These results have changed how we think about the clock, shifting away from a linear model to one in which the clock is viewed as an interactive network of multifunctional components that are integrated into the context of the cell in order to pace and reset the oscillator. We conclude with a discussion of how this basic timekeeping mechanism differs in other cyanobacterial species and how information gleaned from work in cyanobacteria can be translated to understanding rhythmic phenomena in other prokaryotic systems.
All Rights Reserved. The main components of the input pathway in S. CikA senses light and dark from the environment through the direct interaction with quinone molecules whose redox state depends on light and the metabolic redox state of the bacteria Ivleva et al. Co-purification assays showed that in addition to the Kai proteins CikA and LdpA form part of the periodosome the heteromultimeric complex necessary to sustain circadian rhythms; Golden, together with a protein of the output pathway named SasA Ivleva et al.
LdpA entrains the clock with the intensity of the light through sensing the changes in electron transport and molecules like O 2 or reactive oxygen species Ivleva et al. The LdpA protein contains an HcyB domain and two specific, conserved terminal domains and belongs to the ferredoxin family of proteins Katayama et al.
In contrast ldpA mutants show a conditional alteration in the circadian period as compared to the wild type due to an insensitivity to light gradient that normally modulates the circadian period resulting in a lengthening of the period at low light intensities.
Thus the LdpA protein seems to modulate the circadian clock as an indirect function of light intensity by sensing changes in cellular physiology Katayama et al. Another protein involved in the input pathway is Pex period-extender a transcriptional repressor of KaiA Kutsuna et al. Constitutive expression of pex leads to a prolongation of the circadian period to 28 h.
In contrast cells lacking pex , show a 1-h shorter circadian period due to the increase of KaiA that leads to a faster phosphorylation of KaiC Kutsuna et al. KaiC is the central oscillatory protein. KaiC is the only of the three proteins with enzymatic activity. It was reported to function as kinase, autophosphorylase, and ATPase Nishiwaki et al. Indeed, self-sustainable oscillation of KaiC phosphorylation could be reconstituted in vitro by incubating KaiC with KaiA, KaiB, and adenosine triphosphate.
The period of the in vitro oscillation was stable despite temperature change, and the circadian periods observed in vivo in KaiC mutant strains were consistent with those measured in vitro Nakajima et al. The KaiC phosphorylation state persists in absence of transcriptional feedback and protein synthesis Tomita et al.
KaiA forms a homodimer that interacts directly with hexamers of KaiC by binding at the C-terminal tail Kim et al. This interaction stimulates its phosphorylation and inhibits dephosphorylation steps whereas tetramers of KaiB antagonize the effects of KaiA Xu et al.
In the in vitro system, Kai protein complexes assemble and disassemble dynamically over the KaiC phosphorylation cycle Kageyama et al. In the initial step hexamers of KaiC are in unphosphorylated form. Finally, KaiC appears monophosphorylated at residue S, dissociates from KaiB and the cycle starts a new Nishiwaki et al.
Recently a third phosphorylation site, a threonine residue at position 42, has been reported to also be important to maintain rhythmicity Xu et al. The phosphorylation state of the oscillator has been proposed as the pacemaker of the circadian clock, but there is evidence that circadian gene expression persists also when the phosphorylation cycle is disrupted Kitayama et al.
Phosphorylation phase and ATPase activity levels of the oscillator complex determine the information transmitted to the downstream transcriptional regulatory system Nishiwaki et al. This regulatory system is constituted of the SasA Synechococcus adaptive sensor A -RpaA regulator of phycobilisome-associated two-component system Takai et al.
Consequently the target genes of RpaA can be activated or repressed in a circadian manner. Thus the KaiC-SasA-RpaA interaction is so far the major positive pathway known to regulate the circadian shift in gene expression Takai et al. Null mutants of rpaA show arrhythmia under continues light conditions Takai et al. An alternative output pathway by which the circadian clock modulates circadian gene expression is LabA low-amplitude and bright.
LabA is needed for negative feedback regulation of KaiC Taniguchi et al. Mutants in labA increase the levels of circadian gene expression due to the high levels of non-regulated-KaiC resulting in a low amplitude phenotype. In contrast, labA overexpression results in low circadian gene expression Taniguchi et al. Furthermore, it has been suggested that the LabA pathway is implicated in chromosomal compaction Woelfle et al.
