You will be presented with the abstract, introduction, and discussion section from a biomedical research article. Your task is to create a summary that a layperson can understand, capturing the essence of the research article. Keep essential scientific terms, but ensure that the language remains clear and the concepts are explained in an uncomplicated manner.

Title: Active degradation of MarA controls coordination of its downstream targets}
Article:
Abstract:
Several key transcription factors have unusually short half-lives compared to other cellular proteins. Here, we explore the utility of active degradation in shaping how the multiple antibiotic resistance activator MarA coordinates its downstream targets. MarA controls a variety of stress response genes in Escherichia coli. We modify its half-life either by knocking down the protease that targets it via CRISPRi or by engineering MarA to protect it from degradation. Our experimental and analytical results indicate that active degradation can impact both the rate of coordination and the maximum coordination that downstream genes can achieve. In the context of multi-gene regulation, trade-offs between these properties show that perfect information fidelity and instantaneous coordination cannot coexist.
Introduction:
Active degradation is a rare feature in bacteria, affecting only 2–7% of total cellular proteins in Escherichia coli[1, 2]. Active degradation is accomplished by ATP-dependent proteases such as ClpXP, HflB, and Lon[3]. These proteases play a role in protein quality control by degrading misfolded proteins[4–6], but they can also degrade functional proteins. Active degradation of functional proteins can serve as a type of post-translational regulation to modify protein concentration[7]. This can be important in time-sensitive processes when removal through dilution is insufficient. Metabolic processes that incorporate active degradation include DNA damage repair, gene expression during stationary-phase, cell division, filamentation, and accelerated removal of certain regulatory proteins[8, 9]. Although active degradation can play a regulatory role, this comes with an energy cost due to the ATP necessary to activate the proteases, and a metabolic investment required to replace degraded proteins[10]. Active degradation occurs in many other microorganisms as well, such as with the ComK regulator of sporulation in Bacillus subtilis[11] and in many regulatory proteins in humans including the p53 tumor suppressor[12, 13] and IκBα, which dictates NF-κB activity and cellular stress response[14, 15]. The refractory period of NF-κB pulses is determined by this degradation rate, which dictates the limit of information transmission in the system[16]. In eukaryotes, the percentage of proteins that are primarily removed through active degradation ranges from ~15% in yeast[17] to ~50% in humans[18]. Therefore, despite active degradation’s role in regulation across domains of life, it is still comparatively rare in bacteria due to their rapid growth rate, which produces stronger dilution effects. The relative rarity coupled with the cost implicit to active degradation makes the presence of any short half-life protein in bacteria conspicuous. What potential utility could necessitate the use of this rare design feature? To answer this, we focused on the multi-antibiotic resistance activator( MarA) in E. coli as a case study. MarA has a short half-life even by the standards of an actively degraded protein, with an estimated half-life of 1–3 minutes due to Lon protease activity[19, 20]. Moreover, MarA regulates over 60 downstream targets involved in a variety of antibiotic resistance roles, from genes encoding efflux pump components like acrAB and tolC to stress response proteins like inaA[21, 22]. The majority of the downstream genes encode for stable proteins, therefore MarA has a much shorter half-life than most of its downstream targets[21]. MarA is part of a greater regulon, where three homologous proteins—MarA, Rob, and SoxS—regulate an overlapping suite of downstream genes[23]. However, MarA’s clear correlation with phenotypic outcomes make it an ideal target for studying why evolution would select for actively degraded regulatory molecules[24]. Recent studies have revealed that marA is expressed stochastically, creating phenotypic diversity within isogenic populations. This noisy expression is linked to transient antibiotic resistance[24]. Thus, stochastic expression of marA can impact whether a cell lives or dies under antibiotic exposure. At the population level, there is a distribution of MarA levels where some cells are antibiotic resistant and others are susceptible. This may serve as a bet hedging strategy, where cells with high marA expression act as insurance policy to protect against the sudden appearance of antibiotics or other stressors. In conditions with small numbers of cells, the rate at which diversity in MarA levels is generated is important. Starting with a single cell at a single time point, there is no diversity. As the cell grows and divides, diversity develops within the population. The rate at which this diversity develops depends on the time scale of the stochastic dynamics of the genes being expressed, including their rate of degradation[11, 25]. We measure diversity as the distribution of distinct protein concentrations present in a population. The half-life of the protein impacts the rate of diversity generation and the maximum diversity achieved( Fig 1A). For a regulatory protein such as MarA( X), phenotypic diversity can propagate to its downstream targets such as AcrAB and InaA( Y and Z)( Fig 1B). The rate at which diversity appears in downstream genes is impacted by how the upstream regulator changes with time. Active degradation affects the variability in the activator concentration—how quickly the concentration changes in one cell over time, as well as the diversity in concentrations between cells. This produces a spectrum of phenotypes where individual cells exhibit a range from low to high expression for all downstream targets( Fig 1C). This coordinated diversity in expression of genes that share a master regulator is different from the uncoordinated diversity in two uncoupled genes( Fig 1D). We used mutual information to quantify increasing coordination of downstream genes. Mutual information describes how well knowing the concentration of one of these proteins allows us to predict the concentration of the other[26]. It measures their co-expression properties even if the correlation between them is nonlinear, an important feature because transcriptional dose response curves typically saturate, following the shape of a Hill function[27]. S1 Movie shows an animation of how stochastic expression of an activator produces coordinated diversity within downstream targets. Coordination as a function of a shared master regulator is important for establishing synergistic effects between downstream targets. For instance, MarA activates expression of genes in the AcrAB-TolC efflux pump, the small RNA micF which decreases porin expression, and other stress response genes such as inaA. Conceptually, expressing multiple genes is like locking both the front door and the back door to a home in order to protect it; locking just one door makes the home only marginally safer and expends energy. Thus, coordinating expression of stress response genes is essential. Here, we investigate the role of activator half-life in controlling how a stochastic regulator generates coordinated diversity in multiple downstream genes. We do this by controlling the half-life of MarA, either by modulating the concentration of Lon protease or by protecting MarA itself from proteolytic degradation. We then evaluate the impact of MarA’s half-life by computing both the maximum amount of coordinated diversity that MarA can achieve as well as the rate at which it achieves it.
