13 research outputs found
Identifying metabolites by integrating metabolome databases with mass spectrometry cheminformatics.
Novel metabolites distinct from canonical pathways can be identified through the integration of three cheminformatics tools: BinVestigate, which queries the BinBase gas chromatography-mass spectrometry (GC-MS) metabolome database to match unknowns with biological metadata across over 110,000 samples; MS-DIAL 2.0, a software tool for chromatographic deconvolution of high-resolution GC-MS or liquid chromatography-mass spectrometry (LC-MS); and MS-FINDER 2.0, a structure-elucidation program that uses a combination of 14 metabolome databases in addition to an enzyme promiscuity library. We showcase our workflow by annotating N-methyl-uridine monophosphate (UMP), lysomonogalactosyl-monopalmitin, N-methylalanine, and two propofol derivatives
Nicotinic acetylcholine receptor signaling maintains epithelial barrier integrity
Disruption of epithelial barriers is a common disease manifestation in chronic degenerative diseases of the airways, lung, and intestine. Extensive human genetic studies have identified risk loci in such diseases, including in chronic obstructive pulmonary disease (COPD) and inflammatory bowel diseases. The genes associated with these loci have not fully been determined, and functional characterization of such genes requires extensive studies in model organisms. Here, we report the results of a screen in Drosophila melanogaster that allowed for rapid identification, validation, and prioritization of COPD risk genes that were selected based on risk loci identified in human genome-wide association studies (GWAS). Using intestinal barrier dysfunction in flies as a readout, our results validate the impact of candidate gene perturbations on epithelial barrier function in 56% of the cases, resulting in a prioritized target gene list. We further report the functional characterization in flies of one family of these genes, encoding for nicotinic acetylcholine receptor (nAchR) subunits. We find that nAchR signaling in enterocytes of the fly gut promotes epithelial barrier function and epithelial homeostasis by regulating the production of the peritrophic matrix. Our findings identify COPD-associated genes critical for epithelial barrier maintenance, and provide insight into the role of epithelial nAchR signaling for homeostasis
Variation of solar absorptance of CNT coating with incident angle
Color poster with text, graphs, and imagesUniversity of Wisconsin--Stout Research Service
Dissecting the human gut microbiome to better decipher drug liability: A once-forgotten organ takes center stage
Background: The gut microbiome is a diverse system within the gastrointestinal tract composed of trillions of microorganisms (gut microbiota), along with their genomes. Accumulated evidence has revealed the significance of the gut microbiome in human health and disease. Due to its ability to alter drug/xenobiotic pharmacokinetics and therapeutic outcomes, this once-forgotten “metabolic organ” is receiving increasing attention. In parallel with the growing microbiome-driven studies, traditional analytical techniques and technologies have also evolved, allowing researchers to gain a deeper understanding of the functional and mechanistic effects of gut microbiome. Aim of review: From a drug development perspective, microbial drug metabolism is becoming increasingly critical as new modalities (e.g., degradation peptides) with potential microbial metabolism implications emerge. The pharmaceutical industry thus has a pressing need to stay up-to-date with, and continue pursuing, research efforts investigating clinical impact of the gut microbiome on drug actions whilst integrating advances in analytical technology and gut microbiome models. Our review aims to practically address this need by comprehensively introducing the latest innovations in microbial drug metabolism research— including strengths and limitations, to aid in mechanistically dissecting the impact of the gut microbiome on drug metabolism and therapeutic impact, and to develop informed strategies to address microbiome-related drug liability and minimize clinical risk. Key scientific concepts of review: We present comprehensive mechanisms and co-contributing factors by which the gut microbiome influences drug therapeutic outcomes. We highlight in vitro, in vivo, and in silico models for elucidating the mechanistic role and clinical impact of the gut microbiome on drugs in combination with high-throughput, functionally oriented, and physiologically relevant techniques. Integrating pharmaceutical knowledge and insight, we provide practical suggestions to pharmaceutical scientists for when, why, how, and what is next in microbial studies for improved drug efficacy and safety, and ultimately, support precision medicine formulation for personalized and efficacious therapies
Using Accurate Mass Gas Chromatography–Mass Spectrometry with the MINE Database for Epimetabolite Annotation
Mass spectrometry-based
untargeted metabolomics often detects statistically
significant metabolites that cannot be readily identified. Without
defined chemical structure, interpretation of the biochemical relevance
is not feasible. Epimetabolites are produced from canonical metabolites
by defined enzymatic reactions and may represent a large fraction
of the structurally unidentified metabolome. We here present a systematic
workflow for annotating unknown epimetabolites using high resolution
gas chromatography–accurate mass spectrometry with multiple
ionization techniques and stable isotope labeled derivatization methods.
