Metabolic Pathway Maps Research Articles

An integrated approach for studying exposure, metabolism, and disposition of traditional Chinese medicine using PATBS and MDRB tools: a case study of semen Armeniacae Amarum

BackgroundDeciphering the in vivo processes of traditional Chinese medicine (TCM) is crucial for identifying new pharmacodynamic substances and new drugs. Due to the complexity and diversity of components, investigating the exposure, metabolism, and disposition remains a major challenge in TCM research. In recent years, a number of non-targeted smart mass-spectrometry (MS) techniques, such as precise-and-thorough background-subtraction (PATBS) and metabolomics, have realized the intelligent identification of in vivo components of TCM. However, the metabolites characterization still largely relies on manual identification in combination with online databases.ResultsWe developed a scoring approach based on the structural similarity and minimal mass defect variations between metabolites and prototypes. The current method integrates three dimensions of mass spectral data including m/z, mass defect of MS1 and MS2, and the similarity of MS2 fragments, which was sequentially analyzed by a R-based mass dataset relevance bridging (MDRB) data post-processing technique. The MDRB technology constructed a component relationship network for TCM, significantly improving metabolite identification efficiency and facilitating the mapping of translational metabolic pathways. By combining MDRB with PATBS through this non-targeted identification technology, we developed a comprehensive strategy for identification, characterization and bridging analysis of TCM metabolite in vivo. As a proof of concept, we adopted the proposed strategy to investigate the process of exposure, metabolism, and disposition of Semen Armeniacae Amarum (CKXR) in mice.SignificanceThe currently proposed analytical approach is universally applicable and demonstrates its effectiveness in analyzing complex components of TCMs in vitro and in vivo. Furthermore, it enables the correlation of in vitro and in vivo data, providing insights into the metabolic transformations among components sharing the same parent nucleus structure. Finally, the developed MDRB platform is publicly available for (https://github.com/933ZhangDD/MDRB) for accelerating TCM research for the scientific community.Graphical

A multiorgan map of metabolic, signaling, and inflammatory pathways that coordinately control fasting glycemia in mice

To identify the pathways that are coordinately regulated in pancreatic β cells, muscle, liver, and fat to control fasting glycemia we fed C57Bl/6, DBA/2, and Balb/c mice a regular chow or a high fat diet for 5, 13, and 33days. Physiological, transcriptomic and lipidomic data were used in a data fusion approach to identify organ-specific pathways linked to fasting glycemia across all conditions investigated. In pancreatic islets, constant insulinemia despite higher glycemic levels was associated with reduced expression of hormone and neurotransmitter receptors, OXPHOS, cadherins, integrins, and gap junction mRNAs. Higher glycemia and insulin resistance were associated, in muscle, with decreased insulin signaling, glycolytic, Krebs' cycle, OXPHOS, and endo/exocytosis mRNAs; in hepatocytes, with reduced insulin signaling, branched chain amino acid catabolism and OXPHOS mRNAs; in adipose tissue, with increased innate immunity and lipid catabolism mRNAs. These data provide a resource for further studies of interorgan communication in glucose homeostasis.

Proteogenomic reconstruction of organ-specific metabolic networks in an environmental sentinel species, the amphipod Gammarus fossarum

Metabolic pathways are affected by the impacts of environmental contaminants underlying a large variability of toxic effects across different species. However, the systematic reconstruction of metabolic pathways remains limited in environmental sentinel species due to the lack of available genomic data in many taxa of animal diversity. In this study we used a multi-omics approach to reconstruct the most comprehensive map of metabolic pathways for a crustacean model in biomonitoring, the amphipod Gammarus fossarum in order to improve the knowledge of the metabolism of this sentinel species.We revisited the assembly of RNA-seq data by de novo approaches to reduce RNA contaminants and transcript redundancy. We also acquired extensive mass spectrometry shotgun proteomic data on several organs from a reference population of G. fossarum males and females to identify organ-specific metabolic profiles.The G. fossarum metabolic pathway reconstruction (available through the metabolic database GamfoCyc) was performed by adapting the genomic tool CycADS and we identified 377 pathways representing 7630 annotated enzymes, 2610 enzymatic reactions and the expression of 858 enzymes was experimentally validated by proteomics. To our knowledge, our analysis provides for the first time a systematic metabolic pathway reconstruction and the proteome profiles of these pathways at the organ level in this sentinel species. As an example, we show an elevated abundance in enzymes involved in ATP biosynthesis and fatty acid beta-oxidation indicative of the high-energy requirement of the gills, or the key anabolic and detoxification role of the hepatopancreatic caeca, as exemplified by the specific expression of the retinoid biosynthetic pathways and glutathione synthesis.In conclusion, the multi-omics data integration performed in this study provides new resources to investigate metabolic processes in crustacean amphipods and their role in mediating the effects of environmental contaminant exposures in sentinel species. SynopsisThis study provide the first evidence that it is possible to combine multiple omics data to exhaustively describe the metabolic network of a model species in ecotoxicology, Gammarus fossarum, for which a reference genome is not yet available.

