Accurate characterization of dynamic microbial gene expression and growth rate profiles

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dc.contributor.authorVidal, Gonzalo
dc.contributor.authorVidal-Cespedes, Carlos
dc.contributor.authorSilva, Macarena Munoz
dc.contributor.authorCastillo-Passi, Carlos
dc.contributor.authorFeliu, Guillermo Yanez
dc.contributor.authorFederici, Fernan
dc.contributor.authorRudge, Timothy J.
dc.date.accessioned2025-01-20T21:01:53Z
dc.date.available2025-01-20T21:01:53Z
dc.date.issued2022
dc.description.abstractGenetic circuits are subject to variability due to cellular and compositional contexts. Cells face changing internal states and environments, the cellular context, to which they sense and respond by changing their gene expression and growth rates. Furthermore, each gene in a genetic circuit operates in a compositional context of genes which may interact with each other and the host cell in complex ways. The context of genetic circuits can, therefore, change gene expression and growth rates, and measuring their dynamics is essential to understanding natural and synthetic regulatory networks that give rise to functional phenotypes. However, reconstruction of microbial gene expression and growth rate profiles from typical noisy measurements of cell populations is difficult due to the effects of noise at low cell densities among other factors. We present here a method for the estimation of dynamic microbial gene expression rates and growth rates from noisy measurement data. Compared to the current state-of-the-art, our method significantly reduced the mean squared error of reconstructions from simulated data of growth and gene expression rates, improving the estimation of timing and magnitude of relevant shapes of profiles. We applied our method to characterize a triple-reporter plasmid library combining multiple transcription units in different compositional and cellular contexts in Escherichia coli. Our analysis reveals cellular and compositional context effects on microbial growth and gene expression rate dynamics and suggests a method for the dynamic ratiometric characterization of constitutive promoters relative to an in vivo reference.
dc.fuente.origenWOS
dc.identifier.doi10.1093/synbio/ysac020
dc.identifier.eissn2397-7000
dc.identifier.urihttps://doi.org/10.1093/synbio/ysac020
dc.identifier.urihttps://repositorio.uc.cl/handle/11534/92974
dc.identifier.wosidWOS:000868350200001
dc.issue.numero1
dc.language.isoen
dc.revistaSynthetic biology
dc.rightsacceso restringido
dc.subjectInverse problem
dc.subjectcharacterization
dc.subjectdynamical systems
dc.subjectweb application
dc.subjectgene expression
dc.subject.ods03 Good Health and Well-being
dc.subject.odspa03 Salud y bienestar
dc.titleAccurate characterization of dynamic microbial gene expression and growth rate profiles
dc.typeartículo
dc.volumen7
sipa.indexWOS
sipa.trazabilidadWOS;2025-01-12
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