Cohen et al Mammals produce N-palmitoyl glycine, which differs from commendamide by of the B-hydroxyl and, based on our synthetic N-acyl studies, activates G2A. 19 he absence GPRI19 is the most extensively studied of the GPCRs activated by bacterial ligands we identified (Fig 4) Mechanisms that link endogenous GPRI19 agonists(OEA, 2-OG)to changes in host phenotype are well defined as a result of the exploration of GPri19 as a therapeutic target for diabetes and obesity. 0--3GPR119 agonists are thought to primarily affect glucose homeostasis but also gastric emptying and appetite through both gPr119- dependent hormone release from enteroendocrine cells(GLP-1, GIP, PYY)and pancreatic B-cells(insulin) as well as GPrI19-independent mechanisms including PPARa modulation 9, 16, 24-30 Murine enteroendocrine GLUTag cells have been used as a model system for measuring the ability of potential GPri19 agonists to induce GLP-1 release. When administered to gLUTag cells at equimolar concentrations, microbiota-encoded N-oleoyl serinol or the endogenous ligands oEa and 2-oG induced GLP-I secretion to the same magnitude(Fig. 5c). To provide an orthogonal measurement of GPRi19 activation by M acyl serinols, HEK293 cells were stably transfected with a GPR119 expression construct Both Oea and n-oleoyl serinol increased cellular cAMP concentrations in a gPr119 dependent fashion(Extended Data Fig 5) hm-NAS expression alters blood glucose in mice The functional overlap between endogenous and bacterial metabolites suggested that bacteria expressing microbiota-encoded GPRi19 ligands might elicit host phenotypes that mimic those induced by eukaryotic ligands. Endogenous and synthetic GPRi19 ligands have been associated with changes in glucose homeostasis that are relevant to the etiology and treatment of diabetes and obesity including a study where mice were orally administered bacteria engineered to produce a eukaryotic enzyme that increases endogenous GPR119 ligand(OEA)precursors. 9, 16, 24-27, 31 The metabolic effect of the endogenous GPR119 ligands is believed to occur at the intestinal mucosa as the delivery of OEA intravenously fails to lower blood glucose in mice during an oral glucose tolerance test(OGTT) Consequently, we sought to determine whether mice colonized with bacteria engineered to produce human microbiota N-acyl serinols would exhibit predictable host phenotypes notobiotic mice were colonized with E coli engineered to express the N-acyl serinol synthase gene in an IPTG dependent manner. Control mice were colonized with E. coli containing an empty vector. Based on the number of colony forming units detected in fecal pellets both cohorts of mice were colonized to the same extent(Extended Data Fig. 7).After one week of exposure to IPTG both cohorts were fasted overnight and subjected to an OGTT. At 30 minutes post challenge we observed a statistically significant decrease in blood glucose levels for the group colonized with E. coli expressing the N-acyl serinol synthase gene(Fig. 5d). MS analysis of metabolites present in cecal samples revealed the presence of N-acyl serinols in the treatment cohort but not in the control cohort(Extended Data Fig. 6). After two weeks of withdrawing IPTG from the drinking water we no longer observed a difference in blood glucose between the two cohorts in an OGTT(Fig. 5e).32 To further explore the metabolic phenotype induced by N-acyl serinols we repeated OGTT experiment in an antibiotic treated mouse model. In this study we compared mice Nature. Author manuscript; available in PMC 2018 February 28
Mammals produce N-palmitoyl glycine, which differs from commendamide by the absence of the β-hydroxyl and, based on our synthetic N-acyl studies, activates G2A.19 GPR119 is the most extensively studied of the GPCRs activated by bacterial ligands we identified (Fig 4). Mechanisms that link endogenous GPR119 agonists (OEA, 2-OG) to changes in host phenotype are well defined as a result of the exploration of GPR119 as a therapeutic target for diabetes and obesity.20–23 GPR119 agonists are thought to primarily affect glucose homeostasis but also gastric emptying and appetite through both GPR119- dependent hormone release from enteroendocrine cells (GLP-1, GIP, PYY) and pancreatic β-cells (insulin) as well as GPR119-independent mechanisms including PPARα modulation. 