After the generation of the FBMN, the spectral annotation was done in the first instance with the automatic identification of all recorded MS 2 spectra against the public DBs of GNPS. This was followed by two independent in silico annotation strategies. The set was subjected to the taxonomically informed metabolite annotation pipeline (ISDB annotation followed by taxonomical reweighting ), using TimaR. The NPs in silico spectral DB used was based on the structures gathered in the LOTUS initiative (v 4.0) and the Dictionary of Natural Products (DNP). The set was also submitted to Sirius to obtain accurate MFs, and structural annotations through CSI: FingerID , followed the CANOPUS chemical class assignment. To ensure a minimum quality of all the putative identifications, the annotations were filtered and consolidated using one of the modules of Inventa 63 script according to each annotation pipeline. The GNPS annotations were filtered based on the ppm error, the number of shared peaks, the cosine score, and the ionization mode. The Sirius annotations were filtered based on the Zodiac and Confidence scores. Similarly, the chemical classes from CANOPUS were considered only if the Class confidence was higher than the established threshold (see Methods). According to the guidelines proposed by the Metabolomics Standards Initiative (MSI) , the annotation levels of the putative identities assigned to the data include MSI Level 2a for library-based annotations using GNPS , and MSI Level 3 for in silico annotation tools such as CSI:FingerID 40 , CANOPUS , and ISDB .