Solute Carrier Family of the Organic Anion-Transporting Polypeptides 1A2- Madin-Darby Canine Kidney II: A Promising In Vitro System to Understand the Role of Organic Anion-Transporting Polypeptide 1A2 in Blood-Brain Barrier Drug Penetration.

Organic anion-transporting polypeptide (OATP) 1A2 has the potential to be a target for central nervous system drug delivery due to its luminal localization at the human blood-brain barrier and broad substrate specificity. We found OATP1A2 mRNA expression in the human brain to be comparable to breast cancer resistance protein and OATP2B1 and much higher than P-glycoprotein (P-gp), and confirmed greater expression in the brain relative to other tissues. The goal of this study was to establish a model system to explore OATP1A2-mediated transcellular transport of substrate drugs and the interplay with P-gp. In vitro (human embryonic kidney 293 cells stably expressing Oatp1a4, the closest murine isoform) and in vivo (naïve and Oatp1a4 knock-out mice) studies with OATP1A2 substrate triptan drugs demonstrated that these drugs were not Oatp1a4 substrates. This species difference demonstrates that the rodent is not a good model to investigate the active brain uptake of potential OATP1A2 substrates. Thus, we constructed a novel OATP1A2 expressing Madin-Darby canine kidney (MDCK) II wild type and an MDCKII-multidrug resistance protein 1 (MDR1) system using BacMam virus transduction. The spatial expression pattern of OATP1A2 after transduction in MDCKII-MDR1 cells was superimposed to P-gp, confirming apical membrane localization. OATP1A2-mediated uptake of zolmitriptan, rosuvastatin, and fexofenadine across monolayers increased with increasing OATP1A2 protein expression. OATP1A2 counteracted P-gp efflux for cosubstrates zolmitriptan and fexofenadine. A three-compartment model incorporating OATP1A2-mediated influx was used to quantitatively describe the time- and concentration-dependent apical-to-basolateral transcellular transport of rosuvastatin across OATP1A2 expressing the MDCKII monolayer. This novel, simple and versatile experimental system is useful for understanding the contribution of OATP1A2-mediated transcellular transport across barriers, such as the blood-brain barrier.

System-level feedbacks make the anaphase switch irreversible.

The mitotic checkpoint prevents a eukaryotic cell from commencing to separate its replicated genome into two daughter cells (anaphase) until all of its chromosomes are properly aligned on the metaphase plate, with the two copies of each chromosome attached to opposite poles of the mitotic spindle. The mitotic checkpoint is exquisitely sensitive in that a single unaligned chromosome, 1 of a total of ~50, is sufficient to delay progression into anaphase; however, when the last chromosome comes into alignment on the metaphase plate, the mitotic checkpoint is quickly satisfied, and the replicated chromosomes are rapidly partitioned to opposite poles of the dividing cell. The mitotic checkpoint is also curious in the sense that, before metaphase alignment, chromosomes that are not being pulled in opposite directions by the mitotic spindle activate the checkpoint, but during anaphase, these same tensionless chromosomes can no longer activate the checkpoint. These and other puzzles associated with the mitotic checkpoint are addressed by a proposed molecular mechanism, which involves two positive feedback loops that create a bistable response of the checkpoint to chromosomal tension.

BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models.

BACKGROUND: Quantitative models of biochemical and cellular systems are used to answer a variety of questions in the biological sciences. The number of published quantitative models is growing steadily thanks to increasing interest in the use of models as well as the development of improved software systems and the availability of better, cheaper computer hardware. To maximise the benefits of this growing body of models, the field needs centralised model repositories that will encourage, facilitate and promote model dissemination and reuse. Ideally, the models stored in these repositories should be extensively tested and encoded in community-supported and standardised formats. In addition, the models and their components should be cross-referenced with other resources in order to allow their unambiguous identification. DESCRIPTION: BioModels Database http://www.ebi.ac.uk/biomodels/ is aimed at addressing exactly these needs. It is a freely-accessible online resource for storing, viewing, retrieving, and analysing published, peer-reviewed quantitative models of biochemical and cellular systems. The structure and behaviour of each simulation model distributed by BioModels Database are thoroughly checked; in addition, model elements are annotated with terms from controlled vocabularies as well as linked to relevant data resources. Models can be examined online or downloaded in various formats. Reaction network diagrams generated from the models are also available in several formats. BioModels Database also provides features such as online simulation and the extraction of components from large scale models into smaller submodels. Finally, the system provides a range of web services that external software systems can use to access up-to-date data from the database. CONCLUSIONS: BioModels Database has become a recognised reference resource for systems biology. It is being used by the community in a variety of ways; for example, it is used to benchmark different simulation systems, and to study the clustering of models based upon their annotations. Model deposition to the database today is advised by several publishers of scientific journals. The models in BioModels Database are freely distributed and reusable; the underlying software infrastructure is also available from SourceForge https://sourceforge.net/projects/biomodels/ under the GNU General Public License.

System-level feedbacks control cell cycle progression.

Repetitive cell cycles, which are essential to the perpetuation of life, are orchestrated by an underlying biochemical reaction network centered around cyclin-dependent protein kinases (Cdks) and their regulatory subunits (cyclins). Oscillations of Cdk1/CycB activity between low and high levels during the cycle trigger DNA replication and mitosis in the correct order. Based on computational modeling, we proposed that the low and the high kinase activity states are alternative stable steady states of a bistable Cdk-control system. Bistability is a consequence of system-level feedback (positive and double-negative feedback signals) in the underlying control system. We have also argued that bistability underlies irreversible transitions between low and high Cdk activity states and thereby ensures directionality of cell cycle progression.