Auto-deconvolution and molecular networking of gas chromatography–mass spectrometry data

Alexander A. Aksenov; Ivan Laponogov; Zheng Zhang; Sophie L.F. Doran; Ilaria Belluomo; Dennis Veselkov; Wout Bittremieux; Louis Felix Nothias; Mélissa Nothias-Esposito; Katherine N. Maloney; Biswapriya B. Misra; Alexey V. Melnik; Aleksandr Smirnov; Xiuxia Du; Kenneth L. Jones; Kathleen Dorrestein; Morgan Panitchpakdi; Madeleine Ernst; Justin J.J. van der Hooft; Mabel Gonzalez; Chiara Carazzone; Adolfo Amézquita; Chris Callewaert; James T. Morton; Robert A. Quinn; Amina Bouslimani; Andrea Albarracín Orio; Daniel Petras; Andrea M. Smania; Sneha P. Couvillion; Meagan C. Burnet; Carrie D. Nicora; Erika Zink; Thomas O. Metz; Viatcheslav Artaev; Elizabeth Humston-Fulmer; Rachel Gregor; Michael M. Meijler; Itzhak Mizrahi; Stav Eyal; Brooke Anderson; Rachel Dutton; Raphaël Lugan; Pauline Le Boulch; Yann Guitton; Stephanie Prevost; Audrey Poirier; Bruno Le Bizec; Aaron Fait; Noga Sikron Persi; Chao Song; Kelem Gashu; Roxana Coras; Monica Guma; Julia Manasson; Jose U. Scher; Dinesh Kumar Barupal; Saleh Alseekh; Alisdair R. Fernie; Reza Mirnezami; Vasilis Vasiliou; Robin Schmid; Roman S. Borisov; Larisa N. Kulikova; Rob Knight; Mingxun Wang; George B. Hanna; Pieter C. Dorrestein; Kirill Veselkov

doi:10.1038/s41587-020-0700-3

Auto-deconvolution and molecular networking of gas chromatography–mass spectrometry data

Alexander A. Aksenov, Ivan Laponogov, Zheng Zhang, Sophie L.F. Doran, Ilaria Belluomo, Dennis Veselkov, Wout Bittremieux, Louis Felix Nothias, Mélissa Nothias-Esposito, Katherine N. Maloney, Biswapriya B. Misra, Alexey V. Melnik, Aleksandr Smirnov, Xiuxia Du, Kenneth L. Jones, Kathleen Dorrestein, Morgan Panitchpakdi, Madeleine Ernst, Justin J.J. van der Hooft, Mabel GonzalezChiara Carazzone, Adolfo Amézquita, Chris Callewaert, James T. Morton, Robert A. Quinn, Amina Bouslimani, Andrea Albarracín Orio, Daniel Petras, Andrea M. Smania, Sneha P. Couvillion, Meagan C. Burnet, Carrie D. Nicora, Erika Zink, Thomas O. Metz, Viatcheslav Artaev, Elizabeth Humston-Fulmer, Rachel Gregor, Michael M. Meijler, Itzhak Mizrahi, Stav Eyal, Brooke Anderson, Rachel Dutton, Raphaël Lugan, Pauline Le Boulch, Yann Guitton, Stephanie Prevost, Audrey Poirier, Bruno Le Bizec, Aaron Fait, Noga Sikron Persi, Chao Song, Kelem Gashu, Roxana Coras, Monica Guma, Julia Manasson, Jose U. Scher, Dinesh Kumar Barupal, Saleh Alseekh, Alisdair R. Fernie, Reza Mirnezami, Vasilis Vasiliou, Robin Schmid, Roman S. Borisov, Larisa N. Kulikova, Rob Knight, Mingxun Wang, George B. Hanna, Pieter C. Dorrestein, Kirill Veselkov

Ben-Gurion University of the Negev

Research output: Contribution to journal › Article › peer-review

Abstract

We engineered a machine learning approach, MSHub, to enable auto-deconvolution of gas chromatography–mass spectrometry (GC–MS) data. We then designed workflows to enable the community to store, process, share, annotate, compare and perform molecular networking of GC–MS data within the Global Natural Product Social (GNPS) Molecular Networking analysis platform. MSHub/GNPS performs auto-deconvolution of compound fragmentation patterns via unsupervised non-negative matrix factorization and quantifies the reproducibility of fragmentation patterns across samples.

