Design of experiments: an efficient strategy to identify factors influencing extraction and derivatization of Arabidopsis thaliana samples in metabolomic studies with gas chromatography/mass spectrometry

CRISPR-Cas9 mediated knockout of NDUFS4 in human iPSCs: A model for mitochondrial complex I deficiency

Mitochondrial diseases, often caused by defects in complex I (CI) of the oxidative phosphorylation system, currently lack curative treatments. Human-relevant, high-throughput drug screening platforms are crucial for the discovery of effective therapeutics, with induced pluripotent stem cells (iPSCs) emerging as a valuable technology for this purpose. Here, we present a novel iPSC model of NDUFS4-related CI deficiency that displays a strong metabolic phenotype in the pluripotent state. Human iPSCs were edited using CRISPR-Cas9 to target the NDUFS4 gene, generating isogenic NDUFS4 knockout (KO) cell lines. Sanger sequencing detected heterozygous biallelic deletions, whereas no indel mutations were found in isogenic control cells. Western blotting confirmed the absence of NDUFS4 protein in KO iPSCs and CI enzyme kinetics showed a ~56 % reduction in activity compared to isogenic controls. Comprehensive metabolomic profiling revealed a distinct metabolic phenotype in NDUFS4 KO iPSCs, predominantly associated with an elevated NADH/NAD+ ratio, consistent with alterations observed in other models of mitochondrial dysfunction. Additionally, β-lapachone, a recognized NAD+ modulator, alleviated reductive stress in KO iPSCs by modifying the redox state in both the cytosol and mitochondria. Although undifferentiated iPSCs cannot fully replicate the complex cellular dynamics of the disease seen in vivo, these findings highlight the utility of iPSCs in providing a relevant metabolic milieu that can facilitate early-stage, high-throughput exploration of therapeutic strategies for mitochondrial dysfunction.

Parallel single-cell metabolic analysis and extracellular vesicle profiling reveal vulnerabilities with prognostic significance in acute myeloid leukemia

Acute myeloid leukemia (AML) is an aggressive disease with a high relapse rate. In this study, we map the metabolic profile of CD34+(CD38low/-) AML cells and the extracellular vesicle signatures in circulation from AML patients at diagnosis. CD34+ AML cells display high antioxidant glutathione levels and enhanced mitochondrial functionality, both associated with poor clinical outcomes. Although CD34+ AML cells are highly dependent on glucose oxidation and glycolysis for energy, those from intermediate- and adverse-risk patients reveal increased mitochondrial dependence. Extracellular vesicles from AML are mainly enriched in stem cell markers and express antioxidant GPX3, with their profiles showing potential prognostic value. Extracellular vesicles enhance mitochondrial functionality and dependence on CD34+ AML cells via the glutathione/GPX4 axis. Notably, extracellular vesicles from adverse-risk patients enhance leukemia cell engraftment in vivo. Here, we show a potential noninvasive approach based on liquid 'cell-extracellular vesicle' biopsy toward a redefined metabolic stratification in AML.

Impact of thermal seed treatment on spermosphere microbiome, metabolome and viability of winter wheat

Thermal seed treatment can be used as an alternative method to prevent infection by seed-borne diseases, but exposure duration and temperature during thermal treatment are important to maintain high seed viability and emergence whilst decreasing infection rate. A method for predicting suitable treatment parameters to maintain viability and eliminate seed-borne pathogens is therefore needed. Seeds of winter wheat were subjected to thermal treatment at four levels of intensity and pre-treatments with or without imbibition. Treatment impact was measured by metabolome analysis using LC-MS and GC-MS, analysis of spermosphere bacterial and fungal metagenomes using Illumina MiSeq, and detection of presence of Fusarium spp. and Microdochium spp. using ddPCR. The results showed that moderate treatment intensity reduced signs of infection and increased seedling emergence. In imbibed samples, myo-inositol concentration and myo-inositol: glucose ratio were positively correlated with treatment intensity, whereas concentrations of glucose and citric acid were negatively correlated. No correlations were found for non-imbibed samples. Imbibition had a large significant impact on microbial community composition of the wheat spermosphere. Imbibition of wheat seeds prior to thermal treatment altered wheat spermosphere microbiota. The concentration of myo-inositol, potentially in combination with glucose, could be a candidate predictor for suitable thermal treatment intensity of wheat seeds.

Lifecycle DoE-The Companion for a Holistic Development Process

Within process development, numerous experimental studies are undertaken to establish, optimize and characterize individual bioprocess unit operations. These studies pursue diverse objectives such as enhancing titer or minimizing impurities. Consequently, Design of Experiment (DoE) studies are planned and analyzed independently from each other, making it challenging to interlink individual data sets to form a comprehensive overview at the conclusion of the development process. This paper elucidates the methodology for constructing a Life-Cycle-DoE (LDoE), which integrates data-driven process knowledge through design augmentations. It delves into the strategy, highlights the challenges encountered and provides solutions for overcoming them. The LDoE approach facilitates the augmentation of an existing model with new experiments in a unified design. It allows for flexible design adaptations as per the requirements of subject matter experts (SME) during process development, concurrently enhancing model predictions by utilizing all available data. The LDoE boasts a broad application spectrum as it consolidates all data generated within bioprocess development into a single file and model. The study demonstrates that the LDoE approach enables a process characterization study (PCS) to be performed solely with development data. Furthermore, it identifies potentially critical process parameters (pCPPs) early, allowing for timely adaptations in process development to address these challenges.

Comparative proteomic analyses of potato leaves from field-grown plants grown under extremely long days

There are limited molecular data and few biomarkers available for studies of field-grown plants, especially for plants grown during extremely long days. In this study we present quantitative proteomics data from 3 years of field trials on potato, conducted in northern and southern Sweden and analyze over 3000 proteins per year of the study and complement the proteomic analysis with metabolomic and transcriptomic analyses. Small but consistent differences linked to the longer days (an average of four more hours of light per day) in northern Sweden (20 h light/day) compared to southern Sweden can be observed, with a high correlation between the mRNA determined by RNA-seq and protein abundances. The majority of the proteins with differential abundances between northern and southern Sweden could be divided into three groups: metabolic enzymes (especially GABA metabolism), proteins involved in redox metabolism, and hydrolytic enzymes. The observed differences in metabolic enzyme abundances corresponded well with untargeted metabolite data determined by GC and LC mass-spectrometry. We also analyzed differences in protein abundance between potato varieties that performed relatively well in northern Sweden in terms of yield with those that performed relatively less well. This comparison indicates that the proteins with higher abundance in the high-yield quotient group are more anabolic in their character, whereas the proteins with lower abundance are more catabolic. Our results create a base of information about potato "field-omics" for improved understanding of physiological and molecular processes in field-grown plants, and our data indicate that the potato plant is not generally stressed by extremely long days.

Reduced adipocyte glutaminase activity promotes energy expenditure and metabolic health

Glutamine and glutamate are interconverted by several enzymes and alterations in this metabolic cycle are linked to cardiometabolic traits. Herein, we show that obesity-associated insulin resistance is characterized by decreased plasma and white adipose tissue glutamine-to-glutamate ratios. We couple these stoichiometric changes to perturbed fat cell glutaminase and glutamine synthase messenger RNA and protein abundance, which together promote glutaminolysis. In human white adipocytes, reductions in glutaminase activity promote aerobic glycolysis and mitochondrial oxidative capacity via increases in hypoxia-inducible factor 1α abundance, lactate levels and p38 mitogen-activated protein kinase signalling. Systemic glutaminase inhibition in male and female mice, or genetically in adipocytes of male mice, triggers the activation of thermogenic gene programs in inguinal adipocytes. Consequently, the knockout mice display higher energy expenditure and improved glucose tolerance compared to control littermates, even under high-fat diet conditions. Altogether, our findings highlight white adipocyte glutamine turnover as an important determinant of energy expenditure and metabolic health.

