Four new N-acylated aminoalkanoic acids, namely clonoroseins E-H (1-4), together with three previously identified analogs, clonoroseins A, B, and D (5-7), were identified from the endophytic fungus Clonostachys rosea strain 15020 (CR15020), using Feature-based Molecular Networking (FBMN). The elucidation of their chemical structures, including their absolute configurations, was achieved through spectroscopic analysis combined with quantum chemical calculations. Bioinformatics analyses suggested that an iterative type I HR-PKS (CrsE) generates the polyketide side chain of these clonoroseins. Furthermore, a downstream adenylate-forming enzyme of the PKS (CrsD) was suspected to function as an amide synthetase. CrsD potentially facilitates the transformation of the polyketide moiety into an acyl-AMP intermediate, followed by nucleophilic substitution with either β-alanine or γ-aminobutyric acid to produce amide derivatives. These findings significantly expand our understanding of PKS-related products originating from C. rosea and also underscore the powerful application of FBMN analytical methods in characterization of new compounds.

Characterization studies of the plant metabolome are crucial for revealing plant physiology, developing functional foods, and controlling quality. Mass spectrometry-based metabolite profiling allows unprecedented qualitative coverage of complex biological extract composition. However, the electrospray ionization used in metabolite profiling generates multiple artifactual signals for a single analyte, which makes it challenging to filter out redundant signals and organize the signals corresponding to abundant constituents. This study proposed a strategy integrating in-source fragments elimination, diagnostic ions recognition, and feature-based molecular networking (ISFE-DIR-FBMN) to simultaneously characterize cycloartane triterpenoids (CTs) from three medicinal Cimicifuga species. The results showed that 63.1 % of the measured ions were redundant. A total of 184 CTs were annotated, with 27.1 % being reported for the first time. It presents a promising approach to assess the composition of natural extracts, thus facilitating new ingredient registrations or natural-extracts-based drug discovery campaigns. Besides, chemometrics analysis of the three Cimicifuga species identified 32 species-specific markers, highlighting significant differences among them. The valuable information can enhance the sustainable utilization and further development of Cimicifuga resources. The codes involved in ISFE-DIR-FBMN are freely available on GitHub (https://github.com/LHJ-Group/ISFE-DIR-FBMN.git).

Branched fatty acid esters of hydroxy fatty acids (FAHFAs) represent trace lipids with significant natural biological functions. While exogenous FAHFAs have been extensively studied, research on FAHFAs in milk remains limited, constraining our grasp of their nutritional roles. This study introduces a non-targeted mass spectrometry approach combined with chemical networking of spectral fragmentation patterns to uncover FAHFAs. Through meticulous sample handling and comparisons of various data acquisition and processing modes, we validate the method\'s superiority, identifying twice as many FAHFAs compared to alternative techniques. This validated method was then applied to different milk samples, revealing 45 chemical signals associated with known and potential FAHFAs, alongside findings of 66 ceramide/hexosylceramide (Cer/HexCer), 48 phosphatidyl ethanolamine/lyso phosphatidyl ethanolamine (PE/LPE), 21 phosphatidylcholine/lysophosphatidylcholine (PC/LPC), 16 phosphatidylinositol (PI), 7 phosphatidylserine (PS), and 11 sphingomyelin (SM) compounds. This study expands our understanding of the FAHFA family in milk and provides a fast and convenient method for identifying FAHFAs.

Orange processing waste (OPW) generated by the processing of oranges, as well as other citrus fruits, is a major source of pectin in the market nowadays. The residues generated during the pectin extraction process may contain many phytochemicals, including flavonoids. We use state-of-the-art techniques such as liquid chromatography high-resolution mass spectrometry (LC-HRMS/MS) and feature-based molecular network (FBMN) to annotate the flavonoids in OPWs. In particular, four flavonoids, hesperidin, naringin, diosmin, and hesperetin were quantified in the samples by LC-TDQ-MS. In total, 32 flavonoids from different classes were annotated, of which 16 were polymethoxylated flavonoids, 13 were flavonoid glycosides and 3 were flavanone aglycones. The results showed that flavonoid glycosides remain in high concentrations in OPWs from pectin factories even after pectin extraction by harsh conditions. The results show an exciting opportunity to harness the untapped potential of pectin factory waste as a renewable source for the extraction of glycoside flavonoids.

