Theoretical Analysis of the Stress Induced B-Z Transition in Superhelical DNA

We present a method to calculate the propensities of regions within a DNA molecule to transition from B-form to Z-form under negative superhelical stresses. We use statistical mechanics to analyze the competition that occurs among all susceptible Z-forming regions at thermodynamic equilibrium in a superhelically stressed DNA of specified sequence. This method, which we call SIBZ, is similar to the SIDD algorithm that was previously developed to analyze superhelical duplex destabilization. A state of the system is determined by assigning to each base pair either the B- or the Z-conformation, accounting for the dinucleotide repeat unit of Z-DNA. The free energy of a state is comprised of the nucleation energy, the sequence-dependent B-Z transition energy, and the energy associated with the residual superhelicity remaining after the change of twist due to transition. Using this information, SIBZ calculates the equilibrium B-Z transition probability of each base pair in the sequence. This can be done at any physiologically reasonable level of negative superhelicity. We use SIBZ to analyze a variety of representative genomic DNA sequences. We show that the dominant Z-DNA forming regions in a sequence can compete in highly complex ways as the superhelicity level changes. Despite having no tunable parameters, the predictions of SIBZ agree precisely with experimental results, both for the onset of transition in plasmids containing introduced Z-forming sequences and for the locations of Z-forming regions in genomic sequences. We calculate the transition profiles of 5 kb regions taken from each of 12,841 mouse genes and centered on the transcription start site (TSS). We find a substantial increase in the frequency of Z-forming regions immediately upstream from the TSS. The approach developed here has the potential to illuminate the occurrence of Z-form regions in vivo, and the possible roles this transition may play in biological processes

Theoretical Analysis of Competing Conformational Transitions in Superhelical DNA

We develop a statistical mechanical model to analyze the competitive behavior of transitions to multiple alternate conformations in a negatively supercoiled DNA molecule of kilobase length and specified base sequence. Since DNA superhelicity topologically couples together the transition behaviors of all base pairs, a unified model is required to analyze all the transitions to which the DNA sequence is susceptible. Here we present a first model of this type. Our numerical approach generalizes the strategy of previously developed algorithms, which studied superhelical transitions to a single alternate conformation. We apply our multi-state model to study the competition between strand separation and B-Z transitions in superhelical DNA. We show this competition to be highly sensitive to temperature and to the imposed level of supercoiling. Comparison of our results with experimental data shows that, when the energetics appropriate to the experimental conditions are used, the competition between these two transitions is accurately captured by our algorithm. We analyze the superhelical competition between B-Z transitions and denaturation around the c-myc oncogene, where both transitions are known to occur when this gene is transcribing. We apply our model to explore the correlation between stress-induced transitions and transcriptional activity in various organisms. In higher eukaryotes we find a strong enhancement of Z-forming regions immediately 5′ to their transcription start sites (TSS), and a depletion of strand separating sites in a broad region around the TSS. The opposite patterns occur around transcript end locations. We also show that susceptibility to each type of transition is different in eukaryotes and prokaryotes. By analyzing a set of untranscribed pseudogenes we show that the Z-susceptibility just downstream of the TSS is not preserved, suggesting it may be under selection pressure

Review of the algal biology program within the National Alliance for Advanced Biofuels and Bioproducts

In 2010, when the National Alliance for Advanced Biofuels and Bioproducts (NAABB) consortium began, little was known about the molecular basis of algal biomass or oil production. Very few algal genome sequences were available and efforts to identify the best-producing wild species through bioprospecting approaches had largely stalled after the U.S. Department of Energy's Aquatic Species Program. This lack of knowledge included how reduced carbon was partitioned into storage products like triglycerides or starch and the role played by metabolite remodeling in the accumulation of energy-dense storage products. Furthermore, genetic transformation and metabolic engineering approaches to improve algal biomass and oil yields were in their infancy. Genome sequencing and transcriptional profiling were becoming less expensive, however; and the tools to annotate gene expression profiles under various growth and engineered conditions were just starting to be developed for algae. It was in this context that an integrated algal biology program was introduced in the NAABB to address the greatest constraints limiting algal biomass yield. This review describes the NAABB algal biology program, including hypotheses, research objectives, and strategies to move algal biology research into the twenty-first century and to realize the greatest potential of algae biomass systems to produce biofuels

