Molecular networking has become a key method to visualize and annotate the chemical space in non-targeted mass spectrometry data. We present Feature-Based Molecular Networking (FBMN) as an analysis method in the Global Natural Products Social Molecular Networking (GNPS) infrastructure that builds on chromatographic feature detection and alignment tools. The FBMN method brings quantitative analyses, isomeric resolution, including from ion-mobility spectrometry, into molecular networks.

1Molecular networking has become a key method used to visualize and annotate the chemical space in 2 non-targeted mass spectrometry-based experiments. However, distinguishing isomeric compounds and

Symbioses between plants and mycorrhizal fungi are ubiquitous in ecosystems and strengthen the plants' defense against aboveground herbivores. Here, we studied the underlying regulatory networks and biochemical mechanisms in leaves induced by ectomycorrhizae that modify herbivore interactions. Feeding damage and oviposition by the widespread poplar leaf beetle were reduced on the ectomycorrhizal hybrid poplar × Integration of transcriptomics, metabolomics, and volatile emission patterns via mass difference networks demonstrated changes in nitrogen allocation in the leaves of mycorrhizal poplars, down-regulation of phenolic pathways, and up-regulation of defensive systems, including protease inhibitors, chitinases, and aldoxime biosynthesis. Ectomycorrhizae had a systemic influence on jasmonate-related signaling transcripts. Our results suggest that ectomycorrhizae prime wounding responses and shift resources from constitutive phenol-based to specialized protective compounds. Consequently, symbiosis with ectomycorrhizal fungi enabled poplars to respond to leaf beetle feeding with a more effective arsenal of defense mechanisms compared with nonmycorrhizal poplars, thus demonstrating the importance of belowground plant-microbe associations in mitigating aboveground biotic stress.

Untargeted metabolomics experiments rely on spectral libraries for structure annotation, but, typically, only a small fraction of spectra can be matched. Previous in silico methods search in structure databases but cannot distinguish between correct and incorrect annotations. Here we introduce the COSMIC workflow that combines in silico structure database generation and annotation with a confidence score consisting of kernel density P value estimation and a support vector machine with enforced directionality of features. On diverse datasets, COSMIC annotates a substantial number of hits at low false discovery rates and outperforms spectral library search. To demonstrate that COSMIC can annotate structures never reported before, we annotated 12 natural bile acids. The annotation of nine structures was confirmed by manual evaluation and two structures using synthetic standards. In human samples, we annotated and manually validated 315 molecular structures currently absent from the Human Metabolome Database. Application of COSMIC to data from 17,400 metabolomics experiments led to 1,715 high-confidence structural annotations that were absent from spectral libraries.

A combinatory approach using metabolomics and gut microbiome analysis techniques was performed to unravel the nature and specificity of metabolic profiles related to gut ecology in obesity. This study focused on gut and liver metabolomics of two different mouse strains, the C57BL/6J (C57J) and the C57BL/6N (C57N) fed with high-fat diet (HFD) for 3 weeks, causing dietinduced obesity in C57N, but not in C57J mice. Furthermore, a 16S-ribosomal RNA comparative sequence analysis using 454 pyrosequencing detected significant differences between the microbiome of the two strains on phylum level for Firmicutes, Deferribacteres and Proteobacteria that propose an essential role of the microbiome in obesity susceptibility. Gut microbial and liver metabolomics were followed by a combinatory approach using Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS) and ultra performance liquid chromatography time of tlight MS/MS with subsequent multivariate statistical analysis, revealing distinctive host and microbial metabolome patterns between the C57J and the C57N strain. Many taurine-conjugated bile acids (TBAs) were significantly elevated in the cecum and decreased in liver samples from the C57J phenotype likely displaying different energy utilization behavior by the bacterial community and the host. Furthermore, several metabolite groups could specifically be associated with the C57N phenotype involving fatty acids, eicosanoids and urobilinoids. The mass differences based metabolite network approach enabled to extend the range of known metabolites to important bile acids (BAs) and novel taurine conjugates specific for both strains. In summary, our study showed clear alterations of the metabolome in the gastrointestinal tract and liver within a HFD-induced obesity mouse model in relation to the host-microbial nutritional adaptation.

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Preterm delivery (PTD) represents a major health problem that occurs in 1 in 10 births. The hypothesis of the present study was that the metabolic profile of different biological fluids, obtained from pregnant women during the second trimester of gestation, could allow useful correlations with pregnancy outcome. Holistic and targeted metabolomics approaches were applied for the complementary assessment of the metabolic content of prospectively collected amniotic fluid (AF) and paired maternal blood serum samples from 35 women who delivered preterm (between 29 weeks + 0 days and 36 weeks +5 days gestation) and 35 women delivered at term. The results revealed trends relating the metabolic content of the analyzed samples with preterm delivery. Untargeted and targeted profiling showed differentiations in certain key metabolites in the biological fluids of the two study groups. In AF, intermediate metabolites involved in energy metabolism (pyruvic acid, glutamic acid, and glutamine) were found to contribute to the classification of the two groups. In maternal serum, increased levels of lipids and alterations of key end-point metabolites were observed in cases of preterm delivery. Overall, the metabolic content of second-trimester AF and maternal blood serum shows potential for the identification of biomarkers related to fetal growth and preterm delivery.

Dietary restriction (DR) increases healthspan and longevity in many species, including primates, but it is often accompanied by impaired reproductive function. Whether signals associated with the reproductive system contribute to or are required for DR effects on lifespan has not been established. Here we show that expression of the cytochrome P450 DAF-9/CYP450 and production of the steroid hormone D 7 -dafachronic acid (DA) are increased in C. elegans subjected to DR. DA signalling through the non-canonical nuclear hormone receptor NHR-8/NHR and the nutrient-responsive kinase let-363/mTOR is essential for DR-mediated longevity. Steroid signalling also affects germline plasticity in response to nutrient deprivation and this is required to achieve lifespan extension. These data demonstrate that steroid signalling links germline physiology to lifespan when nutrients are limited, and establish a central role for let-363/mTOR in integrating signals derived from nutrients and steroid hormones.