Glucuronides in the gut: Sugar-driven symbioses between microbe and host

The intestinal milieu is astonishingly complex and home to a constantly changing mixture of small and large molecules, along with an abundance of bacteria, viral particles, and eukaryotic cells. Such complexity makes it difficult to develop testable molecular hypotheses regarding host-microbe interactions. Fortunately, mammals and their associated gastrointestinal (GI) microbes contain complementary systems that are ideally suited for mechanistic studies. Mammalian systems inactivate endobiotic and xenobiotic compounds by linking them to a glucuronic acid sugar for GI excretion. In the GI tract, the microbiota express β-glucuronidase enzymes that remove the glucuronic acid as a carbon source, effectively reversing the actions of mammalian inactivation. Thus, by probing the actions of microbial β-glucuronidases, and by understanding which substrate glucuronides they process, molecular insights into mammalian-microbial symbioses may be revealed amid the complexity of the intestinal tract. Here, we focus on glucuronides in the gut and the microbial proteins that process them

Discovering the Microbial Enzymes Driving Drug Toxicity with Activity-Based Protein Profiling

It is increasingly clear that interindividual variability in human gut microbial composition contributes to differential drug responses. For example, gastrointestinal (GI) toxicity is not observed in all patients treated with the anticancer drug irinotecan, and it has been suggested that this variability is a result of differences in the types and levels of gut bacterial β-glucuronidases (GUSs). GUS enzymes promote drug toxicity by hydrolyzing the inactive drug-glucuronide conjugate back to the active drug, which damages the GI epithelium. Proteomics-based identification of the exact GUS enzymes responsible for drug reactivation from the complexity of the human microbiota has not been accomplished, however. Here, we discover the specific bacterial GUS enzymes that generate SN-38, the active and toxic metabolite of irinotecan, from human fecal samples using a unique activity-based protein profiling (ABPP) platform. We identify and quantify gut bacterial GUS enzymes from human feces with an ABPP-enabled proteomics pipeline and then integrate this information with ex vivo kinetics to pinpoint the specific GUS enzymes responsible for SN-38 reactivation. Furthermore, the same approach also reveals the molecular basis for differential gut bacterial GUS inhibition observed between human fecal samples. Taken together, this work provides an unprecedented technical and bioinformatics pipeline to discover the microbial enzymes responsible for specific reactions from the complexity of human feces. Identifying such microbial enzymes may lead to precision biomarkers and novel drug targets to advance the promise of personalized medicine

Structure and Inhibition of Microbiome β-Glucuronidases Essential to the Alleviation of Cancer Drug Toxicity

SummaryThe selective inhibition of bacterial β-glucuronidases was recently shown to alleviate drug-induced gastrointestinal toxicity in mice, including the damage caused by the widely used anticancer drug irinotecan. Here, we report crystal structures of representative β-glucuronidases from the Firmicutes Streptococcus agalactiae and Clostridium perfringens and the Proteobacterium Escherichia coli, and the characterization of a β-glucuronidase from the Bacteroidetes Bacteroides fragilis. While largely similar in structure, these enzymes exhibit marked differences in catalytic properties and propensities for inhibition, indicating that the microbiome maintains functional diversity in orthologous enzymes. Small changes in the structure of designed inhibitors can induce significant conformational changes in the β-glucuronidase active site. Finally, we establish that β-glucuronidase inhibition does not alter the serum pharmacokinetics of irinotecan or its metabolites in mice. Together, the data presented advance our in vitro and in vivo understanding of the microbial β-glucuronidases, a promising new set of targets for controlling drug-induced gastrointestinal toxicity

Examination of Tyrosine/Adenine Stacking Interactions in Protein Complexes

The π-stacking interactions between tyrosine amino acid side chains and adenine-bearing ligands are examined. Crystalline protein structures from the protein data bank (PDB) exhibiting face-to-face tyrosine/adenine arrangements were used to construct 20 unique 4-methylphenol/N9-methyladenine (<i>p</i>-cresol/9MeA) model systems. Full geometry optimization of the 20 crystal structures with the M06-2X density functional theory method identified 11 unique low-energy conformations. CCSD­(T) complete basis set (CBS) limit interaction energies were estimated for all of the structures to determine the magnitude of the interaction between the two ring systems. CCSD­(T) computations with double-ζ basis sets (e.g., 6-31G*(0.25) and aug-cc-pVDZ) indicate that the MP2 method overbinds by as much as 3.07 kcal mol^–1 for the crystal structures and 3.90 kcal mol^–1 for the optimized structures. In the 20 crystal structures, the estimated CCSD­(T) CBS limit interaction energy ranges from −4.00 to −6.83 kcal mol^–1, with an average interaction energy of −5.47 kcal mol^–1, values remarkably similar to the corresponding data for phenylalanine/adenine stacking interactions. Geometry optimization significantly increases the interaction energies of the <i>p</i>-cresol/9MeA model systems. The average estimated CCSD­(T) CBS limit interaction energy of the 11 optimized structures is 3.23 kcal mol^–1 larger than that for the 20 crystal structures

De novo design of luciferases using deep learning.

