skip to main content


Title: Ribosome biogenesis in replicating cells: Integration of experiment and theory
ABSTRACT

Ribosomes—the primary macromolecular machines responsible for translating the genetic code into proteins—are complexes of precisely folded RNA and proteins. The ways in which their production and assembly are managed by the living cell is of deep biological importance. Here we extend a recent spatially resolved whole‐cell model of ribosome biogenesis in a fixed volume [Earnest et al., Biophys J 2015, 109, 1117–1135] to include the effects of growth, DNA replication, and cell division. All biological processes are described in terms of reaction‐diffusion master equations and solved stochastically using the Lattice Microbes simulation software. In order to determine the replication parameters, we construct and analyze a series ofEscherichia colistrains with fluorescently labeled genes distributed evenly throughout their chromosomes. By measuring these cells’ lengths and number of gene copies at the single‐cell level, we could fit a statistical model of the initiation and duration of chromosome replication. We found that for our slow‐growing (120 min doubling time)E. colicells, replication was initiated 42 min into the cell cycle and completed after an additional 42 min. While simulations of the biogenesis model produce the correct ribosome and mRNA counts over the cell cycle, the kinetic parameters for transcription and degradation are lower than anticipated from a recent analytical time dependent model of in vivo mRNA production. Describing expression in terms of a simple chemical master equation, we show that the discrepancies are due to the lack of nonribosomal genes in the extended biogenesis model which effects the competition of mRNA for ribosome binding, and suggest corrections to parameters to be used in the whole‐cell model when modeling expression of the entire transcriptome. © 2016 Wiley Periodicals, Inc. Biopolymers 105: 735–751, 2016.

 
more » « less
NSF-PAR ID:
10236367
Author(s) / Creator(s):
 ;  ;  ;  ;  ;  
Publisher / Repository:
Wiley Blackwell (John Wiley & Sons)
Date Published:
Journal Name:
Biopolymers
Volume:
105
Issue:
10
ISSN:
0006-3525
Format(s):
Medium: X Size: p. 735-751
Size(s):
["p. 735-751"]
Sponsoring Org:
National Science Foundation
More Like this
  1. Computational models of cells cannot be considered complete unless they include the most fundamental process of life, the replication and inheritance of genetic material. By creating a computational framework to model systems of replicating bacterial chromosomes as polymers at 10 bp resolution with Brownian dynamics, we investigate changes in chromosome organization during replication and extend the applicability of an existing whole-cell model (WCM) for a genetically minimal bacterium, JCVI-syn3A, to the entire cell-cycle. To achieve cell-scale chromosome structures that are realistic, we model the chromosome as a self-avoiding homopolymer with bending and torsional stiffnesses that capture the essential mechanical properties of dsDNA in Syn3A. In addition, the conformations of the circular DNA must avoid overlapping with ribosomes identitied in cryo-electron tomograms. While Syn3A lacks the complex regulatory systems known to orchestrate chromosome segregation in other bacteria, its minimized genome retains essential loop-extruding structural maintenance of chromosomes (SMC) protein complexes (SMC-scpAB) and topoisomerases. Through implementing the effects of these proteins in our simulations of replicating chromosomes, we find that they alone are sufficient for simultaneous chromosome segregation across all generations within nested theta structures. This supports previous studies suggesting loop-extrusion serves as a near-universal mechanism for chromosome organization within bacterial and eukaryotic cells. Furthermore, we analyze ribosome diffusion under the influence of the chromosome and calculatein silicochromosome contact maps that capture inter-daughter interactions. Finally, we present a methodology to map the polymer model of the chromosome to a Martini coarse-grained representation to prepare molecular dynamics models of entire Syn3A cells, which serves as an ultimate means of validation for cell states predicted by the WCM.

     
    more » « less
  2. Degradation of most yeast mRNAs involves decapping by Dcp1/Dcp2. DEAD-box protein Dhh1 has been implicated as an activator of decapping, in coupling codon non-optimality to enhanced degradation, and as a translational repressor, but its functions in cells are incompletely understood. RNA-Seq analyses coupled with CAGE sequencing of all capped mRNAs revealed increased abundance of hundreds of mRNAs indcp2Δ cells that appears to result directly from impaired decapping rather than elevated transcription. Interestingly, only a subset of mRNAs requires Dhh1 for targeting by Dcp2, and also generally requires the other decapping activators Pat1, Edc3, or Scd6; whereas most of the remaining transcripts utilize nonsense-mediated mRNA decay factors for Dcp2-mediated turnover. Neither inefficient translation initiation nor stalled elongation appears to be a major driver of Dhh1-enhanced mRNA degradation. Surprisingly, ribosome profiling revealed thatdcp2Δ confers widespread changes in relative translational efficiencies (TEs) that generally favor well-translated mRNAs. Because ribosome biogenesis is reduced while capped mRNA abundance is increased bydcp2Δ,we propose that an increased ratio of mRNA to ribosomes increases competition among mRNAs for limiting ribosomes to favor efficiently translated mRNAs indcp2Δ cells. Interestingly, genes involved in respiration or utilization of alternative carbon or nitrogen sources are upregulated, and both mitochondrial function and cell filamentation are elevated indcp2Δ cells, suggesting that decapping sculpts gene expression post-transcriptionally to fine-tune metabolic pathways and morphological transitions according to nutrient availability.

