Quantifying the Rhythm of KaiB-C Interaction for <em>In Vitro</em> Cyanobacterial Circadian Clock

<div><p>An oscillator consisting of KaiA, KaiB, and KaiC proteins comprises the core of cyanobacterial circadian clock. While one key reaction in this process—KaiC phosphorylation—has been extensively investigated and modeled, other key processes, such as the interactions among Kai proteins, are not understood well. Specifically, different experimental techniques have yielded inconsistent views about Kai A, B, and C interactions. Here, we first propose a mathematical model of cyanobacterial circadian clock that explains the recently observed dynamics of the four phospho-states of KaiC as well as the interactions among the three Kai proteins. Simulations of the model show that the interaction between KaiB and KaiC oscillates with the same period as the phosphorylation of KaiC, but displays a phase delay of ∼8 hr relative to the total phosphorylated KaiC. Secondly, this prediction on KaiB-C interaction are evaluated using a novel FRET (Fluorescence Resonance Energy Transfer)-based assay by tagging fluorescent proteins Cerulean and Venus to KaiC and KaiB, respectively, and reconstituting fluorescent protein-labeled <em>in vitro</em> clock. The data show that the KaiB∶KaiC interaction indeed oscillates with ∼24 hr periodicity and ∼8 hr phase delay relative to KaiC phosphorylation, consistent with model prediction. Moreover, it is noteworthy that our model indicates that the interlinked positive and negative feedback loops are the underlying mechanism for oscillation, with the serine phosphorylated-state (the “S-state") of KaiC being a hub for the feedback loops. Because the kinetics of the KaiB-C interaction faithfully follows that of the S-state, the FRET measurement may provide an important real-time probe in quantitative study of the cyanobacterial circadian clock.</p> </div

FRET and gel electrophoresis assays of the fluorescent protein-labeled <i>in vitro</i> KaiABC clock.

<p>(A) Comparison of FRET and electrophoresis assays of the <i>in vitro</i> clock. The trajectory of FRET signal (blue circle) is the average of 40 time courses normalized by their respective all-time-point mean. The trajectory of phosphorylated KaiC (black circle) relative to total KaiC is the average quantification of three sets of electrophoresis data including that in (B). The error bars represent the respective standard error. The blue and black lines represent fitted curves of FRET and electrophoresis data. (B) SDS-PAGE gel for the <i>in vitro</i> clock of KaiA, KaiB-Venus and KaiC-Cerulean. The protein stoichiometry is described in method. Reaction samples are analyzed on a 6% polyacrylamide gel. The time for each lane at which the sample is taken is labeled on top in hours.</p

Phosphorylation responses of unphosphorylated or mostly phosphorylated KaiC to varying concentrations of KaiA.

<p>(A) KaiC (3.5 µM) of unphosphorylated (upper panel) or mostly phosphorylated (lower panel) initial condition is incubated with different concentrations of KaiA (1× fold equals to 1.5 µM) at 30°C for 16 hrs. Samples at initial condition (left) and 16 hr (right) are subjected to SDS-PAGE using 7.5% gel. (B) Semi-logarithmic plot of relative amount of phosphorylated KaiC at 16 hr as a function of KaiA concentration obtained by quantifying the densitometry of (A) using ImageJ. The data for unphosphorylated (blue circle) and phosphorylated (black circle) initial conditions of KaiC are fitted by sigmoid curves (blue and black lines). Note that the half-maximum concentration of KaiA for unphosphorylated initial condition is about 5 times that for highly phosphorylated initial condition, indicating that KaiA interacts with unphosphorylated KaiC with higher preference.</p

Steady-state FRET between KaiC-Cerulean and KaiB-Venus.

