Relative quantification of the proteomeic changes associated with the mycotoxin zearalenone in the H295R steroidogenesis model

Zearalenone (ZEN) is a mycotoxin with endocrine disrupting effects having vast economic implications in e.g. pig farming. Structurally, ZEN resembles 17b-estradiol, and thus is able to bind to estrogen receptors (ER) in target cells. Because of this, it is also classified as a non-steroidal estrogen, a phytoestrogen, a mycoestrogen, and a growth promoter. Quantitative proteomic analysis was undertaken using stable-isotope labeling by amino acids in cell culture (SILAC) upon exposure of the steroidogenesis cell model H295R with ZEN to elucidate its effect on protein regulation. ZEN significantly regulated 21 proteins, including proteins with known endocrine disrupting effects and several oncogenes. In addition, network analysis using Ingenuity Pathway Analysis showed that ZEN affected the oxidative phosphorylation pathway and the mitochondrial dysfunction pathway, both previously reported to be involved in endocrine dysfunction.

Relative metabolomic flux: Predicting changes in the environmental metabolome from the metagenome

Background: The world's oceans are home to a diverse array of microbial life whose metabolic activity helps to drive the earth's biogeochemical cycles. Metagenomic analysis has revolutionized our access to these communities, providing a system-scale perspective of microbial community interactions. However, while metagenome sequencing can provide useful estimates of the relative change in abundance of specific genes and taxa between environments or over time, this does not investigate the relative changes in the production or consumption of different metabolites.
Results: We propose a methodology, Predicted Relative Metabolic Turnover (PRMT) that defines and enables exploration of metabolite-space inferred from the metagenome. Our analysis of metagenomic data from a time-series study in the Western English Channel demonstrated considerable correlations between predicted relative metabolic turnover and seasonal changes in abundance of measured environmental parameters as well as with observed seasonal changes in bacterial population structure.
Conclusions: The PRMT method was successfully applied to metagenomic data to explore the Western English Channel microbial metabalome to generate specific, biologically testable hypotheses. Generated hypotheses linked organic phosphate utilization to Gammaproteobactaria, Plantcomycetes, and Betaproteobacteria, chitin degradation to Actinomycetes, and potential small molecule biosynthesis pathways for Lentisphaerae, Chlamydiae, and Crenarchaeota. The PRMT method can be applied as a general tool for the analysis of additional metagenomic or transcriptomic datasets.

Interaction strength, food web topology and the relative importance of species in food webs

P>1. We established complex marine communities, consisting of over 100 species, in large subtidal experimental mesocosms. We measured the strength of direct interactions and the net strength of direct and indirect interactions between the species in those communities, using a combination of theoretical and empirical approaches.