RpaA is situated downstream in this cascade to generate the robust modulation of circadian gene expression Kondo, Figure 1. Many efforts have been undertaken to decipher the biochemical basis of the oscillatory machinery and the pathways it controls. However, most approaches have been based on genetics, as it is not easy to predict and model the biochemical processes for such a complex mechanism.
Thus, mainly mutants that target a component gene of the clock machinery have been analyzed to infer their possible roles and their involvement in the circadian clock. Most of the knowledge about the cellular processes that the circadian clock gates comes from alterations in such cellular functional pathways as result of the mutation of one clock component or by determining the rhythmicity of cellular processes.
One of the first physiological evidence that suggested the presence of circadian clock mechanisms in cyanobacteria was the observation that nitrogen fixation onset occurs in a rhythmic way Grobbelaar et al. Apart from photosynthesis and nitrogen fixation, circadian clocks regulate amino acid uptake Chen et al. Circadian expression in S.
Liu et al. Many mechanisms that impact the functioning of the cell and how they make the circadian clock work, remain to be discovered and deciphered, but new parts in the puzzle are added constantly. For example it was known for many years that the circadian clock gates the cell cycle process but the mechanisms that allow this phenomenon were unknown Mori et al.
However, very recently Dong et al. Then, the signal downstream is transmitted through the SasA-RpaA pathway and it results in the inhibition of the midcell FtsZ ring assembly, blocking cell division until the levels of ATPase activity decrease Dong et al. The biological implication of the circadian checkpoint in cell division may impact in different ways by protecting other cellular functions that can be damaged as result of cell division in vulnerable conditions Dong et al.
It is important to notice that in S. In addition, DNA replication also remains constant during the circadian cycle suggesting that the most evident target is cytokinesis Mori et al. Much knowledge to better understand the biological significance of the circadian clock gating different cell functions has been gained in the last years, but further studies are needed to complete our understanding of the impact of the prokaryotic circadian clock on the global physiology of the cell and research should be expanded on putative circadian clocks of other prokaryotes.
Considering that the biochemistry of the KaiC protein depends on conserved motifs Walker motifs for its activity as ATPase and some conserved residues for its autokinase activity, we searched for the presence of these motifs in other prokaryotic organisms, and specifically in L. We selected those prokaryotes that contained both, kaiB and kaiC sequences including L.
It has been reported that in bacteria the KaiC proteins usually contain a double KaiC domain but in some archea shorter KaiC sequences containing only a single domain can occur Dvornyk et al.
Those organisms that have both KaiC domains show also a well conserved second Walker motif, but L. Furthermore, in most of the KaiC protein sequences, the potential N-terminal phosphorylation sites are well conserved T, S, and T in S.
However, the T residue is also missing in F. The S phosphorylation residue is not conserved in Allochromatium vinosum and the T residue is replaced by an S residue in L. Figure 2. Alignment of the KaiC sequences from prokaryotes containing both kaiB and kaiC sequences in their genome. Walker motifs and phosphorylation residues are indicated. The numbers below indicate the amino acid position with respect to the full protein sequence. However, circadian clock systems exist also in organisms that do not have the kaiA gene like P.
With respect to the evolutionary analysis of the circadian components in cyanobacteria it was logical to infer that in cyanobacteria more than one circadian system might exist. First evidence came from the finding that some cyanobacteria lack the kaiA gene Dvornyk et al.
Based on these observations, Dvornyk and colleagues proposed that different circadian systems might exist in bacteria. The kaiABC system that has been extensively studied in S. An example of the kaiBC system is the circadian-like rhythm present in the purple bacterium Rh. To get further insight into the evolution of the KaiC proteins we have undertaken an updated phylogenetic analysis of the KaiC sequence of all organisms listed in Table 1.
In order to have a phylogenetic marker allowing to infer possible horizontal gene transfer, we also retrieved the RpoB sequence for the selected organisms from the NCBI database. As expected the phylogeny based on RpoB allowed good phylogenetic resolution comparable to the one obtained with the 16S rRNA.
