Application of Direct Analysis in Real Time Mass Spectrometry (DART-MS) for Identification of an Epiphytic Cyanobacterium,NostocSp

Tidy-Direct-to-MS: An Open-Source Data-Processing Pipeline for Direct Mass Spectrometry-Based Metabolomics Experiments

Direct-to-Mass Spectrometry and ambient ionization techniques can be used for biochemical fingerprinting in a fast way. Data processing is typically accomplished with vendor-provided software tools. Here, a novel, open-source functionality, entitled Tidy-Direct-to-MS, was developed for data processing of direct-to-MS data sets. It allows for fast and user-friendly processing using different modules for optional sample position detection and separation, mass-to-charge ratio drift detection and correction, consensus spectra calculation, and bracketing across sample positions as well as feature abundance calculation. The tool also provides functionality for the automated comparison of different sets of parameters, thereby assisting the user in the complex task of finding an optimal combination to maximize the total number of detected features while also checking for the detection of user-provided reference features. In addition, Tidy-Direct-to-MS has the capability for data quality review and subsequent data analysis, thereby simplifying the workflow of untargeted ambient MS-based metabolomics studies. Tidy-Direct-to-MS is implemented in the Python programming language as part of the TidyMS library and can thus be easily extended. Capabilities of Tidy-Direct-to-MS are showcased in a data set acquired in a marine metabolomics study reported in MetaboLights (MTBLS1198) using a transmission mode Direct Analysis in Real Time-Mass Spectrometry (TM-DART-MS)-based method.

A Snapshot, Using a Multi-Omic Approach, of the Metabolic Cross-Talk and the Dynamics of the Resident Microbiota in Ripening Cheese Inoculated with Listeria innocua

Raw milk cheeses harbor complex microbial communities. Some of these microorganisms are technologically essential, but undesirable microorganisms can also be present. While most of the microbial dynamics and cross-talking studies involving interaction between food-derived bacteria have been carried out on agar plates in laboratory-controlled conditions, the present study evaluated the modulation of the resident microbiota and the changes of metabolite production directly in ripening raw milk cheese inoculated with Listeria innocua strains. Using a proxy of the pathogenic Listeria monocytogenes, we aimed to establish the key microbiota players and chemical signals that characterize Latteria raw milk cheese over 60 days of ripening time. The microbiota of both the control and Listeria-inoculated cheeses was analyzed using 16S rRNA targeted amplicon sequencing, while direct analysis in real time mass spectrometry (DART-HRMS) was applied to investigate the differences in the metabolic profiles of the cheeses. The diversity analysis showed the same microbial diversity trend in both the control cheese and the inoculated cheese, while the taxonomic analysis highlighted the most representative genera of bacteria in both the control and inoculated cheese: Lactobacillus and Streptococcus. On the other hand, the metabolic fingerprints revealed that the complex interactions between resident microbiota and L. innocua were governed by continuously changing chemical signals. Changes in the amounts of small organic acids, hydroxyl fatty acids, and antimicrobial compounds, including pyroglutamic acid, hydroxy-isocaproic acid, malic acid, phenyllactic acid, and lactic acid, were observed over time in the L. innocua-inoculated cheese. In cheese that was inoculated with L. innocua, Streptococcus was significantly correlated with the volatile compounds carboxylbenzaldheyde and cyclohexanecarboxylic acid, while Lactobacillus was positively correlated with some volatile and flavor compounds (cyclohexanecarboxylic acid, pyroxidal acid, aminobenzoic acid, and vanillic acid). Therefore, we determined the metabolic markers that characterize a raw milk cheese inoculated with L. innocua, the changes in these markers with the ripening time, and the positive correlation of flavor and volatile compounds with the resident microbiota. This multi-omics approach could suggest innovative food safety strategies based on the enhanced management of undesirable microorganisms by means of strain selection in raw matrices and the addition of specific antimicrobial metabolites to prevent the growth of undesirable microorganisms.

Enhancing phytochemical levels, enzymatic and antioxidant activity of spinach leaves by chitosan treatment and an insight into the metabolic pathway using DART-MS technique

Phytochemicals are health promoting compounds, synthesized by the plants to protect them against biotic or abiotic stress. The metabolic pathways leading to the synthesis of these phytochemicals are highly inducible; therefore methods could be developed to enhance their production by the exogenous application of chemical inducers/elicitors. In the present experiment, chitosan was used as an elicitor molecule to improve the phytochemical content of spinach plant. When applied at a concentration of 0.01 mg/ml as a foliar spray, chitosan was able to cause an increase in the enzymatic (peroxidase, catalase and phenylalanine ammonium lyase (PAL)) and non enzymatic (total phenolics, flavonoids and proteins) defensive metabolites, as well as, in the total antioxidant activity of the spinach leaves. A 1.7-fold increase in the total phenolics, a 2-fold increase in total flavonoid and a 1.6-fold increase in total protein were achieved with the treatment. A higher level of enzymatic activity was observed with a 4-fold increase in peroxidase and approximately 3-fold increases in catalase and phenylalanine ammonium lyase activity. Antioxidant activity showed a positive correlation between phenolic compounds and the enzymatic activity. Direct analysis in real time mass spectrometry (DART-MS) was applied to generate the metabolite profile of control and treated leaves. DART analysis revealed the activation of phenylpropanoid pathway by chitosan molecule, targeting the synthesis of diverse classes of flavonoids and their glycosides. Important metabolites of stress response were also visible in the DART spectra, including proline and free sugars.

Evaluation of imprint DESI-MS substrates for the analysis of fungal metabolites

Optimized in situ screening, characterization and imaging of fungal metabolites by imprint DESI-MS.