curve, yielding an area under the curve (AUC) of 0.9084 for MDD and an AUC value of 0.9017 for BD.

CONCLUSIONS

High-resolution mass spectrometry-based assays show promise in identifying urinary biomarkers for depressive disorders. The combination of urine metabolites and clinical indicators is effective in differentiating healthy controls from individuals with MDD and BD. The metabolic pathway indicating oxidative stress is seen to significantly contribute to depressive disorders.

Obscurity of chlorophyll tails - Is chlorophyll with farnesyl tail incorporated into PSII complexes?

Chlorophyll is essential in photosynthesis, converting sunlight into chemical energy in plants, algae, and certain bacteria. Its structure, featuring a porphyrin ring enclosing a central magnesium ion, varies in forms like chlorophyll a, b, c, d, and f, allowing light absorption at a broader spectrum. With a 20-carbon phytyl tail (except for chlorophyll c), chlorophyll is anchored to proteins. Previous findings suggested the presence of chlorophyll with a modified farnesyl tail in thermophilic cyanobacteria Thermosynechoccocus vestitus. In our Arabidopsis thaliana PSII cryo-EM map, specific chlorophylls showed incomplete phytyl tails, suggesting potential farnesyl modifications. However, further high-resolution mass spectrometry (HRMS) analysis in A. thaliana and T. vestitus did not confirm the presence of any farnesyl tails. Instead, we propose the truncated tails in PSII models may result from binding pocket flexibility rather than actual modifications.

Proteomic and metabolomic profiling of plasma predicts immune-related adverse events in older patients with advanced non-small cell lung cancer

The clinical success of immune checkpoint inhibitors is compromised by the fact of immune-related adverse events (irAEs), especially for older patients. To identify predictive biomarkers for older patients with irAEs, we used multiplex immunoassay and flow cytometry and liquid chromatography-tandem mass spectrometry to test immune factors and plasma protein and metabolites levels in non-small cell lung cancer (NSCLC) patients. The results showed that older patients with irAEs displayed lower CD28, CD4+ T cell, and B cell and higher interleukin (IL)-10 and CCL2 levels at baseline. Besides, lower aldolase, fructose-bisphosphate B (ALDOB), higher ST6GAL1, and lower lactate/pyruvate ratio at baseline were found in older patients with irAEs. Based on metabolomic markers, predictive models were developed to distinguish patients with grade 2-4 irAEs from grade 0-1 (Area under curve, AUC = 0.831) and to distinguish patients with grade 3-4 irAEs from grade 2 (AUC = 1). Our results confirmed the predictive value of plasma metabolites for irAEs in older patients with NSCLC.

Discovery of Free Glycated Amines and Glycated Urea in Diabetic Plasma: Potential Implications in Diabetes

The role of protein glycation in the pathogenesis of diabetes has been well established. Akin to proteins, free amino acids and other small-molecule amines are also susceptible to glycation in hyperglycemic conditions and may have a role in the pathogenesis of the disease. However, information about glycation of free amino acids and other small-molecule amines is relatively obscure. In the quest to discover small-molecule glycated amines in the plasma, we have synthesized glycated amino acids, glycated creatine, and glycated urea, and by using a high-resolution accurate mass spectrometer, a mass spectral library was developed comprising the precursor and predominant fragment masses of glycated amines. Using this information, we report the discovery of the glycation of free lysine, arginine, and leucine/isoleucine from the plasma of diabetic patients. This has great physiological significance as glycation of these amino acids may create their deficiency and affect vital physiological processes such as protein synthesis, cell signaling, and insulin secretion. Also, these glycated amino acids could serve as potential markers of diabetes and its complications. While other amines, such as creatinine and urea, accumulate in the plasma and act as biomarkers of diabetic nephropathy. For the first time, we report the detection of glycated urea in diabetic plasma, which is confirmed by matching the precursor and fragment masses with the in vitro synthesized glycated urea by using 12C6 and 13C6-glucose. Further, we quantified glycated urea detected in two forms, monoglycated urea (MGU) and diglycated urea (DGU), by a targeted mass spectrometric approach in the plasma of healthy, diabetic, and diabetic nephropathy subjects. Both MGU and DGU showed a positive correlation with clinical parameters, such as blood glucose and HbA1c. Given that urea gets converted to glycated urea in hyperglycemic conditions, it is crucial to quantify MGU and DGU along with the urea for the diagnosis of diabetic nephropathy and study their physiological role in diabetes.

