Faculty Bibliography

The engineering of microbial metabolic pathways over the last two decades has led to numerous examples of cell factories used for the production of small molecules. These molecules have an array of utility in commercial industries and as in situ expressed biomarkers or therapeutics in microbial applications. While most efforts have focused on the production of molecules in the liquid phase, there has been increasing interest in harnessing microbes' inherent ability to generate volatile compounds. Here, we optimized and characterized the production of methyl salicylate, an aromatic compound found mainly in plants, using a common lab strain of E. coli. We utilized genetic components from both microbes and plants to construct the volatile metabolite circuit cassette. In order to maximize production, we explored expression of methyl salicylate precursors, upregulation of expression by increasing ribosomal binding strength and codon optimization of the methyl transferase gene obtained from plant Petunia x hybrida. Last, we validated and quantified the production of methyl salicylate with liquid chromatography or gas chromatography mass spectrometry (LC-MS or GC-MS) and found that the codon optimized strain with precursor supplementation yielded the highest production compared to the other strains. This work characterizes an optimized metabolite producing genetic circuit and sets the stage for creation of an engineered bacteria diagnostic to be used in volatile assays.

Introduction/UNASSIGNED:Non-alcoholic fatty liver disease (NAFLD) is an increasing cause of chronic liver disease that accompanies obesity and the metabolic syndrome. Excess fructose consumption can initiate or exacerbate NAFLD in part due to a consequence of impaired hepatic fructose metabolism. Preclinical data emphasized that fructose-induced altered gut microbiome, increased gut permeability, and endotoxemia play an important role in NAFLD, but human studies are sparse. The present study aimed to determine if two weeks of excess fructose consumption significantly alters gut microbiota or permeability in humans. Methods/UNASSIGNED:). Each arm provided 75 grams of either fructose or glucose added to subjects' individual diets for 14 days, substituted isocalorically for complex carbohydrates, with a 19-day wash-out period between arms. Total fructose intake provided in the fructose arm of the study totaled a mean of 20.1% of calories. Outcome measures included fecal microbiota distribution, fecal metabolites, intestinal permeability, markers of endotoxemia, and plasma metabolites. Results/UNASSIGNED:), fecal metabolites, gut permeability, indices of endotoxemia, gut damage or inflammation, and plasma metabolites were essentially unchanged by either intervention. Conclusions/UNASSIGNED:In contrast to rodent preclinical findings, excess fructose did not cause changes in the gut microbiome, metabolome, and permeability as well as endotoxemia in humans with obesity fed fructose for 14 days in amounts known to enhance NAFLD.

Neurons communicate by the activity-dependent release of small-molecule neurotransmitters packaged into synaptic vesicles (SVs). Although many molecules have been identified as neurotransmitters, technical limitations have precluded a full metabolomic analysis of synaptic vesicle content. Here, we present a workflow to rapidly isolate SVs and to interrogate their metabolic contents at high-resolution using mass spectrometry. We validated the enrichment of glutamate in SVs of primary cortical neurons using targeted polar metabolomics. Unbiased and extensive global profiling of SVs isolated from these neurons revealed that the only detectable polar metabolites they contain are the established neurotransmitters glutamate and GABA. In addition, we adapted the approach to enable quick capture of SVs directly from brain tissue and determined the neurotransmitter profiles of diverse brain regions in a cell-type specific manner. The speed, robustness, and precision of this method to interrogate SV contents will facilitate novel insights into the chemical basis of neurotransmission.

A hallmark of metastasis is the adaptation of tumor cells to new environments. Metabolic constraints imposed by the serine and glycine-limited brain environment restrict metastatic tumor growth. How brain metastases overcome these growth-prohibitive conditions is poorly understood. Here, we demonstrate that 3-phosphoglycerate dehydrogenase (PHGDH), which catalyzes the rate-limiting step of glucose-derived serine synthesis, is a major determinant of brain metastasis in multiple human cancer types and preclinical models. Enhanced serine synthesis proved important for nucleotide production and cell proliferation in highly aggressive brain metastatic cells. In vivo, genetic suppression and pharmacological inhibition of PHGDH attenuated brain metastasis, but not extracranial tumor growth, and improved overall survival in mice. These results reveal that extracellular amino acid availability determines serine synthesis pathway dependence, and suggests that PHGDH inhibitors may be useful in the treatment of brain metastasis.

The filarial nematode Brugia malayi represents a leading cause of disability in the developing world, causing lymphatic filariasis in nearly 40 million people. Currently available drugs are not well-suited to mass drug administration efforts, so new treatments are urgently required. One potential vulnerability is the endosymbiotic bacteria Wolbachia-present in many filariae-which is vital to the worm. Genome scale metabolic networks have been used to study prokaryotes and protists and have proven valuable in identifying therapeutic targets, but have only been applied to multicellular eukaryotic organisms more recently. Here, we present iDC625, the first compartmentalized metabolic model of a parasitic worm. We used this model to show how metabolic pathway usage allows the worm to adapt to different environments, and predict a set of 102 reactions essential to the survival of B. malayi. We validated three of those reactions with drug tests and demonstrated novel antifilarial properties for all three compounds.

Pancreatic ductal adenocarcinoma (PDAC) evolves a complex microenvironment comprised of multiple cell types, including pancreatic stellate cells (PSCs). Previous studies have demonstrated that stromal supply of alanine, lipids, and nucleotides supports the metabolism, growth, and therapeutic resistance of PDAC. Here we demonstrate that alanine crosstalk between PSCs and PDAC is orchestrated by the utilization of specific transporters. PSCs utilize SLC1A4 and other transporter(s) to rapidly exchange and maintain environmental alanine concentrations. Moreover, PDAC cells upregulate SLC38A2 to supply their increased alanine demand. Cells lacking SLC38A2 fail to concentrate intracellular alanine and undergo a profound metabolic crisis resulting in markedly impaired tumor growth. Our results demonstrate that stromal-cancer metabolic niches can form through differential transporter expression, creating unique therapeutic opportunities to target metabolic demands of cancer.

