Because the human gut microbiota metabolizes a range of catecholic compounds (Figure 1B), we first investigated whether the recently discovered Dadh possessed promiscuous dehydroxylase activity. We evaluated the reactivity of natively purified E. lenta A2 Dadh towards a panel of established or potential host- and diet-derived catechol substrates (Supplementary file 1a and Figure 1—figure supplement 1). This enzyme displayed a narrow substrate scope, metabolizing only dopamine and the structurally related neurotransmitter norepinephrine, which differ only by the presence of a benzylic hydroxyl group (Figure 1C). To identify the elements necessary for substrate recognition by Dadh, we profiled its activity towards synthetic and commercially available dopamine analogs (Figure 1D, Figure 1—figure supplement 1, and Supplementary file 1b). We found that Dadh tolerated only minor modifications to the dopamine scaffold, including a single N-methylation and the presence of additional hydroxyl groups on the aromatic ring (Figure 1E). The catechol moiety was absolutely necessary for activity, and dehydroxylation required that at least one hydroxyl group be in the para position relative to the aminoethyl substituent. These data demonstrated that Dadh specifically recognizes the catecholamine scaffold.

This result prompted us to explore whether the transcriptional regulation of Dadh displayed similar specificity. Thus, we cultured E. lenta A2 in the presence of a subset of the dopamine analogs that we had tested in the previous experiment, measured dehydroxylation using liquid chromatography-mass spectrometry (LC-MS), and profiled the global transcriptome using RNA-seq. We found that the regulation of dadh was also specific for the catecholamine scaffold (Figure 1F, Supplementary file 1c). While the catecholamines dopamine and norepinephrine induced dadh expression and were dehydroxylated by E. lenta, analogs lacking the catechol (analog 1 in Figure 1D) or having a shorter side chain (analog 9 in Figure 1D) did not induce a transcriptional or metabolic response (Figure 1F, Supplementary file 1c) (Maini Rekdal et al., 2019). Together with our biochemical results, these transcriptional data suggest that Dadh may have evolved for the purpose of catecholamine neurotransmitter metabolism in E. lenta. We propose that dopamine is an endogenous substrate of this enzyme, because it was the best substrate both in vitro and in vivo, induced the highest levels of expression in E. lenta, and is produced at substantial levels within the human gastrointestinal tract (Eisenhofer et al., 1997).

In addition to uncovering a preference for the catecholamine scaffold, the substrate scope of Dadh reveals potential mechanistic distinctions between this enzyme and the only other biochemically characterized reductive aromatic dehydroxylase, 4-hydroxybenzoyl Coenzyme A (CoA) reductase (4-HCBR) (Unciuleac et al., 2004). 4-HCBR is a distinct molybdenum dependent-enzyme containing a monomeric molybdopterin co-factor that uses a Birch reduction-like mechanism to remove a single aromatic hydroxyl group from 4-hydroxybenzoyl CoA. While 4-HCBR requires an electron-withdrawing thioester group to stabilize radical anion intermediates (Unciuleac et al., 2004), Dadh does not require an electron-withdrawing substituent and can tolerate additional electron-donating hydroxyl groups (Figure 1D and E, analogs 11–13). We preliminarily propose a mechanism for Dadh in which the dopamine p-hydroxyl group coordinates to the molybdenum center. This could be followed by tautomerization of the m-hydroxyl group to a ketone with protonation of the adjacent carbon atom. Oxygen atom transfer to molybdenum could be accompanied by rearomatization, providing the dehydroxylated product (Figure 1—figure supplement 2). Our proposal is consistent with the postulated mechanisms of other oxygen transfer reactions catalyzed by bis-MGD enzymes (Tenbrink et al., 2011; Hille et al., 2014).

The specificity of Dadh for dopamine suggested this metabolic activity might have an important physiological role in E. lenta. We noted the chemical parallels between catechol dehydroxylation and reductive dehalogenation, a metabolic process in which halogenated aromatics serve as alternative electron acceptors in certain environmental bacteria (Holliger et al., 1998). This insight inspired the hypothesis that dopamine dehydroxylation could serve a similar role in gut bacteria. While we observed no growth benefit when E. lenta was grown in complex BHI medium containing dopamine (Figure 2—figure supplement 1), we found that including dopamine in a minimal medium lacking electron acceptors (basal medium) increased the endpoint optical density of E. lenta cultures (Figure 2A). This growth-promoting effect was only observed in dopamine-metabolizing E. lenta strains, as non-metabolizing strains that express an apparently inactive enzyme (Maini Rekdal et al., 2019) did not gain a growth advantage (Figure 2A and Figure 2—figure supplement 2). The effect of dopamine on E. lenta contrasts with recent studies of digoxin, a drug that is reduced by E. lenta without impacting growth in the same medium (Koppel et al., 2018).

We further investigated the relationship between dopamine and bacterial growth in the metabolizing strain E. lenta A2. The growth increase observed in response to dopamine was dose-dependent (Figure 2—figure supplement 3), mirrored the effects of the known electron acceptors DMSO and nitrate (Koppel et al., 2018; Sperry and Wilkins, 1976), and did not derive from the product of dopamine dehydroxylation, m-tyramine (Figure 2B). Additionally, the growth benefit was directly tied to dopamine dehydroxylation. Inclusion of tungstate in the growth medium, which inactivates the big-MGD cofactor of Dadh, blocked metabolism and inhibited the growth increase. In contrast, inclusion of molybdate in the growth medium did not impact growth or metabolism (Figure 2B and Figure 2—figure supplement 4). Molybdate and tungstate alone did not impact E. lenta A2 growth in the basal medium (Figure 2—figure supplement 5). Taken together, these results indicate that active metabolism of dopamine provides a growth advantage to E. lenta, likely by serving as an alternative electron acceptor.

We next examined whether dopamine could promote E. lenta growth in microbial communities. First, we competed dopamine metabolizing and non-metabolizing E. lenta strains in minimal medium. E. lenta is genetically intractable, preventing the use of engineered plasmids encoding defined fluorescence or antibiotic resistance as markers of strain identity. Instead, we took advantage of intrinsic differences in tetracyline (Tet) resistance to differentiate the closely related strains in pairwise competitions (Bisanz et al., 2018). Inclusion of dopamine in growth medium significantly increased the proportion of the metabolizer relatively to the non-metabolizer in this competition experiment (p<0.001, two-tailed unpaired t-test) (Figure 2C and Figure 2—figure supplement 6). This was driven by the growth increase of the metabolizer rather than a decrease in the non-metabolizer (Figure 2C and Figure 2—figure supplement 6).

Next, we explored the impact of dopamine on Tet-resistant E. lenta in the presence of a defined bacterial community representing the major phylogenetic diversity in the human gut (Figure 2D and Supplementary file 1d) (Devlin et al., 2016; Romano et al., 2015). We found that including dopamine in the medium boosted the growth of metabolizers by an order of magnitude while non-metabolizing strains did not gain a growth advantage (Figure 2D). Finally, we evaluated the impact of dopamine on E. lenta strains present in complex human gut microbiotas. We cultured fecal samples from 24 unrelated subjects ex vivo in the presence and absence of dopamine and used qPCR to assess the abundance of E. lenta and dadh. We found that both dadh and E. lenta significantly increased by an order of magnitude in cultures containing dopamine (p<0.005, two-tailed unpaired t-test) (Figure 2E) (Figure 2—figure supplement 7). Finally, we amplified the full length dadh gene from these cultures and sequenced the region harboring the SNP that distinguishes metabolizing and non-metabolizing strains (Maini Rekdal et al., 2019). These assays indicated that the increase in dadh abundance in the complex communities was accompanied by a shift from a mixture of inactive and active dadh variants to a dominance of the metabolizing R506 variant (p<0.01, Fisher’s exact test) (Figure 2F). Finally, we noticed in these growth assays that a small number of samples did not display an increase in E. lenta or dadh abundance (n = 4 and n = 3 samples, respectively) (Figure 2E and Figure 2—figure supplement 7). While the factors influencing this outcome are unclear, they could include the possibility that these specific communities support the growth of E. lenta in other ways that such that dopamine metabolism does not provide any additional advantage, that these samples contain inhibitory factors, or that organisms not targeted by our primers were responsible for metabolism. Altogether, these results are consistent with the hypothesis that dopamine dehydroxylation can increase the fitness of metabolizing E. lenta strains in microbial communities.

Having uncovered Dadh’s specialized role in gut bacterial dopamine metabolism, we sought to identify additional gut bacterial strains and enzymes that could dehydroxylate other catechol substrates. Among human gut bacteria, only Eggerthella and closely related members of the Actinobacteria phylum have been reported to perform catechol dehydroxylation. For example, Eggerthella metabolizes dopamine (Maini Rekdal et al., 2019) and (+)-catechin (Takagaki and Nanjo, 2015), while related Gordonibacter species dehydroxylate ellagic acid (Selma et al., 2014) and didemethylsecoisolariciresinol (dmSECO), an intermediate in the multi-step biosynthesis of the anti-cancer metabolite enterodiol (Bess et al., 2020). These reports suggest that Actinobacteria could be a promising starting point to identify new dehydroxylating strains and enzymes. Thus, we screened a library of related gut Actinobacteria (Bisanz et al., 2018) (n = 3 replicates for each strain) for metabolism of a range of compounds relevant in the human gut, including plant- and host-derived small molecules, bacterial siderophores, and FDA-approved catecholic drugs (Wilson et al., 2016; Ozdal et al., 2016; Yang et al., 2007) (Supplementary file 1e) (Figure 3A). We initially used a colorimetric assay that detects catechols to assess metabolism, which allowed us to rapidly screen for potential catechol depletion across the collection of 25 strains.

