Skip to main page content
U.S. flag

An official website of the United States government

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2011 Jun 10;145(6):981-92.
doi: 10.1016/j.cell.2011.05.013.

Metazoan operons accelerate recovery from growth-arrested states

Alon Zaslaver  1 , L Ryan Baugh, Paul W Sternberg
Affiliations

Metazoan operons accelerate recovery from growth-arrested states

Alon Zaslaver et al. Cell. .

Abstract

Existing theories explain why operons are advantageous in prokaryotes, but their occurrence in metazoans is an enigma. Nematode operon genes, typically consisting of growth genes, are significantly upregulated during recovery from growth-arrested states. This expression pattern is anticorrelated to nonoperon genes, consistent with a competition for transcriptional resources. We find that transcriptional resources are initially limiting during recovery and that recovering animals are highly sensitive to any additional decrease in transcriptional resources. We provide evidence that operons become advantageous because, by clustering growth genes into operons, fewer promoters compete for the limited transcriptional machinery, effectively increasing the concentration of transcriptional resources and accelerating recovery. Mathematical modeling reveals how a moderate increase in transcriptional resources can substantially enhance transcription rate and recovery. This design principle occurs in different nematodes and the chordate C. intestinalis. As transition from arrest to rapid growth is shared by many metazoans, operons could have evolved to facilitate these processes.