We first determine elemental formulas, which are then used to query
the “metabolic in-silico expansion” database (MINE DB)
to obtain possible molecular structures that are predicted by enzyme
promiscuity from canonical pathways. Accurate mass fragmentation rules
are combined with in silico spectra prediction programs CFM-ID and
MS-FINDER to derive the best candidates. We validated the workflow
by correctly identifying 10 methylated nucleosides and 6 methylated
amino acids. We then employed this strategy to annotate eight unknown
compounds from cancer studies and other biological systems
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Tracking Polymicrobial Metabolism in Cystic Fibrosis Airways: Pseudomonas aeruginosa Metabolism and Physiology Are Influenced by Rothia mucilaginosa-Derived Metabolites.
Due to a lack of effective immune clearance, the airways of cystic fibrosis patients are colonized by polymicrobial communities. One of the most widespread and destructive opportunistic pathogens is Pseudomonas aeruginosa; however, P. aeruginosa does not colonize the airways alone. Microbes that are common in the oral cavity, such as Rothia mucilaginosa, are also present in cystic fibrosis patient sputum and have metabolic capacities different from those of P. aeruginosa Here we examine the metabolic interactions of P. aeruginosa and R. mucilaginosa using stable-isotope-assisted metabolomics. Glucose-derived 13C was incorporated into glycolysis metabolites, namely, lactate and acetate, and some amino acids in R. mucilaginosa grown aerobically and anaerobically. The amino acid glutamate was unlabeled in the R. mucilaginosa supernatant but incorporated the 13C label after P. aeruginosa was cross-fed the R. mucilaginosa supernatant in minimal medium and artificial-sputum medium. We provide evidence that P. aeruginosa utilizes R. mucilaginosa-produced metabolites as precursors for generation of primary metabolites, including glutamate.IMPORTANCEPseudomonas aeruginosa is a dominant and persistent cystic fibrosis pathogen. Although P. aeruginosa is accompanied by other microbes in the airways of cystic fibrosis patients, few cystic fibrosis studies show how P. aeruginosa is affected by the metabolism of other bacteria. Here, we demonstrate that P. aeruginosa generates primary metabolites using substrates produced by another microbe that is prevalent in the airways of cystic fibrosis patients, Rothia mucilaginosa These results indicate that P. aeruginosa may get a metabolic boost from its microbial neighbor, which might contribute to its pathogenesis in the airways of cystic fibrosis patients
Tracking Polymicrobial Metabolism in Cystic Fibrosis Airways: Pseudomonas aeruginosa Metabolism and Physiology Are Influenced by Rothia mucilaginosa-Derived Metabolites.
