Motivation: RNA-seq techniques generate massive amounts of expression data. Several pipelines (e.g. Tophat and Cufflinks) are broadly applied to analyse these datasets. However, accessing and handling the analytical output remain challenging for non-experts. Results: We present the RNASeqExpressionBrowser, an open-source web interface that can be used to access the output from RNA-seq expression analysis packages in different ways, as it allows browsing for genes by identifiers, annotations or sequence similarity. Gene expression information can be loaded as long as it is represented in a matrix-like format. Additionally, data can be made available by setting up the tool on a public server. For demonstration purposes, we have set up a version providing expression information from the barley genome. Availability and implementation: The source code and a show case are accessible at http://mips.helmholtz-muenchen.de/plant/RNASeqExpressionBrowser/. Contact: k.mayer@helmholtz-muenchen.de

Among all nephropathies, diabetic kidney disease (DKD) is the most common cause of kidney impairment advancement to end-stage renal disease (ESRD). Although DKD has no cure, the disease is commonly managed by strict control of blood glucose and blood pressure, and in most of these cases, kidney function often deteriorates, resulting in dialysis, kidney replacement therapy, and high mortality. The difficulties in finding a cure for DKD are mainly due to a poor understanding of the underpinning complex cellular mechanisms that could be identified as druggable targets for the treatment of this disease. The review is thus aimed at giving insight into the interconnection between chronic hyperglycaemia and cellular mechanistic perturbations of nephropathy in diabetes. A comprehensive literature review of observational studies on DKD published within the past ten years, with 57 percent published within the past three years was carried out. The article search focused on original research studies and reviews published in English. The articles were explored using Google Scholar, Medline, Web of Science, and PubMed databases based on keywords, titles, and abstracts related to the topic. This article provides a detailed relationship between hyperglycaemia, oxidative stress, and various cellular mechanisms that underlie the onset and progression of the disease. Moreover, it also shows how these mechanisms affect organelle dysfunction, resulting in fibrosis and podocyte impairment. The advances in understanding the complexity of DKD mechanisms discussed in this review will expedite opportunities to develop new interventions for treating the disease.

Obesity plays an important role in the development of insulin resistance and diabetes, but the molecular mechanism that links obesity and diabetes is still not completely understood. Here, we used 146 targeted metabolomic profiles from the German KORA FF4 cohort consisting of 1715 participants and associated them with obesity and type 2 diabetes. In the basic model, 83 and 51 metabolites were significantly associated with body mass index (BMI) and T2D, respectively. Those metabolites are branched-chain amino acids, acylcarnitines, lysophospholipids, or phosphatidylcholines. In the full model, 42 and 3 metabolites were significantly associated with BMI and T2D, respectively, and replicate findings in the previous studies. Sobel mediation testing suggests that the effect of BMI on T2D might be mediated via lipids such as sphingomyelin (SM) C16:1, SM C18:1 and diacylphosphatidylcholine (PC aa) C38:3. Moreover, mendelian randomization suggests a causal relationship that BMI causes the change of SM C16:1 and PC aa C38:3, and the change of SM C16:1, SM C18:1, and PC aa C38:3 contribute to T2D incident. Biological pathway analysis in combination with genetics and mice experiments indicate that downregulation of sphingolipid or upregulation of phosphatidylcholine metabolism is a causal factor in early-stage T2D pathophysiology. Our findings indicate that metabolites like SM C16:1, SM C18:1, and PC aa C38:3 mediate the effect of BMI on T2D and elucidate their role in obesity related T2D pathologies.