9,16,24–30 Murine enteroendocrine GLUTag cells have been used as a model system for measuring the ability of potential GPR119 agonists to induce GLP-1 release. When administered to GLUTag cells at equimolar concentrations, microbiota-encoded N-oleoyl serinol or the endogenous ligands OEA and 2-OG induced GLP-1 secretion to the same magnitude (Fig. 5c). To provide an orthogonal measurement of GPR119 activation by Nacyl serinols, HEK293 cells were stably transfected with a GPR119 expression construct. Both OEA and N-oleoyl serinol increased cellular cAMP concentrations in a GPR119 dependent fashion (Extended Data Fig 5). hm-NAS expression alters blood glucose in mice The functional overlap between endogenous and bacterial metabolites suggested that bacteria expressing microbiota-encoded GPR119 ligands might elicit host phenotypes that mimic those induced by eukaryotic ligands. Endogenous and synthetic GPR119 ligands have been associated with changes in glucose homeostasis that are relevant to the etiology and treatment of diabetes and obesity including a study where mice were orally administered bacteria engineered to produce a eukaryotic enzyme that increases endogenous GPR119 ligand (OEA) precursors.9,16,24–27,31 The metabolic effect of the endogenous GPR119 ligands is believed to occur at the intestinal mucosa as the delivery of OEA intravenously fails to lower blood glucose in mice during an oral glucose tolerance test (OGTT).26 Consequently, we sought to determine whether mice colonized with bacteria engineered to produce human microbiota N-acyl serinols would exhibit predictable host phenotypes. notobiotic mice were colonized with E. coli engineered to express the N-acyl serinol synthase gene in an IPTG dependent manner. Control mice were colonized with E. coli containing an empty vector. Based on the number of colony forming units detected in fecal pellets both cohorts of mice were colonized to the same extent (Extended Data Fig. 7). After one week of exposure to IPTG both cohorts were fasted overnight and subjected to an OGTT. At 30 minutes post challenge we observed a statistically significant decrease in blood glucose levels for the group colonized with E. coli expressing the N-acyl serinol synthase gene (Fig. 5d). MS analysis of metabolites present in cecal samples revealed the presence of N-acyl serinols in the treatment cohort but not in the control cohort (Extended Data Fig. 6). After two weeks of withdrawing IPTG from the drinking water we no longer observed a difference in blood glucose between the two cohorts in an OGTT (Fig. 5e).32 To further explore the metabolic phenotype induced by N-acyl serinols we repeated the OGTT experiment in an antibiotic treated mouse model. In this study we compared mice Cohen et al. Page 6 Nature. Author manuscript; available in PMC 2018 February 28. Author Manuscript Author Manuscript Author Manuscript Author Manuscript
Cohen et al colonized with E coll expressing an active N-acyl serinol synthase to mice colonized with E. coli expressing an NAS point mutant(Extended Data Fig. 8, p. Glu91Ala) that no longer produced N-acyl serinols. In this model the glucose lowering effect of colonization with N- acyl serinol producing E. coli remained significant(Fig. 5f). In the antibiotic treated mice we measured GLP-I and insulin concentrations after glucose gavage. Both hormones were gnificantly increased in the treatment group compared to the control group(Fig. 5 g, h). In all mouse models the observed correlation between hm-NAS gene induction and increased glucose tolerance is similar in magnitude to several studies with small molecule GPri19 agonists including glyburide, an FDA approved therapeutic for diabetes. 24. 2 Discussion ur characterization of human microbial N-acyl amides, together with other investiga of the human microbiota, suggests that host-microbial interactions may rely heavily on many human signaling systems(e.g, neurotransmitters, bioactive lipids, glycans). This is not surprising, as the genomes of the bacterial taxa common to the human gastrointestinal tract(e.g, Bacteroidetes, Firmicutes and Proteobacteria) are often lacking in gene clusters that encode for the production of complex secondary metabolites(e.g, polyketides nonribosomal peptides, terpenes). It appears that biosynthesis of endogenous mammalian produced by the human modest manipulation of primary metabolites. As a result, the structural conservation between metabolites used in host-microbial interactions and endogenous mammalian signaling metabolites may be a common phenomenon in the human microbiome Evolutionarily, the convergence of bacterial and human signaling systems through structurally related GPCR ligands is not unreasonable as GPCRs are thought to have developed in eukaryotes to allow for structurally simple signaling molecules to regulate increasingly complex cellular interactions. 