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dc.contributorVirginia Tech
dc.contributor.authorMather, William H.
dc.contributor.authorHasty, Jeff
dc.contributor.authorTsimring, Lev S.
dc.contributor.authorWilliams, Ruth J.
dc.date.accessioned2014-02-26T19:10:04Z
dc.date.available2014-02-26T19:10:04Z
dc.date.issued2013-06
dc.identifier.citationMather, William H.; Hasty, Jeff; Tsimring, Lev S.; et al., "Translational Cross Talk in Gene Networks," Biophysical Journal 104(11), 2564-2572 (2013); doi: 10.1016/j.bpj.2013.04.049
dc.identifier.issn0006-3495
dc.identifier.urihttp://hdl.handle.net/10919/25769
dc.description.abstractIt has been shown experimentally that competition for limited translational resources by upstream mRNAs can lead to an anticorrelation between protein counts. Here, we investigate a stochastic model for this phenomenon, in which gene transcripts of different types compete for a finite pool of ribosomes. Throughout, we utilize concepts from the theory of multiclass queues to describe a qualitative shift in protein count statistics as the system transitions from being underloaded (ribosomes exceed transcripts in number) to being overloaded (transcripts exceed ribosonnes in number). The exact analytical solution of a simplified stochastic model, in which the numbers of competing mRNAs and ribosomes are fixed, exhibits weak positive correlations between steady-state protein counts when total transcript count slightly exceeds ribosome count, whereas the solution can exhibit strong negative correlations when total transcript count significantly exceeds ribosome count. Extending this analysis, we find approximate but reasonably accurate solutions for a more realistic model, in which abundances of mRNAs and ribosonnes are allowed to fluctuate randomly. Here, ribosomal fluctuations contribute positively and mRNA fluctuations contribute negatively to correlations, and when mRNA fluctuations dominate ribosomal fluctuations, a strong anticorrelation extremum reliably occurs near the transition from the underloaded to the overloaded regime.
dc.description.sponsorshipNational Institutes of Health R01-GM079333, R01-GM089976
dc.description.sponsorshipNational Institutes of Health (San Diego Center for Systems Biology) P50GM085764
dc.description.sponsorshipNational Science Foundation DMS 1206772
dc.language.isoen_US
dc.publisherCELL PRESS
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectsynthetic biology
dc.subjectregulatory networks
dc.subjectexpression
dc.subjectrna
dc.subjectgrowth
dc.subjectabundance
dc.subjectprotein
dc.subjectretroactivity
dc.subjectcompetition
dc.subjectbacteria
dc.titleTranslational Cross Talk in Gene Networks
dc.typeArticle - Refereed
dc.contributor.departmentPhysicsen_US
dc.identifier.urlhttp://www.sciencedirect.com/science/article/pii/S0006349513005171
dc.date.accessed2014-02-05
dc.title.serialBiophysical Journal
dc.identifier.doihttps://doi.org/10.1016/j.bpj.2013.04.049


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