Biology subjects

Nieto Acuna, C. A.

Publications and source records attributed to Nieto Acuna, C. A..

4 recordsLinked to original sources

bioRxiv2022

Modeling cell size regulation under complex and dynamic environments

In nature, cells face changes in environmental conditions that can modify their growth rate. In these dynamic environments, recent experiments found changes in cell size regulation. Currently, there are few clues about the origin of these cell size changes. In this work, we model cell division as a stochastic process that occurs at a rate proportional to the size. We propose that this rate is zero if the cell is smaller than a minimum size. We show how this model predicts some of the properties found in cell size regulation. For example, among our predictions, we found that the mean cell size is an exponential function of the growth rate under steady conditions. We predict that cells become smaller and the way the division strategy changes during dynamic nutrient depletion. Finally, we use the model to predict cell regulation in an arbitrary complex dynamic environment.

systems biology↗

bioRxiv2020

Division stochasticity can be transmitted to protein expression through chromosome replication

Stochastic fluctuations (noise) are a fundamental characteristic of protein production. Some sources of this stochasticity are still under debate. In this work, we explore how these fluctuations can originate from the stochasticity on division events. To do that, we consider the classical gene expression model with chromosome replication following the known Helmstetter & Cooper model. This model predicts intervals of the cell cycle where bacteria can have more than one copy of a particular gene. Considering the transcription rate as proportional to the number of chromosomes and division based on a continuous rate model, we explore how stochasticity in division or equivalently in cell size, could be transmitted to gene expression. Our simulations suggest that division can be an important source of such fluctuations only if chromosomes are replicating, otherwise, this noise is not well transmitted. This effect happens even if replication is deterministic. This work can be helpful for understanding cell cycle dynamics and their interplay with phenotypic variability.

systems biology↗

bioRxiv2020

Cell size statistics in cell lineages and population snapshots with different growth regimes and division strategies.

Growing populations of bacteria control their growth and division reaching narrow distributions of cell-sizes. In this paper we explored how different combinations of growth regimes and division mechanisms lead to different cell-size statistics in these populations. Deterministic and stochastic modeling were used to describe the size distribution of a population of cells that is observed from two different perspectives: as single cell lineages, i.e. random paths in the lineage tree, or as snapshots, at given times, of a population in which all descendants of a single ancestor cell are observed. Our time-dependent approaches allowed us to obtain both the transient dynamics and the steady state values for the main statistical moments of the cell-size distribution. Also, we established mathematical relationships among the statistics in the two considered perspectives, thus improving our knowledge of how cells control their growth and proliferation.

systems biology↗

bioRxiv2019

Stochasticity in bacterial division control: Preliminary consequences for protein concentration

The stochastic nature of protein concentration inside cells can have important consequences in their physiology and population fitness. Classical models of gene expression consider these processes as first-order reactions with little dependence with the cell size. However, the concentrations of the relevant molecules depend directly on the cellular volume. Here we model the cell size dynamics as exponential growth followed by division with occurrence rate proportional to the size. This framework, together with known models of chromosome replication and both protein and mRNA synthesis, lets us predict relationships between cell size and both protein number and concentration. As a main result, we find that protein production strategies (constant rate or rate proportional to either chromosome number, cell size or chromosome number times cell size) can be experimentally distinguished from the correlation between protein concentration and cell size.

systems biology↗