Corporate Banner
Satellite Banner
Informatics
Scientific Community
 
Become a Member | Sign in
Home>News>This Article
  News
Return

A Digital Test for Toxic Genes

Published: Thursday, January 30, 2014
Last Updated: Friday, January 31, 2014
Bookmark and Share
TAU researchers develop a computer algorithm that identifies genes whose activation is lethal to bacteria.

Like little factories, cells metabolize raw materials and convert them into chemical compounds. Biotechnologists take advantage of this ability, using microorganisms to produce pharmaceuticals and biofuels. To boost output to an industrial scale and create new types of chemicals, biotechnologists manipulate the microorganisms' natural metabolism, often by "overexpressing" certain genes in the cell. But such metabolic engineering is hampered by the fact that many genes become toxic to the cell when overexpressed.

Now, Allon Wagner, Uri Gophna, and Eytan Ruppin of Tel Aviv University'sBlavatnik School of Computer Science and Department of Molecular Microbiology and Biotechnology, along with researchers at the Weizmann Institute of Science, have developed a computer algorithm that predicts which metabolic genes are lethal to cells when overexpressed. The findings, published in Proceedings of the National Academy of Sciences, could help guide metabolic engineering to produce new chemicals in more cost-effective ways.

"In the lab, biotechnologists often determine which genes can be overexpressed using trial and error," said Wagner. "We can save them a lot of time and money by ruling out certain possibilities and highlighting other, more promising ones."

Gaining an EDGE
When metabolic genes are expressed, the genetic information they contain is converted into proteins, which catalyze the chemical reactions necessary for life. Overexpression means that greater-than-normal amounts of proteins are produced. Biotechnologists typically overexpress native genes of an industrial microorganism to boost a certain metabolic pathway in the cell, thus increasing the production of desired compounds. Sometimes they overexpress foreign genes — genes transferred from other organisms — in an industrial microbe to build new metabolic pathways and allow it to synthesize new compounds. But they often find that their efforts are hindered by the toxicity of the genes that they wish to overexpress.

Prof. Ruppin's laboratory builds large-scale software models of cellular metabolism, one of the most fundamental aspects of life. These models convert physical, chemical, and biological information into a set of mathematical equations, allowing scientists to learn how cells work and explore what happens if they are tweaked in certain ways. The newly developed algorithm, Expression Dependent Gene Effects, or EDGE, predicts what happens if scientists manipulate cells to overexpress certain genes. EDGE allows biotechnologists to foresee cases in which the overexpressed genes become toxic and then direct their efforts toward other genes.

To validate their method, TAU researchers used genetic manipulation tools to overexpress 26 different genes in E. coli bacterial cells. Comparing the results of their computer simulations with the actual growth of the overexpressed strains that was measured in the lab, they saw that EDGE was able to predict which of the overexpressed genes turned out to be lethal to E. coli. EDGE was also successful in identifying cases of foreign genes that were toxic to E. coli, as the researchers learned from comparing the simulations' results with data collected by their collaborators at the Weizmann Institute of Science.

Beyond bacteria
EDGE's applications appear to extend beyond bacteria. The researchers conducted tests showing that the genes EDGE predicted to be toxic when overexpressed are expressed at low levels not only in microorganisms like bacteria, but also in multicellular organisms, including humans. The researchers say these results reflect the vital evolutionary need to keep the expression of potentially deleterious genes in check.

"Although EDGE's current focus is biotechnology, gene overexpression also plays a central part in many human diseases, particularly in cancer. We hope that future work will apply EDGE to those directions," Wagner said.


Further Information
Access to this exclusive content is for Technology Networks Premium members only.

Join Technology Networks Premium for free access to:

  • Exclusive articles
  • Presentations from international conferences
  • Over 2,500+ scientific posters on ePosters
  • More than 3,700+ scientific videos on LabTube
  • 35 community eNewsletters


Sign In



Forgotten your details? Click Here
If you are not a member you can join here

*Please note: By logging into TechnologyNetworks.com you agree to accept the use of cookies. To find out more about the cookies we use and how to delete them, see our privacy policy.


Scientific News
Searching Big Data Faster
Theoretical analysis could expand applications of accelerated searching in biology, other fields.
Imaging Software Could Speed Breast Cancer Diagnosis
Technology could improve access to diagnostic services in developing countries.
Data Mining DNA For Polycystic Ovary Syndrome Genes
A new Northwestern Medicine genome-wide association study of PCOS – the first of its kind to focus on women of European ancestry – has provided important new insights into the underlying biology of the disorder.
Firefly Protein Enables Visualization of Roots in Soil
A new imaging tool from a team led by Carnegie’s José Dinneny allows researchers to study the dynamic growth of root systems in soil, and to uncover the molecular signaling pathways that control such growth.
UEA Research Could Help Build Computers From DNA
New research from the University of East Anglia could one day help build computers from DNA.
Viral Comparisons
ORNL team applies genomics expertise to analyze, map virus sequence database.
Preserving Fleeting Digital Information with DNA
A team has demonstrated that DNA they encapsulated can preserve information for at least 2,000 years, and they’re now working on a filing system to make it easier to navigate.
TGAC Leads Development to Diminish Threat to Vietnam’s Most Important Crop
Advanced bioinformatics capabilities for next-generation rice genomics in Vietnam to aid precision breeding.
Mass Extinctions Can Accelerate Evolution
A computer science team at The University of Texas at Austin has found that robots evolve more quickly and efficiently after a virtual mass extinction modeled after real-life disasters such as the one that killed off the dinosaurs.
Furthering Data Analysis of Next-gen Sequencing to Facilitate Research
Researchers at Cincinnati Children's Hospital Medical Center have developed a user-friendly, integrated platform for analyzing the transcriptomic and epigenomic "big data.
Scroll Up
Scroll Down
Skyscraper Banner

Skyscraper Banner
Go to LabTube
Go to eposters
 
Access to the latest scientific news
Exclusive articles
Upload and share your posters on ePosters
Latest presentations and webinars
View a library of 1,800+ scientific and medical posters
2,500+ scientific and medical posters
A library of 2,500+ scientific videos on LabTube
3,700+ scientific videos
Close
Premium CrownJOIN TECHNOLOGY NETWORKS PREMIUM FREE!