Skin cells undergo asynthetic fission to expand body surfaces in zebrafish.

As an animal's surface area expands during development, skin cell populations must quickly respond to maintain sufficient epithelial coverage. Despite much progress in understanding of skin cell behaviours in vivo1,2, it remains unclear how cells collectively act to satisfy coverage demands at an organismic level. Here we created a multicolour cell membrane tagging system, palmskin, to monitor the entire population of superficial epithelial cells (SECs) in developing zebrafish larvae. Using time-lapse imaging, we found that many SECs readily divide on the animal body surface; during a specific developmental window, a single SEC can produce a maximum of four progeny cells over its lifetime on the surface of the animal. Remarkably, EdU assays, DNA staining and hydroxyurea treatment showed that these terminally differentiated skin cells continue splitting despite an absence of DNA replication, causing up to 50% of SECs to exhibit reduced genome size. On the basis of a simple mathematical model and quantitative analyses of cell volumes and apical surface areas, we propose that 'asynthetic fission' is used as an efficient mechanism for expanding epithelial coverage during rapid growth. Furthermore, global or local manipulation of body surface growth affects the extent and mode of SEC division, presumably through tension-mediated activation of stretch-activated ion channels. We speculate that this frugal yet flexible mode of cell proliferation might also occur in contexts other than zebrafish skin expansion.

Interplay between ceRNA and Epigenetic Control of microRNA: Modelling Approaches with Application to the Role of Estrogen in Ovarian Cancer.

MicroRNAs (miRNAs) play an important role in gene regulation by degradation or translational inhibition of the targeted mRNAs. It has been experimentally shown that the way miRNAs interact with their targets can be used to explain the indirect interactions among their targets, i.e., competing endogenous RNA (ceRNA). However, whether the protein translated from the targeted mRNAs can play any role in this ceRNA network has not been explored. Here we propose a deterministic model to demonstrate that in a network of one miRNA interacting with multiple-targeted mRNAs, the competition between miRNA-targeted mRNAs is not sufficient for the significant change of those targeted mRNA levels, while dramatic changes of these miRNA-targeted mRNAs require transcriptional inhibition of miRNA by its target proteins. When applied to estrogen receptor signaling pathways, the miR-193a targets E2F6 (a target of estrogen receptor), c-KIT (a marker for cancer stemness), and PBX1 (a transcriptional activator for immunosuppressive cytokine, IL-10) in ovarian cancer, such that epigenetic silencing of miR-193a by E2F6 protein is required for the significant change of c-KIT and PBX1 mRNA level for cancer stemness and immunoevasion, respectively, in ovarian cancer carcinogenesis.

Basal leakage in oscillation: Coupled transcriptional and translational control using feed-forward loops.

The circadian clock is a complex system that plays many important roles in most organisms. Previously, many mathematical models have been used to sharpen our understanding of the Arabidopsis clock, which brought to light the roles of each transcriptional and post-translational regulations. However, the presence of both regulations, instead of either transcription or post-translation, raised curiosity of whether the combination of these two regulations is important for the clock's system. In this study, we built a series of simplified oscillators with different regulations to study the importance of post-translational regulation (specifically, 26S proteasome degradation) in the clock system. We found that a simple transcriptional-based oscillator can already generate sustained oscillation, but the oscillation can be easily destroyed in the presence of transcriptional leakage. Coupling post-translational control with transcriptional-based oscillator in a feed-forward loop will greatly improve the robustness of the oscillator in the presence of basal leakage. Using these general models, we were able to replicate the increased variability observed in the E3 ligase mutant for both plant and mammalian clocks. With this insight, we also predict a plausible regulator of several E3 ligase genes in the plant's clock. Thus, our results provide insights into and the plausible importance in coupling transcription and post-translation controls in the clock system.

Molecular and nano structures of chiral PEDOT derivatives influence the enantiorecognition of biomolecules. In silico analysis of chiral recognition.

In this study we investigated the synergistic effects of the chirality (molecular structure) and surface morphology (nanostructure) of a newly designed sensing platform for the stereoselective recognition of biomolecules. We synthesized 3,4-ethylenedioxythiophene monomers presenting an OH functional group on the side chain (EDOT-OH) with either R or S chirality and then electropolymerized them in a template-free manner to engineer poly(EDOT-OH) nanotubes and smooth films with R or S chirality. We used a quartz crystal microbalance (QCM) to examine the differential binding of fetal bovine serum, RGD peptide, insulin, and (R)- and (S)-mandelic acid (MA) on these chiral polymeric platforms. All of these biomolecules bound stereoselectively and with greater affinity toward the nanotubes than to the smooth films. The sensitive chiral recognition of (S)- and (R)-MA on the (R)-poly(EDOT-OH) nanotube surface occurred with the highest chiral discrepancy ratio of 1.80. In vitro experiments revealed a greater degree of protein deposition from MCF-7 cells on the chiral nanotube surfaces. We employed ab initio molecular dynamics simulations and density functional theory calculations to investigate the mechanism underlying the sensitive chiral recognition between the chiral sensing platforms and the chiral analyte molecules.

The fluctuation-dissipation theorem for stochastic kinetics--implications on genetic regulations.

