Microbiota-based markers predictive of development of Clostridioides difficile infection
Antibiotic-induced modulation of the intestinal microbiota can lead to Clostridioides difficile infection (CDI), which is associated with considerable morbidity, mortality, and healthcare-costs globally. Therefore, identification of markers predictive of CDI could substantially contribute to guiding therapy and decreasing the infection burden. Here, we analyze the intestinal microbiota of hospitalized patients at increased CDI risk in a prospective, 90-day cohort-study before and after antibiotic treatment and at diarrhea onset. We show that patients developing CDI already exhibit significantly lower diversity before antibiotic treatment and a distinct microbiota enriched in Enterococcus and depleted of Ruminococcus, Blautia, Prevotella and Bifidobacterium compared to non-CDI patients. We find that antibiotic treatment-induced dysbiosis is class-specific with beta-lactams further increasing enterococcal abundance. Our findings, validated in an independent prospective patient cohort developing CDI, can be exploited to enrich for high-risk patients in prospective clinical trials, and to develop predictive microbiota-based diagnostics for management of patients at risk for CDI.
| Medienart: |
E-Artikel |
|---|
| Erscheinungsjahr: |
2021 |
|---|---|
| Erschienen: |
2021 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:12 |
|---|---|
| Enthalten in: |
Nature communications - 12(2021), 1 vom: 14. Apr., Seite 2241 |
| Sprache: |
Englisch |
|---|
| Beteiligte Personen: |
Berkell, Matilda [VerfasserIn] |
|---|
| Links: |
|---|
| Themen: |
Anti-Bacterial Agents |
|---|
| Anmerkungen: |
Date Completed 11.05.2021 Date Revised 01.11.2023 published: Electronic Citation Status MEDLINE |
|---|
| doi: |
10.1038/s41467-021-22302-0 |
|---|
| funding: |
|
|---|---|
| Förderinstitution / Projekttitel: |
|
| PPN (Katalog-ID): |
NLM324088809 |
|---|
| LEADER | 01000naa a22002652 4500 | ||
|---|---|---|---|
| 001 | NLM324088809 | ||
| 003 | DE-627 | ||
| 005 | 20231225185556.0 | ||
| 007 | cr uuu---uuuuu | ||
| 008 | 231225s2021 xx |||||o 00| ||eng c | ||
| 024 | 7 | |a 10.1038/s41467-021-22302-0 |2 doi | |
| 028 | 5 | 2 | |a pubmed24n1080.xml |
| 035 | |a (DE-627)NLM324088809 | ||
| 035 | |a (NLM)33854066 | ||
| 040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
| 041 | |a eng | ||
| 100 | 1 | |a Berkell, Matilda |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Microbiota-based markers predictive of development of Clostridioides difficile infection |
| 264 | 1 | |c 2021 | |
| 336 | |a Text |b txt |2 rdacontent | ||
| 337 | |a ƒaComputermedien |b c |2 rdamedia | ||
| 338 | |a ƒa Online-Ressource |b cr |2 rdacarrier | ||
| 500 | |a Date Completed 11.05.2021 | ||
| 500 | |a Date Revised 01.11.2023 | ||
| 500 | |a published: Electronic | ||
| 500 | |a Citation Status MEDLINE | ||
| 520 | |a Antibiotic-induced modulation of the intestinal microbiota can lead to Clostridioides difficile infection (CDI), which is associated with considerable morbidity, mortality, and healthcare-costs globally. Therefore, identification of markers predictive of CDI could substantially contribute to guiding therapy and decreasing the infection burden. Here, we analyze the intestinal microbiota of hospitalized patients at increased CDI risk in a prospective, 90-day cohort-study before and after antibiotic treatment and at diarrhea onset. We show that patients developing CDI already exhibit significantly lower diversity before antibiotic treatment and a distinct microbiota enriched in Enterococcus and depleted of Ruminococcus, Blautia, Prevotella and Bifidobacterium compared to non-CDI patients. We find that antibiotic treatment-induced dysbiosis is class-specific with beta-lactams further increasing enterococcal abundance. Our findings, validated in an independent prospective patient cohort developing CDI, can be exploited to enrich for high-risk patients in prospective clinical trials, and to develop predictive microbiota-based diagnostics for management of patients at risk for CDI | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Multicenter Study | |
