An Interactive Cluster Heat Map to Visualize and Explore Multidimensional Metabolomic Data

Ecological setting of phlebotomine sand flies in the Republic of Kosovo

Sand flies (Diptera, Psychodidae) are the principal vectors of Leishmania spp., the causative agents of leishmaniasis, as well as phleboviruses. In the Balkans, the endemicity and spreading of sand fly-borne diseases are evident, particularly in the Republic of Kosovo, a country with a predominantly humid continental climate. To date, understanding the drivers behind the spatial structure and diversity patterns of sand fly communities in humid continental regions remains limited. Therefore, elucidating the geographical and ecological factors contributing to the presence of potential vector species in the country is crucial. We aimed to enhance our understanding of factors influencing sand fly occurrence in cool and wet wintering humid continental areas, which could serve as a model for other countries with similar climatic conditions. Therefore, we assessed the currently known sand fly fauna through detailed environmental analyses, including Voronoi tessellation patterns, entropy calculations, Principal Coordinate and Component Analyses, Hierarchical Clustering, Random Trees, and climatic suitability patterns. Notable differences in the ecological tolerance of the species were detected, and the most important climatic features limiting sand fly presence were wind speed and temperature seasonality. Sand flies were observed to prefer topographical environments with little roughness, and the modelled climatic suitability values indicated that, dominantly, the western plain regions of Kosovo harbour the most diverse sand fly fauna; and are the most threatened by sand fly-borne diseases. Phlebotomus neglectus and P. perfiliewi, both confirmed vectors for L. infantum and phleboviruses, were identified as two main species with vast distribution in Kosovo. Contrary to this, most other present species are relatively sparse and restricted to temperate rather than humid continental regions. Our findings reveal a diverse potential sand fly fauna in Kosovo, indicating the need for tailored strategies to address varying risks across the country's western and eastern regions in relation to leishmaniasis control amidst changing environmental conditions.

Data-Driven Characterization of Metabolome Reprogramming during Early Development of Sorghum Seedlings

Specialized metabolites are produced via discrete metabolic pathways. These small molecules play significant roles in plant growth and development, as well as defense against environmental stresses. These include damping off or seedling blight at a post-emergence stage. Targeted metabolomics was followed to gain insights into metabolome changes characteristic of different developmental stages of sorghum seedlings. Metabolites were extracted from leaves at seven time points post-germination and analyzed using ultra-high performance liquid chromatography coupled to mass spectrometry. Multivariate statistical analysis combined with chemometric tools, such as principal component analysis, hierarchical clustering analysis, and orthogonal partial least squares-discriminant analysis, were applied for data exploration and to reduce data dimensionality as well as for the selection of potential discriminant biomarkers. Changes in metabolome patterns of the seedlings were analyzed in the early, middle, and late stages of growth (7, 14, and 29 days post-germination). The metabolite classes were amino acids, organic acids, lipids, cyanogenic glycosides, hormones, hydroxycinnamic acid derivatives, and flavonoids, with the latter representing the largest class of metabolites. In general, the metabolite content showed an increase with the progression of the plant growth stages. Most of the differential metabolites were derived from tryptophan and phenylalanine, which contribute to innate immune defenses as well as growth. Quantitative analysis identified a correlation of apigenin flavone derivatives with growth stage. Data-driven investigations of these metabolomes provided new insights into the developmental dynamics that occur in seedlings to limit post-germination mortality.

Phenotypic and metabolomic characteristics of mouse models of metabolic associated steatohepatitis

BACKGROUND

Metabolic associated steatohepatitis (MASH) is metabolic disease that may progress to cirrhosis and hepatocellular carcinoma. Mouse models of diet-induced MASH, which is characterized by the high levels of fats, sugars, and cholesterol in diets, are commonly used in research. However, mouse models accurately reflecting the progression of MASH in humans remain to be established. Studies have explored the potential use of serological metabolites as biomarkers of MASH severity in relation to human MASH.