We observed complete depletion of several host and diet-derived catechols in this initial screen (Figure 3—figure supplement 1). We chose to focus on the dehydroxylation of hydrocaffeic acid, (+)-catechin, and DOPAC for further characterization, repeating the incubations with these compounds and using LC-MS/MS to confirm the production of dehydroxylated metabolites. This analysis showed that both DOPAC and hydrocaffeic acid are directly dehydroxylated by members of this library, while (+)-catechin undergoes benzyl ether reduction followed by dehydroxylation into derivative 2, as has been observed previously (Takagaki and Nanjo, 2015) (Figure 3). While (+)-catechin metabolism has been previously linked to Eggerthella (Takagaki and Nanjo, 2015), the dehydroxylation of DOPAC and hydrocaffeic acid has only been previously observed by complex gut microbiota communities (Scheline et al., 1960; Peppercorn and Goldman, 1972). The variability in these activities across closely related gut bacterial strains suggests that distinct enzymes might dehydroxylate different catechols.

We next sought to determine the molecular basis of the dehydroxylation reactions examined above. To test the hypothesis specific rather than promiscuous enzymes were involved, we first established that dehydroxylation is an inducible activity in Gordonibacter and Eggerthella strains (Figure 4—figure supplement 1). This allowed us to use the dehydroxylase activity of cell lysates as a proxy for transcriptional induction and a means of examining dehydroxylase activity. We grew E. lenta A2 in the presence of (+)-catechin, hydrocaffeic acid, and dopamine, and grew G. pamelaeae 3C in the presence of DOPAC. We then screened each anaerobic lysate for its activity towards all of these substrates. Consistent with our prediction, each lysate quantitively dehydroxylated only the catechol substrate with which the strain had been grown. While the E. lenta lysates did not display any promiscuity (Figure 4A), cell lysate from G. pamelaeae grown in the presence of DOPAC displayed reduced activity (<45% conversion) towards hydrocaffeic acid, which structurally resembles DOPAC (Figure 4B). Overall, these results suggest that different catechol substrates induce the expression of distinct dehydroxylase enzymes that are specific in their activity and transcriptional regulation. We expected that these enzymes would likely resemble Dadh, as only molybdenum-dependent enzymes are known to catalyze aromatic dehydroxylation (Maini Rekdal et al., 2019; Hille et al., 2014; Unciuleac et al., 2004).

To identify the molecular basis of (+)-catechin and hydrocaffeic acid dehydroxylation in E. lenta A2, we turned to RNA-seq, the approach that we used previously to identify the dopamine dehydroxylase (Maini Rekdal et al., 2019). We grew E. lenta A2 to early exponential phase and then added each catechol substrate, harvesting the cells after ~1.5 hr of induction. Hydrocaffeic acid and (+)-catechin each upregulated a number of genes (21 and 43, respectively), including two predicted molybdenum-dependent enzymes (Supplementary files 2a and 2b). While one of these predicted molybdenum-dependent enzymes was among the highest upregulated genes in response to each substrate (450-fold upregulated in response to catechin, >2000 fold with hydrocaffeic acid), the expression of the other enzyme was only increased 3-fold relative to the vehicle. Thus, we propose that the most highly upregulated molybdenum-dependent enzyme in each dataset is the most reasonable candidate dehydroxylase. The candidate hydrocaffeic acid dehydroxylase (Elenta-A2_02815, named hcdh) shares 35.3% amino acid identity with Dadh, while the candidate (+)-catechin dehydroxylase (E. lenta-A2_00577, named cadh) shares 50.9% amino acid identity with Dadh (Supplementary files 2a-2c).

To evaluate the involvement of a molybdenum enzyme in each dehydroxylation reaction, we cultured the genetically intractable E. lenta A2 in the presence of tungstate (Maini Rekdal et al., 2019; Rothery et al., 2008). As with dopamine dehydroxylation, tungstate inhibited dehydroxylation of (+)-catechin and hydrocaffeic acid by E. lenta A2 without inhibiting growth in the rich BHI medium, suggesting these activities are indeed molybdenum dependent (Figure 4—figure supplements 2 and 3). Tungstate did not inhibit benzyl ether reduction of (+)-catechin, indicating this step is likely performed by a distinct enzyme (Figure 4—figure supplement 3). Finally, we found that the overall distribution of the genes encoding these the putative hydrocaffeic acid and (+)-catechin dehydroxylating enzymes across closely related Eggerthella strains correlated with metabolism of each substrate (Figure 4C). For example, all Eggerthella strains except AN5LG harbored the putative hydrocaffeic acid dehydroxylase and could dehydroxylate this substrate. Similarly, carriage of the putative catechin dehydroxylase correlated with (+)-catechin metabolism, except for in the case of strain AB12#2, which did not encode for the enzyme but still had low metabolism (<10%) (Figure 4C and Figure 4—source data 1). This suggests that another enzyme might metabolize (+)-catechin in this strain. Overall, these data suggest that Eggerthella uses distinct molybdenum-dependent enzymes dehydroxylate hydrocaffeic acid and (+)-catechin.

We next sought to identify the enzyme responsible for DOPAC dehydroxylation in G. pamelaeae 3C. We added DOPAC to G. pamelaeae 3C cultures at mid-exponential phase and harvested cells after 3 hr of induction when the cultures had reached early stationary phase. In this experiment, G. pamelaeae 3C upregulated 100 different genes, including four distinct molybdenum-dependent enzyme-encoding genes (Supplementary file 2d). One of these genes (C1877_13905) was among the highest upregulated genes across the dataset (>1700 fold induced). To further explore the association between this gene and DOPAC dehydroxylation, we repeated the RNA-seq experiment, growing G. pamelaeae 3C in the presence of DOPAC from the time of inoculation and then harvesting cells in mid-exponential phase as soon we could detect metabolism (12 hr of growth). In this experiment, the same molybdenum-dependent enzyme-encoding gene (C1877_13905) that was highly upregulated in our first experiment (Supplementary file 2e) was among the highest upregulated genes. The only two other molybdenum-dependent enzymes induced in this experiment were expressed at an order of magnitude lower levels (<2.5-fold induced). We propose that the molybdenum-dependent enzyme encoded by C1877_13905 is a likely candidate DOPAC dehydroxylase.

This assignment is also supported by comparative genomics. First, carriage of C1877_13905 (named dodh) correlated with DOPAC dehydroxylation among members of our gut Actinobacterial library (Figure 4C). Consistent with our lysate assays, those organisms harboring this gene also had activity towards hydrocaffeic acid, which could explain the pattern of hydrocaffeic acid metabolism across the gut Actinobacterial library (Figure 4C). Finally, the functionally annotated gene most similar to the candidate DOPAC dehydroxylase is Cldh (45% amino acid ID), a Gordonibacter enzyme recently implicated in the dehydroxylation of the lignan dmSECO (Bess et al., 2020) (Supplementary file 2c). Though this functional assignment awaits biochemical confirmation, we propose that the highest upregulated enzyme across our two independent datasets is the DOPAC dehydroxylase. Interestingly, unlike with the Eggerthella dehydroxylases, tungstate did not inhibit dehydroxylation of DOPAC by G. pamelaeae (Figure 4—figure supplement 3). This may be explained if the dehydroxylating enzyme can use both molybdenum and tungsten for catalysis, as is seen in certain closely related enzymes (Rosner and Schink, 1995).

To biochemically validate one of our candidate dehydroxylases, we adapted the native purification protocol used for Dadh to fractionate the hydrocaffeic acid dehydroxylase activity from E. lenta A2 cell lysates. This yielded an active fraction that contained five major bands as assessed by SDS-PAGE (Figure 4—figure supplement 4) and quantitatively dehydroxylated hydrocaffeic acid into m-hydroxyphenylacetic acid under anaerobic conditions (Figure 4D). We confirmed that the band with the apparent correct size (Figure 4—figure supplement 4) contained the proposed hydrocaffeic acid dehydroxylase (Hcdh, Elenta-A2_02815) (Figure 4—figure supplement 5 and Supplementary file 2f) using proteomics. We also performed an additional set of enzyme assays using this preparation to evaluate the substrate scope of Hcdh. Consistent with our experiments in cell lysates (Figure 4A), we observed dehydroxylation only of hydrocaffeic acid and not of dopamine, (+)-catechin, or DOPAC (Figure 4E). These data biochemically link the newly identified hcdh gene to hydrocaffeic acid dehydroxylation, further supporting the proposal that different enzymes dehydroxylate distinct catechol substrates.

Despite being expected to perform the same type of chemical reaction, the putative catechol dehydroxylases from E. lenta and G. pamelaeae differ in sequence identity, genomic context, and predicted subunit composition (Supplementary file 3a and Figure 4—figure supplement 6). The dopamine, catechin and hydrocaffeic acid dehydroxylases from E. lenta (dadh, cadh and hcdh, respectively) are likely membrane-bound complexes as they co-localize with genes encoding an electron shuttling 4Fe-4S ferredoxin and a putative membrane anchor (Figure 4—figure supplement 6) (Rothery et al., 2008; Rothery and Weiner, 2015). These enzymes all carry a Twin-Arginine-Translocation (TAT) signal sequence, suggesting they are exported from the cytoplasm before the signal sequence is cleaved off. We found no peptide coverage of the TAT signal sequence in the proteomics experiment that identified E. lenta Hcdh, further confirming that this sequence is cleaved in the mature protein as in other membrane-anchored moco enzymes (Figure 4—figure supplement 5) (Iobbi-Nivol and Leimkühler, 2013). In contrast, dodh and similar enzymes from G. pamelaeae do not harbor a TAT signal sequence, are smaller than the E. lenta enzymes, and co-localize with a gene predicted to encode a small electron shuttling 4Fe-4S protein, suggesting they are likely soluble protein complexes (Figure 4—figure supplement 6). These putative G. pamelaeae dehydroxylases are also encoded adjacent to members of the Major Facilitator Superfamily, transporters that may import or export the catechol substrates or dehydroxylated metabolites (Figure 4—figure supplement 6). Altogether, these data indicate the existence of distinct subtypes of molybdenum-dependent catechol dehydroxylases.