Designing optimal experiments in metabolomics

BACKGROUND

Metabolomics data is often complex due to the high number of metabolites, chemical diversity, and dependence on sample preparation. This makes it challenging to detect significant differences between factor levels and to obtain accurate and reliable data. To address these challenges, the use of Design of Experiments (DoE) techniques in the setup of metabolomic experiments is crucial. DoE techniques can be used to optimize the experimental design space, ensuring that the maximum amount of information is obtained from a limited sample space.

AIM OF REVIEW

This review aims at providing a baseline workflow for applying DoE when generating metabolomics data.

KEY SCIENTIFIC CONCEPTS OF REVIEW

The review provides insights into the theory of DoE. The review showcases the theory being put into practice by highlighting different examples DoE being applied in metabolomics throughout the literature, considering both targeted and untargeted metabolomic studies in which the data was acquired using both nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry techniques. In addition, the review presents DoE concepts not currently being applied in metabolomics, highlighting these as potential future prospects.

Metabolomics profiling reveals the detoxification and tolerance behavior of two bread wheat (Triticum aestivum L.) varieties under arsenate stress

The present study conducted metabolomics profiling (targeted and untargeted) in the roots of two wheat varieties (BARANI-70 and NARC-09) under arsenate stress in a hydroponic experiment. The findings indicated a better growth response of BARANI-70 compared to the NARC-09. From amino acid profiling, a total of 26 amino acids (AAs) were quantified in roots. BARANI-70 showed higher induction of stress-responsive AAs compared to the NARC-09. From untargeted metabolomics, a total of 136 metabolites were identified: AAs, fatty acids, purines, carnitines, LysoPCs, and others. The KEGG pathway identified pathways such as linoleic acid metabolism, TCA cycle, glutathione metabolism, and aminoacyl-tRNA biosynthesis that were regulated to improve the defense of tolerant variety. BARANI-70 emerged as a tolerant variety based on the psychological response, As accumulation, and behavior of stress-responsive metabolites. This study should facilitate the breeding of low-As accumulating wheat varieties for future application to ensure sustainable production and food safety.

Applications of chromatographic methods in metabolomics: A review

Chromatography is a robust and reliable separation method that can use various stationary phases to separate complex mixtures commonly seen in metabolomics. This review examines the types of chromatography and stationary phases that have been used in targeted or untargeted metabolomics with methods such as mass spectrometry (MS) and nuclear magnetic resonance (NMR) spectroscopy. General considerations for sample pretreatment and separations in metabolomics are considered, along with the various supports and separation formats for chromatography that have been used in such work. The types of liquid chromatography (LC) that have been most extensively used in metabolomics will be examined, such as reversed-phase liquid chromatography and hydrophilic liquid interaction chromatography. In addition, other forms of LC that have been used in more limited applications for metabolomics (e.g., ion-exchange, size-exclusion, and affinity methods) will be discussed to illustrate how these techniques may be utilized for new and future research in this field. Multidimensional LC methods are also discussed, as well as the use of gas chromatography and supercritical fluid chromatography in metabolomics. In addition, the roles of chromatography in NMR- vs. MS-based metabolomics are considered. Applications are given within the field of metabolomics for each type of chromatography, along with potential advantages or limitations of these separation methods.

Endophytic Beauveria bassiana induces biosynthesis of flavonoids in oilseed rape following both seed inoculation and natural colonization

BACKGROUND

Cultivation of oilseed rape Brassica napus is pesticide-intensive, and alternative plant protection strategies are needed because both pesticide resistance and legislation narrow the range of effective chemical pesticides. The entomopathogenic fungus Beauveria bassiana is used as a biocontrol agent against various insect pests, but little is known about its endophytic potential and role in plant protection for oilseed rape. First, we studied whether B. bassiana can establish as an endophyte in oilseed rape, following seed inoculation. To evaluate the plant protection potential of endophytic B. bassiana on oilseed rape, we next examined its ability to induce plant metabolite biosynthesis. In another experiment, we tested the effect of seed inoculation on seedling survival in a semi-field experiment.

RESULTS

Beauveria bassiana endophytically colonized oilseed rape following seed inoculation, and, in addition, natural colonization was also recorded. Maximum colonization rate was 40%, and generally increased with inoculation time. Seed inoculation did not affect the germination probability or growth of oilseed rape, but B. bassiana inoculated seeds germinated more slowly compared to controls. Endophytic colonization of B. bassiana induced biosynthesis of several flavonoids in oilseed rape leaves under controlled conditions. In the experiment conducted in semi-field conditions, inoculated seedlings had slightly higher mortality compared to control seedlings.

CONCLUSION

Beauveria bassiana showed endophytic potential on oilseed rape via both natural colonization and seed inoculation, and it induced the biosynthesis of flavonoids. However, its use as an endophyte for plant protection against pests or pathogens for oilseed rape remains unclear. © 2023 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Impact of the neurotoxin β-N-methylamino-L-alanine on the diatom Thalassiosira pseudonana using metabolomics

The neurotoxin β-N-methylamino-L-alanine (BMAA) has emerged as an environmental factor related to neurodegenerative diseases. BMAA is produced by various microorganisms including cyanobacteria and diatoms, in diverse ecosystems. In the diatom Phaeodactylum tricornutum, BMAA is known to inhibit growth. The present study investigated the impact of BMAA on the diatom Thalassiosira pseudonana by exposing it to different concentrations of exogenous BMAA. Metabolomics was predominantly employed to investigate the effect of BMAA on T. pseudonana, and MetaboAnalyst (https://www.metabo-analyst.ca/) was used to identify BMAA-associated metabolisms/pathways in T. pseudonana. Furthermore, to explore the unique response, specific metabolites were compared between treatments. When the growth was obstructed by BMAA, 17 metabolisms/pathways including nitrogen and glutathione (i.e. oxidative stress) metabolisms, were influenced in T. pseudonana. This study has further determined that 11 out of 17 metabolisms/pathways could be essentially affected by BMAA, leading to the inhibition of diatom growth.

Pseudomonas syringae infectivity correlates to altered transcript and metabolite levels of Arabidopsis mediator mutants

Rapid metabolic responses to pathogens are essential for plant survival and depend on numerous transcription factors. Mediator is the major transcriptional co-regulator for integration and transmission of signals from transcriptional regulators to RNA polymerase II. Using four Arabidopsis Mediator mutants, med16, med18, med25 and cdk8, we studied how differences in regulation of their transcript and metabolite levels correlate to their responses to Pseudomonas syringae infection. We found that med16 and cdk8 were susceptible, while med25 showed increased resistance. Glucosinolate, phytoalexin and carbohydrate levels were reduced already before infection in med16 and cdk8, but increased in med25, which also displayed increased benzenoids levels. Early after infection, wild type plants showed reduced glucosinolate and nucleoside levels, but increases in amino acids, benzenoids, oxylipins and the phytoalexin camalexin. The Mediator mutants showed altered levels of these metabolites and in regulation of genes encoding key enzymes for their metabolism. At later stage, mutants displayed defective levels of specific amino acids, carbohydrates, lipids and jasmonates which correlated to their infection response phenotypes. Our results reveal that MED16, MED25 and CDK8 are required for a proper, coordinated transcriptional response of genes which encode enzymes involved in important metabolic pathways for Arabidopsis responses to Pseudomonas syringae infections.

