An insight towards food-related microbial sets through metabolic modelling and functional analysis
Doctoral thesis, 2020
The systems biology tools allow analysing various size microbial communities under the different functional scope. For example, the homology prediction tools can give detailed functional insights when working with metagenomics data. The whole-cell metabolic processes can be summarised in genome-scale metabolic models (GEMs), which enable to predict the metabolic capabilities and allow for the integration of omics data.
The work shown in this thesis includes i) in silico analysis of food-related microbes; ii) the development of GEMs and RAVEN. With a focus on bile acid metabolism, hundreds of human gut microbes were annotated based on metagenomics data, thereby suggesting the differences in the potential for bile acid processing between healthy and diseased subjects. These findings may be exploitable once aiming to restore the bile acid metabolism for the patients having inflammatory bowel disease. Also, the metabolism of yeast K. marxianus was characterised in genome-scale. Two K. marxianus strains from kefir grains were isolated, sequenced, assembled, and functionally annotated. They were compared with the other ten strains, providing the core and dispensable physiological features for K. marxianus. Furthermore, the first GEM for K. marxianus, namely iSM996, was reconstructed. It was integrated with transcriptomics data to predict its metabolic capabilities in rich medium and high-temperature conditions. The results might be useful to optimise strain-specific medium for high-temperature applications. The final paper comprises the efforts to improve the usability for RAVEN, a toolbox for GEM reconstruction and analysis. Altogether the outcomes of this thesis suggest the potential applications for medicine and industrial biotechnology, which may be facilitated by the newly upgraded RAVEN toolbox.
genome-scale metabolic model
Chalmers, Biology and Biological Engineering, Systems and Synthetic Biology
Metagenomic analysis of bile salt biotransformation in the human gut microbiome
BMC Genomics,; Vol. 20(2019)
Marcišauskas, S., Ji, B., Nielsen, J. The functional diversity between Kluyveromyces marxianus strains
Reconstruction and analysis of a Kluyveromyces marxianus genome-scale metabolic model
BMC Bioinformatics,; Vol. 20(2019)
RAVEN 2.0: A versatile toolbox for metabolic network reconstruction and a case study on Streptomyces coelicolor
PLoS Computational Biology,; Vol. 14(2018)p. e1006541-
This thesis includes several bioinformatics analyses for food-related microbial species and presents the newly upgraded toolbox for metabolic modelling. The systems biology tools allow annotating microbial communities of various sizes. While metagenomics data is a crucial source for community characterisation, the genome sequencing data is the primary source during the reconstruction of a genome-scale metabolic model (GEM), a tool allowing to predict the cell behaviour in a given condition.
Firstly, hundreds of human gut microbes were annotated with a focus on bile acid metabolism and were then used to compare bile acid biotransformation potential between healthy and diseased patient groups. These findings may be exploitable once aiming to restore the bile acid metabolism for the patients having inflammatory bowel disease.
Secondly, a non-conventional yeast Kluyveromyces marxianus was isolated from kefir grains and compared with its other strains, providing the core and accessory physiological features for this species. The first K. marxianus GEM was also reconstructed and integrated with transcriptomics data to predict its metabolic capabilities in rich growth medium and high-temperature (45°C) conditions. The results might be useful to optimise strain-specific medium for high-temperature industrial applications.
Finally, this thesis presents the efforts to improve the usability for RAVEN, a toolbox for GEM reconstruction and analysis. Overall, the results of this thesis hint the potential applications for healthcare and industrial biotechnology, which may be facilitated by the newly upgraded RAVEN toolbox.
SysMilk. Designer microbial communities for fermented milk products: A Systems Biology Approach (ERASysAPP - SysMilk)
Region Västra Götaland, 2014-07-01 -- 2018-06-30.
Metagenomics in Cardiometabolic Diseases (METACARDIS)
European Commission (EC), 2012-11-01 -- 2017-10-31.
Systematic Rebuilding of Actinomycetes for Natural Product Formation (ERASysAPP - SYSTERACT)
Region Västra Götaland, 2015-09-01 -- 2018-12-31.
Facility for Computational Systems Biology
C3SE (Chalmers Centre for Computational Science and Engineering)
Bioinformatics (Computational Biology)
Gastroenterology and Hepatology
Bioinformatics and Systems Biology
Doktorsavhandlingar vid Chalmers tekniska högskola. Ny serie: 4743
Chalmers University of Technology
Online using Zoom
Opponent: Associate Prof. Vassily Hatzimanikatis, École Polytechnique Fédérale de Lausanne, Switzerland