High-resolution view of bacteriophage lambda gene expression by ribosome profiling

Liu, Xiaoqiu; Jiang, Huifeng; Gu, Zhenglong; Roberts, Jeffrey W.

doi:10.1073/pnas.1309739110

Cited by 111 publications

(101 citation statements)

References 26 publications

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“…in I [ {LT, T pR 0 }, and kT pR 0 l is taken to be 15 min [29,30]. As T pR 0 variation only accounts for a small fraction of LT variability [34,35] As we ignore T pR 0 variation in these calculations, the reported values for CV 2 FPT are an upper bound.…”

Section: Connecting Lysis Time To First-passage Timementioning

confidence: 99%

Stochastic holin expression can account for lysis time variation in the bacteriophageλ

Singh

Dennehy

2014

J. R. Soc. Interface.

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The inherent stochastic nature of biochemical processes can drive differences in gene expression between otherwise identical cells. While cell-to-cell variability in gene expression has received much attention, randomness in timing of events has been less studied. We investigate event timing at the single-cell level in a simple system, the lytic pathway of the bacterial virus phage l. In individual cells, lysis occurs on average at 65 min, with an s.d. of 3.5 min. Interestingly, mutations in the lysis protein, holin, alter both the lysis time (LT) mean and variance. In our analysis, LT is formulated as the first-passage time (FPT) for cellular holin levels to cross a critical threshold. Exact analytical formulae for the FPT moments are derived for stochastic gene expression models. These formulae reveal how holin transcription and translation efficiencies independently modulate the LT mean and variation. Analytical expressions for the LT moments are used to evaluate previously published single-cell LT data for l phages with mutations in the holin sequence or its promoter. Our results show that stochastic holin expression is sufficient to account for the intercellular LT differences in both wild-type phages, and phage variants where holin transcription and the threshold for lysis have been experimentally altered. Finally, our analysis reveals regulatory motifs that enhance the robustness of lysis timing to cellular noise.

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Section: Connecting Lysis Time To First-passage Timementioning

confidence: 99%

Stochastic holin expression can account for lysis time variation in the bacteriophageλ

Singh

Dennehy

2014

J. R. Soc. Interface.

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“…Profiling has proven to be increasingly valuable in studies of the translation process, for example, in the discovery of novel open reading frames (ORFs), the determination of elongation rates, the identification of sites of ribosome pausing and in the study of protein folding (for review, see Morris 2009;Weiss and Atkins 2011;Michel and Baranov 2013;Ingolia 2014;Jackson and Standart 2015). It also has broad application in the analysis of global gene expression and has been exploited in studies of infectious diseases (Stern-Ginossar et al 2012, 2015Liu et al 2013;Arias et al 2014;Caro et al 2014;Jensen et al 2014;Muzzey et al 2014;Vasquez et al 2014;Yang et al 2015), cell growth, differentiation and development Huang et al 2013;Lee et al 2013;Stadler and Fire, 2013;Stumpf et al 2013;Subramaniam et al 2013;Baudin-Baillieu et al 2014;Brubaker et al 2014;Duncan and Mata 2014;Gonzalez et al 2014;Hendriks et al 2014;Katz et al 2014;Kronja et al 2014;Schrader et al 2014;Vaidyanathan et al 2014;de Klerk et al 2015), apoptosis (Wiita et al 2013), mitochondrial gene expression and disease (Rooijers et al 2013;Williams et al 2014), cell stress (Gerashenko et al 2012;Labunskyy et al 2014;Zid and O'Shea 2014;Sidrauski et al 2015), cell toxicity …”

Section: Introductionmentioning

confidence: 99%

The use of duplex-specific nuclease in ribosome profiling and a user-friendly software package for Ribo-seq data analysis

Chung

Hardcastle

Jones

et al. 2015

RNA

119

129

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Ribosome profiling is a technique that permits genome-wide, quantitative analysis of translation and has found broad application in recent years. Here we describe a modified profiling protocol and software package designed to benefit more broadly the translation community in terms of simplicity and utility. The protocol, applicable to diverse organisms, including organelles, is based largely on previously published profiling methodologies, but uses duplex-specific nuclease (DSN) as a convenient, species-independent way to reduce rRNA contamination. We show that DSN-based depletion compares favorably with other commonly used rRNA depletion strategies and introduces little bias. The profiling protocol typically produces high levels of triplet periodicity, facilitating the detection of coding sequences, including upstream, downstream, and overlapping open reading frames (ORFs) and an alternative ribosome conformation evident during termination of protein synthesis. In addition, we provide a software package that presents a set of methods for parsing ribosomal profiling data from multiple samples, aligning reads to coding sequences, inferring alternative ORFs, and plotting average and transcript-specific aspects of the data. Methods are also provided for extracting the data in a form suitable for differential analysis of translation and translational efficiency.

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“…TraR | bacterial transcription initiation | RNA polymerase | ppGpp/DksA | F element I t is becoming increasingly clear that small proteins can play important regulatory roles in bacteriophage and bacterial biology (1,2). A case in point is TraR, a 73-amino acid protein encoded in the transfer region operon (tra) of the Escherichia coli conjugative F plasmid (3).…”

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confidence: 99%

TraR directly regulates transcription initiation by mimicking the combined effects of the global regulators DksA and ppGpp

Gopalkrishnan

Ross

Chen

et al. 2017

Proc. Natl. Acad. Sci. U.S.A.

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The Escherichia coli F element-encoded protein TraR is a distant homolog of the chromosome-encoded transcription factor DksA. Here we address the mechanism by which TraR acts as a global regulator, inhibiting some promoters and activating others. We show that TraR regulates transcription directly in vitro by binding to the secondary channel of RNA polymerase (RNAP) using interactions similar, but not identical, to those of DksA. Even though it binds to RNAP with only slightly higher affinity than DksA and is only half the size of DksA, TraR by itself inhibits transcription as strongly as DksA and ppGpp combined and much more than DksA alone. Furthermore, unlike DksA, TraR activates transcription even in the absence of ppGpp. TraR lacks the residues that interact with ppGpp in DksA, and TraR binding to RNAP uses the residues in the β′ rim helices that contribute to the ppGpp binding site in the DksA–ppGpp–RNAP complex. Thus, unlike DksA, TraR does not bind ppGpp. We propose a model in which TraR mimics the effects of DksA and ppGpp together by binding directly to the region of the RNAP secondary channel that otherwise binds ppGpp, and its N-terminal region, like the coiled-coil tip of DksA, engages the active-site region of the enzyme and affects transcription allosterically. These data provide insights into the function not only of TraR but also of an evolutionarily widespread and diverse family of TraR-like proteins encoded by bacteria, as well as bacteriophages and other extrachromosomal elements.

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High-resolution view of bacteriophage lambda gene expression by ribosome profiling

Cited by 111 publications

References 26 publications

Stochastic holin expression can account for lysis time variation in the bacteriophageλ

Stochastic holin expression can account for lysis time variation in the bacteriophageλ

The use of duplex-specific nuclease in ribosome profiling and a user-friendly software package for Ribo-seq data analysis

TraR directly regulates transcription initiation by mimicking the combined effects of the global regulators DksA and ppGpp

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