We have isolated a filamentous fungus that actively secretes a pigmented exudate when growing on agar plates. The fungus was identified as being a strain of Epicoccum nigrum. The fungal exudate presented strong antifungal activity against both yeasts and filamentous fungi, and inhibited the germination of fungal spores. The chemical characterization of the exudate showed that the pigmented molecule presenting antifungal activity is the disalt of epipyrone A—a water-soluble polyene metabolite with a molecular mass of 612.29 and maximal UV–Vis absorbance at 428 nm. This antifungal compound showed excellent stability to different temperatures and neutral to alkaline pH.

To ensure biological validity in metabolic phenotyping, findings must be replicated in independent sample sets. Targeted workflows have long been heralded as ideal platforms for such validation due to their robust quantitative capability. We evaluated the capability of liquid chromatography-mass spectrometry (LC-MS) assays targeting organic acids and bile acids to validate metabolic phenotypes of SARS-CoV-2 infection. Two independent sample sets were collected: (1) Australia: plasma, SARS-CoV-2 positive (n = 20), noninfected healthy controls (n = 22) and COVID-19 disease-like symptoms but negative for SARS-CoV-2 infection (n = 22). (2) Spain: serum, SARS-CoV-2 positive (n = 33) and noninfected healthy controls (n = 39). Multivariate modeling using orthogonal projections to latent structures discriminant analyses (OPLS-DA) classified healthy controls from SARS-CoV-2 positive (Australia; R² = 0.17, ROC-AUC = 1; Spain R² = 0.20, ROC-AUC = 1). Univariate analyses revealed 23 significantly different (p < 0.05) metabolites between healthy controls and SARS-CoV-2 positive individuals across both cohorts. Significant metabolites revealed consistent perturbations in cellular energy metabolism (pyruvic acid, and 2-oxoglutaric acid), oxidative stress (lactic acid, 2-hydroxybutyric acid), hypoxia (2-hydroxyglutaric acid, 5-aminolevulinic acid), liver activity (primary bile acids), and host-gut microbial cometabolism (hippuric acid, phenylpropionic acid, indole-3-propionic acid). These data support targeted LC-MS metabolic phenotyping workflows for biological validation in independent sample sets.

Pooled quality control (PQC) samples are the gold standard for data quality monitoring in metabolic phenotyping studies. Typically composed of equal parts from all study samples, PQCs can be challenging to generate in large cohorts or when sample volumes are low. As an alternative, externally sourced matrix-matched surrogate QCs (sQC) have been proposed. This study evaluates the performance of sQCs against PQCs for assessing analytical variation, data pre-processing, and downstream data analysis in a targeted lipidomics workflow. Plasma samples (n = 701) from the Microbiome Understanding in Maternity Study, along with PQC (n = 80) and sQC (n = 80) samples, were analyzed using a lipidomics assay targeting 1162 lipids. QC samples were injected throughout acquisition, and data pre-processing was performed using each strategy. For simplicity, a subset (n = 381) of the study samples was used to assess differences in downstream statistical analyses. Both QC approaches demonstrated high analytical repeatability. While PQC and sQC compositions differed, use of PQCs retained less than 4 % more lipid species during pre-processing. Univariate analysis identified more statistically significant lipids with PQC-based pre-processing, but multivariate model performance was similar between datasets. This study provides a comprehensive comparison of QC strategies and emphasizes the importance of careful QC workflow selection. While PQCs offer advantages, sQCs serve as a suitable alternative for quality assessment and pre-processing. Their commercial availability also supports use as intra- and inter-laboratory long-term references, aiding data harmonization across studies and laboratories.

Multidrug-resistant fungal pathogens and antifungal drug toxicity have challenged our current ability to fight fungal infections. Therefore, there is a strong global demand for novel antifungal molecules with the distinct mode of action and specificity to service the medical and agricultural sectors. Polyenes are a class of antifungal drugs with the broadest spectrum of activity among the current antifungal drugs. Epipyrone A, a water-soluble antifungal molecule with a unique, linear polyene structure, was isolated from the fungus Epiccocum nigrum. Since small changes in a compound structure can significantly alter its cell target and mode of action, we present here a study on the antifungal mode of action of the disalt of epipyrone A (DEA) using chemical-genetic profiling, fluorescence microscopy, and metabolomics. Our results suggest the disruption of sphingolipid/fatty acid biosynthesis to be the primary mode of action of DEA, followed by the intracellular accumulation of toxic phenolic compounds, in particular p-toluic acid (4-methylbenzoic acid). Although membrane ergosterol is known to be the main cell target for polyene antifungal drugs, we found little evidence to support that is the case for DEA. Sphingolipids, on the other hand, are known for their important roles in fungal cell physiology, and their biosynthesis has been recognized as a potential fungal-specific cell target for the development of new antifungal drugs.

The evolution of complex in vitro models of the human gastrointestinal system to interrogate the biochemical functionality of the gut microbiome has augmented our understanding of its role in human physiology and pathology. With 5718 authors from 52 countries, gut bioreactor research reflects the growing awareness of our need to understand the contribution of the gut microbiome to human health. Although a large body of knowledge has been generated from in vitro models, it is scattered and defined by application-specific terminologies. To better grasp the capacity of bioreactors and further our knowledge of the human gastrointestinal system, we have conducted a cross-field bibliometric search and mapped the evolution of human gastrointestinal in vitro research. We present reference material with the aim of identifying key authors and bioreactor types to enable researchers to make decisions regarding the choice of method for simulating the human gut in the context of microbiome functionality.