METHODS

We performed a comparative analysis of three mouse models of diet-induced MASH in terms of phenotypic and metabolomic characteristics; MASH was induced using different diets: a high-fat diet; a Western diet; and a high-fat, high-cholesterol diet. Liver cirrhosis was diagnosed using standard clinical approaches (e.g., METAVIR score, hyaluronan level, and collagen deposition level). Mouse serum samples were subjected to nuclear magnetic resonance spectroscopy-based metabolomic profiling followed by bioinformatic analyses. Metabolomic analysis of a retrospective cohort of patients with hepatocellular carcinoma was performed; the corresponding cirrhosis scores were also evaluated.

RESULTS

Using clinically relevant quantitative diagnostic methods, the severity of MASH was evaluated. Regarding metabolomics, the number of lipoprotein metabolites increased with both diet and MASH progression. Notably, the levels of very low-density lipoprotein (VLDL) and low-density lipoprotein (LDL) significantly increased with fibrosis progression. During the development of diet-induced MASH in mice, the strongest upregulation of expression was noted for VLDL receptor. Metabolomic analysis of a retrospective cohort of patients with cirrhosis indicated lipoproteins (e.g., VLDL and LDL) as predominant biomarkers of cirrhosis.

CONCLUSIONS

Our findings provide insight into the pathophysiology and metabolomics of experimental MASH and its relevance to human MASH. The observed upregulation of lipoprotein expression reveals a feedforward mechanism for MASH development that may be targeted for the development of noninvasive diagnosis.

Wild Edible Flowers of Western Himalayas: Nutritional Characterization, UHPLC-QTOF-IMS-Based Phytochemical Profiling, Antioxidant Properties, and In Vitro Bioaccessibility of Polyphenols

Four edible flowers commonly consumed in the Western Himalayan region, namely, Bauhinia variegata (Kachnar), Tropaeolum majus (Nasturtium), Matricaria chamomilla (Chamomile), and Tagetes erecta (Marigold), were characterized for their nutritional and phytochemical composition. Through the UHPLC-QTOF-IMS-based metabolomics approach, 131 compounds were tentatively identified consisting of phenolic acids, flavonoid glycosides, terpenoids, amino acids, and fatty acid derivatives. Kaempferol and quercetin glycosides for Kachnar, apigenin glycosides and caffeoylquinic acid derivatives for Chamomile, patulin and quercetin derivatives for Marigold, cyanidin and delphinidin glycosides for Nasturtium were the predicted marker metabolites identified through non-targeted metabolomics. Kachnar and Chamomile scored best in terms of macronutrients and essential micronutrients, respectively. Nasturtium contained high concentrations of α-linolenic acid, anthocyanins, and lutein. Kachnar contained the highest total phenolic acids (63.36 ± 0.38 mg GAE g-1), while Marigold contained the highest total flavonoids (118.90 ± 1.30 mg QUE g-1). Marigolds possessed excellent free radical scavenging and metal chelation activities. Chamomile exhibited strong α-glucosidase inhibition activity, followed by Nasturtium. The in vitro gastrointestinal digestibility of flower extracts indicated that the bioaccessibility of phenolic acids was higher than that of flavonoids. Polyphenols from Nasturtium and Chamomile showed the highest bioaccessibility. The study is an attempt to characterize traditionally consumed edible flowers and promote their wider utilization in gastronomy and nutraceuticals.

PANOMICS at the interface of root-soil microbiome and BNI

Nitrification and denitrification are soil biological processes responsible for large nitrogen losses from agricultural soils and generation of the greenhouse gas (GHG) N₂O. Increased use of nitrogen fertilizer and the resulting decline in nitrogen use efficiency (NUE) are a major concern in agroecosystems. This nitrogen cycle in the rhizosphere is influenced by an intimate soil microbiome-root exudate interaction and biological nitrification inhibition (BNI). A PANOMICS approach can dissect these processes. We review breakthroughs in this area, including identification and characterization of root exudates by metabolomics and proteomics, which facilitate better understanding of belowground chemical communications and help identify new biological nitrification inhibitors (BNIs). We also address challenges for advancing the understanding of the role root exudates play in biotic and abiotic stresses.

