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6 results on '"Duggan, Brendan M"'

1. Sharing and community curation of mass spectrometry data with Global Natural Products Social Molecular Networking

Author

Wang, Mingxun, Carver, Jeremy J., Phelan, Vanessa V., Sanchez, Laura M., Garg, Neha, Peng, Yao, Don Duy Nguyen, Watrous, Jeramie, Kapono, Clifford A., Luzzatto-knaan, Tal, Porto, Carla, Bouslimani, Amina, Melnik, Alexey V., Meehan, Michael J., Liu, Wei -ting, Criisemann, Max, Boudreau, Paul D., Esquenazi, Eduardo, Sandoval-calderon, Mario, Kersten, Roland D., Pace, Laura A., Quinn, Robert A., Duncan, Katherine R., Hsu, Cheng-chih, Floros, Dimitrios J., Gavilan, Ronnie G., Kleigrewe, Karin, Northen, Trent, Dutton, Rachel J., Parrot, Delphine, Carlson, Erin E., Aigle, Bertrand, Michelsen, Charlotte F., Jelsbak, Lars, Sohlenkamp, Christian, Pevzner, Pavel, Edlund, Anna, Mclean, Jeffrey, Piel, Jorn, Murphy, Brian T., Gerwick, Lena, Liaw, Chih-chuang, Yang, Yu-liang, Humpf, Hans-ulrich, Maansson, Maria, Keyzers, Robert A., Sims, Amy C., Johnson, Andrew R., Sidebottom, Ashley M., Sedio, Brian E., Klitgaard, Andreas, Larson, Charles B., Boya P, Cristopher A., Torres-mendoza, Daniel, Gonzalez, David J., Silva, Denise B., Marques, Lucas M., Demarque, Daniel P., Pociute, Egle, O'Neill, Ellis C., Briand, Enora, Helfrich, Eric J. N., Granatosky, Eve A., Glukhov, Evgenia, Ryffel, Florian, Houson, Hailey, Mohimani, Hosein, Kharbush, Jenan J., Zeng, Yi, Vorholt, Julia A., Kurita, Kenji L., Charusanti, Pep, Mcphail, Kerry L., Nielsen, Kristian Fog, Vuong, Lisa, Elfeki, Maryam, Traxler, Matthew F., Engene, Niclas, Koyama, Nobuhiro, Vining, Oliver B., Baric, Ralph, Silva, Ricardo R., Mascuch, Samantha J., Tomasi, Sophie, Jenkins, Stefan, Macherla, Venkat, Hoffman, Thomas, Agarwal, Vinayak, Williams, Philip G., Dai, Jingqui, Neupane, Ram, Gurr, Joshua, Rodriguez, Andres M. C., Lamsa, Anne, Zhang, Chen, Dorrestein, Kathleen, Duggan, Brendan M., Almaliti, Jehad, Allard, Pierre-marie, Phapale, Prasad, Nothias, Louis-felix, Alexandrovr, Theodore, Litaudon, Marc, Wolfender, Jean-luc, Kyle, Jennifer E., Metz, Thomas O., Peryea, Tyler, Dac-trung Nguyen, Vanleer, Danielle, Shinn, Paul, Jadhav, Ajit, Muller, Rolf, Waters, Katrina M., Shi, Wenyuan, Liu, Xueting, Zhang, Lixin, Knight, Rob, Jensen, Paul R., Palsson, Bernhard O., Pogliano, Kit, Linington, Roger G., Gutierrez, Marcelino, Lopes, Norberto P., Gerwick, William H., Moore, Bradley S., Dorrestein, Pieter C., Bandeira, Nuno, Wang, Mingxun, Carver, Jeremy J., Phelan, Vanessa V., Sanchez, Laura M., Garg, Neha, Peng, Yao, Don Duy Nguyen, Watrous, Jeramie, Kapono, Clifford A., Luzzatto-knaan, Tal, Porto, Carla, Bouslimani, Amina, Melnik, Alexey V., Meehan, Michael J., Liu, Wei -ting, Criisemann, Max, Boudreau, Paul D., Esquenazi, Eduardo, Sandoval-calderon, Mario, Kersten, Roland D., Pace, Laura A., Quinn, Robert A., Duncan, Katherine R., Hsu, Cheng-chih, Floros, Dimitrios J., Gavilan, Ronnie G., Kleigrewe, Karin, Northen, Trent, Dutton, Rachel J., Parrot, Delphine, Carlson, Erin E., Aigle, Bertrand, Michelsen, Charlotte F., Jelsbak, Lars, Sohlenkamp, Christian, Pevzner, Pavel, Edlund, Anna, Mclean, Jeffrey, Piel, Jorn, Murphy, Brian T., Gerwick, Lena, Liaw, Chih-chuang, Yang, Yu-liang, Humpf, Hans-ulrich, Maansson, Maria, Keyzers, Robert A., Sims, Amy C., Johnson, Andrew R., Sidebottom, Ashley M., Sedio, Brian E., Klitgaard, Andreas, Larson, Charles B., Boya P, Cristopher A., Torres-mendoza, Daniel, Gonzalez, David J., Silva, Denise B., Marques, Lucas M., Demarque, Daniel P., Pociute, Egle, O'Neill, Ellis C., Briand, Enora, Helfrich, Eric J. N., Granatosky, Eve A., Glukhov, Evgenia, Ryffel, Florian, Houson, Hailey, Mohimani, Hosein, Kharbush, Jenan J., Zeng, Yi, Vorholt, Julia A., Kurita, Kenji L., Charusanti, Pep, Mcphail, Kerry L., Nielsen, Kristian Fog, Vuong, Lisa, Elfeki, Maryam, Traxler, Matthew F., Engene, Niclas, Koyama, Nobuhiro, Vining, Oliver B., Baric, Ralph, Silva, Ricardo R., Mascuch, Samantha J., Tomasi, Sophie, Jenkins, Stefan, Macherla, Venkat, Hoffman, Thomas, Agarwal, Vinayak, Williams, Philip G., Dai, Jingqui, Neupane, Ram, Gurr, Joshua, Rodriguez, Andres M. C., Lamsa, Anne, Zhang, Chen, Dorrestein, Kathleen, Duggan, Brendan M., Almaliti, Jehad, Allard, Pierre-marie, Phapale, Prasad, Nothias, Louis-felix, Alexandrovr, Theodore, Litaudon, Marc, Wolfender, Jean-luc, Kyle, Jennifer E., Metz, Thomas O., Peryea, Tyler, Dac-trung Nguyen, Vanleer, Danielle, Shinn, Paul, Jadhav, Ajit, Muller, Rolf, Waters, Katrina M., Shi, Wenyuan, Liu, Xueting, Zhang, Lixin, Knight, Rob, Jensen, Paul R., Palsson, Bernhard O., Pogliano, Kit, Linington, Roger G., Gutierrez, Marcelino, Lopes, Norberto P., Gerwick, William H., Moore, Bradley S., Dorrestein, Pieter C., and Bandeira, Nuno

