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The gene expression in cells is regulated at different stages: (i) transcription, (ii) RNA processing, (iii) RNA localization, and (iv) translation. Transcriptional regulation is mediated by regulatory proteins such as transcription factors, activators, or repressors—these control gene expression by initiating or inhibiting the transcription of genes. Once a precursor or pre-mRNA is produced, it undergoes post-transcriptional modification, including 5' capping, splicing, and the...
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Gene expression in prokaryotes is governed by constitutive and regulated systems, allowing cells to balance the production of essential proteins with adaptive responses to environmental changes.Constitutive Gene ExpressionConstitutive, or housekeeping, genes are continuously expressed as they encode proteins vital for fundamental cellular processes. These include enzymes for glycolysis, ribosomal components for protein synthesis, and proteins involved in DNA replication. Their constant...
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Computational study of parameter sensitivity in DevR regulated gene expression.

Jagannath Das1, Tarunendu Mapder1, Sudip Chattopadhyay1

  • 1Department of Chemistry, Indian Institute of Engineering Science and Technology, Shibpur, Howrah, India.

Plos One
|February 14, 2020
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Summary
This summary is machine-generated.

The DevRS system in Mycobacterium tuberculosis regulates gene expression under hypoxia. Computational analysis identified key kinetic parameters controlling this vital process, revealing their sensitivity and importance for bacterial survival.

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Area of Science:

  • Microbiology
  • Molecular Biology
  • Computational Biology

Background:

  • The DevRS two-component system is crucial for signal transduction and gene regulation in Mycobacterium tuberculosis.
  • Under hypoxic conditions, phosphorylated DevR binds to target gene promoter regions.

Purpose of the Study:

  • To computationally analyze the sensitivity of kinetic parameters governing DevRS-mediated gene expression.
  • To identify and quantify the essential kinetic parameters for DevR-regulated gene expression.

Main Methods:

  • Detailed computational analysis was performed.
  • Stochastic optimization was employed to determine kinetic parameter sets.
  • Correlation coefficients and sensitivity amplification were used to assess parameter importance.

Main Results:

  • The study identified the relative importance of various kinetic parameters in DevR-regulated gene expression.
  • Sensitivity analysis revealed critical parameters influencing the DevRS system's function.
  • Correlation coefficients helped order the kinetic parameters based on their impact.

Conclusions:

  • Understanding DevRS kinetic parameters is vital for deciphering Mycobacterium tuberculosis gene regulation under hypoxia.
  • This computational approach provides insights into the sensitivity and relative importance of kinetic parameters in a key bacterial regulatory system.