A STAR Bioinformatics Institute
A STAR Bioinformatics Institute
Gaughwin P.,A STAR Genome Institute of Singapore |
Gaughwin P.,Lund University |
Ciesla M.,Jagiellonian University |
Yang H.,A STAR Bioinformatics Institute |
And 3 more authors.
Cerebral Cortex | Year: 2011
To realize the potential of microRNAs (miRs) as fine-tuning regulators of embryonic neuronal differentiation, it is critical to define their developmental function. Mmu-miR-134 (miR-134) is a powerful inducer of pluripotent stem cell differentiation. However, its functional role during embryonic, neuronal development is unknown. We demonstrate that mature, miR-134 transcript levels elevate during embryonic, neuronal differentiation in vitro and in vivo. To define the developmental targets and function of miR-134, we identified multiple brain-expressed targets including the neural progenitor cell-enriched, bone morphogenetic protein (BMP) antagonist Chordin-like 1 (Chrdl-1) and the postmitotic, neuron-specific, microtubule-associated protein, Doublecortin (Dcx). We show that, through interaction with Dcx and/or Chrdl-1, miR-134 has stage-specific effects on cortical progenitors, migratory neurons, and differentiated neurons. In neural progenitors, miR-134 promotes cell proliferation and counteracts Chrdl-1-induced apoptosis and Dcx-induced differentiation in vitro. In neurons, miR-134 reduces cell migration in vitro and in vivo in a Dcx-dependent manner. In differentiating neurons, miR-134 modulates process outgrowth in response to exogenous BMP-4 in a noggin-reversible manner. Taken together, we present Dcx and Chrdl-1 as new regulatory targets of miR-134 during embryonic, mouse, cortical, and neuronal differentiation and show a novel and previously undiscovered role for miR-134 in the stage-specific modulation of cortical development. © 2011 The Authors.
Qian C.,National University of Singapore |
Ching Wong C.,National University of Singapore |
Swarup S.,National University of Singapore |
Swarup S.,Nanyang Technological University |
And 2 more authors.
Applied and Environmental Microbiology | Year: 2013
We have developed a program that can accurately analyze the dynamic properties of tethered bacterial cells. The program works especially well with cells that tend to give rise to unstable rotations, such as polar-flagellated bacteria. The program has two novel components. The first dynamically adjusts the center of the cell's rotational trajectories. The second applies piecewise linear approximation to the accumulated rotation curve to reduce noise and separate the motion of bacteria into phases. Thus, it can separate counterclockwise (CCW) and clockwise (CW) rotations distinctly and measure rotational speed accurately. Using this program, we analyzed the properties of tethered Pseudomonas aeruginosa and Pseudomonas putida cells for the first time. We found that the Pseudomonas flagellar motor spends equal time in both CCW andCWphases and that it rotates with the same speed in both phases. In addition, we discovered that the cell body can remain stationary for short periods of time, leading to the existence of a third phase of the flagellar motor which we call "pause." In addition, P. aeruginosa cells adopt longer run lengths, fewer pause frequencies, and shorter pause durations as part of their chemotactic response. We propose that one purpose of the pause phase is to allow the cells to turn at a large angle, where we show that pause durations in free-swimming cells positively correlate with turn angle sizes. Taken together, our results suggest a new "run-reverse-turn" paradigm for polar-flagellated Pseudomonas motility that is different from the "run-and-tumble" paradigm established for peritrichous Escherichia coli. © 2013, American Society for Microbiology. All Rights Reserved.
Tan R.Z.,A STAR Bioinformatics Institute |
Chiam K.-H.,A STAR Bioinformatics Institute |
Chiam K.-H.,National University of Singapore
PLoS ONE | Year: 2014
Robust tissue patterning is crucial to many processes during development. The "French Flag" model of patterning, whereby naïve cells in a gradient of diffusible morphogen signal adopt different fates due to exposure to different amounts of morphogen concentration, has been the most widely proposed model for tissue patterning. However, recently, using timelapse experiments, cell sorting has been found to be an alternative model for tissue patterning in the zebrafish neural tube. But it remains unclear what the sorting mechanism is. In this article, we used computational modeling to show that two mechanisms, chemotaxis and differential adhesion, are needed for robust cell sorting. We assessed the performance of each of the two mechanisms by quantifying the fraction of correct sorting, the fraction of stable clusters formed after correct sorting, the time needed to achieve correct sorting, and the size variations of the cells having different fates. We found that chemotaxis and differential adhesion confer different advantages to the sorting process. Chemotaxis leads to high fraction of correct sorting as individual cells will either migrate towards or away from the source depending on its cell type. However after the cells have sorted correctly, there is no interaction among cells of the same type to stabilize the sorted boundaries, leading to cell clusters that are unstable. On the other hand, differential adhesion results in low fraction of correct clusters that are more stable. In the absence of morphogen gradient noise, a combination of both chemotaxis and differential adhesion yields cell sorting that is both accurate and robust. However, in the presence of gradient noise, the simple combination of chemotaxis and differential adhesion is insufficient for cell sorting; instead, chemotaxis coupled with delayed differential adhesion is required to yield optimal sorting. © 2014 Tan, Chiam.
Koon Y.L.,National University of Singapore |
Koon Y.L.,Nanyang Technological University |
Koh C.G.,National University of Singapore |
Koh C.G.,Nanyang Technological University |
And 2 more authors.
PLoS ONE | Year: 2014
Intracellular transport of proteins by motors along cytoskeletal filaments is crucial to the proper functioning of many eukaryotic cells. Since most proteins are synthesized at the cell body, mechanisms are required to deliver them to the growing periphery. In this article, we use computational modeling to study the strategies of protein transport in the context of JNK (c-JUN NH2-terminal kinase) transport along microtubules to the terminals of neuronal cells. One such strategy for protein transport is for the proteins of the JNK signaling cascade to bind to scaffolds, and to have the whole protein-scaffold cargo transported by kinesin motors along microtubules. We show how this strategy outperforms protein transport by diffusion alone, using metrics such as signaling rate and signal amplification. We find that there exists a range of scaffold concentrations for which JNK transport is optimal. Increase in scaffold concentration increases signaling rate and signal amplification but an excess of scaffolds results in the dilution of reactants. Similarly, there exists a range of kinesin motor speeds for which JNK transport is optimal. Signaling rate and signal amplification increases with kinesin motor speed until the speed of motor translocation becomes faster than kinase/scaffold-motor binding. Finally, we suggest experiments that can be performed to validate whether, in physiological conditions, neuronal cells do indeed adopt such an optimal strategy. Understanding cytoskeletal-assisted protein transport is crucial since axonal and cell body accumulation of organelles and proteins is a histological feature in many human neurodegenerative diseases. In this paper, we have shown that axonal transport performance changes with altered transport component concentrations and transport speeds wherein these aspects can be modulated to improve axonal efficiency and prevent or slowdown axonal deterioration. © 2014 Koon et al.