Aims/hypothesis: Type 2 diabetes is a chronic condition that is caused by hyperglycaemia. Our aim was to characterise the metabolomics to find their association with the glycaemic spectrum and find a causal relationship between metabolites and type 2 diabetes. Methods: As part of the Innovative Medicines Initiative - Diabetes Research on Patient Stratification (IMI-DIRECT) consortium, 3000 plasma samples were measured with the Biocrates AbsoluteIDQ p150 Kit and Metabolon analytics. A total of 911 metabolites (132 targeted metabolomics, 779 untargeted metabolomics) passed the quality control. Multivariable linear and logistic regression analysis estimates were calculated from the concentration/peak areas of each metabolite as an explanatory variable and the glycaemic status as a dependent variable. This analysis was adjusted for age, sex, BMI, study centre in the basic model, and additionally for alcohol, smoking, BP, fasting HDL-cholesterol and fasting triacylglycerol in the full model. Statistical significance was Bonferroni corrected throughout. Beyond associations, we investigated the mediation effect and causal effects for which causal mediation test and two-sample Mendelian randomisation (2SMR) methods were used, respectively. Results: In the targeted metabolomics, we observed four (15), 34 (99) and 50 (108) metabolites (number of metabolites observed in untargeted metabolomics appear in parentheses) that were significantly different when comparing normal glucose regulation vs impaired glucose regulation/prediabetes, normal glucose regulation vs type 2 diabetes, and impaired glucose regulation vs type 2 diabetes, respectively. Significant metabolites were mainly branched-chain amino acids (BCAAs), with some derivatised BCAAs, lipids, xenobiotics and a few unknowns. Metabolites such as lysophosphatidylcholine a C17:0, sum of hexoses, amino acids from BCAA metabolism (including leucine, isoleucine, valine, N-lactoylvaline, N-lactoylleucine and formiminoglutamate) and lactate, as well as an unknown metabolite (X-24295), were associated with HbA_1c progression rate and were significant mediators of type 2 diabetes from baseline to 18 and 48 months of follow-up. 2SMR was used to estimate the causal effect of an exposure on an outcome using summary statistics from UK Biobank genome-wide association studies. We found that type 2 diabetes had a causal effect on the levels of three metabolites (hexose, glutamate and caproate [fatty acid (FA) 6:0]), whereas lipids such as specific phosphatidylcholines (PCs) (namely PC aa C36:2, PC aa C36:5, PC ae C36:3 and PC ae C34:3) as well as the two n-3 fatty acids stearidonate (18:4n3) and docosapentaenoate (22:5n3) potentially had a causal role in the development of type 2 diabetes. Conclusions/interpretation: Our findings identify known BCAAs and lipids, along with novel N-lactoyl-amino acid metabolites, significantly associated with prediabetes and diabetes, that mediate the effect of diabetes from baseline to follow-up (18 and 48 months). Causal inference using genetic variants shows the role of lipid metabolism and n-3 fatty acids as being causal for metabolite-to-type 2 diabetes whereas the sum of hexoses is causal for type 2 diabetes-to-metabolite. Identified metabolite markers are useful for stratifying individuals based on their risk progression and should enable targeted interventions. Graphical

Cultivated carrot is one of the most important vegetable plants in the world and favored by consumers for its typically sweet flavor. Unfortunately, the attractive sensory quality is hindered by a sporadic bitter off-taste. To evaluate the influence of the abiotic stress conditions, waterlogging and drought, on the bitter sensometabolome as well as agronomical traits of six genotypes of Daucus carota, a field trial was performed. Enabling the accurate tracing of carrots’ bitter compounds and therefore their metabolic changes, a fast and robust high-throughput UHPLC-MS/MS was developed and validated. Remarkably, the genotypes are the driving source for the biological fate of the bitter metabolites that are reflected in concentrations, dose-over-threshold factors, and fold changes. A certain influence of the irrigation level is observable but is overruled by its cultivar. Therefore, metabolic stress response in carrots seems to be genotype dependent. Hence, this study might help to plant specific carrot genotypes that are adapted to stress conditions evoked by future climatic changes.

Summary: Arbuscular mycorrhiza (AM) improves mineral nutrient supply, stress tolerance, and growth of host plants through re‐programing of plant physiology. We investigated the effect of AM on the root secondary metabolome of the model legume Lotus japonicus using untargeted metabolomics. Acetonitrile extracts of AM and control roots were analysed using ultra‐high‐performance liquid chromatography‐electrospray ionization‐ion mobility‐time‐of‐flight‐mass spectrometry (UPLC‐ESI‐IM‐ToF‐MS). We characterized AM‐regulated metabolites using co‐chromatography with authentic standards or isolation and structure identification from L. japonicus roots using preparative high‐performance liquid chromatography and nuclear magnetic resonance spectroscopy. Arbuscular mycorrhiza triggered major changes in the root metabolome, with most features representing unknown compounds. We identified three novel polyphenols: 5,7‐dihydroxy‐4′‐methoxycoumaronochromone (lotuschromone), 4‐hydroxy‐2‐(2′‐hydroxy‐4′‐methoxyphenyl)‐6‐methoxybenzofuran‐3‐carbaldehyde (lotusaldehyde), and 7‐hydroxy‐3,9‐dimethoxypterocarp‐6a‐ene (lotuscarpene). Further AM‐enhanced secondary metabolites included the previously known lupinalbin A and B, ayamenin D, biochanin A, vestitol, acacetin, coumestrol, and betulinic acid. Lupinalbin A, biochanin A, ayamenin D, liquiritigenin, isoliquiritigenin, lotuscarpene, medicarpin, daidzein, genistein, and 2′‐hydroxygenistein inhibited Rhizophagus irregularis spore germination upon direct application. Our results show that AM enhances the production of polyphenols in L. japonicus roots and highlights a treasure trove of numerous unknown plant secondary metabolites awaiting structural identification and functional characterization.