A 5:2 intermittent fasting regimen ameliorates NASH and fibrosis and blunts HCC development via hepatic PPARα and PCK1

The role and molecular mechanisms of intermittent fasting (IF) in non-alcoholic steatohepatitis (NASH) and its transition to hepatocellular carcinoma (HCC) are unknown. Here, we identified that an IF 5:2 regimen prevents NASH development as well as ameliorates established NASH and fibrosis without affecting total calorie intake. Furthermore, the IF 5:2 regimen blunted NASH-HCC transition when applied therapeutically. The timing, length, and number of fasting cycles as well as the type of NASH diet were critical parameters determining the benefits of fasting. Combined proteome, transcriptome, and metabolome analyses identified that peroxisome-proliferator-activated receptor alpha (PPARα) and glucocorticoid-signaling-induced PCK1 act co-operatively as hepatic executors of the fasting response. In line with this, PPARα targets and PCK1 were reduced in human NASH. Notably, only fasting initiated during the active phase of mice robustly induced glucocorticoid signaling and free-fatty-acid-induced PPARα signaling. However, hepatocyte-specific glucocorticoid receptor deletion only partially abrogated the hepatic fasting response. In contrast, the combined knockdown of Ppara and Pck1 in vivo abolished the beneficial outcomes of fasting against inflammation and fibrosis. Moreover, overexpression of Pck1 alone or together with Ppara in vivo lowered hepatic triglycerides and steatosis. Our data support the notion that the IF 5:2 regimen is a promising intervention against NASH and subsequent liver cancer.

Saiga antelope horn suppresses febrile seizures in rats by regulating neurotransmitters and the arachidonic acid pathway

BACKGROUND

Saiga antelope horn (SAH) is a traditional Chinese medicine for treating febrile seizure (FS) with precise efficacy, but its mechanism of action and functional substances are still unclear. Given the need for further research on SAH, our group conducted studies to elucidate its mechanisms and active substances.

METHODS

An FS rat pup model was constructed through intraperitoneal injection of LPS and hyperthermia induction. Behavioural indicators of seizures, hippocampal histopathological alterations, serum levels of inflammatory cytokines and hippocampal levels of neurotransmitters were observed and measured to investigate the effects of SAH on FS model rats. Hippocampal metabolomics and network pharmacology analyses were conducted to reveal the differential metabolites, key peptides and pathways involved in the suppression of FS by SAH.

RESULTS

SAH suppressed FS, decreased the inflammatory response and regulated the Glu-GABA balance. Metabolomic analysis revealed 13 biomarkers of FS, of which SAH improved the levels of 8 differential metabolites. Combined with network pharmacology, a "biomarker-core target-key peptide" network was constructed. The peptides of SAH, such as YGQL and LTGGF, could exert therapeutic effects via the arachidonic acid pathway. Molecular docking and ELISA results indicated that functional peptides of SAH could bind to PTGS2 target, inhibiting the generation of AA and its metabolites in hippocampal samples.

CONCLUSION

In summary, the functional peptides contained in SAH are the main material basis for the treatment of FS, potentially acting through neurotransmitter regulation and the arachidonic acid pathway.

Multi-omic analysis tools for microbial metabolites prediction

How to resolve the metabolic dark matter of microorganisms has long been a challenging problem in discovering active molecules. Diverse omics tools have been developed to guide the discovery and characterization of various microbial metabolites, which make it gradually possible to predict the overall metabolites for individual strains. The combinations of multi-omic analysis tools effectively compensates for the shortcomings of current studies that focus only on single omics or a broad class of metabolites. In this review, we systematically update, categorize and sort out different analysis tools for microbial metabolites prediction in the last five years to appeal for the multi-omic combination on the understanding of the metabolic nature of microbes. First, we provide the general survey on different updated prediction databases, webservers, or software that based on genomics, transcriptomics, proteomics, and metabolomics, respectively. Then, we discuss the essentiality on the integration of multi-omics data to predict metabolites of different microbial strains and communities, as well as stressing the combination of other techniques, such as systems biology methods and data-driven algorithms. Finally, we identify key challenges and trends in developing multi-omic analysis tools for more comprehensive prediction on diverse microbial metabolites that contribute to human health and disease treatment.

