Alternative pathway for dopamine production by acetogenic gut bacteria that O-Demethylate 3-Methoxytyramine, a metabolite of catechol O-Methyltransferase.

AIMS: The gut microbiota modulates dopamine levels in vivo, but the bacteria and biochemical processes responsible remain incompletely characterized. A potential precursor of bacterial dopamine production is 3-methoxytyramine (3MT); 3MT is produced when dopamine is O-methylated by host catechol O-methyltransferase (COMT), thereby attenuating dopamine levels. This study aimed to identify whether gut bacteria are capable of reverting 3MT to dopamine. METHODS AND RESULTS: Human faecal bacterial communities O-demethylated 3MT and yielded dopamine. Gut bacteria that mediate this transformation were identified as acetogens Eubacterium limosum and Blautia producta. Upon exposing these acetogens to propyl iodide, a known inhibitor of cobalamin-dependent O-demethylases, 3MT O-demethylation was inhibited. Culturing E. limosum and B. producta with 3MT afforded increased acetate levels as compared with vehicle controls. CONCLUSIONS: Gut bacterial acetogens E. limosum and B. producta synthesized dopamine from 3MT. This O-demethylation of 3MT was likely performed by cobalamin-dependent O-demethylases implicated in reductive acetogenesis. SIGNIFICANCE AND IMPACT OF THE STUDY: This is the first report that gut bacteria can synthesize dopamine by O-demethylation of 3MT. Owing to 3MT being the product of host COMT attenuating dopamine levels, gut bacteria that reverse this transformation-converting 3MT to dopamine-may act as a counterbalance for dopamine regulation by COMT.

Interrogating selectivity in catalysis using molecular vibrations.

The delineation of molecular properties that underlie reactivity and selectivity is at the core of physical organic chemistry, and this knowledge can be used to inform the design of improved synthetic methods or identify new chemical transformations. For this reason, the mathematical representation of properties affecting reactivity and selectivity trends, that is, molecular parameters, is paramount. Correlations produced by equating these molecular parameters with experimental outcomes are often defined as free-energy relationships and can be used to evaluate the origin of selectivity and to generate new, experimentally testable hypotheses. The premise behind successful correlations of this type is that a systematically perturbed molecular property affects a transition-state interaction between the catalyst, substrate and any reaction components involved in the determination of selectivity. Classic physical organic molecular descriptors, such as Hammett, Taft or Charton parameters, seek to independently probe isolated electronic or steric effects. However, these parameters cannot address simultaneous, non-additive variations to more than one molecular property, which limits their utility. Here we report a parameter system based on the vibrational response of a molecule to infrared radiation that can be used to mathematically model and predict selectivity trends for reactions with interlinked steric and electronic effects at positions of interest. The disclosed parameter system is mechanistically derived and should find broad use in the study of chemical and biological systems.

The Development of Multidimensional Analysis Tools for Asymmetric Catalysis and Beyond.