High-throughput analysis reveals disturbances throughout the cell caused by Arabidopsis UCP1 and UCP3 double knockdown

Three genes encoding mitochondrial uncoupling proteins (UCPs) have been described in Arabidopsis thaliana (UCP1 to UCP3). In plants, UCPs may act as an uncoupler or as an aspartate/glutamate exchanger. For instance, much of the data regarding UCP functionality were obtained for the UCP1 and UCP2 isoforms compared with UCP3. Here, to get a better understanding about the concerted action of UCP1 and UCP3 in planta, we investigated the transcriptome and metabolome profiles of ucp1 ucp3 double mutant plants during the vegetative phase. For that, 21-day-old mutant plants, which displayed the most evident phenotypic alterations compared to wild type (WT) plants, were employed. The double knockdown of UCP1 and UCP3, isoforms unequivocally present inside the mitochondria, promoted important transcriptional reprogramming with alterations in the expression of genes related to mitochondrial and chloroplast function as well as those responsive to abiotic stress, suggesting disturbances throughout the cell. The observed transcriptional changes were well integrated with the metabolomic data of ucp1 ucp3 plants. Alterations in metabolites related to primary and secondary metabolism, particularly enriched in the Alanine, Aspartate and Glutamate metabolism, were detected. These findings extend our knowledge of the underlying roles played by UCP3 in concert with UCP1 at the whole plant level.

Molecular profiling of high-level athlete skeletal muscle after acute endurance or resistance exercise - A systems biology approach

OBJECTIVE

Long-term high-level exercise training leads to improvements in physical performance and multi-tissue adaptation following changes in molecular pathways. While skeletal muscle baseline differences between exercise-trained and untrained individuals have been previously investigated, it remains unclear how training history influences human multi-omics responses to acute exercise.

METHODS

We recruited and extensively characterized 24 individuals categorized as endurance athletes with >15 years of training history, strength athletes or control subjects. Timeseries skeletal muscle biopsies were taken from M. vastus lateralis at three time-points after endurance or resistance exercise was performed and multi-omics molecular analysis performed.

RESULTS

Our analyses revealed distinct activation differences of molecular processes such as fatty- and amino acid metabolism and transcription factors such as HIF1A and the MYF-family. We show that endurance athletes have an increased abundance of carnitine-derivates while strength athletes increase specific phospholipid metabolites compared to control subjects. Additionally, for the first time, we show the metabolite sorbitol to be substantially increased with acute exercise. On transcriptional level, we show that acute resistance exercise stimulates more gene expression than acute endurance exercise. This follows a specific pattern, with endurance athletes uniquely down-regulating pathways related to mitochondria, translation and ribosomes. Finally, both forms of exercise training specialize in diverging transcriptional directions, differentiating themselves from the transcriptome of the untrained control group.

CONCLUSIONS

We identify a "transcriptional specialization effect" by transcriptional narrowing and intensification, and molecular specialization effects on metabolomic level Additionally, we performed multi-omics network and cluster analysis, providing a novel resource of skeletal muscle transcriptomic and metabolomic profiling in highly trained and untrained individuals.

Evaluating Machine Learning Methods of Analyzing Multiclass Metabolomics

Multiclass metabolomic studies have become popular for revealing the differences in multiple stages of complex diseases, various lifestyles, or the effects of specific treatments. In multiclass metabolomics, there are multiple data manipulation steps for analyzing raw data, which consist of data filtering, the imputation of missing values, data normalization, marker identification, sample separation, classification, and so on. In each step, several to dozens of machine learning methods can be chosen for the given data set, with potentially hundreds or thousands of method combinations in the whole data processing chain. Therefore, a clear understanding of these machine learning methods is helpful for selecting an appropriate method combination for obtaining stable and reliable analytical results of specific data. However, there has rarely been an overall introduction or evaluation of these methods based on multiclass metabolomic data. Herein, detailed descriptions of these machine learning methods in multiple data manipulation steps are reviewed. Moreover, an assessment of these methods was performed using a benchmark data set for multiclass metabolomics. First, 12 imputation methods for imputing missing values were evaluated based on the PSS (Procrustes statistical shape analysis) and NRMSE (normalized root-mean-square error) values. Second, 17 normalization methods for processing multiclass metabolomic data were evaluated by applying the PMAD (pooled median absolute deviation) value. Third, different methods of identifying markers of multiclass metabolomics were evaluated based on the CWrel (relative weighted consistency) value. Fourth, nine classification methods for constructing multiclass models were assessed using the AUC (area under the curve) value. Performance evaluations of machine learning methods are highly recommended to select the most appropriate method combination before performing the final analysis of the given data. Overall, detailed descriptions and evaluation of various machine learning methods are expected to improve analyses of multiclass metabolomic data.

Structural and chemical insights into the prebiotic property of hemicellulosic polysaccharide from Santalum album L

Hemicellulose was extracted by alkali treatment of de-pectinated cell wall material of Santalum album L. (sandalwood) suspension culture cells. The physicochemical properties and prebiotic activities of a purified major fraction of Hemicellulose-B, termed as HB-I, were investigated. GC analysis of hydrolyzed and derivatized HB-I showed the presence of arabinose (~64 %), galactose (~16 %) and glucose (~16 %) as major monosaccharide units along with minor amount of rhamnose. Methylation and NMR studies on the purified polysaccharide revealed the presence of 6-β-d-Glcp, β-d-Galp, 3,5-α-l-Araf, α-l-Araf, 5-α-l-Araf, 2,3-α-l-Araf and, α-l-Rhap residues, from which a proposed structure of repeating units was established. The growth of probiotic Lactobacillus spp. strains L. acidophilus, L. casei, L. plantarum and L. rhamnosus was promoted while that of Escherichia coli was suppressed significantly in presence of HB-I. Our results highlight valorization of sandalwood biomass and explore the role of mixed α, β-linked heteroglycan as a potential prebiotic molecule thus indicating the possibility of development of low-cost bioprocesses for production of functional food ingredients.

Green Synthesis of Chitosan-Capped Gold Nanoparticles Using Salvia officinalis Extract: Biochemical Characterization and Antimicrobial and Cytotoxic Activities

Increasing antimicrobial resistance to the action of existing antibiotics has prompted researchers to identify new natural molecules with antimicrobial potential. In this study, a green system was developed for biosynthesizing gold nanoparticles (BAuNPs) using sage (Salvia officinalis L.) leaf extract bioconjugated with non-toxic, eco-friendly, and biodegradable chitosan, forming chitosan/gold bioconjugates (Chi/BAuNPs). Characterization of the BAuNPs and Chi/BAuNPs conjugates takes place using transmission electron microscopy (TEM), X-ray spectra, Fourier transform infrared (FT-IR) spectroscopy, and zeta potential (Z-potential). The chemical composition of S. officinalis extract was evaluated via gas chromatography/mass spectrometry (GC/MS). This study evaluated the antioxidant and antimicrobial activities of human pathogenic multidrug-resistant (MDR) and multisensitive (MS) bacterial isolates using the agar diffusion method. Chi/BAuNPs showed inhibition of the MDR strains more effectively than BAuNPs alone as compared with a positive standard antibiotic. The cytotoxicity assay revealed that the human breast adenocarcinoma cancer cells (MCF7) were more sensitive toward the toxicity of 5-Fu + BAuNPs and 5-Fu + Chi/BAuNPs composites compared to non-malignant human fibroblast cells (HFs). The study shows that BAuNPs and Chi/BAuNPs, combined with 5-FU NPs, can effectively treat cancer at concentrations where the free chemical drug (5-Fu) is ineffective, with a noted reduction in the required dosage for noticeable antitumor action.

