A metabolomics footprinting approach using GC-MS to study inhibitory effects of the fungal metabolite diplopyrone C against nosocomial pathogen biofilms

Seen initially as wonder drugs, the widespread and often inappropriate use of antibiotics led to the development of microbial resistances. As a result, a true emergency has arisen, and a significant need has emerged to discover and develop new safe and valuable antibiotics. The captivating chemical structure of the fungal metabolite diplopyrone C has caught our attention as an excellent candidate for a circumstantial study aimed at revealing its antimicrobial and antibiofilm activities. In this work, we describe the full analytical strategy from the isolation/identification to the evaluation of the metabolomics effect on target microorganisms of this fungal metabolite. Our results show interesting antimicrobial and antibiofilm activities of diplopyrone C against two frequently isolated nosocomial pathogens (i.e., the fungus Candida albicans and the gram-negative bacterium Klebsiella pneumoniae). Moreover, a GC-MS based metabolomics footprinting approach gave an insight into the uptake and excretion of metabolites from and into the culture medium as a response to the presence of this active substance. The workflow employed in this study is suitable to exploit natural resources for the search of lead compounds for drug development.

Biological and metabolic effects of the association between the microalga Galdieria sulphuraria and the fungus Penicillium citrinum

Contamination of microalgae cultures can reduce their productivity and affect the quality of biomass and valuable bioproducts. In this article, after having isolated and identified for the first time the filamentous fungus Penicillium citrinum from heterotrophic cultures of the red polyextremophilic microalga Galdieria sulphuraria, we investigated the biological and metabolic significance of this alga-fungus association. In the same medium, both organisms grow better in each other's presence than separately. Both cell density and cell size of G. sulphuraria increase in co-cultures compared to pure alga cultures. In co-cultures, despite very severe growth conditions, the load of P. citrinum increases compared to pure fungus cultures. Optical microscope images have shown physical contact between cells of P. citrinum hyphae and G. sulphuraria which, however, retain their morphology and cell wall intact. GC-MS-based metabolomics analysis of metabolites excreted in the culture medium shows that pure cultures of the fungus and alga and co-cultures of alga plus fungus can be easily differentiated based on their metabolic products. Indeed, a richer assortment of extracellular metabolites (comprising both products of primary and secondary metabolism) is a distinct feature of co-cultures compared to both pure alga and pure fungus cultures.

A model for microbial interactions and metabolomic alterations in Candida glabrata-Staphylococcus epidermidis dual-species biofilms

The fungus Candida glabrata and the bacterium Staphylococcus epidermidis are important biofilm-forming microorganisms responsible of nosocomial infections in patients. In addition to causing single-species disease, these microorganisms are also involved in polymicrobial infections leading to an increased antimicrobial resistance. To expand knowledge about polymicrobial biofilms, in this study we investigate the formation of single- and dual-species biofilms of these two opportunistic pathogens employing several complementary approaches. First, biofilm biomass, biofilm metabolic activity and the microbial composition in single- and dual-species biofilms were assessed and compared. Then, the expression of three genes of C. glabrata and three genes of S. epidermidis positively related to the process of biofilm formation was evaluated. Although S. epidermidis is a stronger biofilm producer than C. glabrata, both biological and genetic data indicate that S. epidermidis growth is inhibited by C. glabrata which dominates the dual-species biofilms. To better understand the mechanisms of the interactions between the two microorganisms, a broad GC-MS metabolomic dataset of extracellular metabolites for planktonic, single- and dual-species biofilm cultures of C. glabrata and S. epidermidis was collected. As demonstrated by Partial Least Squares Discriminant Analysis (PLS-DA) of GC-MS metabolomic data, planktonic cultures, single- and dual-species biofilms can be sharply differentiated from each other by the nature and levels of an assortment of primary and secondary metabolites secreted in the culture medium. However, according to our data, 2-phenylethanol (secreted by C. glabrata) and the synergistically combined antifungal activity of 3-phenyllactic acid and of the cyclic dipeptide cyclo-(l-Pro-l-Trp) (secreted by S. epidermidis) play a major role in the race of the two microorganisms for predominance and survival.

Analysis of sequential hair segments reflects changes in the metabolome across the trimesters of pregnancy

The hair metabolome has been recognized as a valuable source of information in pregnancy research, as it provides stable metabolite information that could assist with studying biomarkers or metabolic mechanisms of pregnancy and its complications. We tested the hypothesis that hair segments could be used to reflect a metabolite profile containing information from both endogenous and exogenous compounds accumulated during the nine months of pregnancy. Segments of hair samples corresponding to the trimesters were collected from 175 pregnant women in New Zealand. The hair samples were analysed using gas chromatography-mass spectrometry and liquid chromatography-mass spectrometry. In healthy pregnancies, 56 hair metabolites were significantly different between the first and second trimesters, while 62 metabolites were different between the first and third trimesters (p < 0.05). Additionally, three metabolites in the second trimester hair samples were significantly different between healthy controls and women who delivered small-for-gestational-age infants (p < 0.05), and ten metabolites in third trimester hair were significantly different between healthy controls and women with gestational diabetes mellitus (p < 0.01). The findings from this pilot study provide improved insight into the changes of the hair metabolome during pregnancy, as well as highlight the potential of the maternal hair metabolome to differentiate pregnancy complications from healthy pregnancies.

Review of emerging metabolomic tools and resources: 2015-2016

Data processing and analysis are major bottlenecks in high-throughput metabolomic experiments. Recent advancements in data acquisition platforms are driving trends toward increasing data size (e.g., petabyte scale) and complexity (multiple omic platforms). Improvements in data analysis software and in silico methods are similarly required to effectively utilize these advancements and link the acquired data with biological interpretations. Herein, we provide an overview of recently developed and freely available metabolomic tools, algorithms, databases, and data analysis frameworks. This overview of popular tools for MS and NMR-based metabolomics is organized into the following sections: data processing, annotation, analysis, and visualization. The following overview of newly developed tools helps to better inform researchers to support the emergence of metabolomics as an integral tool for the study of biochemistry, systems biology, environmental analysis, health, and personalized medicine.