33-33The structural similarities between microbiota-encoded N-acyl amides and endogenous GPCR-active lipids may be indicative of a broader structural and functional overlap among bacterial and human bioactive lipids including other GPCR-active N-acyl amides, eiconasoids(prostaglandins, leukotrienes)and sphingolipids Sphingolipid based signaling molecules may also be common in the human microbiome as prevalent bacterial species are known to synthesize membrane sphingolipids. The GPCRs with which bacterial N-acyl amides were found to interact are all part of the same"lipid-like " GPCR gene family. The potential importance of this GPCR family to the regulation of host-microbial interactions is suggested by their localization to areas of gastrointestinal track enriched in bacteria that are predicted to synthesize GPCr ligands (Extended Data Fig 4). Lipid-like GPCRs have been shown to play roles in disease models that are correlated with changes in microbial ecology including colitis(SIPR4, PTGir PTGER4), obesity(GPRi19), diabetes( GPri19), autoimmunity(G2A) and atherosclerosis (G2A, PTGIR). 9,10, 13, 14 The fact that the expression of an NAS gene in a gastrointestinal nizing bacterium is sufficient to alter host phys between lipid-like GPCRs and their N-acyl amide ligands could be relevant to human physiology and warrants further study. By LCMS analysis we observed most of the
colonized with E. coli expressing an active N-acyl serinol synthase to mice colonized with E. coli expressing an NAS point mutant (Extended Data Fig. 8, p.Glu91Ala) that no longer produced N-acyl serinols. In this model the glucose lowering effect of colonization with Nacyl serinol producing E. coli remained significant (Fig. 5f). In the antibiotic treated mice we measured GLP-1 and insulin concentrations after glucose gavage. Both hormones were significantly increased in the treatment group compared to the control group (Fig. 5 g, h). In all mouse models the observed correlation between hm-NAS gene induction and increased glucose tolerance is similar in magnitude to several studies with small molecule GPR119 agonists including glyburide, an FDA approved therapeutic for diabetes.24,25 Discussion Our characterization of human microbial N-acyl amides, together with other investigations of the human microbiota, suggests that host-microbial interactions may rely heavily on simple metabolites built from the same common lipids, sugars, and peptides that define many human signaling systems (e.g., neurotransmitters, bioactive lipids, glycans). This is not surprising, as the genomes of the bacterial taxa common to the human gastrointestinal tract (e.g., Bacteroidetes, Firmicutes and Proteobacteria) are often lacking in gene clusters that encode for the production of complex secondary metabolites (e.g., polyketides, nonribosomal peptides, terpenes). It appears that biosynthesis of endogenous mammalian signaling molecules as well as those produced by the human microbiota may rely on the modest manipulation of primary metabolites. As a result, the structural conservation between metabolites used in host-microbial interactions and endogenous mammalian signaling metabolites may be a common phenomenon in the human microbiome. Evolutionarily, the convergence of bacterial and human signaling systems through structurally related GPCR ligands is not unreasonable as GPCRs are thought to have developed in eukaryotes to allow for structurally simple signaling molecules to regulate increasingly complex cellular interactions.33–35 The structural similarities between microbiota-encoded N-acyl amides and endogenous GPCR-active lipids may be indicative of a broader structural and functional overlap among bacterial and human bioactive lipids including other GPCR-active N-acyl amides, eiconasoids (prostaglandins, leukotrienes) and sphingolipids. Sphingolipid based signaling molecules may also be common in the human microbiome as prevalent bacterial species are known to synthesize membrane sphingolipids. 