Flavor is the main factor driving consumers acceptance of food products. However, tracking the biochemistry of flavor is a formidable challenge due to the complexity of food composition. Current methodologies for linking individual molecules to flavor in foods and beverages are expensive and time-consuming. Predictive models based on machine learning (ML) are emerging as an alternative to speed up this process. Nonetheless, the optimal approach to predict flavor features of molecules remains elusive. In this work we present FlavorMiner, an ML-based multilabel flavor predictor. FlavorMiner seamlessly integrates different combinations of algorithms and mathematical representations, augmented with class balance strategies to address the inherent class of the input dataset. Notably, Random Forest and K-Nearest Neighbors combined with Extended Connectivity Fingerprint and RDKit molecular descriptors consistently outperform other combinations in most cases. Resampling strategies surpass weight balance methods in mitigating bias associated with class imbalance. FlavorMiner exhibits remarkable accuracy, with an average ROC AUC score of 0.88. This algorithm was used to analyze cocoa metabolomics data, unveiling its profound potential to help extract valuable insights from intricate food metabolomics data. FlavorMiner can be used for flavor mining in any food product, drawing from a diverse training dataset that spans over 934 distinct food products.Scientific Contribution FlavorMiner is an advanced machine learning (ML)-based tool designed to predict molecular flavor features with high accuracy and efficiency, addressing the complexity of food metabolomics. By leveraging robust algorithmic combinations paired with mathematical representations FlavorMiner achieves high predictive performance. Applied to cocoa metabolomics, FlavorMiner demonstrated its capacity to extract meaningful insights, showcasing its versatility for flavor analysis across diverse food products. This study underscores the transformative potential of ML in accelerating flavor biochemistry research, offering a scalable solution for the food and beverage industry.

Mapping the chemical space of compounds to chemical structures remains a challenge in metabolomics. Despite the advancements in untargeted liquid chromatography-mass spectrometry (LC–MS) to achieve a high-throughput profile of metabolites from complex biological resources, only a small fraction of these metabolites can be annotated with confidence. Many novel computational methods and tools have been developed to enable chemical structure annotation to known and unknown compounds such as in silico generated spectra and molecular networking. Here, we present an automated and reproducible Metabolome Annotation Workflow (MAW) for untargeted metabolomics data to further facilitate and automate the complex annotation by combining tandem mass spectrometry (MS2) input data pre-processing, spectral and compound database matching with computational classification, and in silico annotation. MAW takes the LC-MS2 spectra as input and generates a list of putative candidates from spectral and compound databases. The databases are integrated via the R package Spectra and the metabolite annotation tool SIRIUS as part of the R segment of the workflow (MAW-R). The final candidate selection is performed using the cheminformatics tool RDKit in the Python segment (MAW-Py). Furthermore, each feature is assigned a chemical structure and can be imported to a chemical structure similarity network. MAW is following the FAIR (Findable, Accessible, Interoperable, Reusable) principles and has been made available as the docker images, maw-r and maw-py. The source code and documentation are available on GitHub (https://github.com/zmahnoor14/MAW). The performance of MAW is evaluated on two case studies. MAW can improve candidate ranking by integrating spectral databases with annotation tools like SIRIUS which contributes to an efficient candidate selection procedure. The results from MAW are also reproducible and traceable, compliant with the FAIR guidelines. Taken together, MAW could greatly facilitate automated metabolite characterization in diverse fields such as clinical metabolomics and natural product discovery.