New mechanistic understanding of osteoclast differentiation and bone resorption mediated by P2X7 receptors and PI3K-Akt-GSK3β signaling

ObjectiveOsteoporosis is a global health issue characterized by decreased bone mass and microstructural degradation, leading to an increased risk of fractures. This study aims to explore the molecular mechanism by which P2X7 receptors influence osteoclast formation and bone resorption through the PI3K-Akt-GSK3β signaling pathway.MethodsAn osteoporosis mouse model was generated through ovariectomy (OVX) in normal C57BL/6 and P2X7f/f; LysM-cre mice. Osteoclasts were isolated for transcriptomic analysis, and differentially expressed genes were selected for functional enrichment analysis. Metabolite analysis was performed using liquid chromatography-tandem mass spectrometry (LC–MS/MS), and multivariate statistical analysis and pattern recognition were used to identify differential lipid metabolism markers and their distribution. Bioinformatics analyses were conducted using the Encyclopedia of Genes and Genomes database and the MetaboAnalyst database to assess potential biomarkers and create a metabolic pathway map. Osteoclast precursor cells were used for in vitro cell experiments, evaluating cell viability and proliferation using the Cell Counting Kit 8 (CCK-8) assay. Osteoclast precursor cells were induced to differentiate into osteoclasts using macrophage colony-stimulating factor (M-CSF) and receptor activator of nuclear factor kappa-beta ligand (RANKL), and tartrate-resistant acid phosphatase (TRAP) staining was performed to compare differentiation morphology, size, and quantity between different groups. Western blot analysis was used to assess the expression of differentiation markers, fusion gene markers, and bone resorption ability markers in osteoclasts. Immunofluorescence staining was employed to examine the spatial distribution and quantity of osteoclast cell skeletons, P2X7 protein, and cell nuclei, while pit assay was used to evaluate osteoclast bone resorption ability. Finally, in vivo animal experiments, including micro computed tomography (micro-CT), hematoxylin and eosin (HE) staining, TRAP staining, and immunohistochemistry, were conducted to observe bone tissue morphology, osteoclast differentiation, and the phosphorylation level of the PI3K-Akt-GSK3β signaling pathway.ResultsTranscriptomic and metabolomic data collectively reveal that the P2X7 receptor can impact the pathogenesis of osteoporosis through the PI3K-Akt-GSK3β signaling pathway. Subsequent in vitro experiments showed that cells in the Sh-P2X7 + Recilisib group exhibited increased proliferative activity (1.15 versus 0.59), higher absorbance levels (0.68 versus 0.34), and a significant increase in resorption pit area (13.94 versus 3.50). Expression levels of osteoclast differentiation-related proteins MMP-9, CK, and NFATc1 were markedly elevated (MMP-9: 1.72 versus 0.96; CK: 2.54 versus 0.95; NFATc1: 3.05 versus 0.95), along with increased fluorescent intensity of F-actin rings. In contrast, the OE-P2X7 + LY294002 group showed decreased proliferative activity (0.64 versus 1.29), reduced absorbance (0.34 versus 0.82), and a significant decrease in resorption pit area (5.01 versus 14.96), accompanied by weakened expression of MMP-9, CK, and NFATc1 (MMP-9: 1.14 versus 1.79; CK: 1.26 versus 2.75; NFATc1: 1.17 versus 2.90) and decreased F-actin fluorescent intensity. Furthermore, in vivo animal experiments demonstrated that compared with the wild type (WT) + Sham group, mice in the WT + OVX group exhibited significantly increased levels of CTX and NTX in serum (CTX: 587.17 versus 129.33; NTX: 386.00 versus 98.83), a notable decrease in calcium deposition (19.67 versus 53.83), significant reduction in bone density, increased trabecular separation, and lowered bone mineral density (BMD). When compared with the KO + OVX group, mice in the KO + OVX + recilisib group showed a substantial increase in CTX and NTX levels in serum (CTX: 503.50 versus 209.83; NTX: 339.83 versus 127.00), further reduction in calcium deposition (29.67 versus 45.33), as well as decreased bone density, increased trabecular separation, and reduced BMD.ConclusionP2X7 receptors positively regulate osteoclast formation and bone resorption by activating the PI3K-Akt-GSK3β signaling pathway.

