Literature DB >> 22705841

PanDaTox: a tool for accelerated metabolic engineering.

Gil Amitai, Rotem Sorek.   

Abstract

Metabolic engineering is often facilitated by cloning of genes encoding enzymes from various heterologous organisms into E. coli. Such engineering efforts are frequently hampered by foreign genes that are toxic to the E. coli host. We have developed PanDaTox (www.weizmann.ac.il/pandatox), a web-based resource that provides experimental toxicity information for more than 1.5 million genes from hundreds of different microbial genomes. The toxicity predictions, which were extensively experimentally verified, are based on serial cloning of genes into E. coli as part of the Sanger whole genome shotgun sequencing process. PanDaTox can accelerate metabolic engineering projects by allowing researchers to exclude toxic genes from the engineering plan and verify the clonability of selected genes before the actual metabolic engineering experiments are conducted.

Entities:  

Year:  2012        PMID: 22705841      PMCID: PMC3476872          DOI: 10.4161/bioe.20431

Source DB:  PubMed          Journal:  Bioengineered        ISSN: 2165-5979            Impact factor:   3.269


  14 in total

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Authors:  Jay D Keasling
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Review 2.  Tools for genome-wide strain design and construction.

Authors:  Nanette R Boyle; Ryan T Gill
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Authors:  Rotem Sorek; Luis Serrano
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Review 4.  Manufacturing molecules through metabolic engineering.

Authors:  Jay D Keasling
Journal:  Science       Date:  2010-12-03       Impact factor: 47.728

5.  A vast collection of microbial genes that are toxic to bacteria.

Authors:  Aya Kimelman; Asaf Levy; Hila Sberro; Shahar Kidron; Azita Leavitt; Gil Amitai; Deborah R Yoder-Himes; Omri Wurtzel; Yiwen Zhu; Edward M Rubin; Rotem Sorek
Journal:  Genome Res       Date:  2012-02-01       Impact factor: 9.043

Review 6.  Synthetic biology for synthetic chemistry.

Authors:  Jay D Keasling
Journal:  ACS Chem Biol       Date:  2008-01-18       Impact factor: 5.100

Review 7.  Metabolic engineering of microorganisms for biofuels production: from bugs to synthetic biology to fuels.

Authors:  Sung Kuk Lee; Howard Chou; Timothy S Ham; Taek Soon Lee; Jay D Keasling
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8.  High-level production of amorpha-4,11-diene in a two-phase partitioning bioreactor of metabolically engineered Escherichia coli.

Authors:  Jack D Newman; Jessica Marshall; Michelle Chang; Farnaz Nowroozi; Eric Paradise; Douglas Pitera; Karyn L Newman; Jay D Keasling
Journal:  Biotechnol Bioeng       Date:  2006-11-05       Impact factor: 4.530

9.  Biosynthesis of complex polyketides in a metabolically engineered strain of E. coli.

Authors:  B A Pfeifer; S J Admiraal; H Gramajo; D E Cane; C Khosla
Journal:  Science       Date:  2001-03-02       Impact factor: 47.728

Review 10.  Metabolic engineering of Escherichia coli and Corynebacterium glutamicum for biotechnological production of organic acids and amino acids.

Authors:  Volker F Wendisch; Michael Bott; Bernhard J Eikmanns
Journal:  Curr Opin Microbiol       Date:  2006-04-17       Impact factor: 7.934

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  6 in total

1.  A set of powerful negative selection systems for unmodified Enterobacteriaceae.

Authors:  Varnica Khetrapal; Kurosh Mehershahi; Shazmina Rafee; Siyi Chen; Chiew Ling Lim; Swaine L Chen
Journal:  Nucleic Acids Res       Date:  2015-03-23       Impact factor: 16.971

2.  Phylogenomic networks reveal limited phylogenetic range of lateral gene transfer by transduction.

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3.  Codon reassignment to facilitate genetic engineering and biocontainment in the chloroplast of Chlamydomonas reinhardtii.

Authors:  Rosanna E B Young; Saul Purton
Journal:  Plant Biotechnol J       Date:  2015-10-15       Impact factor: 9.803

4.  Reconstruction of real and simulated phylogenies based on quartet plurality inference.

Authors:  Eliran Avni; Sagi Snir
Journal:  BMC Genomics       Date:  2018-08-13       Impact factor: 3.969

Review 5.  Bioengineering tools for the production of pharmaceuticals: current perspective and future outlook.

Authors:  Surendra Sarsaiya; Jingshan Shi; Jishuang Chen
Journal:  Bioengineered       Date:  2019-12       Impact factor: 3.269

6.  Computational evaluation of cellular metabolic costs successfully predicts genes whose expression is deleterious.

Authors:  Allon Wagner; Raphy Zarecki; Leah Reshef; Camelia Gochev; Rotem Sorek; Uri Gophna; Eytan Ruppin
Journal:  Proc Natl Acad Sci U S A       Date:  2013-11-06       Impact factor: 11.205

  6 in total

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