Sensory and metabolite migration from tilapia skin to soup during the boiling process: fast and then slow

This study mainly studied sensory and metabolite migration from the skin to the soup in the boiling process of tilapia skin using content analysis, electronic nose technique, electronic tongue technique, and metabolomics technique based on ultra-high performance liquid chromatography-mass spectrometry/mass spectrometry and gas chromatography-time-of-flight-mass spectrometry. The content changes, flavor changes, taste changes, metabolite numbers and differential metabolite numbers for both tilapia skin and soup mainly occurred in the initial 30 min. Moreover, the initial 10 min was the key period for the metabolite changes in the boiling process. Further, the differential metabolites in these three periods (0–10, 10–30, and 30–60 min) were identified to show the metabolites migration process. Six (adenine, gingerol, terephthalic acid, vanillin, pentanenitrile, and 2-pyrrolidinonede) and seven (butyramide, lysope(0:0/20:4(5z,8z,11z,14z)), lysope(22:6(4z,7z,10z,13z,16z,19z)/0:0), linoleic acid, N-acetylneuraminic acid, L-threose, and benzoin) chemicals were screened out in the differential metabolites of tilapia skin and soup, respectively, with Variable Importance in the Projection of >1 and p value of <0.05. This work would be beneficial to understand the sensory and metabolite migration in the preparation process of fish soup and provided a metabolomic analysis route to analyze metabolites migration in food.

The use of ecological analytical tools as an unconventional approach for untargeted metabolomics data analysis: the case of Cecropia obtusifolia and its adaptive responses to nitrate starvation

Plant metabolomics studies haves revealed new bioactive compounds. However, like other omics disciplines, the generated data are not fully exploited, mainly because the commonly performed analyses focus on elucidating the presence/absence of distinctive metabolites (and/or their precursors) and not on providing a holistic view of metabolomic changes and their participation in organismal adaptation to biotic and abiotic stress conditions. Therefore, spectral libraries generated from Cecropia obtusifolia cell suspension cultures in a previous study were considered as a case study and were reanalyzed herein. These libraries were obtained from a time-course experiment under nitrate starvation conditions using both electrospray ionization modes. The applied methodology included the use of ecological analytical tools in a systematic four-step process, including a population analysis of metabolite α diversity, richness, and evenness (i); a chemometrics analysis to identify discriminant groups (ii); differential metabolic marker identification (iii); and enrichment analyses and annotation of active metabolic pathways enriched by differential metabolites (iv). Our species α diversity results referring to the diversity of metabolites represented by mass-to-charge ratio (m/z) values detected at a specific retention time (rt) (an uncommon way to analyze untargeted metabolomic data) suggest that the metabolome is dynamic and is modulated by abiotic stress. A total of 147 and 371 m/z_rt pairs was identified as differential markers responsive to nitrate starvation in ESI^- and ESI⁺ modes, respectively. Subsequent enrichment analysis showed a high degree of completeness of biosynthetic pathways such as those of brassinosteroids, flavonoids, and phenylpropanoids.

Chemometric and sensometric techniques in enological data analysis

Enological evaluations capture the chemical and sensory space of wine using different techniques; many sensory methods as well as a variety of analytical chemistry techniques contribute to the amount of information generated. Data fusion, especially integrating data sets, is important when working with complex systems. The success reported when trying to integrate different modalities is generally low and has been attributed to the lack of statistically considerate strategies focusing on the data handling process. Multiple stages of data handling must be carefully considered when dealing with multi-modal data. In this review, the different stages in the data analysis process were examined. The study revealed misconceptions surrounding the process and elucidated rules for purpose-driven approaches by examining the complexities of each stage and the impact the decisions made at each stage have on the resulting models. The two major modeling approaches are either supervised (discrimination, classification, prediction) or unsupervised (exploration). Supervised approaches were emphatic on the pre-processing steps and prioritized increasing performance. Unsupervised approaches were mostly used for preliminary steps. The review found aspects often neglected when it came to the data collection and capturing which in the end contributed to the low success in combining sensory and chemistry data.

Targeted and Untargeted Mass Spectrometry-Based Metabolomics for Chemical Profiling of Three Coffee Species

While coffee beans have been studied for many years, researchers are showing a growing interest in coffee leaves and by-products, but little information is currently available on coffee species other than Coffea arabica and Coffea canephora. The aim of this work was to perform a targeted and untargeted metabolomics study on Coffea arabica, Coffea canephora and Coffea anthonyi. The application of the recent high-resolution mass spectrometry-based metabolomics tools allowed us to gain a clear overview of the main differences among the coffee species. The results showed that the leaves and fruits of Coffea anthonyi had a different metabolite profile when compared to the two other species. In Coffea anthonyi, caffeine levels were found in lower concentrations while caffeoylquinic acid and mangiferin-related compounds were found in higher concentrations. A large number of specialized metabolites can be found in Coffea anthonyi tissues, making this species a valid candidate for innovative healthcare products made with coffee extracts.

