Cytometric fingerprints of gut microbiota predict Crohn's disease state
Variations in the gut microbiome have been associated with changes in health state such as Crohn's disease (CD). Most surveys characterize the microbiome through analysis of the 16S rRNA gene. An alternative technology that can be used is flow cytometry. In this report, we reanalyzed a disease cohort that has been characterized by both technologies. Changes in microbial community structure are reflected in both types of data. We demonstrate that cytometric fingerprints can be used as a diagnostic tool in order to classify samples according to CD state. These results highlight the potential of flow cytometry to perform rapid diagnostics of microbiome-associated diseases.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2021 |
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| Erschienen: |
2021 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:15 |
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| Enthalten in: |
The ISME journal - 15(2021), 1 vom: 02. Jan., Seite 354-358 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Rubbens, Peter [VerfasserIn] |
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| Links: |
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| Themen: |
Journal Article |
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| Anmerkungen: |
Date Completed 21.04.2021 Date Revised 02.01.2022 published: Print-Electronic Citation Status MEDLINE |
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| doi: |
10.1038/s41396-020-00762-4 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
NLM314523898 |
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| 100 | 1 | |a Rubbens, Peter |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Cytometric fingerprints of gut microbiota predict Crohn's disease state |
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| 500 | |a Date Revised 02.01.2022 | ||
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| 520 | |a Variations in the gut microbiome have been associated with changes in health state such as Crohn's disease (CD). Most surveys characterize the microbiome through analysis of the 16S rRNA gene. An alternative technology that can be used is flow cytometry. In this report, we reanalyzed a disease cohort that has been characterized by both technologies. Changes in microbial community structure are reflected in both types of data. We demonstrate that cytometric fingerprints can be used as a diagnostic tool in order to classify samples according to CD state. These results highlight the potential of flow cytometry to perform rapid diagnostics of microbiome-associated diseases | ||
| 650 | 4 | |a Journal Article | |
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| 700 | 1 | |a Kerckhof, Frederiek-Maarten |e verfasserin |4 aut | |
| 700 | 1 | |a Boon, Nico |e verfasserin |4 aut | |
| 700 | 1 | |a Waegeman, Willem |e verfasserin |4 aut | |
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