36 The GPCRs with which bacterial N-acyl amides were found to interact are all part of the same “lipid-like” GPCR gene family. The potential importance of this GPCR family to the regulation of host-microbial interactions is suggested by their localization to areas of gastrointestinal track enriched in bacteria that are predicted to synthesize GPCR ligands (Extended Data Fig. 4). Lipid-like GPCRs have been shown to play roles in disease models that are correlated with changes in microbial ecology including colitis (S1PR4, PTGIR, PTGER4), obesity (GPR119), diabetes (GPR119), autoimmunity (G2A) and atherosclerosis (G2A, PTGIR).9,10,13,14 The fact that the expression of an NAS gene in a gastrointestinal colonizing bacterium is sufficient to alter host physiology suggests that the interaction between lipid-like GPCRs and their N-acyl amide ligands could be relevant to human physiology and warrants further study. By LCMS analysis we observed most of the Cohen et al. Page 7 Nature. Author manuscript; available in PMC 2018 February 28. Author Manuscript Author Manuscript Author Manuscript Author Manuscript
Cohen et al microbiota encoded N-acyl amides reported here in human stool samples(Extended Data ig. 9). Further studies will be needed to better define the distribution and concentration of these metabolites throughout the gastrointestinal tract especially at the mucosa where the physiologic activity of these metabolites likely occurs. Interestingly, Gemella spp. predicted to encode N-acyl serinols are tightly associated with the small intestinal mucosa supporting this site as a potentially important location for N-acyl amide mediated interactions. 37As the mouse model system used here relies on induced expression of NAS genes it will also be mportant to understand how these genes are natively regulated Current strategies for treating diseases associated with the microbiome such as inflammatory owel disease or diabetes are not believed to address the dysfunction of the host-microbial interactions that are likely part of the disease pathogenesis. Bacteria engineered to delive bioactive small molecules produced by the human microbiota have the potential to help ddress diseases of the microbiome by modulating the native distribution and abundance of these metabolites. Regulation of GPCRs by microbiota-derived N-acyl amides is a particularly attractive therapeutic strategy for the treatment of human diseases as gPCrs have been extensively validated as therapeutic targets. As our mechanistic understanding of how human microbiota-encoded small molecules effect changes in host physiology grows the potential for using"microbiome-biosynthetic-gene-therapy to treat human disease by complementing small molecule deficiencies in native host-microbial interactions with microbiota derived biosynthetic genes should increase accordingly. The use of functional metagenomics to identify microbiota encoded effectors combined with bioinformatics and synthetic biology to expand effector molecule families provides a generalizable platform to help define the role microbiota-encoded small molecules play in host-microbial interactions Methods Bioinformatics analysis of human N-acyl synthase genes Protein sequences for members of the PFAM family 13444 Acetyltransferase(GNAT domain(http://pfam.xfam,org/family/pf13444)(n=689)weredownloadedand corresponding gene sequences identified based on European Bioinformatics Institute(EBD) numberAmultiplesequencealignmentwasperformedusingClustalOmega(http:// www.ebi.ac.uk/tools/msa/clustalo/),generatingaphylogenetictreeinNewickformatwith the"--guidetree-outoption The 689 PFAM sequences were queried against the Human Microbiome Project(HMP)clustered gene index datasets and reference genome datasets with BlasTn(htTp: //hmpdacc. org/hmgc/). The Pfam13444 sequences that aligned to a HMP gene [expectation(E)value <e+0 and >70% identity] were identified and comprise the human N-acyl synthase(hm-NAS) gene dataset (143 hm-NAS genes). Reference genomes for 111/143 hm-NAS genes were identified (Supplementary Table 2) To determine the abundance of hm-NAS genes within microbiomes at specific human body sites, hm-NAS genes were queried against HMP whole metagenome shotgun sequencing gene wo BLASTN searched against the non-redundant gene sets from the following body sites buccal mucosa, anterior nares, mid vagina, posterior fornix, vaginal introitus, retroauricular crease(combined left and right, stool, supragingival plaque and tongue dorsum. These body Nature. Author manuscript; available in PMC 2018 February 28
