Biology subjects

Salman, H.

Publications and source records attributed to Salman, H..

3 recordsLinked to original sources

bioRxiv2024

Single-cell Growth Rate Variability in Balanced Exponential Growth

Exponential accumulation of cell size and highly expressed proteins is observed at the single-cell level in many bacterial species. While the exponential rates fluctuate from cycle to cycle, they remain stable on average over time and strongly correlated across different proteins and cell size. In this study, we investigate growth-rate variability at this state of balanced biosyn-thesis, and present a theoretical framework to explain its properties through the emergence of a high-dimensional collective dynamic attractor. This stable attractor arises from recurrent interactions among multiple cellular components, driving them to converge to the same expo-nential growth rate, thereby sustaining the balanced state. The convergence of growth rates induces a decay in instantaneous growth rate noise throughout the cell cycle, with a faster decay for higher average growth rates. Notably, our analysis identifies random deviations from symmetric division as the primary source of growth rate variability. The theory offers a coherent set of predictions for many observations, validated by extensive experimental single-cell data. The spontaneous emergence of homeostasis through dynamic interactions suggests that specific control mechanisms to compensate deviations from a target may not be necessary to maintain homeostasis in a balanced state.

biophysics↗

bioRxiv2023

Metabolomic rearrangement controls the intrinsic microbial response to temperature changes

Temperature is one of the key determinants of microbial behavior and survival, whose impact is typically studied under heat- or cold-shock conditions that elicit specific regulation to combat lethal stress. At intermediate temperatures, cellular growth rate varies according to the Arrhenius law of thermodynamics without stress responses, a behavior whose origins have not yet been elucidated. Using single-cell microscopy during temperature perturbations, we show that bacteria exhibit a highly conserved, gradual response to temperature upshifts with a time scale of [~]1.5 doublings at the higher temperature, regardless of initial/final temperature or nutrient source. We find that this behavior is coupled to a temperature memory, which we rule out as being neither transcriptional, translational, nor membrane dependent. Instead, we demonstrate that an autocatalytic enzyme network incorporating temperature-sensitive Michaelis-Menten kinetics recapitulates all temperature-shift dynamics through metabolome rearrangement, which encodes a temperature memory and successfully predicts alterations in the upshift response observed under simple-sugar, low-nutrient conditions, and in fungi. This model also provides a mechanistic framework for both Arrhenius-dependent growth and the classical Monod Equation through temperature-dependent metabolite flux.

cell biology↗

bioRxiv2021

Multiple timescales in bacterial growth homeostasis

In balanced exponential growth, bacterial cells maintain the stability of multiple properties simultaneously: cell size, growth rate, cycle time and more. These are not independent but strongly coupled variables; it is not a-priori clear which are under direct regulation and which are stabilized as a by-product of interactions. Here, we address this problem by separating different timescales in bacterial single-cell dynamics. Disentangling homeostatic set-points from fluctuations around them, we find that some properties have flexible set-points that highly sensitive to environment - defining "sloppy" variables, while other set-points are buffered and held tightly controlled - "stiff" variables. These control variables are combinations of sloppy ones that compensate one another over long times, creating a hierarchical buffering that protects them from environmental perturbations. This is manifested geometrically as a control manifold in the space of growth and division variables, whose in-plane directions span sloppy variables, while out-of-plane deviations are highly constrained. Cell size is found to be a sloppy variable, which is coupled to growth and division only on the short, single-cycle timescale. Our results show that cellular homeostasis involves multi-level regulation operating on multiple timescales. More generally, our work offers a data-driven approach for identifying control variables in a multi-dimensional system that can be applicable also in other contexts.

biophysics↗