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Record W4391543451 · doi:10.1038/s41564-023-01575-9

microbeMASST: a taxonomically informed mass spectrometry search tool for microbial metabolomics data

2024· article· en· W4391543451 on OpenAlexfundno aff
Simone Zuffa, Robin Schmid, Anelize Bauermeister, Paulo Wender Portal Gomes, Andrés Mauricio Caraballo‐Rodríguez, Yasin El Abiead, Allegra T. Aron, Emily C. Gentry, Jasmine Zemlin, Michael J. Meehan, Nicole E. Avalon, Robert H. Cichewicz, Ekaterina Buzun, Marvic Carrillo Terrazas, Chia-Yun Hsu, Renee Oles, Adriana Vasquez Ayala, Jiaqi Zhao, Hiutung Chu, Mirte C. M. Kuijpers, Sara L. Jackrel, Fidele Tugizimana, Lerato Nephali, Ian A. Dubery, Ntakadzeni Edwin Madala, Eduarda Antunes Moreira, Letícia V. Costa‐Lotufo, Norberto Peporine Lopes, Paula Rezende‐Teixeira, Paula C. Jimenez, Bipin Rimal, Andrew D. Patterson, Matthew F. Traxler, Rita de Cássia Pessotti, Daniel Alvarado-Villalobos, Giselle Tamayo‐Castillo, Priscila Chaverrí, Efraín Escudero‐Leyva, Luis-Manuel Quirós-Guerrero, Alexandre Bory, Juliette Joubert, Adriano Rutz, Jean‐Luc Wolfender, Pierre‐Marie Allard, Andreas Sichert, Sammy Pontrelli, Benjamin Pullman, Nuno Bandeira, William H. Gerwick, Katia Gindro, Josep Massana‐Codina, Berenike Wagner, Karl Forchhammer, Daniel Petras, Nicole Aiosa, Neha Garg, Manuel Liebeke, Patric Bourceau, Kyo Bin Kang, Henna Gadhavi, Luiz Pedro S. de Carvalho, Mariana Silva dos Santos, Alicia Isabel Pérez‐Lorente, Carlos Molina‐Santiago, Diego Romero, Raimo Franke, Mark Brönstrup, Arturo Vera Ponce de León, Phillip B. Pope, Sabina Leanti La Rosa, Giorgia La Barbera, Henrik M. Roager, Martin Frederik Laursen, Fabian Hammerle, Bianka Siewert, Ursula Peintner, Cuauhtémoc Licona‐Cassani, Lorena Rodríguez-Orduña, Evelyn Rampler, Felina Hildebrand, Gunda Koellensperger, Harald Schoeny, Katharina Hohenwallner, Lisa Panzenboeck, Rachel Gregor, Ellis C. O’Neill, Eve Tallulah Roxborough, Jane Odoi, Nicole J. Bale, Su Ding, Jaap S. Sinninghe Damsté, Xue Li Guan, Jerry Cui, Kou‐San Ju, Denise Brentan Silva, Fernanda Motta Ribeiro Silva, Gilvan Ferreira da Silva, Héctor H. F. Koolen, Carlismari O. Grundmann, Jason A. Clement, Hosein Mohimani, Kirk Broders, Kerry L. McPhail, Sidnee E. Ober-Singleton, Christopher M. Rath, Daniel McDonald, Rob Knight, Mingxun Wang, Pieter C. Dorrestein

Bibliographic record

VenueNature Microbiology · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMetabolomics and Mass Spectrometry Studies
Canadian institutionsnot available
FundersNational Institute of Arthritis and Musculoskeletal and Skin DiseasesNational Institute of Diabetes and Digestive and Kidney DiseasesNational Institute of Allergy and Infectious DiseasesNational Center for Complementary and Integrative HealthNational Institute on AgingBiotechnology and Biological Sciences Research CouncilAgricultural Research ServiceNational Institutes of HealthJunta de AndalucíaNovo Nordisk FondenNorges ForskningsrådUniversidad de Costa RicaInstituto Tecnológico y de Estudios Superiores de MonterreyFundação de Amparo à Pesquisa do Estado do AmazonasMinisterio de Ciencia e InnovaciónFord FoundationNational Research Foundation of KoreaConselho Nacional de Desenvolvimento Científico e TecnológicoNederlandse Organisatie voor Wetenschappelijk OnderzoekConsejo Nacional de Ciencia y TecnologíaNational Research FoundationAustrian Science FundDeutsche ForschungsgemeinschaftFundação de Apoio ao Desenvolvimento do Ensino, Ciência e Tecnologia do Estado de Mato Grosso do SulEidgenössische Technische Hochschule ZürichFundação de Amparo à Pesquisa do Estado de São PauloNational Institute of General Medical SciencesFrancis Crick InstituteUniversidad de MálagaNational Academies of Sciences, Engineering, and MedicineU.S. National Library of MedicineCanadian Institute for Advanced ResearchGordon and Betty Moore FoundationMinistry of Science and ICT, South KoreaNovo NordiskDeutsches Zentrum für InfektionsforschungMax-Planck-GesellschaftSimons FoundationHoward Hughes Medical InstituteU.S. Department of AgricultureNational Science FoundationSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungU.S. Department of Health and Human Services
KeywordsMetabolomicsComputational biologyMass spectrometryBiologyChemistryBioinformaticsChromatography

Abstract

fetched live from OpenAlex

microbeMASST, a taxonomically informed mass spectrometry (MS) search tool, tackles limited microbial metabolite annotation in untargeted metabolomics experiments. Leveraging a curated database of >60,000 microbial monocultures, users can search known and unknown MS/MS spectra and link them to their respective microbial producers via MS/MS fragmentation patterns. Identification of microbe-derived metabolites and relative producers without a priori knowledge will vastly enhance the understanding of microorganisms' role in ecology and human health.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.012
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.010
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0070.004
Science and technology studies0.0010.001
Scholarly communication0.0030.004
Open science0.0020.005
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0120.010

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.016
GPT teacher head0.290
Teacher spread0.274 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreMethods

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations114
Published2024
Admission routes1
Has abstractyes

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