ترغب بنشر مسار تعليمي؟ اضغط هنا

Analysis of interaction partners of H4 histone by a new proteomics approach

310   0   0.0 ( 0 )
 نشر من قبل Vasily Ogryzko V
 تاريخ النشر 2009
  مجال البحث علم الأحياء
والبحث باللغة English




اسأل ChatGPT حول البحث

We describe a modification of the TAP method for purification and analysis of multiprotein complexes, termed here DEF-TAP (for Differential Elution Fractionation after Tandem Affinity Purification). Its essential new feature is the use for last purification step of 6XHis-Ni++ interaction, which is resistant to a variety of harsh washing conditions, including high ionic strength and presence of organic solvents. This allows us to use various fractionation schemes before the protease digestion, which is expected to improve the coverage of the analysed protein mixture and also to provide an additional insight into the structure of the purified macromolecular complex and the nature of protein-protein interactions involved. We illustrate our new approach by analysis of soluble nuclear complexes containing histone H4 purified from HeLa cells. In particular, we observed different fractionation patterns of HAT1 and RbAp46 proteins as compared to RbAp48 protein, all identified as interaction partners of H4 histone. In addition, we report all components of the licensing MCM2-7 complex and the apoptosis-related DAXX protein among the interaction partners of the soluble H4. Finally, we show that HAT1 requires N-terminal tail of H4 for its stable association with this histone.



قيم البحث

اقرأ أيضاً

93 - J. M. Deutsch 2018
The evolution of the genome has led to very sophisticated and complex regulation. Because of the abundance of non-coding RNA (ncRNA) in the cell, different species will promiscuously associate with each other, suggesting collective dynamics similar t o artificial neural networks. Here we present a simple mechanism allowing ncRNA to perform computations equivalent to neural network algorithms such as Boltzmann machines and the Hopfield model. The quantities analogous to the neural couplings are the equilibrium constants between different RNA species. The relatively rapid equilibration of RNA binding and unbinding is regulated by a slower process that degrades and creates new RNA. The model requires that the creation rate for each species be an increasing function of the ratio of total to unbound RNA. Similar mechanisms have already been found to exist experimentally for ncRNA regulation. With the overall concentration of RNA regulated, equilibrium constants can be chosen to store many different patterns, or many different input-output relations. The network is also quite insensitive to random mutations in equilibrium constants. Therefore one expects that this kind of mechanism will have a much higher mutation rate than ones typically regarded as being under evolutionary constraint.
Transforming Growth Factor-beta (TGF-beta) signalling is an important regulator of cellular growth and differentiation. The principal intracellular mediators of TGF-beta signalling are the Smad proteins, which upon TGF-beta stimulation accumulate in the nucleus and regulate transcription of target genes. To investigate the mechanisms of Smad nuclear accumulation, we developed a simple mathematical model of canonical Smad signalling. The model was built using both published data and our experimentally determined cellular Smad concentrations (isoforms 2, 3, and 4). We found in mink lung epithelial cells that Smad2 (8.5-12 x 10^4 molecules/cell) was present in similar amounts to Smad4 (9.3-12 x 10^4 molecules/cell), while both were in excess of Smad3 (1.1-2.0 x 10^4 molecules/cell). Variation of the model parameters and statistical analysis showed that Smad nuclear accumulation is most sensitive to parameters affecting the rates of RSmad phosphorylation and dephosphorylation and Smad complex formation/dissociation in the nucleus. Deleting Smad4 from the model revealed that rate-limiting phospho-R-Smad dephosphorylation could be an important mechanism for Smad nuclear accumulation. Furthermore, we observed that binding factors constitutively localised to the nucleus do not efficiently mediate Smad nuclear accumulation if dephosphorylation is rapid. We therefore conclude that an imbalance in the rates of R-Smad phosphorylation and dephosphorylation is likely an important mechanism of Smad nuclear accumulation during TGF-beta signalling.
The primary activation of the epidermal growth factor receptor (EGFR) has become a prominent target for molecular therapies against several forms of cancer. But despite considerable progress during the last years, many of its aspects remain poorly un derstood. Experiments on lateral spreading of receptor activity into ligand-free regions challenge the current standard models of EGFR activation. Here, we propose and study a theoretical model, which explains spreading into ligand-free regions without introducing any new, unknown kinetic parameters. The model exhibits bistability of activity, induced by a generic reaction mechanism, which consists of activation via dimerization and deactivation via a Michaelis-Menten reaction. It possesses slow propagating front solutions and faster initial transients. We analyze relevant experiments and find that they are in quantitative accordance with the fast initial modes of spreading, but not with the slow propagating front. We point out that lateral spreading of activity is linked to pathological levels of persistent receptor activity as observed in cancer cells and exemplify uses of this link for the design and quick evaluation of molecular therapies targeting primary activation of EGFR.
Signaling pathways serve to communicate information about extracellular conditions into the cell, to both the nucleus and cytoplasmic processes to control cell responses. Genetic mutations in signaling network components are frequently associated wit h cancer and can result in cells acquiring an ability to divide and grow uncontrollably. Because signaling pathways play such a significant role in cancer initiation and advancement, their constituent proteins are attractive therapeutic targets. In this review, we discuss how signaling pathway modeling can assist with identifying effective drugs for treating diseases, such as cancer. An achievement that would facilitate the use of such models is their ability to identify controlling biochemical parameters in signaling pathways, such as molecular abundances and chemical reaction rates, because this would help determine effective points of attack by therapeutics.
Enzymes within biochemical pathways are often colocalized, yet the consequences of specific spatial enzyme arrangements remain poorly understood. We study the impact of enzyme arrangement on reaction efficiency within a reaction-diffusion model. The optimal arrangement transitions from a cluster to a distributed profile as a single parameter, which controls the probability of reaction versus diffusive loss of pathway intermediates, is varied. We introduce the concept of enzyme exposure to explain how this transition arises from the stochastic nature of molecular reactions and diffusion.
التعليقات
جاري جلب التعليقات جاري جلب التعليقات
سجل دخول لتتمكن من متابعة معايير البحث التي قمت باختيارها
mircosoft-partner

هل ترغب بارسال اشعارات عن اخر التحديثات في شمرا-اكاديميا