Original language	American English
Pages (from-to)	169-173
Number of pages	5
Journal	Nature biotechnology
Volume	39
Issue number	2
DOIs	https://doi.org/10.1038/s41587-020-0700-3
State	Published - 1 Feb 2021

All Science Journal Classification (ASJC) codes

Biotechnology
Bioengineering
Applied Microbiology and Biotechnology
Molecular Medicine
Biomedical Engineering

Access to Document

10.1038/s41587-020-0700-3

Cite this

Aksenov, A. A., Laponogov, I., Zhang, Z., Doran, S. L. F., Belluomo, I., Veselkov, D., Bittremieux, W., Nothias, L. F., Nothias-Esposito, M., Maloney, K. N., Misra, B. B., Melnik, A. V., Smirnov, A., Du, X., Jones, K. L., Dorrestein, K., Panitchpakdi, M., Ernst, M., van der Hooft, J. J. J., ... Veselkov, K. (2021). Auto-deconvolution and molecular networking of gas chromatography–mass spectrometry data. Nature biotechnology, 39(2), 169-173. https://doi.org/10.1038/s41587-020-0700-3

@article{db65e5a77ae74a8694fce238b1896e92,

title = "Auto-deconvolution and molecular networking of gas chromatography–mass spectrometry data",

abstract = "We engineered a machine learning approach, MSHub, to enable auto-deconvolution of gas chromatography–mass spectrometry (GC–MS) data. We then designed workflows to enable the community to store, process, share, annotate, compare and perform molecular networking of GC–MS data within the Global Natural Product Social (GNPS) Molecular Networking analysis platform. MSHub/GNPS performs auto-deconvolution of compound fragmentation patterns via unsupervised non-negative matrix factorization and quantifies the reproducibility of fragmentation patterns across samples.",

author = "Aksenov, {Alexander A.} and Ivan Laponogov and Zheng Zhang and Doran, {Sophie L.F.} and Ilaria Belluomo and Dennis Veselkov and Wout Bittremieux and Nothias, {Louis Felix} and M{\'e}lissa Nothias-Esposito and Maloney, {Katherine N.} and Misra, {Biswapriya B.} and Melnik, {Alexey V.} and Aleksandr Smirnov and Xiuxia Du and Jones, {Kenneth L.} and Kathleen Dorrestein and Morgan Panitchpakdi and Madeleine Ernst and {van der Hooft}, {Justin J.J.} and Mabel Gonzalez and Chiara Carazzone and Adolfo Am{\'e}zquita and Chris Callewaert and Morton, {James T.} and Quinn, {Robert A.} and Amina Bouslimani and Orio, {Andrea Albarrac{\'i}n} and Daniel Petras and Smania, {Andrea M.} and Couvillion, {Sneha P.} and Burnet, {Meagan C.} and Nicora, {Carrie D.} and Erika Zink and Metz, {Thomas O.} and Viatcheslav Artaev and Elizabeth Humston-Fulmer and Rachel Gregor and Meijler, {Michael M.} and Itzhak Mizrahi and Stav Eyal and Brooke Anderson and Rachel Dutton and Rapha{\"e}l Lugan and Boulch, {Pauline Le} and Yann Guitton and Stephanie Prevost and Audrey Poirier and {Le Bizec}, Bruno and Aaron Fait and Persi, {Noga Sikron} and Chao Song and Kelem Gashu and Roxana Coras and Monica Guma and Julia Manasson and Scher, {Jose U.} and Barupal, {Dinesh Kumar} and Saleh Alseekh and Fernie, {Alisdair R.} and Reza Mirnezami and Vasilis Vasiliou and Robin Schmid and Borisov, {Roman S.} and Kulikova, {Larisa N.} and Rob Knight and Mingxun Wang and Hanna, {George B.} and Dorrestein, {Pieter C.} and Kirill Veselkov",

note = "Publisher Copyright: {\textcopyright} 2020, The Author(s), under exclusive licence to Springer Nature America, Inc.",

year = "2021",

month = feb,

day = "1",

doi = "10.1038/s41587-020-0700-3",

language = "American English",

volume = "39",

pages = "169--173",

journal = "Nature biotechnology",

issn = "1087-0156",

publisher = "Nature Research",

number = "2",

}

Aksenov, AA, Laponogov, I, Zhang, Z, Doran, SLF, Belluomo, I, Veselkov, D, Bittremieux, W, Nothias, LF, Nothias-Esposito, M, Maloney, KN, Misra, BB, Melnik, AV, Smirnov, A, Du, X, Jones, KL, Dorrestein, K, Panitchpakdi, M, Ernst, M, van der Hooft, JJJ, Gonzalez, M, Carazzone, C, Amézquita, A, Callewaert, C, Morton, JT, Quinn, RA, Bouslimani, A, Orio, AA, Petras, D, Smania, AM, Couvillion, SP, Burnet, MC, Nicora, CD, Zink, E, Metz, TO, Artaev, V, Humston-Fulmer, E, Gregor, R, Meijler, MM , Mizrahi, I, Eyal, S, Anderson, B, Dutton, R, Lugan, R, Boulch, PL, Guitton, Y, Prevost, S, Poirier, A, Le Bizec, B, Fait, A, Persi, NS, Song, C, Gashu, K, Coras, R, Guma, M, Manasson, J, Scher, JU, Barupal, DK, Alseekh, S, Fernie, AR, Mirnezami, R, Vasiliou, V, Schmid, R, Borisov, RS, Kulikova, LN, Knight, R, Wang, M, Hanna, GB, Dorrestein, PC & Veselkov, K 2021, 'Auto-deconvolution and molecular networking of gas chromatography–mass spectrometry data', Nature biotechnology, vol. 39, no. 2, pp. 169-173. https://doi.org/10.1038/s41587-020-0700-3

TY - JOUR

T1 - Auto-deconvolution and molecular networking of gas chromatography–mass spectrometry data

AU - Aksenov, Alexander A.