Discussion:
In E. coli, several key regulators are subject to active degradation. We show that in the case of MarA, the half-life of a regulatory molecule affects not only its time-series behavior and population statistics, but also its ability to coordinate downstream genes. This downstream coordination develops over time, with both a rate and maximum value. We focus on how individual founders of new bacterial populations can quickly establish a spectrum of coordinated phenotypes. We show that generating variability in downstream targets is limited by variability in the activators that control them. Also, signals from activators that change too quickly can be filtered, narrowing the spectrum of coordination in downstream targets. Our results indicate that there is a trade-off between information rate and maximum information in coordinating downstream targets. While this will depend on a number of system specific parameters, this trade-off shows that perfect information fidelity and instantaneous coordination cannot coexist. This is analogous to instructing two people to do a task in tandem–the faster you speak, the faster they can be instructed to coordinate and execute the objective, but at some point information is lost and mistakes will be made. Although we focused on how individual genes and proteins generate phenotypic diversity, extrinsic factors like growth rate have the potential to affect this as well. For instance, varying the cell division time can affect how variability in MarA forms( S5 Fig). In effect, the analytical solutions to the variance functions represent the upper limit on how diversity develops, and decreasing the growth rate scales this curve. Moreover, the greater complexity of the combined mar-rob-sox regulon may affect the rate at which their shared downstream genes coordinate[23]. Expanding this study to investigate the role of each component may reveal more complex emergent effects. While our experiments and models focused on downstream genes where the typical concentrations of MarA fall within their linear regime of activation, it should be noted that this is not true for all downstream targets of MarA. Previous research has highlighted that each downstream target possesses a unique nonlinear dose response curve as a function of MarA activation[27, 32]. It may be possible for growing cells to exploit the inherent nonlinearity of each downstream gene’s activation curve to better achieve the stoichiometric balance required by downstream targets with wide ranging functions. That is to say, while multiple downstream targets may be necessary to mount an effective barrier to stressors such as antibiotic challenge, the optimal activation curves of each may be unique. This flexibility of downstream activation allows for this balance to occur despite signals coming from a single shared activator. Alternatively, it may be possible that the promoters compete for a shared pool of regulatory molecules[41]. This would produce an anti-correlation between downstream gene responses, unlike the correlated responses we observed. Still in other systems or possibly in other regimes of MarA expression, this phenomenon may be observable. Moreover, we have focused on the role of MarA as a stochastic activator, however the concentration of MarA is also dependent on the environment[42]. Interestingly, the natural degradation rate of MarA may be below our calculated optimum for balancing between rate and information. In this case, the utility of active degradation may play a role in signal transmission as well by decreasing the response time[43, 44]. For instance, active degradation may allow for a transcription factor to more accurately track a time-varying environmental signal. By erasing the memory of a previous protein level, active degradation may allow for a more responsive and agile signaling network. Alternatively, the capacity of a degraded activator to generate phenotypic diversity rapidly may be useful for a few remaining cells to regenerate diversity following antibiotic challenge. Using a combination of single-cell time-lapse movies with multiple fluorescent reporters and analytical models we have demonstrated a role that protein half-life plays in generating single-cell variability and the ability of an activator to produce coordinated diversity in downstream genes. Our results show that both maximum coordinated diversity as well as the rate of coordination between multiple targets is dependent on activator half-life. This suggests a possible design advantage for active degradation and sheds light on how cells grow from individuals to diverse populations, while coordinating expression of related processes.
Very few proteins are actively degraded in bacteria , and those that are tend to be regulatory molecules . One example is MarA , which is a master regulator of stress response in E . coli . To study the role of active degradation , we decreased the degradation of MarA two ways: either by knocking down the protease that degrades it , or by modifying MarA to make it resistant to degradation . We measured how changes to the half-life of MarA change the way MarA’s downstream genes are coordinated over time . Combining these results with a theoretical model shows that active degradation in MarA represents a tradeoff favoring an increased rate of coordination over high maximum coordination . By combining experimental results with a theoretical framework , this research provides new insights into the advantages and disadvantage of actively degrading MarA .