Abstract
We present a study investigating the role of mitochondrial variability in generating noise in eukaryotic cells. Noise in cellular physiology plays an important role in many fundamental cellular processes, including transcription, translation, stem cell differentiation and response to medication, but the specific random influences that affect these processes have yet to be clearly elucidated. Here we present a mechanism by which variability in mitochondrial volume and functionality, along with cell cycle dynamics, is linked to variability in transcription rate and hence has a profound effect on downstream cellular processes. Our model mechanism is supported by an appreciable volume of recent experimental evidence, and we present the results of several new experiments with which our model is also consistent. We find that noise due to mitochondrial variability can sometimes dominate over other extrinsic noise sources (such as cell cycle asynchronicity) and can significantly affect large-scale observable properties such as cell cycle length and gene expression levels. We also explore two recent regulatory network-based models for stem cell differentiation, and find that extrinsic noise in transcription rate causes appreciable variability in the behaviour of these model systems. These results suggest that mitochondrial and transcriptional variability may be an important mechanism influencing a large variety of cellular processes and properties.
Highlights
Stochastic influences significantly affect a multitude of processes in cellular biology [1,2,3,4,5]
We report new experimental results of relevance to the study of mitochondrial variability and show that these too largely agree with the predictions from our simple model
We show how our model allows a quantitative link to be formed between mitochondrial variability and variability in transcription rate in cells
Summary
Stochastic influences significantly affect a multitude of processes in cellular biology [1,2,3,4,5]. Noise in cellular processes may result from sources intrinsic to the gene in question (those responsible for differences in the expression levels of genes under identical regulation in the same cell) or extrinsic sources (those responsible for cell-to-cell variation in genes under identical regulation in a population). Some studies have found the contribution of extrinsic factors to overall noise levels to be stronger in eukaryotes [14,15] than prokaryotes [3], others debate this interpretation [16] To investigate these influences, several mathematical models for the emergence of intrinsic and extrinsic cellular noise have been introduced and explored [12,17,18,19,20,21,22,23,24]. Recent studies have investigated, both experimentally and theoretically, the architecture of extrinsic noise and its causal factors [14,15,16,19,25,26,27], though substantial uncertainty surrounds the importance of individual contributions (such as variability in cell cycle stage and cellular volume) to extrinsic noise [28]
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