Mass spectrometry (MS) offers unrivalled sensitivity for the metabolite profiling of complex biological matrices encountered in natural products (NP) research. The massive and complex sets of spectral data generated by such platforms require computational approaches for their interpretation. Within such approaches, computational metabolite annotation automatically links spectral data to candidate structures via a score, which is usually established between the acquired data and experimental or theoretical spectral databases (DB). This process leads to various candidate structures for each MS features. However, at this stage, obtaining high annotation confidence level remains a challenge notably due to the extensive chemodiversity of specialized metabolomes. The design of a metascore is a way to capture complementary experimental attributes and improve the annotation process. Here, we show that integrating the taxonomic position of the biological source of the analyzed samples and candidate structures enhances confidence in metabolite annotation. A script is proposed to automatically input such information at various granularity levels (species, genus, and family) and complement the score obtained between experimental spectral data and output of available computational metabolite annotation tools (ISDB-DNP, MS-Finder, Sirius). In all cases, the consideration of the taxonomic distance allowed an efficient re-ranking of the candidate structures leading to a systematic enhancement of the recall and precision rates of the tools (1.5- to 7-fold increase in the F1 score). Our results clearly demonstrate the importance of considering taxonomic information in the process of specialized metabolites annotation. This requires to access structural data systematically documented with biological origin, both for new and previously reported NPs. In this respect, the establishment of an open structural DB of specialized metabolites and their associated metadata, particularly biological sources, is timely and critical for the NP research community.

Plant specialized metabolites play an important role in soil carbon (C) and nutrient fluxes. Through anti-microbial effects, they can modulate microbial assemblages and associated microbial-driven processes, such as nutrient cycling, so to positively or negatively cascade on plant fitness. As such, plant specialized metabolites can be used as a tool to supplant competitors. These compounds are little studied in bryophytes. This is especially notable in peatlands where Sphagnum mosses can dominate the vegetation and show strong interspecific competition. Sphagnum mosses form carpets where diverse microbial communities live and play a crucial role in Sphagnum fitness by regulating C and nutrient cycling. Here, by means of a microcosm experiment, we assessed to what extent moss metabolites of two Sphagnum species (S. fallax and S. divinum) modulate the competitive Sphagnum microbiome, with particular focus on microbial respiration. Using a reciprocal leachate experiment, we found that interactions between Sphagnum leachates and microbiome are species-specific. We show that both Sphagnum leachates differed in compound richness and compound relative abundance, especially sphagnum acid derivates, and that they include microbial-related metabolites. The addition of S. divinum leachate on the S. fallax microbiome immediately reduced microbial respiration (−95%). Prolonged exposition of S. fallax microbiome to S. divinum leachate destabilized the food web structure due to a modulation of microbial abundance. In particular, leachate addition decreased the biomass of testate amoebae and rotifers but increased that of ciliates. These changes did not influence microbial CO2 respiration, suggesting that the structural plasticity of the food web leads to its functional resistance through the replacement of species that are functionally redundant. In contrast, S. fallax leachate neither affected S. divinum microbial respiration, nor microbial biomass. We, however, found that S. fallax leachate addition stabilized the food web structure associated to S. divinum by changing trophic interactions among species. The differences in allelopathic effects between both Sphagnum leachates might impact their competitiveness and affect species distribution at local scale. Our study further paves the way to better understand the role of moss and microbial specialized metabolites in peatland C dynamics.

25 Mass spectrometry (MS) hyphenated to liquid chromatography (LC)-MS offers unrivalled sensitivity 26 for metabolite profiling of complex biological matrices encountered in natural products (NP) research. 27 With advanced platforms LC, MS/MS spectra are acquired in an untargeted manner on most detected 28 features. This generates massive and complex sets of spectral data that provide valuable structural 29 information on most analytes. To interpret such datasets, computational methods are mandatory. To 30 this extent, computerized annotation of metabolites links spectral data to candidate structures. When 31 profiling complex extracts spectra are often organized in clusters by similarity via Molecular 32 Networking (MN). A spectral matching score is usually established between the acquired data and 33 experimental or theoretical spectral databases (DB). The process leads to various candidate structures 34 for each MS features. At this stage, obtaining high annotation confidence level remains a challenge 35 notably due to the high chemodiversity of specialized metabolomes. 36