An insight towards food-related microbial sets through metabolic modelling and functional analysis
Doktorsavhandling, 2020

The dietary food digestion depends on the human gastrointestinal tract, where host cells and gut microbes mutually interact. This interplay may also mediate host metabolism, as shown by microbial-derived secondary bile acids, needed for receptor signalling. Microbes are also crucial in the production of fermented foods, such as wine and dairy. Kefir is fermented milk processed by the symbiotic community of bacteria and yeasts. One such species is a yeast Kluyveromyces marxianus. Its thermotolerance is a desired trait in biotechnology since it may reduce the cooling demands during cultivation.
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.

RAVEN

gut

systems biology

comparative genomics

Kluyveromyces marxianus

bile acids

genome-scale metabolic model

next-generation sequencing

transcriptomics

thermotolerance

Online using Zoom
Opponent: Associate Prof. Vassily Hatzimanikatis, École Polytechnique Fédérale de Lausanne, Switzerland

Författare

Simonas Marcisauskas

Chalmers, Biologi och bioteknik, Systembiologi

Metagenomic analysis of bile salt biotransformation in the human gut microbiome

BMC Genomics,;Vol. 20(2019)

Artikel i vetenskaplig tidskrift

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)

Artikel i vetenskaplig tidskrift

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-

Artikel i vetenskaplig tidskrift

Nature contains numerous examples of how living forms adapt to their niche environments. One may assume that the organisms exhaustively compete for the same limited food resources, but the species diversity in biochemical level suggests that they might also complement each other and develop somehow mutual interactions. Such interactions may sometimes become essential and even form the basis of the local communities like in soil, food, seawater or the human gut. Although much work has been done to identify the community-driven adaptation mechanisms, there are still many communities worthwhile to be annotated. A better understanding of these communities and their member species may highlight new candidates for applications in biofuel or biopharmaceuticals production, thereby contributing to a sustainable future.
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)

Västra Götalandsregionen (RUN 612-0651-14), 2014-07-01 -- 2018-06-30.

Metagenomics in Cardiometabolic Diseases (METACARDIS)

Europeiska kommissionen (EU) (EC/FP7/305312), 2012-11-01 -- 2017-10-31.

Systematic Rebuilding of Actinomycetes for Natural Product Formation (ERASysAPP - SYSTERACT)

Västra Götalandsregionen (RUN 612-0436-15), 2015-09-01 -- 2018-12-31.

Infrastruktur

Beräkningsinfrastruktur för systembiologi

C3SE (Chalmers Centre for Computational Science and Engineering)

Ämneskategorier

Bioprocessteknik

Bioinformatik (beräkningsbiologi)

Gastroenterologi

Bioinformatik och systembiologi

Genetik

ISBN

978-91-7905-276-8

Doktorsavhandlingar vid Chalmers tekniska högskola. Ny serie: 4743

Utgivare

Chalmers

Online using Zoom

Online

Opponent: Associate Prof. Vassily Hatzimanikatis, École Polytechnique Fédérale de Lausanne, Switzerland

Mer information

Senast uppdaterat

2020-08-13