Biology subjects

Domitilla Del Vecchio

Publications and source records attributed to Domitilla Del Vecchio.

3 recordsLinked to original sources

bioRxiv2016

The Effects of Ribosome Autocatalysis and Negative Feedback in Resource Competition

BackgroundResource competition, and primarily competition for ribosomes, can lead to unexpected behavior of genetic circuits and has recently gained renewed attention with both experimental and theoretical studies. Current models studying the effects of resource competition assume a constant production of ribosomes and these models describe the experimental results well. However, ribosomes are also autocatalytic since they are partially made of protein and autocatalysis has been shown to have detrimental effects on a systems stability and robustness. Additionally, there are known feedback regulations on ribosome synthesis such as inhibition of rRNA synthesis via ppGpp.\n\nResultsHere, we develop two-state models of ribosome and protein synthesis incorporating autocatalysis and feedback to investigate conditions under which these regulatory actions have a significant effect in situations of increased ribosome demand. Our modeling results indicate that for sufficiently low demand, defined by the mRNA level of synthetic genes, autocatalysis has little or no effect. However, beyond a certain demand level, the system goes through a transcritical bifurcation at which the only non-negative steady state is at zero ribosome concentration. The presence of negative feedback, in turn, can shift this point to higher demand values, thus restoring the qualitative behavior observed in a model with a constant ribosome production at low demand. However, autocatalysis affects the dynamics of the system and can lead to an overshoot in the temporal response of the synthetic genes to changes in induction level.\n\nConclusionOur results show that ribosome autocatalysis has a significant effect on the system robustness to increases in ribosome demand, however the existing negative feedback on ribosome production compensates for the effects of the necessary autocatalytic loop and restores the behavior seen in the system with constant ribosome production. These findings explain why previous models with constant ribosome production reproduce the steady state behavior well, however incorporating autocatalysis and feedback is needed to capture the transient behavior.

Systems Biology↗

bioRxiv2016

Transcription factor loads tend to decrease the robustness of stable gene transcription networks

Robustness of a systems behavior to changes in parameter values is a remarkable property of natural systems and especially desirable when designing de novo synthetic gene circuits. Loads on transcription factors resulting from binding to target promoters have been shown to significantly affect the effective time constants of gene transcription networks and to thus alter the overall systems behavior. Here, we employ models that explicitly account for load effects to investigate how these impact the robustness of a stable gene transcription network to parameter perturbations. By employing a combination of sampling-based methods and analytical tools from control theory, we demonstrate that the presence of loading shrinks the region of parameter space where a gene circuit performs the desired function. A number of multi-module synthetic gene circuits are analyzed to demonstrate this point, including an event detector and a molecular signature classifier. These results indicate that for designing genetic circuits that are robust to parameter uncertainty it is highly desirable to find ways to mitigate the effects of transcription factor loading.\n\nAuthor SummaryEfforts to understand how loads affect gene transcription networks have been underway in the past decade. Here we perform a numerical investigation on three synthetic gene circuits to show that loads tend to decrease the robustness of stable gene transcriptional networks. We complement the numerical findings with analytical derivations that employ the stability radius to compare the robustness of different networks to parameter perturbations near an equilibrium point. Consistent with the numerical finding, the analytical results support that systems with substantial transcription factor loading have smaller stability radius (less robustness) than systems without loading.

Systems Biology↗

bioRxiv2015

A Dynamical Model for the Low Efficiency of Induced Pluripotent Stem Cell Reprogramming

In the past decade, researchers have been able to obtain pluripotent stem cells directly from an organisms differentiated cells through a process called cell reprogramming. This opens the way to potentially groundbreaking applications in regenerative and personalized medicine, in which ill patients could use self-derived induced pluripotent stem (iPS) cells where needed. While the process of reprogramming has been shown to be possible, its efficiency remains so low after almost ten years since its conception as to render its applicability limited to laboratory research. In this paper, we study a mathematical model of the core transcriptional circuitry among a set of key transcription factors, which is thought to determine the switch among pluripotent and differentiated cell types. By employing standard tools from dynamical systems theory, we analyze the effects on the systems dynamics of overexpressing the core factors, which is what is performed during the reprogramming process. We demonstrate that the structure of the system is such that it can render the switch from an initial stable steady state (differentiated cell type) to the desired stable steady state (pluripotent cell type) highly unlikely. This finding provides insights into a possible reason for the low efficiency of current reprogramming approaches.

Systems Biology↗