Mechanism and bioinformatics analysis of the effect of berberine-enhanced fluconazole against drug-resistant Candida albicans

Biofilms produced by Candida albicans present a challenge in treatment with antifungal drug. Enhancing the sensitivity to fluconazole (FLC) is a reasonable method for treating FLC-resistant species. Moreover, several lines of evidence have demonstrated that berberine (BBR) can have antimicrobial effects. The aim of this study was to clarify the underlying mechanism of these effects. We conducted a comparative study of the inhibition of FLC-resistant strain growth by FLC treatment alone, BBR treatment alone, and the synergistic effect of combined FLC and BBR treatment. Twenty-four isolated strains showed distinct biofilm formation capabilities. The antifungal effect of combined FLC and BBR treatment in terms of the growth and biofilm formation of Candida albicans species was determined via checkerboard, time-kill, and fluorescence microscopy assays. The synergistic effect of BBR and FLC downregulated the expression of the efflux pump genes CDR1 and MDR, the hyphal gene HWP1, and the adhesion gene ALS3; however, the gene expression of the transcriptional repressor TUP1 was upregulated following treatment with this drug combination. Furthermore, the addition of BBR led to a marked reduction in cell surface hydrophobicity. To identify resistance-related genes and virulence factors through genome-wide sequencing analysis, we investigated the inhibition of related resistance gene expression by the combination of BBR and FLC, as well as the associated signaling pathways and metabolic pathways. The KEGG metabolic map showed that the metabolic genes in this strain are mainly involved in amino acid and carbon metabolism. The metabolic pathway map showed that several ergosterol (ERG) genes were involved in the synthesis of cell membrane sterols, which may be related to drug resistance. In this study, BBR + FLC combination treatment upregulated the expression of the ERG1, ERG3, ERG4, ERG5, ERG24, and ERG25 genes and downregulated the expression of the ERG6 and ERG9 genes compared with fluconazole treatment alone (p < 0.05).

GC/MS and LC/MS serum metabolomic analysis of Chinese LN patients

China, being a densely populated nation, faces a substantial economic burden due to a high incidence of lupus nephritis (LN) cases. The concealed onset of LN has resulted in many individuals have missed the optimal timing for treatment. The aim of the research is to study the serum metabolomics of Chinese LN patients using gas chromatography (GC)/mass spectrometry (MS) and liquid chromatography (LC)/MS to identify potential diagnostic markers. Fifty LN patients and fifty normal controls, matched for Body Mass Index (BMI) and age, were selected. Serum analysis was conducted using GC/MS and LC/MS, followed by multivariate statistical analysis. Various multidimensional analyses, including principal component analysis, partial least squares discrimination analysis, and orthogonal partial least squares discrimination analysis, along with one-dimensional analyses such as t-tests, were performed. Metabolites with variable importance in projection value > 1 and a p-value < 0.05 were considered critical biomarkers for LN. Furthermore, identified biomarkers delineated relevant metabolic pathways, and a metabolic pathway map was obtained from the database. Forty-one metabolites were identified as potential LN biomarkers, primarily associated with immune regulation, energy metabolism, intestinal microbial metabolism, renal damage, and oxidative stress. The potential for diagnosing LN and other diseases through metabolomics is demonstrated. Future research should explore larger sample sizes, metabolomic comparisons across different diseases and health states, and integration of metabolomics with clinical diagnostics. Such studies will enhance the understanding of metabolomics in medical diagnosis and provide robust support for its practical application.

