Recon 2: Virtual Reconstruction of Human Metabolism

Author: University of California - San Diego
Published: 3 Mar 2013 - Updated: 3 Aug 2026
Publication Details: Peer-Reviewed | Informative

Table of Contents:
Synopsis - Definition - Overview - FAQs - Insights, Updates - Related Content

Synopsis

This research presents Recon 2, a peer-reviewed virtual reconstruction of the human metabolic network published in the journal Nature Biotechnology and built by an international consortium of university researchers led by Ines Thiele of the University of Iceland, working from earlier pioneering efforts at the University of California, San Diego. The model maps more than 7,400 biochemical reactions, more than doubling the roughly 3,300 reactions captured by the 2007 Recon 1 predecessor, and gives biomedical researchers a precise way to see where metabolic pathways go off track to create disease. It matters because metabolic imbalances underlie conditions such as cancer, diabetes and psychiatric and neurodegenerative disorders, meaning the tool holds practical value for patients, clinicians and people living with inherited metabolic diseases, including seniors and those with disabilities who may benefit from more personalized diagnosis and treatment. The findings show that Recon 2 has already predicted metabolic alterations now used to diagnose certain inherited conditions, and its authority rests on peer review, consensus standards set through collaborative "jamboree" meetings, and free public availability that lets researchers test how drugs affect specific pathways.*

At a Glance

• 1 - Recon 2 is freely available to researchers worldwide.
• 2 - The model accounts for almost 1,800 of an estimated 20,000 protein-coding genes.
• 3 - Lead researcher Ines Thiele earned her Ph.D. under Bernhard Palsson and worked on the original Recon 1 team.
• 4 - Palsson compared Recon 2 to Google mapping, letting researchers zoom into single reactions or out to whole pathway patterns.

Topic Definition

Human Metabolic Reconstruction

Human Metabolic Reconstruction is the process of assembling a comprehensive, computer-based model that maps the biochemical reactions, genes, enzymes and metabolites that make up human metabolism, the set of physical and chemical processes that convert food into energy and build the molecules the body needs. These reconstructions gather data from published literature and existing metabolic models into a single, navigable network that researchers can query, allowing them to trace how specific pathways function normally and how they break down to cause disease. By representing metabolism at multiple scales, from individual reactions up to whole systems, a reconstruction such as Recon 2 serves as a reference framework for virtual experiments, disease research and the development of personalized diagnosis and treatment.

Overview

Building on earlier pioneering work by researchers at the University of California, San Diego, an international consortium of university researchers has produced the most comprehensive virtual reconstruction of human metabolism to date. Scientists could use the model, known as Recon 2, to identify causes of and new treatments for diseases like cancer, diabetes and even psychiatric and neurodegenerative disorders. Each person's metabolism, which represents the conversion of food sources into energy and the assembly of molecules, is determined by genetics, environment and nutrition.

What is metabolism? Metabolism refers to all the physical and chemical processes in the body that convert or use energy, such as:

• Breathing
• Circulating blood
• Contracting muscles
• Digesting food and nutrients
• Controlling body temperature
• Functioning of the brain and nerves
• Eliminating waste through urine and feces

The researchers presented Recon 2 in a paper published online March 3 in the journal Nature Biotechnology.

Importance of Metabolic Imbalances

Doctors have long recognized the importance of metabolic imbalances as an underlying cause of disease, but scientists have been ramping up their research on the connection as a result of compelling evidence enabled by the Human Genome Project and advances in systems biology, which leverages the power of high-powered computing to build vast interactive databases of biological information.

"Recon 2 allows biomedical researchers to study the human metabolic network with more precision than was ever previously possible. This is essential to understanding where and how specific metabolic pathways go off track to create disease," said Bernhard Palsson, Galletti Professor of Bioengineering at UC San Diego Jacobs School of Engineering.

"It's like having the coordinates of all the cars in town, but no street map. Without this tool, we don't know why people are moving the way they are," said Palsson.