OSBPL10, a novel candidate gene for high triglyceride trait in dyslipidemic Finnish subjects, regulates cellular lipid metabolism

Analysis of variants in three genes encoding oxysterol-binding protein (OSBP) homologues (OSBPL2, OSBPL9, OSBPL10) in Finnish families with familial low high-density lipoprotein (HDL) levels (N = 426) or familial combined hyperlipidemia (N = 684) revealed suggestive linkage of OSBPL10 single-nucleotide polymorphisms (SNPs) with extreme end high triglyceride (TG; >90th percentile) trait. Prompted by this initial finding, we carried out association analysis in a metabolic syndrome subcohort (Genmets) of Health2000 examination survey (N = 2,138), revealing association of multiple OSBPL10 SNPs with high serum TG levels (>95th percentile). To investigate whether OSBPL10 could be the gene underlying the observed linkage and association, we carried out functional experiments in the human hepatoma cell line Huh7. Silencing of OSBPL10 increased the incorporation of [3H]acetate into cholesterol and both [3H]acetate and [3H]oleate into triglycerides and enhanced the accumulation of secreted apolipoprotein B100 in growth medium, suggesting that the encoded protein ORP10 suppresses hepatic lipogenesis and very-low-density lipoprotein production. ORP10 was shown to associate dynamically with microtubules, consistent with its involvement in intracellular transport or organelle positioning. The data introduces OSBPL10 as a gene whose variation may contribute to high triglyceride levels in dyslipidemic Finnish subjects and provides evidence for ORP10 as a regulator of cellular lipid metabolism

Therapeutic Efficacy of Potent Neutralizing HIV-1-Specific Monoclonal Antibodies in SHIV-Infected Rhesus Monkeys

HIV-1-specific monoclonal antibodies (mAbs) with extraordinary potency and breadth have recently been described. In humanized mice, combinations of mAbs have been shown to suppress viremia, but the therapeutic potential of these mAbs has not yet been evaluated in primates with an intact immune system. Here we show that administration of a cocktail of HIV-1-specific mAbs, as well as the single glycan-dependent mAb PGT121, resulted in a rapid and precipitous decline of plasma viremia to undetectable levels in rhesus monkeys chronically infected with the pathogenic virus SHIV-SF162P3. A single mAb infusion afforded up to a 3.1 log decline of plasma viral RNA in 7 days and also reduced proviral DNA in peripheral blood, gastrointestinal mucosa, and lymph nodes without the development of viral resistance. Moreover, following mAb administration, host Gag-specific T lymphocyte responses exhibited improved functionality. Virus rebounded in the majority of animals after a median of 56 days when serum mAb titers had declined to undetectable levels, although a subset of animals maintained long-term virologic control in the absence of further mAb infusions. These data demonstrate a profound therapeutic effect of potent neutralizing HIV-1-specific mAbs in SHIV-infected rhesus monkeys as well as an impact on host immune responses. Our findings strongly encourage the investigation of mAb therapy for HIV-1 in humans

Human Skeletal Muscle Possesses an Epigenetic Memory of Hypertrophy

It is unknown if adult human skeletal muscle has an epigenetic memory of earlier encounters with growth. We report, for the first time in humans, genome-wide DNA methylation (850,000 CpGs) and gene expression analysis after muscle hypertrophy (loading), return of muscle mass to baseline (unloading), followed by later hypertrophy (reloading). We discovered increased frequency of hypomethylation across the genome after reloading (18,816 CpGs) versus earlier loading (9,153 CpG sites). We also identified AXIN1, GRIK2, CAMK4, TRAF1 as hypomethylated genes with enhanced expression after loading that maintained their hypomethylated status even during unloading where muscle mass returned to control levels, indicating a memory of these genes methylation signatures following earlier hypertrophy. Further, UBR5, RPL35a, HEG1, PLA2G16, SETD3 displayed hypomethylation and enhanced gene expression following loading, and demonstrated the largest increases in hypomethylation, gene expression and muscle mass after later reloading, indicating an epigenetic memory in these genes. Finally, genes; GRIK2, TRAF1, BICC1, STAG1 were epigenetically sensitive to acute exercise demonstrating hypomethylation after a single bout of resistance exercise that was maintained 22 weeks later with the largest increase in gene expression and muscle mass after reloading. Overall, we identify an important epigenetic role for a number of largely unstudied genes in muscle hypertrophy/memory

