Project description:De novo methylation of CpG islands is seen in many tumors, but the general rules governing this process are not known. By analyzing DNA from tumors, as well as normal tissues, and by utilizing a wide range of published data, we have been able to identify a well-defined set of tumor targets, each of which has its own M-bM-^@M-^\coefficientM-bM-^@M-^] of methylation that is largely determined by its inherent relative ability to recruit the polycomb complex. This pattern is initially formed by a slow process of de novo methylation that occurs during aging and then undergoes expansion early in tumorigenesis, where it may play a role as an inhibitor of development-associated gene activation. We also demonstrate that DNA methylation patterns can be used to diagnose the primary tissue source of tumor metastases. CpG-methylated genomic DNA was enriched using a methyl-DNA immunoprecipitation (mDIP) assay. DNA from the input and bound (enriched) DNA for each sample were labeled and hybridized on the array to define the methylation state of each region.
Project description:De novo methylation of CpG islands is seen in many tumors, but the general rules governing this process are not known. By analyzing DNA from tumors, as well as normal tissues, and by utilizing a wide range of published data, we have been able to identify a well-defined set of tumor targets, each of which has its own “coefficient” of methylation that is largely determined by its inherent relative ability to recruit the polycomb complex. This pattern is initially formed by a slow process of de novo methylation that occurs during aging and then undergoes expansion early in tumorigenesis, where it may play a role as an inhibitor of development-associated gene activation. We also demonstrate that DNA methylation patterns can be used to diagnose the primary tissue source of tumor metastases.
Project description:BackgroundCarbonyl derivatives are mainly formed by direct metal-catalysed oxidation (MCO) attacks on the amino-acid side chains of proline, arginine, lysine and threonine residues. For reasons unknown, only some proteins are prone to carbonylation.Methodology/principal findingswe used mass spectrometry analysis to identify carbonylated sites in: BSA that had undergone in vitro MCO, and 23 carbonylated proteins in Escherichia coli. The presence of a carbonylated site rendered the neighbouring carbonylatable site more prone to carbonylation. Most carbonylated sites were present within hot spots of carbonylation. These observations led us to suggest rules for identifying sites more prone to carbonylation. We used these rules to design an in silico model (available at http://www.lcb.cnrs-mrs.fr/CSPD/), allowing an effective and accurate prediction of sites and of proteins more prone to carbonylation in the E. coli proteome.Conclusions/significanceWe observed that proteins evolve to either selectively maintain or lose predicted hot spots of carbonylation depending on their biological function. As our predictive model also allows efficient detection of carbonylated proteins in Bacillus subtilis, we believe that our model may be extended to direct MCO attacks in all organisms.
Project description:Coinfection of a host by multiple parasite species has important epidemiological and clinical implications. However, the direction and magnitude of effects vary considerably among systems, and, until now, there has been no general framework within which to explain this variation. Community ecology has great potential for application to such problems in biomedicine. Here, metaanalysis of data from 54 experiments on laboratory mice reveals that basic ecological rules govern the outcome of coinfection across a broad spectrum of parasite taxa. Specifically, resource-based ("bottom-up") and predator-based ("top-down") control mechanisms combined to determine microparasite population size in helminth-coinfected hosts. Coinfection imposed bottom-up control (resulting in decreased microparasite density) when a helminth that causes anemia was paired with a microparasite species that requires host red blood cells. At the same time, coinfection impaired top-down control of microparasites by the immune system: the greater the helminth-induced suppression of the inflammatory cytokine interferon (IFN)-gamma, the greater the increase in microparasite density. These results suggest that microparasite population growth will be most explosive when underlying helminths do not impose resource limitations but do strongly modulate IFN-gamma responses. Surprisingly simple rules and an ecological framework within which to analyze biomedical data thus emerge from analysis of this dataset. Through such an interdisciplinary lens, predicting the outcome of coinfection may become tractable.
Project description:One of the most fundamental but yet unanswered questions in the synthesis of zeolites and zeolite-like materials is whether or not any parameter controlling the microporosity of the crystallized product from synthesis mixtures with feasible chemical compositions exists. Here we report that an experimentally optimized parameter (ca. 3.3 ≤ MOH/P2O5 ≤ 5.3, where M is alkali metal ions) is the criterion bringing about the successful formation of various high-charge-density silicoaluminophosphate (SAPO) and zincoaluminophosphate (ZnAPO) molecular sieves, without the aid of organic structure-directing agents. The materials obtained using this empirical concept include SAPO molecular sieves with CHA and LTA topologies, as well as a SAPO FAU/EMT intergrowth, and ZnAPO ones with CZP and SOD topologies. This study demonstrates the existence of an essential factor determining not only phase selectivity but also microporosity (0.3-2 nm) in the synthesis of zeotypes with charged frameworks which may offer interesting opportunities for more efficiently producing novel zeolite structures and/or compositions.