He likened Recon 2 to Google mapping for its ability to merge complex details into a single, interactive map. For example, researchers looking at how metabolism sets the stage for cancerous tumor growth could zoom in on the "map" for finely detailed images of individual metabolic reactions or zoom out to look at patterns and relationships among pathways or different sectors of metabolism. This is not unlike how you can get a street view of a single house or zoom out to see how the house fits into the whole neighborhood, city, state, country and globe. And just as Google maps brings together a broad set of data - such as images, addresses, streets and traffic flow - into an easily navigated tool, Recon 2 pulls together a vast compendium of data from published literature and existing models of metabolic processes.

As a multi-scale representation of the human metabolic network, Recon 2 provides essential context for data being reviewed by researchers. Palsson and other scientists in the field have already successfully demonstrated the utility of such models in simple organisms such as yeast and E.coli. As a result, they have been able to engineer these organisms in the lab to improve the efficiency of ethanol production and predict drug resistance in bacteria.

Targeted Drug Delivery

One of the most promising applications for the network reconstruction is the ability to identify specific gene expressions and their metabolic pathways for targeted drug delivery. Large gene expression databases are available for human cells that have been treated with molecules extracted from existing drugs as well as drugs that are in development. Recon 2 allows researchers to use this existing gene expression data and knowledge of the entire metabolic network to figure how certain drugs would affect specific metabolic pathways found to create the conditions for cancerous cell growth, for example. They could then conduct virtual experiments to see whether the drug can fix the metabolic imbalance causing the disease.

Recon 1

Palsson's Systems Biology Research Group at UC San Diego built the first virtual reconstruction of the human metabolism network, known as Recon 1, in 2007 with a six-person team. It featured more than 3,300 known biochemical reactions documented in over 50 years of metabolic research. Recon 2, which contains more than 7,400 reactions, was built by bringing together researchers from dozens of institutions around the globe in a series of "jamboree" meetings to refine and consolidate the data used in the reconstruction. Palsson said this jamboree approach helped the group establish common standards to build a consensus reconstruction, simplify its usability for biomedical researchers, and increase its transparency.

Recon 2

Recon 2 is already proving its utility, according to Ines Thiele, a professor at the University of Iceland and UC San Diego alumna, who led the Recon 2 effort. Thiele earned her Ph.D. in bioinformatics as a student of Palsson's and was part of the original Recon 1 team. Several other UC San Diego alumni, and former Palsson students, participated in the consortium from their new institutions, including Neema Jamshidi (Ph.D., 2008, M.D., 2009), who is now interning at UCLA; Jason Papin (Ph.D., 2004), a professor at the University of Virginia; and Nathan Price (Ph.D., 2005), who is a professor at the Institute for Systems Biology in Seattle, Wash.

Thiele said Recon 2 has successfully predicted alterations in metabolism that are currently used to diagnose certain inherited metabolic diseases:

"The use of this foundational resource will undoubtedly lead to a myriad of exciting predictions that will accelerate the translation of basic experimental results into clinical applications," said Thiele. "Ultimately, I envision it being used to personalize diagnosis and treatment to meet the needs of individual patients. In the future, this capability could enable doctors to develop virtual models of their patients' individual metabolic networks and identify the most efficacious treatment for various diseases including diabetes, cancer and neurodegenerative diseases."

As much as Recon 2 marks a significant improvement over Recon 1, there is still much work to be done, according to the research team. Thiele said Recon 2 accounts for almost 1,800 genes of an estimated 20,000 protein-coding genes in the human genome. "Clearly, further community effort will be required to capture chemical interactions with and between the rest of the genome," she said.

Recon 2 will facilitate many future biomedical studies and is freely available.