De novo enzyme design has sought to introduce active sites and substrate-binding pockets that are predicted to catalyse a reaction of interest into geometrically compatible native scaffolds1,2, but has been limited by a lack of suitable protein structures and the complexity of native protein sequence-structure relationships. Here we describe a deep-learning-based 'family-wide hallucination' approach that generates large numbers of idealized protein structures containing diverse pocket shapes and designed sequences that encode them. We use these scaffolds to design artificial luciferases that selectively catalyse the oxidative chemiluminescence of the synthetic luciferin substrates diphenylterazine3 and 2-deoxycoelenterazine. The designed active sites position an arginine guanidinium group adjacent to an anion that develops during the reaction in a binding pocket with high shape complementarity. For both luciferin substrates, we obtain designed luciferases with high selectivity; the most active of these is a small (13.9 kDa) and thermostable (with a melting temperature higher than 95 °C) enzyme that has a catalytic efficiency on diphenylterazine (kcat/Km = 106 M-1 s-1)&nbsp;comparable to that of native luciferases, but a much higher substrate specificity. The creation&nbsp;of highly active and specific biocatalysts from scratch with broad applications in biomedicine is a key milestone for computational enzyme design, and our approach should enable&nbsp;generation of a wide range of luciferases and other enzymes

Improving Protein Expression, Stability, and Function with ProteinMPNN

Natural proteins are highly optimized for function but are often difficult to produce at a scale suitable for biotechnological applications due to poor expression in heterologous systems, limited solubility, and sensitivity to temperature. Thus, a general method that improves the physical properties of native proteins while maintaining function could have wide utility for protein-based technologies. Here, we show that the deep neural network ProteinMPNN, together with evolutionary and structural information, provides a route to increasing protein expression, stability, and function. For both myoglobin and tobacco etch virus (TEV) protease, we generated designs with improved expression, elevated melting temperatures, and improved function. For TEV protease, we identified multiple designs with improved catalytic activity as compared to the parent sequence and previously reported TEV variants. Our approach should be broadly useful for improving the expression, stability, and function of biotechnologically important proteins

Garcinoic Acid Is a Natural and Selective Agonist of Pregnane X Receptor

Pregnane X receptor (PXR) is a master xenobiotic-sensing transcription factor with a key role in drug metabolism and disposition. Its activity regulates a number of physiological processes in the liver and intestine, and it is now a validated target for human diseases associated with inflammation and dysregulation of the immune system. The identification of chemical probes to investigate the therapeutic relevance of the receptor is still highly desired. In fact, currently available PXR ligands are not highly selective and can exhibit toxicity and/or potential off-target effects. In this study, we have identified the naturally-occurring garcinoic acid as a selective and efficient PXR agonist. The properties of garcinoic acid as a specific PXR agonist was demonstrated using different approaches - screening on a panel of nuclear receptors, physical and thermodynamic evaluation of binding affinity, and co-crystallization study. Cytotoxicity assays, transcriptional and functional experiments were carried out in human liver cells, in mouse liver and gut tissue to prove compound activity and target engagement. Taken together, these data support the conclusion that garcinoic acid efficiently activates PXR and may prove to be an amenable lead toward the development of differentially acting PXR regulating compounds

Gut microbiome responds to alteration in female sex hormone status and exacerbates metabolic dysfunction

ABSTRACTWomen are at significantly greater risk of metabolic dysfunction after menopause, which subsequently leads to numerous chronic illnesses. The gut microbiome is associated with obesity and metabolic dysfunction, but its interaction with female sex hormone status and the resulting impact on host metabolism remains unclear. Herein, we characterized inflammatory and metabolic phenotypes as well as the gut microbiome associated with ovariectomy and high-fat diet feeding, compared to gonadal intact and low-fat diet controls. We then performed fecal microbiota transplantation (FMT) using gnotobiotic mice to identify the impact of ovariectomy-associated gut microbiome on inflammatory and metabolic outcomes. We demonstrated that ovariectomy led to greater gastrointestinal permeability and inflammation of the gut and metabolic organs, and that a high-fat diet exacerbated these phenotypes. Ovariectomy also led to alteration of the gut microbiome, including greater fecal β-glucuronidase activity. However, differential changes in the gut microbiome only occurred when fed a low-fat diet, not the high-fat diet. Gnotobiotic mice that received the gut microbiome from ovariectomized mice fed the low-fat diet had greater weight gain and hepatic gene expression related to metabolic dysfunction and inflammation than those that received intact sham control-associated microbiome. These results indicate that the gut microbiome responds to alterations in female sex hormone status and contributes to metabolic dysfunction. Identifying and developing gut microbiome-targeted modulators to regulate sex hormones may be useful therapeutically in remediating menopause-related diseases

Gut Microbial β-Glucuronidase Inhibition via Catalytic Cycle Interception

Microbial β-glucuronidases (GUSs) cause severe gut toxicities that limit the efficacy of cancer drugs and other therapeutics. Selective inhibitors of bacterial GUS have been shown to alleviate these side effects. Using structural and chemical biology, mass spectrometry, and cell-based assays, we establish that piperazine-containing GUS inhibitors intercept the glycosyl-enzyme catalytic intermediate of these retaining glycosyl hydrolases. We demonstrate that piperazine-based compounds are substrate-dependent GUS inhibitors that bind to the GUS–GlcA catalytic intermediate as a piperazine-linked glucuronide (GlcA, glucuronic acid). We confirm the GUS-dependent formation of inhibitor–glucuronide conjugates by LC–MS and show that methylated piperazine analogs display significantly reduced potencies. We further demonstrate that a range of approved piperazine- and piperidine-containing drugs from many classes, including those for the treatment of depression, infection, and cancer, function by the same mechanism, and we confirm through gene editing that these compounds selectively inhibit GUS in living bacterial cells. Together, these data reveal a unique mechanism of GUS inhibition and show that a range of therapeutics may impact GUS activities in the human gut