A metabonomic study to explore potential markers of asymptomatic hyperuricemia and acute gouty arthritis

BackgroundAcute gouty arthritis (AGA) is a metabolic disease with acute arthritis as its main manifestation. However, the pathogenesis of asymptomatic hyperuricemia (HUA) to AGA is still unclear, and metabolic markers are needed to early predict and diagnose. In this study, gas chromatography (GC)/liquid chromatography (LC)–mass spectrometry (MS) was used to reveal the changes of serum metabolites from healthy people to HUA and then to AGA, and to find the pathophysiological mechanism and biological markers.MethodsFifty samples were included in AGA, HUA, and healthy control group, respectively. The metabolites in serum samples were detected by GC/LC–MS. According to the statistics of pairwise grouping, the statistically significant differential metabolites were obtained by the combination of multidimensional analysis and one-dimensional analysis. Search the selected metabolites in KEGG database, determine the involved metabolic pathways, and draw the metabolic pathway map in combination with relevant literature.ResultsUsing metabonomics technology, 23 different serum metabolic markers related to AGA and HUA were found, mainly related to uric acid metabolism and inflammatory response caused by HUA/AGA. Three of them are completely different from the previous gout studies, nine metabolites with different trends from conventional inflammation.ConclusionsIn conclusion, we analyzed 150 serum samples from AGA, HUA, and healthy control group by GC/LC–MS to explore the changes of these differential metabolites and metabolic pathways, suggesting that the disease progression may involve the changes of biomarkers, which may provide a basis for disease risk prediction and early diagnosis.

Review on microbial metabolomics of probiotics and pathogens: Methodologies and applications

In recent years, microbial metabolomics, a new field that has attracted wide attention, provides a map of metabolic pathways and clarifies the interaction mechanism between microorganisms and hosts. Many microorganisms are found in the human intestine, oral cavity, vagina, etc. Probiotics could maintain the good health of the host, while pathogens and an imbalance of bacterial flora lead to a series of diseases of the body and mind. Metabolomics is a science for qualitative and quantitative analysis of all metabolites in an organism or biological system, which could provide key information to understand the related metabolic pathways and associated changes. This approach analyzes the final products of cellular regulatory processes, the level of which can be regarded as the ultimate response of the biological system to genetic or environmental changes. Microbial metabolomics has been widely used in different research fields, such as microbial phenotypic classification, mutant screening, metabolic pathways, microbial metabolic engineering, fermentation engineering monitoring and optimization, microbial environmental pollution, and so on. However, there are only a few reviews on microbial metabolomics of probiotics and pathogens. This review summarizes the main methodologies, including sample preparation, identification of metabolites, data processing, and analysis. Recent applications in microbial metabolomics of probiotics and pathogens are also described. This paper first summarized the research progress and application of microbial metabolomics from two aspects: probiotics and pathogenic bacteria. Probiotics and pathogenic bacteria do not exist independently most of the time; hence, these were reviewed in the research field of coexistence of probiotics and pathogenic bacteria, which was subdivided into important microbial research fields closely related to human health, including the human gut, oral cavity, food, and nutrition-related microorganisms. Then, the main problems and trends associated with microbial metabolomics are discussed.

Combining metabolomics and machine learning models as a tool to distinguish non-classic 21-hydroxylase deficiency from polycystic ovary syndrome without adrenocorticotropic hormone testing.

Can a combination of metabolomic signature and machine learning (ML) models distinguish nonclassic 21-hydroxylase deficiency (NC21OHD) from polycystic ovary syndrome (PCOS) without adrenocorticotrophic hormone (ACTH) testing? A single sampling methodology may be an alternative to the dynamic ACTH test in order to exclude the diagnosis of NC21OHD in the presence of a clinical hyperandrogenic presentation at any time of the menstrual cycle. The clinical presentation of patients with NC21OHD is similar with that for other disorders of androgen excess. Currently, cosyntropin stimulation remains the gold standard diagnosis of NC21OHD. The study was designed using a bicentric recruitment: an internal training set included 19 women with NC21OHD and 19 controls used for developing the model; a test set included 17 NC21OHD, 72 controls and 266 PCOS patients used to evaluate the performance of the diagnostic strategy thanks to an ML approach. Fifteen steroid species were measured in serum by liquid chromatography-mass spectrometry (LC-MS/MS). This set of 15 steroids (defined as 'steroidome') used to map the steroid biosynthesis pathway was the input for our models. From a single sample, modeling involving metabolic pathway mapping by profiling 15 circulating steroids allowed us to identify perfectly NC21OHD from a confounding PCOS population. The constructed model using baseline LC-MS/MS-acquired steroid fingerprinting successfully excluded all 17 NC21OHDs (sensitivity and specificity of 100%) from 266 PCOS from an external testing cohort of originally 549 women, without the use of ACTH testing. Blood sampling timing during the menstrual cycle phase did not impact the efficiency of our model. The main limitations were the use of a restricted and fully prospective cohort as well as an analytical issue, as not all laboratories are equipped with mass spectrometers able to routinely measure this panel of 15 steroids. Moreover, the robustness of our model needs to be established with a larger prospective study for definitive validation in clinical practice. This tool makes it possible to propose a new semiology for the management of hyperandrogenism. The model presents better diagnostic performances compared to the current reference strategy. The management of patients may be facilitated by limiting the use of ACTH tests. Finally, the modeling process allows a classification of steroid contributions to rationalize the biomarker approach and highlight some underlying pathophysiological mechanisms. This study was supported by 'Agence Française de Lutte contre le dopage' and DIM Région Ile de France. This study was supported by the French institutional PHRC 2010-AOR10032 funding source and APHP. All authors declare no competing financial interests. N/A.

