A case-control study of apolipoprotein E genotypes in Alzheimer's disease associated with Down syndrome.

The prevalence of clinical signs and neuropathological findings of Alzheimer's disease (AD) is high in Down's syndrome (DS). In the general population, the apolipoprotein E (ApoE) epsilon 4 isoform is an important risk for AD. We studied the allelic frequencies of ApoE in 26 DS cases fulfilling clinical diagnostic criteria for AD and in 26 DS controls matched for age, sex, and premorbid level of mental retardation. A meta-analysis of data available in the literature was used for comparison with allele frequencies in other AD and control populations. ApoE type 2, 3, or 4 allele frequencies were not significantly different in AD-DS cases and DS controls. The ApoE epsilon 4 frequency in DS cases with AD (0.14; CI, 0.06-0.26) was significantly lower than in any other AD population studied so far and it is within the range of nondemented controls from the general population. These findings suggest that ApoE epsilon 4 does not significantly affect the pathogenesis of AD in DS patients

Complex type 4 structure changing dynamics of digital agents: Nash equilibria of a game with arms race in innovations

The new digital economy has renewed interest in how digital agents can innovate. This follows the legacy of John von Neumann dynamical systems theory on complex biological systems as computation. The Gödel-Turing-Post (GTP) logic is shown to be necessary to generate innovation based structure changing Type 4 dynamics of the Wolfram-Chomsky schema. Two syntactic procedures of GTP logic permit digital agents to exit from listable sets of digital technologies to produce novelty and surprises. The first is meta-analyses or offline simulations. The second is a fixed point with a two place encoding of negation or opposition, referred to as the Gödel sentence. It is postulated that in phenomena ranging from the genome to human proteanism, the Gödel sentence is a ubiquitous syntactic construction without which escape from hostile agents qua the Liar is impossible and digital agents become entrained within fixed repertoires. The only recursive best response function of a 2-person adversarial game that can implement strategic innovation in lock-step formation of an arms race is the productive function of the Emil Post [58] set theoretic proof of the Gödel incompleteness result. This overturns the view of game theorists that surprise and innovation cannot be a Nash equilibrium of a game

Prospective functional classification of all possible missense variants in PPARG.

Clinical exome sequencing routinely identifies missense variants in disease-related genes, but functional characterization is rarely undertaken, leading to diagnostic uncertainty. For example, mutations in PPARG cause Mendelian lipodystrophy and increase risk of type 2 diabetes (T2D). Although approximately 1 in 500 people harbor missense variants in PPARG, most are of unknown consequence. To prospectively characterize PPARγ variants, we used highly parallel oligonucleotide synthesis to construct a library encoding all 9,595 possible single-amino acid substitutions. We developed a pooled functional assay in human macrophages, experimentally evaluated all protein variants, and used the experimental data to train a variant classifier by supervised machine learning. When applied to 55 new missense variants identified in population-based and clinical sequencing, the classifier annotated 6 variants as pathogenic; these were subsequently validated by single-variant assays. Saturation mutagenesis and prospective experimental characterization can support immediate diagnostic interpretation of newly discovered missense variants in disease-related genes.This work was supported by grants from the National Institute of Diabetes and Digestive and Kidney Diseases (1K08DK102877-01, to A.R.M.; 1R01DK097768-01, to D.A.), NIH/Harvard Catalyst (1KL2TR001100-01, to A.R.M.), the Broad Institute (SPARC award, to A.R.M. and T.M.), and the Wellcome Trust (095564, to K.C.; 107064, to D.B.S.).This is the author accepted manuscript. The final version is available from Nature Publishing Group via http://dx.doi.org/10.1038/ng.370

Presence of a basic secretory protein in xylem sap and shoots of poplar in winter and its physicochemical activities against winter environmental conditions

XSP25, previously shown to be the most abundant hydrophilic protein in xylem sap of Populus nigra in winter, belongs to a secretory protein family in which the arrangement of basic and acidic amino acids is conserved between dicotyledonous and monocotyledonous species. Its gene expression was observed at the same level in roots and shoots under long-day conditions, but highly induced under short-day conditions and at low temperatures in roots, especially in endodermis and xylem parenchyma in the root hair region of Populus trichocarpa, and its protein level was high in dormant buds, but not in roots or branches. Addition of recombinant PtXSP25 protein mitigated the denaturation of lactate dehydrogenase by drying, but showed only a slight effect on that caused by freeze–thaw cycling. Recombinant PtXSP25 protein also showed ice recrystallization inhibition activity to reduce the size of ice crystals, but had no antifreezing activity. We suggest that PtXSP25 protein produced in shoots and/or in roots under short-day conditions and at non-freezing low temperatures followed by translocation via xylem sap to shoot apoplast may protect the integrity of the plasma membrane and cell wall functions from freezing and drying damage in winter environmental conditions

Functional modularity of nuclear hormone receptors in a Caenorhabditis elegans metabolic gene regulatory network

