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Treffer: NCMW: A Python Package to Analyze Metabolic Interactions in the Nasal Microbiome.

Title:
NCMW: A Python Package to Analyze Metabolic Interactions in the Nasal Microbiome.
Authors:
Glöckler M; Department of Computer Science, University of Tübingen, Tübingen, Germany., Dräger A; Department of Computer Science, University of Tübingen, Tübingen, Germany.; Computational Systems Biology of Infections and Antimicrobial-Resistant Pathogens, Institute for Bioinformatics and Medical Informatics (IBMI), University of Tübingen, Tübingen, Germany.; German Center for Infection Research (DZIF), Partner Site Tübingen, Tübingen, Germany.; Cluster of Excellence 'Controlling Microbes to Fight Infections', University of Tübingen, Tübingen, Germany., Mostolizadeh R; Department of Computer Science, University of Tübingen, Tübingen, Germany.; Computational Systems Biology of Infections and Antimicrobial-Resistant Pathogens, Institute for Bioinformatics and Medical Informatics (IBMI), University of Tübingen, Tübingen, Germany.; German Center for Infection Research (DZIF), Partner Site Tübingen, Tübingen, Germany.; Cluster of Excellence 'Controlling Microbes to Fight Infections', University of Tübingen, Tübingen, Germany.
Source:
Frontiers in bioinformatics [Front Bioinform] 2022 Feb 25; Vol. 2, pp. 827024. Date of Electronic Publication: 2022 Feb 25 (Print Publication: 2022).
Publication Type:
Journal Article
Language:
English
Journal Info:
Publisher: Frontiers Media S.A Country of Publication: Switzerland NLM ID: 9918227263306676 Publication Model: eCollection Cited Medium: Internet ISSN: 2673-7647 (Electronic) Linking ISSN: 26737647 NLM ISO Abbreviation: Front Bioinform Subsets: PubMed not MEDLINE
Imprint Name(s):
Original Publication: Lausanne : Frontiers Media S.A., [2021]-
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Contributed Indexing:
Keywords: computational biology; constraint-based modeling; genome-scale modeling; microbial communities; nasal microbiome
Entry Date(s):
Date Created: 20221028 Latest Revision: 20221029
Update Code:
20250114
PubMed Central ID:
PMC9580955
DOI:
10.3389/fbinf.2022.827024
PMID:
36304309
Database:
MEDLINE

Weitere Informationen

The human upper respiratory tract is the reservoir of a diverse community of commensals and potential pathogens (pathobionts), including Streptococcus pneumoniae (pneumococcus), Haemophilus influenzae , Moraxella catarrhalis , and Staphylococcus aureus , which occasionally turn into pathogens causing infectious diseases, while the contribution of many nasal microorganisms to human health remains undiscovered. To better understand the composition of the nasal microbiome community, we create a workflow of the community model, which mimics the human nasal environment. To address this challenge, constraint-based reconstruction of biochemically accurate genome-scale metabolic models (GEMs) networks of microorganisms is mandatory. Our workflow applies constraint-based modeling (CBM), simulates the metabolism between species in a given microbiome, and facilitates generating novel hypotheses on microbial interactions. Utilizing this workflow, we hope to gain a better understanding of interactions from the metabolic modeling perspective. This article presents nasal community modeling workflow (NCMW)-a python package based on GEMs of species as a starting point for understanding the composition of the nasal microbiome community. The package is constructed as a step-by-step mathematical framework for metabolic modeling and analysis of the nasal microbial community. Using constraint-based models reduces the need for culturing species in vitro , a process that is not convenient in the environment of human noses. Availability: NCMW is freely available on the Python Package Index (PIP) via pip install NCMW. The source code, documentation, and usage examples (Jupyter Notebook and example files) are available at https://github.com/manuelgloeckler/ncmw.
(Copyright © 2022 Glöckler, Dräger and Mostolizadeh.)

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.