Background: ZFP57 is a maternal-zygotic effect gene that maintains genomic imprinting in mouse embryos. Results: KAP1 facilitates the interaction between ZFP57 and DNA methyltransferases. The KRAB box of ZFP57 is required for maintaining DNA methylation imprint in ES cells. Conclusion: ZFP57 recruits DNA methyltransferases and maintains DNA methylation imprint through KRAB box-mediated interaction.Significance: This work implies that ZFP57 recruits DNA methyltransferases via KAP1 to maintain DNA methylation imprint.

Stable isotope labeling is widely used to encode and quantify proteins in mass-spectrometry-based proteomics. We compared metabolic labeling with stable isotope labeling by amino acids in cell culture (SILAC) and chemical labeling by stable isotope dimethyl labeling and find that they have comparable accuracy and quantitative dynamic range in unfractionated proteome analyses and affinity pull-down experiments. Analyzing SILAC- and dimethyl-labeled samples together in single liquid chromatography–mass spectrometric analyses minimizes differences under analytical conditions, allowing comparisons of quantitative errors introduced during sample processing. We find that SILAC is more reproducible than dimethyl labeling. Because proteins from metabolically labeled populations can be combined before proteolytic digestion, SILAC is particularly suited to studies with extensive sample processing, such as fractionation and enrichment of peptides with post-translational modifications. We compared both methods in pull-down experiments using a kinase inhibitor, dasatinib, and tagged GRB2-SH2 protein as affinity baits. We describe a StageTip dimethyl-labeling protocol that we applied to in-solution and in-gel protein digests. Comparing the impact of post-digest isotopic labeling on quantitative accuracy, we demonstrate how specific experimental designs can benefit most from metabolic labeling approaches like SILAC and situations where chemical labeling by stable isotope-dimethyl labeling can be a practical alternative.

Micro-dissection of rat brain into various regions is extremely important for the study of different neurodegenerative diseases. This video demonstrates micro-dissection of four major brain regions include olfactory bulb, frontal cortex, striatum and hippocampus in fresh rat brain tissue. Useful tips for quick removal of respective regions to avoid RNA and protein degradation of the tissue are given. ProtocolStep 1Sacrifice the rat according to established protocols. Remove the brain from the skull and rinse it in ice cold DEPC treated Milli Q water to remove any surface blood.Step 2 Place on cold metal plate. Cut the brain bi-half into right and left hemisphere. Step 3Collect the olfactory bulb right after the first cut. Flash freeze the specimen in liquid nitrogen and store at -80°C.

A-kinase anchoring proteins (AKAPs) shape second-messenger signaling responses by constraining protein kinase A (PKA) at precise intracellular locations. A defining feature of AKAPs is a helical region that binds to regulatory subunits (RII) of PKA. Mining patient-derived databases has identified 42 nonsynonymous SNPs in the PKA-anchoring helices of five AKAPs. Solid-phase RII binding assays confirmed that 21 of these amino acid substitutions disrupt PKA anchoring. The most deleterious side-chain modifications are situated toward C-termini of AKAP helices. More extensive analysis was conducted on a valine-to-methionine variant in the PKA-anchoring helix of AKAP18. Molecular modeling indicates that additional density provided by methionine at position 282 in the AKAP18γ isoform deflects the pitch of the helical anchoring surface outward by 6.6°. Fluorescence polarization measurements show that this subtle topological change reduces RII-binding affinity 8.8-fold and impairs cAMP responsive potentiation of L-type Ca2+ currents in situ. Live-cell imaging of AKAP18γ V282M-GFP adducts led to the unexpected discovery that loss of PKA anchoring promotes nuclear accumulation of this polymorphic variant. Targeting proceeds via a mechanism whereby association with the PKA holoenzyme masks a polybasic nuclear localization signal on the anchoring protein. This led to the discovery of AKAP18ε: an exclusively nuclear isoform that lacks a PKA-anchoring helix. Enzyme-mediated proximity-proteomics reveal that compartment-selective variants of AKAP18 associate with distinct binding partners. Thus, naturally occurring PKA-anchoring-defective AKAP variants not only perturb dissemination of local second-messenger responses, but also may influence the intracellular distribution of certain AKAP18 isoforms.

In this paper, an automatically skin cancer classification system is developed and the relationship of skin cancer image across different type of neural network are studied with different types of preprocessing.. The collected images are feed into the system, and across different image processing procedure to enhance the image properties. Then the normal skin is removed from the skin affected area and the cancer cell is left in the image. Useful information can be extracted from these images and pass to the classification system for training and testing. Recognition accuracy of the 3layers back-propagation neural network classifier is 89.9% and auto-associative neural network is 80.8% in the image database that include dermoscopy photo and digital photo

Epigenetic reprogramming occurs during oocyte growth in mice, a stage where a number of important events are occurring, including transcription of maternal mRNAs for storage in the mature egg, global transcriptional silencing and the acquisition of meiotic competence. Oocyte growth occurs in conjunction with follicular development over a period of many days. The signals involved in initiating different stages in oocyte and follicular development and the concurrent epigenetic changes are poorly understood. Here we examine the role of stem cell factor (SCF or Kit ligand) on the early- to mid-stages of oocyte growth and on DNA methyltransferase expression and function using a one-step in vitro culture system. Our results show that SCF promotes early oocyte growth and development to the multilaminar follicle stage. Oocyte growth is sufficient to trigger transcription of Dnmt1 and Dnmt3L from dedicated oocyte promoters, and we show that eggs undergoing growth in the absence of follicle development in Foxo3 mutants show elevated levels of Dnmt1. The methyltransferase proteins undergo sequential relocalisation in the oocyte, with DNMT1 being exported from the nucleus at the bilaminar follicle stage, while DNMT3A is transported into the nucleus at the multilaminar stage, indicating an important role for trafficking in controlling imprinting. SCF is thought to signal partly through the phophostidylinositol 3 (PI3) kinase pathway: inhibiting this path was previously shown to prevent FOXO3 nuclear export and we could show here that it also prevented DNMT1 export. Some oocytes reached full size (70 microM) in this in vitro system, but no secondary follicles were formed, most likely due to failure of the thecal layer to form properly. De novo methylation of imprinted genes was seen in some oocyte cultures, with methylation levels being highest for Snrpn and Igf2r which are methylated early in vivo, while Peg1, which is methylated late, showed little or no methylation. SCF treatment did not increase the number of cultures showing methylation. We saw no evidence for de novo methylation of IAP repeats in our cultures. These results suggest that while methyltransferase loading is triggered by oocyte growth, in which SCF plays an important role, complete methylation probably requires progression to the secondary follicle stage and is unlikely to be affected by SCF.

No abstract

Interest in protein methylation has grown rapidly in recent years. Mass spectrometry-based proteomics is ideally suited to characterize protein modifications, but the multiplicity of methylated residues and the lack of efficient methods to enrich methylated proteins have limited the proteomic identification of protein methylation sites. In this protocol, we compare two metabolic labeling approaches, stable isotope labeling by amino acids in cell culture (SILAC) and its variant heavy methyl SILAC, for studying protein methylation. Instead of heavy lysine and arginine in the typical SILAC experiment, heavy methyl SILAC uses (13)C, (2)H methionine as the labeling amino acid. As cells convert methionine to S-adenosylmethionine, heavy methyl SILAC encodes a 4 Da mass tag for each methyl group, distinguishing between degrees of methylation is possible from mass difference alone. We provide a protocol for SILAC-based analyses of protein methylation and highlight the strengths and weaknesses of each method for targeted and proteomic analyses.