Molecular Effects of Doxycycline Treatment on Pterygium as Revealed by Massive Transcriptome Sequencing

Pterygium is a lesion of the eye surface which involves cell proliferation, migration, angiogenesis, fibrosis, and extracellular matrix remodelling. Surgery is the only approved method to treat this disorder, but high recurrence rates are common. Recently, it has been shown in a mouse model that treatment with doxycycline resulted in reduction of the pterygium lesions. Here we study the mechanism(s) of action by which doxycycline achieves these results, using massive sequencing techniques. Surgically removed pterygia from 10 consecutive patients were set in short term culture and exposed to 0 (control), 50, 200, and 500 µg/ml doxycycline for 24 h, their mRNA was purified, reverse transcribed and sequenced through Illumina’s massive sequencing protocols. Acquired data were subjected to quantile normalization and analyzed using cytoscape plugin software to explore the pathways involved. False discovery rate (FDR) methods were used to identify 332 genes which modified their expression in a dose-dependent manner upon exposure to doxycycline. The more represented cellular pathways included all mitochondrial genes, the endoplasmic reticulum stress response, integrins and extracellular matrix components, and growth factors. A high correlation was obtained when comparing ultrasequencing data with qRT-PCR and ELISA results

Computational Modeling of Silicate Glasses: A Quantitative Structure-Property Relationship Perspective

This article reviews the present state of Quantitative Structure-Property Relationships (QSPR) in glass design and gives an outlook into future developments. First an overview is given of the statistical methodology, with particular emphasis to the integration of QSPR with molecular dynamics simulations to derive informative structural descriptors. Then, the potentiality of this approach as a tool for interpretative and predictive purposes is highlighted by a number of recent inspiring applications

Identification of co-expression gene networks, regulatory genes and pathways for obesity based on adipose tissue RNA Sequencing in a porcine model

Background: Obesity is a complex metabolic condition in strong association with various diseases, like type 2 diabetes, resulting in major public health and economic implications. Obesity is the result of environmental and genetic factors and their interactions, including genome-wide genetic interactions. Identification of co-expressed and regulatory genes in RNA extracted from relevant tissues representing lean and obese individuals provides an entry point for the identification of genes and pathways of importance to the development of obesity. The pig, an omnivorous animal, is an excellent model for human obesity, offering the possibility to study in-depth organ-level transcriptomic regulations of obesity, unfeasible in humans. Our aim was to reveal adipose tissue co-expression networks, pathways and transcriptional regulations of obesity using RNA Sequencing based systems biology approaches in a porcine model. Methods: We selected 36 animals for RNA Sequencing from a previously created F2 pig population representing three extreme groups based on their predicted genetic risks for obesity. We applied Weighted Gene Co-expression Network Analysis (WGCNA) to detect clusters of highly co-expressed genes (modules). Additionally, regulator genes were detected using Lemon-Tree algorithms. Results: WGCNA revealed five modules which were strongly correlated with at least one obesity-related phenotype (correlations ranging from -0.54 to 0.72, P <0.001). Functional annotation identified pathways enlightening the association between obesity and other diseases, like osteoporosis (osteoclast differentiation, P = 1.4E(-7)), and immune-related complications (e. g. Natural killer cell mediated cytotoxity, P = 3.8E(-5); B cell receptor signaling pathway, P = 7.2E(-5)). Lemon-Tree identified three potential regulator genes, using confident scores, for the WGCNA module which was associated with osteoclast differentiation: CCR1, MSR1 and SI1 (probability scores respectively 95.30, 62.28, and 34.58). Moreover, detection of differentially connected genes identified various genes previously identified to be associated with obesity in humans and rodents, e.g. CSF1R and MARC2. Conclusions: To our knowledge, this is the first study to apply systems biology approaches using porcine adipose tissue RNA-Sequencing data in a genetically characterized porcine model for obesity. We revealed complex networks, pathways, candidate and regulatory genes related to obesity, confirming the complexity of obesity and its association with immune-related disorders and osteoporosis