MolNetEnhancer: Enhanced Molecular Networks by Integrating Metabolome Mining and Annotation Tools
Madeleine Ernst,Madeleine Ernst,Kyo Bin Kang,Kyo Bin Kang,Andrés Mauricio Caraballo-Rodríguez,Louis-Félix Nothias,Joe Wandy,Christopher Chen,Mingxun Wang,Simon Rogers,Marnix H. Medema,Pieter C. Dorrestein,Pieter C. Dorrestein,Justin J. J. van der Hooft,Justin J. J. van der Hooft +14 more
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TLDR
MolNetEnhancer is a useful tool that greatly assists the metabolomics researcher in deciphering the metabolome through combination of multiple independent in silico pipelines.Abstract:
Metabolomics has started to embrace computational approaches for chemical interpretation of large data sets. Yet, metabolite annotation remains a key challenge. Recently, molecular networking and MS2LDA emerged as molecular mining tools that find molecular families and substructures in mass spectrometry fragmentation data. Moreover, in silico annotation tools obtain and rank candidate molecules for fragmentation spectra. Ideally, all structural information obtained and inferred from these computational tools could be combined to increase the resulting chemical insight one can obtain from a data set. However, integration is currently hampered as each tool has its own output format and efficient matching of data across these tools is lacking. Here, we introduce MolNetEnhancer, a workflow that combines the outputs from molecular networking, MS2LDA, in silico annotation tools (such as Network Annotation Propagation or DEREPLICATOR), and the automated chemical classification through ClassyFire to provide a more comprehensive chemical overview of metabolomics data whilst at the same time illuminating structural details for each fragmentation spectrum. We present examples from four plant and bacterial case studies and show how MolNetEnhancer enables the chemical annotation, visualization, and discovery of the subtle substructural diversity within molecular families. We conclude that MolNetEnhancer is a useful tool that greatly assists the metabolomics researcher in deciphering the metabolome through combination of multiple independent in silico pipelines.read more
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Feature-based molecular networking in the GNPS analysis environment.
Louis-Félix Nothias,Louis-Félix Nothias,Daniel Petras,Daniel Petras,Robin Schmid,Kai Dührkop,Johannes Rainer,Abinesh Sarvepalli,Abinesh Sarvepalli,Ivan Protsyuk,Madeleine Ernst,Madeleine Ernst,Madeleine Ernst,Hiroshi Tsugawa,Markus Fleischauer,Fabian Aicheler,Alexander A. Aksenov,Alexander A. Aksenov,Oliver Alka,Pierre-Marie Allard,Aiko Barsch,Xavier Cachet,Andrés Mauricio Caraballo-Rodríguez,Andrés Mauricio Caraballo-Rodríguez,Ricardo Silva,Ricardo Silva,Tam Dang,Tam Dang,Neha Garg,Julia M. Gauglitz,Julia M. Gauglitz,Alexey Gurevich,Giorgis Isaac,Alan K. Jarmusch,Alan K. Jarmusch,Zdeněk Kameník,Kyo Bin Kang,Kyo Bin Kang,Kyo Bin Kang,Nikolas Kessler,Irina Koester,Irina Koester,Ansgar Korf,Audrey Le Gouellec,Marcus Ludwig,Christian Martin H,Laura-Isobel McCall,Jonathan McSayles,Sven W. Meyer,Hosein Mohimani,Mustafa Morsy,Oriane Moyne,Oriane Moyne,Steffen Neumann,Heiko Neuweger,Ngoc Hung Nguyen,Ngoc Hung Nguyen,Mélissa Nothias-Esposito,Mélissa Nothias-Esposito,Julien Paolini,Vanessa V. Phelan,Tomáš Pluskal,Robert A. Quinn,Simon Rogers,Bindesh Shrestha,Anupriya Tripathi,Anupriya Tripathi,Justin J. J. van der Hooft,Justin J. J. van der Hooft,Justin J. J. van der Hooft,Fernando Vargas,Fernando Vargas,Kelly C. Weldon,Kelly C. Weldon,Michael Witting,Heejung Yang,Zheng Zhang,Zheng Zhang,Florian Zubeil,Oliver Kohlbacher,Sebastian Böcker,Theodore Alexandrov,Theodore Alexandrov,Nuno Bandeira,Nuno Bandeira,Mingxun Wang,Mingxun Wang,Pieter C. Dorrestein +87 more
TL;DR: Feature-based molecular networking (FBMN) as discussed by the authors is an analysis method in the Global Natural Products Social Molecular Networking (GNPS) infrastructure that builds on chromatographic feature detection and alignment tools.
Journal ArticleDOI
Towards the sustainable discovery and development of new antibiotics
Marcus Miethke,Marco Pieroni,Tilmann Weber,Mark Brönstrup,Peter Hammann,Ludovic Halby,Paola B. Arimondo,Philippe Glaser,Bertrand Aigle,Helge B. Bode,Helge B. Bode,Rui Moreira,Yanyan Li,Andriy Luzhetskyy,Marnix H. Medema,Jean-Luc Pernodet,Marc Stadler,José R. Tormo,Olga Genilloud,Andrew W. Truman,Kira J. Weissman,Eriko Takano,Stefano Sabatini,Evi Stegmann,Heike Brötz-Oesterhelt,Wolfgang Wohlleben,Myriam Seemann,Martin Empting,Anna K. H. Hirsch,Brigitta Loretz,Claus-Michael Lehr,Alexander Titz,Jennifer Herrmann,Timo Jaeger,Silke Alt,Thomas Hesterkamp,Mathias Winterhalter,Andrea Schiefer,Kenneth Pfarr,Achim Hoerauf,Heather Graz,Michael Graz,Mika Lindvall,Savithri Ramurthy,Anders Karlén,Maarten van Dongen,Hrvoje Petković,Andreas Keller,Frédéric Peyrane,Stefano Donadio,Laurent Fraisse,Laura J. V. Piddock,Ian H. Gilbert,Heinz E. Moser,Rolf Müller +54 more
TL;DR: In this paper, the authors present a strategic blueprint to substantially improve our ability to discover and develop new antibiotics, and propose both short-term and long-term solutions to overcome the most urgent limitations in the various sectors of research and funding.
Journal ArticleDOI
Systematic classification of unknown metabolites using high-resolution fragmentation mass spectra
Kai Dührkop,Louis-Félix Nothias,Markus Fleischauer,Raphael Reher,Marcus Ludwig,Martin Hoffmann,Martin Hoffmann,Daniel Petras,Daniel Petras,William H. Gerwick,William H. Gerwick,Juho Rousu,Pieter C. Dorrestein,Sebastian Böcker +13 more
TL;DR: The broad utility of CANOPUS is demonstrated by investigating the effect of microbial colonization in the mouse digestive system, through analysis of the chemodiversity of different Euphorbia plants and regarding the discovery of a marine natural product, revealing biological insights at the compound class level.
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Natural products targeting strategies involving molecular networking: different manners, one goal
TL;DR: This review illustrates through selected cornerstone studies the new thinking in natural product isolation by drawing a parallel between the different underlying philosophies behind the use of molecular networking in targeting natural products.
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Ecology and genomics of Actinobacteria: new concepts for natural product discovery.
TL;DR: It is argued that combining insights into actinobacterial ecology with state-of-the-art computational approaches holds great promise to unlock this unexplored reservoir of actinOBacterial metabolism.
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TL;DR: In GNPS, crowdsourced curation of freely available community-wide reference MS libraries will underpin improved annotations and data-driven social-networking should facilitate identification of spectra and foster collaborations.
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