The pile fermentation process of Fuzhuan brick tea is unique in that it involves preheating without the use of starter cultures. The detailed metabolite changes and their drivers during this procedure are not known. Characterizing these unknown changes that occur in the metabolites and microbes during pile fermentation of Fuzhuan brick tea is important for industrial modernization of this traditional fermented food. Using microbial DNA amplicon sequencing, mass spectrometry-based untargeted metabolomics, and feature-based molecular networking, we herein reveal that significant changes in the microbial community occur before changes in the metabolite profile. These changes were characterized by a decrease in Klebsiella and Aspergillus, alongside an increase in Bacillus and Eurotium. The decrease in lysophosphatidylcholines, unsaturated fatty acids, and some astringent flavan-3-ols and bitter amino acids, as well as the increase in some less astringent flavan-3-ols and sweet or umami amino acids, contributed importantly to the overall changes observed in the metabolite profile. The majority of these changes was caused by bacterial metabolism and the corresponding heat generated by it.

Epimedii Folium (EF), a commonly used herbal medicine to treat osteoporosis, has caused serious concern due to potential hepatotoxicity. Until now, its intrinsic hepatotoxic mechanism and hepatotoxic ingredients remain unclear. Here, a novel high-throughput approach was designed to investigate the intrinsic hepatotoxic of EF. High-content screen imaging (HCS) and biochemical tests were first performed to obtain the cytotoxicity parameter matrix of 17 batch EF samples. EF-treated alpha mouse liver 12 (AML12) cells showed increased reactive oxygen species (ROS), reduced glutathione (GSH) and mitochondrial membrane potential (MMP), and apoptosis and cholestasis were further observed. Network toxicology predicted that EF-triggered hepatotoxiciy was involved in transcription factor (TF) activity. The FXR expression, screened by a TF PCR array, exhibited down-regulation following EF extract administration. Moreover, EF inhibited bile acid (BA) metabolism pathway in an FXR-dependent manner. Pearson correlation between the cytotoxicity parameter matrix and quantification feature table obtained from UHPLC-QTOF data of EF suggested 7 prenylated flavonoids possessed potent hepatotoxicities and their cytotoxicity order was further summarized. The transcriptional repression effects of them on FXR were also verified. Collectively, our findings indicate that FXR is probably responsible for EF-induced hepatotoxicity and prenylated flavonoids may be a major class of hepatotoxic constituents in EF.

The complexity of natural ingredients and the diversity of preparations are the major obstacles to the quality evaluation of traditional Chinese medicines (TCMs). A more comprehensive characterization of herbal compounds using different types of chromatographic separation techniques and covering a diverse polarity range can help evaluate the quality of TCMs. In this study, we first proposed a comprehensive method for characterizing compounds derived from Imperatae Rhizoma by combining the complementary strengths of UPCC-QTOF-MS (ultra-performance convergence chromatography coupled with quadrupole-time of flight mass spectrometry) with UPLC-QTOF-MS (ultra-performance liquid chromatography coupled with quadrupole-time of flight mass spectrometry). The method based on the UNIFI scientific platform significantly shortened the analysis time and enabled a more comprehensive characterization of known and unreported compounds. Meanwhile, a feature-based molecular network (FBMN) was established on the Global Natural Product Social (GNPS) to infer potential compounds by rapidly classifying and visualizing these components. A total of 62 compounds in Imperatae Rhizoma were jointly characterizedand classified into six types. In comparison, the UPCC-QTOF-MS technology individually characterized 17 components, including lactones, phenols, aldehydes, phenylpropanoids, and small polar organic acids. The UPLC-QTOF-MS technology characterized 16 compounds mainly phenylpropionic acids, flavonoid glycosides, and chromone glycosides. Furthermore, three types of characteristic compounds could be well aggregated into an FBMN approach. Five possible potential new compounds were detected through the supplementary identification of GNPS and the correlation analysis of vicinal known compounds. The strategy was first applied to Imperatae Rhizoma and facilitated the characterization of a large quantity of data to provide comprehensive chemical composition results. This approach can be easily extended to the study of the material basis of other herbs or preparations in order to improve the accuracy of herb quality evaluation.