Abstract

The potential of the diverse chemistries present in natural products (NP) for biotechnology and medicine remains untapped because NP databases are not searchable with raw data and the NP community has no way to share data other than in published papers. Although mass spectrometry (MS) techniques are well-suited to high-throughput characterization of NP, there is a pressing need for an infrastructure to enable sharing and curation of data. We present Global Natural Products Social Molecular Networking (GNPS; http://gnps.ucsd.edu), an open-access knowledge base for community-wide organization and sharing of raw, processed or identified tandem mass (MS/MS) spectrometry data. In GNPS, crowdsourced curation of freely available community-wide reference MS libraries will underpin improved annotations. Data-driven social-networking should facilitate identification of spectra and foster collaborations. We also introduce the concept of 'living data' through continuous reanalysis of deposited data.

Published
2016
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3. Small Molecule Accurate Recognition Technology (SMART) to Enhance Natural Products Research.

Author

Zhang C, Idelbayev Y, Roberts N, Tao Y, Nannapaneni Y, Duggan BM, Min J, Lin EC, Gerwick EC, Cottrell GW, and Gerwick WH

Subjects
Cyanobacteria chemistry, Peptide Synthases chemistry, Biological Products chemistry, Data Analysis, Magnetic Resonance Spectroscopy methods, Neural Networks, Computer
Abstract

Various algorithms comparing 2D NMR spectra have been explored for their ability to dereplicate natural products as well as determine molecular structures. However, spectroscopic artefacts, solvent effects, and the interactive effect of functional group(s) on chemical shifts combine to hinder their effectiveness. Here, we leveraged Non-Uniform Sampling (NUS) 2D NMR techniques and deep Convolutional Neural Networks (CNNs) to create a tool, SMART, that can assist in natural products discovery efforts. First, an NUS heteronuclear single quantum coherence (HSQC) NMR pulse sequence was adapted to a state-of-the-art nuclear magnetic resonance (NMR) instrument, and data reconstruction methods were optimized, and second, a deep CNN with contrastive loss was trained on a database containing over 2,054 HSQC spectra as the training set. To demonstrate the utility of SMART, several newly isolated compounds were automatically located with their known analogues in the embedded clustering space, thereby streamlining the discovery pipeline for new natural products.