Our finding that catechol dehydroxylases and their associated metabolic activities are variably distributed among closely related gut Actinobacteria made us wonder whether human gut microbial communities would harbor similar genetic and metabolic diversity. To address this, we first searched >1800 publicly available human gut metagenomes (Nayfach et al., 2015) for dadh, hcdh, cadh, dodh, and the recently identified cldh (Bess et al., 2020) genes. Although found at generally low abundances, these catechol dehydroxylases were widely but variably distributed across these metagenomes. Dadh and hcdh were the most prevalent (in >70% and>90% of individuals, respectively), followed by cadh (30%), dodh (20%), and cldh (25%) (Figure 5A). Notably, the prevalence of the different genes in metagenomes is consistent with their distribution among individual human gut Actinobacterial isolates (Figure 4C).

To assess the presence of catechol dehydroxylation in complex gut microbiotas, we incubated fecal samples from unrelated humans (n = 12) ex vivo with hydrocaffeic acid, (+)-catechin, and stable-isotope deuterium-labeled dopamine and DOPAC and analyzed dehydroxylation by LC-MS/MS. In this experiment, we observed dehydroxylation of dopamine, hydrocaffeic acid, and DOPAC across the majority of subjects, indicating that metabolic activities of low-abundance gut Actinobacteria are indeed prevalent (Figure 5B–D). However, catechol metabolism varied between compounds and subjects, with some individuals metabolizing all compounds and some metabolizing none (Figure 5B–D). (+)-Catechin was depleted without production of the corresponding dehydroxylated metabolites, consistent with this compound undergoing a wide range of metabolic reactions in complex communities (Figure 5—source data 1) (Takagaki and Nanjo, 2013; van't Slot and Humpf, 2009; Aura et al., 2008).

To investigate whether metabolic variability correlated with the presence of specific dehydroxylase enzymes, we further investigated DOPAC metabolism. We separated the 12 samples into a group of 9 metabolizers and three non-metabolizers (in which no biological replicate displayed dehydroxylation activity). qPCR enumeration in these cultures revealed that the abundance of the candidate DOPAC dehydroxylase gene dodh discriminated metabolizing and nonmetabolizing subjects (p<0.001, unpaired t-test) (Figure 4E), and correlated significantly with dehydroxylation activity within the nine metabolizers (Pearson’s correlation, r = 0.73, R² = 0.53, p<0.05) (Figure 4F). Altogether, these data are consistent with our previous finding that dadh SNP status correlates with dopamine metabolism in human gut microbiotas ex vivo (Maini Rekdal et al., 2019) and suggest that the candidate dehydroxylases may be active in complex gut communities.

We next investigated the relationship of catechol dehydroxylases to other characterized molybdenum-dependent enzymes. These enzymes bear no sequence homology to the only other biochemically characterized aromatic dehydroxylase, 4-HCBR; whereas 4-HCBR belongs to the xanthine oxidase family of molybdenum-dependent enzymes, the catechol dehydroxylases belong to the bis-MGD family of molybdenum-dependent enzymes, suggesting independent evolutionary origins (Hille et al., 2014; Unciuleac et al., 2004; Tenbrink et al., 2011). Further phylogenetic analysis revealed that catechol dehydroxylases form a unique clade within the bis-MGD enzyme family, clustering away from pyrogallol hydroxytransferase (Pht), the only other bis-MGD enzyme known to modify the aromatic ring of a substrate (Messerschmidt et al., 2004) (Figure 6 and Supplementary file 3b). The catechol dehydroxylases are instead most closely related to acetylene hydratase, an enzyme that adds water to acetylene to provide a carbon source for the marine Proteobacterium Pelobacter acetylenicus (Figure 6) (Tenbrink et al., 2011; Rosner and Schink, 1995; Schoepp-Cothenet et al., 2012). A sequence similarity network (SSN) analysis using sequences of bis-MGD enzymes revealed distinct clusters of catechol dehydroxylases, further suggesting these enzymes are functionally different from known family members (Figure 7—figure supplement 1). The clustering of the dehydroxylases in the SSN did not simply reflect the phylogeny of the organisms because additional sequences from both Eggerthella and Gordonibacter were found in clusters containing distinct, biochemically characterized enzymes (Figure 7—figure supplement 2). In addition, we found that the two catechol dehydroxylase-containing clusters also harbored sequences from organisms other than Eggerthella and Gordonibacter (Figure 7—figure supplement 2). Based on these data, we propose that catechol dehydroxylases are a distinct group of molybdenum-dependent enzymes.

To assess the diversity of putative dehydroxylases, we queried the NCBI nucleotide database and our collection of Actinobacterial genomes for homologs of the Eggerthella and Gordonibacter enzymes. Phylogenetic analyses of the resulting sequences revealed a large diversity of putative dehydroxylases, including numerous uncharacterized enzymes encoded in individual Gordonibacter and Eggerthella genomes (Figure 7). This highlights that catechol dehydroxylases likely have diversified within these closely related gut Actinobacteria, that individual gut Actinobacteria can likely metabolize a range of different catechols, and that many substrate-enzyme pairs remain to be discovered. Our analysis also revealed that catechol dehydroxylases are not restricted to human-associated Actinobacteria and are instead part of a larger group of bis-MGD enzymes present in diverse bacteria and even Archaea (Figure 7). These organisms come from mammal-associated, plant-associated, soil, and aquatic habitats. Notable organisms encoding putative dehydroxylases include soil-dwelling Streptomycetes (Wu et al., 2017; Huang et al., 2012), the industrially important anaerobe Clostridium ljungdahlii (Köpke et al., 2010), and a large number of anaerobic bacterial genera known for their ability to degrade aromatic compounds, including Azoarcus, Thauera, Desulfobacula, Geobacter, Desulfumonile, and Desulfitobacterium (Figure 7) (DeWeerd et al., 1991; Wöhlbrand et al., 2013; Butler et al., 2007; Wagner et al., 2012; Cole et al., 1995; Fernández et al., 2014; Molina-Fuentes et al., 2015; Villemur et al., 2006; Pacheco-Sánchez et al., 2019a). The presence of similar enzymes in gut and environmental microbes likely reflects the availability of catechol substrates in many different environments (Figure 7).

As the vast majority of dehydroxylase homologs remain uncharacterized, it is difficult to assign the biochemical activities of the major clades and define the characteristic features of these enzymes. However, we are confident that at least some portion of the sequences captured in this analysis are true catechol dehydroxylases. First, we found that representative sequences from across our phylogenetic tree are more closely related to acetylene hydratase and the Gordonibacter and Eggerthella dehydroxylases than to any other member of the bis-MGD enzyme family, indicating shared evolutionary origins (Supplementary file 3c and Figure 7—figure supplements 3 and 4). Moreover, recent genetic studies have implicated several homologs from environmental bacteria in catechol dehydroxylation. For instance, a putative dehydroxylase is present in Streptomyces biosynthetic gene clusters that produce the potent anti-tumor compounds yatakemycin and CC-1065 (Wu et al., 2017; Huang et al., 2012) (Figure 7). Gene knock-out and complementation studies revealed this enzyme is essential for CC-1065 production and likely catalyzes reductive dehydroxylation of a late-stage biosynthetic intermediate (Wu et al., 2017). Another homolog is present in the 3,5-dihydroxybenzoate (3,5-DHB) degradation operon within the anaerobic soil Proteobacterium Thaeura aromatica (Figure 7). Strains lacking this enzyme exhibit impaired growth on 3,5-DHB as a sole carbon source, suggesting a possible role for this enzyme in metabolizing the one of the two catecholic intermediates involved in this pathway (Molina-Fuentes et al., 2015; Pacheco-Sánchez et al., 2019a; Pacheco-Sánchez et al., 2019b). Based on this analysis, we conclude that the catechol dehydroxylases harbor vast uncharacterized diversity that contributes to both primary and secondary metabolic pathways in habitats beyond the human gut.

Our phylogenetic analysis suggested that catechol dehydroxylase activity is present in a range of microbial habitats, making us curious whether we could detect this metabolism in additional microbial communities. As a first step, we explored catechol dehydroxylation by gut microbiotas of non-human mammals. We assembled a panel of gut microbiota samples from 12 different mammals representing diverse phylogenetic origins and diets (three individuals per mammal) (Reese et al., 2018; Reese et al., 2019) (Figure 8 and Figure 8—figure supplement 1). We cultured these gut communities anaerobically ex vivo, assessed metabolism using a colorimetric assay, and confirmed potential hits using LC-MS/MS (Figure 8—figure supplement 1). We observed catechol dehydroxylation across the gut microbiotas of mammals spanning different diets and phylogenies (Figure 8). Hydrocaffeic acid dehydroxylation occurred in >50% of species, while dopamine and (+)-catechin metabolism were observed in 5/12 and 4/12 animals, respectively (Figure 8). DOPAC was only metabolized by the rat gut microbiota, which was the only community that had activity towards all compounds tested. While a larger sample size is required to reach clear conclusions about possible links between metabolism of specific catechols and individual mammal gut microbiotas, our results clearly demonstrate that catechol dehydroxylation is found in distantly related mammal gut microbiotas that have large differences in species composition and gene content (Reese et al., 2018; Reese et al., 2019; Coelho et al., 2018). This finding further reinforces the relevance of catechol dehydroxylation to variety of different microbial habitats.