Metabolic signature and response to glutamine deprivation are independent of p53 status in B cell malignancies

The tumor suppressor p53 has been described to control various aspects of metabolic reprogramming in solid tumors, but in B cell malignancies that role is as yet unknown. We generated pairs of p53 functional and knockout (KO) clones from distinct B cell malignancies (acute lymphoblastic leukemia, chronic lymphocytic leukemia, diffuse large B cell lymphoma, and multiple myeloma). Metabolomics and isotope tracing showed that p53 loss did not drive a common metabolic signature. Instead, cell lines segregated according to cell of origin. Next, we focused on glutamine as a crucial energy source in the B cell tumor microenvironment. In both TP53 wild-type and KO cells, glutamine deprivation induced cell death through the integrated stress response, via CHOP/ATF4. Lastly, combining BH3 mimetic drugs with glutamine starvation emerged as a possibility to target resistant clones. In conclusion, our analyses do not support a common metabolic signature of p53 deficiency in B cell malignancies and suggest therapeutic options for exploration based on glutamine dependency.

Functional metabolomics reveals arsenic-induced inhibition of linoleic acid metabolism in mice kidney in drinking water

Arsenic (As) is a heavy metal known for its detrimental effects on the kidneys, but the precise mechanisms underlying its toxicity remain unclear. In this study, we employed an integrated approach combining traditional toxicology methods with functional metabolomics to explore the nephrotoxicity induced by As in mice. Our findings demonstrated that after 28 days of exposure to sodium arsenite, blood urea nitrogen, serum creatinine levels were significantly increased, and pathological examination of the kidneys revealed dilation of renal tubules and glomerular injury. Additionally, uric acid, total cholesterol, and low-density lipoprotein cholesterol levels were significant increased while triglyceride level was decreased, resulting in renal insufficiency and lipid disorders. Subsequently, the kidney metabolomics analysis revealed that As exposure disrupted 24 differential metabolites, including 14 up-regulated and 10 down-regulated differential metabolites. Ten metabolic pathways including linoleic acid and glycerophospholipid metabolism were significantly enriched. Then, 80 metabolic targets and 168 predicted targets were identified using metabolite network pharmacology analysis. Of particular importance, potential toxicity targets, such as glycine amidinotransferase, mitochondrial (GATM), and nitric oxide synthase, and endothelial (NOS3), were prioritized through the "metabolite-target-pathway" network. Receiver operating characteristics curve and molecular docking analyses suggested that 1-palmitoyl-2-myristoyl-sn-glycero-3-PC, linoleic acid, and L-hydroxyarginine might be functional metabolites associated with GATM and NOS3. Moreover, targeted verification result showed that the level of linoleic acid in As group was 0.4951 μg/mL, which was significantly decreased compared with the control group. And in vivo and in vitro protein expression experiments confirmed that As exposure inhibited the expression of GATM and NOS3. In conclusion, these results suggest that As-induced renal injury may be associated with the inhibition of linoleic acid metabolism through the down-regulation of GATM and NOS3, resulting in decreased levels of linoleic acid, 1-palmitoyl-2-myristoyl-sn-glycero-3-PC, and L-hydroxyarginine metabolites.