| 650 | 4 | |a Observational Study | |
| 650 | 4 | |a Research Support, Non-U.S. Gov't | |
| 650 | 7 | |a Anti-Bacterial Agents |2 NLM | |
| 650 | 7 | |a Biomarkers |2 NLM | |
| 700 | 1 | |a Mysara, Mohamed |e verfasserin |4 aut | |
| 700 | 1 | |a Xavier, Basil Britto |e verfasserin |4 aut | |
| 700 | 1 | |a van Werkhoven, Cornelis H |e verfasserin |4 aut | |
| 700 | 1 | |a Monsieurs, Pieter |e verfasserin |4 aut | |
| 700 | 1 | |a Lammens, Christine |e verfasserin |4 aut | |
| 700 | 1 | |a Ducher, Annie |e verfasserin |4 aut | |
| 700 | 1 | |a Vehreschild, Maria J G T |e verfasserin |4 aut | |
| 700 | 1 | |a Goossens, Herman |e verfasserin |4 aut | |
| 700 | 1 | |a de Gunzburg, Jean |e verfasserin |4 aut | |
| 700 | 1 | |a Bonten, Marc J M |e verfasserin |4 aut | |
| 700 | 1 | |a Malhotra-Kumar, Surbhi |e verfasserin |4 aut | |
| 700 | 0 | |a ANTICIPATE study group |e verfasserin |4 aut | |
| 700 | 1 | |a Engbers, Annemarie |e investigator |4 oth | |
| 700 | 1 | |a de Regt, Marieke |e investigator |4 oth | |
| 700 | 1 | |a Biehl, Lena M |e investigator |4 oth | |
| 700 | 1 | |a Cornely, Oliver A |e investigator |4 oth | |
| 700 | 1 | |a Jazmati, Nathalie |e investigator |4 oth | |
| 700 | 1 | |a Bouverne, Marie-Noelle |e investigator |4 oth | |
| 700 | 1 | |a Sablier-Gallis, Frederique |e investigator |4 oth | |
| 700 | 1 | |a Mentré, France |e investigator |4 oth | |
| 700 | 1 | |a Merle, Uta |e investigator |4 oth | |
| 700 | 1 | |a Stallmach, Andreas |e investigator |4 oth | |
| 700 | 1 | |a Rupp, Jan |e investigator |4 oth | |
| 700 | 1 | |a Bogner, Johannes |e investigator |4 oth | |
| 700 | 1 | |a Lübbert, Christoph |e investigator |4 oth | |
| 700 | 1 | |a Silling, Gerda |e investigator |4 oth | |
| 700 | 1 | |a Witzke, Oliver |e investigator |4 oth | |
| 700 | 1 | |a Gikas, Achilleas |e investigator |4 oth | |
| 700 | 1 | |a Maraki, Sofia |e investigator |4 oth | |
| 700 | 1 | |a Daikos, George |e investigator |4 oth | |
| 700 | 1 | |a Tsiodras, Sotirios |e investigator |4 oth | |
| 700 | 1 | |a Skoutelis, Athanasios |e investigator |4 oth | |
| 700 | 1 | |a Sambatakou, Helen |e investigator |4 oth | |
| 700 | 1 | |a Pujol, Miquel |e investigator |4 oth | |
| 700 | 1 | |a Dominguez-Luzon, M Angeles |e investigator |4 oth | |
| 700 | 1 | |a Aguado, Jose M |e investigator |4 oth | |
| 700 | 1 | |a Bouza, Emilio |e investigator |4 oth | |
| 700 | 1 | |a Cobo, Javier |e investigator |4 oth | |
| 700 | 1 | |a Rodríguez-Baño, Jesús |e investigator |4 oth | |
| 700 | 1 | |a Almirante, Benito |e investigator |4 oth | |
| 700 | 1 | |a de la Torre Cisneros, Julian |e investigator |4 oth | |
| 700 | 1 | |a Florescu, Simin A |e investigator |4 oth | |
| 700 | 1 | |a Nica, Maria |e investigator |4 oth | |
| 700 | 1 | |a Vata, Andrei |e investigator |4 oth | |
| 700 | 1 | |a Hristea, Adriana |e investigator |4 oth | |
| 700 | 1 | |a Lupse, Mihaela |e investigator |4 oth | |
| 700 | 1 | |a Herghea, Delia |e investigator |4 oth | |
| 700 | 1 | |a Postil, Deborah |e investigator |4 oth | |
| 700 | 1 | |a Barraud, Olivier |e investigator |4 oth | |
| 700 | 1 | |a Molina, Jean-Michel |e investigator |4 oth | |
| 700 | 1 | |a De Lastours, Victoire |e investigator |4 oth | |
| 700 | 1 | |a Guimard, Thomas |e investigator |4 oth | |
| 700 | 1 | |a Talarmin, Jean-Philippe |e investigator |4 oth | |
| 700 | 1 | |a Duval, Xavier |e investigator |4 oth | |
| 700 | 1 | |a Bernard, Louis |e investigator |4 oth | |
| 700 | 1 | |a Launay, Odile |e investigator |4 oth | |
| 773 | 0 | 8 | |i Enthalten in |t Nature communications |d 2010 |g 12(2021), 1 vom: 14. Apr., Seite 2241 |w (DE-627)NLM199274525 |x 2041-1723 |7 nnns |
| 773 | 1 | 8 | |g volume:12 |g year:2021 |g number:1 |g day:14 |g month:04 |g pages:2241 |
| 856 | 4 | 0 | |u http://dx.doi.org/10.1038/s41467-021-22302-0 |3 Volltext |
| 912 | |a GBV_USEFLAG_A | ||
| 912 | |a GBV_NLM | ||
| 951 | |a AR | ||
| 952 | |d 12 |j 2021 |e 1 |b 14 |c 04 |h 2241 | ||