Cell cycle and lineage progression of neural progenitors in the ventricular-subventricular zones of adult mice

Proliferating neural stem cells and intermediate progenitors persist in the ventricular-subventricular zone (V-SVZ) of the adult mammalian brain. This extensive germinal layer in the walls of the lateral ventricles is the site of birth of different types of interneurons destined for the olfactory bulb. The cell cycle dynamics of stem cells (B1 cells), intermediate progenitors (C cells), and neuroblasts (A cells) in the V-SVZ and the number of times these cells divide remain unknown. Using whole mounts of the walls of the lateral ventricles of adult mice and three cell cycle analysis methods using thymidine analogs, we determined the proliferation dynamics of B1, C, and A cells in vivo. Achaete-scute complex homolog (Ascl)1(+) C cells were heterogeneous with a cell cycle length (T(C)) of 18–25 h and a long S phase length (T(S)) of 14–17 h. After C cells, Doublecortin(+) A cells were the second-most common dividing cell type in the V-SVZ and had a T(C) of 18 h and T(S) of 9 h. Human glial fibrillary acidic protein (hGFAP)::GFP(+) B1 cells had a surprisingly short Tc of 17–18 h and a T(S) of 4 h. Progenitor population analysis suggests that following the initial division of B1 cells, C cells divide three times and A cells once, possibly twice. These data provide essential information on the dynamics of adult progenitor cell proliferation in the V-SVZ and how large numbers of new neurons continue to be produced in the adult mammalian brain

Dispersal of transgenes through maize seed systems in Mexico.

ObjectivesCurrent models of transgene dispersal focus on gene flow via pollen while neglecting seed, a vital vehicle for gene flow in centers of crop origin and diversity. We analyze the dispersal of maize transgenes via seeds in Mexico, the crop's cradle.MethodsWe use immunoassays (ELISA) to screen for the activity of recombinant proteins in a nationwide sample of farmer seed stocks. We estimate critical parameters of seed population dynamics using household survey data and combine these estimates with analytical results to examine presumed sources and mechanisms of dispersal.ResultsRecombinant proteins Cry1Ab/Ac and CP4/EPSPS were found in 3.1% and 1.8% of samples, respectively. They are most abundant in southeast Mexico but also present in the west-central region. Diffusion of seed and grain imported from the United States might explain the frequency and distribution of transgenes in west-central Mexico but not in the southeast.ConclusionsUnderstanding the potential for transgene survival and dispersal should help design methods to regulate the diffusion of germplasm into local seed stocks. Further research is needed on the interactions between formal and informal seed systems and grain markets in centers of crop origin and diversification

"Antelope": a hybrid-logic model checker for branching-time Boolean GRN analysis

<p>Abstract</p> <p>Background</p> <p>In Thomas' formalism for modeling gene regulatory networks (GRNs), <it>branching time</it>, where a state can have <it>more than one possible future</it>, plays a prominent role. By representing a certain degree of unpredictability, branching time can model several important phenomena, such as (a) asynchrony, (b) incompletely specified behavior, and (c) interaction with the environment. Introducing more than one possible future for a state, however, creates a difficulty for ordinary simulators, because <it>infinitely many </it>paths may appear, limiting ordinary simulators to statistical conclusions. <it>Model checkers </it>for branching time, by contrast, are able to prove properties in the presence of infinitely many paths.</p> <p>Results</p> <p>We have developed <it>Antelope </it>("Analysis of Networks through TEmporal-LOgic sPEcifications", <url>http://turing.iimas.unam.mx:8080/AntelopeWEB/</url>), a model checker for analyzing and constructing Boolean GRNs. Currently, software systems for Boolean GRNs use branching time almost exclusively for asynchrony. <it>Antelope</it>, by contrast, also uses branching time for incompletely specified behavior and environment interaction. We show the usefulness of modeling these two phenomena in the development of a Boolean GRN of the <it>Arabidopsis thaliana </it>root stem cell niche.</p> <p>There are two obstacles to a direct approach when applying model checking to Boolean GRN analysis. First, ordinary model checkers normally only verify whether or not a <it>given </it>set of model states has a given property. In comparison, a model checker for Boolean GRNs is preferable if it <it>reports </it>the set of states having a desired property. Second, for efficiency, the expressiveness of many model checkers is limited, resulting in the inability to express some interesting properties of Boolean GRNs.</p> <p><it>Antelope </it>tries to overcome these two drawbacks: Apart from reporting the set of all states having a given property, our model checker can express, at the expense of efficiency, some properties that ordinary model checkers (e.g., NuSMV) cannot. This additional expressiveness is achieved by employing a logic extending the standard Computation-Tree Logic (CTL) with hybrid-logic operators.</p> <p>Conclusions</p> <p>We illustrate the advantages of <it>Antelope </it>when (a) modeling incomplete networks and environment interaction, (b) exhibiting the set of all states having a given property, and (c) representing Boolean GRN properties with hybrid CTL.</p

Origins and Proliferative States of Human Oligodendrocyte Precursor Cells.