Bioformulation of Bacillus proteolyticus MITWPUB1 and its biosurfactant to control the growth of phytopathogen Sclerotium rolfsii for the crop Brassica juncea var local, as a sustainable approach

Bacillus proteolyticus MITWPUB1 is a potential producer of biosurfactants (BSs), and the organism is also found to be a producer of plant growth promoting traits, such as hydrogen cyanide and indole acetic acid (IAA), and a solubilizer of phosphate. The BSs were reportedly a blend of two classes, namely glycolipids and lipopeptides, as found by thin layer chromatography and Fourier-transform infrared spectroscopy analysis. Furthermore, semi-targeted metabolite profiling via liquid chromatography mass spectroscopy revealed the presence of phospholipids, lipopeptides, polyamines, IAA derivatives, and carotenoids. The BS showed dose-dependent antagonistic activity against Sclerotium rolfsii; scanning electron microscopy showed the effects of the BS on S. rolfsii in terms of mycelial deformations and reduced branching patterns. In vitro studies showed that the application of B. proteolyticus MITWPUB1 and its biosurfactant to seeds of Brassica juncea var local enhanced the seed germination rate. However, sawdust-carrier-based bioformulation with B. proteolyticus MITWPUB1 and its BS showed increased growth parameters for B. juncea var L. This study highlights a unique bioformulation combination that controls the growth of the phytopathogen S. rolfsii and enhances the plant growth of B. juncea var L. Bacillus proteolyticus MITWPUB1 was also shown for the first time to be a prominent BS producer with the ability to control the growth of the phytopathogen S. rolfsii.

Quantitative Metabolomics and Lipoprotein Analysis of PDAC Patients Suggests Serum Marker Categories for Pancreatic Function, Pancreatectomy, Cancer Metabolism, and Systemic Disturbances

Pancreatic ductal adenocarcinoma (PDAC) is difficult to diagnose in the early stages and lacks reliable biomarkers. The scope of this project was to establish quantitative nuclear magnetic resonance (NMR) spectroscopy to comprehensively study blood serum alterations in PDAC patients. Serum samples from 34 PDAC patients obtained before and after pancreatectomy as well as 83 age- and sex-matched control samples from healthy donors were analyzed with in vitro diagnostics research (IVDr) proton NMR spectroscopy at 600 MHz. Uni- and multivariate statistics were applied to identify significant biofluid alterations. We identified 29 significantly changed metabolites and 98 lipoproteins when comparing serum from healthy controls with those of PDAC patients. The most prominent features were assigned to (i) markers of pancreatic function (e.g., glucose and blood triglycerides), (ii) markers related to surgery (e.g., ketone bodies and blood cholesterols), (iii) PDAC-associated markers (e.g., amino acids and creatine), and (iv) markers for systemic disturbances in PDAC (e.g., gut metabolites DMG, TMAO, DMSO2, and liver lipoproteins). Quantitative serum NMR spectroscopy is suited as a diagnostic tool to investigate PDAC. Remarkably, 2-hydroxybutyrate (2-HB) as a previously suggested marker for insulin resistance was found in extraordinarily high levels only after pancreatectomy, suggesting this metabolite is the strongest marker for pancreatic loss of function.

DNA nanomachines reveal an adaptive energy mode in confinement-induced amoeboid migration powered by polarized mitochondrial distribution

Energy metabolism is highly interdependent with adaptive cell migration in vivo. Mechanical confinement is a critical physical cue that induces switchable migration modes of the mesenchymal-to-amoeboid transition (MAT). However, the energy states in distinct migration modes, especially amoeboid-like stable bleb (A2) movement, remain unclear. In this report, we developed multivalent DNA framework-based nanomachines to explore strategical mitochondrial trafficking and differential ATP levels during cell migration in mechanically heterogeneous microenvironments. Through single-particle tracking and metabolomic analysis, we revealed that fast A2-moving cells driven by biomimetic confinement recruited back-end positioning of mitochondria for powering highly polarized cytoskeletal networks, preferentially adopting an energy-saving mode compared with a mesenchymal mode of cell migration. We present a versatile DNA nanotool for cellular energy exploration and highlight that adaptive energy strategies coordinately support switchable migration modes for facilitating efficient metastatic escape, offering a unique perspective for therapeutic interventions in cancer metastasis.

