DNA-condensation, redissolution and mesocrystals induced by tetravalent counterions

The distance-resolved effective interaction potential between two parallel DNA molecules is calculated by computer simulations with explicit tetravalent counterions and monovalent salt. Adding counterions first yields an attractive minimum in the potential at short distances which then disappears in favor of a shallower minimum at larger separations. The resulting phase diagram includes a DNA-condensation and redissolution transition and a stable mesocrystal with an intermediate lattice constant for high counterion concentration.Comment: 4 pages, 4 figure

DNA condensation and redissolution: Interaction between overcharged DNA molecules

The effective DNA-DNA interaction force is calculated by computer simulations with explicit tetravalent counterions and monovalent salt. For overcharged DNA molecules, the interaction force shows a double-minimum structure. The positions and depths of these minima are regulated by the counterion density in the bulk. Using two-dimensional lattice sum and free energy perturbation theories, the coexisting phases for DNA bundles are calculated. A DNA-condensation and redissolution transition and a stable mesocrystal with an intermediate lattice constant for high counterion concentration are obtained.Comment: 26 pages, 10 figure

Structure-based programming of lymph-node targeting in molecular vaccines

In cancer patients, visual identification of sentinel lymph nodes (LNs) is achieved by the injection of dyes that bind avidly to endogenous albumin, targeting these compounds to LNs, where they are efficiently filtered by resident phagocytes1, 2. Here we translate this ‘albumin hitchhiking’ approach to molecular vaccines, through the synthesis of amphiphiles (amph-vaccines) comprising an antigen or adjuvant cargo linked to a lipophilic albumin-binding tail by a solubility-promoting polar polymer chain. Administration of structurally optimized CpG-DNA/peptide amph-vaccines in mice resulted in marked increases in LN accumulation and decreased systemic dissemination relative to their parent compounds, leading to 30-fold increases in T-cell priming and enhanced anti-tumour efficacy while greatly reducing systemic toxicity. Amph-vaccines provide a simple, broadly applicable strategy to simultaneously increase the potency and safety of subunit vaccines.David H. Koch Institute for Integrative Cancer Research at MIT (Koch Institute Support (core) Grant P30-CA14051)National Cancer Institute (U.S.)National Institutes of Health (U.S.) (grant AI091693)National Institutes of Health (U.S.) (grant AI104715)National Institutes of Health (U.S.) (AI095109)United States. Dept. of Defense (contract W911NF-13-D-0001)United States. Dept. of Defense (contract W911NF-07-D-0004)Ragon Institute of MGH, MIT, and Harvar

Layer-by-Layer Assembled Antisense DNA Microsponge Particles for Efficient Delivery of Cancer Therapeutics

Antisense oligonucleotides can be employed as a potential approach to effectively treat cancer. However, the inherent instability and inefficient systemic delivery methods for antisense therapeutics remain major challenges to their clinical application. Here, we present a polymerized oligonucleotides (ODNs) that self-assemble during their formation through an enzymatic elongation method (rolling circle replication) to generate a composite nucleic acid/magnesium pyrophosphate sponge-like microstructure, or DNA microsponge, yielding high molecular weight nucleic acid product. In addition, this densely packed ODN microsponge structure can be further condensed to generate polyelectrolyte complexes with a favorable size for cellular uptake by displacing magnesium pyrophosphate crystals from the microsponge structure. Additional layers are applied to generate a blood-stable and multifunctional nanoparticle via the layer-by-layer (LbL) assembly technique. By taking advantage of DNA nanotechnology and LbL assembly, functionalized DNA nanostructures were utilized to provide extremely high numbers of repeated ODN copies for efficient antisense therapy. Moreover, we show that this formulation significantly improves nucleic acid drug/carrier stability during in vivo biodistribution. These polymeric ODN systems can be designed to serve as a potent means of delivering stable and large quantities of ODN therapeutics systemically for cancer treatment to tumor cells at significantly lower toxicity than traditional synthetic vectors, thus enabling a therapeutic window suitable for clinical translation.United States. Dept. of Defense. Ovarian Cancer Research Program (Teal Innovator Award Grant OC120504)Natural Sciences and Engineering Research Council of Canada (Postdoctoral Fellowship)National Institutes of Health (U.S.) (Ruth L. Kirschstein National Research Service Award 1F32EB017614-01)National Science Foundation (U.S.). Graduate Research Fellowshi

PEG−peptide conjugates

The remarkable diversity of the self-assembly behavior of PEG−peptides is reviewed, including self-assemblies formed by PEG−peptides with β-sheet and α-helical (coiled-coil) peptide sequences. The modes of self-assembly in solution and in the solid state are discussed. Additionally, applications in bionanotechnology and synthetic materials science are summarized