PubMed Disclaimer

Figures

Figure 1
Figure 1. Expression profile of operon genes is anti-correlated to the expression profile of operon genes
(A) The lifecycle of free-living nematodes (e.g., C. elegans) consist of four larval stages followed by an adult stage. If unfavorable conditions arise during larval development worms stop growing and arrest at the L1 state, or proceed through L2d stage into dauer, a highly-resistant and long-lived state. When conditions improve the worms recover and resume normal development. Fast growing stages are denoted by green arrows. The red arrow marks the first divisions of the egg, a process characterized by fine-regulation rather than rapid growth and mass accumulation. Red rectangles indicate a growth arrested state. (Inset) The average expression levels of operon genes are higher compared to non-operon genes. The higher expression level is consistent throughout all developmental stages. Average expression levels calculated based on microarray data obtained from http://elegans.bcgsc.bc.ca/. Emb, embryo; YA, young adult. (B-E) Expression patterns of operon genes (blue) and non-operon genes (red). Bootstrap analysis is in black. a set of random genes (with the same number of operon genes as that included in the data set) was pooled from the total set of genes (including operon genes) and their average calculated. This process was iterated 1,000 times, and the average is plotted with error bars (s.e.m). (B) Time-series during recovery from L1 arrest. (C) Time-series during recovery from dauer state. (D) Time-series following hatching. (E) Time-series during early embryogenesis. See also Table S1 and Fig S1-S3.
Figure 2
Figure 2. Growth arrested worms have low levels of transcriptional resources and are therefore sensitive to any further reduction
(A,C) Many genes associated with transcriptional machinery are found at lower levels (~50%) during growth arrest when compared to their levels in non-arrested worms (Wang and Kim, 2003); in particular (A) during dauer arrest and (C) during L1 arrest. Shown are the genes that are at most 75% of maximum levels. Many other transcriptional machinery genes are found at moderately lower levels. (B,D) Expression of many transcriptional machinery genes is significantly increased upon recovery. (B) Fold change in expression levels following dauer recovery. (D) Fold change in expression levels following recovery from L1 arrest. Fold change is calculated as the ratio between the mean expressions during 3-5 hrs of recovery to the mean expression during the first 1.5 hrs of recovery. Note that while the average increase in expression levels for all operon genes is ~20% expression levels of many transcriptional genes is increased by 100% and more. The list of transcriptional machinery genes is based on (Blackwell and Walker, 2006).
Figure 3
Figure 3. Clustering genes into operons is beneficial when transcriptional resources are limiting
An illustration demonstrating how operons become advantageous for successful transcription when transcriptional resources are limited. Assume there is a fixed amount of transcriptional resources (for example, 2 RNA Pol II, 2 mediator complexes and 4 TAF complexes) in the cell and that a functional transcriptional initiation complex requires half of these resources (1 RNA Pol II, 1 mediator and 2 TAFs). Suppose also there are three growth genes required to be expressed in high levels. (A) The three genes are on separate monocistronic units each having its own promoter. In this case the probability to form a functional transcriptional initiation complex is low as transcriptional resources are stochastically distributed among the different binding sites of the different promoters. (B) The three genes are on the same operon regulated by a single shared promoter. In this case, the number of potential biding sites competing for transcriptional resources is reduced by three fold. This effectively increases the concentration of the transcriptional resources increasing the probability to form productive transcriptional initiation complex.
Figure 4
Figure 4. A model based on Hill–function analysis demonstrating that a moderate increase or decrease in transcriptional resources can lead to recovery or death
(A) Heat map showing the fold increase in transcription rate obtained if levels of transcriptional machinery are increased by 20%. Considerable enhancement in transcription rate is found for a wide range of possible values of transcriptional machinery levels (TM/K) and Hill-coefficient values (n). (B) Heat map demonstrating that response time and recovery are very sensitive to initial levels of transcription machinery. The upper-left blue area indicates that recovery is impossible. A sharp, high boundary is found for intermediate levels of transcriptional machinery. Thus, any small increase in the levels of the transcriptional machinery can push the animals from the no recovery regime to the recovery and growth regime. Note that the maximal possible increase in transcription rate (A) is obtained at the ‘poor’ no recovery area shown in blue in (B). See also Fig S6.
Figure 5
Figure 5. Recovery of arrested worms is significantly impaired by reduced levels of transcriptional components
Deletion mutants lacking transcriptional machinery components were analyzed for their growth rate during normal growth and during recovery from L1 arrest. Growth rates were calculated based on the first ~30 hours following recovery, or during the first ~30 hours of non-arrested growing L1 larvae (indicated by the gray-shadowed area). (A-B) An example of growth curves (measuring length of the worms) over ~80 hrs following: (A) hatching into non-arresting conditions, or (B) following recovery from L1 arrest. The three strains given as an example are: taf-9(ok2871), wild type (N2), and a control strain gpa-16(ok2349), defective in a non transcriptional-related gene. (C-E) Three experimental repeats measuring the relative growth rates of the different deletion mutants: (C) taf-9(ok2871) and gpa-16(ok2349). (D) Cyclin C (tm3740) and the control srbc-58(tm3893), a serpentine receptor. (E) Cyclin T (gk316), taf-11.2(gk682), and the control miR-84(gk473). Relative growth rates were calculated by taking the ratio between the growth rates of the mutants and the growth rate of N2 (wild type), which was included in each of the growth experiments. Error bars indicate standard error of the mean. P-values are based on t-tests. Each time point is the mean of ~100 worms.
Figure 6
Figure 6. Recovery of arrested worms is significantly impaired by reduced levels of RNA Pol II
Growth rate of wild-type (N2) worms was measured in the presence of RNA Pol II inhibitor α-amanitin. (A) Growth curves in non-arresting conditions from L1 stage to adults. (B) Growth curves of arrested L1 worms following recovery. At time zero arrested L1 larvae were washed and allowed to recover in the presence of the indicated levels of α-amanitin. At the same time actively growing L1 larvae were treated with the same concentrations of α–amanitin. (C) Summary of three repeats measuring relative growth rates in the presence of α-amanitin. Growth rates were calculated by averaging growth during the first ~30 hrs following the addition of α-amanitin (indicated by the gray-shadowed area). Relative growth rates are the ratio between growth rates in the presence of α-amanitin and the absence of α-amanitin. Error bars indicate standard error of the mean. P-values are based on t-tests. Each time point is the mean of ~100 worms.
Figure 7
Figure 7. Various metazoans contain operons that are enriched with growth genes and may promote rapid recovery form developmental arrested states
(A) Lifecycle of the parasitic nematode B. malayi. B. malayi passages between mosquitoes, which serve as vectors, and humans, the infected hosts. Microfilaria arrest as L1s in the human bloodstream. They are then taken by feeding mosquitoes where they recover and develop until they arrest in the L3 stage. The next time mosquitoes feed on human blood the L3 arrested worms are transmitted to the bloodstream where they recover and resume growth until they reach adult stage and produce progeny (microfilaria). Red rectangles denote growth arrested states. (B) Operon genes in B. malayi and P. pacificus typically comprise growth related genes. P-values are calculated by hyper geometric test (HGT) performed on GO annotations (WS190). Included are GO annotations that contain more than 200 genes. Bootstrap analysis verified that the set of genes in GO annotations is not biased to contain preferentially growth related genes. Data are clustered using hierarchical clustering algorithm (euclidean distances, average linkage). (C) Microarray time-series during the lifecycle of Ciona intestinalis. Average expression of operon genes is in blue, and average expression of non-operon genes is in red. For bootstrap analysis (black) a set of random genes (with the same number of operon genes included in the data set) was pooled from the total set of genes (including operon genes) and their average was calculated. This process was iterated 1,000 times and the average is plotted with error bars (s.e.m). Since expression of operon genes ranges much widely than expression of non-operon genes, the two expression profiles were normalized (inset). Notations used: 2-cell, 4-cell…64-cell embryos; EG – early gastrula; LG – late gastrula; EN – early neurula; ITB – initial tailbud; MTB middle tailbud; LTB – late tailbud; LV – early larvae; JN – juvenile; 1.5M – 1.5 months-old adults etc. See also Fig S7.
See this image and copyright information in PMC

Comment in

Similar articles

See all similar articles

Cited by

See all "Cited by" articles

References

    1. Abad P, Gouzy J, Aury JM, Castagnone-Sereno P, Danchin EG, Deleury E, Perfus-Barbeoch L, Anthouard V, Artiguenave F, Blok VC, et al. Genome sequence of the metazoan plant-parasitic nematode Meloidogyne incognita. Nat Biotechnol. 2008;26:909–915. - PubMed
    1. Alon U. An Introduction to Systems Biology: Design Principles of Biological Circuits. CRC press; 2006. 2007.
    1. Azumi K, Sabau SV, Fujie M, Usami T, Koyanagi R, Kawashima T, Fujiwara S, Ogasawara M, Satake M, Nonaka M, et al. Gene expression profile during the life cycle of the urochordate Ciona intestinalis. Dev Biol. 2007;308:572–582. - PubMed
    1. Barriere A, Felix MA. High local genetic diversity and low outcrossing rate in Caenorhabditis elegans natural populations. Curr Biol. 2005;15:1176–1184. - PubMed
    1. Baugh LR, DeModena J, Sternberg PW. RNA Pol II Accumulates at Promoters of Growth Genes During Developmental Arrest in C. elegans. Science. 2009;324:92–94. - PubMed

Publication types