Published
2017
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5. Indexing the Pseudomonas specialized metabolome enabled the discovery of poaeamide B and the bananamides.

Author

Nguyen DD, Melnik AV, Koyama N, Lu X, Schorn M, Fang J, Aguinaldo K, Lincecum TL Jr, Ghequire MG, Carrion VJ, Cheng TL, Duggan BM, Malone JG, Mauchline TH, Sanchez LM, Kilpatrick AM, Raaijmakers JM, De Mot R, Moore BS, Medema MH, and Dorrestein PC

Subjects
Biosynthetic Pathways, Mass Spectrometry, Pseudomonas genetics, Triticum microbiology, Lipopeptides isolation & purification, Metabolome, Peptides, Cyclic isolation & purification, Pseudomonas chemistry
Abstract

Pseudomonads are cosmopolitan microorganisms able to produce a wide array of specialized metabolites. These molecules allow Pseudomonas to scavenge nutrients, sense population density and enhance or inhibit growth of competing microorganisms. However, these valuable metabolites are typically characterized one-molecule-one-microbe at a time, instead of being inventoried in large numbers. To index and map the diversity of molecules detected from these organisms, 260 strains of ecologically diverse origins were subjected to mass-spectrometry-based molecular networking. Molecular networking not only enables dereplication of molecules, but also sheds light on their structural relationships. Moreover, it accelerates the discovery of new molecules. Here, by indexing the Pseudomonas specialized metabolome, we report the molecular-networking-based discovery of four molecules and their evolutionary relationships: a poaeamide analogue and a molecular subfamily of cyclic lipopeptides, bananamides 1, 2 and 3. Analysis of their biosynthetic gene cluster shows that it constitutes a distinct evolutionary branch of the Pseudomonas cyclic lipopeptides. Through analysis of an additional 370 extracts of wheat-associated Pseudomonas, we demonstrate how the detailed knowledge from our reference index can be efficiently propagated to annotate complex metabolomic data from other studies, akin to the way in which newly generated genomic information can be compared to data from public databases.

Published
2016
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6. MS/MS-based networking and peptidogenomics guided genome mining revealed the stenothricin gene cluster in Streptomyces roseosporus.

Author

Liu WT, Lamsa A, Wong WR, Boudreau PD, Kersten R, Peng Y, Moree WJ, Duggan BM, Moore BS, Gerwick WH, Linington RG, Pogliano K, and Dorrestein PC

Subjects
Biotechnology methods, Data Mining, Glycosylation, Hydrolysis, Multigene Family, Anti-Bacterial Agents biosynthesis, Genome, Bacterial, Genomics methods, Streptomyces genetics, Tandem Mass Spectrometry methods
Abstract

Most (75%) of the anti-infectives that save countless lives and enormously improve quality of life originate from microbes found in nature. Herein, we described a global visualization of the detectable molecules produced from a single microorganism, which we define as the 'molecular network' of that organism, followed by studies to characterize the cellular effects of antibacterial molecules. We demonstrate that Streptomyces roseosporus produces at least four non-ribosomal peptide synthetase-derived molecular families and their gene subnetworks (daptomycin, arylomycin, napsamycin and stenothricin) were identified with different modes of action. A number of previously unreported analogs involving truncation, glycosylation, hydrolysis and biosynthetic intermediates and/or shunt products were also captured and visualized by creation of a map through MS/MS networking. The diversity of antibacterial compounds produced by S. roseosporus highlights the importance of developing new approaches to characterize the molecular capacity of an organism in a more global manner. This allows one to more deeply interrogate the biosynthetic capacities of microorganisms with the goal to streamline the discovery pipeline for biotechnological applications in agriculture and medicine. This is a contribution to a special issue to honor Chris Walsh's amazing career.

Published
2014
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