The circadian metabolome of atopic dermatitis

BACKGROUND

Atopic dermatitis (AD) is a chronic inflammatory skin disease characterized by dry, pruritic skin. Several studies have described nocturnal increases in itching behavior, suggesting a role for the circadian rhythm in modulating symptom severity. However, the circadian rhythm of metabolites in the skin and serum of patients with AD is yet to be described.

OBJECTIVE

We sought to assess circadian patterns of skin and serum metabolism in patients with AD.

METHODS

Twelve patients with moderate to severe AD and 5 healthy volunteers were monitored for 28 hours in a controlled environment. Serum was collected every 2 hours and tape strips every 4 hours from both lesional and nonlesional skin in participants with AD and location-, sex-, and age-matched healthy skin of controls. We then performed an untargeted metabolomics analysis, examining the circadian peaks of metabolism in patients with AD.

RESULTS

Distinct metabolic profiles were observed in AD versus control samples. When accounting for time of collection, the greatest differences in serum metabolic pathways were observed in arachidonic acid, steroid biosynthesis, and terpenoid backbone biosynthesis. We identified 42 circadian peaks in AD or control serum and 17 in the skin. Pathway enrichment and serum-skin metabolite correlation varied throughout the day. Differences were most evident in the late morning and immediately after sleep onset.

CONCLUSIONS

Although limited by a small sample size and observational design, our findings suggest that accounting for sample collection time could improve biomarker detection studies in AD and highlight that metabolic changes may be associated with nocturnal differences in symptom severity.

Untargeted metabolomics of buffalo urine reveals hydracyrlic acid, 3-bromo-1-propanol and benzyl serine as potential estrus biomarkers

Buffalo is a silent heat animal and doesn't show prominent signs of estrous like cattle so it becomes difficult for farmers to determine the receptivity of the animal based purely on the animal behaviour. India, having a huge population size, needs to produce more milk for the population. Successful artificial insemination greatly depends on the receptivity of the animal. Hence the present study aimed to identify the changes in the metabolome of the buffalo. GC-MS based mass spectrometric analysis was deployed for the determination of estrous by differential expression of metabolites. It was found that hydracrylic acid, 3-bromo-1-propanol and benzyl serine were significantly upregulated in the estrous phase of buffalo (p.value ≤0.05, FC ≥ 2). The pathway enrichment analysis also supported the same as pathways related to amino acid metabolism and fatty acid metabolism were up regulated along with the Warburg effect which is linked to the rapid cell proliferation which might help prepare animals to meet the energy requirement during the estrous. Further analysis of the metabolic biomarkers using ROC analysis also supported these three metabolites as probable biomarkers as they were identified with AUC values of 0.7 or greater. SIGNIFICANCE: The present study focuses on the untargeted metabolomics studies of buffalo urine with special reference to the estrous phase of reproductive cycle. The estrous signals are more prominent in cattle, where animals show clear estrous signals such as mounting and discharge along with vocal signals. Buffalo is a silent heat animal and it becomes difficult for farmers to detect the estrous based on the physical and behavioral signals. Hence the present study focuses on GC-MS based untargeted metabolomics to identify differentially expressed urine metabolites. In this study, hydracrylic acid, 3-bromo-1-propanol and benzyl serine were found to be significantly upregulated in the estrous phase of buffalo (p-value ≤0.05, FC ≥ 2). Further confirmation of the metabolic biomarkers was done using Receiver operating characteristics (ROC) analysis which also supported these three metabolites as probable biomarkers as they had AUC values of 0.7 or greater. Hence, this study will be of prime importance for the people working in the area of animal metabolomics.

First-in-class MKK4 inhibitors enhance liver regeneration and prevent liver failure

Diminished hepatocyte regeneration is a key feature of acute and chronic liver diseases and after extended liver resections, resulting in the inability to maintain or restore a sufficient functional liver mass. Therapies to restore hepatocyte regeneration are lacking, making liver transplantation the only curative option for end-stage liver disease. Here, we report on the structure-based development and characterization (nuclear magnetic resonance [NMR] spectroscopy) of first-in-class small molecule inhibitors of the dual-specificity kinase MKK4 (MKK4i). MKK4i increased liver regeneration upon hepatectomy in murine and porcine models, allowed for survival of pigs in a lethal 85% hepatectomy model, and showed antisteatotic and antifibrotic effects in liver disease mouse models. A first-in-human phase I trial (European Union Drug Regulating Authorities Clinical Trials [EudraCT] 2021-000193-28) with the clinical candidate HRX215 was conducted and revealed excellent safety and pharmacokinetics. Clinical trials to probe HRX215 for prevention/treatment of liver failure after extensive oncological liver resections or after transplantation of small grafts are warranted.

