Faculty Bibliography

RATIONALE/BACKGROUND:Microbiome studies of the lower airway based on bacterial 16S rRNA gene sequencing assess microbial community structure but can only infer functional characteristics. Microbial products, such as short chain fatty acids (SCFAs), in the lower airways have significant impact on the host's immune tone. Thus, functional approaches to the analyses of the microbiome are necessary. METHODS:Here we used upper and lower airway samples from a research bronchoscopy smoker cohort. In addition, we validated our results in an experimental mouse model. MEASUREMENTS/METHODS:We extended our microbiota characterisation beyond 16S rRNA gene sequencing with the use of whole genome (WGS) and RNA metatranscriptome sequencing. Short chain fatty acids (SCFA) were also measured in lower airway samples and correlated with each of the sequencing datasets. In the mouse model, 16S rRNA gene and RNA metatranscriptome sequencing were performed. MAIN RESULTS/RESULTS:Functional evaluations of the lower airway microbiota using inferred metagenome, WGS and metatranscriptome were dissimilar. Comparison with measured levels of SCFAs shows that the inferred metagenome from the 16S rRNA gene sequencing data was poorly correlated, while better correlations were noted when SCFAs levels were compared with WGS and metatranscriptome. Modelling lower airway aspiration with oral commensals in a mouse model showed that the metatranscriptome most efficiently captures transient active microbial metabolism, which was overestimated by 16S rRNA gene sequencing. CONCLUSIONS:Functional characterisation of the lower airway microbiota through metatranscriptome identify metabolically active organisms capable of producing metabolites with immunomodulatory capacity such as SCFAs.

OBJECTIVES/UNASSIGNED:(1) Determine the feasibility of obtaining a global, unbiased metabolomic profile on laryngeal muscle in a rat model; (2) evaluate the impact of biological aging on the laryngeal metabolome; and (3) characterize biochemical expression differences between aged and non-aged laryngeal and hindlimb muscle. METHODS/UNASSIGNED:Thyroarytenoid laryngeal muscle and plantaris hindlimb muscle were harvested from 5 young adult (9 months old) and 5 older adult (32 months old) F344BN rats. Tissue was processed and analyzed using LC-MS methods. Detected metabolites were compared to widely used metabolite databases and KEGG pathway enrichment was performed on significant metabolites. RESULTS/UNASSIGNED:The greatest differences in metabolite expression were between laryngeal and limb muscle with 126 different metabolites found between laryngeal and limb within the young group and 149 different metabolites within the old group. Significant hits between muscle groups highlighted amino acid differences between these tissues. There were more robust differences with age in limb muscle compared to laryngeal muscle. CONCLUSIONS/UNASSIGNED:Amino acid metabolism is a key difference between muscles of the limbs and larynx. Due to the number of differentially expressed metabolites between the 2 muscle groups, caution should be exercised when applying skeletal limb muscle physiology and biology concepts to the vocal muscles in both aged and non-aged musculoskeletal systems. Mechanisms underlying less robust effects of age on laryngeal muscle compared to limb muscle require elucidation.

D-type cyclins are central regulators of the cell division cycle and are among the most frequently deregulated therapeutic targets in human cancer¹, but the mechanisms that regulate their turnover are still being debated^2,3. Here, by combining biochemical and genetics studies in somatic cells, we identify CRL4^AMBRA1 (also known as CRL4^DCAF3) as the ubiquitin ligase that targets all three D-type cyclins for degradation. During development, loss of Ambra1 induces the accumulation of D-type cyclins and retinoblastoma (RB) hyperphosphorylation and hyperproliferation, and results in defects of the nervous system that are reduced by treating pregnant mice with the FDA-approved CDK4 and CDK6 (CDK4/6) inhibitor abemaciclib. Moreover, AMBRA1 acts as a tumour suppressor in mouse models and low AMBRA1 mRNA levels are predictive of poor survival in cancer patients. Cancer hotspot mutations in D-type cyclins abrogate their binding to AMBRA1 and induce their stabilization. Finally, a whole-genome, CRISPR-Cas9 screen identified AMBRA1 as a regulator of the response to CDK4/6 inhibition. Loss of AMBRA1 reduces sensitivity to CDK4/6 inhibitors by promoting the formation of complexes of D-type cyclins with CDK2. Collectively, our results reveal the molecular mechanism that controls the stability of D-type cyclins during cell-cycle progression, in development and in human cancer, and implicate AMBRA1 as a critical regulator of the RB pathway.

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.