Discovery of Potential Biomarkers for Postmenopausal Osteoporosis Based on Untargeted GC/LC-MS.

PurposeAs an important public health problem, osteoporosis (OP) in China is also in an upward trend year by year. As a standard method for diagnosing OP, dual-energy X-ray absorptiometry (DXA) cannot analyze the pathological process but only see the results. It is difficult to evaluate the early diagnosis of OP. Our study was carried out through a serum metabolomic study of OP in Chinese postmenopausal women on untargeted gas chromatography (GC)/liquid chromatography (LC)–mass spectrometry (MS) to find possible diagnostic markers.Materials and Methods50 Chinese postmenopausal women with osteoporosis and 50 age-matched women were selected as normal controls. We first used untargeted GC/LC-MS to analyze the serum of these participants and then combined it with a large number of multivariate statistical analyses to analyze the data. Finally, based on a multidimensional analysis of the metabolites, the most critical metabolites were considered to be biomarkers of OP in postmenopausal women. Further, biomarkers identified relevant metabolic pathways, followed by a map of metabolic pathways found in the database.ResultsWe found that there may be metabolic pathway disorders like glucose metabolism, lipid metabolism, and amino acid metabolism in postmenopausal women with OP. 18 differential metabolites are considered to be potential biomarkers of OP in postmenopausal women which are a major factor in metabolism and bone physiological function.ConclusionThese findings can be applied to clinical work through further validation studies. It also shows that metabonomic analysis has great potential in the application of early diagnosis and recurrence monitoring in postmenopausal OP women.

Dietary Omega-3 Polyunsaturated Fatty-Acid Supplementation Upregulates Protective Cellular Pathways in Patients with Type 2 Diabetes Exhibiting Improvement in Painful Diabetic Neuropathy

Background: Omega-3 polyunsaturated fatty acids (PUFAs) have been proposed to improve chronic neuroinflammatory diseases in peripheral and central nervous systems. For instance, docosahexaenoic acid (DHA) protects nerve cells from noxious stimuli in vitro and in vivo. Recent reports link PUFA supplementation to improving painful diabetic neuropathy (pDN) symptoms, but cellular mechanisms responsible for this therapeutic effect are not well understood. The objective of this study is to identify distinct cellular pathways elicited by dietary omega-3 PUFA supplementation in patients with type 2 diabetes mellitus (T2DM) affected by pDN. Methods: Forty volunteers diagnosed with type 2 diabetes were enrolled in the “En Balance-PLUS” diabetes education study. The volunteers participated in weekly lifestyle/nutrition education and daily supplementation with 1000 mg DHA and 200 mg eicosapentaenoic acid. The Short-Form McGill Pain Questionnaire validated clinical determination of baseline and post-intervention pain complaints. Laboratory and untargeted metabolomics analyses were conducted using blood plasma collected at baseline and after three months of participation in the dietary regimen. The metabolomics data were analyzed using random forest, hierarchical clustering, ingenuity pathway analysis, and metabolic pathway mapping. Results: The data show that metabolites involved in oxidative stress and glutathione production shifted significantly to a more anti-inflammatory state post supplementation. Example of these metabolites include cystathionine (+90%), S-methylmethionine (+9%), glycine cysteine-glutathione disulfide (+157%) cysteinylglycine (+19%), glutamate (−11%), glycine (+11%), and arginine (+13.4%). In addition, the levels of phospholipids associated with improved membrane fluidity such as linoleoyl-docosahexaenoyl-glycerol (18:2/22:6) (+253%) were significantly increased. Ingenuity pathway analysis suggested several key bio functions associated with omega-3 PUFA supplementation such as formation of reactive oxygen species (p = 4.38 × 10−4, z-score = −1.96), peroxidation of lipids (p = 2.24 × 10−5, z-score = −1.944), Ca2+ transport (p = 1.55 × 10−4, z-score = −1.969), excitation of neurons (p = 1.07 ×10−4, z-score = −1.091), and concentration of glutathione (p = 3.06 × 10−4, z-score = 1.974). Conclusion: The reduction of pro-inflammatory and oxidative stress pathways following dietary omega-3 PUFA supplementation is consistent with the promising role of these fatty acids in reducing adverse symptoms associated with neuroinflammatory diseases and painful neuropathy.