Metabolic Analysis of Schizochytrium Mutants With High DHA Content Achieved With ARTP Mutagenesis Combined With Iodoacetic Acid and Dehydroepiandrosterone Screening

High DHA production cost caused by low DHA titer and productivity of the current Schizochytrium strains is a bottleneck for its application in competition with traditional fish-oil based approach. In this study, atmospheric and room-temperature plasma with iodoacetic acid and dehydroepiandrosterone screening led to three mutants, 6–8, 6–16 and 6–23 all with increased growth and DHA accumulations. A LC/MS metabolomic analysis revealed the increased metabolism in PPP and EMP as well as the decreased TCA cycle might be relevant to the increased growth and DHA biosynthesis in the mutants. Finally, the mutant 6–23, which achieved the highest growth and DHA accumulation among all mutants, was evaluated in a 5 L fermentor. The results showed that the DHA concentration and productivity in mutant 6–23 were 41.4 g/L and 430.7 mg/L/h in fermentation for 96 h, respectively, which is the highest reported so far in literature. The study provides a novel strain improvement strategy for DHA-producing Schizochytrium.

Bean cultivars (Phaseolus vulgaris L.) under the spotlight of NMR metabolomics

The seeds of Phaseolus vulgaris are a rich source of protein consumed around the world and are considered as the most important source of proteins and antioxidants in the Mexican diet. This work reports on the 1H NMR metabolomics profiling of the cultivars Peruano (FPe), Pinto (FPi), Flor de mayo (FM), Negro (FN) and Flor de junio (FJ). Total phenolics, total flavonoids and total protein contents were determined to complement the nutritional facts in seeds and leaves. According to our results, the metabolomics fingerprint of beans seeds and leaves were very similar, showing the presence of 52 metabolites, 46 in seeds and 48 in leaves, including 8 sugars, 17 amino acids, 15 organic acids, 5 nucleosides and 7 miscellaneous compounds. In seeds, free amino acids were detected in higher concentrations than in the leaves, whereas organic acids were more abundant in leaves than in seeds. With multivariate and cluster analysis it was possible to rank the cultivars according to their nutritional properties according to NMR profiling, then a machine learning algorithm was used to reveal the most important differential metabolites which are the key for correct classification. The results coincide in highlighting the FN seeds and FPe leaves for the best nutritional facts. Finally, in terms of cultivars, FN and FM present the best nutritional properties, with high protein and flavonoids content, as well as, a high concentration of amino acids and nucleosides.

Investigation of the individual human sulfatome in plasma and urine samples reveals an age-dependency

Metabolic microbiome interaction with the human host has been linked to human physiology and disease development. The elucidation of this interspecies metabolite exchange will lead to identification of beneficial metabolites and disease modulators. Their discovery and quantitative analysis requires the development of specific tools and analysis of specific compound classes. Sulfated metabolites are considered a readout for the co-metabolism of the microbiome and their host. This compound class is part of the human phase II clearance process of xenobiotics and is the main focus in drug or doping metabolism and also includes dietary components and microbiome-derived compounds. Here, we report the targeted analysis of sulfated metabolites in plasma and urine samples in the same individuals to identify the core sulfatome and similarities between these two sample types. This analysis of 27 individuals led to the identification of the core sulfatome of 41 metabolites in plasma and urine samples as well as an age effect for 15 metabolites in both sample types.

Development of an Online Health Care Assessment for Preventive Medicine: A Machine Learning Approach

BACKGROUND

In the era of information explosion, the use of the internet to assist with clinical practice and diagnosis has become a cutting-edge area of research. The application of medical informatics allows patients to be aware of their clinical conditions, which may contribute toward the prevention of several chronic diseases and disorders.

OBJECTIVE

In this study, we applied machine learning techniques to construct a medical database system from electronic medical records (EMRs) of subjects who have undergone health examination. This system aims to provide online self-health evaluation to clinicians and patients worldwide, enabling personalized health and preventive health.

