Evidence for rate-dependent filtering of global extrinsic noise by biochemical reactions in mammalian cells

Gradient matching accelerates mixed-effects inference for biochemical networks

MOTIVATION

Single-cell time series data often exhibit significant variability within an isogenic cell population. When modeling intracellular processes, it is therefore more appropriate to infer parameter distributions that reflect this variability, rather than fitting the population average to obtain a single point estimate. The Global Two-Stage (GTS) approach for nonlinear mixed-effects (NLME) models is a simple and modular method commonly used for this purpose. However, this method is computationally intensive due to its repeated use of nonconvex optimization and numerical integration of the underlying system.

RESULTS

We propose the Gradient Matching GTS (GMGTS) method as an efficient alternative to GTS. Gradient matching offers an integration-free approach to parameter estimation that is particularly powerful for systems that are linear in the unknown parameters, such as biochemical networks modeled by mass action kinetics. By incorporating gradient matching into the GTS framework, we expand its capabilities through uncertainty propagation calculations and an iterative estimation scheme for partially observed systems. Comparisons between GMGTS and GTS across various inference setups show that our method significantly reduces computational demands, facilitating the application of complex NLME models in systems biology.

AVAILABILITY AND IMPLEMENTATION

A Matlab implementation of GMGTS is provided at https://github.com/yulanvanoppen/GMGTS (DOI: http://doi.org/10.5281/zenodo.14884457).

In enzymatic reactions, the reverse reaction reduces product noise

Enzymatic reactions are essential for most cellular reactions and ubiquitous in living organisms. In the present study, we explore the pivotal role of the reverse reaction in enzymatic reactions. It is a powerful noise-buffering motif. By SSA (stochastic simulation algorithm), a remarkable 32% reduction of product CV (coefficient of variation) was observed. To better understand the causes, we split the upstream noise. The product CV reduction is more than 35% for the noise inherited from the enzyme but merely 6%-21% for that from the substrate. It implies that the system applies different strategies to different upstream noises. We identified two leading causes responsible for noise attenuation. A cell is well designed to control its intracellular noise, and to acquire wisdom from nature is always enjoyable.

A guide to genetically-encoded redox biosensors: State of the art and opportunities

Genetically-encoded redox biosensors have become invaluable tools for monitoring cellular redox processes with high spatiotemporal resolution, coupling the presence of the redox-active analyte with a change in fluorescence signal that can be easily recorded. This review summarizes the available fluorescence recording methods and presents an in-depth classification of the redox biosensors, organized by the analytes they respond to. In addition to the fluorescent protein-based architectures, this review also describes the recent advances on fluorescent, chemigenetic-based redox biosensors and other emerging chemigenetic strategies. This review examines how these biosensors are designed, the biosensors sensing mechanism, and their practical advantages and disadvantages.

Systematic In Vivo Characterization of Fluorescent Protein Maturation in Budding Yeast

Fluorescent protein (FP) maturation can limit the accuracy with which dynamic intracellular processes are captured and reduce the in vivo brightness of a given FP in fast-dividing cells. The knowledge of maturation timescales can therefore help users determine the appropriate FP for each application. However, in vivo maturation rates can greatly deviate from in vitro estimates that are mostly available. In this work, we present the first systematic study of in vivo maturation for 12 FPs in budding yeast. To overcome the technical limitations of translation inhibitors commonly used to study FP maturation, we implemented a new approach based on the optogenetic stimulations of FP expression in cells grown under constant nutrient conditions. Combining the rapid and orthogonal induction of FP transcription with a mathematical model of expression and maturation allowed us to accurately estimate maturation rates from microscopy data in a minimally invasive manner. Besides providing a useful resource for the budding yeast community, we present a new joint experimental and computational approach for characterizing FP maturation, which is applicable to a wide range of organisms.

The switch of DNA states filtering the extrinsic noise in the system of frequency modulation

There is a special node, which the large noise of the upstream element may not always lead to a broad distribution of downstream elements. This node is DNA, with upstream element TF and downstream elements mRNA and proteins. By applying the stochastic simulation algorithm (SSA) on gene circuits inspired by the fim operon in Escherichia coli, we found that cells exchanged the distribution of the upstream transcription factor (TF) for the transitional frequency of DNA. Then cells do an inverse transform, which exchanges the transitional frequency of DNA for the distribution of downstream products. Due to this special feature, DNA in the system of frequency modulation is able to reset the noise. By probability generating function, we know the ranges of parameter values that grant such an interesting phenomenon.