Emerging trends and applications of metabolomics in food science and nutrition

The study of all chemical processes involving metabolites is known as metabolomics. It has been developed into an essential tool in several disciplines, such as the study of plant physiology, drug development, human diseases, and nutrition. The field of food science, diagnostic biomarker research, etiological analysis in the field of medical therapy, and raw material quality, processing, and safety have all benefited from the use of metabolomics recently. Food metabolomics includes the use of metabolomics in food production, processing, and human diets. As a result of changing consumer habits and the rising of food industries all over the world, there is a remarkable increase in interest in food quality and safety. It requires the employment of various technologies for the food supply chain, processing of food, and even plant breeding. This can be achieved by understanding the metabolome of food, including its biochemistry and composition. Additionally, Food metabolomics can be used to determine the similarities and differences across crop kinds, as an indicator for tracking the process of ripening to increase crops' shelf life and attractiveness, and identifying metabolites linked to pathways responsible for postharvest disorders. Moreover, nutritional metabolomics is used to investigate the connection between diet and human health through detection of certain biomarkers. This review assessed and compiled literature on food metabolomics research with an emphasis on metabolite extraction, detection, and data processing as well as its applications to the study of food nutrition, food-based illness, and phytochemical analysis. Several studies have been published on the applications of metabolomics in food but further research concerning the use of standard reproducible procedures must be done. The results published showed promising uses in the food industry in many areas such as food production, processing, and human diets. Finally, metabolome-wide association studies (MWASs) could also be a useful predictor to detect the connection between certain diseases and low molecular weight biomarkers.

Xylan glucuronic acid side chains fix suberin-like aliphatic compounds to wood cell walls

Wood is the most important repository of assimilated carbon in the biosphere, in the form of large polymers (cellulose, hemicelluloses including glucuronoxylan, and lignin) that interactively form a composite, together with soluble extractives including phenolic and aliphatic compounds. Molecular interactions among these compounds are not fully understood. We have targeted the expression of a fungal α-glucuronidase to the wood cell wall of aspen (Populus tremula L. × tremuloides Michx.) and Arabidopsis (Arabidopsis thaliana (L.) Heynh), to decrease contents of the 4-O-methyl glucuronopyranose acid (mGlcA) substituent of xylan, to elucidate mGlcA's functions. The enzyme affected the content of aliphatic insoluble cell wall components having composition similar to suberin, which required mGlcA for binding to cell walls. Such suberin-like compounds have been previously identified in decayed wood, but here, we show their presence in healthy wood of both hardwood and softwood species. By contrast, γ-ester bonds between mGlcA and lignin were insensitive to cell wall-localized α-glucuronidase, supporting the intracellular formation of these bonds. These findings challenge the current view of the wood cell wall composition and reveal a novel function of mGlcA substituent of xylan in fastening of suberin-like compounds to cell wall. They also suggest an intracellular initiation of lignin-carbohydrate complex assembly.

Matrix Effects in GC–MS Profiling of Common Metabolites after Trimethylsilyl Derivatization

Metabolite profiling using gas chromatography coupled to mass spectrometry (GC–MS) is one of the most frequently applied and standardized methods in research projects using metabolomics to analyze complex samples. However, more than 20 years after the introduction of non-targeted approaches using GC–MS, there are still unsolved challenges to accurate quantification in such investigations. One particularly difficult aspect in this respect is the occurrence of sample-dependent matrix effects. In this project, we used model compound mixtures of different compositions to simplify the study of the complex interactions between common constituents of biological samples in more detail and subjected those to a frequently applied derivatization protocol for GC–MS analysis, namely trimethylsilylation. We found matrix effects as signal suppression and enhancement of carbohydrates and organic acids not to exceed a factor of ~2, while amino acids can be more affected. Our results suggest that the main reason for our observations may be an incomplete transfer of carbohydrate and organic acid derivatives during the injection process and compound interaction at the start of the separation process. The observed effects were reduced at higher target compound concentrations and by using a more suitable injection-liner geometry.

Lactate exposure shapes the metabolic and transcriptomic profile of CD8+ T cells

Introduction

CD8+ T cells infiltrate virtually every tissue to find and destroy infected or mutated cells. They often traverse varying oxygen levels and nutrient-deprived microenvironments. High glycolytic activity in local tissues can result in significant exposure of cytotoxic T cells to the lactate metabolite. Lactate has been known to act as an immunosuppressor, at least in part due to its association with tissue acidosis.

Methods

To dissect the role of the lactate anion, independently of pH, we performed phenotypical and metabolic assays, high-throughput RNA sequencing, and mass spectrometry, on primary cultures of murine or human CD8+ T cells exposed to high doses of pH-neutral sodium lactate.

Results

The lactate anion is well tolerated by CD8+ T cells in pH neutral conditions. We describe how lactate is taken up by activated CD8+ T cells and can displace glucose as a carbon source. Activation in the presence of sodium lactate significantly alters the CD8+ T cell transcriptome, including the expression key effector differentiation markers such as granzyme B and interferon-gamma.

Discussion

Our studies reveal novel metabolic features of lactate utilization by activated CD8+ T cells, and highlight the importance of lactate in shaping the differentiation and activity of cytotoxic T cells.

Targeting the gut-lung axis by synbiotic feeding to infants in a randomized controlled trial

BACKGROUND

Formula-fed infants are at increased risk of infections. Due to the cross-talk between the mucosal systems of the gastrointestinal and respiratory tracts, adding synbiotics (prebiotics and probiotics) to infant formula may prevent infections even at distant sites. Infants that were born full term and weaned from breast milk were randomized to prebiotic formula (fructo- and galactooligosaccharides) or the same prebiotic formula with Lactobacillus paracasei ssp. paracasei F19 (synbiotics) from 1 to 6 months of age. The objective was to examine the synbiotic effects on gut microbiota development.

RESULTS

Fecal samples collected at ages 1, 4, 6, and 12 months were analyzed using 16S rRNA gene sequencing and a combination of untargeted gas chromatography-mass spectrometry/liquid chromatography-mass spectrometry. These analyses revealed that the synbiotic group had a lower abundance of Klebsiella, a higher abundance of Bifidobacterium breve compared to the prebiotic group, and increases in the anti-microbial metabolite d-3-phenyllactic acid. We also analyzed the fecal metagenome and antibiotic resistome in the 11 infants that had been diagnosed with lower respiratory tract infection (cases) and 11 matched controls using deep metagenomic sequencing. Cases with lower respiratory tract infection had a higher abundance of Klebsiella species and antimicrobial resistance genes related to Klebsiella pneumoniae, compared to controls. The results obtained using 16S rRNA gene amplicon and metagenomic sequencing were confirmed in silico by successful recovery of the metagenome-assembled genomes of the bacteria of interest.

CONCLUSIONS

This study demonstrates the additional benefit of feeding specific synbiotics to formula-fed infants over prebiotics only. Synbiotic feeding led to the underrepresentation of Klebsiella, enrichment of bifidobacteria, and increases in microbial degradation metabolites implicated in immune signaling and in the gut-lung and gut-skin axes. Our findings support future clinical evaluation of synbiotic formula in the prevention of infections and associated antibiotic treatment as a primary outcome when breastfeeding is not feasible.

TRIAL REGISTRATION

ClinicalTrials.gov NCT01625273 . Retrospectively registered on 21 June 2012.

Unveiling Chemical Interactions Between Plants and Fungi Using Metabolomics Approaches

Metabolomics has been extensively used in clinical studies in the search for new biomarkers of human diseases. However, this approach has also been highlighted in agriculture and biological sciences, once metabolomics studies have been assisting researchers to deduce new chemical mechanisms involved in biological interactions that occur between microorganisms and plants. In this sense, the knowledge of the biological role of each metabolite (virulence factors, signaling compounds, antimicrobial metabolites, among others) and the affected biochemical pathways during the interaction contribute to a better understand of different ecological relationships established in nature. The current chapter addresses five different applications of the metabolomics approach in fungal-plant interactions research: (1) Discovery of biomarkers in pathogen-host interactions, (2) plant diseases diagnosis, (3) chemotaxonomy, (4) plant defense, and (5) plant resistance; using mass spectrometry and/or nuclear magnetic resonance spectroscopy, which are the techniques most used in metabolomics.