METHODS

We built a medical database system based on the literature, and data preprocessing and cleaning were performed for the database. We utilized both supervised and unsupervised machine learning technology to analyze the EMR data to establish prediction models. The models with EMR databases were then applied to the internet platform.

RESULTS

The validation data were used to validate the online diagnosis prediction system. The accuracy of the prediction model for metabolic syndrome reached 91%, and the area under the receiver operating characteristic (ROC) curve was 0.904 in this system. For chronic kidney disease, the prediction accuracy of the model reached 94.7%, and the area under the ROC curve (AUC) was 0.982. In addition, the system also provided disease diagnosis visualization via clustering, allowing users to check their outcome compared with those in the medical database, enabling increased awareness for a healthier lifestyle.

CONCLUSIONS

Our web-based health care machine learning system allowed users to access online diagnosis predictions and provided a health examination report. Users could understand and review their health status accordingly. In the future, we aim to connect hospitals worldwide with our platform, so that health care practitioners can make diagnoses or provide patient education to remote patients. This platform can increase the value of preventive medicine and telemedicine.

Fruit phytochemical composition and color parameters of 21 accessions of five Rosa species grown in North West Iran

BACKGROUND

The genus Rosa comprises economically important horticultural plants belonging to the family Rosaceae. Recently, the use of different Rosa species has increased owing to their multipurpose properties (ornamental, food and medicinal uses). In this study, 21 accessions of Rosa genotypes were compared for fruit phytochemical composition and color parameters.

RESULTS

The highest antioxidant activity (37.86 mg AAE g^-1 FW) and total phenolic (8.17 mg GAE g^-1 FW), total flavonoid (2.53 mg QUE g^-1 FW), total carotenoid (20.21 mg g^-1 FW) and ascorbic acid (84.27 mg g^-1 FW) contents were observed in G20 (R. canina), G8 (R. canina), G9 (R. canina), G5 (R. damascena) and G10 (R. moschata) respectively. Chlorogenic acid and gallic acid were found as the main phenolic constituents of Rosa fruits. High amounts of apigenin, rutin, quercetin, p-coumaric acid, cinnamic acid, chlorogenic acid, caffeic acid and gallic acid were obtained in fruit extracts of G6, G14, G6, G8, G19, G9, G19 and G12 respectively. Moreover, the level of color parameters also varied among genotypes. The highest values of a*, b*, L* and chroma were obtained in G4 (R. canina). Based on hierarchical clustering analysis with heat-map, five groups of accessions were identified.

CONCLUSION

Different Rosa genotypes are rich in certain phytochemical compounds, with significant variations in their levels being observed. Hence evaluation of Rosa genetic resources can supply valuable data for screening accessions containing high levels of individual phenolics, antioxidants and other bioactive compounds for use in breeding programs and food and pharma industries. © 2019 Society of Chemical Industry.

Elucidating the interaction of kansui and licorice by comparative plasma/tissue metabolomics and a heatmap with relative fold change

Although compatibility is highly advocated in traditional Chinese medicine (TCM), inappropriate combination of some herbs may reduce the therapeutic action and even produce toxic effects. Kansui and licorice, one of TCM "Eighteen Incompatible Medicaments", are the most representative cases of improper herbal combination, which may still be applied simultaneously under given conditions. However, the potential mechanism of their compatibility and incompatibility is unclear. In the present study, two different ratios of kansui and licorice, representing their compatibility and incompatibility respectively, were designed to elucidate their interaction by comparative plasma/tissue metabolomics and a heatmap with relative fold change. As a result, glycocholic acid, prostaglandin F2a, dihydroceramide and sphinganine were screened out as the principal alternative biomarkers of compatibility group; sphinganine, dihydroceramide, arachidonic acid, leukotriene B4, acetoacetic acid and linoleic acid were those of incompatibility group. Based on the values of biomarkers in each tissue, the liver was identified as the compatible target organ, while the heart, liver, and kidney were the incompatible target organs. Furthermore, important pathways for compatibility and incompatibility were also constructed. These results help us to better understand and utilize the two herbs, and the study was the first to reveal some innate characters of herbs related to TCM "Eighteen Incompatible Medicaments".

