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Network Analysis Based on Unique Spectral Features Enables an Efficient Selection of Genomically Diverse Operational Isolation Units

Culturomics-based bacterial diversity studies benefit from the implementation of MALDI-TOF MS to remove genomically redundant isolates from isolate collections. We previously introduced SPeDE, a novel tool designed to dereplicate spectral datasets at an infraspecific level into operational isolation...

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Detalles Bibliográficos
Autores principales: Dumolin, Charles, Peeters, Charlotte, De Canck, Evelien, Boon, Nico, Vandamme, Peter
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7922279/
https://www.ncbi.nlm.nih.gov/pubmed/33671218
http://dx.doi.org/10.3390/microorganisms9020416
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author Dumolin, Charles
Peeters, Charlotte
De Canck, Evelien
Boon, Nico
Vandamme, Peter
author_facet Dumolin, Charles
Peeters, Charlotte
De Canck, Evelien
Boon, Nico
Vandamme, Peter
author_sort Dumolin, Charles
collection PubMed
description Culturomics-based bacterial diversity studies benefit from the implementation of MALDI-TOF MS to remove genomically redundant isolates from isolate collections. We previously introduced SPeDE, a novel tool designed to dereplicate spectral datasets at an infraspecific level into operational isolation units (OIUs) based on unique spectral features. However, biological and technical variation may result in methodology-induced differences in MALDI-TOF mass spectra and hence provoke the detection of genomically redundant OIUs. In the present study, we used three datasets to analyze to which extent hierarchical clustering and network analysis allowed to eliminate redundant OIUs obtained through biological and technical sample variation and to describe the diversity within a set of spectra obtained from 134 unknown soil isolates. Overall, network analysis based on unique spectral features in MALDI-TOF mass spectra enabled a superior selection of genomically diverse OIUs compared to hierarchical clustering analysis and provided a better understanding of the inter-OIU relationships.
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spelling pubmed-79222792021-03-03 Network Analysis Based on Unique Spectral Features Enables an Efficient Selection of Genomically Diverse Operational Isolation Units Dumolin, Charles Peeters, Charlotte De Canck, Evelien Boon, Nico Vandamme, Peter Microorganisms Article Culturomics-based bacterial diversity studies benefit from the implementation of MALDI-TOF MS to remove genomically redundant isolates from isolate collections. We previously introduced SPeDE, a novel tool designed to dereplicate spectral datasets at an infraspecific level into operational isolation units (OIUs) based on unique spectral features. However, biological and technical variation may result in methodology-induced differences in MALDI-TOF mass spectra and hence provoke the detection of genomically redundant OIUs. In the present study, we used three datasets to analyze to which extent hierarchical clustering and network analysis allowed to eliminate redundant OIUs obtained through biological and technical sample variation and to describe the diversity within a set of spectra obtained from 134 unknown soil isolates. Overall, network analysis based on unique spectral features in MALDI-TOF mass spectra enabled a superior selection of genomically diverse OIUs compared to hierarchical clustering analysis and provided a better understanding of the inter-OIU relationships. MDPI 2021-02-17 /pmc/articles/PMC7922279/ /pubmed/33671218 http://dx.doi.org/10.3390/microorganisms9020416 Text en © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Dumolin, Charles
Peeters, Charlotte
De Canck, Evelien
Boon, Nico
Vandamme, Peter
Network Analysis Based on Unique Spectral Features Enables an Efficient Selection of Genomically Diverse Operational Isolation Units
title Network Analysis Based on Unique Spectral Features Enables an Efficient Selection of Genomically Diverse Operational Isolation Units
title_full Network Analysis Based on Unique Spectral Features Enables an Efficient Selection of Genomically Diverse Operational Isolation Units
title_fullStr Network Analysis Based on Unique Spectral Features Enables an Efficient Selection of Genomically Diverse Operational Isolation Units
title_full_unstemmed Network Analysis Based on Unique Spectral Features Enables an Efficient Selection of Genomically Diverse Operational Isolation Units
title_short Network Analysis Based on Unique Spectral Features Enables an Efficient Selection of Genomically Diverse Operational Isolation Units
title_sort network analysis based on unique spectral features enables an efficient selection of genomically diverse operational isolation units
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7922279/
https://www.ncbi.nlm.nih.gov/pubmed/33671218
http://dx.doi.org/10.3390/microorganisms9020416
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