A Sensitive GC-MS Method for Quantitation of Lipid A Backbone Components and Terminal Phosphate Modifications

Lipid A, the hydrophobic anchor of lipopolysaccharide (LPS) present in the outer membrane of Gram-negative bacteria, serves as a target for cationic antimicrobial peptides, such as polymyxins. Membrane stress from polymyxins results in activation of two-component regulatory systems that produce lipid A modifying enzymes. These enzymes add neutral moieties, such as aminoarabinose (AraN) and ethanolamine (EtN) to lipid A terminal phosphates that mask the phosphate's negative charge and inhibit electrostatic interaction with the cationic polymyxins. Currently, these modifications may be detected by MALDI-TOF MS; however, this analysis is only semiquantitative. Herein we describe a GC-MS method to quantitate lipid A backbone components, glucosamine (GlcN) and inorganic phosphate (Pi), along with terminal phosphate modifications AraN and EtN. In this assay, lipid A is isolated from Gram-negative bacterial samples, hydrolyzed into its individual moieties, and derivatized via methoximation followed by silylation prior to analysis via GC-MS. Changes in AraN and EtN quantity were characterized using a variety of regulatory mutants of Salmonella, revealing differences that were not detected using MALDI-TOF MS analysis. Additionally, an increase in the abundance of AraN and EtN modifications were observed when resistant Enterobacter and Escherichia coli strains were grown in the presence of colistin (polymyxin E). Lastly, increased levels of Pi were found in bisphosphorylated lipid A compared to monophosphorylated lipid A samples. Because lipid A modifications serve as indicators of polymyxin resistance in Gram-negative bacteria, this method provides the capacity to monitor polymyxin resistance by quantification of lipid A modification using GC-MS.

Derivatization Strategies in Flavor Analysis: An Overview over the Wine and Beer Scenario

Wine and beer are the most appreciated and consumed beverages in the world. This success is mainly due to their characteristic taste, smell, and aroma, which can delight consumer’s palates. These olfactory characteristics are produced from specific classes of volatile compounds called “volatile odor-active compounds” linked to different factors such as age and production. Given the vast market of drinking beverages, the characterization of these odor compounds is increasingly important. However, the chemical complexity of these beverages has led the scientific community to develop several analytical techniques for extracting and quantifying these molecules. Even though the recent “green-oriented” trend is directed towards direct preparation-free procedures, for some class of analytes a conventional step like derivatization is unavoidable. This review is a snapshot of the most used derivatization strategies developed in the last 15 years for VOAs’ determination in wine and beer, the most consumed fermented beverages worldwide and among the most complex ones. A comprehensive overview is provided for every method, whereas pros and cons are critically analyzed and discussed. Emphasis was given to miniaturized methods which are more consistent with the principles of “green analytical chemistry”.

Antiviral COVID-19 protein and molecular docking: In silico characterization of various antiviral compounds extracted from Arisaema jacquemontii Blume

Arisaema jacquemontii Blume is a highly medicinal and poisonous plant belong to the family Araceae. It is used to treat several deadly diseases, including viral infections. It has antioxidant, anti-cancerous, antimalarial, anti-vermicidal, and antiviral activities. Therefore, five parts of the Arisaema jacquemontii Blume plant, such as leaf, seed, stem, pulp, and rhizome extract, were evaluated for metabolic and in silico characterization of probable compounds using gas chromatography-mass spectrometry (GC-MS) analysis. A total of 22 compounds were isolated from the methanolic extracts of A. jacquemontii Blume. A selected antiviral COVID-19 protein i.e., protease (6LU7) was docked against the obtained compounds. Different affinities were obtained through various compounds. The best results were shown by three different compounds identified in the rhizome. The maximum binding affinity of these compounds is 8.1 kJ/mol. Molecular docking (MD) indicate that these molecules have the highest binding energies and hydrogen bonding interactions. The binding mode of interaction was discovered to be reasonably effective for counteracting the SARS virus COVID-19. The findings of this study could be extremely useful in the development of more phytochemical-based COVID-19 therapeutics.

Metabolic flux analysis: a comprehensive review on sample preparation, analytical techniques, data analysis, computational modelling, and main application areas

Metabolic flux analysis (MFA) quantitatively describes cellular fluxes to understand metabolic phenotypes and functional behaviour after environmental and/or genetic perturbations. In the last decade, the application of stable isotopes became extremely important to determine and integrate in vivo measurements of metabolic reactions in systems biology. 13C-MFA is one of the most informative methods used to study central metabolism of biological systems. This review aims to outline the current experimental procedure adopted in 13C-MFA, starting from the preparation of cell cultures and labelled tracers to the quenching and extraction of metabolites and their subsequent analysis performed with very powerful software. Here, the limitations and advantages of nuclear magnetic resonance spectroscopy and mass spectrometry techniques used in carbon labelled experiments are elucidated by reviewing the most recent published papers. Furthermore, we summarise the most successful approaches used for computational modelling in flux analysis and the main application areas with a particular focus in metabolic engineering.

Multi-omics personalized network analyses highlight progressive disruption of central metabolism associated with COVID-19 severity

The clinical outcome and disease severity in coronavirus disease 2019 (COVID-19) are heterogeneous, and the progression or fatality of the disease cannot be explained by a single factor like age or comorbidities. In this study, we used system-wide network-based system biology analysis using whole blood RNA sequencing, immunophenotyping by flow cytometry, plasma metabolomics, and single-cell-type metabolomics of monocytes to identify the potential determinants of COVID-19 severity at personalized and group levels. Digital cell quantification and immunophenotyping of the mononuclear phagocytes indicated a substantial role in coordinating the immune cells that mediate COVID-19 severity. Stratum-specific and personalized genome-scale metabolic modeling indicated monocarboxylate transporter family genes (e.g., SLC16A6), nucleoside transporter genes (e.g., SLC29A1), and metabolites such as α-ketoglutarate, succinate, malate, and butyrate could play a crucial role in COVID-19 severity. Metabolic perturbations targeting the central metabolic pathway (TCA cycle) can be an alternate treatment strategy in severe COVID-19.

Single, but not dual, attack by a biotrophic pathogen and a sap-sucking insect affects the oak leaf metabolome

Plants interact with a multitude of microorganisms and insects, both below- and above ground, which might influence plant metabolism. Despite this, we lack knowledge of the impact of natural soil communities and multiple aboveground attackers on the metabolic responses of plants, and whether plant metabolic responses to single attack can predict responses to dual attack. We used untargeted metabolic fingerprinting (gas chromatography-mass spectrometry, GC-MS) on leaves of the pedunculate oak, Quercus robur, to assess the metabolic response to different soil microbiomes and aboveground single and dual attack by oak powdery mildew (Erysiphe alphitoides) and the common oak aphid (Tuberculatus annulatus). Distinct soil microbiomes were not associated with differences in the metabolic profile of oak seedling leaves. Single attacks by aphids or mildew had pronounced but different effects on the oak leaf metabolome, but we detected no difference between the metabolomes of healthy seedlings and seedlings attacked by both aphids and powdery mildew. Our findings show that aboveground attackers can have species-specific and non-additive effects on the leaf metabolome of oak. The lack of a metabolic signature detected by GC-MS upon dual attack might suggest the existence of a potential negative feedback, and highlights the importance of considering the impacts of multiple attackers to gain mechanistic insights into the ecology and evolution of species interactions and the structure of plant-associated communities, as well as for the development of sustainable strategies to control agricultural pests and diseases and plant breeding.