Due to a lack of effective immune clearance, the airways of cystic fibrosis patients are colonized by polymicrobial communities. One of the most widespread and destructive opportunistic pathogens is Pseudomonas aeruginosa; however, P. aeruginosa does not colonize the airways alone. Microbes that are common in the oral cavity, such as Rothia mucilaginosa, are also present in cystic fibrosis patient sputum and have metabolic capacities different from those of P. aeruginosa Here we examine the metabolic interactions of P. aeruginosa and R. mucilaginosa using stable-isotope-assisted metabolomics. Glucose-derived 13C was incorporated into glycolysis metabolites, namely, lactate and acetate, and some amino acids in R. mucilaginosa grown aerobically and anaerobically. The amino acid glutamate was unlabeled in the R. mucilaginosa supernatant but incorporated the 13C label after P. aeruginosa was cross-fed the R. mucilaginosa supernatant in minimal medium and artificial-sputum medium. We provide evidence that P. aeruginosa utilizes R. mucilaginosa-produced metabolites as precursors for generation of primary metabolites, including glutamate.IMPORTANCEPseudomonas aeruginosa is a dominant and persistent cystic fibrosis pathogen. Although P. aeruginosa is accompanied by other microbes in the airways of cystic fibrosis patients, few cystic fibrosis studies show how P. aeruginosa is affected by the metabolism of other bacteria. Here, we demonstrate that P. aeruginosa generates primary metabolites using substrates produced by another microbe that is prevalent in the airways of cystic fibrosis patients, Rothia mucilaginosa These results indicate that P. aeruginosa may get a metabolic boost from its microbial neighbor, which might contribute to its pathogenesis in the airways of cystic fibrosis patients
Tracking Polymicrobial Metabolism in Cystic Fibrosis Airways: Pseudomonas aeruginosa Metabolism and Physiology Are Influenced by Rothia mucilaginosa-Derived Metabolites
ABSTRACT Due to a lack of effective immune clearance, the airways of cystic fibrosis patients are colonized by polymicrobial communities. One of the most widespread and destructive opportunistic pathogens is Pseudomonas aeruginosa; however, P. aeruginosa does not colonize the airways alone. Microbes that are common in the oral cavity, such as Rothia mucilaginosa, are also present in cystic fibrosis patient sputum and have metabolic capacities different from those of P. aeruginosa. Here we examine the metabolic interactions of P. aeruginosa and R. mucilaginosa using stable-isotope-assisted metabolomics. Glucose-derived 13C was incorporated into glycolysis metabolites, namely, lactate and acetate, and some amino acids in R. mucilaginosa grown aerobically and anaerobically. The amino acid glutamate was unlabeled in the R. mucilaginosa supernatant but incorporated the 13C label after P. aeruginosa was cross-fed the R. mucilaginosa supernatant in minimal medium and artificial-sputum medium. We provide evidence that P. aeruginosa utilizes R. mucilaginosa-produced metabolites as precursors for generation of primary metabolites, including glutamate. IMPORTANCE Pseudomonas aeruginosa is a dominant and persistent cystic fibrosis pathogen. Although P. aeruginosa is accompanied by other microbes in the airways of cystic fibrosis patients, few cystic fibrosis studies show how P. aeruginosa is affected by the metabolism of other bacteria. Here, we demonstrate that P. aeruginosa generates primary metabolites using substrates produced by another microbe that is prevalent in the airways of cystic fibrosis patients, Rothia mucilaginosa. These results indicate that P. aeruginosa may get a metabolic boost from its microbial neighbor, which might contribute to its pathogenesis in the airways of cystic fibrosis patients
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Identification of small molecules using accurate mass MS/MS search
Tandem mass spectral library search (MS/MS) is the fastest way to correctly annotate MS/MS spectra from screening small molecules in fields such as environmental analysis, drug screening, lipid analysis, and metabolomics. The confidence in MS/MS-based annotation of chemical structures is impacted by instrumental settings and requirements, data acquisition modes including data-dependent and data-independent methods, library scoring algorithms, as well as post-curation steps. We critically discuss parameters that influence search results, such as mass accuracy, precursor ion isolation width, intensity thresholds, centroiding algorithms, and acquisition speed. A range of publicly and commercially available MS/MS databases such as NIST, MassBank, MoNA, LipidBlast, Wiley MSforID, and METLIN are surveyed. In addition, software tools including NIST MS Search, MS-DIAL, Mass Frontier, SmileMS, Mass++, and XCMS2 to perform fast MS/MS search are discussed. MS/MS scoring algorithms and challenges during compound annotation are reviewed. Advanced methods such as the in silico generation of tandem mass spectra using quantum chemistry and machine learning methods are covered. Community efforts for curation and sharing of tandem mass spectra that will allow for faster distribution of scientific discoveries are discussed