Integrative taxonomy is a fundamental part of biodiversity and combines traditional morphology with additional methods such as DNA sequencing or biochemistry. Here, we aim to establish untargeted metabolomics for use in chemotaxonomy. We used three thallose liverwort species Riccia glauca, R. sorocarpa, and R. warnstorfii (order Marchantiales, Ricciaceae) with Lunularia cruciata (order Marchantiales, Lunulariacea) as an outgroup. Liquid chromatography high-resolution mass-spectrometry (UPLC/ESI-QTOF-MS) with data-dependent acquisition (DDA-MS) were integrated with DNA marker-based sequencing of the trnL-trnF region and high-resolution bioimaging. Our untargeted chemotaxonomy methodology enables us to distinguish taxa based on chemophenetic markers at different levels of complexity: (1) molecules, (2) compound classes, (3) compound superclasses, and (4) molecular descriptors. For the investigated Riccia species, we identified 71 chemophenetic markers at the molecular level, a characteristic composition in 21 compound classes, and 21 molecular descriptors largely indicating electron state, presence of chemical motifs, and hydrogen bonds. Our untargeted approach revealed many chemophenetic markers at different complexity levels that can provide more mechanistic insight into phylogenetic delimitation of species within a clade than genetic-based methods coupled with traditional morphology-based information. However, analytical and bioinformatics analysis methods still need to be better integrated to link the chemophenetic information at multiple scales.

12-Oxophytodienoate reductase is the enzyme involved in the biosynthesis of phytohormone jasmonates, which are considered to be the major regulators of plant tolerance to biotic challenges, especially necrotrophic pathogens. However, we observe compromised tolerance to the necrotrophic fungal pathogen Botrytis cinerea in transgenic hexaploid bread wheat and tetraploid emmer wheat plants overexpressing 12-OXOPHYTODIENOATE REDUCTASE-3 gene from Arabidopsis thaliana, while in Arabidopsis plants themselves, endogenously produced and exogenously applied jasmonates exert a strong protective effect against B. cinerea. Exogenous application of methyl jasmonate on hexaploid and tetraploid wheat leaves suppresses tolerance to B. cinerea and induces the formation of chlorotic damages. Exogenous treatment with methyl jasmonate in concentrations of 100 µM and higher causes leaf yellowing even in the absence of the pathogen, in agreement with findings on the role of jasmonates in the regulation of leaf senescence. Thereby, the present study demonstrates the negative role of the jasmonate system in hexaploid and tetraploid wheat tolerance to B. cinerea and reveals previously unknown jasmonate-mediated responses.

Bryophytes are prolific producers of unique, specialized metabolites that are not found in other plants. As many of these unique natural products are potentially interesting, for example, pharmacological use, variations in the production regarding ecological or environmental conditions have not often been investigated. Here, we investigate metabolic shifts in the epiphytic Radula complanata L. (Dumort) with regard to different environmental conditions and the type of phorophyte (host tree). Plant material was harvested from three different locations in Sweden, Germany, and Canada and subjected to untargeted liquid chromatography high-resolution mass-spectrometry (UPLC/ESI-QTOF-MS) and data-dependent acquisition (DDA-MS). Using multivariate statistics, variable selection methods, in silico compound identification, and compound classification, a large amount of variation (39%) in the metabolite profiles was attributed to the type of host tree and 25% to differences in environmental conditions. We identified 55 compounds to vary significantly depending on the host tree (36 on the family level) and 23 compounds to characterize R. complanata in different environments. Taken together, we found metabolic shifts mainly in primary metabolites that were associated with the drought response to different humidity levels. The metabolic shifts were highly specific to the host tree, including mostly specialized metabolites suggesting high levels of ecological interaction. As R. complanata is a widely distributed generalist species, we found it to flexibly adapt its metabolome according to different conditions. We found metabolic composition to also mirror the constitution of the habitat, which makes it interesting for conservation measures.

The leaves of the wild tomato Solanum galapagense harbor type-IV glandular trichomes (GT) that produce high levels of acylsugars (AS), conferring insect resistance. Conversely, domesticated tomatoes (S. lycopersicum) lack type-IV trichomes on the leaves of mature plants, preventing high AS production, thus rendering the plants more vulnerable to insect predation. We hypothesized that cultivated tomatoes engineered to harbor type-IV trichomes on the leaves of adult plants could be insect-resistant. We introgressed the genetic determinants controlling type-IV trichome development from S. galapagense into cv. Micro-Tom (MT) and created a line named “Galapagos-enhanced trichomes” (MT-Get). Mapping-by-sequencing revealed that five chromosomal regions of S. galapagense were present in MT-Get. Further genetic mapping showed that S. galapagense alleles in chromosomes 1, 2, and 3 were sufficient for the presence of type-IV trichomes on adult organs but at lower densities. Metabolic and gene expression analyses demonstrated that type-IV trichome density was not accompanied by the AS production and exudation in MT-Get. Although the plants produce a significant amount of acylsugars, those are still not enough to make them resistant to whiteflies. We demonstrate that type-IV glandular trichome development is insufficient for high AS accumulation. The results from our study provided additional insights into the steps necessary for breeding an insect-resistant tomato.

