Large-scale mRNA translation and the intricate effects of competition for the finite pool of ribosomes

Jain, Aditi; Margaliot, Michael; Gupta, Arvind Kumar

doi:10.1098/rsif.2022.0033

Cited by 11 publications

(13 citation statements)

References 57 publications

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“…Several mathematical models for the translation process have been described, and they include the TASEP model, the Ribosome Flow Model (RFM) and their variants 45,46,[64][65][66][67] . Totally Asymmetric Simple Exclusion Process or TASEP model assumes that an mRNA molecule is a one-dimensional lattice through which a ribosome can hop in only one direction from one site to the next, provided the latter is empty.…”

Section: Mathematical Model Of Translation At Single Mrna Level For C...mentioning

confidence: 99%

Ribosome demand links transcriptional bursts to protein expression noise

Pal,

Ray,

Dhar

2023

Preprint

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Stochastic variation in protein expression generates phenotypic heterogeneity in a cell population, and has important role in antibiotic persistence, mutation penetrance, cancer growth and therapy resistance. Studies investigating molecular origins of noise have predominantly focused on the transcription process. However, the noise generated during the transcription process is further modulated by the translation process, which eventually determines the expression noise at the protein level. Studies across different organisms have revealed a positive correlation between translational efficiency and protein noise. However, the molecular basis of this correlation has remained unknown. In this work, through stochastic modeling of translation in single mRNA molecules and empirical measurement of protein noise, we demonstrate that ribosome demand associated with high translational efficiency drives the correlation between translational efficiency and protein noise. We also show that this correlation is present only in genes with bursty transcription, where ribosome demand varies with stochastic fluctuations in mRNA numbers. Thus, our work reveals how transcriptional bursts are translated into protein noise, which has important implications for investigating protein noise and phenotypic heterogeneity across biological systems.

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Section: Mathematical Model Of Translation At Single Mrna Level For C...mentioning

confidence: 99%

Ribosome demand links transcriptional bursts to protein expression noise

Pal,

Ray,

Dhar

2023

Preprint

View full text Add to dashboard Cite

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“…This proves (20). To prove (21), consider first the case where the number of RFMIOs m is fixed and the total density in the network satisfies s → 0. Recall that q = e z /s, and (19)…”

Section: Proof Of Propositionmentioning

confidence: 99%

“…A generalization of this network, that includes the possibility of ribosome drop-off and attachment at each site along the RFM, was recently suggested in [21]. Simulations of this model showed that ribosome drop-off from an isolated mRNA always decreases the protein production rate, yet in the network ribosome drop-off from a jammed mRNA may increase the total production rate of all the mRNAs, as the drop-off frees ribosomes that enter the pool, and this improves the production rate in the other mRNAs.…”

Section: Introductionmentioning

confidence: 99%

Translation in the cell under fierce competition for shared resources: a mathematical model

Katz

Attias

Tuller

et al. 2022

Preprint

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During the process of translation the mRNAs in the cell "compete" for shared resources like tRNA molecules and ribosomes. This creates an indirect and intricate coupling between the mRNAs. For example, if ribosomal "traffic jams" evolve on some mRNA then the abundance of free ribosomes may decrease leading to lower initiation rates in the other mRNAs. When the shared resources are abundant the coupling between mRNAs due to this competition is weak. However, when the resources are scarce, e.g., when the pool of free ribosomes is starved, the competition may have a dramatic effect on the dynamics of translation in the cell. This scenario may be relevant for example under stress conditions or during a high yield viral infection, where the viral mRNAs "hijack" components of the translation machinery. Fierce competition for shared resources may also take place in synthetic or engineered systems such as cell free systems or in the case of high-throughput heteroglougs gene expression. We study this scenario using a mathematical model that includes a network of m ribosome flow models (RFMs) interconnected via a pool of free ribosomes. Each RFM is a non-linear dynamical model for ribosome flow along a single mRNA molecule, and the interconnection via the pool encapsulates the competition for shared resources. We analyze the case where m is large, i.e., a there is a large number of mRNAs. This implies that many ribosomes are attached to the mRNAs and thus the pool is starved. Our model allows quantitative and qualitative analysis of the network steady state when the pool is starved. Our analysis results show that adding an mRNA to the network always decreases the steady state pool density. This makes sense, as every new mRNA "consumes" ribosomes. We also show that adding an mRNA has an intricate effect on the total protein production in the network: on the one-hand, the new mRNA produces new proteins. On the other-hand, the other mRNAs produce less proteins, as the pool that feeds these mRNAs now has a smaller abundance of ribosomes. Our analysis yields an explicit bound for the total production rate of the network when the number of RFMIOs is very large. In particular, we analyze how the total density of ribosomes in the network bounds the total production rate. This bound demonstrates that when the number of mRNAs increases, the marginal utility of adding another mRNA diminishes, and the total protein production rate saturates to a limiting value. We demonstrate our analysis approach using an example of producing insulin in a cell free system.

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“…A generalization of this network, that includes the possibility of ribosome drop-off and attachment at each site along the RFM, was recently suggested in [ 39 ]. Simulations of this model showed that ribosome drop-off from an isolated mRNA always decreases the protein production rate, yet in the network ribosome drop-off from a jammed mRNA may increase the total production rate of all the mRNAs, as the drop-off frees ribosomes that enter the pool, and this improves the production rate in the other mRNAs.…”

Section: Introductionmentioning

confidence: 99%

Translation in the cell under fierce competition for shared resources: a mathematical model

Katz

Attias

Tuller

et al. 2022

J. R. Soc. Interface.

Self Cite

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During translation, mRNAs ‘compete’ for shared resources. Under stress conditions, during viral infection and also in high-throughput heterologous gene expression, these resources may become scarce, e.g. the pool of free ribosomes is starved, and then the competition may have a dramatic effect on the global dynamics of translation in the cell. We model this scenario using a network that includes m ribosome flow models (RFMs) interconnected via a pool of free ribosomes. Each RFM models ribosome flow along an mRNA molecule, and the pool models the shared resource. We assume that the number of mRNAs is large, so many ribosomes are attached to the mRNAs, and the pool is starved. Our analysis shows that adding an mRNA has an intricate effect on the total protein production. The new mRNA produces new proteins, but the other mRNAs produce less proteins, as the pool that feeds these mRNAs now has a smaller abundance of ribosomes. As the number of mRNAs increases, the marginal utility of adding another mRNA diminishes, and the total protein production rate saturates to a limiting value. We demonstrate our approach using an example of insulin protein production in a cell-free system.

show abstract

Large-scale mRNA translation and the intricate effects of competition for the finite pool of ribosomes

Cited by 11 publications

References 57 publications

Ribosome demand links transcriptional bursts to protein expression noise

Ribosome demand links transcriptional bursts to protein expression noise

Translation in the cell under fierce competition for shared resources: a mathematical model

Translation in the cell under fierce competition for shared resources: a mathematical model

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