However, the advantage is, that rpoB is a single copy gene and thus no intra-genomic heterogeneity among copies as seen for the 16S rRNA is present. Both groups of sequences were aligned using the program ClustalX v. The best evolutionary model was selected using Prottest Abascal et al. Using the best model according to AIC criterion, phylogenetic trees were constructed using both a distance method Neighbor-joining and likelihood with replicates of bootstrap.
As shown in Figure 3 , the RpoB tree allowed to clearly separate the different taxonomic groups and was supported by high bootstrap values in both, distance and likelihood trees. Figure 3. Phylogenetic tree of rpoB and kaiC sequences of prokaryotes containing kaiB and kaiC in their genome. A RpoB amino acid sequence tree obtained by the neighbor-joining method.
B KaiC amino acid sequences obtained by the likelihood method. The bootstrap values presented at corresponding nodes were obtained from replicates. The model is elegant and simple and produces experimentally testable predictions that the authors follow up on. Both reviewers agreed that this argument is not well supported.
Please either justify why biological repeats are not needed, or largely recommended repeat the experiments to verify reproduciblity. The authors study the phase of the cyanobacterial circadian oscillator under entrainment with different photoperiods day length. A main finding is that the internal clock phase tracks midday under entrainment, both in vivo and in the test tube, and this can be explained by the measured phase shifts at dawn and dusk.
Linearity properties of the phase shifting curves in a physiological range are sufficient to explain midday tracking, but this also generalizes to more complex perturbations. Overall, an elegant and general picture emerges, and a simple geometrical interpretation is proposed: that of the deformation of the clock orbit in light vs.
Would there be a more powerful way to exploit the purF reporter? I assume the authors do not have dual reporter strains? I would recommend putting the purF figure in the main, and to analyze the KaiC data in the same way i.
An important test for the model would be to analyze period mutants. That, is assuming that the phase shifts do not depend on the mutations, it would be straightforward to predict if mode-locking can still occur, and if so what the entrainment phase is.
Looking at period mutants seems quite obvious, why did the authors not do this? Moreover, it would have been informative to identify mutants with entrainment defects. Or perhaps some entrainment mutants are already reported, and could have been analyzed? Also, from the dynamical systems points of view, 1-d maps like the one proposed exhibit complex behavior period doubling, chaos, etc.
It would have been very interesting to try and probe whether other regimes besides can occur. The work appears to be of high quality, has very robust data, and should be interesting to the eLife audience. I do have the following concerns however. In the paper it is assumed that clocks in individual cells can only track one phase, and it is argued that tracking midday should be the optimal strategy, as it allows proportional expression of dawn and dusk genes.
I think both these ideas require further thought and justification. It is well known in the plant clock field that the clock network can track dawn and dusk. For example Edwards et al. There has also been theoretical studies on clocks without assuming any multicellularity or coupling between cells to examine what it takes to track more than one phase Rand et al. Royal Society Interface, As the cyanobacterial clock is limited to one feedback loop this presumably means it is limited to tracking one phase, but this point should be discussed.
If you are going to track one phase, it is not clear that tracking midday is an optimal decision. It could be that evening genes become more important under shorter days for example. It is not clear to me that equi-partitioning of the resources into two classes is necessarily clearly the optimal strategy. Thank you for resubmitting your work entitled "The cyanobacterial circadian clock follows midday in vivo and in vitro" for further consideration at eLife. Your revised article has been favorably evaluated by Naama Barkai as the Senior Editor and Reviewing Editor, and two reviewers.
Please see comments below — the reviewers would like you to emphasize aspects related to the reproducibility, as was raised in the previous review. Specifically, please show all that data in the main figures in Figure 2C, there's plenty of space to plot the two additional in vitro measurements.
Also, please adapt your interpretation to take into the observed variability and discuss what the potential sources are. I believe the revised version addresses the general editorial comments adequately. In addition, though the authors have partially addressed my comments, I regret that they did not consider my first major point on integrating the purF data in the main text, and also not analyze their KaiC data in the same way.
I liked the purF analysis with the multiple peaks, which seemed more thorough than that presented for KaiC in the main. In particular this modification seemed not to represent a lot of extra work, so it is not intuitive why it was not done.
This is especially true as Figure 3 now uses the new data from the fluorescent probe. The authors should include the values from the new experiments in Figure 2C. Could the authors please explain the differences? We agree with the reviewers that the argument that biosynthetic resources need to be equally partitioned by the clock between morning and afternoon gene expression programs is not strongly supported by our data.