RALF1 peptide triggers biphasic root growth inhibition upstream of auxin biosynthesis

Plant cell growth responds rapidly to various stimuli, adapting architecture to environmental changes. Two major endogenous signals regulating growth are the phytohormone auxin and the secreted peptides rapid alkalinization factors (RALFs). Both trigger very rapid cellular responses and also exert long-term effects [Du et al., Annu. Rev. Plant Biol. 71, 379-402 (2020); Blackburn et al., Plant Physiol. 182, 1657-1666 (2020)]. However, the way, in which these distinct signaling pathways converge to regulate growth, remains unknown. Here, using vertical confocal microscopy combined with a microfluidic chip, we addressed the mechanism of RALF action on growth. We observed correlation between RALF1-induced rapid Arabidopsis thaliana root growth inhibition and apoplast alkalinization during the initial phase of the response, and revealed that RALF1 reversibly inhibits primary root growth through apoplast alkalinization faster than within 1 min. This rapid apoplast alkalinization was the result of RALF1-induced net H⁺ influx and was mediated by the receptor FERONIA (FER). Furthermore, we investigated the cross-talk between RALF1 and the auxin signaling pathways during root growth regulation. The results showed that RALF-FER signaling triggered auxin signaling with a delay of approximately 1 h by up-regulating auxin biosynthesis, thus contributing to sustained RALF1-induced growth inhibition. This biphasic RALF1 action on growth allows plants to respond rapidly to environmental stimuli and also reprogram growth and development in the long term.

Effect and function of β-N-methylamino-L-alanine in the diatom Phaeodactylum tricornutum

The neurotoxin β-N-methylamino-L-alanine (BMAA) is an environmental factor connected to neurodegenerative diseases. BMAA can be produced by various microorganisms (e.g. bacteria, cyanobacteria, dinoflagellates and diatoms) present in diverse ecosystems. No previous study has revealed the function of BMAA in diatoms. In the present study, we combined physiological data with metabolomic and transcriptional data in order to investigate the effect and function of BMAA in the diatom Phaeodactylum tricornutum. P. tricornutum, exposed to different concentrations of exogenous BMAA, showed concentration dependent responses. When the concentration of supplemented BMAA was sufficient to arrest the growth of P. tricornutum, oxidative stress and obstructed carbon fixation were obtained from the specific metabolite and transcriptional data. Results also indicated increased concentration of intracellular chlorophyll a and alterations in the GS-GOGAT cycle, whereas the urea cycle was suppressed. We therefore conclude that BMAA represents a toxic metabolite able to control the growth of P. tricornutum by triggering oxidative stress, and further influencing photosynthesis and nitrogen metabolisms.

A Surrogate Model Based Multi-Objective Optimization Method for Optical Imaging System

An optimization model for the optical imaging system was established in this paper. It combined the modern design of experiments (DOE) method known as Latin hypercube sampling (LHS), Kriging surrogate model training, and the multi-objective optimization algorithm NSGA-III into the optimization of a triplet optical system. Compared with the methods that rely mainly on optical system simulation, this surrogate model-based multi-objective optimization method can achieve a high-accuracy result with significantly improved optimization efficiency. Using this model, case studies were carried out for two-objective optimizations of a Cooke triplet optical system. The results showed that the weighted geometric spot diagram and the maximum field curvature were reduced 5.32% and 11.59%, respectively, in the first case. In the second case, where the initial parameters were already optimized by Code-V, this model further reduced the weighted geometric spot diagram and the maximum field curvature by another 3.53% and 4.33%, respectively. The imaging quality in both cases was considerably improved compared with the initial design, indicating that the model is suitable for the optimal design of an optical system.

Nitrate fertilization may delay autumn leaf senescence, while amino acid treatments do not

Fertilization with nitrogen (N)-rich compounds leads to increased growth but may compromise phenology and winter survival of trees in boreal regions. During autumn, N is remobilized from senescing leaves and stored in other parts of the tree to be used in the next growing season. However, the mechanism behind the N fertilization effect on winter survival is not well understood, and it is unclear how N levels or forms modulate autumn senescence. We performed fertilization experiments and showed that treating Populus saplings with inorganic nitrogen resulted in a delay in senescence. In addition, by using precise delivery of solutes into the xylem stream of Populus trees in their natural environment, we found that delay of autumn senescence was dependent on the form of N administered: inorganic N ( NO 3 - ) delayed senescence, but amino acids (Arg, Glu, Gln, and Leu) did not. Metabolite profiling of leaves showed that the levels of tricarboxylic acids, arginine catabolites (ammonium, ornithine), glycine, glycine-serine ratio and overall carbon-to-nitrogen (C/N) ratio were affected differently by the way of applying NO₃ ^- and Arg treatments. In addition, the onset of senescence did not coincide with soluble sugar accumulation in control trees or in any of the treatments. We propose that different regulation of C and N status through direct molecular signaling of NO₃ ^- and/or different allocation of N between tree parts depending on N forms could account for the contrasting effects of NO₃ ^- and tested here amino acids (Arg, Glu, Gln, and Leu) on autumn senescence.

Wastewater effluent affects behaviour and metabolomic endpoints in damselfly larvae

Wastewater treatment plant effluents have been identified as a major contributor to increasing anthropogenic pollution in aquatic environments worldwide. Yet, little is known about the potentially adverse effects of wastewater treatment plant effluent on aquatic invertebrates. In this study, we assessed effects of wastewater effluent on the behaviour and metabolic profiles of damselfly larvae (Coenagrion hastulatum), a common aquatic invertebrate species. Four key behavioural traits: activity, boldness, escape response, and foraging (traits all linked tightly to individual fitness) were studied in larvae before and after one week of exposure to a range of effluent dilutions (0, 50, 75, 100%). Effluent exposure reduced activity and foraging, but generated faster escape response. Metabolomic analyses via targeted and non-targeted mass spectrometry methods revealed that exposure caused significant changes to 14 individual compounds (4 amino acids, 3 carnitines, 3 lysolipids, 1 peptide, 2 sugar acids, 1 sugar). Taken together, these compound changes indicate an increase in protein metabolism and oxidative stress. Our findings illustrate that wastewater effluent can affect both behavioural and physiological traits of aquatic invertebrates, and as such might pose an even greater threat to aquatic ecosystems than previously assumed. More long-term studies are now needed evaluate if these changes are linked to adverse effects on fitness. The combination of behavioural and metabolomic assessments provide a promising tool for detecting effects of wastewater effluent, on multiple biological levels of organisation, in aquatic ecosystems.

Impaired phosphocreatine metabolism in white adipocytes promotes inflammation

The mechanisms promoting disturbed white adipocyte function in obesity remain largely unclear. Herein, we integrate white adipose tissue (WAT) metabolomic and transcriptomic data from clinical cohorts and find that the WAT phosphocreatine/creatine ratio is increased and creatine kinase-B expression and activity is decreased in the obese state. In human in vitro and murine in vivo models, we demonstrate that decreased phosphocreatine metabolism in white adipocytes alters adenosine monophosphate-activated protein kinase activity via effects on adenosine triphosphate/adenosine diphosphate levels, independently of WAT beigeing. This disturbance promotes a pro-inflammatory profile characterized, in part, by increased chemokine (C-C motif) ligand 2 (CCL2) production. These data suggest that the phosphocreatine/creatine system links cellular energy shuttling with pro-inflammatory responses in human and murine white adipocytes. Our findings provide unexpected perspectives on the mechanisms driving WAT inflammation in obesity and may present avenues to target adipocyte dysfunction.

Defining Blood Plasma and Serum Metabolome by GC-MS

Metabolomics uses advanced analytical chemistry methods to analyze metabolites in biological samples. The most intensively studied samples are blood and its liquid components: plasma and serum. Armed with advanced equipment and progressive software solutions, the scientific community has shown that small molecules’ roles in living systems are not limited to traditional “building blocks” or “just fuel” for cellular energy. As a result, the conclusions based on studying the metabolome are finding practical reflection in molecular medicine and a better understanding of fundamental biochemical processes in living systems. This review is not a detailed protocol of metabolomic analysis. However, it should support the reader with information about the achievements in the whole process of metabolic exploration of human plasma and serum using mass spectrometry combined with gas chromatography.