IMFLer: A Web Application for Interactive Metabolic Flux Analysis and Visualization.

Increasing genome-wide data in biological sciences and medicine has contributed to the development of a variety of visualization tools. Several automatic, semiautomatic, and manual visualization tools have already been developed. Some even have integrated flux balance analysis (FBA), but in most cases, it depends on separately installed third party software that is proprietary and does not allow customization of its functionality and has many restrictions for easy data distribution and analysis. In this study, we present an interactive metabolic flux analyzer and visualizer (IMFLer)-a static single-page web application that enables the reading and management of metabolic model layout maps, as well as immediate visualization of results from both FBA and flux variability analysis (FVA). IMFLer uses the Escher Builder tool to load, show, edit, and save metabolic pathway maps. This makes IMFLer an attractive and easily applicable tool with a user-friendly interface. Moreover, it allows to faster interpret results from FBA and FVA and improves data interoperability by using a standardized file format for the genome-scale metabolic model. IMFLer is a fully open-source tool that enables the rapid visualization and interpretation of the results of FBA and FVA with no time setup and no programming skills required, available at https://lv-csbg.github.io/IMFLer/.

Identification of Key Genes Controlling Carotenoid Metabolism during Apricot Fruit Development by Integrating Metabolic Phenotypes and Gene Expression Profiles.

To explore the metabolic basis of carotenoid accumulation in different developmental periods of apricot fruits, targeted metabonomic and transcriptomic analyses were conducted in four developmental periods (S1-S4) in two cultivars (Prunus armeniaca cv. "Kuchebaixing" with white flesh and P. armeniaca cv. "Shushangganxing" with orange flesh) with different carotenoid contents. 14 types of carotenes and 27 types of carotene lipids were identified in apricot flesh in different developmental periods. In S3 and S4, the carotenoid contents of the two cultivars were significantly different, and β-carotene and (E/Z)-phytoene were the key metabolites that caused the difference in the total carotenoid content between the examined cultivars. Twenty-five structural genes (including genes in the methylerythritol 4-phosphate and carotenoid biosynthesis pathways) related to carotenoid biosynthesis were identified among the differentially expressed genes in different developmental periods of the two cultivars, and a carotenoid metabolic pathway map of apricot fruits was drawn according to the KEGG pathway map. The combined analysis of carotenoid metabolism data and transcriptome data showed that PSY, NCED1, and CCD4 were the key genes leading to the great differences in the total carotenoid content. The results provide a new approach to study the synthesis and accumulation of carotenoids in apricot fruits.

Comparing Metabolites and Functional Properties of Various Tomatoes Using Mass Spectrometry-Based Metabolomics Approach.

Tomato is one of the world's most consumed vegetables, and thus, various cultivars have been developed. Therefore, metabolic differences and nutrient contents of various tomatoes need to be discovered. To do so, we performed metabolite profiling along with evaluation of morphological and physicochemical properties of five representative tomato types. Common tomato cultivars, bigger and heavier than other tomatoes, contained higher levels of amino acids, organic acids, and lipids. On the contrary, cherry tomato cultivars contained a higher proportion of phenylpropanoids, lycopene, β-carotene, and α-carotene than the other tomatoes. Also, the highest antioxidant activity and total phenolic and flavonoid contents were observed in cherry tomato cultivars. Furthermore, to understand metabolic distributions in various tomato cultivars, we constructed a metabolic pathway map. The higher metabolic flux distribution of most primary metabolite synthetic pathways was observed in common tomatoes, while cherry tomato cultivars showed a significantly elevated flux in secondary metabolite synthetic pathways. Accordingly, these results provide valuable information of different characteristics in various tomatoes, which can be considered while purchasing and improving tomato cultivars.

