Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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Author Correction: Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2
Bolyen, Evan ; Rideout, Jai Ram ; Dillon, Matthew R. ; Bokulich, Nicholas A. ; Abnet, Christian C. ; Al-Ghalith, Gabriel A. ; Alexander, Harriet ; Alm, Eric J. ; Arumugam, Manimozhiyan ; Asnicar, Francesco ; Bai, Yang ; Bisanz, Jordan E. ; Bittinger, Kyle ; Brejnrod, Asker ; Brislawn, Colin J. ; Brown, C.T. ; Callahan, Benjamin J. ; Caraballo-Rodríguez, Andrés Mauricio ; Chase, John ; Cope, Emily K. ; Silva, Ricardo Da; Diener, Christian ; Dorrestein, Pieter C. ; Douglas, Gavin M. ; Durall, Daniel M. ; Duvallet, Claire ; Edwardson, Christian F. ; Ernst, Madeleine ; Estaki, Mehrbod ; Fouquier, Jennifer ; Gauglitz, Julia M. ; Gibbons, Sean M. ; Gibson, Deanna L. ; Gonzalez, Antonio ; Gorlick, Kestrel ; Guo, Jiarong ; Hillmann, Benjamin ; Holmes, Susan ; Holste, Hannes ; Huttenhower, Curtis ; Huttley, Gavin A. ; Janssen, Stefan ; Jarmusch, Alan K. ; Jiang, Lingjing ; Kaehler, Benjamin D. ; Kang, Kyo Bin ; Keefe, Christopher R. ; Keim, Paul ; Kelley, Scott T. ; Knights, Dan ; Koester, Irina ; Kosciolek, Tomasz ; Kreps, Jorden ; Langille, Morgan G.I. ; Lee, Joslynn ; Ley, Ruth ; Liu, Yong Xin ; Loftfield, Erikka ; Lozupone, Catherine ; Maher, Massoud ; Marotz, Clarisse ; Martin, Bryan D. ; McDonald, Daniel ; McIver, Lauren J. ; Melnik, Alexey V. ; Metcalf, Jessica L. ; Morgan, Sydney C. ; Morton, Jamie T. ; Naimey, Ahmad Turan ; Navas-Molina, Jose A. ; Nothias, Louis Felix ; Orchanian, Stephanie B. ; Pearson, Talima ; Peoples, Samuel L. ; Petras, Daniel ; Preuss, Mary Lai ; Pruesse, Elmar ; Rasmussen, Lasse Buur ; Rivers, Adam ; Robeson, Michael S. ; Rosenthal, Patrick ; Segata, Nicola ; Shaffer, Michael ; Shiffer, Arron ; Sinha, Rashmi ; Song, Se Jin ; Spear, John R. ; Swafford, Austin D. ; Thompson, Luke R. ; Torres, Pedro J. ; Trinh, Pauline ; Tripathi, Anupriya ; Turnbaugh, Peter J. ; Ul-Hasan, Sabah ; Hooft, Justin J.J. van der; Vargas, Fernando ; Vázquez-Baeza, Yoshiki ; Vogtmann, Emily ; Hippel, Max von; Walters, William ; Wan, Yunhu ; Wang, Mingxun ; Warren, Jonathan ; Weber, Kyle C. ; Williamson, Charles H.D. ; Willis, Amy D. ; Xu, Zhenjiang Zech ; Zaneveld, Jesse R. ; Zhang, Yilong ; Zhu, Qiyun ; Knight, Rob ; Caporaso, J.G. - \ 2019
Nature Biotechnology (2019). - ISSN 1087-0156

In the version of this article initially published, some reference citations were incorrect. The three references to Jupyter Notebooks should have cited Kluyver et al. instead of Gonzalez et al. The reference to Qiita should have cited Gonzalez et al. instead of Schloss et al. The reference to mothur should have cited Schloss et al. instead of McMurdie & Holmes. The reference to phyloseq should have cited McMurdie & Holmes instead of Huber et al. The reference to Bioconductor should have cited Huber et al. instead of Franzosa et al. And the reference to the biobakery suite should have cited Franzosa et al. instead of Kluyver et al. The errors have been corrected in the HTML and PDF versions of the article.