Project description:Ribosomopathies are cell-type-specific pathologies related to a ribosomal protein (RP) gene insult. The 5q- syndrome is a somatic ribosomopathy linked to RPS14 gene haploinsufficiency and characterized by a prominent erythroid hypoplasia. Using quantitative proteomic, we show that GATA1 protein expression is low in shRPS14 cells in which ribosome quantities are diminished. Here, we investigated the cause of low GATA1 protein expression in limiting ribosome availability. A global analysis of translation in RPs deficiencies highlights the rules that drive translation selectivity. We demonstrate that in addition of the transcript length, a high codon adaptation index (CAI) and a highly structured 3’UTR are the key characteristics for a selective translation. An integrated analysis of transcriptome and proteome confirms that the post-transcriptional regulations of gene expression are directly linked to the criteria governing the translational selectivity. In particular, these criteria explain GATA1 translation default with unprecedented precision. More generally, the proteins that accumulate along normal erythropoiesis share the determinants of translation selectivity revealed by the conditions of limiting ribosome availability. We performed translatome expression profiling of cells infected with shRPS14 or shSCR
Project description:Similar universal phenomena can emerge in different complex systems when those systems share a common symmetry in their governing laws. In physical systems operating near a critical phase transition, the governing physical laws obey a fractal symmetry; they are the same whether considered at fine or coarse scales. This scale-change symmetry is responsible for universal critical phenomena found across diverse systems. Experiments suggest that the cerebral cortex can also operate near a critical phase transition. Thus we hypothesize that the laws governing cortical dynamics may obey scale-change symmetry. Here we develop a practical approach to test this hypothesis. We confirm, using two different computational models, that neural dynamical laws exhibit scale-change symmetry near a dynamical phase transition. Moreover, we show that as a mouse awakens from anesthesia, scale-change symmetry emerges. Scale-change symmetry of the rules governing cortical dynamics may explain observations of similar critical phenomena across diverse neural systems.
Project description:A fundamental question in protein science is where allosteric hotspots - residues critical for allosteric signaling - are located, and what properties differentiate them. We carried out deep mutational scanning (DMS) of four homologous bacterial allosteric transcription factors (aTFs) to identify hotspots and built a machine learning model with this data to glean the structural and molecular properties of allosteric hotspots. We found hotspots to be distributed protein-wide rather than being restricted to 'pathways' linking allosteric and active sites as is commonly assumed. Despite structural homology, the location of hotspots was not superimposable across the aTFs. However, common signatures emerged when comparing hotspots coincident with long-range interactions, suggesting that the allosteric mechanism is conserved among the homologs despite differences in molecular details. Machine learning with our large DMS datasets revealed global structural and dynamic properties to be a strong predictor of whether a residue is a hotspot than local and physicochemical properties. Furthermore, a model trained on one protein can predict hotspots in a homolog. In summary, the overall allosteric mechanism is embedded in the structural fold of the aTF family, but the finer, molecular details are sequence-specific.
Project description:Septins are conserved GTP-binding proteins that assemble into lateral diffusion barriers and molecular scaffolds. Vertebrate genomes contain 9-17 septin genes that encode both ubiquitous and tissue-specific septins. Expressed septins may assemble in various combinations through both heterotypic and homotypic G-domain interactions. However, little is known regarding assembly states of mammalian septins and mechanisms directing ordered assembly of individual septins into heteromeric units, which is the focus of this study. Our analysis of the septin system in cells lacking or overexpressing selected septins reveals interdependencies coinciding with previously described homology subgroups. Hydrodynamic and single-particle data show that individual septins exist solely in the context of stable six- to eight-subunit core heteromers, all of which contain SEPT2 and SEPT6 subgroup members and SEPT7, while heteromers comprising more than six subunits also contain SEPT9. The combined data suggest a generic model for how the temporal order of septin assembly is homology subgroup-directed, which in turn determines the subunit arrangement of native heteromers. Because mammalian cells normally express multiple members and/or isoforms of some septin subgroups, our data also suggest that only a minor fraction of native heteromers are arranged as perfect palindromes.
Project description:G protein-coupled receptors (GPCRs) convert extracellular stimuli into intracellular signaling by coupling to heterotrimeric G proteins of four classes: Gi/o, Gq, Gs, and G12/13. However, our understanding of the G protein selectivity of GPCRs is incomplete. Here, we quantitatively measure the enzymatic activity of GPCRs in living cells and reveal the G protein selectivity of 124 GPCRs with the exact rank order of their G protein preference. Using this information, we establish a classification of GPCRs by functional selectivity, discover the existence of a G12/13-coupled receptor, G15-coupled receptors, and a variety of subclasses for Gi/o-, Gq-, and Gs-coupled receptors, culminating in development of the predictive algorithm of G protein selectivity. We further identify the structural determinants of G protein selectivity, allowing us to synthesize non-existent GPCRs with de novo G protein selectivity and efficiently identify putative pathogenic variants.