In most modern organic chemistry reports, including many of ours, reaction optimization schemes are typically presented to showcase how reaction conditions have been tailored to augment the reaction's yield and selectivity. In asymmetric catalysis, this often involves evaluation of catalyst, solvent, reagent, and, sometimes, substrate features. Such an article will then detail the process's scope, which mainly focuses on its successes and briefly outlines the "limitations". These limitations or poorer-performing substrates are occasionally the result of obvious, significant changes to structure (e.g., a Lewis basic group binds to a catalyst), but frequently, a satisfying explanation for inferior performance is not clear. This is one of several reasons such results are not often reported. These apparent outliers are also commonplace in the evaluation of catalyst structure, although most of this information is placed in the Supporting Information. These practices are unfortunate because results that appear at first glance to be peculiar or poor are considerably more interesting than ones that follow obvious or intuitive trends. In other words, all of the data from an optimization campaign contain relevant information about the reaction under study, and the "outliers" may be the most revealing. Realizing the power of outliers as an entry point to entirely new reaction development is not unusual. Nevertheless, the concept that no data should be wasted when considering the underlying phenomena controlling the observations of a given reaction is at the heart of the strategy we describe in this Account. The idea that one can concurrently optimize a reaction to expose the structural features that control its outcomes would represent a transformative addition to the arsenal of catalyst development and, ultimately, de novo design. Herein we outline the development of a recently initiated program in our lab that unites optimization with mechanistic interrogation by correlating reaction outputs (e.g., electrochemical potential or enantio-, site, or chemoselectivity) with structural descriptors of the molecules involved. The ever-evolving inspiration for this program is rooted in outliers of classical linear free energy relationships. These outliers encouraged us to ask questions about the parameters themselves, suggest potential interactions at the source of the observed effects, and, of particular applicability, identify more sophisticated physical organic descriptors. Throughout this program, we have integrated techniques from disparate fields, including synthetic methodology development, mechanistic investigations, statistics, computational chemistry, and data science. The implementation of many of these strategies is described, and the resulting tools are illustrated in a wide range of case studies, which include data sets with simultaneous and multifaceted changes to the reagent, substrate, and catalyst structures. This tactic constitutes a modern approach to physical organic chemistry wherein no data are wasted and mechanistic hypotheses regarding sophisticated processes can be developed and probed.

Designer substrate library for quantitative, predictive modeling of reaction performance.

Assessment of reaction substrate scope is often a qualitative endeavor that provides general indications of substrate sensitivity to a measured reaction outcome. Unfortunately, this field standard typically falls short of enabling the quantitative prediction of new substrates' performance. The disconnection between a reaction's development and the quantitative prediction of new substrates' behavior limits the applicative usefulness of many methodologies. Herein, we present a method by which substrate libraries can be systematically developed to enable quantitative modeling of reaction systems and the prediction of new reaction outcomes. Presented in the context of rhodium-catalyzed asymmetric transfer hydrogenation, these models quantify the molecular features that influence enantioselection and, in so doing, lend mechanistic insight to the modes of asymmetric induction.

Quantitatively analyzing metathesis catalyst activity and structural features in silica-supported tungsten imido-alkylidene complexes.

A broad series of fully characterized, well-defined silica-supported W metathesis catalysts with the general formula [(≡SiO)W(═NAr)(═CHCMe2R)(X)] (Ar = 2,6-iPr2C6H3 (AriPr), 2,6-Cl2C6H3 (ArCl), 2-CF3C6H4 (ArCF3), and C6F5 (ArF5); X = OC(CF3)3 (OtBuF9), OCMe(CF3)2 (OtBuF6), OtBu, OSi(OtBu)3, 2,5-dimethylpyrrolyl (Me2Pyr) and R = Me or Ph) was prepared by grafting bis-X substituted complexes [W(NAr)(═CHCMe2R)(X)2] on silica partially dehydroxylated at 700 °C (SiO2-(700)), and their activity was evaluated with the goal to obtain detailed structure-activity relationships. Quantitative influence of the ligand set on the activity (turnover frequency, TOF) in self-metathesis of cis-4-nonene was investigated using multivariate linear regression analysis tools. The TOF of these catalysts (activity) can be well predicted from simple steric and electronic parameters of the parent protonated ligands; it is described by the mutual contribution of the NBO charge of the nitrogen or the IR intensity of the symmetric N-H stretch of the ArNH2, corresponding to the imido ligand, together with the Sterimol B5 and pKa of HX, representing the X ligand. This quantitative and predictive structure-activity relationship analysis of well-defined heterogeneous catalysts shows that high activity is associated with the combination of X and NAr ligands of opposite electronic character and paves the way toward rational development of metathesis catalysts.

Analyzing site selectivity in Rh2(esp)2-catalyzed intermolecular C-H amination reactions.

