Background: Obesity is a metabolic disease caused by environmental and genetic factors. However, the epigenetic mechanisms of obesity are incompletely understood. The aim of our study was to investigate the role of skeletal muscle DNA methylation in combination with transcriptomic changes in obesity.

Results: Muscle biopsies were obtained basally from lean (n = 12; BMI = 23.4 ± 0.7 kg/m[superscript 2]) and obese (n = 10; BMI = 32.9 ± 0.7 kg/m[superscript 2]) participants in combination with euglycemic-hyperinsulinemic clamps to assess insulin sensitivity. We performed reduced representation bisulfite sequencing (RRBS) next-generation methylation and microarray analyses on DNA and RNA isolated from vastus lateralis muscle biopsies. There were 13,130 differentially methylated cytosines (DMC; uncorrected P < 0.05) that were altered in the promoter and untranslated (5' and 3'UTR) regions in the obese versus lean analysis. Microarray analysis revealed 99 probes that were significantly (corrected P < 0.05) altered. Of these, 12 genes (encompassing 22 methylation sites) demonstrated a negative relationship between gene expression and DNA methylation. Specifically, sorbin and SH3 domain containing 3 (SORBS3) which codes for the adapter protein vinexin was significantly decreased in gene expression (fold change −1.9) and had nine DMCs that were significantly increased in methylation in obesity (methylation differences ranged from 5.0 to 24.4 %). Moreover, differentially methylated region (DMR) analysis identified a region in the 5'UTR (Chr.8:22,423,530–22,423,569) of SORBS3 that was increased in methylation by 11.2 % in the obese group. The negative relationship observed between DNA methylation and gene expression for SORBS3 was validated by a site-specific sequencing approach, pyrosequencing, and qRT-PCR. Additionally, we performed transcription factor binding analysis and identified a number of transcription factors whose binding to the differentially methylated sites or region may contribute to obesity.

Conclusions: These results demonstrate that obesity alters the epigenome through DNA methylation and highlights novel transcriptomic changes in SORBS3 in skeletal muscle.

Salmonella enterica serovar Typhimurium, a gram-negative facultative rod-shaped bacterium causing salmonellosis and foodborne disease, is one of the most common isolated Salmonella serovars in both developed and developing nations. Several S. Typhimurium genomes have been completed and many more genome-sequencing projects are underway. Comparative genome analysis of the multiple strains leads to a better understanding of the evolution of S. Typhimurium and its pathogenesis. S. Typhimurium strain UK-1 (belongs to phage type 1) is highly virulent when orally administered to mice and chickens and efficiently colonizes lymphoid tissues of these species. These characteristics make this strain a good choice for use in vaccine development. In fact, UK-1 has been used as the parent strain for a number of nonrecombinant and recombinant vaccine strains, including several commercial vaccines for poultry. In this study, we conducted a thorough comparative genome analysis of the UK-1 strain with other S. Typhimurium strains and examined the phenotypic impact of several genomic differences. Whole genomic comparison highlights an extremely close relationship between the UK-1 strain and other S. Typhimurium strains; however, many interesting genetic and genomic variations specific to UK-1 were explored. In particular, the deletion of a UK-1-specific gene that is highly similar to the gene encoding the T3SS effector protein NleC exhibited a significant decrease in oral virulence in BALB/c mice. The complete genetic complements in UK-1, especially those elements that contribute to virulence or aid in determining the diversity within bacterial species, provide key information in evaluating the functional characterization of important genetic determinants and for development of vaccines.

We have previously hypothesized a biological pathway of activity-dependent synaptic plasticity proteins that addresses the dual genetic and environmental contributions to schizophrenia. Accordingly, variations in the immediate early gene EGR3, and its target ARC, should influence schizophrenia susceptibility. We used a pooled Next-Generation Sequencing approach to identify variants across these genes in U.S. populations of European (EU) and African (AA) descent. Three EGR3 and one ARC SNP were selected and genotyped for validation, and three SNPs were tested for association in a replication cohort. In the EU group of 386 schizophrenia cases and 150 controls EGR3 SNP rs1877670 and ARC SNP rs35900184 showed significant associations (p = 0.0078 and p = 0.0275, respectively). In the AA group of 185 cases and 50 controls, only the ARC SNP revealed significant association (p = 0.0448). The ARC SNP did not show association in the Han Chinese (CH) population. However, combining the EU, AA, and CH groups revealed a highly significant association of ARC SNP rs35900184 (p = 2.353 x 10^-7; OR [95% CI] = 1.54 [1.310–1.820]). These findings support previously reported associations between EGR3 and schizophrenia. Moreover, this is the first report associating an ARC SNP with schizophrenia and supports recent large-scale GWAS findings implicating the ARC complex in schizophrenia risk. These results support the need for further investigation of the proposed pathway of environmentally responsive, synaptic plasticity-related, schizophrenia genes.

