Control of DNA structure and gene expression.

Metabolic control theory traditionally assumes enzyme concentrations remain constant during system adjustments. This simplification helps analyze short-term metabolic changes without gene expression shifts. However, in living systems, metabolic changes often coincide with gene expression variations. Prior research has shown that gene expression can influence enzyme levels over time. This gap motivated the development of a more comprehensive control analysis framework. Researchers propose that integrating gene expression variability into metabolic models can improve understanding of regulatory mechanisms. Existing models do not account for mRNA and enzyme dynamics influenced by RNA polymerase or ribosome activity. Experimental systems have yet to explore how transcription rates are affected by DNA supercoiling. This uncertainty drove the need to define new regulatory coefficients and test their relevance in prokaryotic systems.

The aim of this work is to expand metabolic control analysis by incorporating variable gene expression. Researchers focus on how mRNA and enzyme concentrations change due to RNA polymerase and ribosome activity. They also examine feedback repression at the translation level. The study introduces new coefficients to quantify regulatory loop strengths. These coefficients help assess how regulatory strengths are influenced by system parameters. The researchers test their framework using a prokaryotic model system. They investigate how DNA supercoiling affects transcription rates. This system includes enzymes that regulate DNA supercoiling, such as DNA gyrase and topoisomerase I.

Theoretical models are used to simulate systems with fixed gene numbers but variable mRNA and enzyme concentrations. These models consider RNA polymerase, RNAase, ribosome, and protease activities. A second model includes feedback repression by a metabolite at the translation stage. New coefficients are defined to measure regulatory loop strengths. These coefficients are linked to system parameters through a summation theorem. Experimental systems are based on prokaryotic DNA supercoiling effects on transcription. DNA gyrase activity is tested in vitro using ATP hydrolytic free energy. Researchers also inspect how active transcription influences DNA supercoiling in living cells.

Theoretical models show that mRNA and enzyme concentrations are regulated by RNA polymerase and ribosome activities. Feedback repression at the translation level alters regulatory loop strengths. New coefficients quantify these effects and their dependence on system parameters. Experimental data reveal that DNA supercoiling influences transcription rates in prokaryotes. Cellular free-energy states are linked to DNA supercoiling levels. Active transcription was found to affect DNA supercoiling in live cells. The study demonstrates that DNA gyrase activity is modulated by ATP hydrolytic free energy. These findings suggest that gene expression and metabolic control are interdependent.

The study shows that metabolic control analysis becomes more complex when gene expression is variable. Regulatory coefficients help quantify how gene expression affects metabolic control. Experimental evidence supports the idea that DNA supercoiling influences transcription rates. Researchers propose that prokaryotic systems can be analyzed using four hierarchical levels: DNA, RNA, enzymes, and metabolites. The summation theorem provides a framework for understanding regulatory interactions. These findings suggest that gene expression and metabolic control are tightly linked. The study does not claim that these mechanisms are essential for all systems. It highlights the need for further research on regulatory loop dynamics.