Speed variations of bacterial replisomes

Bhat, Deepak; Hauf, Samuel; Plessy, Charles; Yokobayashi, Yohei; Pigolotti, Simone

doi:10.7554/elife.75884

“…Importance of a model-independent approach. As we prepared this manuscript, we became aware of a competing group which also uses marker-frequency analysis to test a specific hypothesis: the fork velocity is oscillatory in E. coli [15], consistent with our own observations. Although our reports share some conclusions, this competing approach requires detailed models for the cell cycle and the fork velocity, along with explicit stochastic simulations.…”

Section: Discussionsupporting

confidence: 70%

“…Ref. [15] has also argued that this oscillating-dNTP-level model would lead to time-dependent oscillations in the mutation rate which are consistent with the origin-mirror-symmetric distribution of the mutation observed in E. coli. However, this interesting phenomenon and this hypothesized mechanism will require further investigation.…”

Section: Systematic Error In Datasetsmentioning

confidence: 55%

The high-resolution in vivo measurement of replication fork velocity and pausing by lag-time analysis

Huang

¹

,

Johnson

²

,

Sim

³

et al. 2022

Preprint

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An important step towards understanding the replication process in the context of the cell is the quantitative characterization of replication dynamics, including the rate of replication fork progression (i.e. fork velocity) with genomic and temporal specificity in vivo. In this paper, we develop a novel method, lag-time analysis, for measuring replisome dynamics using next-generation sequencing. We provide the first quantitative locus-specific measurements of fork velocity. The measured velocity is observed to be both locus and time dependent, even in wild-type cells. To benchmark the approach, we analyze replication dynamics in three different species and a collection of mutants which facilitate the quantitative characterization of replication-conflict-induced fork slowdowns as well as a host of other replication dynamics phenomena, including the observation of temporal fork velocity oscillation. With increases in sequencing depth and improvements in sample preparation, the approach has the potential to provide new insights at higher genomic resolution and in a wide range of biological systems.

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“…Importance of a model-independent approach. As we prepared this manuscript, we became aware of a competing group which also uses marker-frequency analysis to test a specific hypothesis: the fork velocity is oscillatory in E. coli [47], consistent with our own observations. Although our reports share some conclusions, this competing approach requires explicit stochastic simulations to test a detailed hypothesis and it is unclear from this approach whether the conclusions are model independent.…”

Section: Discussionsupporting

confidence: 70%

“…Ref. [47] has also argued that this oscillating-dNTP-level model would lead to time-dependent oscillations in the mutation rate which are consistent with the origin-mirror-symmetric distribution of the mutation observed in E. coli. However, this interesting phenomenon and this hypothesized mechanism will require further investigation.…”

Section: Systematic Error In Datasetsmentioning

confidence: 55%

The high-resolution in vivo measurement of replication fork velocity and pausing

Huang¹,

Johnson²,

Sim³

et al. 2022

Preprint

0

View full text Add to dashboard Cite

An important step towards understanding the replication process in the context of the cell is the quantitative characterization of replication dynamics, including the rate of replication fork progression (i.e. fork velocity) with genomic and temporal specificity in vivo. In this paper, we develop a novel method, lag-time analysis, for measuring replisome dynamics using next-generation sequencing. We provide the first quantitative locus-specific measurements of fork velocity. The measured velocity is observed to be both locus and time dependent, even in wild-type cells. To benchmark the approach, we analyze replication dynamics in three different species and a collection of mutants which facilitate the quantitative characterization of replication-conflict-induced fork slowdowns as well as a host of other replication dynamics phenomena, including the observation of temporal fork velocity oscillation. With increases in sequencing depth and improvements in sample preparation, the approach has the potential to provide new insights at higher genomic resolution and in a wide-range of biological systems.

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“…We uncovered a temperature-dependent growth law for yeast by examining the temperature-dependent quantitative relationships among the rates of genome-wide transcription, protein synthesis, and cell proliferation (Supplementary Discussion). These relationships have been unclear despite previous studies having examined how temperature affects specific genes in microbes 6 , 37 – 40 . We discovered how slowly gene-expression machineries can function and how their slow functioning constrains the cell-cycling pace.…”

Section: Discussionmentioning

confidence: 99%

Slowest possible replicative life at frigid temperatures for yeast

Trip

¹

,

Maire

²

,

Youk

³

2022

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Determining whether life can progress arbitrarily slowly may reveal fundamental barriers to staying out of thermal equilibrium for living systems. By monitoring budding yeast’s slowed-down life at frigid temperatures and with modeling, we establish that Reactive Oxygen Species (ROS) and a global gene-expression speed quantitatively determine yeast’s pace of life and impose temperature-dependent speed limits - shortest and longest possible cell-doubling times. Increasing cells’ ROS concentration increases their doubling time by elongating the cell-growth (G1-phase) duration that precedes the cell-replication (S-G2-M) phase. Gene-expression speed constrains cells’ ROS-reducing rate and sets the shortest possible doubling-time. To replicate, cells require below-threshold concentrations of ROS. Thus, cells with sufficiently abundant ROS remain in G1, become unsustainably large and, consequently, burst. Therefore, at a given temperature, yeast’s replicative life cannot progress arbitrarily slowly and cells with the lowest ROS-levels replicate most rapidly. Fundamental barriers may constrain the thermal slowing of other organisms’ lives.

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Speed variations of bacterial replisomes

Cited by 13 publications

References 42 publications

The high-resolution in vivo measurement of replication fork velocity and pausing by lag-time analysis

The high-resolution in vivo measurement of replication fork velocity and pausing by lag-time analysis

The high-resolution in vivo measurement of replication fork velocity and pausing

Slowest possible replicative life at frigid temperatures for yeast

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