Molnetenhancer: Enhanced molecular networks by integrating metabolome mining and annotation tools
Ernst, Madeleine ; Kang, Kyo Bin ; Caraballo-Rodríguez, Andrés Mauricio ; Nothias, Louis Felix ; Wandy, Joe ; Chen, Christopher ; Wang, Mingxun ; Rogers, Simon ; Medema, Marnix H. ; Dorrestein, Pieter C. ; Hooft, Justin J.J. van der - \ 2019
Metabolites 9 (2019)7. - ISSN 2218-1989
Chemical classification - In silico workflows - Metabolite annotation - Metabolite identification - Metabolome mining - Molecular families - Networking - Substructures

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.

Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2
Bolyen, Evan ; Rideout, Jai Ram ; Dillon, Matthew R. ; Bokulich, Nicholas A. ; Abnet, Christian C. ; Al-Ghalith, Gabriel A. ; Alexander, Harriet ; Alm, Eric J. ; Arumugam, Manimozhiyan ; Asnicar, Francesco ; Bai, Yang ; Bisanz, Jordan E. ; Bittinger, Kyle ; Brejnrod, Asker ; Brislawn, Colin J. ; Brown, Titus C. ; Callahan, Benjamin J. ; Caraballo-Rodríguez, Andrés Mauricio ; Chase, John ; Cope, Emily K. ; Silva, Ricardo da; Diener, Christian ; Dorrestein, Pieter C. ; Douglas, Gavin M. ; Durall, Daniel M. ; Duvallet, Claire ; Edwardson, Christian F. ; Ernst, Madeleine ; Estaki, Mehrbod ; Fouquier, Jennifer ; Gauglitz, Julia M. ; Gibbons, Sean M. ; Gibson, Deanna L. ; Gonzalez, Antonio ; Gorlick, Kestrel ; Guo, Jiarong ; Hillmann, Benjamin ; Holmes, Susan ; Holste, Hannes ; Huttenhower, Curtis ; Huttley, Gavin A. ; Janssen, Stefan ; Jarmusch, Alan K. ; Jiang, Lingjing ; Kaehler, Benjamin D. ; Kang, Kyo Bin ; Keefe, Christopher R. ; Keim, Paul ; Kelley, Scott T. ; Knights, Dan ; Koester, Irina ; Kosciolek, Tomasz ; Kreps, Jorden ; Langille, Morgan G.I. ; Lee, Joslynn ; Ley, Ruth ; Liu, Yong Xin ; Loftfield, Erikka ; Lozupone, Catherine ; Maher, Massoud ; Marotz, Clarisse ; Martin, Bryan D. ; McDonald, Daniel ; McIver, Lauren J. ; Melnik, Alexey V. ; Metcalf, Jessica L. ; Morgan, Sydney C. ; Morton, Jamie T. ; Naimey, Ahmad Turan ; Navas-Molina, Jose A. ; Nothias, Louis Felix ; Orchanian, Stephanie B. ; Pearson, Talima ; Peoples, Samuel L. ; Petras, Daniel ; Preuss, Mary Lai ; Pruesse, Elmar ; Rasmussen, Lasse Buur ; Rivers, Adam ; Robeson, Michael S. ; Rosenthal, Patrick ; Segata, Nicola ; Shaffer, Michael ; Shiffer, Arron ; Sinha, Rashmi ; Song, Se Jin ; Spear, John R. ; Swafford, Austin D. ; Thompson, Luke R. ; Torres, Pedro J. ; Trinh, Pauline ; Tripathi, Anupriya ; Turnbaugh, Peter J. ; Ul-Hasan, Sabah ; Hooft, Justin J.J. van der; Vargas, Fernando ; Vázquez-Baeza, Yoshiki ; Vogtmann, Emily ; Hippel, Max von; Walters, William ; Wan, Yunhu ; Wang, Mingxun ; Warren, Jonathan ; Weber, Kyle C. ; Williamson, Charles H.D. ; Willis, Amy D. ; Xu, Zhenjiang Zech ; Zaneveld, Jesse R. ; Zhang, Yilong ; Zhu, Qiyun ; Knight, Rob ; Caporaso, J.G. - \ 2019
Nature Biotechnology 37 (2019)8. - ISSN 1087-0156 - p. 852 - 857.
Assessing specialized metabolite diversity in the cosmopolitan plant genus Euphorbia l.
Ernst, Madeleine ; Nothias, Louis Félix ; Hooft, Justin J.J. van der; Silva, Ricardo R. ; Saslis-Lagoudakis, Haris C. ; Grace, Olwen M. ; Martinez-Swatson, Karen ; Hassemer, Gustavo ; Funez, Luís A. ; Simonsen, Henrik T. ; Medema, Marnix H. ; Staerk, Dan ; Nilsson, Niclas ; Lovato, Paola ; Dorrestein, Pieter C. ; Rønsted, Nina - \ 2019
Frontiers in Plant Science 10 (2019). - ISSN 1664-462X
Coevolution - Computational metabolomics - Euphorbia - Immunomodulatory testing - Specialized metabolites