Predicting site selectivity in C-H bond oxidation reactions involving heteroatom transfer is challenged by the small energetic differences between disparate bond types and the subtle interplay of steric and electronic effects that influence reactivity. Herein, the factors governing selective Rh2(esp)2-catalyzed C-H amination of isoamylbenzene derivatives are investigated, where modification to both the nitrogen source, a sulfamate ester, and substrate are shown to impact isomeric product ratios. Linear regression mathematical modeling is used to define a relationship that equates both IR stretching parameters and Hammett σ(+) values to the differential free energy of benzylic versus tertiary C-H amination. This model has informed the development of a novel sulfamate ester, which affords the highest benzylic-to-tertiary site selectivity (9.5:1) observed for this system.

Mechanistic Insight into Intestinal α-Synuclein Aggregation in Parkinson's Disease Using a Laser-Printed Electrochemical Sensor.

Aggregated deposits of the protein α-synuclein and depleting levels of dopamine in the brain correlate with Parkinson's disease development. Treatments often focus on replenishing dopamine in the brain; however, the brain might not be the only site requiring attention. Aggregates of α-synuclein appear to accumulate in the gut years prior to the onset of any motor symptoms. Enteroendocrine cells (specialized gut epithelial cells) may be the source of intestinal α-synuclein, as they natively express this protein. Enteroendocrine cells are constantly exposed to gut bacteria and their metabolites because they border the gut lumen. These cells also express the dopamine metabolic pathway and form synapses with vagal neurons, which innervate the gut and brain. Through this connection, Parkinson's disease pathology may originate in the gut and spread to the brain over time. Effective therapeutics to prevent this disease progression are lacking due to a limited understanding of the mechanisms by which α-synuclein aggregation occurs in the gut. We previously proposed a gut bacterial metabolic pathway responsible for the initiation of α-synuclein aggregation that is dependent on the oxidation of dopamine. Here, we develop a new tool, a laser-induced graphene-based electrochemical sensor chip, to track α-synuclein aggregation and dopamine level over time. Using these sensor chips, we evaluated diet-derived catechols dihydrocaffeic acid and caffeic acid as potential inhibitors of α-synuclein aggregation. Our results suggest that these molecules inhibit dopamine oxidation. We also found that these dietary catechols inhibit α-synuclein aggregation in STC-1 enteroendocrine cells. These findings are critical next steps to reveal new avenues for targeted therapeutics to treat Parkinson's disease, specifically in the context of functional foods that may be used to reshape the gut environment.

Discovery of a Gut Bacterial Metabolic Pathway that Drives α-Synuclein Aggregation.

Parkinson's disease (PD) etiology is associated with aggregation and accumulation of α-synuclein (α-syn) proteins in midbrain dopaminergic neurons. Emerging evidence suggests that in certain subtypes of PD, α-syn aggregates originate in the gut and subsequently spread to the brain. However, mechanisms that instigate α-syn aggregation in the gut have remained elusive. In the brain, the aggregation of α-syn is induced by oxidized dopamine. Such a mechanism has not been explored in the context of the gastrointestinal tract, a niche harboring 46% of the body's dopamine reservoirs. Here, we report that Enterobacteriaceae, a bacterial family prevalent in human gut microbiotas, induce α-syn aggregation. More specifically, our in vitro data indicate that respiration of nitrate by Escherichia coli K-12, which results in production of nitrite that mediates oxidation of Fe2+ to Fe3+, creates an oxidizing redox potential. These oxidizing conditions enabled the formation of dopamine-derived quinones and α-syn aggregates. Exposing nitrite, but not nitrate, to enteroendocrine STC-1 cells induced aggregation of α-syn that is natively expressed in these cells, which line the intestinal tract. Taken together, our findings indicate that bacterial nitrate reduction may be critical for initiating intestinal α-syn aggregation.

Human gut Actinobacteria boost drug absorption by secreting P-glycoprotein ATPase inhibitors.