Determination of metabolites of Geotrichum citri-aurantii treated with peppermint oil using liquid chromatography-mass spectrometry and gas chromatography-mass spectrometry

Sour rot is a leading disease of citrus fruit caused by the postharvest pathogen Geotrichum citri-aurantii. It has been reported that essential oils can be used as substitutes for synthetic fungicides to control the pathogen. In this study, changes in metabolites and antifungal effects of G. citri-aurantii treated with peppermint oil (PO) were investigated. The inhibition rate of the mycelial growth increased as the PO concentration increased, and 6 μl PO/disk resulted in a radial growth inhibition of 79.2%. The electrical conductivity of G. citri-aurantii treated with PO increased compared to the control. By comparing the metabolic profiles of treated and untreated G. citri-aurantii cells, a total of 53 distinct metabolites 9 were up-regulated and 44 were down-regulated were found, including 16 lipid metabolites, 6 carbohydrate metabolites, 2 amino acid metabolites, 5 alcohols, 2 glycoside metabolites, and 3 ketone metabolites, etc, and these metabolites are involved in 25 major metabolic pathways. PRACTICAL APPLICATIONS: Chemical fungicides can effectively control G. citri-aurantii during fruit postharvest period. However, synthetic chemical fungicides have gradually led to buildup of resistance of fungil, which seriously causes the frequent of food-borne diseases. PO extracted from natural plants can be used as natural additive in many foods due to their antioxidant, antibacterial, and antifungal properties. Therefore, PO can be considered as a promising bacteriostatic agent for the defense of G. citri-aurantii during fruit postharvest period.

Metabolomics of Solanum lycopersicum Infected with Phytophthora infestans Leads to Early Detection of Late Blight in Asymptomatic Plants

Tomato crops suffer attacks of various pathogens that cause large production losses. Late blight caused by Phytophthora infestans is a devastating disease in tomatoes because of its difficultly to control. Here, we applied metabolomics based on liquid chromatography⁻mass spectrometry (LC-MS) and metabolic profiling by matrix-assisted laser desorption ionization mass spectrometry (MALDI-MS) in combination with multivariate data analysis in the early detection of late blight on asymptomatic tomato plants and to discriminate infection times of 4, 12, 24, 36, 48, 60, 72 and 96 h after inoculation (hpi). MALDI-MS and LC-MS profiles of metabolites combined with multivariate data analysis are able to detect early-late blight-infected tomato plants, and metabolomics based on LC-MS discriminates infection times in asymptomatic plants. We found the metabolite tomatidine as an important biomarker of infection, saponins as early infection metabolite markers and isocoumarin as early and late asymptomatic infection marker along the post infection time. MALDI-MS and LC-MS analysis can therefore be used as a rapid and effective method for the early detection of late blight-infected tomato plants, offering a suitable tool to guide the correct management and application of sanitary defense approaches. LC-MS analysis also appears to be a suitable tool for identifying major metabolites of asymptomatic late blight-infected tomato plants.

A Metabolomic and HPLC-MS/MS Analysis of the Foliar Phenolics, Flavonoids and Coumarins of the Fraxinus Species Resistant and Susceptible to Emerald Ash Borer

The Emerald Ash Borer (EAB), Agrilus planipennis, Fairmaire, an Asian invasive alien buprestid has devastated tens of millions of ash trees (Fraxinus spp.) in North America. Foliar phytochemicals of the genus Fraxinus (Oleaceae): Fraxinus pennsylvanica (Green ash), F. americana (White ash), F. profunda (Bush) Bush. (Pumpkin ash), F. quadrangulata Michx. (Blue ash), F. nigra Marsh. (Black ash) and F. mandshurica (Manchurian ash) were investigated using HPLC-MS/MS and untargeted metabolomics. HPLC-MS/MS help identified 26 compounds, including phenolics, flavonoids and coumarins in varying amounts. Hydroxycoumarins, esculetin, esculin, fraxetin, fraxin, fraxidin and scopoletin were isolated from blue, black and Manchurian ashes. High-throughput metabolomics revealed 35 metabolites, including terpenes, secoiridoids and lignans. Metabolomic profiling indicated several upregulated putative compounds from Manchurian ash, especially fraxinol, ligstroside, oleuropin, matairesinol, pinoresinol glucoside, 8-hydroxypinoresinol-4-glucoside, verbenalin, hydroxytyrosol-1-O-glucoside, totarol and ar-artemisene. Further, dicyclomine, aphidicolin, parthenolide, famciclovir, ar-turmerone and myriocin were identified upregulated in blue ash. Principal component analysis demonstrated a clear separation between Manchurian and blue ashes from black, green, white and pumpkin ashes. The presence of defensive compounds upregulated in Manchurian ash, suggests their potential role in providing constitutive resistance to EAB, and reflects its co-evolutionary history with A. planipennis, where they appear to coexist in their native habitats.