microbiota encoded N-acyl amides reported here in human stool samples (Extended Data Fig. 9). Further studies will be needed to better define the distribution and concentration of these metabolites throughout the gastrointestinal tract especially at the mucosa where the physiologic activity of these metabolites likely occurs. Interestingly, Gemella spp. predicted to encode N-acyl serinols are tightly associated with the small intestinal mucosa supporting this site as a potentially important location for N-acyl amide mediated interactions.37 As the mouse model system used here relies on induced expression of NAS genes it will also be important to understand how these genes are natively regulated. Current strategies for treating diseases associated with the microbiome such as inflammatory bowel disease or diabetes are not believed to address the dysfunction of the host-microbial interactions that are likely part of the disease pathogenesis. Bacteria engineered to deliver bioactive small molecules produced by the human microbiota have the potential to help address diseases of the microbiome by modulating the native distribution and abundance of these metabolites. Regulation of GPCRs by microbiota-derived N-acyl amides is a particularly attractive therapeutic strategy for the treatment of human diseases as GPCRs have been extensively validated as therapeutic targets. As our mechanistic understanding of how human microbiota-encoded small molecules effect changes in host physiology grows, the potential for using “microbiome-biosynthetic-gene-therapy” to treat human disease by complementing small molecule deficiencies in native host-microbial interactions with microbiota derived biosynthetic genes should increase accordingly. The use of functional metagenomics to identify microbiota encoded effectors combined with bioinformatics and synthetic biology to expand effector molecule families provides a generalizable platform to help define the role microbiota-encoded small molecules play in host-microbial interactions. Methods Bioinformatics analysis of human N-acyl synthase genes Protein sequences for members of the PFAM family 13444 Acetyltransferase (GNAT) domain (http://pfam.xfam.org/family/PF13444) (n=689) were downloaded and corresponding gene sequences identified based on European Bioinformatics Institute (EBI) number. A multiple sequence alignment was performed using Clustal Omega (http:// www.ebi.ac.uk/Tools/msa/clustalo/), generating a phylogenetic tree in Newick format with the “--guidetree-out” option. The 689 PFAM sequences were queried against the Human Microbiome Project (HMP) clustered gene index datasets and reference genome datasets with BLASTN (http://hmpdacc.org/HMGC/). The PFAM13444 sequences that aligned to a HMP gene [expectation (E) value < e−40 and > 70% identity] were identified and comprise the human N-acyl synthase (hm-NAS) gene dataset (143 hm-NAS genes). Reference genomes for 111/143 hm-NAS genes were identified (Supplementary Table 2). To determine the abundance of hm-NAS genes within microbiomes at specific human body sites, hm-NAS genes were queried against HMP whole metagenome shotgun sequencing data on a per body site basis (http://hmpdacc.org/HMASM/). Each hm-NAS gene was BLASTN searched against the non-redundant gene sets from the following body sites: buccal mucosa, anterior nares, mid vagina, posterior fornix, vaginal introitus, retroauricular crease (combined left and right), stool, supragingival plaque and tongue dorsum. These body Cohen et al. Page 8 Nature. Author manuscript; available in PMC 2018 February 28. Author Manuscript Author Manuscript Author Manuscript Author Manuscript
Cohen et al sites were chosen because they contained sequence data from the largest number of unique patients.38hm-NAS genes and highly similar genes in the hMP non redundant gene set(E- value <e 4 )were aligned to shotgun sequencing reads from each patient sample taken from different sites in the human microbiome Aligned reads were normalized to hm-NAS gene length and sequencing depth of each dataset. The normalized count of the reads aligned to each hm-NAS gene or its highly similar gene from the HMP non redundant gene set were scaled [O-l] and color coded per body site, and added as concentric rings around the phylogenetic tree(Fig. 1A). To determine the variability and distribution of hm-NAS gene hat correspond to specific N-acyl amide families 1-6(Fig. 1)in the human microbiome normalized read counts for hm-NAS gene from each N-acyl