A three-dimensional layout from Metabolic Atlas of the network of genes, metabolites, and reactions associated with metabolism i
A three-dimensional layout from Metabolic Atlas of the network of genes, metabolites, and reactions associated with metabolism in the endoplasmic reticulum. White and blue spheres represent reactions and metabolites, respectively, whereas genes are coloured from yellow to red based on their expression (low to high) in human liver tissue. Genes are connected to their encoded reactions, and reactions are connected to the metabolites they consume or produce. Illustration: metabolicatlas.org
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The next generation of human metabolic modelling

​Researchers at Chalmers University of Technology have developed a human metabolic model, Human1, which enables integrative analysis of human biological data and simulation of metabolite flow through the reaction network. The model can be used to predict metabolic behaviour in cells, which can help researchers identify novel metabolic markers or drug targets for many diseases, such as cancer, type 2 diabetes, and Alzheimer’s disease.

“Human1 will transform the way in which scientists develop and apply models to study human health and disease”, says project leader Jens Nielsen, Professor in Systems and Synthetic Biology, at the Department of Biology and Biological Engineering at Chalmers University of Technology, about the model that was recently published in in Science Signaling.

Metabolism is the network of chemical reactions providing cells with the building blocks and energy necessary to sustain life. Studying the individual components of human metabolism and how they function as part of a connected system is therefore critical to improving health and treating disease. To study such a complex system, computational tools such as genome-scale metabolic models have been developed. 

Human1 − ​highest quality genome-scale model

Human1 is the newest, most advanced, and highest quality genome-scale model for human metabolism. The model consolidates decades of biochemical and modelling research into a high-quality resource with over 13,000 biochemical reactions, 4,100 metabolites, and 3,500 genes comprising human metabolism. 

Unlike previous human models, Human1, was developed entirely in a public online repository that tracks all changes to the model. 

“The primary aim of this framework is to ensure transparency and reproducibility,” explains co-author Jonathan Robinson, Researcher in the Computational Systems Biology Infrastructure at the Department of Biology and Biological Engineering, “and to provide a system through which others in the modelling community can contribute and collaborate in real time.”

In the study, the researchers integrated Human1 with gene expression data from hundreds of different tumour and healthy tissue cell types. The integration revealed metabolic differences of clinical relevance, such as potential drug targets for cancers of the liver and blood. Furthermore, Human1 was demonstrated to predict the effect of gene disruptions with substantially greater accuracy than previous human models.

"An advancement in the area of human metabolic modelling​"

A major limitation for human metabolic models has been the difficulty in simulating realistic reaction rates due to the infeasibility of obtaining the necessary measurements. However, the authors demonstrated that applying an enzyme-limitation framework to Human1 enabled the prediction of realistic growth and metabolite exchange rates without requiring these difficult measurements. 

“This is a considerable advancement in the area of human metabolic modelling,” says Jens Nielsen. 

“The framework now unlocks many powerful approaches that have typically only been feasible for studying microbes and it will enable a wide use of the model for studying metabolic diseases.”

​Metabolic Atlas provides maps for metabolic pathways

In parallel with Human1, the researchers developed Metabolic Atlas, an online resource to explore and visualise the model. The website provides 2D and 3D maps for different cellular compartments and metabolic pathways, and links content to other biochemical databases. 

The project was led by Professor Jens Nielsen with a group of researchers in the Department of Biology and Biological Engineering at Chalmers, in collaboration with the Human Protein Atlas (HPA) and National Bioinformatics Infrastructure Sweden (NBIS). The work was funded by the Knut and Alice Wallenberg Foundation.


 

Read the article in Science Signaling

Science for Life Laboratory 

  • Science for Life Laboratory, SciLifeLab, is a research institution for the advancement of molecular biosciences in Sweden. 
  • SciLifeLab started out in 2010 as a joint effort between four universities: Karolinska Institutet, KTH Royal Institute of Technology, Stockholm University and Uppsala University.
  • The center provides access to a variety of advanced infrastructures in life science for thousands of researchers creating a unique environment for health and environmental research at the highest level.
  • More information Science for Life Laboratory​,​

Metabolic Atlas

  • The Metabolic Atlas is a program run by Prof. Jens Nielsen’s research group at Chalmers University of Technology in collaboration with National Bioinformatics Infrastructure Sweden (NBIS). 

  • The program started in 2010 with the aim to identify all metabolic reactions in the human body, including mapping of active reactions in cells, tissues and organs. 

  • The new version of the Metabolic Atlas provides several different resources:

    (i) an updated genome-scale metabolic model for human cells. This model is based on merging information from several different previous models and is the most comprehensive model of human metabolism to date.

    (ii) a visualisation tool that provides an overview of metabolism in human cells. Through overlay of data from the Human Protein Atlas (HPA) or other sources it is possible to visualise different metabolic functions in different cells, e.g. in cancer cells versus normal cells.

    (iii) an interaction map that visualise how each enzyme is connected with other enzymes through sharing of metabolites.

    (iv) a proteome constrained metabolic model that enables predictive model simulation of human metabolism in different cells and tissues. 

  • Resources from the Metabolic Atlas has resulted in more than 100 research papers on human metabolism and it has resulted in the identification of novel biomarkers and potential drug targets.

  • More information ​Metabolic Atlas

Human Protein Atlas 

  • The Human Protein Atlas (HPA) is a program based at the Science for Life Laboratory (Stockholm) and started in 2003 with the aim to map all of the human proteins in cells, tissues and organs using integration of various omics technologies, including antibody-based imaging, mass spectrometry-based proteomics, transcriptomics and systems biology. 

  • All the data in the knowledge resource is open access to allow scientists both in academia and industry to freely use the data for exploration of the human proteome. 

  • Version 19 consists of six separate parts, each focusing on a particular aspect of analysis of the human proteins: 
    (i) the Tissue Atlas showing the distribution of the proteins across all major tissues and organs in the human body.
    (ii) the Cell Atlas showing the subcellular localisation of proteins in single cells.
    (iii) the Pathology Atlas showing the impact of protein levels for survival of patients with cancer.
    (iv) the Blood Atlas showing the profiles of blood cells and proteins detectable in the blood.
    (v) the Brain Atlas showing the distribution of proteins in human, mouse and pig brain.
    (vi) the Metabolic Atlas showing the presence of metabolic pathways across human tissues. 

  • The Human Protein Atlas program has already contributed to several thousands of publications in the field of human biology and disease and it has been selected by the organisation ELIXIR as a European core resource due to its fundamental importance for a wider life science community.  
  • More information Human Protein Atlas


 

Published: Thu 26 Mar 2020.