Dynamic changes of transcriptome of fifth-instar spodoptera litura larvae in response to insecticide.

The online version of this article (10.1007/s13205-021-02651-9) contains supplementary material, which is available to authorized users.

LimeMap: a comprehensive map of lipid mediator metabolic pathways

Lipid mediators are major factors in multiple biological functions and are strongly associated with disease. Recent lipidomics approaches have made it possible to analyze multiple metabolites and the associations of individual lipid mediators. Such systematic approaches have enabled us to identify key changes of biological relevance. Against this background, a knowledge-based pathway map of lipid mediators would be useful to visualize and understand the overall interactions of these factors. Here, we have built a precise map of lipid mediator metabolic pathways (LimeMap) to visualize the comprehensive profiles of lipid mediators that change dynamically in various disorders. We constructed the map by focusing on ω-3 and ω-6 fatty acid metabolites and their respective metabolic pathways, with manual curation of referenced information from public databases and relevant studies. Ultimately, LimeMap comprises 282 factors (222 mediators, and 60 enzymes, receptors, and ion channels) and 279 reactions derived from 102 related studies. Users will be able to modify the map and visualize measured data specific to their purposes using CellDesigner and VANTED software. We expect that LimeMap will contribute to elucidating the comprehensive functional relationships and pathways of lipid mediators.

MetaboMAPS: Pathway sharing and multi-omics data visualization in metabolic context.

Metabolic pathways are an important part of systems biology research since they illustrate complex interactions between metabolites, enzymes, and regulators. Pathway maps are drawn to elucidate metabolism or to set data in a metabolic context. We present MetaboMAPS, a web-based platform to visualize numerical data on individual metabolic pathway maps. Metabolic maps can be stored, distributed and downloaded in SVG-format. MetaboMAPS was designed for users without computational background and supports pathway sharing without strict conventions. In addition to existing applications that established standards for well-studied pathways, MetaboMAPS offers a niche for individual, customized pathways beyond common knowledge, supporting ongoing research by creating publication-ready visualizations of experimental data.

MetaboMAPS: Pathway sharing and multi-omics data visualization in metabolic context

Metabolic pathways are an important part of systems biology research since they illustrate complex interactions between metabolites, enzymes, and regulators. Pathway maps are drawn to elucidate metabolism or to set data in a metabolic context. We present MetaboMAPS, a web-based platform to visualize numerical data on individual metabolic pathway maps. Metabolic maps can be stored, distributed and downloaded in SVG-format. MetaboMAPS was designed for users without computational background and supports pathway sharing without strict conventions. In addition to existing applications that established standards for well-studied pathways, MetaboMAPS offers a niche for individual, customized pathways beyond common knowledge, supporting ongoing research by creating publication-ready visualizations of experimental data.

MetaboMAPS: Pathway sharing and multi-omics data visualization in metabolic context

Metabolic pathways are an important part of systems biology research since they illustrate complex interactions between metabolites, enzymes, and regulators. Pathway maps are drawn to elucidate metabolism or to set data in a metabolic context. We present MetaboMAPS, a web-based platform to visualize numerical data on individual metabolic pathway maps. Metabolic maps can be stored, distributed and downloaded in SVG-format. MetaboMAPS was designed for users without computational background and supports pathway sharing without strict conventions. In addition to existing applications that established standards for well-studied pathways, MetaboMAPS offers a niche for individual, customized pathways beyond common knowledge, supporting ongoing research by creating publication-ready visualizations of experimental data.

Breeding, genetics, and genomics for tolerance against terminal heat in lentil: Current status and future directions

AbstractHeat stress at terminal stage in lentil is one of the major factors causing drastic yield loss. Development of heat tolerant cultivars is one of the ways to tackle this problem. However, heat stress tolerance is a complex trait in nature and many morphological, physiological, biochemical, and metabolic changes are responsible for heat stress tolerance in lentil. Therefore, in the past years, efforts have been made to know genetics and genomics of heat stress tolerance in lentil. In this review, we discussed current progress on breeding, genetics, and genomics including quantitative trait locus (QTL) mapping, transcriptomics, proteomics, and network of metabolic pathways for heat tolerance and future directions for developing heat tolerant cultivars in lentil.