The Fluctuation-Dissipation theorem (FDT) connects the "memory" in the fluctuation in equilibrium to the response of a system after a perturbation, which has been a fundamental ground in many branches of physics. When viewing a cell as a stochastic biochemical system, the cell's response under a perturbation is related to its intrinsic steady-state correlation functions via the FDT, a theorem we derived and present in this work. FDT allows us to use the noise to derive dynamic response and infer dynamic properties in the system. We tested FDT's validity with gene regulation models and found that it is limited to the linear response. For an indirect regulation pathway where unknown components may exist, FDT still works within the linear response region. Thus, FDT may be used for systems with partial knowledge, and it is potentially possible to identify the existence of unobserved components. With FDT, the dynamic response can be composed of steady-state measurements without the complete detailed knowledge for the regulation or kinetics. The response function derived can give important insights into the dynamics and time scales of the system.

DNA tension assays reveal that force-dependent integrin activation regulates neurite outgrowth in primary cortical neurons.

Biomechanical inputs are ubiquitously present in biological systems and are known to regulate various cell functions. In particular, neural cell development is sensitive to mechanical regulation, as these cells reside in one of the softest microenvironments in the body. To fully characterize and comprehend how mechanical force modulates early neuronal processes, we prepared substrates functionalized with DNA probes displaying integrin ligands, including cRGD and laminin, to quantify integrin-mediated molecular tension during neurite initiation in primary cortical neurons. Our live-cell imaging analysis reveals that integrin-mediated tension force is highly dynamic and distributed across the cell body, with the overall tension signal gradually increasing during neurite outgrowth. Notably, we detected a consistent level of mechanical force (amplitude = 4.7-12 piconewtons, pN) for cell integrin-ligand interactions. Further quantifications reveal that neurons exhibit faster cell spreading and neurite outgrowth upon interacting with ligands functionalized with 4.7 pN relative to 12 pN probes. These findings indicate that the magnitude of integrin-mediated mechanical feedback regulates neuronal activity during early neuritogenesis. Additionally, we observed that mechanical tension is correlated with calcium signaling, since inhibiting calcium influx substantially reduced mechanical tension. Thus, our findings support that the magnitude of integrin-mediated mechanical feedback regulates neuronal activity during early neuritogenesis and that mechanical force is an essential element complementing well-known biochemical regulatory mechanisms orchestrating the integrin activation machinery and controlled neurite outgrowth in cortical neurons.

Noise reduction by upstream open reading frames.

Gene expression is prone to burst production, making it a highly noisy process that requires additional controls. Upstream open reading frames (uORFs) are widely present in the 5' leader sequences of 30-50% of eukaryotic messenger RNAs1-3. The translation of uORFs can repress the translation efficiency of the downstream main coding sequences. Whether the low translation efficiency leads to a different variation, or noise, in gene expression has not been investigated, nor has the direct biological impact of uORF-repressed translation. Here we show that uORFs achieve low but precise protein production in plant cells, possibly by reducing the protein production rate. We also demonstrate that, by buffering a stable TIMING OF CAB EXPRESSION 1 (TOC1) protein production level, uORFs contribute to the robust operation of the plant circadian clock. Our results provide both an action model and the biological impact of uORFs in translational control to mitigate transcriptional noise for precise protein production.

Efficient and flexible implementation of Langevin simulation for gene burst production.

Gene expression involves bursts of production of both mRNA and protein, and the fluctuations in their number are increased due to such bursts. The Langevin equation is an efficient and versatile means to simulate such number fluctuation. However, how to include these mRNA and protein bursts in the Langevin equation is not intuitively clear. In this work, we estimated the variance in burst production from a general gene expression model and introduced such variation in the Langevin equation. Our approach offers different Langevin expressions for either or both transcriptional and translational bursts considered and saves computer time by including many production events at once in a short burst time. The errors can be controlled to be rather precise (<2%) for the mean and <10% for the standard deviation of the steady-state distribution. Our scheme allows for high-quality stochastic simulations with the Langevin equation for gene expression, which is useful in analysis of biological networks.

Noise propagation with interlinked feed-forward pathways.

Functionally similar pathways are often seen in biological systems, forming feed-forward controls. The robustness in network motifs such as feed-forward loops (FFLs) has been reported previously. In this work, we studied noise propagation in a development network that has multiple interlinked FFLs. A FFL has the potential of asymmetric noise-filtering (i.e., it works at either the "ON" or the "OFF" state in the target gene). With multiple, interlinked FFLs, we show that the propagated noises are largely filtered regardless of the states in the input genes. The noise-filtering property of an interlinked FFL can be largely derived from that of the individual FFLs, and with interlinked FFLs, it is possible to filter noises in both "ON" and "OFF" states in the output. We demonstrated the noise filtering effect in the developmental regulatory network of Caenorhabditis elegans that controls the timing of distal tip cell (DTC) migration. The roles of positive feedback loops involving blmp-1 and the degradation regulation of DRE-1 also studied. Our analyses allow for better inference from network structures to noise-filtering properties, and provide insights into the mechanisms behind the precise DTC migration controls in space and time.