Human cerebral cortex size and complexity has increased greatly during evolution. While increased progenitor diversity and enhanced proliferative potential play important roles in human neurogenesis and gray matter expansion, the mechanisms of human oligodendrogenesis and white matter expansion remain largely unknown. Here, we identify EGFR-expressing "Pre-OPCs" that originate from outer radial glial cells (oRGs) and undergo mitotic somal translocation (MST) during division. oRG-derived Pre-OPCs provide an additional source of human cortical oligodendrocyte precursor cells (OPCs) and define a lineage trajectory. We further show that human OPCs undergo consecutive symmetric divisions to exponentially increase the progenitor pool size. Additionally, we find that the OPC-enriched gene, PCDH15, mediates daughter cell repulsion and facilitates proliferation. These findings indicate properties of OPC derivation, proliferation, and dispersion important for human white matter expansion and myelination

Unique Organization of the Nuclear Envelope in the Post-natal Quiescent Neural Stem Cells

Neural stem cells (B1 astrocytes; NSCs) in the adult ventricular-subventricular-zone (V-SVZ) originate in the embryo. Surprisingly, recent work has shown that B1 cells remain largely quiescent. They are reactivated postnatally to function as primary progenitors for neurons destined for the olfactory bulb and some corpus callosum oligodendrocytes. The cellular and molecular properties of quiescent B1 cells remain unknown. Here we found that a subpopulation of B1 cells has a unique nuclear envelope invagination specialization similar to envelope-limited chromatin sheets (ELCS), reported in certain lymphocytes and some cancer cells. Using molecular markers, [3H]thymidine birth-dating, and Ara-C, we found that B1 cells with ELCS correspond to quiescent NSCs. ELCS begin forming in embryonic radial glia cells and represent a specific nuclear compartment containing particular epigenetic modifications and telomeres. These results reveal a unique nuclear compartment in quiescent NSCs, which is useful for identifying these primary progenitors and study their gene regulation

Information flow during gene activation by signaling molecules: ethylene transduction in Arabidopsis cells as a study system

<p>Abstract</p> <p>Background</p> <p>We study root cells from the model plant <it>Arabidopsis thaliana </it>and the communication channel conformed by the ethylene signal transduction pathway. A basic equation taken from our previous work relates the probability of expression of the gene <it>ERF</it>1 to the concentration of ethylene.</p> <p>Results</p> <p>The above equation is used to compute the Shannon entropy (<it>H</it>) or degree of uncertainty that the genetic machinery has during the decoding of the message encoded by the ethylene specific receptors embedded in the endoplasmic reticulum membrane and transmitted into the nucleus by the ethylene signaling pathway. We show that the amount of information associated with the expression of the master gene <it>ERF</it>1 (Ethylene Response Factor 1) can be computed. Then we examine the system response to sinusoidal input signals with varying frequencies to determine if the cell can distinguish between different regimes of information flow from the environment. Our results demonstrate that the amount of information managed by the root cell can be correlated with the frequency of the input signal.</p> <p>Conclusion</p> <p>The ethylene signaling pathway cuts off very low and very high frequencies, allowing a window of frequency response in which the nucleus reads the incoming message as a sinusoidal input. Out of this window the nucleus reads the input message as an approximately non-varying one. From this frequency response analysis we estimate: a) the gain of the system during the synthesis of the protein ERF1 (~-5.6 dB); b) the rate of information transfer (0.003 bits) during the transport of each new ERF1 molecule into the nucleus and c) the time of synthesis of each new ERF1 molecule (~21.3 s). Finally, we demonstrate that in the case of the system of a single master gene (<it>ERF</it>1) and a single slave gene (<it>HLS</it>1), the total Shannon entropy is completely determined by the uncertainty associated with the expression of the master gene. A second proposition shows that the Shannon entropy associated with the expression of the <it>HLS</it>1 gene determines the information content of the system that is related to the interaction of the antagonistic genes <it>ARF</it>1, 2 and <it>HLS</it>1.</p

Modeling stochasticity and robustness in gene regulatory networks

Motivation: Understanding gene regulation in biological processes and modeling the robustness of underlying regulatory networks is an important problem that is currently being addressed by computational systems biologists. Lately, there has been a renewed interest in Boolean modeling techniques for gene regulatory networks (GRNs). However, due to their deterministic nature, it is often difficult to identify whether these modeling approaches are robust to the addition of stochastic noise that is widespread in gene regulatory processes. Stochasticity in Boolean models of GRNs has been addressed relatively sparingly in the past, mainly by flipping the expression of genes between different expression levels with a predefined probability. This stochasticity in nodes (SIN) model leads to over representation of noise in GRNs and hence non-correspondence with biological observations