AU - Laponogov, Ivan

AU - Zhang, Zheng

AU - Doran, Sophie L.F.

AU - Belluomo, Ilaria

AU - Veselkov, Dennis

AU - Bittremieux, Wout

AU - Nothias, Louis Felix

AU - Nothias-Esposito, Mélissa

AU - Maloney, Katherine N.

AU - Misra, Biswapriya B.

AU - Melnik, Alexey V.

AU - Smirnov, Aleksandr

AU - Du, Xiuxia

AU - Jones, Kenneth L.

AU - Dorrestein, Kathleen

AU - Panitchpakdi, Morgan

AU - Ernst, Madeleine

AU - van der Hooft, Justin J.J.

AU - Gonzalez, Mabel

AU - Carazzone, Chiara

AU - Amézquita, Adolfo

AU - Callewaert, Chris

AU - Morton, James T.

AU - Quinn, Robert A.

AU - Bouslimani, Amina

AU - Orio, Andrea Albarracín

AU - Petras, Daniel

AU - Smania, Andrea M.

AU - Couvillion, Sneha P.

AU - Burnet, Meagan C.

AU - Nicora, Carrie D.

AU - Zink, Erika

AU - Metz, Thomas O.

AU - Artaev, Viatcheslav

AU - Humston-Fulmer, Elizabeth

AU - Gregor, Rachel

AU - Meijler, Michael M.

AU - Mizrahi, Itzhak

AU - Eyal, Stav

AU - Anderson, Brooke

AU - Dutton, Rachel

AU - Lugan, Raphaël

AU - Boulch, Pauline Le

AU - Guitton, Yann

AU - Prevost, Stephanie

AU - Poirier, Audrey

AU - Le Bizec, Bruno

AU - Fait, Aaron

AU - Persi, Noga Sikron

AU - Song, Chao

AU - Gashu, Kelem

AU - Coras, Roxana

AU - Guma, Monica

AU - Manasson, Julia

AU - Scher, Jose U.

AU - Barupal, Dinesh Kumar

AU - Alseekh, Saleh

AU - Fernie, Alisdair R.

AU - Mirnezami, Reza

AU - Vasiliou, Vasilis

AU - Schmid, Robin

AU - Borisov, Roman S.

AU - Kulikova, Larisa N.

AU - Knight, Rob

AU - Wang, Mingxun

AU - Hanna, George B.

AU - Dorrestein, Pieter C.

AU - Veselkov, Kirill

PY - 2021/2/1

Y1 - 2021/2/1

N2 - We engineered a machine learning approach, MSHub, to enable auto-deconvolution of gas chromatography–mass spectrometry (GC–MS) data. We then designed workflows to enable the community to store, process, share, annotate, compare and perform molecular networking of GC–MS data within the Global Natural Product Social (GNPS) Molecular Networking analysis platform. MSHub/GNPS performs auto-deconvolution of compound fragmentation patterns via unsupervised non-negative matrix factorization and quantifies the reproducibility of fragmentation patterns across samples.

AB - We engineered a machine learning approach, MSHub, to enable auto-deconvolution of gas chromatography–mass spectrometry (GC–MS) data. We then designed workflows to enable the community to store, process, share, annotate, compare and perform molecular networking of GC–MS data within the Global Natural Product Social (GNPS) Molecular Networking analysis platform. MSHub/GNPS performs auto-deconvolution of compound fragmentation patterns via unsupervised non-negative matrix factorization and quantifies the reproducibility of fragmentation patterns across samples.

UR - http://www.scopus.com/inward/record.url?scp=85095678581&partnerID=8YFLogxK

U2 - 10.1038/s41587-020-0700-3

DO - 10.1038/s41587-020-0700-3

M3 - Article

C2 - 33169034

SN - 1087-0156

VL - 39

SP - 169

EP - 173

JO - Nature biotechnology

JF - Nature biotechnology

IS - 2

ER -

Auto-deconvolution and molecular networking of gas chromatography–mass spectrometry data

Abstract

All Science Journal Classification (ASJC) codes

Access to Document

Other files and links

Fingerprint

Cite this