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

Huang, Dean; Johnson, Anna E.; Sim, Brandon S.; Lo, Teresa; Merrikh, Houra; Wiggins, Paul A.

doi:10.1101/2022.08.13.503874

Cited by 3 publications

(7 citation statements)

References 65 publications

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“…Furthermore, more insightful information may be within reach based on new high-throughput data and mathematical modeling (Huang et al, 2023;Pflug et al, 2023;Bhat et al, 2023;Le Treut et al, 2021), which can reveal the relationship between initiation and replication dynamics.…”

Section: Discussionmentioning

confidence: 99%

Robust control of replication initiation in the absence of DnaA-ATP ↔ DnaA-ADP regulatory elements inEscherichia coli

Boesen

Charbon

et al. 2022

Preprint

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Replication initiation, especially the widely conserved master initiator protein DnaA, is one of the most well-studied biological problems in bacteria. Specifically, conversion between the ATP and ADP form of DnaA during growth is critical for initiation control. In Escherichia coli, the regulatory elements for conversion have been discovered and extensively characterized over decades. However, they are not widely conserved in bacteria, raising questions on how to generalize the findings in E. coli to other organisms. In this work, we show that the intrinsic ATPase activity of DnaA itself is sufficient for robust and precise initiation control. We constructed and studied E. coli mutants lacking the extrinsic control of either DnaA-ATP → DnaA-ADP (by hda and datA) or DnaA-ADP → DnaA-ATP (by DARS1 and DARS2) at the single-cell and population levels. These cells showed distinct and opposing characteristics in initiation timing, the degree of initiation asynchrony, and cell-to-cell variability. Strikingly, when all four regulatory elements were deleted, E. coli exhibited a near wild-type phenotype, with only mildly increased intrinsic and extrinsic initiation noise. By further characterizing the DnaA variants with increased and decreased ATPase activity, we conclude that DnaA is the only requirement for robust initiation, shedding new evolutionary light on cell-cycle control in bacteria.

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Section: Discussionmentioning

confidence: 99%

Robust control of replication initiation in the absence of DnaA-ATP ↔ DnaA-ADP regulatory elements inEscherichia coli

Boesen

Charbon

et al. 2022

Preprint

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“…For completeness, we provide a derivation of the growth rate with stochastic cell-cycle arrest that we have previously described [29]. Starting from the exponential mean expression for the population growth rate [29]: where k is the population growth rate and is the exponential mean, where T is the stochastic cell cycle duration and E is the expectation operator [29, 40].…”

Section: Methods: Detailed Description Of the Noise Modelmentioning

confidence: 99%

“…is the exponential mean, where T is the stochastic cell cycle duration and E is the expectation operator [29,40]. Let P + be the probability of growth.…”

Section: Growth Rate With Stochastic Arrestmentioning

confidence: 99%

Noise robustness and metabolic load determine the principles of central dogma regulation

Lo,

Choi,

Huang

et al. 2023

Preprint

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Protein expression levels optimize cell fitness: Too low of an expression level of essential proteins slows growth by compromising the function of essential processes, whereas the overexpression of proteins slows growth by increasing the metabolic load. This trade-off naïvely predicts that the cell maximizes its fitness by a Goldilocks principle in which cells express just enough protein for function; however, this strategy neglects the significance of the inherent stochasticity of the gene expression process which leads to significant cell-to-cell variation in protein numbers. How does the cell ensure robust growth in the face of the inherent stochasticity of these central dogma processes? To explore the consequences of noise in the expression of hundreds of essential genes, we build a minimal model where the trade-off between metabolic cost and growth robustness can be analyzed analytically. The model predicts that growth-rate maximization leads to a highly-asymmetric cost-benefit analysis which drives the optimal protein expression levels far above what is required on average, with low-expression essential proteins expressed at more than 10-fold what is required for growth in the typical cell. This robustness mechanism naturally explains the surprisingly strong buffering effect observed in essential protein depletion experiments and leads to a second qualitative prediction: there is a lower floor on the transcription level of essential genes corresponding to one message per cell cycle. We show that nearly all essential, but not non-essential, genes obey this limit in three evolutionarily-divergent model organisms: Escherichia coli, yeast, and human. The model also predicts that the optimal translation efficiency is roughly proportional to message abundance, predicting the observed relation between proteome fraction and message abundance in eukaryotic cells. This optimal translation efficiency predicts a non-canonical scaling of gene expression noise with protein abundance, which we show is observed in yeast. Together, these results reveal that noise robustness and metabolic load determine the global regulatory principles that govern central dogma function.

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“…i.e., the replication speed is inversely proportional to the logarithmic slope of P(x) [22,23]. An advantage of the deterministic assumption is that it leads to a one-to-one correspondence between DNA abundance and local replisome speed thanks to Eq.…”

Section: B Deterministic Limitmentioning

confidence: 99%

“…For example, we recently proposed a stochastic model describing DNA replication in growing E.coli populations [21]. A broader range of bacterial systems have been studied assuming a deterministic replication program [22,23]. Finally, a model of the replication program in budding yeast adopted the working hypothesis that cells in an asynchronous population are at random, uniformly distributed stages in their cell cycle [3].…”

Section: Introductionmentioning

confidence: 99%

Genome replication in asynchronously growing microbial populations

Pflug,

Bhat,

Pigolotti

2023

Preprint

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Biological cells adopt specific programs to replicate their genomes. Information about the replication program of an organism can be obtained by sequencing an exponentially growing cell culture and studying the frequency of DNA fragments as a function of genomic position. However, a quantitative interpretation of this data has been challenging for asynchronously growing cultures. In this paper, we introduce a general theory to predict the abundance of DNA fragments in asynchronously growing cultures from any given stochastic model of the DNA replication program. As key examples, we present stochastic models of DNA replication in Escherichia coli and in budding yeast. In both cases, our approach leads to analytical predictions that are in excellent agreement with experimental data and permit to infer biophysically relevant parameters. In particular, our method is able to infer the locations of known replication origins in budding yeast with high accuracy. These examples demonstrate that our method can provide insight into a broad range of organisms, from bacteria to eukaryotes.

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

Cited by 3 publications

References 65 publications

Robust control of replication initiation in the absence of DnaA-ATP ↔ DnaA-ADP regulatory elements inEscherichia coli

Robust control of replication initiation in the absence of DnaA-ATP ↔ DnaA-ADP regulatory elements inEscherichia coli

Noise robustness and metabolic load determine the principles of central dogma regulation

Genome replication in asynchronously growing microbial populations

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