Antioxidant Activity of the Lignins Derived from Fluidized-Bed Fast Pyrolysis

A challenge in recent years has been the rational use of forest and agriculture residues for the production of bio-fuel, biochemical, and other bioproducts. In this study, potentially useful compounds from pyrolytic lignins were identified by HPLC-MS/MS and untargeted metabolomics. The metabolites identified were 2-(4-allyl-2-methoxyphenoxy)-1-(4-hydroxy-3-methoxyphenyl)-1-propanol, benzyl benzoate, fisetinidol, phenyllactic acid, 2-phenylpropionic acid, 6,3′-dimethoxyflavone, and vanillin. The 2,2-diphenyl-1-picrylhydrazyl radical scavenging activity (DPPH), trolox equivalent antioxidant capacity (TEAC), and total phenolics content (TPC) per gram of pyrolytic lignin ranged from 14 to 503 mg ascorbic acid equivalents, 35 to 277 mg trolox equivalents, and 0.42 to 50 mg gallic acid equivalents, respectively. A very significant correlation was observed between the DPPH and TPC (r = 0.8663, p ≤ 0.0001), TEAC and TPC (r = 0.8044, p ≤ 0.0001), and DPPH and TEAC (r = 0.8851, p ≤ 0.0001). The polyphenolic compounds in the pyrolytic lignins which are responsible for radical scavenging activity and antioxidant properties can be readily profiled with HPLC-MS/MS combined with untargeted metabolomics. The results also suggest that DPPH, TEAC, and TPC assays are suitable methods for the measurement of antioxidant activity in a variety of pyrolytic lignins. These data show that the pyrolytic lignins can be considered as promising sources of natural antioxidants and value-added chemicals.

PRODIGEN: visualizing the probability landscape of stochastic gene regulatory networks in state and time space

Background

Visualizing the complex probability landscape of stochastic gene regulatory networks can further biologists’ understanding of phenotypic behavior associated with specific genes.

Results

We present PRODIGEN (PRObability DIstribution of GEne Networks), a web-based visual analysis tool for the systematic exploration of probability distributions over simulation time and state space in such networks. PRODIGEN was designed in collaboration with bioinformaticians who research stochastic gene networks. The analysis tool combines in a novel way existing, expanded, and new visual encodings to capture the time-varying characteristics of probability distributions: spaghetti plots over one dimensional projection, heatmaps of distributions over 2D projections, enhanced with overlaid time curves to display temporal changes, and novel individual glyphs of state information corresponding to particular peaks.

Conclusions

We demonstrate the effectiveness of the tool through two case studies on the computed probabilistic landscape of a gene regulatory network and of a toggle-switch network. Domain expert feedback indicates that our visual approach can help biologists: 1) visualize probabilities of stable states, 2) explore the temporal probability distributions, and 3) discover small peaks in the probability landscape that have potential relation to specific diseases.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-016-1447-1) contains supplementary material, which is available to authorized users.

Metabolomics in the Rhizosphere: Tapping into Belowground Chemical Communication

The rhizosphere is densely populated with a variety of organisms. Interactions between roots and rhizosphere community members are mostly achieved via chemical communication. Root exudates contain an array of primary and secondary plant metabolites that can attract, deter, or kill belowground insect herbivores, nematodes, and microbes, and inhibit competing plants. Metabolomics of root exudates can potentially help us to better understand this chemical dialogue. The main limitations are the proper sampling of the exudate, the sensitivity of the metabolomics platforms, and the multivariate data analysis to identify causal relations. Novel technologies may help to generate a spatially explicit metabolome of the root and its exudates at a scale that is relevant for the rhizosphere community.