<p>(A) Cartoon of interaction between a KaiC-Cerulean hexamer and a KaiB-Venus tetramer. Unphosphorylated KaiC binds with KaiB-Venus at low affinity producing weak FRET, while the S-phosphorylated KaiC recruits KaiB-Venus to its vicinity and induces high FRET signal. (B) Fluorescence spectra of KaiC-Cerulean alone (solid line), KaiC-Cerulean plus KaiB-Venus (dashed line), KaiC-Cerulean plus Venus (dotted line) excited at 433 nm in standard clock reaction buffer. The concentration of KaiC-Cerulean is 3.75 µM. The concentration of KaiB-Venus and Venus is 4.05 µM. Note that the emission spectrum of KaiB-Venus plus Cerulean is almost identical to that of KaiC-Cerulean plus Venus, and therefore is not shown. (C) Peak fluorescence intensities of Cerulean (black dashed line) and Venus (black dash-dot line) plotted versus the concentrations of KaiB-Venus when KaiC-Cerulean (3.75 µM) is incubated with different amount of KaiB-Venus (1× fold equals to 4.05 µM) in clock reaction buffer. The fluorescence intensity is mean of 10 measurements and the standard deviation is included. The FRET efficiency calculated using the mean intensity shows a graded increase (blue line).</p

Model scheme of the <i>in vitro</i> KaiABC clock.

<p>The model includes the ordered phosphorylation/dephosphorylaton among KaiC phospho-forms U, S, ST and S (plotted in shaded box). It also accounts for reactions among the four KaiC phospho-forms, KaiA, KaiB and their derivative complexes. For example, phospho-form T undergoes auto-phosphorylation, auto-dephosphorylation, association and dissociation with KaiA. In addition, UA, TA and SA are assumed to respectively enhance phosphorylation from U, T and S, SB is assumed to promote dephosphorylation from ST to S as well as from S to U, and SAB is assumed to inhibit the phosphorylation from U to T.</p

Image_1_Association between prenatal exposure to ambient ozone, birth weight, and macrosomia in healthy women.JPEG

Studies have shown that prenatal ozone exposure is associated with an increased risk of adverse pregnancy outcomes, among which abnormal birth weight is a detrimental factor for diseases in adulthood, but the association between birth weight and ozone is inconclusive. Herein, we conducted this study by enrolling 407 couples of pregnant women and collected their demographical materials, their exposure to ambient ozone was assessed according to the place of their residence. The hourly monitored ozone was first averaged to the daily level, then monthly and whole-gestationally levels. After adjusting confounders, we processed a multivariate generalized addictive analysis to predict the association between prenatal ozone exposure and birth weight. We also divided the cohort into two categories according to whether the infant met the standard of macrosomia, and the occurrence of macrosomia was studied via univariate and multivariate logistic regression analyses as extreme conditions of the effects of ozone exposure on birth weight. We found that the ground-level ozone in Jinan changed with temperature periodically, higher in summer and lower in winter. Over the past 8 years from 2014, the ambient ozone increased by 1.74 μg/m3 per year. Of the 407 singleton-pregnant women, 21 infants were diagnosed with macrosomia. After adjusting confounders, we found that each unit increase in prenatal ozone exposure caused 8.80% [ORozone90%CI: 0.912 (0.850, 0.978)] decreased risk of macrosomia, but the splined ambient ozone exposure data was not statistically associated with birth weight, which is probably due to the limited sample size. In conclusion, prenatal ozone exposure is associated with decreased risk of macrosomia but is weakly linked to birth weight.</p

Diagram of the p53-MDM2 oscillator under the regulation of positive feedbacks via microRNA-192, -34a and -29a.

<p>p53 is translated from p53 mRNA and remains inactive. Phosphorylated by ATM*, p53 becomes active (p53*), and able to transcribe mdm2 mRNA. MDM2 protein, translated from mdm2 mRNA, promotes a fast degradation of p53 and a slow degradation of p53*. In addition to a basal self-degradation, MDM2 is degraded by a mechanism stimulated by ATM*. The three microRNAs, miR-192, miR-34a and miR-29a, are induced by p53*, and inhibit the mRNAs of mdm2, cdc42, wip1, sirt1 and yy1, whose protein products further regulate p53* and MDM2. Specifically, the microRNA binds with its target mRNA molecule with high affinity, forming a microRNA-mRNA complex, and subsequently dispose the complex into a degradation machinery. In other words, the microRNAs in our model are assumed to enhance the degradation of their mRNA target by complexation and subsequent disposal. In particular, CDC42, Wip1 and SIRT1 proteins deactivate p53 directly, while YY1 enhances the MDM2-dependent degradation of p53 and p53* proteins. In addition, Wip1 protein inhibits the degradation of MDM2 protein. The wip1 mRNA is also induced by p53*, whose protein product inhibits active ATM, forming a second negative feedback loop.</p