Thus we have shortened the discussion of this hypothesis and moved it to the Discussion section of the paper. Likewise, we have moved the figure panels explaining the idea to Figure 7—figure supplement 3. We have included additional, independent in vitro measurements in the paper and clarified the number of biological replicates for the in vivo results 3 independent measurements of entrainment scaling, as detailed in new Table 1.
The in vitro entrainment experiment in Figure 2 has been repeated two more times with a new batch of purified proteins and measured using a fluorescent reporter of oscillations which allows us to more accurately determine phase.
These data, along with validation of the fluorescent reporter system, are now in Figure 2—figure supplements 1 and 2. These data are now shown in Figure 3. While replicate measurements on the same protein prep are in close agreement curves in Figure 3C and 3D there is some prep-to-prep variability in these experiments; our new protein prep is less responsive to nucleotide shifts. For both preparations of clock proteins, the model works well in the sense that phase shift functions correctly predict linear scaling of entrainment Figure 4C.
We decided to keep the purF reporter data in the supplement as in the original submission. As the reviewer suggests, the best comparison would use a dual reporter approach, which is not currently feasible using our bioluminescence detection system.
We agree that varying the natural frequency of the clock vs. Our preliminary experiments with period mutants suggested that many known point mutants that alter the period of oscillations also alter their amplitude. In light of our geometric model, where amplitude changes correspond to altered size of the limit cycle attractor, we expect that mutants that change both period and amplitude will change the entrained behavior of the clock in a way which requires a case-by-case investigation of each mutant.
For this reason, we probed this issue in the reverse way, by changing the frequency of the driving cycle for WT cells. These data are in Figure 6C along with a simultaneous fit showing self-consistency of the model unchanged from the original submission. This is a good suggestion, though most known entrainment mutants e.
We have now generated a bifurcation diagram as a function of driving period for the model based on the L and D maps derived from our biochemical measurements. This map is in Figure 3—figure supplement 1. As expected, we find a band of frequencies around the natural frequency where entrainment occurs an Arnold tongue. Outside of this band, apparently chaos-like dynamics emerge, though entrainment reappears at multiples of the natural frequency e.
We agree with the reviewer that it is not obvious that an organism with a single feedback loop clock should track the middle of the day. We have removed our speculative hypothesis about metabolic balance from the beginning of the paper and instead raise the idea briefly in the Discussion section. We have now included citations to this previous work in the following paragraph:.
We agree that the model in Figure 7 with the assumption of circular, strongly attracting limit cycles is unrealistically simple. We have added new material in Figure 7—figure supplement 2 that shows the results of relaxing these assumptions. We consider a finite relaxation time when the system is displaced from the limit cycle following a dusk or dawn transition, ellipticity, and nonuniform angular velocity. We find that the entrainment behavior is very similar until the relaxation time becomes comparable to the length of the day itself.
Similarly, ellipticity or nonuniform rotational velocity have minor effects, but do not change the basic conclusion that limit cycle separation in day vs. We have moved all of our in vitro measurements of entrainment and step-response functions into the main panels in Figures 2 and 3. Additionally, we have modified the text in the Results section to discuss variability in our in vitro measurements and its possible sources:.
Taking into account our observed variability, we have also modified the text to deemphasize the specific value of the scaling coefficient, m ; that m takes intermediate values both in vivo and in vitro shows that the reconstitution captures the essential physics of the system, but we have no reason to expect the in vivo and in vitro phase responses to be precisely the same:.
We have added text explaining why we have higher confidence in our fluorescence polarization measurements than in the traditional SDS-PAGE analysis of KaiC phosphorylation:. Because the fluorescence polarization approach allows us to measure many conditions in an automated way over many days, and thus to disentangle phase shifts from period differences Figure 3C-D , these higher time resolution measurements better constrain the portions of the response functions critical for entrainment. We agree with the reviewer that locally fitting parabolas to mark peak positions is a good way to estimate peak times of our oscillations.
We have done this analysis for the strain carrying the kaiBC reporter and have replaced data in Figure 1C with peak times obtained using this approach.
