Metabotyping of Andean pseudocereals and characterization of emerging mycotoxins

Abstract

Pseudocereals are best known for three crops derived from the Andes: quinoa (Chenopodium quinoa, Chenopods I), canihua (C. pallidicaule, Chenopods I), and kiwicha (Amaranthus caudatus). Their grains are recognized for their nutritional benefits; however, there is a higher level of polyphenism and the chemical foundation that would rely with such polyphenism has not been thoroughly investigated. Meanwhile, the chemical food safety of pseudocereals remains poorly documented. Here we applied untargeted and targeted metabolomics approach by LC-MS to achieve both: i) a comprehensive chemical mapping of pseudocereal samples collected in the Andes to classify them according to their chemotype; ii) a quantification of their contents in emerging mycotoxins. An inventory of the fungal community was also realized with the aims to better know the filamentous fungi present in these grains and try to parallel this information with the presence of the molecules produced, especially mycotoxins. Metabotyping permitted to add new insights into the chemotaxonomy of pseudocereals, confirming the previously established phylotranscriptomic clades: Chenopods I (clusters quinoa and canihua), and Amaranthaceae s.s. (cluster kiwicha). Moreover, we report for the first time the presence of mycotoxins in pseudocereals. Sixteen samples of Peru (out of 27) and one sample from France (out of one) were contaminated with Beauvericin, an emerging mycotoxin. There were several mycotoxigenic fungi detected, including Aspergillus sp., Penicillium sp., and Alternaria sp., but not Fusaria.

Biodereplication of Antiplasmodial Extracts: Application of the Amazonian Medicinal Plant Piper coruscans Kunth

“…Peaks were aligned with an RT tolerance of 0.2 min, a mass tolerance of 0.015 Da, and a minimum peak height detection at 1 × 10 4 . MS-DIAL data were deconvoluted with MS-CleanR [ 73 ] by selecting all filters with a minimum blank ratio set to 0.8 and a maximum relative standard deviation (RSD) set to 40 as previously reported [ 74 , 75 ]. Two peaks were kept in each cluster for further database requests and the retained features were annotated with MS-FINDER version 3.52 [ 76 ].…”

Deciphering anti-infectious compounds from Peruvian medicinalCordoncillosextract library through multiplexed assays and chemical profiling

“…Metabolite annotation at level 2 was prioritized according to: i) a search would be made using MSFinder for a match with compounds identified in the literature for the Piper genus (genus level) and Piperaceae family (family level) (Dictionary of Natural Products version 28.2, CRC Press) based on exact mass and in silico fragmentation. For metabolite annotation level 3, a search was made using MS-FINDER for a match with natural compounds included in their databases embedded (PlantCyc, ChEBI, NANPDB, COCONUT, and KNApSAcK) (generic level) (Vásquez-Ocmín et al, 2022b).…”