Drug efflux transporters are a major determinant of drug efficacy and toxicity. A canonical example is P-glycoprotein (P-gp), an efflux transporter that controls the intestinal absorption of diverse compounds. Despite a rich literature on the dietary and pharmaceutical compounds that impact P-gp activity, its sensitivity to gut microbial metabolites remains an open question. Surprisingly, we found that the cardiac drug-metabolizing gut Actinobacterium Eggerthella lenta increases drug absorption in mice. Experiments in cell culture revealed that E. lenta produces a soluble factor that post-translationally inhibits P-gp ATPase efflux activity. P-gp inhibition is conserved in the Eggerthellaceae family but absent in other Actinobacteria. Comparative genomics identified genes associated with P-gp inhibition. Finally, activity-guided biochemical fractionation coupled to metabolomics implicated a group of small polar metabolites with P-gp inhibitory activity. These results highlight the importance of considering the broader relevance of the gut microbiome for drug disposition beyond first-pass metabolism.

Emergence of Caenorhabditis elegans as a Model Organism for Dissecting the Gut-Brain Axis.

Accumulating evidence links the gut microbiome to neuronal functions in the brain. Given the increasing prevalence of brain disorders, there is a critical need to understand how gut microbes impact neuronal functions so that targeted therapeutic interventions can be developed. In this commentary, we discuss what makes the nematode Caenorhabditis elegans a valuable model for dissecting the molecular basis of gut microbiome-brain interactions. With a fully mapped neuronal circuitry, C. elegans is an effective model for studying signaling of the nervous system in a context that bears translational relevance to human disease. We highlight C. elegans as a potent but underexploited tool to interrogate the influence of the bacterial variable on the complex equation of the nervous system. We envision that routine use of gnotobiotic C. elegans to examine the gut-brain axis will be an enabling technology for the development of novel therapeutic interventions for brain diseases.

A widely distributed metalloenzyme class enables gut microbial metabolism of host- and diet-derived catechols.

Catechol dehydroxylation is a central chemical transformation in the gut microbial metabolism of plant- and host-derived small molecules. However, the molecular basis for this transformation and its distribution among gut microorganisms are poorly understood. Here, we characterize a molybdenum-dependent enzyme from the human gut bacterium Eggerthella lenta that dehydroxylates catecholamine neurotransmitters. Our findings suggest that this activity enables E. lenta to use dopamine as an electron acceptor. We also identify candidate dehydroxylases that metabolize additional host- and plant-derived catechols. These dehydroxylases belong to a distinct group of largely uncharacterized molybdenum-dependent enzymes that likely mediate primary and secondary metabolism in multiple environments. Finally, we observe catechol dehydroxylation in the gut microbiotas of diverse mammals, confirming the presence of this chemistry in habitats beyond the human gut. These results suggest that the chemical strategies that mediate metabolism and interactions in the human gut are relevant to a broad range of species and habitats.

Inside the human gut there are trillions of bacteria. These microbes are critical for breaking down and modifying molecules that the body consumes (such as nutrients and drugs) and produces (such as hormones). Although metabolizing these molecules is known to impact health and disease, little is known about the specific components, such as the genes and enzymes, involved in these reactions. A prominent microbial reaction in the gut metabolizes molecules by removing a hydroxyl group from an aromatic ring and replacing it with a hydrogen atom. This chemical reaction influences the fate of dietary compounds, clinically used drugs and chemicals which transmit signals between nerves (neurotransmitters). But even though this reaction was discovered over 50 years ago, it remained unknown which microbial enzymes are directly responsible for this metabolism. In 2019, researchers discovered the human gut bacteria Eggerthella lenta produces an enzyme named Dadh that can remove a hydroxyl group from the neurotransmitter dopamine. Now, Maini Rekdal et al. ­ including many of the researchers involved in the 2019 study ­ have used a range of different experiments to further characterize this enzyme and see if it can break down molecules other than dopamine. This revealed that Dadh specifically degrades dopamine, and this process promotes E. lenta growth. Next, Maini Rekdal et al. uncovered a group of enzymes that had similar characteristics to Dadh and could metabolize molecules other than dopamine, including molecules derived from plants and nutrients in food. These Dadh-like enzymes were found not only in the guts of humans, but in other organisms and environments, including the soil, ocean and plants. Plant-derived molecules are associated with human health, and the discovery of the enzymes that break down these products could provide new insights into the health effects of plant-based foods. In addition, the finding that gut bacteria harbor a dopamine metabolizing enzyme has implications for the interaction between the gut microbiome and the nervous system, which has been linked to human health and disease. These newly discovered enzymes are also involved in metabolic reactions outside the human body. Future work investigating the mechanisms and outputs of these reactions could improve current strategies for degrading pollutants and producing medically useful molecules.