The following chemicals were used in this study: tetracycline (Sigma Aldrich, catalog# 87128–25G), p-tyramine (Sigma Aldrich, catalog# T2879-1G), DL-3,4-Dihydroxymandelic acid (Carbo Synth, catalog# FD22118), protocatechuic Acid (Millipore Sigma, catalog# 37580–25 G-F), DL norepinephrine (Millipore Sigma, catalog# A7256-1G), L-norepinephrine (Matrix Scientific, catalog# 037592–500 MG) L-epinephrine (Alfa Aesar, catalog# L04911.06), DL-epinephrine (Sigma Aldrich, catalog# E4642-5G), 3,4-dihydroxyphenylacetic acid (Millipore Sigma, catalog# 850217–1G), 3,4-dihydroxyhydrocinnamic acid (hydrocaffeic acid) (Millipore Sigma, catalog# 102601–10G), caffeic acid (Millipore Sigma, catalog# C0625-2G), (+)-catechin hydrate (Millimore Sigma, catalog# C1251-5G), (+/–)-catechin hydrate (Millipore Sigma, catalog# C1788-500MG), (–)-Epicatechin (Millipore Sigma, catalog# E1753-1G), L-(-)-a-Methyldopa (Chemcruz, catalog# sc-203092), 2,3-dihydroxybenzoic acid (Millipore Sigma, catalog# 126209–5G), R-(–)-apomorphine hydrochloride hemihydrate (Sigma Aldrich, catalog# A4393-100MG), hydroxytyrosol (Ava Chem Scientific, catalog# 2528), enterobactin (generous gift from Prof. Elizabeth Nolan, MIT), fenoldopam mesylate (Sigma Aldrich, catalog# SML0198-10MG), 5-hydroxydopamine (Sigma Aldrich, catalog# 151564–100G), 6-hydroxydopamine (Sigma Aldrich, catalog #H4381-100MG), 3-methoxytyramine (Sigma Aldrich, catalog# M4251-100MG), 3,4-dihydroxybenzylamine (Sigma Aldrich, catalog# 858781–250 MG), N-methyldopamine (Santa Cruz Biotechnology, catalog# sc-358430A), 4-(2-aminoethyl)benzene-1,3-diol (Enamine, catalog # EN300-65185), m-tyramine (Chemcruz, catalog# sc-255257), 3-hydroxyphenylacetic acid (Sigma Aldrich, catalog# H49901-5G), 3-hydroxyphenylpropionic acid (Toronto Research Chemicals, catalog# H940090), L-dopa (Oakwood Chemical, catalog# 358380–25 g), dopamine (Sigma-Aldrich, catalog# PHR1090-1G, or Millipore Sigma, catalog# H8502-25G), m-tyramine (Santa Cruz Biotechnology, catalog# sc-255257), carbidopa (Sigma-Aldrich, catalog# PHR1655-1G), L-arginine (Sigma-Aldrich, catalog# A5006-100G), sodium molybdate (Sigma-Aldrich, catalog # 243655–100G), sodium tungstate (72069–25G), SIGMAFAST protease inhibitor tablets (Sigma-Aldrich, catalog#: S8830), benzyl viologen (Sigma-Aldrich, catalog# 271845–250 mg), methyl viologen (Sigma-Aldrich, catalog# 856177–1 g), diquat (Sigma-Aldrich, catalog# 45422–250 mg), sodium dithionite (Sigma-Aldrich, catalog# 157953–5G), 3,4-dihydroxyphenylacetic acid (ring-d3, 2,2-d2, 98%) (Cambridge Isotope Laboratories, catalog #DLM-2499–0.01), dopamine HCl (1,1,2,2-d4, 97–98%) (Cambridge Isotope Laboratories, catalog #DLM-2498–0.1). LC-MS grade acetonitrile and methanol for LC-MS analyses were purchased from Honeywell Burdick and Jackson or Sigma-Aldrich. Brain Heart Infusion (BHI) broth was purchased from Beckton Dickinson (catalog# 211060) or from VWR (catalog# 95021–488).

All bacterial culturing work was performed in an anaerobic chamber (Coy Laboratory Products) under an atmosphere of 10% hydrogen, 10% carbon dioxide, and nitrogen as the balance, unless otherwise noted. Hungate tubes were used for anaerobic culturing unless otherwise noted (Chemglass, catalog# CLS-4209–01). All lysate work and biochemical experiments were performed in an anaerobic chamber (Coy Laboratory Products) situated in a cold room at 4°C under an atmosphere of 10% hydrogen and nitrogen as the balance. Gut Actinobacterial strains were grown on BHI containing 1% arginine (w/v) to obtain isolated colonies for culturing.

All genomic DNA (gDNA) was extracted from bacterial cultures using the DNeasy UltraClean Microbial Kit (Qiagen, catalog # 12224–50) according to the manufacturer’s protocol.

Method A: Samples were analyzed using an Agilent technologies 6410 Triple Quad LC/MS and a Dikma Technologies Inspire Phenyl column (4.6 × 150 mm, 5 μm; catalog #81801). The flow rate was 0.5 mL min⁻¹ using 0.1% formic acid in water as mobile phase A and 0.1% formic acid in acetonitrile as mobile phase B. The column temperature was maintained at room temperature. The following gradient was applied: 0–2 min: 0% B isocratic, 2–9 min: 0–10% B, 9–11 min: 10–95% B, 11–15 min: 95% B isocratic, 15–18 min: 95–0% B, 18–21 min: 0% B isocratic. For mass spectrometry, the source temperature was 300°C, and the masses of dopamine (precursor ion m/z = 154.3, daughter ion m/z = 137.3), and tyramine (precursor ion m/z = 138.3, daughter ion m/z = 121.3) were monitored at a collision energy of 15 mV and fragmentor setting of 135 in positive MRM mode.

Method B: Samples were analyzed using an Agilent technologies 6410 Triple Quad LC/MS and a Thermo Scientific Acclaim Polar Advantage II column (3 µM, 120A, 2.1*150 mm, product #: 063187). The flow rate was 0.2 mL min⁻¹ using 0.1% formic acid in water as mobile phase A and methanol as mobile phase B. The following gradient was applied: 0–4 min: 50% B isocratic, 4–7 min: 50–99%, 7–9 min: 99–50%, 9–13 min: 50% B isocratic. For mass spectrometry, the source temperature was 300°C, and the masses of trihydroxydopamine (precursor ion m/z = 170.3, daughter ion m/z = 153.3), dopamine (precursor ion m/z = 154.3, daughter ion m/z = 137.3), phenylethylamine (precursor ion m/z = 122.3, daughter ion m/z = 105.2), and tyramine (precursor ion m/z = 138.3, daughter ion m/z = 121.3) were monitored at a collision energy of 15 mV and fragmentor setting of 135 in positive MRM mode.

Method C: Samples were analyzed using an Agilent technologies 6530 Accurate-Mass Q-TOF LC/MS and a Dikma Technologies Inspire Phenyl column (4.6 × 150 mm, 5 μm; catalog #81801). The flow rate was 0.4 mL min⁻¹ using 0.1% formic acid in water as mobile phase A and 0.1% formic acid in acetonitrile as mobile phase B. The column temperature was maintained at room temperature. The following gradient was applied: 0–2 min: 5% B isocratic, 2–25 min: 0–95% B, 25–30 min: 95% B isocratic, 30–40 min: 95–5% B. For the MS detection, the ESI mass spectra data were recorded in positive mode for a mass range of m/z 50 to 3000. A mass window of ±0.005 Da was used to extract the ion of [M+H].

Method D: Samples were analyzed using an Agilent technologies 6530 Accurate-Mass Q-TOF LC/MS and a Dikma Technologies Inspire Phenyl column (4.6 × 150 mm, 5 μm; catalog #81801). The flow rate was 0.4 mL min⁻¹ using 0.1% formic acid in water as mobile phase A and 0.1% formic acid in acetonitrile as mobile phase B. The column temperature was maintained at room temperature. The following gradient was applied: 0–2 min: 5% B isocratic, 2–25 min: 0–95% B, 25–30 min: 95% B isocratic, 30–40 min: 95–5% B. For the MS detection, the ESI mass spectra data were recorded in negative mode for a mass range of m/z 50 to 3000. A mass window of ±0.005 Da was used to extract the ion of [M+H].

Method E: Samples were analyzed using an Agilent technologies 6410 Triple Quad LC/MS and a Thermo Scientific Acclaim Polar Advantage II column (3 µM, 120A, 2.1*150 mm, product #: 063187). The flow rate was 0.2 mL min⁻¹ using 0.1% formic acid in water as mobile phase A and methanol as mobile phase B. The following gradient was applied: 0–4 min: 50% B isocratic, 4–7 min: 50–99%, 7–9 min: 99–50%, 9–13 min: 50% B isocratic. For mass spectrometry, the source temperature was 300°C, and the masses of catechin (precursor ion m/z = 289.2, daughter ion m/z = 109.1), benzyl ether reduced catechin (precursor ion m/z = 291.2, daughter ion m/z = 123.1), benzyl ether reduced, dehydroxylated catechin (precursor ion m/z = 275.2, daughter ion m/z = 107.1) were monitored at a collision energy of 15 mV and fragmentor setting of 135 in negative MRM mode.

Method F: Samples were analyzed using an Agilent technologies 6410 Triple Quad LC/MS and a Thermo Scientific Acclaim Polar Advantage II column (3 µM, 120A, 2.1*150 mm, product #: 063187). The flow rate was 0.2 mL min⁻¹ using 0.1% formic acid in water as mobile phase A and methanol as mobile phase B. The following gradient was applied: 0–4 min: 50% B isocratic, 4–7 min: 50–99%, 7–9 min: 99–50%, 9–13 min: 50% B isocratic. For mass spectrometry, the source temperature was 300°C, and the masses of hydrocaffeic acid (precursor ion m/z = 181.2, daughter ion m/z = 137.2), hydroxyphenylpropionic acid (precursor ion m/z = 165.1, daughter ion m/z = 121.2), DOPAC (precursor ion m/z = 167.2, daughter ion m/z = 123.2), and hydroxyphenylacetic acid (precursor ion m/z = 151.3, daughter ion m/z = 107.3) were monitored at a collision energy of 15 mV and fragmentor setting of 135 in negative MRM mode.