Metabolomics is increasingly important for biomedical research, but large-scale metabolite identification in untargeted metabolomics is still challenging. Here, we present Jumbo Mass spectrometry-based Program of Metabolomics (JUMPm) software, a streamlined software tool for identifying potential metabolite formulas and structures in mass spectrometry. During database search, the false discovery rate is evaluated by a target-decoy strategy, where the decoys are produced by breaking the octet rule of chemistry. We illustrated the utility of JUMPm by detecting metabolite formulas and structures from liquid chromatography coupled tandem mass spectrometry (LC-MS/MS) analyses of unlabeled and stable-isotope labeled yeast samples. We also benchmarked the performance of JUMPm by analyzing a mixed sample from a commercially available metabolite library in both hydrophilic and hydrophobic LC-MS/MS. These analyses confirm that metabolite identification can be significantly improved by estimating the element composition in formulas using stable isotope labeling, or by introducing LC retention time during a spectral library search, which are incorporated into JUMPm functions. Finally, we compared the performance of JUMPm and two commonly used programs, Compound Discoverer 3.1 and MZmine 2, with respect to putative metabolite identifications. Our results indicate that JUMPm is an effective tool for metabolite identification of both unlabeled and labeled data in untargeted metabolomics.

OBJECTIVE:To characterize the ecological effects of biologic therapies on the gut bacterial and fungal microbiome of psoriatic arthritis (PsA)/spondyloarthritis (SpA) patients. METHODS:Fecal samples from PsA/SpA patients pre- and post-treatment with tumor necrosis factor inhibitors (TNFi; n=15) or an anti-interleukin (IL)-17A monoclonal antibody inhibitor (IL-17i; n=14) underwent sequencing (16S, ITS and shotgun metagenomics) and computational microbiome analysis. Fecal levels of fatty acid metabolites and cytokines/proteins implicated in PsA/SpA pathogenesis or intestinal inflammation were correlated with sequence data. Additionally, ileal biopsies obtained from SpA patients who developed clinically overt Crohn's disease (CD) after treatment with IL-17i (n=5) were analyzed for expression of IL-23/Th-17 related cytokines, IL-25/IL-17E-producing cells and type-2 innate lymphoid cells (ILC2s). RESULTS:There were significant shifts in abundance of specific taxa after treatment with IL-17i compared to TNFi, particularly Clostridiales (p=0.016) and Candida albicans (p=0.041). These subclinical alterations correlated with changes in bacterial community co-occurrence, metabolic pathways, IL-23/Th17-related cytokines and various fatty acids. Ileal biopsies showed that clinically overt CD was associated with expansion of IL-25/IL-17E-producing tuft cells and ILC2s (p<0.05) compared to pre-IL-17i treatment levels. CONCLUSION/CONCLUSIONS:In a subgroup of SpA patients, the initiation of IL-17A blockade correlated with features of subclinical gut inflammation and intestinal dysbiosis of certain bacterial and fungal taxa, most notably C. albicans. Further, IL-17i-related CD was associated with overexpression of IL-25/IL-17E-producing tuft cells and ILC2s. These results may help to explain the potential link between inhibition of a specific IL-17 pathway and the (sub)clinical gut inflammation observed in SpA.

Background and aims: Chronic granulomatous disease (CGD) is characterized by recurrent infections and inflammatory dysregulation, especially in the gut. Almost 50% of patients with CGD have CGD-associated inflammatory bowel disease (CGD-IBD), yet its pathophysiology remains poorly understood. We characterized the intestinal microbiome and metabolome in patients with CGD to determine if intestinal microbiome and metabolomic signatures could distinguish subpopulations of patients with CGD while using the metabolome to add a functional dimension to observed microbiome signatures.
Method(s): Clinical metadata and fecal samples were collected crosssectionally from healthy volunteers (HV; n=16) and patients with CGD (n=77). Metabolomic profiling and 16S rRNA (V4) sequencing was performed on fecal samples (total samples: 108; reads/sample: 15,254 to 191,415; median: 60,816).
Result(s): Samples from patients with CGD had distinct intestinal microbiome signatures and metabolomic profiles depending on genotype, presence of CGD-IBD and specific interventions (e.g. treatment with an elemental diet). Notably, samples from patients with active CGD-IBD (compared to samples from patients without a history of CGD-IBD) had significantly different alpha- and betadiversities, and were enriched for Enterococcus spp. (8.5 vs. 1.5%), Serratia spp. (8.6 vs. 3.9%) and Raoultella spp. (6.1 vs. 0.6%), while being depleted of Bacteroides spp. (9.3 vs. 23.6%). Metabolomic profiles from CGD patient samples pointed toward an aberrant metabolism of toxic ammonia waste by the intestinal microbiota compared to HV. Interestingly, use of an elemental diet to treat a patient with CGD-IBD induced long-term changes in the alpha- and beta-diversities of the patients intestinal microbiota, stabilized the intestinal metabolome, and allowed his microbial and metabolic profiles to resemble those of patients without CGD-IBD.
Conclusion(s): Intestinal microbiome and metabolomic signatures can distinguish subpopulations of patients CGD based on genotype, presence of intestinal inflammation and certain treatment interventions