In vivo localization of proteins using fluorescence-based approaches by fusion of the protein of interest (POI) to a fluorescent protein is a cost- and time-effective tool to gain insights into its physiological function in a plant cell. Determining the proper localization, however, requires the co-expression of defined organelle markers (OM). Several marker sets are available but, so far, the procedure requires successful co-transformation of POI and OM into the same cell and/or several cloning steps. We developed a set of vectors containing markers for basic cell organelles that enables the insertion of the gene of interest (GOI) by a single cloning step using the Golden Gate cloning approach and resulting in POI–GFP fusions. The set includes markers for plasma membrane, tonoplast, nucleus, endoplasmic reticulum, Golgi apparatus, peroxisomes, plastids, and mitochondria, all labelled with mCherry. Most of them were derived from well-established marker sets, but those localized in plasma membrane and tonoplast were improved by using different proteins. The final vectors are usable for localization studies in isolated protoplasts and for transient transformation of leaves of Nicotiana benthamiana. Their functionality is demonstrated using two enzymes involved in biosynthesis of jasmonic acid and located in either plastids or peroxisomes.

The seed-to-seedling transition is a crucial step in the plant life cycle. The transition occurs at the end of seed germination and corresponds to the initiation of embryonic root growth. To improve our understanding of how a seed transforms into a seedling, we germinated the Pisum sativum L. seeds for 72 h and divided them into samples before and after radicle protrusion. Before radicle protrusion, seeds survived after drying and formed normally developed seedlings upon rehydration. Radicle protrusion increased the moisture content level in seed axes, and the accumulation of ROS first generated in the embryonic root and plumule. The water and oxidative status shift correlated with the desiccation tolerance loss. Then, we compared RNA sequencing-based transcriptomics in the embryonic axes isolated from pea seeds before and after radicle protrusion. We identified 24,184 differentially expressed genes during the transition to the post-germination stage. Among them, 2101 genes showed more prominent expression. They were related to primary and secondary metabolism, photosynthesis, biosynthesis of cell wall components, redox status, and responses to biotic stress. On the other hand, 415 genes showed significantly decreased expression, including the groups related to water deprivation (eight genes) and response to the ABA stimulus (fifteen genes). We assume that the water deprivation group, especially three genes also belonging to ABA stimulus (LTI65, LTP4, and HVA22E), may be crucial for the desiccation tolerance loss during a metabolic switch from seed to seedling. The latter is also accompanied by the suppression of ABA-related transcription factors ABI3, ABI4, and ABI5. Among them, HVA22E, ABI4, and ABI5 were highly conservative in functional domains and showed homologous sequences in different drought-tolerant species. These findings elaborate on the critical biochemical pathways and genes regulating seed-to-seedling transition.