Method G: Samples were analyzed using an Agilent technologies 6410 Triple Quad LC/MS and a Thermo Scientific Acclaim polar advantage II column (3 µM, 120A, 2.1*150 mm, product #: 063187). The flow rate was 0.2 mL min⁻¹ using 0.1% formic acid in water as mobile phase A and methanol as mobile phase B. The following gradient was applied: 0–4 min: 50% B isocratic, 4–7 min: 50–99%, 7–9 min: 99–50%, 9–13 min: 50% B isocratic. For mass spectrometry, the source temperature was 275°C, and the masses of norepinephrine (precursor ion m/z = 170.1, daughter ion m/z = 152.1) and octopamine (precursor ion m/z = 154.2, daughter ion m/z = 136.1) were monitored at a collision energy of 5 mV and fragmentor setting of 135 in positive MRM mode.

Method H: Samples were analyzed using an Agilent technologies 6410 Triple Quad LC/MS and a Thermo Scientific Acclaim Polar Advantage II column (3 µM, 120A, 2.1*150 mm, product #: 063187). The flow rate was 0.2 mL min⁻¹ using 0.1% formic acid in water as mobile phase A and methanol as mobile phase B. The following gradient was applied: 0–4 min: 50% B isocratic, 4–7 min: 50–99%, 7–9 min: 99–50%, 9–13 min: 50% B isocratic. For mass spectrometry, the source temperature was 275°C, and the masses of caffeic acid (precursor ion m/z = 179.2, daughter ion m/z = 135.2) and coumaric acid (precursor ion m/z = 163.3, daughter ion m/z = 119.2) were monitored at a collision energy of 5 mV and fragmentor setting of 135 in negative MRM mode.

Method I: Samples were analyzed using an Agilent technologies 6410 Triple Quad LC/MS and a Thermo Scientific Acclaim Polar Advantage II column (3 µM, 120A, 2.1*150 mm, product #: 063187). The flow rate was 0.2 mL min⁻¹ using 0.1% formic acid in water as mobile phase A and methanol as mobile phase B. The following gradient was applied: 0–4 min: 50% B isocratic, 4–7 min: 50–99%, 7–9 min: 99–50%, 9–13 min: 50% B isocratic. For mass spectrometry, the source temperature was 300°C, and the masses of dihydroxybenzoic acid (precursor ion m/z = 153.1, daughter ion m/z = 137.1) and hydroxybenzoic acid (precursor ion m/z = 137.1, daughter ion m/z = 93.2) were monitored at a collision energy of 15 mV and fragmentor setting of 135 in negative MRM mode.

Method J: Samples were analyzed using an Agilent technologies 6410 Triple Quad LC/MS and a Thermo Scientific Acclaim Polar Advantage II column (3 µM, 120A, 2.1*150 mm, product #: 063187). The flow rate was 0.2 mL min⁻¹ using 0.1% formic acid in water as mobile phase A and methanol as mobile phase B. The following gradient was applied: 0–4 min: 50% B isocratic, 4–7 min: 50–99%, 7–9 min: 99–50%, 9–13 min: 50% B isocratic. For mass spectrometry, the source temperature was 300°C, and the masses of norepinephrine (precursor ion m/z = 184.1, daughter ion m/z = 166.1) and dehydroxynorepinephrine (precursor ion m/z = 168.1, daughter ion m/z = 150.1) were monitored at a collision energy of 15 mV and fragmentor setting of 135 in positive MRM mode.

Method K: Samples were analyzed using an Agilent technologies 6410 Triple Quad LC/MS and a Thermo Scientific Acclaim Polar Advantage II column (3 µM, 120A, 2.1*150 mm, product #: 063187). The flow rate was 0.2 mL min⁻¹ using 0.1% formic acid in water as mobile phase A and methanol as mobile phase B. The following gradient was applied: 0–4 min: 50% B isocratic, 4–7 min: 50–99%, 7–9 min: 99–50%, 9–13 min: 50% B isocratic. For mass spectrometry, the source temperature was 300°C, and the masses of dihydroxybenzylamine (precursor ion m/z = 140.3, daughter ion m/z = 123.2) and hydroxybenzylamine (precursor ion m/z = 124.3, daughter ion m/z = 107.2) were monitored at a collision energy of 15 mV and fragmentor setting of 135 in positive MRM mode.

Method L: Samples were analyzed using an Agilent technologies 6410 Triple Quad LC/MS and a Thermo Scientific Acclaim Polar Advantage II column (3 µM, 120A, 2.1*150 mm, product #: 063187). The flow rate was 0.2 mL min⁻¹ using 0.1% formic acid in water as mobile phase A and methanol as mobile phase B. The following gradient was applied: 0–4 min: 50% B isocratic, 4–7 min: 50–99%, 7–9 min: 99–50%, 9–13 min: 50% B isocratic. For mass spectrometry, the source temperature was 300°C, and the masses of 3-aminotyramine (precursor ion m/z = 153.3, daughter ion m/z = 136.2) and 3-aminophenylethylamine (precursor ion m/z = 137.3, daughter ion m/z = 120.2) were monitored at a collision energy of 15 mV and fragmentor setting of 135 in positive MRM mode.

Method M: Samples were analyzed using an Agilent technologies 6410 Triple Quad LC/MS and a Thermo Scientific Acclaim Polar Advantage II column (3 µM, 120A, 2.1*150 mm, product #: 063187). The flow rate was 0.2 mL min⁻¹ using 0.1% formic acid in water as mobile phase A and methanol as mobile phase B. The following gradient was applied: 0–4 min: 50% B isocratic, 4–7 min: 50–99%, 7–9 min: 99–50%, 9–13 min: 50% B isocratic. For mass spectrometry, the source temperature was 300°C, and the masses 3-methoxytyramine (precursor ion m/z = 151.1, daughter ion m/z = 91.1) and 3-methoxyphenylethylamine (precursor ion m/z = 135.1, daughter ion m/z = 75.1) were monitored at a collision energy of 15 mV and fragmentor setting of 135 in positive MRM mode.

Method N: Samples were analyzed using an Agilent technologies 6410 Triple Quad LC/MS and a Thermo Scientific Acclaim Polar Advantage II column (3 µM, 120A, 2.1*150 mm, product #: 063187). The flow rate was 0.2 mL min⁻¹ using 0.1% formic acid in water as mobile phase A and methanol as mobile phase B. The following gradient was applied: 0–4 min: 50% B isocratic, 4–7 min: 50–99%, 7–9 min: 99–50%, 9–13 min: 50% B isocratic. For mass spectrometry, the source temperature was 300°C, and the masses 3-hydroxytyrosol (precursor ion m/z = 153.2, daughter ion m/z = 123.1) and tyrosol (precursor ion m/z = 137.2, daughter ion m/z = 107.1) were monitored at a collision energy of 15 mV and fragmentor setting of 135 in negative MRM mode.

Method O: Samples were analyzed using an Agilent technologies 6410 Triple Quad LC/MS and a Thermo Scientific Acclaim Polar Advantage II column (3 µM, 120A, 2.1*150 mm, product #: 063187). The flow rate was 0.15 mL min⁻¹ using 0.1% formic acid in water as mobile phase A and methanol as mobile phase B. The following gradient was applied: 0–4 min: 50% B isocratic, 4–7 min: 50–99%, 7–9 min: 99–50%, 9–13 min: 50% B isocratic. For mass spectrometry, the source temperature was 300°C, and the masses of d5-DOPAC (precursor ion m/z = 172.2, daughter ion m/z = 128.2) and d5-hydroxyphenylacetic acid (precursor ion m/z = 156.3, daughter ion m/z = 113.3) were monitored at a collision energy of 15 mV and fragmentor setting of 135 in negative MRM mode.

Method P: Samples were analyzed using an Agilent technologies 6410 Triple Quad LC/MS and a Thermo Scientific Acclaim Polar Advantage II column (3 µM, 120A, 2.1*150 mm, product #: 063187). The flow rate was 0.2 mL min⁻¹ using 0.1% formic acid in water as mobile phase A and methanol as mobile phase B. The following gradient was applied: 0–4 min: 50% B isocratic, 4–7 min: 50–99%, 7–9 min: 99–50%, 9–13 min: 50% B isocratic. For mass spectrometry, the source temperature was 300°C, and the masses of d4-dopamine (precursor ion m/z = 158.3, daughter ion m/z = 141.3), and d4-tyramine (precursor ion m/z = 142.3, daughter ion m/z = 125.3) were monitored at a collision energy of 15 mV and fragmentor setting of 135 in positive MRM mode.

The colorimetric assay for dopamine dehydroxylation was based on the Arnow test (Arnow, 1937). Briefly, 50 µL of 0.5 M aqueous HCl was added to 50 µL of culture supernatant. After mixing, 50 µL of an aqueous solution containing both sodium molybdate and sodium nitrite (0.1 g/mL each) was added, which produced a yellow color. Finally, 50 µL of 1 M aqueous NaOH was added followed by pipetting up and down to mix. This allowed the characteristic pink color to develop. Absorbance was measured at 500 nm immediately using a Synergy HTX Multi-Mode Microplate Reader (BioTek) or SPECTROstar Nano (BMG LABTECH).