Osteocyte mitochondria regulate angiogenesis of transcortical vessels

Transcortical vessels (TCVs) provide effective communication between bone marrow vascular system and external circulation. Although osteocytes are in close contact with them, it is not clear whether osteocytes regulate the homeostasis of TCVs. Here, we show that osteocytes maintain the normal network of TCVs by transferring mitochondria to the endothelial cells of TCV. Partial ablation of osteocytes causes TCV regression. Inhibition of mitochondrial transfer by conditional knockout of Rhot1 in osteocytes also leads to regression of the TCV network. By contrast, acquisition of osteocyte mitochondria by endothelial cells efficiently restores endothelial dysfunction. Administration of osteocyte mitochondria resultes in acceleration of the angiogenesis and healing of the cortical bone defect. Our results provide new insights into osteocyte-TCV interactions and inspire the potential application of mitochondrial therapy for bone-related diseases.

Combined functional genomic and metabolomic approaches identify new genes required for growth in human urine by multidrug-resistant Escherichia coli ST131

Urinary tract infections (UTIs) are one of the most common bacterial infections in humans, with ~400 million cases across the globe each year. Uropathogenic Escherichia coli (UPEC) is the major cause of UTI and increasingly associated with antibiotic resistance. This scenario has been worsened by the emergence and spread of pandemic UPEC sequence type 131 (ST131), a multidrug-resistant clone associated with extraordinarily high rates of infection. Here, we employed transposon-directed insertion site sequencing in combination with metabolomic profiling to identify genes and biochemical pathways required for growth and survival of the UPEC ST131 reference strain EC958 in human urine (HU). We identified 24 genes required for growth in HU, which mapped to diverse pathways involving small peptide, amino acid and nucleotide metabolism, the stringent response pathway, and lipopolysaccharide biosynthesis. We also discovered a role for UPEC resistance to fluoride during growth in HU, most likely associated with fluoridation of drinking water. Complementary nuclear magnetic resonance (NMR)-based metabolomics identified changes in a range of HU metabolites following UPEC growth, the most pronounced being L-lactate, which was utilized as a carbon source via the L-lactate dehydrogenase LldD. Using a mouse UTI model with mixed competitive infection experiments, we demonstrated a role for nucleotide metabolism and the stringent response in UPEC colonization of the mouse bladder. Together, our application of two omics technologies combined with different infection-relevant settings has uncovered new factors required for UPEC growth in HU, thus enhancing our understanding of this pivotal step in the UPEC infection pathway.

IMPORTANCE

Uropathogenic Escherichia coli (UPEC) cause ~80% of all urinary tract infections (UTIs), with increasing rates of antibiotic resistance presenting an urgent threat to effective treatment. To cause infection, UPEC must grow efficiently in human urine (HU), necessitating a need to understand mechanisms that promote its adaptation and survival in this nutrient-limited environment. Here, we used a combination of functional genomic and metabolomic techniques and identified roles for the metabolism of small peptides, amino acids, nucleotides, and L-lactate, as well as the stringent response pathway, lipopolysaccharide biosynthesis, and fluoride resistance, for UPEC growth in HU. We further demonstrated that pathways involving nucleotide metabolism and the stringent response are required for UPEC colonization of the mouse bladder. The UPEC genes and metabolic pathways identified in this study represent targets for the development of innovative therapeutics to prevent UPEC growth during human UTI, an urgent need given the rapidly rising rates of global antibiotic resistance.