Background: Immunosignaturing is a new peptide microarray based technology for profiling of humoral immune responses. Despite new challenges, immunosignaturing gives us the opportunity to explore new and fundamentally different research questions. In addition to classifying samples based on disease status, the complex patterns and latent factors underlying immunosignatures, which we attempt to model, may have a diverse range of applications.

Methods: We investigate the utility of a number of statistical methods to determine model performance and address challenges inherent in analyzing immunosignatures. Some of these methods include exploratory and confirmatory factor analyses, classical significance testing, structural equation and mixture modeling.

Results: We demonstrate an ability to classify samples based on disease status and show that immunosignaturing is a very promising technology for screening and presymptomatic screening of disease. In addition, we are able to model complex patterns and latent factors underlying immunosignatures. These latent factors may serve as biomarkers for disease and may play a key role in a bioinformatic method for antibody discovery.

Conclusion: Based on this research, we lay out an analytic framework illustrating how immunosignatures may be useful as a general method for screening and presymptomatic screening of disease as well as antibody discovery.

Background: Glioblastoma is the most aggressive primary central nervous tumor and carries a very poor prognosis. Invasion precludes effective treatment and virtually assures tumor recurrence. In the current study, we applied analytical and bioinformatics approaches to identify a set of microRNAs (miRs) from several different human glioblastoma cell lines that exhibit significant differential expression between migratory (edge) and migration-restricted (core) cell populations. The hypothesis of the study is that differential expression of miRs provides an epigenetic mechanism to drive cell migration and invasion.

Results: Our research data comprise gene expression values for a set of 805 human miRs collected from matched pairs of migratory and migration-restricted cell populations from seven different glioblastoma cell lines. We identified 62 down-regulated and 2 up-regulated miRs that exhibit significant differential expression in the migratory (edge) cell population compared to matched migration-restricted (core) cells. We then conducted target prediction and pathway enrichment analysis with these miRs to investigate potential associated gene and pathway targets. Several miRs in the list appear to directly target apoptosis related genes. The analysis identifies a set of genes that are predicted by 3 different algorithms, further emphasizing the potential validity of these miRs to promote glioblastoma.

Conclusions: The results of this study identify a set of miRs with potential for decreased expression in invasive glioblastoma cells. The verification of these miRs and their associated targeted proteins provides new insights for further investigation into therapeutic interventions. The methodological approaches employed here could be applied to the study of other diseases to provide biomedical researchers and clinicians with increased opportunities for therapeutic interventions.

Background: The discovery of genetic associations is an important factor in the understanding of human illness to derive disease pathways. Identifying multiple interacting genetic mutations associated with disease remains challenging in studying the etiology of complex diseases. And although recently new single nucleotide polymorphisms (SNPs) at genes implicated in immune response, cholesterol/lipid metabolism, and cell membrane processes have been confirmed by genome-wide association studies (GWAS) to be associated with late-onset Alzheimer's disease (LOAD), a percentage of AD heritability continues to be unexplained. We try to find other genetic variants that may influence LOAD risk utilizing data mining methods.

Methods: Two different approaches were devised to select SNPs associated with LOAD in a publicly available GWAS data set consisting of three cohorts. In both approaches, single-locus analysis (logistic regression) was conducted to filter the data with a less conservative p-value than the Bonferroni threshold; this resulted in a subset of SNPs used next in multi-locus analysis (random forest (RF)). In the second approach, we took into account prior biological knowledge, and performed sample stratification and linkage disequilibrium (LD) in addition to logistic regression analysis to preselect loci to input into the RF classifier construction step.

Results: The first approach gave 199 SNPs mostly associated with genes in calcium signaling, cell adhesion, endocytosis, immune response, and synaptic function. These SNPs together with APOE and GAB2 SNPs formed a predictive subset for LOAD status with an average error of 9.8% using 10-fold cross validation (CV) in RF modeling. Nineteen variants in LD with ST5, TRPC1, ATG10, ANO3, NDUFA12, and NISCH respectively, genes linked directly or indirectly with neurobiology, were identified with the second approach. These variants were part of a model that included APOE and GAB2 SNPs to predict LOAD risk which produced a 10-fold CV average error of 17.5% in the classification modeling.

Conclusions: With the two proposed approaches, we identified a large subset of SNPs in genes mostly clustered around specific pathways/functions and a smaller set of SNPs, within or in proximity to five genes not previously reported, that may be relevant for the prediction/understanding of AD.