Active fractions from the size exclusion chromatography described above were combined and then diluted in 20 mM Tris pH 8 containing 250 mM NaCl to a final enzyme concentration of 0.1 µM. The enzyme mixture was transferred the wells of a 96 well plate, for a final volume of 50 µL in each well (VWR, catalog# 82006–636). 1 µL of substrate (in water, or 50:50 water:DMF for caffeic acid and catechin substrates) was then added at a final concentration of 500 µM. Following this, 1 µL of a solution containing electron donors (final concentration 1 mM each of methyl viologen, 1 mM diquat dibromide, 1 mM benzyl viologen, all dissolved in water) and 2 µL of sodium dithionite (2 mM final concentration, dissolved in water) were added. The resulting solution was mixed by pipetting and the 96-well plate was then sealed tightly with an aluminum seal. The enzyme assay mixtures were left at room temperature in an anaerobic chamber for 22 hr to allow dehydroxylation to proceed. The enzyme reaction mixtures were quenched by bringing the samples out of the anaerobic chamber and freezing at –20°C. These mixtures were then diluted 1:10 with LC-MS grade methanol and analyzed by LC-MS/MS. For the screen with physiologically relevant catechol substrates, samples containing caffeic acid were analyzed using Method H, hydrocaffeic acid and DOPAC were analyzed using Method F, catechin was analyzed using Method E, protocathecuic acid was analyzed using Method I, epinephrine was analyzed using Method J, norepinephrine was analyzed using Method G, and ellagic acid was analyzed using Method D. For the screen with dopamine analogs, all monohydroxylated, dihydroxylated, and trihydroxylated phenylethylamine analogs were analyzed using method B, N-methyldopamine was analyzed using Method C, methoxytyramine was analyzed using Method M, dihydroxybenzylamine was analyzed using Method K, hydroxytyrosol was analyzed using Method N, and aminotyramine was analyzed using Method L.

Cells were cultured in 96-well plates and all experiments were performed anaerobically. The strains screened for dopamine dehydroxylation have been previously described (Koppel et al., 2018; Bisanz et al., 2018). E. lenta A2 was inoculated from a single colony into 10 mL of BHI liquid medium and grown for 48 hr at 37°C to provide turbid starter cultures. These were diluted 1:10 in triplicate into 200 µL of fresh BHI medium containing 500 µM substrate (p-tyramine, dopamine, 3,4-dihydroxybenzylamine, or DL-norepinephrine). These cultures were grown for 48 hr at 37°C. Cultures were harvested by centrifugation at 4000 rpm for 10 min, and the supernatants were diluted 1:10 with LC-MS grade methanol. Samples containing dopamine or p-tyramine were analyzed using Method B, norepinephrine was analyzed using Method G, dihydroxybenzylamine was analyzed using Method K.

We repeated the setup previously used in the RNA-sequencing experiment with dopamine (Maini Rekdal et al., 2019). Turbid 48 hr starter cultures of E. lenta in BHI medium were inoculated 1:100 into 5 mL of BHI medium containing 1% arginine and 10 mM formate, and cultures were grown at 37°C anaerobically. When the cultures reached OD₆₀₀ = 0.200, hydrocaffeic acid, (+)-catechin, p-tyramine, 3,4-dihydroxybenzylamine, DL-norepinephrine, or N-methyldopamine were added at final concentrations of 500 µM to triplicate cultures. All compounds except for (+)-catechin were dissolved in water; (+)-catechin was dissolved in DMF. Control cultures contained vehicle (water or DMF). Cultures were harvested when they reached OD₆₀₀ = 0.500. They were centrifuged for 15 min at 4000 rpm, and cell pellets were re-suspended in 500 µL Trizol reagent (ThermoFisher, catalog#: 15596026). Total RNA was isolated by first bead beating to lyse cells and then using the Zymo Research Direct-Zol RNA MiniPrep Plus kit (Catalog # R2070) according to the manufacturer’s protocol. Illumina cDNA libraries were generated using a modified version of the RNAtag-Seq protocol (Shishkin et al., 2015). Briefly, 500 ng of total RNA was fragmented, depleted of genomic DNA, and dephosphorylated prior to its ligation to DNA adapters carrying 5’-AN8-3’ barcodes with a 5’ phosphate and a 3’ blocking group. Barcoded RNAs were pooled and depleted of rRNA using the RiboZero rRNA depletion kit (Epicentre). These pools of barcoded RNAs were converted to Illumina cDNA libraries in three main steps: (i) reverse transcription of the RNA using a primer designed to the constant region of the barcoded adaptor; (ii) addition of a second adapter on the 3’ end of the cDNA during reverse transcription using SmartScribe RT (Clonetech) as described (Shishkin et al., 2015); (iii) PCR amplification using primers that target the constant regions of the 3’ and 5’ ligated adaptors and contain the full sequence of the Illumina sequencing adaptors. cDNA libraries were sequenced on Illumina HiSeq 2500. For the analysis of RNAtag-Seq data, reads from each sample in the pool were identified based on their associated barcode using custom scripts, and up to one mismatch in the barcode was allowed with the caveat that it did not enable assignment to more than one barcode. Barcode sequences were removed from the first read as were terminal G’s from the second read that may have been added by SMARTScribe during template switching. Reads were aligned to the Eggerthella lenta A2 genome using BWA (Li and Durbin, 2009) and read counts were assigned to genes and other genomic features using custom scripts. Differential expression analysis was conducted with DESeq2 (Love et al., 2014) and/or edgeR (Robinson et al., 2010).

Method 1 (compound added at mid-exponential phase): Turbid 48 hr starter cultures of G. pamelaeae 3C grown in BHI medium were inoculated 1:100 into triplicate Hungate tubes containing 20 mL BHI medium with 10 mM formate. When cultures reached OD₆₀₀ = 0.110, DOPAC (0.5 mM final) or vehicle (water) was added to the cultures. The cultures were then grown at 37°C anaerobically and harvested when they reached OD₆₀₀ = 0.185. They were centrifuged, and cell pellets were re-suspended in 500 µL Trizol reagent (ThermoFisher, catalog#: 15596026).

Method 2 (compound added at the beginning of growth): Turbid 48 hr starter cultures of G. pamelaeae 3C grown in BHI medium were inoculated 1:100 into triplicate hungate tubes containing 20 mL BHI with 10 mM formate and DOPAC (0.5 mM final) or vehicle (water). These cultures were then left to grow at 37°C anaerobically. When cultures reached OD₆₀₀ = 0.110, they were harvested. They were centrifuged, and cell pellets were re-suspended in 500 µL Trizol reagent (ThermoFisher, catalog#: 15596026).

RNA extraction and sequencing: this was performed using the exactly same setup as described above, except the reads were aligned to the genome of Gordonibacter pamelaeae 3C.

Cells were cultured in Hungate tubes and all experiments were performed anaerobically. E. lenta A2 was inoculated from a single colony into 10 mL BHI liquid medium and grown for 48 hr at 37°C to provide turbid starter cultures. These were diluted 1:100 in triplicate into 5 mL BHI medium containing either 0.5 mM dopamine or vehicle. Growth was assessed by measuring the optical density at 600 nm using a Genesys 20 spectrophotometer (Thermo Scientific).

The medium was prepared as described previously, with minor modifications (Maini Rekdal et al., 2019). A 100-fold stock solution of salts was first prepared by dissolving 100 g NaCl, 50 g MgCl₂•6H₂O, 20 g KH₂PO₄, 30 g NH₄Cl, 30 g KCl, 1.5 g CaCl₂ × 2H₂O in 1 L of water. Then, 10 mL of this solution was added to 1 L of water containing 1 g yeast extract (Beckton Dickinson #288260), 1 g tryptone (Beckton Dickinson #21175), and 0.25 mL of 0.1% resazurin (dissolved in MilliQ water). This medium was autoclaved. Following autoclaving, the medium was left to cool for 15 min in an atmosphere of air (outside the anaerobic chamber). After cooling, the following components were added using sterile technique: 10 mL of ATCC Trace element mix (ATCC, catalog# MD-TMS), 10 mL of Vitamin Supplement (ATCC, catalog# MD-VS), solid NaHCO₃ (SIGMA, 2.52 g, to give 30 mM) and solid L-cysteine HCl (SIGMA, 63 mg, to give 0.4 mM). The medium had a final pH of 7.2–7.3. The medium was then sparged with nitrogen gas (for how long) and was brought into the anaerobic chamber to equilibrate for at least 30 hr prior to use. In all experiments utilizing the basal medium, except for those experiments performed with Gordonibacter pamelaeae 3C or the screen for catechol metabolism by mammalian gut microbiota samples, sodium acetate was added at a final concentration of 10 mM at the time of bacterial inoculation. In experiments performed with Gordonibacter pamelaeae 3C, sodium formate was added at a final concentration of 10 mM. In the ex vivo experiments with the mammalian gut microbiota, neither acetate nor formate were added to the basal medium.

Cells were cultured in hungate tubes and all experiments were performed anaerobically. E. lenta strains were inoculated from single colonies into 10 mL of BHI liquid medium and grown for 48–72 hr at 37°C to provide turbid starter cultures. These were diluted 1:100 in triplicate into 5 mL of basal medium containing 10 mM acetate and either 1 mM dopamine (in water) or vehicle (water). If applicable. molybdate (0.5 mM), tungstate (0.5 mM), DMSO (14 mM), or nitrate (1 mM) were added at the time of inoculation. Cultures were grown anaerobically for 36–72 hr at 37°C. Endpoint growth was assessed by measuring the optical density at 600 nm using a Genesys 20 spectrophotometer (Thermo Scientific). Catechol dehydroxylation was assessed at the end of growth in culture supernatants using the colorimetric method.

