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Microbial natural products form the basis of most of the antibiotics used in the clinic. The vast majority has not yet been discovered, among others because the hidden chemical space is obscured by previously identified (and typically abundant) antibiotics in culture extracts. Efficient dereplication is therefore key to the discovery of our future medicines. Here we present an analytical platform for the efficient identification and prioritization of low abundance bioactive compounds at nanoliter scale, called nanoRAPIDS. NanoRAPIDS encompasses analytical scale separation and nanofractionation of natural extracts, followed by the bioassay of interest, automated mass spectrometry identification, and Global Natural Products Social molecular networking (GNPS) for dereplication. As little as 10 μL crude extract is fractionated into 384 fractions. First, bioactive congeners of iturins and surfactins were identified in Bacillus, based on their bioactivity. Subsequently, bioactive molecules were identified in an extensive network of angucyclines elicited by catechol in cultures of Streptomyces sp. This allowed the discovery of a highly unusual N-acetylcysteine conjugate of saquayamycin, despite low production levels in an otherwise abundant molecular family. These data underline the utility and broad application of the technology for the prioritization of minor bioactive compounds in complex extracts. Microbial natural products are an important source for antibiotic discovery, however, their efficient dereplication remains challenging. Here, the authors develop an analytical pipeline, nanoRAPIDS, to prioritize low abundance bioactive compounds at nanoscale, by integrating the bioassay of interest, automated mass spectrometry identification and GNPS-based dereplication, resulting in the discovery of saquayamycin N from Streptomyces sp. MBT84. [ABSTRACT FROM AUTHOR]

Farnesoid X receptor (FXR) activation reduces renal inflammation, but the underlying mechanisms remain elusive. Neutrophil extracellular traps (NETs) are webs of DNA formed when neutrophils undergo specialized programmed cell death (NETosis). The signaling lipid sphingosine-1-phosphate (S1P) stimulates NETosis via its receptor on neutrophils. Here, we identify FXR as a negative regulator of NETosis via repressing S1P signaling. We determined the effects of the FXR agonist obeticholic acid (OCA) in mouse models of adenosine phosphoribosyltransferase (APRT) deficiency and Alport syndrome, both genetic disorders that cause chronic kidney disease. Renal FXR activity is greatly reduced in both models, and FXR agonism reduces disease severity. Renal NETosis and sphingosine kinase 1 (Sphk1) expression are increased in diseased mice, and they are reduced by OCA in both models. Genetic deletion of FXR increases Sphk1 expression, and Sphk1 expression correlates with NETosis. Importantly, kidney S1P levels in Alport mice are two-fold higher than controls, and FXR agonism restores them back to baseline. Short-term inhibition of sphingosine synthesis in Alport mice with severe kidney disease reverses NETosis, establishing a causal relationship between S1P signaling and renal NETosis. Finally, extensive NETosis is present in human Alport kidney biopsies (six male, nine female), and NETosis severity correlates with clinical markers of kidney disease. This suggests the potential clinical relevance of the newly identified FXR-S1P-NETosis pathway. In summary, FXR agonism represses kidney Sphk1 expression. This inhibits renal S1P signaling, thereby reducing neutrophilic inflammation and NETosis. NEW & NOTEWORTHY Many preclinical studies have shown that the farnesoid X receptor (FXR) reduces renal inflammation, but the mechanism is poorly understood. This report identifies FXR as a novel regulator of neutrophilic inflammation and NETosis via the inhibition of sphingosine-1-phosphate signaling. Additionally, NETosis severity in human Alport kidney biopsies correlates with clinical markers of kidney disease. A better understanding of this signaling axis may lead to novel treatments that prevent renal inflammation and chronic kidney disease. [ABSTRACT FROM AUTHOR]