Metabolic profiling of synovial fluid in human temporomandibular joint osteoarthritis

Introduction

Temporomandibular joint (TMJ) osteoarthritis (OA) is a common TMJ degenerative disease with an unclear mechanism. Synovial fluid (SF), an important component of TMJ, contains various proteins and metabolites that may directly contribute to OA. The present study aimed to investigate the influence of SF in TMJOA at the metabolite level.

Methods

Untargeted and widely targeted metabolic profiling were employed to identify metabolic changes in SF of 90 patients with different TMJOA grades according to TMJ magnetic resonance imaging.

Results

A total 1498 metabolites were detected. Most of the metabolites were amino acids and associated metabolites, benzene and substituted derivatives, and lipids. Among patients with mild, moderate and severe TMJOA, 164 gradually increasing and 176 gradually decreasing metabolites were identified, indicating that biosynthesis of cofactors, choline metabolism, mineral absorption and selenocompound metabolism are closely related to TMJOA grade. Combined metabolomics and clinical examination revealed 37 upregulated metabolites and 16 downregulated metabolites in patients with pain, of which 19 and 26 metabolites were positively and negatively correlated, respectively, with maximum interincisal opening. A model was constructed to diagnose TMJOA grade and nine biomarkers were identified. The identified metabolites are key to exploring the mechanism of TMJOA.

Discussion

In the present study, a metabolic profile was constructed and assessed using a much larger number of human SF samples from patients with TMJOA, and a model was established to contribute to the diagnosis of TMJOA grade. The findings expand our knowledge of metabolites in human SF of TMJOA patients, and provide an important basis for further research on the pathogenesis and treatment of TMJOA.

A comprehensive overview of microbiome data in the light of machine learning applications: categorization, accessibility, and future directions

Metagenomics, Metabolomics, and Metaproteomics have significantly advanced our knowledge of microbial communities by providing culture-independent insights into their composition and functional potential. However, a critical challenge in this field is the lack of standard and comprehensive metadata associated with raw data, hindering the ability to perform robust data stratifications and consider confounding factors. In this comprehensive review, we categorize publicly available microbiome data into five types: shotgun sequencing, amplicon sequencing, metatranscriptomic, metabolomic, and metaproteomic data. We explore the importance of metadata for data reuse and address the challenges in collecting standardized metadata. We also, assess the limitations in metadata collection of existing public repositories collecting metagenomic data. This review emphasizes the vital role of metadata in interpreting and comparing datasets and highlights the need for standardized metadata protocols to fully leverage metagenomic data's potential. Furthermore, we explore future directions of implementation of Machine Learning (ML) in metadata retrieval, offering promising avenues for a deeper understanding of microbial communities and their ecological roles. Leveraging these tools will enhance our insights into microbial functional capabilities and ecological dynamics in diverse ecosystems. Finally, we emphasize the crucial metadata role in ML models development.

The 2024 Nucleic Acids Research database issue and the online molecular biology database collection

The 2024 Nucleic Acids Research database issue contains 180 papers from across biology and neighbouring disciplines. There are 90 papers reporting on new databases and 83 updates from resources previously published in the Issue. Updates from databases most recently published elsewhere account for a further seven. Nucleic acid databases include the new NAKB for structural information and updates from Genbank, ENA, GEO, Tarbase and JASPAR. The Issue's Breakthrough Article concerns NMPFamsDB for novel prokaryotic protein families and the AlphaFold Protein Structure Database has an important update. Metabolism is covered by updates from Reactome, Wikipathways and Metabolights. Microbes are covered by RefSeq, UNITE, SPIRE and P10K; viruses by ViralZone and PhageScope. Medically-oriented databases include the familiar COSMIC, Drugbank and TTD. Genomics-related resources include Ensembl, UCSC Genome Browser and Monarch. New arrivals cover plant imaging (OPIA and PlantPAD) and crop plants (SoyMD, TCOD and CropGS-Hub). The entire Database Issue is freely available online on the Nucleic Acids Research website (https://academic.oup.com/nar). Over the last year the NAR online Molecular Biology Database Collection has been updated, reviewing 1060 entries, adding 97 new resources and eliminating 388 discontinued URLs bringing the current total to 1959 databases. It is available at http://www.oxfordjournals.org/nar/database/c/.