Coevolutionary theory suggests that an arms race between plants and herbivores yields increased plant specialized metabolite diversity and the geographic mosaic theory of coevolution predicts that coevolutionary interactions vary across geographic scales. Consequently, plant specialized metabolite diversity is expected to be highest in coevolutionary hotspots, geographic regions, which exhibit strong reciprocal selection on the interacting species. Despite being well-established theoretical frameworks, technical limitations have precluded rigorous hypothesis testing. Here we aim at understanding how geographic separation over evolutionary time may have impacted chemical differentiation in the cosmopolitan plant genus Euphorbia. We use a combination of state-of-the-art computational mass spectral metabolomics tools together with cell-based high-throughput immunomodulatory testing. Our results show significant differences in specialized metabolite diversity across geographically separated phylogenetic clades. Chemical structural diversity of the highly toxic Euphorbia diterpenoids is significantly reduced in species native to the Americas, compared to Afro-Eurasia. The localization of these compounds to young stems and roots suggest a possible ecological relevance in herbivory defense. This is further supported by reduced immunomodulatory activity in the American subclade as well as herbivore distribution patterns. We conclude that computational mass spectrometric metabolomics coupled with relevant ecological data provide a strong tool for exploring plant specialized metabolite diversity in a chemo-evolutionary framework.

Propagating annotations of molecular networks using in silico fragmentation
Silva, Ricardo R. da; Wang, Mingxun ; Nothias, Louis Félix ; Hooft, Justin J.J. van der; Caraballo-Rodríguez, Andrés Mauricio ; Fox, Evan ; Balunas, Marcy J. ; Klassen, Jonathan L. ; Lopes, Norberto Peporine ; Dorrestein, Pieter C. - \ 2018
PLoS Computational Biology 14 (2018)4. - ISSN 1553-734X

The annotation of small molecules is one of the most challenging and important steps in untargeted mass spectrometry analysis, as most of our biological interpretations rely on structural annotations. Molecular networking has emerged as a structured way to organize and mine data from untargeted tandem mass spectrometry (MS/MS) experiments and has been widely applied to propagate annotations. However, propagation is done through manual inspection of MS/MS spectra connected in the spectral networks and is only possible when a reference library spectrum is available. One of the alternative approaches used to annotate an unknown fragmentation mass spectrum is through the use of in silico predictions. One of the challenges of in silico annotation is the uncertainty around the correct structure among the predicted candidate lists. Here we show how molecular networking can be used to improve the accuracy of in silico predictions through propagation of structural annotations, even when there is no match to a MS/MS spectrum in spectral libraries. This is accomplished through creating a network consensus of re-ranked structural candidates using the molecular network topology and structural similarity to improve in silico annotations. The Network Annotation Propagation (NAP) tool is accessible through the GNPS web-platform https://gnps.ucsd.edu/ProteoSAFe/static/gnps-theoretical.jsp.

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