Applying polygenic risk scoring for psychiatric disorders to a large family with bipolar disorder and major depressive disorder

Psychiatric disorders are thought to have a complex genetic pathology consisting of interplay of common and rare variation. Traditionally, pedigrees are used to shed light on the latter only, while here we discuss the application of polygenic risk scores to also highlight patterns of common genetic risk. We analyze polygenic risk scores for psychiatric disorders in a large pedigree (n similar to 260) in which 30% of family members suffer from major depressive disorder or bipolar disorder. Studying patterns of assortative mating and anticipation, it appears increased polygenic risk is contributed by affected individuals who married into the family, resulting in an increasing genetic risk over generations. This may explain the observation of anticipation in mood disorders, whereby onset is earlier and the severity increases over the generations of a family. Joint analyses of rare and common variation may be a powerful way to understand the familial genetics of psychiatric disorders

A new strategy for enhancing imputation quality of rare variants from next-generation sequencing data via combining SNP and exome chip data

Background: Rare variants have gathered increasing attention as a possible alternative source of missing heritability. Since next generation sequencing technology is not yet cost-effective for large-scale genomic studies, a widely used alternative approach is imputation. However, the imputation approach may be limited by the low accuracy of the imputed rare variants. To improve imputation accuracy of rare variants, various approaches have been suggested, including increasing the sample size of the reference panel, using sequencing data from study-specific samples (i.e., specific populations), and using local reference panels by genotyping or sequencing a subset of study samples. While these approaches mainly utilize reference panels, imputation accuracy of rare variants can also be increased by using exome chips containing rare variants. The exome chip contains 250 K rare variants selected from the discovered variants of about 12,000 sequenced samples. If exome chip data are available for previously genotyped samples, the combined approach using a genotype panel of merged data, including exome chips and SNP chips, should increase the imputation accuracy of rare variants. Results: In this study, we describe a combined imputation which uses both exome chip and SNP chip data simultaneously as a genotype panel. The effectiveness and performance of the combined approach was demonstrated using a reference panel of 848 samples constructed using exome sequencing data from the T2D-GENES consortium and 5,349 sample genotype panels consisting of an exome chip and SNP chip. As a result, the combined approach increased imputation quality up to 11 %, and genomic coverage for rare variants up to 117.7 % (MAF < 1 %), compared to imputation using the SNP chip alone. Also, we investigated the systematic effect of reference panels on imputation quality using five reference panels and three genotype panels. The best performing approach was the combination of the study specific reference panel and the genotype panel of combined data. Conclusions: Our study demonstrates that combined datasets, including SNP chips and exome chips, enhances both the imputation quality and genomic coverage of rare variants

Improving Genetic Prediction by Leveraging Genetic Correlations Among Human Diseases and Traits

Genomic prediction has the potential to contribute to precision medicine. However, to date, the utility of such predictors is limited due to low accuracy for most traits. Here theory and simulation study are used to demonstrate that widespread pleiotropy among phenotypes can be utilised to improve genomic risk prediction. We show how a genetic predictor can be created as a weighted index that combines published genome-wide association study (GWAS) summary statistics across many different traits. We apply this framework to predict risk of schizophrenia and bipolar disorder in the Psychiatric Genomics consortium data, finding substantial heterogeneity in prediction accuracy increases across cohorts. For six additional phenotypes in the UK Biobank data, we find increases in prediction accuracy ranging from 0.7 for height to 47 for type 2 diabetes, when using a multi-trait predictor that combines published summary statistics from multiple traits, as compared to a predictor based only on one trait. © 2018 The Author(s)

Refining the accuracy of validated target identification through coding variant fine-mapping in type 2 diabetes

We aggregated coding variant data for 81,412 type 2 diabetes cases and 370,832 controls of diverse ancestry, identifying 40 coding variant association signals (P &lt; 2.2 × 10-7); of these, 16 map outside known risk-associated loci. We make two important observations. First, only five of these signals are driven by low-frequency variants: even for these, effect sizes are modest (odds ratio ≤1.29). Second, when we used large-scale genome-wide association data to fine-map the associated variants in their regional context, accounting for the global enrichment of complex trait associations in coding sequence, compelling evidence for coding variant causality was obtained for only 16 signals. At 13 others, the associated coding variants clearly represent 'false leads' with potential to generate erroneous mechanistic inference. Coding variant associations offer a direct route to biological insight for complex diseases and identification of validated therapeutic targets; however, appropriate mechanistic inference requires careful specification of their causal contribution to disease predisposition.</p