Cells were cultured in hungate tubes and all experiments were performed anaerobically. E. lenta strains W1BHI6 (Tet resistant non-metabolizer, and Valencia (Tet sensitive metabolizer) were inoculated from single colonies into individual tubes containing 10 mL of BHI liquid medium and grown for 48 hr at 37°C to provide turbid starter cultures. For the competition experiment, 50 µL of each starter culture of the two competing strains was combined in triplicate in 5 mL of basal medium containing 10 mM acetate and either 1 mM dopamine or vehicle (water). Following inoculation, cultures were grown anaerobically for 72 hr at 37°C. At the end of the incubation, growth of E. lenta was assessed. Cultures were serially diluted in PBS under anaerobic conditions, and 8 µL of each serial dilution (10⁻¹ through 10⁻⁷) was plated onto BHI plates containing 1% arginine (w/v) with and without 10 µg/mL Tetracycline using a spot plating method. Plates were grown at 37°C for 72 hr following by counting of colonies. To calculate the proportion of metabolizer in the W1BHI6/Valencia competition experiment, we selected a dilution where distinct colonies were clearly visible (10⁻⁴-10⁻⁵) and counted the number of colonies growing on the BHI 1% arginine Tetracycline plates (W1BHI6) as well as the colonies growing on the BHI 1% arginine plates (Both Valencia and W1BHI6). To get the number of metabolizer (Valencia) colonies, we subtracted the number of Tetraycline resistant colonies from the colonies on the no Tetracycline plate.

Cells were cultured in hungate tubes and all experiments were performed anaerobically. E. lenta strains, as well as Enterococcus faecalis OGR1F, Escherichia coli MG1655, Bacteroides fragilis ATCC 25285, Clostridium sporogenes ATCC 15579, Edwarsiella tarda ATCC 23685, were inoculated from single colonies into individual tubes containing 10 mL of BHI liquid medium and grown for 48–72 hr at 37°C to provide turbid starter cultures. Growth was assessed by measuring the optical density at 600 nm using a Genesys 20 spectrophotometer (Thermo Scientifc). These starter cultures were then diluted to a final OD₆₀₀ of 0.100 in BHI medium anaerobically. The defined community was created by combining equal volumes of all strains (after diluting each culture to OD₆₀₀ = 0.100) except for E. lenta. The community was then inoculated 1:100 in triplicate into 5 mL basal medium containing 10 mM acetate and either 1 mM dopamine or vehicle. E. lenta strains were then added by diluting the E. lenta starter cultures (normalized to OD₆₀₀ = 0.100) 1:50 into the tubes containing the defined community. Cultures were then grown anaerobically for 72 hr at 37°C. At the end of the incubation, growth of E. lenta was assessed. Cultures were serially diluted in PBS under anaerobic conditions, and 8 µL of each serial dilution (10⁻¹ through 10⁻⁷) was plated onto BHI plates containing 1% arginine (w/v) and 10 µg/mL Tetracycline (spot plating method). Plates were grown at 37°C for 72 hr following by counting of colonies.

The human fecal samples used in this study have been previously described (Maini Rekdal et al., 2019). To prepare them for culturing, all samples were resuspended anaerobically in anaerobic PBS at a final concentration of 0.1 g/mL. The mixture was vortexed to produce a homogenous slurry and was then left for 30 min to let particulates settle. Aliquots of the supernatant were dissolved 50:50 with 40% glycerol and flash-frozen in liquid nitrogen, creating slurries that were used for anaerobic culturing of human fecal samples. Slurries were stored at –80°C and were thawed anaerobically at room temperature at the time of use.

This procedure was performed in an anaerobic chamber (Coy Laboratory Products, atmospheric conditions: 20% CO₂, 2–2.5% H₂, and the balance N₂)—equilibrating media and consumables to the atmosphere prior to use—until centrifugation, which was performed using a benchtop centrifuge. The 96-well plates used in this experiment were purchased from VWR (catalog# 10861–562). Into the wells of flat-bottom 96-well plates, 100 μL of BHI medium supplemented with L-cysteine-HCl (0.05%, w/v), L-arginine (1%, w/v), and sodium formate (10 mM) (referred to here as BHI++) were aliquoted. Seed cultures were prepared by inoculating wells, in triplicate, with Actinobacterial strains that were cultured on BHI++ agar plates. Additional wells served as sterile controls. Plates were sealed with tape and incubated at 37°C for 12 to 18 hr to afford dense cultures. Next, 99 μL of BHI++ medium containing 500 μM of compound were aliquoted into the wells of a 96-well plate. To these wells, 1 μL of dense seed culture (or sterile control) was added. Plates were sealed and incubated at 37°C for 24 or 48 hr. Plates were then centrifuged at 2000 rpm for 10 min at 4°C, and the supernatant was aspirated and transferred to a fresh 96-well plate. An aliquot (35 μL) of supernatant was then immediately screened via the catechol colorimetric assay (described above in ‘Colorimetric assay for catechol detection’). Absorbance was immediately measured at 500 nm using a plate reader (Spectrostar Nano, BMG LABTECH). A standard curve (2-fold serial dilutions, 1000–15.6 μM in BHI++) was simultaneously prepared, developed, and analyzed using the conditions listed above. The catechol concentrations in bacterial cultures were normalized to the sterile control. To confirm metabolism of (+)-catechin, DOPAC, and hydrocaffeic acid, the incubations were repeated following the same procedure with minor modifications. Strains were grown in BHI for 48 hr anaerobically at 37°C. Cultures were harvested by centrifugation and were then analyzed by LC-MS. To prepare samples for LC-MS, 20 µL of the culture supernatant was diluted 1:10 with 180 µL of methanol, followed by centrifugation at 4000 rpm for 10 min to pellet particulates, salts, and proteins. 50 µL of the resulting supernatant was then transferred to a 96-well plate and 5 µL of the supernatant was injected onto the instrument using Method E for catechin and Method F for hydrocaffeic acid and DOPAC. Following this screen, select strains were re-cultured to confirm absence/presence of metabolism. The following stock solutions were used in the screens: dihydroxymandelic acid (50 mM in water), dopamine (50 mM in water), protocatechuic acid (50 mM in ethanol), L-dopa (50 mM in 0.5 M HCl), norepinephrine (50 mM in 0.5 M HCl), epinephrine (50 mM in 0.5 M HCl), DOPAC (50 mM in 0.5 M HCl), Hydrocaffeic acid (50 mM in ethanol), caffeic acid (50 mM in ethanol), (+)-catechin (50 mM in ethanol), (+/–)-catechin (50 mM in ethanol), (–)-epicatechin (50 mM in DMSO), methyldopa (solid dissolved directly into the media at 0.5 mM final concentration), carbidopa (solid dissolved directly into the media at 0.5 mM final concentration), dihydroxybenzoic acid (50 mM in methanol). Hydroxytyrosol (50 mM in water), enterobactin (10 mM in DMSO), apomorphine (50 mM in DMSO).

Cells were cultured in hungate tubes and all experiments were performed anaerobically. E. lenta A2 was inoculated from a single colony into 10 mL BHI liquid medium and grown for 48 hr at 37°C to provide turbid starter cultures. These were diluted 1:100 in triplicate into 5 mL of BHI medium containing either 0.5 mM hydrocaffeic acid (in water), 0.5 mM (+)-catechin (in DMF), or vehicle (water or DMF). After 48 hr of anaerobic growth at 37°C, cultures were harvested by centrifugation and were then analyzed by LC-MS. To prepare samples for LC-MS, 20 µL of the culture supernatant was diluted 1:10 with 180 µL of methanol, followed by centrifugation at 4000 rpm for 10 min to pellet particulates, salts, and proteins. 50 µL of the resulting supernatant was then transferred to a 96-well plate and 5 µL of the supernatant was injected onto the instrument using Method E for catechin and Method F for hydrocaffeic acid.

Cells were cultured in hungate tubes and all experiments were performed anaerobically. G. pamelaeae 3C was inoculated from a single colony into 10 mL of BHI liquid medium and grown for 48 hr at 37°C to provide turbid starter cultures. These were diluted 1:100 in triplicate into 5 mL of BHI medium containing 10 mM formate and 0.5 mM DOPAC or vehicle (water). After 72 hr of anaerobic growth at 37°C, the cultures were harvested by centrifugation and were then analyzed by LC-MS. To prepare samples for LC-MS, 20 µL of the culture supernatant was diluted 1:10 with 180 µL of methanol, followed by centrifugation at 4000 rpm for 10 min to pellet particulates, salts, and proteins. 50 µL of the resulting supernatant was then transferred to the LC-MS 96-well plate and 5 µL of the supernatant was injected onto the instrument using Method F for DOPAC.

To characterize the distribution of Cadh, Hcdh, Dodh among our gut Actinobacterial strain library, we performed a tBLASTn search. We queried the genomes for Cadh, Hcdh, Dodh and used 90% coverage, 75% amino acid identity, and e-value = 0 as the cutoff for assessing the presence of each dehydroxylase.

Active fractions from the size exclusion chromatography described above were combined and then diluted 1:5 in 20 mM Tris pH 8 containing 250 mM NaCl. The enzyme mixture was transferred the wells of a 96 well plate, for a final volume of 50 µL in each well (VWR, catalog# 82006–636). 1 µL of substrate (in water for hydrocaffeic acid, dopamine, and DOPAC, or 50:50 water:DMF for (+)-catechin) was then added at a final concentration of 500 µM. Following this, 1 µL of a solution containing methyl viologen (1 mM final concentration) and 2 µL of sodium dithionite (2 mM final concentration, dissolved in water) were added. The resulting solution was mixed by pipetting and the 96-well plate was then sealed tightly with an aluminum seal. The enzyme assay mixtures were left at room temperature in an anaerobic chamber for 26 hr to allow dehydroxylation to proceed. The enzyme reaction mixtures were quenched by bringing the samples out of the anaerobic chamber and freezing at –20°C. These mixtures were then diluted 1:10 with LC-MS grade methanol and analyzed by LC-MS/MS. Samples containing hydrocaffeic acid and DOPAC were analyzed using Method F, catechin was analyzed using Method E, and dopamine was analyzed using Method C.