Genetic basis for the cooperative bioactivation of plant lignans by Eggerthella lenta and other human gut bacteria.

Plant-derived lignans, consumed daily by most individuals, are thought to protect against cancer and other diseases1; however, their bioactivity requires gut bacterial conversion to enterolignans2. Here, we dissect a four-species bacterial consortium sufficient for all five reactions in this pathway. A single enzyme (benzyl ether reductase, encoded by the gene ber) was sufficient for the first two biotransformations, variable between strains of Eggerthella lenta, critical for enterolignan production in gnotobiotic mice and unique to Coriobacteriia. Transcriptional profiling (RNA sequencing) independently identified ber and genomic loci upregulated by each of the remaining substrates. Despite their low abundance in gut microbiomes and restricted phylogenetic range, all of the identified genes were detectable in the distal gut microbiomes of most individuals living in northern California. Together, these results emphasize the importance of considering strain-level variations and bacterial co-occurrence to gain a mechanistic understanding of the bioactivation of plant secondary metabolites by the human gut microbiome.

A Genomic Toolkit for the Mechanistic Dissection of Intractable Human Gut Bacteria.

Despite the remarkable microbial diversity found within humans, our ability to link genes to phenotypes is based upon a handful of model microorganisms. We report a comparative genomics platform for Eggerthella lenta and other Coriobacteriia, a neglected taxon broadly relevant to human health and disease. We uncover extensive genetic and metabolic diversity and validate a tool for mapping phenotypes to genes and sequence variants. We also present a tool for the quantification of strains from metagenomic sequencing data, enabling the identification of genes that predict bacterial fitness. Competitive growth is reproducible under laboratory conditions and attributable to intrinsic growth rates and resource utilization. Unique signatures of in vivo competition in gnotobiotic mice include an adhesin enriched in poor colonizers. Together, these computational and experimental resources represent a strong foundation for the continued mechanistic dissection of the Coriobacteriia and a template that can be applied to study other genetically intractable taxa.

Discovery and inhibition of an interspecies gut bacterial pathway for Levodopa metabolism.

The human gut microbiota metabolizes the Parkinson's disease medication Levodopa (l-dopa), potentially reducing drug availability and causing side effects. However, the organisms, genes, and enzymes responsible for this activity in patients and their susceptibility to inhibition by host-targeted drugs are unknown. Here, we describe an interspecies pathway for gut bacterial l-dopa metabolism. Conversion of l-dopa to dopamine by a pyridoxal phosphate-dependent tyrosine decarboxylase from Enterococcus faecalis is followed by transformation of dopamine to m-tyramine by a molybdenum-dependent dehydroxylase from Eggerthella lenta These enzymes predict drug metabolism in complex human gut microbiotas. Although a drug that targets host aromatic amino acid decarboxylase does not prevent gut microbial l-dopa decarboxylation, we identified a compound that inhibits this activity in Parkinson's patient microbiotas and increases l-dopa bioavailability in mice.

