Infoscience

Journal article

An algorithmic framework for genome-wide modeling and analysis of translation networks

The sequencing of genomes of several organisms and advances in high throughput technologies for transcriptome and proteome anal. has allowed detailed mechanistic studies of transcription and translation using math. frameworks that allow integration of both sequence-specific and kinetic properties of these fundamental cellular processes. To understand how perturbations in mRNA levels affect the synthesis of individual proteins within a large protein synthesis network, we consider here a genome-scale codon-wide model of the translation machinery with explicit description of the processes of initiation, elongation, and termination. The mechanistic codon-wide description of the translation process and the large no. of mRNAs competing for resources, such as ribosomes, requires the use of novel efficient algorithmic approaches. We have developed such an efficient algorithmic framework for genome-scale models of protein synthesis. The math. and computational framework was applied to the anal. of the sensitivity of a translation network to perturbation in the rate consts. and in the mRNA levels in the system. These studies suggest that the highest specific protein synthesis rate (protein synthesis rate per mRNA mol.) is achieved when translation is elongation-limited. We find that the mRNA species with the highest no. of actively translating ribosomes exerts max. control on the synthesis of every protein, and the response of protein synthesis rates to mRNA expression variation is a function of the strength of initiation of translation at different mRNA species. Such quant. understanding of the sensitivity of protein synthesis to the variation of mRNA expression can provide insights into cellular robustness mechanisms and guide the design of protein prodn. systems. [on SciFinder (R)]

    Keywords: algorithm framework genomewide modeling translation network

    Note:

    3-1 FIELD Section Title:Biochemical Genetics

    6, 20

    Department of Chemical and Biological Engineering, McCormick School of Engineering and Applied Sciences,Northwestern University,Evanston,IL,USA. FIELD URL:

    written in English.

    Reference

    • LCSB-ARTICLE-2006-002

    Record created on 2007-01-11, modified on 2016-08-08

Fulltext

  • There is no available fulltext. Please contact the lab or the authors.

Related material