     
    more » « less
  3. Bradford, Patricia A. (Ed.)
    ABSTRACT

    Efflux and motility are two key biological functions in bacteria. Recent findings have shown that efflux impacts flagellum biosynthesis and motility inEscherichia coliand other bacteria. AcrR is known to be the major transcriptional repressor of AcrAB-TolC, the main multidrug efflux pump inE. coliand otherEnterobacteriaceae. However, the underlying molecular mechanisms of how efflux and motility are co-regulated remain poorly understood. Here, we have studied the role of AcrR in direct regulation of motility inE. coli. By combining bioinformatics, electrophoretic mobility shift assays (EMSAs), gene expression, and motility experiments, we have found that AcrR represses motility inE. coliby directly repressing transcription of theflhDCoperon, but not the other flagellum genes/operons tested.flhDCencodes the master regulator of flagellum biosynthesis and motility genes. We found that such regulation primarily occurs by direct binding of AcrR to theflhDCpromoter region containing the first of the two predicted AcrR-binding sites identified in this promoter. This is the first report of direct regulation by AcrR of genes unrelated to efflux or detoxification. Moreover, we report that overexpression of AcrR restores to parental levels the increased swimming motility previously observed inE. colistrains without a functional AcrAB-TolC pump, and that such effect by AcrR is prevented by the AcrR ligand and AcrAB-TolC substrate ethidium bromide. Based on these and prior findings, we provide a novel model in which AcrR senses efflux and then co-regulates efflux and motility inE. colito maintain homeostasis and escape hazards.

    IMPORTANCE

    Efflux and motility play a major role in bacterial growth, colonization, and survival. InEscherichia coli, the transcriptional repressor AcrR is known to directly repress efflux and was later found to also repress flagellum biosynthesis and motility by Kim et al. (J Microbiol Biotechnol 26:1824–1828, 2016, doi: 10.4014/jmb.1607.07058). However, it remained unknown whether AcrR represses flagellum biosynthesis and motility directly and through which target genes, or indirectly because of altering the amount of efflux. This study reveals that AcrR represses flagellum biosynthesis and motility by directly repressing the expression of theflhDCmaster regulator of flagellum biosynthesis and motility genes, but not the other flagellum genes tested. We also show that the antimicrobial, efflux pump substrate, and AcrR ligand ethidium bromide regulates motility via AcrR. Overall, these findings support a novel model of direct co-regulation of efflux and motility mediated by AcrR in response to stress inE. coli.

     
    more » « less
  4. null (Ed.)
    Abstract Background Cotton fibers provide a powerful model for studying cell differentiation and elongation. Each cotton fiber is a singular and elongated cell derived from epidermal-layer cells of a cotton seed. Efforts to understand this dramatic developmental shift have been impeded by the difficulty of separation between fiber and epidermal cells. Results Here we employed laser-capture microdissection (LCM) to separate these cell types. RNA-seq analysis revealed transitional differences between fiber and epidermal-layer cells at 0 or 2 days post anthesis. Specifically, down-regulation of putative cell cycle genes was coupled with upregulation of ribosome biosynthesis and translation-related genes, which may suggest their respective roles in fiber cell initiation. Indeed, the amount of fibers in cultured ovules was increased by cell cycle progression inhibitor, Roscovitine, and decreased by ribosome biosynthesis inhibitor, Rbin-1. Moreover, subfunctionalization of homoeologs was pervasive in fiber and epidermal cells, with expression bias towards 10% more D than A homoeologs of cell cycle related genes and 40–50% more D than A homoeologs of ribosomal protein subunit genes. Key cell cycle regulators were predicted to be epialleles in allotetraploid cotton. MYB-transcription factor genes displayed expression divergence between fibers and ovules. Notably, many phytohormone-related genes were upregulated in ovules and down-regulated in fibers, suggesting spatial-temporal effects on fiber cell development. Conclusions Fiber cell initiation is accompanied by cell cycle arrest coupled with active ribosome biosynthesis, spatial-temporal regulation of phytohormones and MYB transcription factors, and homoeolog expression bias of cell cycle and ribosome biosynthesis genes. These valuable genomic resources and molecular insights will help develop breeding and biotechnological tools to improve cotton fiber production. 
    more » « less
  5. Nucleolar stress occurs when ribosome production or function declines. Nucleolar stress in stem cells or progenitor cells often leads to disease states called ribosomopathies. Drosophila offers a robust system to explore how nucleolar stress causes cell cycle arrest, apoptosis, or autophagy depending on the cell type. We provide an overview of nucleolar stress in Drosophila by depleting nucleolar phosphoprotein of 140 kDa (Nopp140), a ribosome biogenesis factor (RBF) in nucleoli and Cajal bodies (CBs). The depletion of Nopp140 in eye imaginal disc cells generates eye deformities reminiscent of craniofacial deformities associated with the Treacher Collins syndrome (TCS), a human ribosomopathy. We show the activation of c-Jun N-terminal Kinase (JNK) in Drosophila larvae homozygous for a Nopp140 gene deletion. JNK is known to induce the expression of the pro-apoptotic Hid protein and autophagy factors Atg1, Atg18.1, and Atg8a; thus, JNK is a central regulator in Drosophila nucleolar stress. Ribosome abundance declines upon Nopp140 loss, but unusual cytoplasmic granules accumulate that resemble Processing (P) bodies based on marker proteins, Decapping Protein 1 (DCP1) and Maternal expression at 31B (Me31B). Wild type brain neuroblasts (NBs) express copious amounts of endogenous coilin, but coilin levels decline upon nucleolar stress in most NB types relative to the Mushroom body (MB) NBs. MB NBs exhibit resilience against nucleolar stress as they maintain normal coilin, Deadpan, and EdU labeling levels. 
    more » « less