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Droghetti, R.

Publications and source records attributed to Droghetti, R..

5 recordsLinked to original sources

Universal sublinear population growth density dependence unrelated to resource limitation

Growth slows as population density increases, sensitively influencing species coexistence, conservation, and resource management. This slowdown is widely attributed to declining per-capita access to energy and nutrients, and standard models of resource-limited growth predict superlinear declines of growth rate with density. However, we observed sublinear declines for 94% of 4,022 bacterial and eukaryotic growth curves. High-resolution experiments with Escherichia coli revealed a two-phase density dependence: a dominant sublinear regime that transitions to superlinear decline only very near population saturation. The sublinear pattern was invariant across initial resource concentrations, ruling out resource depletion as the cause of early slowing. Our results challenge the standard resource-limitation paradigm and identify non-resource inhibitory processes as a widespread and previously unappreciated regulator of population growth.

ecology↗

Transcriptional competition biases the effects of second messengers in E. coli

Cells regulate gene expression by balancing transcriptional resources across different functional groups of genes. In Escherichia coli, second messengers such as ppGpp and cAMP control ribosome biogenesis and metabolic gene expression, respectively. While these regulators are typically studied in isolation, we provide a theory showing that their effects are intertwined due to global transcriptional competition. Using experimental data from RelA overexpression and a mechanistic modeling framework, we show that ppGpp-mediated repression of ribosomal genes competes for transcriptional resources with cAMP-driven activation of catabolic genes. This competition reshapes proteome allocation in a way that transcends individual regulators. Our findings challenge common modeling assumptions about transcription factor action and revive classical ideas suggesting that large-scale gene regulation should be studied within the broader context of resource availability, with implications for understanding cellular regulation across diverse biological systems, beyond bacterial physiology.

systems biology↗

Gradual entry into carbon starvation decreases the death rate of Escherichia coli

Bacterial fitness is determined both by how fast cells grow in nutrient-rich environments and by how well they survive when nutrients are depleted. However, these behaviors are not independent, since the molecular composition of non-growing cells is affected by their prior growth history. For instance, recent work observed that the death rates of Escherichia coli cultures that rapidly entered carbon starvation depend on their prior growth rates, with faster growth leading to exponentially faster death. On the other hand, it is well known that cells adapt their molecular composition as they slow down growth and enter stationary phase, which is generally believed to improve their chance of survival. Hence, the question arises to what extent this adaptation process reduces the subsequent death rate. And how does the duration of the time window during which cells are allowed to adapt determine the reduction in death rate, and thus the fitness benefit of adaptation? Here, we study these quantitative questions by probing the adaptation of E. coli during gradual transitions from exponential growth to carbon starvation. We monitor such transitions in cultures with different initial growth conditions and measure the resulting rates of cell death after the transition. Our experiments demonstrate that cells with the opportunity to adapt their proteome composition before entering a state of starvation exhibit lower death rates compared to those that cannot, across various substrate conditions. The quantitative data is consistent with a theoretical model built on the assumption that before starvation, cells up-regulate a specific sector of the proteome, the effect of which is to decrease the death rate in energy-limiting conditions. This work highlights the influence of the non-genetic memory of a cell, specifically in the form of inherited proteome composition, on bacterial fitness. Our results emphasize that a comprehensive understanding of bacterial fitness requires quantitative characterization of bacterial physiology in all phases of their life cycle, including growth, stationary phase, and death, as well as the transitions between them. AUTHOR SUMMARYBacteria inhabit dynamic environments and are frequently challenged by scarcity of nutrients. A recent study uncovered a curious link - faster bacterial growth leads to more rapid death when resources run out. We find that bacteria that gradually enter starvation exhibit significantly enhanced survival compared to those that do not have the chance to adapt. We interpret the observed quantitative behavior with the help of a theoretical model, which shows that our data is not compatible with a passive adaptation process, which would rely only on the general remodeling of the cellular proteome that is associated with growth transitions. Instead, our data are consistent with an active adaptation via up-regulation of genes that enhance survival during starvation. These results provide a novel perspective on bacterial survival strategies and underscore the importance of quantitatively investigating all phases of bacterial life cycles.

physiology↗

Coupled ribosome allocation and nutrient sensing lead to incoherent feedback and oscillatory response in bacterial growth.

Current theories of bacterial growth physiology demonstrate impressive predictive power but are often phenomenological, lacking mechanistic detail. Incorporating such details would significantly enhance our ability to predict and control bacterial growth under varying environmental conditions. The "Flux Controlled Regulation" (FCR) model serves as a reference framework, linking ribosome allocation to translation efficiency through a steady-state assumption. However, it neglects ppGpp-mediated nutrient sensing and transcriptional regulation of ribosomal operons. Here, we propose a mechanistic model that extends the FCR framework by incorporating three key components: (i) the amino acid pool, (ii) ppGpp sensing of translation elongation rate, and (iii) transcriptional regulation of protein allocation by ppGpp-sensitive promoters. Our model aligns with observed steady-state growth laws and makes testable predictions for unobserved quantities. We show that during environmental changes, the incoherent feedback between sensing and regulation generates oscillatory relaxation dynamics, a behavior that we support by new and existing experimental data.

systems biology↗

An evolutionary model identifies the main selective pressures for the evolution of genome-replication profiles.

Recent results comparing the temporal program of genome replication of yeast species belonging to the Lachancea clade support the scenario that the evolution of replication timing program could be mainly driven by correlated acquisition and loss events of active replication origins. Using these results as a benchmark, we develop an evolutionary model defined as birth-death process for replication origins, and use it to identify the selective pressures that shape the replication timing profiles. Comparing different evolutionary models with data, we find that replication origin birth and death events are mainly driven by two evolutionary pressures, the first imposes that events leading to higher double-stall probability of replication forks are penalized, while the second makes less efficient origins more prone to evolutionary loss. This analysis provides an empirically grounded predictive framework for quantitative evolutionary studies of the replication timing program.

evolutionary biology↗