Optimized Workflow for On-Line Derivatization for Targeted Metabolomics Approach by Gas Chromatography-Mass Spectrometry

Using manual derivatization in gas chromatography-mass spectrometry samples have varying equilibration times before analysis which increases technical variability and limits the number of potential samples analyzed. By contrast, automated derivatization methods can derivatize and inject each sample in an identical manner. We present a fully automated (on-line) derivatization method used for targeted analysis of different matrices. We describe method optimization and compare results from using off-line and on-line derivatization protocols, including the robustness and reproducibility of the methods. Our final parameters for the derivatization process were 20 µL of methoxyamine (MeOx) in pyridine for 60 min at 30 °C followed by 80 µL N-Methyl-N-trimethylsilyltrifluoracetamide (MSTFA) for 30 min at 30 °C combined with 4 h of equilibration time. The repeatability test in plasma and liver revealed a median relative standard deviation (RSD) of 16% and 10%, respectively. Serum samples showed a consistent intra-batch median RSD of 20% with an inter-batch variability of 27% across three batches. The direct comparison of on-line versus off-line demonstrated that on-line was fit for purpose and improves repeatability with a measured median RSD of 11% compared to 17% using the same method off-line. In summary, we recommend that optimized on-line methods may improve results for metabolomics and should be used where available.

Improved Peripheral and Hepatic Insulin Sensitivity after Lifestyle Interventions in Type 2 Diabetes Is Associated with Specific Metabolomic and Lipidomic Signatures in Skeletal Muscle and Plasma

Lifestyle interventions with weight loss can improve insulin sensitivity in type 2 diabetes (T2D), but mechanisms are unclear. We explored circulating and skeletal muscle metabolite signatures of altered peripheral (pIS) and hepatic insulin sensitivity (hIS) in overweight and obese T2D individuals that were randomly assigned a 12-week Paleolithic-type diet with (diet-ex, n = 13) or without (diet, n = 13) supervised exercise. Baseline and post-intervention measures included: mass spectrometry-based metabolomics and lipidomics of skeletal muscle and plasma; pIS and hIS; ectopic lipid deposits in the liver and skeletal muscle; and skeletal muscle fat oxidation rate. Both groups lowered BMI and total % fat mass and increased their pIS. Only the diet-group improved hIS and reduced ectopic lipids in the liver and muscle. The combined improvement in pIS and hIS in the diet-group were associated with decreases in muscle and circulating branched-chain amino acid (BCAA) metabolites, specifically valine. Improved pIS with diet-ex was instead linked to increased diacylglycerol (34:2) and triacylglycerol (56:0) and decreased phosphatidylcholine (34:3) in muscle coupled with improved muscle fat oxidation rate. This suggests a tissue crosstalk involving BCAA-metabolites after diet intervention with improved pIS and hIS, reflecting reduced lipid influx. Increased skeletal muscle lipid utilization with exercise may prevent specific lipid accumulation at sites that perturb insulin signaling.

Cross-comparison of systemic and tissue-specific metabolomes in a mouse model of Leigh syndrome

INTRODUCTION

The value of metabolomics in multi-systemic mitochondrial disease research has been increasingly recognized, with the ability to investigate a variety of biofluids and tissues considered a particular advantage. Although minimally invasive biofluids are the generally favored sample type, it remains unknown whether systemic metabolomes provide a clear reflection of tissue-specific metabolic alterations.

OBJECTIVES

Here we cross-compare urine and tissue-specific metabolomes in the Ndufs4 knockout mouse model of Leigh syndrome-a complex neurometabolic MD defined by progressive focal lesions in specific brain regions-to identify and evaluate the extent of common and unique metabolic alterations on a systemic and brain regional level.

METHODS

Untargeted and semi-targeted multi-platform metabolomics were performed on urine, four brain regions, and two muscle types of Ndufs4 KO (n≥19) vs wildtype (n≥20) mice.

RESULTS

Widespread alterations were evident in alanine, aspartate, glutamate, and arginine metabolism in Ndufs4 KO mice; while brain-region specific metabolic signatures include the accumulation of branched-chain amino acids, proline, and glycolytic intermediates. Furthermore, we describe a systemic dysregulation in one-carbon metabolism and the tricarboxylic acid cycle, which was not clearly reflected in the Ndufs4 KO brain.

CONCLUSION

Our results confirm the value of urinary metabolomics when evaluating MD-associated metabolites, while cautioning against mechanistic studies relying solely on systemic biofluids.

Imatinib protects against human beta-cell death via inhibition of mitochondrial respiration and activation of AMPK

The protein tyrosine kinase inhibitor imatinib is used in the treatment of various malignancies but may also promote beneficial effects in the treatment of diabetes. The aim of the present investigation was to characterize the mechanisms by which imatinib protects insulin producing cells. Treatment of non-obese diabetic (NOD) mice with imatinib resulted in increased beta-cell AMP-activated kinase (AMPK) phosphorylation. Imatinib activated AMPK also in vitro, resulting in decreased ribosomal protein S6 phosphorylation and protection against islet amyloid polypeptide (IAPP)-aggregation, thioredoxin interacting protein (TXNIP) up-regulation and beta-cell death. 5-Aminoimidazole-4-carboxamide ribonucleotide (AICAR) mimicked and compound C counteracted the effect of imatinib on beta-cell survival. Imatinib-induced AMPK activation was preceded by reduced glucose/pyruvate-dependent respiration, increased glycolysis rates, and a lowered ATP/AMP ratio. Imatinib augmented the fractional oxidation of fatty acids/malate, possibly via a direct interaction with the beta-oxidation enzyme enoyl coenzyme A hydratase, short chain, 1, mitochondrial (ECHS1). In non-beta cells, imatinib reduced respiratory chain complex I and II-mediated respiration and acyl-CoA carboxylase (ACC) phosphorylation, suggesting that mitochondrial effects of imatinib are not beta-cell specific. In conclusion, tyrosine kinase inhibitors modestly inhibit mitochondrial respiration, leading to AMPK activation and TXNIP down-regulation, which in turn protects against beta-cell death.

A metabolomic study of Gomphrena agrestis in Brazilian Cerrado suggests drought-adaptive strategies on metabolism

Drought is the main factor that limits the distribution and productivity of plant species. In the Brazilian Cerrado, the vegetation is adapted to a seasonal climate with long- and short-term periods of drought. To analyze the metabolic strategies under such conditions, a metabolomic approach was used to characterize Gomphrena agrestis Mart. (Amaranthaceae) a native species that grows under natural conditions, in a rock-field area. Roots and leaves material from native specimens were sampled along different seasons of the year and LC–MS and GC–MS analyzed for multiple chemical constituents. The datasets derived from the different measurements were combined and evaluated using multivariate analysis. Principal component analysis was used to obtain an overview of the samples and identify outliers. Later, the data was analyzed with orthogonal projection to latent structures discriminant analysis to obtain valid models that could explain the metabolite variations in the different seasons. Two hundred and eighty metabolites were annotated, generating a unique database to characterize metabolic strategies used to cope with the effects of drought. The accumulation of fructans in the thickened roots is consistent with the storage of carbons during the rainy season to support the energy demand during a long period of drought. The accumulation of Abscisic acid, sugars and sugar alcohols, phenolics, and pigment in the leaves suggests physiological adaptations. To cope with long-term drought, the data suggests that tissue water status and storage of reserves are important to support plant survival and regrowth. However, during short-term drought, osmoregulation and oxidative protection seems to be essential, probably to support the maintenance of active photosynthesis.