Water avens (Geum rivale L.) is a common Rosaceae plant widely spread in Europe and North America. It is rich in biologically active natural products, some of which are promising as prospective pharmaceuticals. The extracts of water avens are well known for their triterpenoid metabolites and associated anti-inflammatory, antimicrobial and antioxidant activities. However, the polyphenolic profiles of G. rivale L. are still awaiting complete characterization. Accordingly, the contribution of its individual components to the antioxidant, antibacterial and neuroprotective activity of the extracts is still unknown. As this plant can be available on an industrial scale, a better knowledge of its properly-relevant constituents might give access to new highly-efficient pharmaceutical substances and functional products. Therefore, herein we comprehensively characterize the secondary metabolome of G. rivale by ESI-HR-MS, ESI-HR-MSn and NMR spectroscopy with a special emphasis on the polyphenolic composition of its aerial parts. Furthermore, a multilateral evaluation of the antioxidant, neuroprotective and antibacterial properties of the aqueous and ethyl acetate fractions of the total aqueous alcoholic extract as well as individual isolated polyphenols was accomplished. Altogether four phenolic acid derivatives (trigalloyl hexose, caffeoyl-hexoside malate, ellagic acid and ellagic acid pentoside), six flavonoids (three quercetin derivatives, kaempferol and three its derivatives and two isorhamnetin derivatives) and four tannins (HHDP-hexoside, proantocyanidin dimer, pedunculagin I and galloyl-bis-HHDP-hexose) were identified in this plant for the first time. The obtained aqueous and ethyl acetate fractions of the total extract as well as the isolated individual compounds showed pronounced antioxidant activity. In addition, a pronounced antibacterial activity against several strains was proved for the studied fractions (for ethyl acetate fraction the highest activity against E. coli АТСС 25922 and S. aureus strains ATCC 27853 and SG-511 (MIC 15.6 μg/mL) was observed; for aqueous fraction—against Staphylococcus aureus SG-511 (MIC 31.2 μg/mL)). However, the anti-neurodegenerative (neuroprotective) properties could not be found with the employed methods. However, the antibacterial activity of the fractions could not be associated with any of the isolated individual major phenolics (excepting 3-O-methylellagic acid). Thus, the aerial parts of water avens represent a promising source of polyphenolic compounds with antioxidant activity and therefrom derived human health benefits, although the single constituents isolated so far lack a dominant selectively bioactive constituent in the bioassays performed.

The chemical composition of the essential oils (EOs) of Stachys byzantina, S. hissarica and S. betoniciflora growing in Uzbekistan were determined, and their antioxidant and enzyme inhibitory activity were assessed. A gas chromatography-mass spectrometry (GC-MS) analysis revealed the presence of 143 metabolites accounting for 70.34, 76.78 and 88.63% of the total identified components of S. byzantina, S. hissarica and S. betoniciflora, respectively. Octadecanal (9.37%) was the most predominant in S. betoniciflora. However, n-butyl octadecenoate (4.92%) was the major volatile in S. byzantina. Benzaldehyde (5.01%) was present at a higher percentage in S. hissarica. A chemometric analysis revealed the ability of volatile profiling to discriminate between the studied Stachys species. The principal component analysis plot displayed a clear diversity of Stachys species where the octadecanal and benzaldehyde were the main discriminating markers. The antioxidant activity was evaluated in vitro using 2,2-diphenyl-1-picryl-hydrazyl (DPPH), 2,2-azino bis (3-ethylbenzothiazoline-6-sulphonic acid) (ABTS), cupric reducing antioxidant capacity (CUPRAC), ferric reducing power (FRAP), chelating and phosphomolybdenum (PBD). Moreover, the ability of the essential oils to inhibit both acetyl/butyrylcholinesterases (AChE and BChE), α-amylase, α-glucosidase and tyrosinase was assessed. The volatiles from S. hissarica exhibited the highest activity in both the ABTS (226.48 ± 1.75 mg Trolox equivalent (TE)/g oil) and FRAP (109.55 ± 3.24 mg TE/g oil) assays. However, S. betoniciflora displayed the strongest activity in the other assays (174.94 ± 0.20 mg TE/g oil for CUPRAC, 60.11 ± 0.36 mg EDTA equivalent (EDTAE)/g oil for chelating and 28.24 ± 1.00 (mmol TE/g oil) for PBD. Regarding the enzyme inhibitory activity, S. byzantina demonstrated the strongest AChE (5.64 ± 0.04 mg galantamine equivalent (GALAE)/g oil) and tyrosinase inhibitory (101.07 ± 0.60 mg kojic acid equivalent (KAE)/g) activity. The highest activity for BChE (11.18 ± 0.19 mg GALAE/g oil), amylase inhibition (0.76 ± 0.02 mmol acarbose equivalent (ACAE)/g oil) and glucosidase inhibition (24.11 ± 0.06 mmol ACAE/g oil) was observed in S. betoniciflora. These results showed that EOs of Stachys species could be used as antioxidant, hypoglycemic and skincare agents.