Cooking shapes the structure and function of the gut microbiome.

Diet is a critical determinant of variation in gut microbial structure and function, outweighing even host genetics1-3. Numerous microbiome studies have compared diets with divergent ingredients1-5, but the everyday practice of cooking remains understudied. Here, we show that a plant diet served raw versus cooked reshapes the murine gut microbiome, with effects attributable to improvements in starch digestibility and degradation of plant-derived compounds. Shifts in the gut microbiota modulated host energy status, applied across multiple starch-rich plants, and were detectable in humans. Thus, diet-driven host-microbial interactions depend on the food as well as its form. Because cooking is human-specific, ubiquitous and ancient6,7, our results prompt the hypothesis that humans and our microbiomes co-evolved under unique cooking-related pressures.

The microbial pharmacists within us: a metagenomic view of xenobiotic metabolism.

Although the importance of human genetic polymorphisms in therapeutic outcomes is well established, the role of our 'second genome' (the microbiome) has been largely overlooked. In this Review, we highlight recent studies that have shed light on the mechanisms that link the human gut microbiome to the efficacy and toxicity of xenobiotics, including drugs, dietary compounds and environmental toxins. Continued progress in this area could enable more precise tools for predicting patient responses and for the development of a new generation of therapeutics based on, or targeted at, the gut microbiome. Indeed, the admirable goal of precision medicine may require us to first understand the microbial pharmacists within.

Using IR vibrations to quantitatively describe and predict site-selectivity in multivariate Rh-catalyzed C-H functionalization.

Achieving selective C-H functionalization is a significant challenge that requires discrimination between many similar C-H bonds. Yet, reaction systems employing Rh2(DOSP)4 and Rh2(BPCP)4 were recently demonstrated to afford high levels of selectivity in the C-H insertion of carbenes into toluene-derived substrates. Herein, we explore the origin of this selectivity through a systematic analysis of substrate and reagent features that alter levels of selectivity from 20 : 1 to 1 : 610 for secondary (or tertiary)-to-primary benzylic C-H functionalization of toluene derivatives. Describing this variation using infrared vibrations and point charges, we have developed a mathematical model from which are identified features of the systems that determine levels of site-selectivity and are applied as predictive factors to describe the selectivity behavior of new substrate/reagent combinations.

Distinctive meta-directing group effect for iridium-catalyzed 1,1-diarylalkene enantioselective hydrogenation.

An iridium-catalyzed asymmetric hydrogenation of 1,1-diarylkenes is described. Employing a novel, modular phosphoramidite ligand, PhosPrOx, in this transformation affords biologically relevant 1,1-diarylmethine products in good enantiomeric ratios (96.5:3.5 to 71:29). We propose that a meta-directing group, 3,5-dimethoxyphenyl, is responsible for the observed enantioselection, the highest reported, to date, for iridium-catalyzed hydrogenation of 1,1-diarylalkenes lacking ortho-directing groups.

Multidimensional steric parameters in the analysis of asymmetric catalytic reactions.

Although asymmetric catalysis is universally dependent on spatial interactions to impart specific chirality on a given substrate, examination of steric effects in these catalytic systems remains empirical. Previous efforts by our group and others have seen correlation between steric parameters developed by Charton and simple substituents in both substrate and ligand; however, more complex substituents were not found to be correlative. Here, we review and compare the steric parameters common in quantitative structure activity relationships (QSAR), a common method for pharmaceutical function optimization, and how they might be applied in asymmetric catalysis, as the two fields are undeniably similar. We re-evaluate steric/enantioselection relationships, which we previously analysed with Charton steric parameters, using the more sophisticated Sterimol parameters developed by Verloop and co-workers in a QSAR context. Use of these Sterimol parameters led to strong correlations in numerous processes where Charton parameters had previously failed. Sterimol parameterization also allows for greater mechanistic insight into the key elements of asymmetric induction within these systems.