English
 
Help Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
  Metabolic model predictions enable targeted microbiome manipulation through precision prebiotics

Marinos, G., Hamerich, I. K., Debray, R., Obeng, N., Petersen, C., Taubenheim, J., et al. (2024). Metabolic model predictions enable targeted microbiome manipulation through precision prebiotics. Microbiology Spectrum, 12: e01144-23. doi:10.1128/spectrum.01144-23.

Item is

Files

show Files
hide Files
:
marinos-et-al-2024-metabolic-model-predictions-enable-targeted-microbiome-manipulation-through-precision-prebiotics.pdf (Publisher version), 2MB
 
File Permalink:
-
Name:
marinos-et-al-2024-metabolic-model-predictions-enable-targeted-microbiome-manipulation-through-precision-prebiotics.pdf
Description:
-
OA-Status:
Visibility:
Private (embargoed till 2024-07-17)
MIME-Type / Checksum:
application/pdf
Technical Metadata:
Copyright Date:
-
Copyright Info:
-
License:
-

Locators

show

Creators

show
hide
 Creators:
Marinos, Georgios, Author
Hamerich, Inga K., Author
Debray, Reena, Author
Obeng, Nancy, Author
Petersen, Carola, Author
Taubenheim, Jan, Author
Zimmermann, Johannes, Author
Blackburn, Dana, Author
Samuel, Buck S., Author
Dierking, Katja, Author
Franke, Andre, Author
Laudes, Matthias, Author
Waschina, Silvio, Author
Schulenburg, Hinrich1, Author                 
Kaleta, Christoph, Author
Affiliations:
1Max Planck Fellow Group Antibiotic Resistance Evolution, Max Planck Institute for Evolutionary Biology, Max Planck Society, ou_2600692              

Content

show
hide
Free keywords: -
 Abstract: While numerous health-beneficial interactions between host and microbiota have been identified, there is still a lack of targeted approaches for modulating these interactions. Thus, we here identify precision prebiotics that specifically modulate the abundance of a microbiome member species of interest. In the first step, we show that defining precision prebiotics by compounds that are only taken up by the target species but no other species in a community is usually not possible due to overlapping metabolic niches. Subsequently, we use metabolic modeling to identify precision prebiotics for a two-member Caenorhabditis elegans microbiome community comprising the immune-protective target species Pseudomonas lurida MYb11 and the persistent colonizer Ochrobactrum vermis MYb71. We experimentally confirm four of the predicted precision prebiotics, L-serine, L-threonine, D-mannitol, and γ-aminobutyric acid, to specifically increase the abundance of MYb11. L-serine was further assessed in vivo, leading to an increase in MYb11 abundance also in the worm host. Overall, our findings demonstrate that metabolic modeling is an effective tool for the design of precision prebiotics as an important cornerstone for future microbiome-targeted therapies.

Details

show
hide
Language(s): eng - English
 Dates: 2023-03-172023-12-132023-01-172024-02
 Publication Status: Issued
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1128/spectrum.01144-23
 Degree: -

Event

show

Legal Case

show

Project information

show

Source 1

show
hide
Title: Microbiology Spectrum
  Abbreviation : Microbiol. Spectr.
Source Genre: Journal
 Creator(s):
Affiliations:
Publ. Info: American Society for Microbiology
Pages: - Volume / Issue: 12 Sequence Number: e01144-23 Start / End Page: - Identifier: ISSN: 2165-0497
CoNE: https://pure.mpg.de/cone/journals/resource/2165-0497