Researchers

The international consortium includes researchers from the following institutions: University of Vienna, Austria; Charite- Universitatsmedizin Berlin, Germany; Jacobs University Bremen, Germany; Center for Systems Biology, University of Iceland; Okinawa Institute Science and Technology, Japan; Luxembourg Center for Systems Biomedicine; University of Amsterdam, the Netherlands; Netherlands Bioinformatics Center, the Netherlands; Vrije Universiteit, Amsterdam, the Netherlands; Netherlands Consortium for Systems Biology; Institute of Cell Biophysics, Moscow region, Pushchino, Russia; Chalmers University of Technology, Sweden; University of Manchester, United Kingdom; Manchester Institute of Biotechnology, UK; Central Manchester University Hospitals NHS Foundation Trust, Manchester Academic Health Sciences Center, UK; European Bioinformatics Institute, UK; Babraham Institute, Cambridge, UK; University of Warwick, UK; University of Edinburgh, UK; University of Sheffield, UK; University of California, San Diego; University of Virginia; Virginia Tech; Center for Advanced Discovery and Experimental Therapeutics (CADET), University of North Texas; Genome Designs, Inc., Walnut Creek, Calif.; California Institute of Technology; and Institute for Systems Biology, Seattle, Wash.

Related Information

• Connecting Omics: Molecular Map of The Human Body: Molecular map of the human body and its complex physiological processes based on analysis of molecules in blood, urine and saliva samples.
• Google Maps for Human Body at Cellular Level: Using Google algorithms to zoom in and out from the whole joint down to cellular level as you would with Google Maps.
• How Emotions are Mapped in the Human Body: Researchers find most common emotions trigger strong bodily sensations and the bodily maps of these sensations were topographically different for different emotions.
• Immune System Connections Map Reveals Therapeutic Opportunities: Researchers create a connectivity map of the human immune system showing how immune cells communicate with each other and ways to modulate these pathways in disease.

Frequently Asked Questions

NOTE: Researched FAQs by Disabled World (DW)

Who can access Recon 2 and is there a cost to use it

Recon 2 is freely available to biomedical researchers, so there is no cost to access and use the model in metabolic studies.

What is the difference between Recon 1 and Recon 2

Recon 1 was built in 2007 with about 3,300 reactions, while Recon 2 expands this to more than 7,400 reactions compiled by an international consortium.

What is systems biology

Systems biology is a field that uses high powered computing to build large interactive databases of biological information and study how components interact as a whole.

How does Recon 2 relate to the Human Genome Project

Evidence enabled by the Human Genome Project encouraged researchers to study links between metabolic imbalance and disease, which supported the creation of models like Recon 2.

Can Recon 2 be used to study conditions other than cancer and diabetes

Yes, researchers expect it to help study inherited metabolic diseases and neurodegenerative and psychiatric disorders in addition to cancer and diabetes.

What does targeted drug delivery mean in this context

It means identifying specific gene expressions and metabolic pathways so researchers can predict how a drug will affect the pathways involved in a disease.

Why is a metabolic map compared to Google mapping

The comparison reflects how the model merges complex data into one interactive tool that users can zoom into for detail or out for broad patterns.

Insights, Analysis, and Developments

Editorial Note: What makes Recon 2 notable is not only its scale but the collaborative model behind it, with researchers drawn from dozens of institutions across Austria, Germany, Iceland, Japan, Luxembourg, the Netherlands, Russia, Sweden, the United Kingdom and the United States pooling decades of published metabolic research into one consensus resource. For clinicians and patients, the long-term promise lies in personalization, since the same framework that predicts drug resistance in bacteria and improves ethanol yields in yeast could one day let doctors build a virtual model of an individual patient's metabolism and select the treatment most likely to work. The team is candid that much remains unfinished, with the bulk of the human genome's chemical interactions still to be captured, so Recon 2 is best understood as a living foundation that further community effort will continue to extend rather than a finished endpoint.*

Attribution/Source(s): This peer reviewed publication was selected for publishing by the editors of Disabled World (DW) due to its relevance to the disability community. Originally authored by University of California - San Diego and published on 3 Mar 2013, this content may have been edited for style, clarity, or brevity.

* Editorial additions by Ian C. Langtree.