amide family were plotted separately per body site as Reads per Kilobase of Gene Per Million Reads(RPKM)(Fig Ic).ThetreeinFigureIwasplottedusinggraphlan(https://huttenhower.sph.harvard.edu/ Analysis of metatranscriptome datasets Two RNAseq datasets were identified with multiple patient samples taken from separate sites in the human microbiome.39, 40 One RnaSeq dataset was part of the Hmp(Http: // hmpdacc. org/RSEQ/) and generated from supragingival samples taken from twin pairs with and without dental caries. The second RNAseq dataset was generated from stool samples and compared different RNA extraction methods. We used only samples labeled"whole which functioned as controls for the original study. Alignment of all hm-NAS genes to each dataset only identified hm-NAS genes from N-acyl amide family I and 2 in each of the RNASeq datasets(I in stool, 2 in supragingival plaque). To explore whether hm-NAS gene expression might vary in patient samples we performed two different analyses. In the first analysis we identified reference genomes containing hm-NAS genes identical to those we used in heterologous expression experiments for molecule families I and 2 (Bacteroides dorer for compound 1, Capnocytophaga ochracea for compound 2). RNAseq reads were aligned to all of the genes from each reference genome. For each genome the average per gene read density normalized for gene length was compared to the read density seen for the hm-NAS gene. The percentile of the normalized expression of each hm-NAS gene was then plotted(0 for not expressed, I for the most expressed) and compared between patient samples for each RNAseq dataset(Fig. 2a). In the second analysis the direct correlation between DNA and RNa abundance was determined for the stool metatranscriptome datas for which DNA reads were also available.39 RNAseq and shotgun-sequenced dNA reads were aligned to the 15 hm-NAS genes from N-acyl amide family I that encoded for N-acyl glycines(Supplementary Table 1). The reads were normalized(rPKm) and each hm-NAS gene from each patient sample was plotted as a single point with DNA and rNa read counts on the X and Y axis( Fig. 2b) Heterologous expression of PFAM13444 genes in Escherichia coli The 44 hm-NAS genes we examined by heterologous expression were codon optimized, appended with Ncol and Ndel sites at the n and c terminus respectively and synthesized by Geng Genes obtained from Gen were digested with Ndel and Ncol and ligated into the orresponding restriction sites in pET28c(Novagen). For heterologous expression purposes the resulting constructs were transformed into E. coli EC100 containing the T7 polymerase Nature. Author manuscript; available in PMC 2018 February 28
sites were chosen because they contained sequence data from the largest number of unique patients.38 hm-NAS genes and highly similar genes in the HMP non redundant gene set (Evalue < e−40) were aligned to shotgun sequencing reads from each patient sample taken from different sites in the human microbiome. Aligned reads were normalized to hm-NAS gene length and sequencing depth of each dataset. The normalized count of the reads aligned to each hm-NAS gene or its highly similar gene from the HMP non redundant gene set were scaled [0–1] and color coded per body site, and added as concentric rings around the phylogenetic tree (Fig. 1A). To determine the variability and distribution of hm-NAS genes that correspond to specific N-acyl amide families 1–6 (Fig. 1) in the human microbiome normalized read counts for hm-NAS gene from each N-acyl amide family were plotted separately per body site as Reads per Kilobase of Gene Per Million Reads (RPKM) (Fig. 1c). The tree in Figure 1 was plotted using graphlan (https://huttenhower.sph.harvard.edu/ graphlan). Analysis of metatranscriptome datasets Two RNAseq datasets were identified with multiple patient samples taken from separate sites in the human microbiome.39,40 One RNAseq dataset was part of the HMP (http:// hmpdacc.org/RSEQ/) and generated from supragingival samples taken from twin pairs with and without dental caries. The second RNAseq dataset was generated from stool samples and compared different RNA extraction methods. We used only samples labeled “whole” which functioned as controls for the original study.39 Alignment of all hm-NAS genes to each dataset only identified hm-NAS genes from N-acyl amide family 1 and 2 in each of the RNAseq datasets (1 in stool, 2 in supragingival plaque). To