Next-Generation Mass Spectrometry Metabolomics Revives the Functional Analysis of Plant Metabolic Diversity

The remarkable diversity of specialized metabolites produced by plants has inspired several decades of research and nucleated a long list of theories to guide empirical ecological studies. However, analytical constraints and the lack of untargeted processing workflows have long precluded comprehensive metabolite profiling and, consequently, the collection of the critical currencies to test theory predictions for the ecological functions of plant metabolic diversity. Developments in mass spectrometry (MS) metabolomics have revolutionized the large-scale inventory and annotation of chemicals from biospecimens. Hence, the next generation of MS metabolomics propelled by new bioinformatics developments provides a long-awaited framework to revisit metabolism-centered ecological questions, much like the advances in next-generation sequencing of the last two decades impacted all research horizons in genomics. Here, we review advances in plant (computational) metabolomics to foster hypothesis formulation from complex metabolome data. Additionally, we reflect on how next-generation metabolomics could reinvigorate the testing of long-standing theories on plant metabolic diversity.

Comprehensive Lipidome and Metabolome Profiling Investigations of Panax quinquefolius and Application in Different Growing Regions Using Liquid Chromatography Coupled with Mass Spectrometry

Panax quinquefolius is one of the most recognized ginseng species. In this study, lipidome and metabolome extraction methods for P. quinquefolius were optimized with methanol/methyl-tert-butyl ether/water (0.3 mg/1 μL/6 μL/8 μL). A total of 497 metabolites were identified, including 365 lipids and 76 ginsenosides. Comprehensive lipidome profiling was first performed for P. quinquefolius, in which 32.6% glycerophospholipids, 39.5% glycerolipids, 9.3% sphingolipids, 3.3% sterol lipids, and 15.3% fatty acyls were identified. Orthogonal partial least squares discrimination analysis (OPLS-DA) showed obvious metabolomic differences in two growing regions of China. In the northern growing region, the ratio of bilayer- to nonbilayer-forming membrane lipids (PCs/PEs, DGDGs/MGDGs), the degree of unsaturation of acyl chains in galactolipids, and the content of membrane glycerophospholipids were increased. In the eastern growing region, the synthesis of storage lipids, ceramides, and fatty acyls was increased, and secondary metabolism was enhanced with 24 differential ginsenosides found. The investigation deepens the understanding of metabolic regulation mechanisms of P. quinquefolius.

Non-natural Aldol Reactions Enable the Design and Construction of Novel One-Carbon Assimilation Pathways in vitro

Methylotrophs utilizes cheap, abundant one-carbon compounds, offering a promising green, sustainable and economical alternative to current sugar-based biomanufacturing. However, natural one-carbon assimilation pathways come with many disadvantages, such as complicated reaction steps, the need for additional energy and/or reducing power, or loss of CO₂, resulting in unsatisfactory biomanufacturing performance. Here, we predicted eight simple, novel and carbon-conserving formaldehyde (FALD) assimilation pathways based on the extended metabolic network with non-natural aldol reactions using the comb-flux balance analysis (FBA) algorithm. Three of these pathways were found to be independent of energy/reducing equivalents, and thus chosen for further experimental verification. Then, two novel aldol reactions, condensing D-erythrose 4-phosphate and glycolaldehyde (GALD) into 2R,3R-stereo allose 6-phosphate by DeoC or 2S,3R-stereo altrose 6-phosphate by TalB^F178Y/Fsa, were identified for the first time. Finally, a novel FALD assimilation pathway proceeding via allose 6-phosphate, named as the glycolaldehyde-allose 6-phosphate assimilation (GAPA) pathway, was constructed in vitro with a high carbon yield of 94%. This work provides an elegant paradigm for systematic design of one-carbon assimilation pathways based on artificial aldolase (ALS) reactions, which could also be feasibly adapted for the mining of other metabolic pathways.

Stem girdling affects the onset of autumn senescence in aspen in interaction with metabolic signals

Autumn senescence in aspen (Populus tremula) is precisely timed every year to relocate nutrients from leaves to storage organs before winter. Here we demonstrate how stem girdling, which leads to the accumulation of photosynthates in the crown, influences senescence. Girdling resulted in an early onset of senescence, but the chlorophyll degradation was slower and nitrogen more efficiently resorbed than during normal autumn senescence. Girdled stems accumulated or retained anthocyanins potentially providing photoprotection in senescing leaves. Girdling of one stem in a clonal stand sharing the same root stock did not affect senescence in the others, showing that the stems were autonomous in this respect. One girdled stem with unusually high chlorophyll and nitrogen contents maintained low carbon-to-nitrogen (C/N) ratio and did not show early senescence or depleted chlorophyll level unlike the other girdled stems suggesting that the responses depended on the genotype or its carbon and nitrogen status. Metabolite analysis highlighted that the tricarboxylic acid (TCA) cycle, salicylic acid pathway, and redox homeostasis are involved in the regulation of girdling-induced senescence. We propose that disrupted sink-source relation and C/N status can provide cues through the TCA cycle and phytohormone signaling to override the phenological control of autumn senescence in the girdled stems.

HPLC-MS-based design of experiments approach on cocoa roasting

Modern statistical methods, such as the design of experiments and response surface methodology, are widely used to describe changes in multiparameter processes during the processing of food in both science and technology contexts. However, these approaches are described to a lesser degree in the case of cocoa roasting than other foods and processes. Our study aimed to use the design of experiments to establish a model of cocoa roasting for relevant flavor-related constituents. We have used HPLC-MS techniques to link standard process parameters with chemical compounds changing in concentration during cocoa roasting. Influence of time, temperature, the addition of water, acid, and base, on relative concentrations of procyanidin monomers, dimers, and trimers, an Amadori compound, and a peptide, was shown. High-quality models for each compound were established and validated, displaying good prediction accuracy. Such an approach could be used to optimize processing conditions for cocoa roasting in order to influence the concentration of certain chemical compounds, and in turn, improving the flavor of chocolate products.

Metabolomics, a Powerful Tool for Understanding Plant Abiotic Stress

Metabolomics is a technology that generates large amounts of data and contributes to obtaining wide and integral explanations of the biochemical state of a living organism. Plants are continuously affected by abiotic stresses such as water scarcity, high temperatures and high salinity, and metabolomics has the potential for elucidating the response-to-stress mechanisms and develop resistance strategies in affected cultivars. This review describes the characteristics of each of the stages of metabolomic studies in plants and the role of metabolomics in the characterization of the response of various plant species to abiotic stresses.

Metabolomic Study of Heterotrophically Grown Chlorella sp. Isolated from Wastewater in Northern Sweden

There are numerous strains of Chlorella with a corresponding variety of metabolic pathways. A strain we previously isolated from wastewater in northern Sweden can grow heterotrophically as well as autotrophically in light and has higher lipid contents under heterotrophic growth conditions. The aims of the present study were to characterize metabolic changes associated with the higher lipid contents in order to enhance our understanding of lipid production in microalgae and potentially identify new compounds with utility in sustainable development. Inter alia, the amino acids glutamine and lysine were 7-fold more abundant under heterotrophic conditions, the key metabolic intermediate alpha-ketoglutarate was more abundant under heterotrophic conditions with glucose, and maltose was more abundant under heterotrophic conditions with glycerol than under autotrophic conditions. The metabolite 3-hydroxy-butyric acid, the direct precursor of the biodegradable plastic PHB (poly-3-hydroxy-butyric acid), was also more abundant under heterotrophic conditions. Our metabolomic analysis has provided new insights into the alga's lipid production pathways and identified metabolites with potential use in sustainable development, such as the production of renewable, biodegradable plastics, cosmetics, and nutraceuticals, with reduced pollution and improvements in both ecological and human health.