To generate estimates of the enzyme prevalence in human populations, the amino acid sequences of Cldh, Dodh, Dadh, Hcdh, and Cadh were searched against a non-redundant gut microbiome gene catalogue using BLASTP with a minimum 70% percent identity, query coverage and target coverage and used to extract per-sample gene abundances from a collection of human metagenomes (10.1093/bioinformatics/btv382). High identity matches were obtained for all queries (81.7%, 81.7%, 100%, 99.5%, and 99.9% respectively over >99% target coverage) with a second lower-identity match observed for Hcdh (75.7%) for which abundances were summed with the higher identity hit. Next, to account for repeated sampling of individuals, the median gene abundance across a subject’s samples was calculated and carried forward for prevalence estimates leading to a total of 1872 human subjects considered (Nayfach et al., 2015). Prevalence was then calculated as a rolling function of minimum abundance.

For phylogenetic analysis of the bis-MGD enzymes, we gathered sequences that have been previously used to study the evolution of bis-MGD enzymes (Schoepp-Cothenet et al., 2012). However, we also added sequences to capture additional diversity of biochemically characterized bis-MGD enzymes that were not included in the original tree described in Schoepp-Cothenet et al. (2012). In particular, we performed a pBLAST search in Uniprot using perchlorate reductase (Uniprot ID# PCRA_DECAR), ethylbenzene dehydrogenase (Uniprot ID# Q5NZV2_AROAE), acetylene hydratase (Uniprot ID# AHY_PELAE), and pyrogallol transhydroxylase (Uniprot ID# PGTL_PELAC) as the queries, and collected sequences with 85–90% amino acid ID. In addition, we added the sequences of Dadh, Hcdh, Cadh from E. lenta A2, and Dodh and Cldh (Bess et al., 2020) from G. pamelaeae 3C. The sequences were combined with those reported in Schoepp-Cothenet et al. (2012) and were aligned in Geneious (version 11) using MUSCLE. We subsequently used FastTree (standard settings, 20 rate categories of sites) to create a maximum likelihood tree. The tree files were uploaded to the Interactive Tree of Life web server (https://itol.embl.de/) to annotate the trees (Letunic and Bork, 2016).

A SSN was generated using the EFI-EST tool (http://efi.igb.illinois.edu/efi-est/) on July 15 2017 (Gerlt et al., 2015). In particular, we generated an SSN of the molybdopterin dinucleotide binding domain enzyme superfamily (PF01568), including sequences between 600 and 1400 amino acids in length and using an initial alignment score of e-150. Nodes represented sequences with 75% amino acid identity. The SSN was imported into Cytoscope v 3.2.1 and visualized with the ‘Organic layout’ setting. The alignment score cutoff was increased to e-167 until the groups of biochemically characterized enzymes included in our phylogenetic analysis (Figure 6) separated from each other into putatively isofunctional clusters.

To identify additional diversity beyond the newly identified putative dehydroxylases from this study, we created a database containing putative homologs from a collection of 26 previously sequenced Actinobacterial genomes (Bisanz et al., 2018), as well as from genomes publicly available through NCBI. First, the Eggerthella lenta A2 dopamine dehydroxylase (Dadh) protein sequence was used as the query sequence for a tBLASTn search of 26 previously sequenced Actinobacterial genomes (Bisanz et al., 2018) (April 23, 2019). The genomes were loaded in Geneious (version 11) and hits with an amino acid ID of >30% and e-value of e-34 were considered potential dehydroxylase hits and were saved. This cutoff was chosen because sequences captured within this window more closely resembled the acetylene hydratase and Dadh than to any other biochemically characterized moco enzyme, as assessed by percent amino acid identity. In addition, we used the representative Gordonibacter enzyme Cldh as a separate query to identify the more distantly related, smaller enzymes from Gordonibacter that were not detected when using the large, multi-subunit Dadh as the query. Specifically, we used tBLASTn to search the 26 Actinobacterial genomes for the Gordonibacter pamelaeae 3C Cldh protein sequence. Hits from Paraeggerthella hongongensis, Gordonibacter pamelaeae 3C and Gordonibacter sp. 28C, the only organisms containing these smaller Cldh-like enzymes in our collection, were saved. Again, amino acid ID of >30% and e-value of e-34 were considered potential hits because sequences captured within this window more closely resembled the acetylene hydratase and Dadh than to any other biochemically characterized moco enzyme, as assessed by percent amino acid identity. The hits from our searches with Cldh and Dadh were combined into a preliminary database in Geneious. To expand the sequence diversity within this database, we used Cldh and Dadh as queries for two separate tBLASTn searches in NCBI (nucleotide collection). To ensure that we captured diversity beyond human gut microbes, we excluded Gordonibacter and Eggerthella as organisms in the tBLASTn searches for Cldh and Dadh queries, respectively. For the two searches, sequences of >29% amino acid ID and e-value of e-55 were considered potential dehydroxylase hits. This was a more conservative cutoff than we used with human Actinobacteria and was selected based on the observation that the pBLAST alignment of Dadh and Cldh has an e value of e-45% and 29% amino acid ID. The sequences retrieved from NCBI were added to the database already containing the hits from searches of the 26 Actinobacterial genomes. In addition, we added the biochemically characterized E. coli bis-MGD enzyme DMSO reductase (DmsA, Uniprot ID#P18775) to this database as the outgroup. This sequence was also used as the root of the tree. For phylogenetic analysis of these sequences, we first aligned sequences in Geneious using MUSCLE and removed sequences that were 95% identical to each other (considered duplicates). After deleting these duplicate sequences, we re-aligned the sequences using MUSCLE (standard settings) and subsequently used FastTree (standard settings, 20 rate categories of sites) to create a maximum likelihood tree. The tree files were uploaded to the Interactive Tree of Life web server (https://itol.embl.de/) to annotate the trees (Letunic and Bork, 2016).

Once we had constructed the two trees described above (Figures 6 and 7 in the main text) and uncovered dehydroxylase homologs in gut and environmental bacteria, we wanted to explore the phylogenetic relationship between these enzymes and the broader bis-molybdopterin guanine dinucleotide (bis-MGD) enzyme family. To do this, we added the representative sequences from Figure 7—figure supplement 3 and Supplementary file 3c to the sequence database already described in ‘Phylogenetic analysis of relationship between catechol dehydroxylases and other characterized members of the bis-molybdopterin guanine dinucleotide enzyme family’. Using MUSCLE, we aligned the newly added sequences with the sequences represented on the tree (Figure 6 in main text). We then used FastTree (standard settings, 20 rate categories of sites) in Geneious (version 11) to generate the tree seen in Figure 7—figure supplement 4. The tree files were uploaded to the Interactive Tree of Life web server (https://itol.embl.de/) to annotate the trees (Letunic and Bork, 2016).

The collection of fecal samples from mammals (n = 12 different species, n = 3 individuals per species) has been previously described (Reese et al., 2018). To prepare these samples for culturing, all samples were resuspended anaerobically in pre-reduced PBS at a final concentration of 0.1 g/mL. The mixture was vortexed to produce a homogenous slurry and was then left for 30 min to let particulates settle. Aliquots of the supernatant were dissolved 50:50 with 40% glycerol in water and flash-frozen in liquid nitrogen, creating slurries. These slurries were stored at –80°C and were defrosted anaerobically at room temperature at the time of use.

Mammalian fecal slurries were prepared as described above and were defrosted by incubation at room temperature at the time of use. 20 µL of each slurry was then combined with 980 µL of basal medium containing 500 µM each of dopamine, (+) catechin, DOPAC, or hydrocaffeic acid. Each individual sample was grown in one well, with the n = 3 individual samples for each animal serving as the biological replicates. Control wells contained compound but no bacteria. Samples were grown anaerobically at 37°C for 96 hr in a 96-well plate (Agilent Technology, catalog# A696001000). Following growth, we first assessed the total microbial growth by measuring the OD₆₀₀ in a plate reader (BioTek Synergy HTX). Cultures were then harvested by centrifugation and 50 µL of supernatant was transferred to a new 96-well plate, at which time the catechol colorimetric assay was used to assess total dehydroxylation by the complex microbial community. Samples that had potential catechol depletion as assessed by the colorimetric assay were then further analyzed by LC-MS. To prepare samples for LC-MS, 20 µL of the culture supernatant was diluted 1:10 with 180 µL of methanol, followed by centrifugation at 4000 rpm for 10 min to pellet particulates, salts, and proteins. 50 µL of the resulting supernatant was then transferred to the LC-MS 96-well plate and 5 µL of the supernatant was injected onto the instrument using Method A for dopamine, Method E for catechin, and Method F for DOPAC and hydrocaffeic acid.

The mammalian phylogenetic tree was generated using the Automatic Phylogenetic Tree Generator (aptg, version 0.1.0) script in R (version 3.5.1). Mammals not part of the aptg database were added manually to the tree using additional information about the mammalian phylogeny as a reference (Reese et al., 2019). The mammalian icons were adapted under a Creative Commons license (https://creativecommons.org/licenses/by/3.0/) at phylopic (http://phylopic.org), including Alpaca logo (made by Steven Traver), Bison (Lukasiniho). Cow (Steven Traver), Dog (Tracy A Heath), Fox (Anthony Caravaggi), Guinea pig (Zimices), Mouse (Madeleine Price Ball), Pig (Steven Traver), Rabbit (Steven Traver), Rabbit (Steven Traver), Rat (Rebecca Groom), Sheep (Zimices), and Wolf (Tracy A. Heath).