explore whether hm-NAS gene expression might vary in patient samples we performed two different analyses. In the first analysis we identified reference genomes containing hm-NAS genes identical to those we used in heterologous expression experiments for molecule families 1 and 2 (Bacteroides dorei for compound 1, Capnocytophaga ochracea for compound 2). RNAseq reads were aligned to all of the genes from each reference genome. For each genome the average per gene read density normalized for gene length was compared to the read density seen for the hm-NAS gene. The percentile of the normalized expression of each hm-NAS gene was then plotted (0 for not expressed, 1 for the most expressed) and compared between patient samples for each RNAseq dataset (Fig. 2a). In the second analysis the direct correlation between DNA and RNA abundance was determined for the stool metatranscriptome dataset for which DNA reads were also available.39 RNAseq and shotgun-sequenced DNA reads were aligned to the 15 hm-NAS genes from N-acyl amide family 1 that encoded for N-acyl glycines (Supplementary Table 1). The reads were normalized (RPKM) and each hm-NAS gene from each patient sample was plotted as a single point with DNA and RNA read counts on the X and Y axis (Fig. 2b). Heterologous expression of PFAM13444 genes in Escherichia coli The 44 hm-NAS genes we examined by heterologous expression were codon optimized, appended with NcoI and NdeI sites at the N and C terminus respectively and synthesized by Gen9. Genes obtained from Gen9 were digested with NdeI and NcoI and ligated into the corresponding restriction sites in pET28c (Novagen). For heterologous expression purposes the resulting constructs were transformed into E. coli EC100 containing the T7 polymerase Cohen et al. Page 9 Nature. Author manuscript; available in PMC 2018 February 28. Author Manuscript Author Manuscript Author Manuscript Author Manuscript
gene integrated into its genome(E coli EC100: DE3). E. coli EC100: DE3 hm-NAs containing strains were inoculated into 10 ml of Luria-Bertani (lB) broth supplemented with kanamycin(50 ug/ml)and grown overnight (37C with shaking 200 rpm). One ml of overnight culture was used to inoculate 50 ml of LB supplemented with kanamycin(50 ug/ml)and isopropyl B-D-1-thiogalactopyranoside(IPTG)(25 HM). Cultures were incubated at 30C for 4 days with shaking(200 rpm). Each culture broth was extracted with an equal volume of ethyl acetate and the resulting crude extracts were dried in vacuo. Crude extracts were resuspended in 50 uL of methanol and analyzed by reversed phase HPLC-MS (XBridgeTm C18 4.6 mm x 150 mm)using a binary solvent system(A/B solvent of water/ acetonitrile with 0. 1% formic acid: 10% B isocratic for 5 minutes, gradient 10% to 100% B over 25 minutes). Clone specific metabolites encoded by each hm-NAS gene were identified by comparing experimental extracts with extracts prepared from cultures of E. coln EC100 DE3 transformed with an empty pET28c vector N-acyl amide isolation and structure determination For each group of clones that, based on LCMS analysis, were predicted to produce a different N-acyl amide family we chose one representative clone for use in molecule solation studies. Each representative clone was grown in 1. 5L of LB in a 2.7L Fernach flask (30C, 200 RPM). After 4 days, cultures were extracted 2 times with an equal volume of ethyl acetate. Dried ethyl acetate extracts were partitioned by reversed phase flash chromatography (Teledyne Isco, CI8 RediSep rF gold m 15 g)using the following mobile phase conditions: water acetonitrile with 0. 1% formic acid, 10% acetonitrile isocratic for 5 minutes, gradient to 100% acetonitrile over 20 minutes(30 mL/minute). Fractions containing clone specific metabolites were pooled and semi preparative reversed phase HPLC was used to separate individual N-acyl amide molecules( Supplementary Information). The structures of compounds 2-6 were determined using a combination of HRMS,H, C, and 2D NMR data( Supplementary Information ). Compound 1 was described in our previous study. hm-NAS gene containing bacterial species culture broth analysis Capnocytophaga ochracea F0287(compound 2), Klebsiella pneumoniae WGLWI-5 (compound 3), Neisseria flavescens SKI 14(compounds 4a and 4b), and gemella haemolysans M341(compound 6)were obtained from the Biodefense and Emerging Infections Research Resources Repository(BEl Resources)HMP catalogue. Compound 1 was previously identified in culture broth extracts from cultures of Bacteroides vulgatus. 