Characterizing stochastic cell-cycle dynamics in exponential growth

Huang, Dean; Lo, Teresa; Merrikh, Houra; Wiggins, Paul A.

doi:10.1103/physreve.105.014420

“…This marker frequency can be reinterpreted as a measurement of the lag time τ ( ℓ ): where N ( ℓ ) is the observed number of the locus at genomic position ℓ and N 0 is the observed number of the origin in the culture and k G is the growth rate. This relation can be understood as a consequence of the exponential growth law [31].…”

Section: Resultsmentioning

confidence: 99%

“…In reality, the timing of all processes in the cell cycle is stochastic. We previously showed that the measured lag time is related to the distribution of durations in single cells by the exponential mean [31]: where 𝔼 t is the expectation over stochastic time t with distribution t ∼ p i (·).…”

Section: Resultsmentioning

confidence: 99%

“…For a stochastic model with locus-dependent fork velocity, we showed that Eqs. 14 and 15 generalize to where we will call τ ( ℓ ) the lag time of a locus at position ℓ , which is equal to the sum of the differential lag times for each sequential step: where δτ i is the differential lag time for state i or the exponential mean of the state lifetime [31]. In the continuum limit, it is more convenient to represent this sum as an integral: where the fork velocity is defined: v ( ℓ i ) ≡1 bp /δτ i .…”

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

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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“…where N ( ) is the observed number of the locus at genomic position and N 0 is the observed number of the origin in the culture and k G is the growth rate. This relation can be understood as a consequence of the exponential growth law [31].…”

Section: Resultsmentioning

confidence: 99%

“…In reality, the timing of all processes in the cell cycle is stochastic. We previously showed that the measured lag time is related to the distribution of durations in single cells by the exponential mean [31]:…”

Section: Resultsmentioning

confidence: 99%

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

Huang¹,

Johnson²,

Sim³

et al. 2022

Preprint

Self Cite

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.

show abstract

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

Huang

¹

,

Johnson

²

,

Sim

³

et al. 2023

Self Cite

View full text Add to dashboard Cite

An important step towards understanding the mechanistic basis of the central dogma is the quantitative characterization of the dynamics of nucleic-acid-bound molecular motors in the context of the living cell. To capture these dynamics, we develop lag-time analysis, a method for measuring in vivo dynamics. Using this approach, we provide quantitative locus-specific measurements of fork velocity, in units of kilobases per second, as well as replisome pause durations, some with the precision of seconds. The measured fork velocity is observed to be both locus and time dependent, even in wild-type cells. In this work, we quantitatively characterize known phenomena, detect brief, locus-specific pauses at ribosomal DNA loci in wild-type cells, and observe temporal fork velocity oscillations in three highly-divergent bacterial species.

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Characterizing stochastic cell-cycle dynamics in exponential growth

Cited by 8 publications

References 30 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

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

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