Phospholipids are small but critical lipids in milk. Conventional lipidomics is a powerful method for the analysis of lipids in milk. Although the number of lipidomics software has drastically increased over the past five years, reducing false positives and obtaining structurally accurate annotations of phospholipids remain a significant challenge. In this study, we developed a rapid and accurate method for measuring a wide spectrum of phospholipids in milk. The developed approach that employed information-dependent acquisition (IDA) mode and feature-based molecular networking has exhibited better performance on data processing and lipid annotation when compared with sequential window acquisition of all theoretical mass spectra (SWATH) and MS-DIAL. This validated method was further evaluated using three kinds of sheep milk. A total of 150 phospholipids were identified, including rarely reported phospholipids containing ethers or vinyl ethers. The result indicated that phospholipids could be used as potential markers to distinguish sheep milk from different varieties and origins. The experimental and computational methods provide a rapid and reliable method for the investigation of phospholipids in milk.

Understanding the microbial and chemical diversities, as well as what affects these diversities, is important for modern manufacturing of traditional fermented foods. In this work, Chinese dark teas (CDTs) that are traditional microbial fermented beverages with relatively high sample diversity were collected. Microbial DNA amplicon sequencing and mass spectrometry-based untargeted metabolomics show that the CDT microbial β diversity, as well as the nonvolatile chemical α and β diversities, is determined by the primary impact factors of geography and manufacturing procedures, in particular, latitude and pile fermentation after blending. A large number of metabolites sharing between CDTs and fungi were discovered by Feature-based Molecular Networking (FBMN) on the Global Natural Products Social Molecular Networking (GNPS) web platform. These molecules, such as prenylated cyclic dipeptides and B-vitamins, are functionally important for nutrition, biofunctions, and flavor. Molecular networking has revealed patterns in metabolite profiles on a chemical family level in addition to individual structures.

Fungi have developed a wide array of defense strategies to overcome mechanical injuries and pathogen infections. Recently, photoactivity has been discovered by showing that pigments isolated from Cortinarius uliginosus produce singlet oxygen under irradiation. To test if this phenomenon is limited to dermocyboid Cortinarii, six colourful Cortinarius species belonging to different classical subgenera (i.e., Dermocybe, Leprocybe, Myxacium, Phlegmacium, and Telamonia) were investigated. Fungal extracts were explored by the combination of in vitro photobiological methods, UHPLC coupled to high-resolution tandem mass spectrometry (UHPLC-HRMS2), feature-based molecular networking (FBMN), and metabolite dereplication techniques. The fungi C. rubrophyllus (Dermocybe) and C. xanthophyllus (Phlegmacium) exhibited promising photobiological activity in a low concentration range (1-7 µg/mL). Using UHPLC-HRMS2-based metabolomic tools, the underlying photoactive principle was investigated. Several monomeric and dimeric anthraquinones were annotated as compounds responsible for the photoactivity. Furthermore, the results showed that light-induced activity is not restricted to a single subgenus, but rather is a trait of Cortinarius species of different phylogenetic lineages and is linked to the presence of fungal anthraquinones. This study highlights the genus Cortinarius as a promising source for novel photopharmaceuticals. Additionally, we showed that putative dereplication of natural photosensitizers can be done by FBMN.