3 Each chosen bacteria contains an hm-NAS gene related to that which was heterologously expressed to produce compound 2, 3, 4a, 4b or 6. Strains were inoculated under sterile conditions into 2 L of LY BHI medium[brain-heart infusion medium supplemented with .5% yeast extract(Difco), 5 mg/L hemin (Sigma), I mg/ml cellobiose(Sigma), I mg/ml maltose(Sigma), 0.5 mg/ml cysteine( Sigma)] and grown anaerobically(C ochracea)or aerobically (N. flavescens, G. haemolysans, K. pneumoniae) for 7 days. Culture broths were extracted with an equal volume of ethyl acetate. To look for the presence of N-acyl amides these extracts were examined by HPLC-MS as was done in the original heterologous expression experiments. With the exception of family 3, the N-acyl metabolite that was Nature. Author manuscript; available in PMC 2018 February 28
gene integrated into its genome (E. coli EC100:DE3). E. coli EC100:DE3 hm-NAS containing strains were inoculated into 10 ml of Luria-Bertani (LB) broth supplemented with kanamycin (50 µg/ml) and grown overnight (37 °C with shaking 200 rpm). One ml of overnight culture was used to inoculate 50 ml of LB supplemented with kanamycin (50 µg/ml) and isopropyl β-D-1-thiogalactopyranoside (IPTG) (25 µM). Cultures were incubated at 30 °C for 4 days with shaking (200 rpm). Each culture broth was extracted with an equal volume of ethyl acetate and the resulting crude extracts were dried in vacuo. Crude extracts were resuspended in 50 µL of methanol and analyzed by reversed phase HPLC-MS (XBridgeTm C18 4.6 mm × 150 mm) using a binary solvent system (A/B solvent of water/ acetonitrile with 0.1% formic acid: 10% B isocratic for 5 minutes, gradient 10% to 100% B over 25 minutes). Clone specific metabolites encoded by each hm-NAS gene were identified by comparing experimental extracts with extracts prepared from cultures of E. coli EC100:DE3 transformed with an empty pET28c vector. N-acyl amide isolation and structure determination For each group of clones that, based on LCMS analysis, were predicted to produce a different N-acyl amide family we chose one representative clone for use in molecule isolation studies. Each representative clone was grown in 1.5 L of LB in a 2.7 L Fernach flask (30 °C, 200 RPM). After 4 days, cultures were extracted 2 times with an equal volume of ethyl acetate. Dried ethyl acetate extracts were partitioned by reversed phase flash chromatography (Teledyne Isco, C18 RediSep RF GoldTm 15 g) using the following mobile phase conditions: water:acetonitrile with 0.1% formic acid, 10% acetonitrile isocratic for 5 minutes, gradient to 100% acetonitrile over 20 minutes (30 mL/minute). Fractions containing clone specific metabolites were pooled and semi preparative reversed phase HPLC was used to separate individual N-acyl amide molecules (Supplementary Information). The structures of compounds 2–6 were determined using a combination of HRMS, 1H, 13C, and 2D NMR data (Supplementary Information). Compound 1 was described in our previous study.3 hm-NAS gene containing bacterial species culture broth analysis Capnocytophaga ochracea F0287 (compound 2), Klebsiella pneumoniae WGLW1–5 (compound 3), Neisseria flavescens SK114 (compounds 4a and 4b), and Gemella haemolysans M341 (compound 6) were obtained from the Biodefense and Emerging Infections Research Resources Repository (BEI Resources) HMP catalogue. Compound 1 was previously identified in culture broth extracts from cultures of Bacteroides vulgatus. 3 Each chosen bacteria contains an hm-NAS gene related to that which was heterologously expressed to produce compound 2, 3, 4a, 4b or 6. Strains were inoculated under sterile conditions into 2 L of LYBHI medium [brain–heart infusion medium supplemented with 0.5% yeast extract (Difco), 5 mg/L hemin (Sigma), 1 mg/ml cellobiose (Sigma), 1 mg/ml maltose (Sigma), 0.5 mg/ml cysteine (Sigma)] and grown anaerobically (C. ochracea) or aerobically (N. flavescens, G. haemolysans, K. pneumoniae) for 7 days. Culture broths were extracted with an equal volume of ethyl acetate. To look for the presence of N-acyl amides these extracts were examined by HPLC-MS as was done in the original heterologous expression experiments. With the exception of family 3, the N-acyl metabolite that was Cohen et al. Page 10 Nature. Author manuscript; available in PMC 2018 February 28. Author Manuscript Author Manuscript Author Manuscript Author Manuscript