Correlation Between the Computed Tomography and 3D Scanning System-Based Periorbital Morphology of Children with Congenital Microphthalmia

This article aimed to explore the correlation between the periorbital morphology determined using a 3D scanning system and CT in congenital microphthalmia. Fifty-two children with microphthalmia aged 0–6 were enrolled in this study. All the participants were subjected to orbital CT scans and 3D scanning. The CT and 3D scanning images were separately processed to obtain the orbital and facial parameters. Multivariate regression was used to analyze the correlation between 3D parameters and orbital volume. The orbital volume of the affected side (15.25 ± 3.35 cm3) was generally smaller than the unaffected side (18.58 ± 2.65 cm3, p 2 = 0.808, p  The retarded orbital volume could be estimated by the parameters based on 3D scanning, along with axial length. In the follow-up stage, 3D scanning can be a novel alternative method to assess the degree of orbital growth retardation in congenital microphthalmia.</p

Improvement of start-up and nitrogen removal of the anammox process in reactors inoculated with conventional activated sludge using biofilm carrier materials

<p>The start-up of the anaerobic ammonium oxidation (anammox) process in three up-flow column reactors seeded with common mixed activated sludge and added with three materials, sponge (R1), sponge + volcanic rock (R2) and sponge + charcoal (R3), as carriers for biofilm formation were comparatively investigated in this study. The supplement of volcanic rock and charcoal could significantly shorten the start-up time of the anammox process, which primarily occurred in the activity-enhanced phase, with ammonium and nitrite removal efficiencies stabilized above 92.5% and 93.4% after an operation period of 145, 105 and 121 d for R1, R2 and R3, respectively. After the successful anammox start-up, R2 performed significantly better in TN removal (<i>p </i>< .05), achieving an average rate of 91.0% and 191.5 g N m⁻³ d⁻¹ compared to R1 of 88.4% and 172.1 g N m⁻³ d⁻¹, and R3 of 89.9% and 180.1 g N m⁻³ d⁻¹ in the steady running phase. The ratios of consumed and generated /consumed after anammox start-up were lower than the theoretical values, probably suggesting the simultaneous existences of anammox, denitrification as well as nitrification processes in the reactors. A reddish brown biofilm was wrapped on the carriers and morphological detection of biofilm displayed the presentations of thick and compact floc aggregates and some filamentous bacteria on the sponge, and spherical-, ovoid- and shortrod-shaped microorganisms on the volcanic rock and charcoal. Using porous material as carrier for biofilm development is an effective strategy for practical application of the anammox reactor.</p

MiR-192-Mediated Positive Feedback Loop Controls the Robustness of Stress-Induced p53 Oscillations in Breast Cancer Cells

<div><p>The p53 tumor suppressor protein plays a critical role in cellular stress and cancer prevention. A number of post-transcriptional regulators, termed microRNAs, are closely connected with the p53-mediated cellular networks. While the molecular interactions among p53 and microRNAs have emerged, a systems-level understanding of the regulatory mechanism and the role of microRNAs-forming feedback loops with the p53 core remains elusive. Here we have identified from literature that there exist three classes of microRNA-mediated feedback loops revolving around p53, all with the nature of positive feedback coincidentally. To explore the relationship between the cellular performance of p53 with the microRNA feedback pathways, we developed a mathematical model of the core p53-MDM2 module coupled with three microRNA-mediated positive feedback loops involving miR-192, miR-34a, and miR-29a. Simulations and bifurcation analysis in relationship to extrinsic noise reproduce the oscillatory behavior of p53 under DNA damage in single cells, and notably show that specific microRNA abrogation can disrupt the wild-type cellular phenotype when the ubiquitous cell-to-cell variability is taken into account. To assess these <i>in silico</i> results we conducted microRNA-perturbation experiments in MCF7 breast cancer cells. Time-lapse microscopy of cell-population behavior in response to DNA double-strand breaks, together with image classification of single-cell phenotypes across a population, confirmed that the cellular p53 oscillations are compromised after miR-192 perturbations, matching well with the model predictions. Our study via modeling in combination with quantitative experiments provides new evidence on the role of microRNA-mediated positive feedback loops in conferring robustness to the system performance of stress-induced response of p53.</p></div