R3613 --> 856.4 --> Objective: This study investigates the protective properties of farsenoid X receptor (FXR) agonism by the drug Obeticholic Acid (OCA) in the adenine‐induced tubulointerstitial fibrosis model of kidney disease male and female mice. Hypothesis: OCA treatment will decrease the expression of SMAD3 and phosphorylated‐SMAD3, and therefore will be nephroprotective in the adenine model of kidney disease in male and female mice. Methods: Male and female C57BL/6J mice (12 weeks old) were fed chow (Research Diets D1912040li) or chow admixed with adenine (0.2% w/w) ad lib for 7 weeks. Mice were treated with either vehicle (corn oil) or obeticholic acid (10 mg/kg BW) by gavage 5 days per week. Plasma and organs were collected and processed for bio‐chemical analysis. Results: OCA treatment reduced BUN and plasma creatinine in diseased mice of both sexes. FXR agonism reduced SMAD3 expression in both male (P<0.05) and female (P<0.05) mice. Importantly, FXR agonism also reduced SMAD3 phosphorylation in both male (P<0.05) and female (P<0.001) mice. On histology, OCA reduced renal fibrosis in male (P<0.05) but not female mice. Conclusions: FXR agonism by OCA is anti‐fibrotic in the adenine model of tubulointerstitial fibrotic crystalline nephropathy in male and female mice. Mechanistically, OCA prevents renal fibrosis by reducing SMAD3 expression and phosphorylation. [ABSTRACT FROM AUTHOR]

Actinobacteria are a rich source of bioactive molecules, and genome sequencing has shown that the vast majority of their biosynthetic potential has yet to be explored. However, many of their biosynthetic gene clusters (BGCs) are poorly expressed in the laboratory, which prevents discovery of their cognate natural products. To exploit their full biosynthetic potential, better understanding of the signals that promote the expression of BGCs is needed. Here, we show that the human stress hormone epinephrine (adrenaline) elicits siderophore production by Actinobacteria. Catechol was established as the likely eliciting moiety, since similar responses were seen for catechol and for the catechol-containing molecules dopamine and catechin but not for related molecules. Exploration of the catechol-responsive strain Streptomyces sp. MBT84 using mass spectral networking revealed elicitation of a BGC that produces the angucycline glycosides aquayamycin, urdamycinone B and galtamycin C. Heterologous expression of the catechol-cleaving enzymes catechol 1,2-dioxygenase or catechol 2,3-dioxygenase counteracted the eliciting effect of catechol. Thus, our work identifies the ubiquitous catechol moiety as a novel elicitor of the expression of BGCs for specialized metabolites. The biosynthetic gene clusters of Actinobacteria are poorly expressed in the laboratory, necessitating a better understanding of the signals that promote their expression in order to exploit their full biosynthetic potential. Here, the authors show that the stress hormone epinephrine elicits the expression of biosynthetic gene clusters and influences the metabolism of Streptomyces, with the catechol moiety proving key to this response. [ABSTRACT FROM AUTHOR]

This paper presents a stochastic framework for the optimization of microgrids that has the functionality of providing flexibility services to System Operators (SOs) considering uncertainties in the energy forecast. The methodology is developed with the aim of being applied to complex microgrids composed of different distributed energy resources and hybrid energy storage systems (ESS). The associated optimization problem is operated in two stages: the first one performs a stochastic optimization of the microgrid in order to reserve an up/down regulation capacity with which to deal with the energy forecast uncertainties of the microgrid. The different microgrid devices are optimized by considering their operational costs in order to achieve their optimal operation in the Day-Ahead Market (DM). The second stage is used to re-schedule the initial planning according to the signal request and an economic offer from the SO. The control problem is developed using Stochastic Model Predictive Control (SMPC) techniques and Mixed-Integer Quadratic Programming (MIQP), owing to the presence of logic, integer, mixed and probabilistic variables. The simulation results show that the proposed methodology reduces the risk of undergoing up/down-penalty deviations in the Regulation Service Market (RM), also being able to provide flexibility services to the SOs, despite being subject to uncertainties in the energy forecast carried out for the microgrid. [ABSTRACT FROM AUTHOR]