Natural products from microbes have provided humans with beneficial antibiotics for millennia. However, a decline in the pace of antibiotic discovery exerts pressure on human health as antibiotic resistance spreads, a challenge that may better faced by unveiling chemical diversity produced by microbes. Current microbial genome mining approaches have revitalized research into antibiotics, but the empirical nature of these methods limits the chemical space that is explored. Here, we address the problem of finding novel pathways by incorporating evolutionary principles into genome mining. We recapitulated the evolutionary history of twenty-three enzyme families previously uninvestigated in the context of natural product biosynthesis in Actinobacteria , the most proficient producers of natural products. Our genome evolutionary analyses where based on the assumption that expanded—repurposed enzyme families—from central metabolism, occur frequently and thus have the potential to catalyze new conversions in the context of natural products biosynthesis. Our analyses led to the discovery of biosynthetic gene clusters coding for hidden chemical diversity, as validated by comparing our predictions with those from state-of-the-art genome mining tools; as well as experimentally demonstrating the existence of a biosynthetic pathway for arseno-organic metabolites in Streptomyces coelicolor and Streptomyces lividans , Using a gene knockout and metabolite profile combined strategy. As our approach does not rely solely on sequence similarity searches of previously identified biosynthetic enzymes, these results establish the basis for the development of an evolutionary-driven genome mining tool termed EvoMining that complements current platforms. We anticipate that by doing so real ‘chemical dark matter’ will be unveiled.

Purpose: We aimed to evaluate age-dependent changes of six trace elements (TE) [manganese (Mn), iron (Fe), zinc (Zn), copper (Cu), iodine (I), and selenium (Se)] over a 20-year period. Methods: TE concentrations were determined using repeated serum samples taken at baseline and after 20 years of follow-up from 219 healthy participants of the EPIC-Potsdam study, using inductively coupled plasma tandem mass spectrometry. For each TE, absolute and relative differences were calculated between the two time points, as well as the proportion of individuals within normal reference ranges. Interdependence between age-related TE differences was investigated using principal component analysis (PCA). Relationships between selected factors (lifestyle, sociodemographic, anthropometric factors, and hypertension) and corresponding TE longitudinal variability were examined using multivariable linear regression models. Results: Median age of our study sample was 58.32 years (4.42) at baseline and 40% were females. Median Mn, Zn, Se concentrations and Se to Cu ratio significantly decreased during aging while median Fe, Cu, I concentrations and Cu to Zn ratio significantly increased. A substantial percentage of the participants, at both time points, had Zn concentrations below the reference range. The first PCA-extracted factor reflected the correlated decline in both Mn and Zn over time while the second factor reflected the observed (on average) increase in both Cu and I over time. Overall, none of the investigated factors were strong determinants of TE longitudinal variability, except possibly dietary supplement use, and alcohol use for Fe. Conclusions: In conclusion, in this population-based study of healthy elderly, decrease in Mn, Zn, and Se concentrations and increase in Fe, Cu, and I concentrations were observed over 20 years of follow-up. Further research is required to investigate dietary determinants and markers of TE status as well as the relationships between TE profiles and the risk of age-related diseases.

Trace elements, like Cu, Zn, Fe, or Se, are important for the proper functioning of antioxidant enzymes. However, in excessive amounts, they can also act as pro-oxidants. Accordingly, trace elements influence redox-modulated signaling pathways, such as the Nrf2 pathway. Vice versa, Nrf2 target genes belong to the group of transport and metal binding proteins. In order to investigate whether Nrf2 directly regulates the systemic trace element status, we used mice to study the effect of a constitutive, whole-body Nrf2 knockout on the systemic status of Cu, Zn, Fe, and Se. As the loss of selenoproteins under Se-deprived conditions has been described to further enhance Nrf2 activity, we additionally analyzed the combination of Nrf2 knockout with feeding diets that provide either suboptimal, adequate, or supplemented amounts of Se. Experiments revealed that the Nrf2 knockout partially affected the trace element concentrations of Cu, Zn, Fe, or Se in the intestine, liver, and/or plasma. However, aside from Fe, the other three trace elements were only marginally modulated in an Nrf2-dependent manner. Selenium deficiency mainly resulted in increased plasma Zn levels. One putative mediator could be the metal regulatory transcription factor 1, which was up-regulated with an increasing Se supply and downregulated in Se-supplemented Nrf2 knockout mice.

Insulin receptor signaling is crucial for white adipose tissue (WAT) function. Consequently, lack of insulin receptor (IR) in WAT results in a diabetes-like phenotype. Yet, causes for IR downregulation in WAT of patients with diabetes are not well understood. By using multiple mouse models of obesity and insulin resistance, we identify a common downregulation of IR with a reduction of mRNA expression of selenoproteins Txnrd3 , Sephs2 , and Gpx3 in gonadal adipose tissue. Consistently, GPX3 is also decreased in adipose tissue of insulin-resistant and obese patients. Inducing Gpx3 expression via selenite treatment enhances IR expression via activation of the transcription factor Sp1 in 3T3-L1 preadipocytes and improves adipocyte differentiation and function. Feeding mice a selenium-enriched high-fat diet alleviates diet-induced insulin resistance with increased insulin sensitivity, decreased tissue inflammation, and elevated IR expression in WAT. Again, IR expression correlated positively with Gpx3 expression, a phenotype that is also conserved in humans. Consequently, decreasing GPx3 using siRNA technique reduced IR expression and insulin sensitivity in 3T3-L1 preadipocytes. Overall, our data identify GPx3 as a potentially novel regulator of IR expression and insulin sensitivity in adipose tissue.

This study describes the identification and quantification of five new arsenolipids present in raw marine fish oil extracted mainly from Peruvian anchoveta (Engraulis ringens). The arsenolipids accumulated on bentonite, which has been used to clean-up raw fish oils in an industrial process for producing commercial fish oil rich in omega-3 fatty acids. The bentonite, which adsorbed the arsenolipids efficiently from the raw fish oil was extracted with different solvents and subsequently cleaned up by normal phase chromatography, which fractionated all absorbed compounds according to polarity. The arsenic containing fatty acids (AsFA) and arsenic containing hydrocarbons (AsHC) were determined using a separation by reverse phase high performance liquid chromatography coupled online to inductively coupled plasma mass spectrometry (RP-HPLC-ICP-MS) for quantification and simultaneously to electrospray ionization mass spectrometry (ESI-MS) for identification. A mixture of methanol/chloroform (1 : 2 v/v) was sufficient for the extraction of the majority of the adsorbed arsenic species (129 μg g⁻¹ As bentonite). The pre-concentration using the adsorbent with subsequent fractionation made it possible to identify minor arsenolipids especially in the polar methanol fraction. Besides two major arsenic containing hydrocarbons (AsHC332 and AsHC360) three new arsenic containing medium chain fatty acids (As-MCFA) of molecular mass 250, 278, 292 and two new arsenic containing long chain fatty acids (As-LCFA) of mass 306 and 320 could be identified although their concentrations were as low as 0.004 μg g⁻¹ As bentonite. The significance of MCFA is that these compounds usually occur not as free fatty acids but are conjugated to glycerol forming triglycerides. Confirmation of this hypothesis is given in the fact that a methanol extract which was directly analyzed without any clean up procedure did only contain traces of As-LCFA and no As-MCFA but the same concentration of the more inert AsHCs, which are not expected to be conjugated to other organic compounds. This highlights that a successful pre-concentration and clean up procedure is essential to determine traces of minor arsenolipids but it does not provide a guarantee for the integrity of all arsenolipid species.