Our estimates of the slope m for the kaiBC expression reporter are listed in Table 1. Interested readers can find these data in Figure 1—figure supplement 3. In general I am happy with the revision, but I have the following concerns. The reviewer raises an excellent point that there is a visual discrepancy between the phase shift magnitudes in Figure 3A and 3C.
Thus, differences in peak times in Figure 3A, which shows oscillations over a 72 hour time period after the step perturbation, have two contributions: 1 the instantaneous phase shift caused by the step and 2 the two rhythms drifting out of phase over time as a result of the different periods of the control and step-down reactions.
Thus the peak-to-peak time differences in Figure 3A are larger than in Figure 3C, which displays our estimates of instantaneous phase shifts at the time of the step and excludes any contributions from period differences accumulated in free-running conditions after the step transition. While this shifts certain numbers slightly, it does not have any significant impact on the results or their interpretation. To avoid confusion, we have clarified how these measurements are described in the main text and have added a new supplementary figure Figure 3—figure supplement 1 illustrating the data analysis procedure:.
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication. Joel Heisler and Andy LiWang assisted us with fluorescence polarization measurements. EL analyzed data. This article is distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use and redistribution provided that the original author and source are credited. Article citation count generated by polling the highest count across the following sources: Crossref , Scopus , PubMed Central.
Bacteria must balance the different needs for substrate assimilation, growth functions, and resilience in order to thrive in their environment. Of all cellular macromolecules, the bacterial proteome is by far the most important resource and its size is limited. Here, we investigated how the highly versatile 'knallgas' bacterium Cupriavidus necator reallocates protein resources when grown on different limiting substrates and with different growth rates.
We determined protein quantity by mass spectrometry and estimated enzyme utilization by resource balance analysis modeling. We found that C. Of the enzymes that are utilized, many are present in excess abundance. One prominent example is the strong expression of CBB cycle genes such as Rubisco during growth on fructose.
Modeling and mutant competition experiments suggest that CO 2 -reassimilation through Rubisco does not provide a fitness benefit for heterotrophic growth, but is rather an investment in readiness for autotrophy. The genetic code has been proposed to be a 'frozen accident', but the discovery of alternative genetic codes over the past four decades has shown that it can evolve to some degree. Since most examples were found anecdotally, it is difficult to draw general conclusions about the evolutionary trajectories of codon reassignment and why some codons are affected more frequently.
To fill in the diversity of genetic codes, we developed Codetta, a computational method to predict the amino acid decoding of each codon from nucleotide sequence data. We surveyed the genetic code usage of over , bacterial and archaeal genome sequences in GenBank and discovered five new reassignments of arginine codons AGG, CGA, and CGG , representing the first sense codon changes in bacteria. In a clade of uncultivated Bacilli, the reassignment of AGG to become the dominant methionine codon likely evolved by a change in the amino acid charging of an arginine tRNA.
Protein phosphorylation is a reversible post-translation modification essential in cell signaling. Using molecular and cellular approaches, we identified a conserved region 1 R1, residues — encompassing the strongest p binding site. Cited 21 Views 2, Annotations Open annotations. The current annotation count on this page is being calculated. Cite this article as: eLife ;6:e doi: Figure 1 with 3 supplements see all.
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Step fun. Appendix 1—figure 1. The following previously published data sets were used. Journal of Biological Rhythms 16 — Daan S The Colin S. Pittendrigh Lecture. Chronobiology International 16 — Genome-wide fitness assessment during diurnal growth reveals an expanded role of the cyanobacterial circadian clock protein KaiA. Vijayan, V.
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Livak, K. Methods 25 , — Mackey, S. Detection of rhythmic bioluminescence from luciferase reporters in cyanobacteria. Download references. We thank D. Welkie, C. Sancar, and R. Simkovsky for their input on the experimental design and data analyses, B. McKnight, L. Lowe, and C. Peterson for assistance with strain construction and transformation assays. We thank T. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author s and do not necessarily reflect the views of the National Science Foundation. Rubin, Scott A. Rifkin, James W. You can also search for this author in PubMed Google Scholar. G, and S. Correspondence to Susan S. Peer review information Nature Communications thanks Takashi Osanai and the other, anonymous, reviewers for their contribution to the peer review of this work. Peer reviewer reports are available.
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