The field of cyanobacterial biofuel production is advancing rapidly, yet we know little of the basic biology of these organisms outside of their photosynthetic pathways. We aimed to gain a greater understanding of how the cyanobacterium Synechocystis PCC 6803 (Synechocystis, hereafter) modulates its cell surface. Such understanding will allow for the creation of mutants that autoflocculate in a regulated way, thus avoiding energy intensive centrifugation in the creation of biofuels. We constructed mutant strains lacking genes predicted to function in carbohydrate transport or synthesis. Strains with gene deletions of slr0977 (predicted to encode a permease component of an ABC transporter), slr0982 (predicted to encode an ATP binding component of an ABC transporter) and slr1610 (predicted to encode a methyltransferase) demonstrated flocculent phenotypes and increased adherence to glass. Upon bioinformatic inspection, the gene products of slr0977, slr0982, and slr1610 appear to function in O-antigen (OAg) transport and synthesis. However, the analysis provided here demonstrated no differences between OAg purified from wild-type and mutants. However, exopolysaccharides (EPS) purified from mutants were altered in composition when compared to wild-type. Our data suggest that there are multiple means to modulate the cell surface of Synechocystis by disrupting different combinations of ABC transporters and/or glycosyl transferases. Further understanding of these mechanisms may allow for the development of industrially and ecologically useful strains of cyanobacteria. Additionally, these data imply that many cyanobacterial gene products may possess as-yet undiscovered functions, and are meritorious of further study.

Background: Salmonella has been employed to deliver therapeutic molecules against cancer and infectious diseases. As the carrier for target gene(s), the cargo plasmid should be stable in the bacterial vector. Plasmid recombination has been reduced in E. coli by mutating several genes including the recA, recE, recF and recJ. However, to our knowledge, there have been no published studies of the effect of these or any other genes that play a role in plasmid recombination in Salmonella enterica.

Results: The effect of recA, recF and recJ deletions on DNA recombination was examined in three serotypes of Salmonella enterica. We found that (1) intraplasmid recombination between direct duplications was RecF-independent in Typhimurium and Paratyphi A, but could be significantly reduced in Typhi by a ΔrecA or ΔrecF mutation; (2) in all three Salmonella serotypes, both ΔrecA and ΔrecF mutations reduced intraplasmid recombination when a 1041 bp intervening sequence was present between the duplications; (3) ΔrecA and ΔrecF mutations resulted in lower frequencies of interplasmid recombination in Typhimurium and Paratyphi A, but not in Typhi; (4) in some cases, a ΔrecJ mutation could reduce plasmid recombination but was less effective than ΔrecA and ΔrecF mutations. We also examined chromosome-related recombination. The frequencies of intrachromosomal recombination and plasmid integration into the chromosome were 2 and 3 logs lower than plasmid recombination frequencies in Rec[superscript +] strains. A ΔrecA mutation reduced both intrachromosomal recombination and plasmid integration frequencies.

Conclusions: The ΔrecA and ΔrecF mutations can reduce plasmid recombination frequencies in Salmonella enterica, but the effect can vary between serovars. This information will be useful for developing Salmonella delivery vectors able to stably maintain plasmid cargoes for vaccine development and gene therapy.

Urban environmental measurements and observational statistics should reflect the properties generated over an adjacent area of adequate length where homogeneity is usually assumed. The determination of this characteristic source area that gives sufficient representation of the horizontal coverage of a sensing instrument or the fetch of transported quantities is of critical importance to guide the design and implementation of urban landscape planning strategies. In this study, we aim to unify two different methods for estimating source areas, viz. the statistical correlation method commonly used by geographers for landscape fragmentation and the mechanistic footprint model by meteorologists for atmospheric measurements. Good agreement was found in the intercomparison of the estimate of source areas by the two methods, based on 2-m air temperature measurement collected using a network of weather stations. The results can be extended to shed new lights on urban planning strategies, such as the use of urban vegetation for heat mitigation. In general, a sizable patch of landscape is required in order to play an effective role in regulating the local environment, proportional to the height at which stakeholders’ interest is mainly concerned.

The net storage heat flux (ΔQ[subscript S]) is important in the urban surface energy balance (SEB) but its determination remains a significant challenge. The hysteresis pattern of the diurnal relation between the ΔQ[subscript S] and net all-wave radiation (Q[superscript ∗]) has been captured in the Objective Hysteresis Model (OHM) parameterization of ΔQ[subscript S]. Although successfully used in urban areas, the limited availability of coefficients for OHM hampers its application. To facilitate use, and enhance physical interpretations of the OHM coefficients, an analytical solution of the one-dimensional advection–diffusion equation of coupled heat and liquid water transport in conjunction with the SEB is conducted, allowing development of AnOHM (Analytical Objective Hysteresis Model). A sensitivity test of AnOHM to surface properties and hydrometeorological forcing is presented using a stochastic approach (subset simulation). The sensitivity test suggests that the albedo, Bowen ratio and bulk transfer coefficient, solar radiation and wind speed are most critical. AnOHM, driven by local meteorological conditions at five sites with different land use, is shown to simulate the ΔQ[subscript S] flux well (RMSE values of ∼ 30 W m[superscript −2]). The intra-annual dynamics of OHM coefficients are explored. AnOHM offers significant potential to enhance modelling of the surface energy balance over a wider range of conditions and land covers.