We present the first gene regulatory network (GRN) that pertains to post-developmental gene expression. Specifically, we mapped a transcription regulatory network of Caenorhabditis elegans metabolic gene promoters using gene-centered yeast one-hybrid assays. We found that the metabolic GRN is enriched for nuclear hormone receptors (NHRs) compared with other gene-centered regulatory networks, and that these NHRs organize into functional network modules.The NHR family has greatly expanded in nematodes; C. elegans has 284 NHRs, whereas humans have only 48. We show that the NHRs in the metabolic GRN have metabolic phenotypes, suggesting that they do not simply function redundantly.The mediator subunit MDT-15 preferentially interacts with NHRs that occur in the metabolic GRN.We describe an NHR circuit that responds to nutrient availability and propose a model for the evolution and organization of NHRs in C. elegans metabolic regulatory networks

Support Vector Machines and Kernels for Computational Biology

ISSN:1553-734XISSN:1553-735

Computing with bacterial constituents, cells and populations: from bioputing to bactoputing

The relevance of biological materials and processes to computing—aliasbioputing—has been explored for decades. These materials include DNA, RNA and proteins, while the processes include transcription, translation, signal transduction and regulation. Recently, the use of bacteria themselves as living computers has been explored but this use generally falls within the classical paradigm of computing. Computer scientists, however, have a variety of problems to which they seek solutions, while microbiologists are having new insights into the problems bacteria are solving and how they are solving them. Here, we envisage that bacteria might be used for new sorts of computing. These could be based on the capacity of bacteria to grow, move and adapt to a myriad different fickle environments both as individuals and as populations of bacteria plus bacteriophage. New principles might be based on the way that bacteria explore phenotype space via hyperstructure dynamics and the fundamental nature of the cell cycle. This computing might even extend to developing a high level language appropriate to using populations of bacteria and bacteriophage. Here, we offer a speculative tour of what we term bactoputing, namely the use of the natural behaviour of bacteria for calculating

Epigenetic Features of Human Mesenchymal Stem Cells Determine Their Permissiveness for Induction of Relevant Transcriptional Changes by SYT-SSX1

BACKGROUND: A characteristic SYT-SSX fusion gene resulting from the chromosomal translocation t(X;18)(p11;q11) is detectable in almost all synovial sarcomas, a malignant soft tissue tumor widely believed to originate from as yet unidentified pluripotent stem cells. The resulting fusion protein has no DNA binding motifs but possesses protein-protein interaction domains that are believed to mediate association with chromatin remodeling complexes. Despite recent advances in the identification of molecules that interact with SYT-SSX and with the corresponding wild type SYT and SSX proteins, the mechanisms whereby the SYT-SSX might contribute to neoplastic transformation remain unclear. Epigenetic deregulation has been suggested to be one possible mechanism. METHODOLOGY/PRINCIPAL FINDINGS: We addressed the effect of SYT/SSX expression on the transcriptome of four independent isolates of primary human bone marrow mesenchymal stem cells (hMSC). We observed transcriptional changes similar to the gene expression signature of synovial sarcoma, principally involving genes whose regulation is linked to epigenetic factors, including imprinted genes, genes with transcription start sites within a CpG island and chromatin related genes. Single population analysis revealed hMSC isolate-specific transcriptional changes involving genes that are important for biological functions of stem cells as well as genes that are considered to be molecular markers of synovial sarcoma including IGF2, EPHRINS, and BCL2. Methylation status analysis of sequences at the H19/IGF2 imprinted locus indicated that distinct epigenetic features characterize hMSC populations and condition the transcriptional effects of SYT-SSX expression. CONCLUSIONS/SIGNIFICANCE: Our observations suggest that epigenetic features may define the cellular microenvironment in which SYT-SSX displays its functional effects

Dpp Signaling Activity Requires Pentagone to Scale with Tissue Size in the Growing Drosophila Wing Imaginal Disc

The activity of the Dpp morphogen adapts to tissue size in the growing Drosophila wing imaginal disc, and Pentagone, an important secreted feedback regulator of the Dpp pathway, is required for this adaptation

The Impact of Multifunctional Genes on "Guilt by Association" Analysis

Many previous studies have shown that by using variants of “guilt-by-association”, gene function predictions can be made with very high statistical confidence. In these studies, it is assumed that the “associations” in the data (e.g., protein interaction partners) of a gene are necessary in establishing “guilt”. In this paper we show that multifunctionality, rather than association, is a primary driver of gene function prediction. We first show that knowledge of the degree of multifunctionality alone can produce astonishingly strong performance when used as a predictor of gene function. We then demonstrate how multifunctionality is encoded in gene interaction data (such as protein interactions and coexpression networks) and how this can feed forward into gene function prediction algorithms. We find that high-quality gene function predictions can be made using data that possesses no information on which gene interacts with which. By examining a wide range of networks from mouse, human and yeast, as well as multiple prediction methods and evaluation metrics, we provide evidence that this problem is pervasive and does not reflect the failings of any particular algorithm or data type. We propose computational controls that can be used to provide more meaningful control when estimating gene function prediction performance. We suggest that this source of bias due to multifunctionality is important to control for, with widespread implications for the interpretation of genomics studies