MAR-mediated integration of plasmid vectors for in vivo gene transfer and regulation.

BACKGROUND: The in vivo transfer of naked plasmid DNA into organs such as muscles is commonly used to assess the expression of prophylactic or therapeutic genes in animal disease models. RESULTS: In this study, we devised vectors allowing a tight regulation of transgene expression in mice from such non-viral vectors using a doxycycline-controlled network of activator and repressor proteins. Using these vectors, we demonstrate proper physiological response as consequence of the induced expression of two therapeutically relevant proteins, namely erythropoietin and utrophin. Kinetic studies showed that the induction of transgene expression was only transient, unless epigenetic regulatory elements termed Matrix Attachment Regions, or MAR, were inserted upstream of the regulated promoters. Using episomal plasmid rescue and quantitative PCR assays, we observed that similar amounts of plasmids remained in muscles after electrotransfer with or without MAR elements, but that a significant portion had integrated into the muscle fiber chromosomes. Interestingly, the MAR elements were found to promote plasmid genomic integration but to oppose silencing effects in vivo, thereby mediating long-term expression. CONCLUSIONS: This study thus elucidates some of the determinants of transient or sustained expression from the use of non-viral regulated vectors in vivo.

MGMT methylation analysis of glioblastoma on the Infinium methylation BeadChip identifies two distinct CpG regions associated with gene silencing and outcome, yielding a prediction model for comparisons across datasets, tumor grades, and CIMP-status.

The methylation status of the O(6)-methylguanine-DNA methyltransferase (MGMT) gene is an important predictive biomarker for benefit from alkylating agent therapy in glioblastoma. Recent studies in anaplastic glioma suggest a prognostic value for MGMT methylation. Investigation of pathogenetic and epigenetic features of this intriguingly distinct behavior requires accurate MGMT classification to assess high throughput molecular databases. Promoter methylation-mediated gene silencing is strongly dependent on the location of the methylated CpGs, complicating classification. Using the HumanMethylation450 (HM-450K) BeadChip interrogating 176 CpGs annotated for the MGMT gene, with 14 located in the promoter, two distinct regions in the CpG island of the promoter were identified with high importance for gene silencing and outcome prediction. A logistic regression model (MGMT-STP27) comprising probes cg1243587 and cg12981137 provided good classification properties and prognostic value (kappa = 0.85; log-rank p < 0.001) using a training-set of 63 glioblastomas from homogenously treated patients, for whom MGMT methylation was previously shown to be predictive for outcome based on classification by methylation-specific PCR. MGMT-STP27 was successfully validated in an independent cohort of chemo-radiotherapy-treated glioblastoma patients (n = 50; kappa = 0.88; outcome, log-rank p < 0.001). Lower prevalence of MGMT methylation among CpG island methylator phenotype (CIMP) positive tumors was found in glioblastomas from The Cancer Genome Atlas than in low grade and anaplastic glioma cohorts, while in CIMP-negative gliomas MGMT was classified as methylated in approximately 50 % regardless of tumor grade. The proposed MGMT-STP27 prediction model allows mining of datasets derived on the HM-450K or HM-27K BeadChip to explore effects of distinct epigenetic context of MGMT methylation suspected to modulate treatment resistance in different tumor types.

Advanced geostatistical and machine-learning models for spatial data analysis of radioactively contaminated regions

Radioactive soil-contamination mapping and risk assessment is a vital issue for decision makers. Traditional approaches for mapping the spatial concentration of radionuclides employ various regression-based models, which usually provide a single-value prediction realization accompanied (in some cases) by estimation error. Such approaches do not provide the capability for rigorous uncertainty quantification or probabilistic mapping. Machine learning is a recent and fast-developing approach based on learning patterns and information from data. Artificial neural networks for prediction mapping have been especially powerful in combination with spatial statistics. A data-driven approach provides the opportunity to integrate additional relevant information about spatial phenomena into a prediction model for more accurate spatial estimates and associated uncertainty. Machine-learning algorithms can also be used for a wider spectrum of problems than before: classification, probability density estimation, and so forth. Stochastic simulations are used to model spatial variability and uncertainty. Unlike regression models, they provide multiple realizations of a particular spatial pattern that allow uncertainty and risk quantification. This paper reviews the most recent methods of spatial data analysis, prediction, and risk mapping, based on machine learning and stochastic simulations in comparison with more traditional regression models. The radioactive fallout from the Chernobyl Nuclear Power Plant accident is used to illustrate the application of the models for prediction and classification problems. This fallout is a unique case study that provides the challenging task of analyzing huge amounts of data ('hard' direct measurements, as well as supplementary information and expert estimates) and solving particular decision-oriented problems.

A comparison of rapid bioassessment protocols used in 2 regions with Mediterranean climates, the Iberian Peninsula and South Africa

Abstract. The ability of 2 Rapid Bioassessment Protocols (RBPs) to assess stream water quality was compared in 2 Mediterranean-climate regions. The most commonly used RBPs in South Africa (SAprotocol) and the Iberian Peninsula (IB-protocol) are both multihabitat, field-based methods that use macroinvertebrates. Both methods use preassigned sensitivity weightings to calculate metrics and biotic indices. The SA- and IB-protocols differ with respect to sampling equipment (mesh size: 1000 lm vs 250 300 lm, respectively), segregation of habitats (substrate vs flow-type), and sampling and sorting procedures (variable time and intensity). Sampling was undertaken at 6 sites in South Africa and 5 sites in the Iberian Peninsula. Forty-four and 51 macroinvertebrate families were recorded in South Africa and the Iberian Peninsula, respectively; 77.3% of South African families and 74.5% of Iberian Peninsula families were found using both protocols. Estimates of community similarity compared between the 2 protocols were .60% similar among sites in South Africa and .54% similar among sites in the Iberian Peninsula (BrayCurtis similarity), and no significant differences were found between protocols (Multiresponse Permutation Procedure). Ordination based on Non-metric Multidimensional Scaling grouped macroinvertebrate samples on the basis of site rather than protocol. Biotic indices generated with the 2 protocols at each site did not differ. Thus, both RBPs produced equivalent results, and both were able to distinguish between biotic communities (mountain streams vs foothills) and detect water-quality impairment, regardless of differences in sampling equipment, segregation of habitats, and sampling and sorting procedures. Our results indicate that sampling a single habitat may be sufficient for assessing water quality, but a multihabitat approach to sampling is recommended where intrinsic variability of macroinvertebrate assemblages is high (e.g., in undisturbed sites in regions with Mediterranean climates). The RBP of choice should depend on whether the objective is routine biomonitoring of water quality or autecological or faunistic studies.

Characterization of a genomic signature of pregnancy identified in the breast.

The objective of this study was to comprehensively compare the genomic profiles in the breast of parous and nulliparous postmenopausal women to identify genes that permanently change their expression following pregnancy. The study was designed as a two-phase approach. In the discovery phase, we compared breast genomic profiles of 37 parous with 18 nulliparous postmenopausal women. In the validation phase, confirmation of the genomic patterns observed in the discovery phase was sought in an independent set of 30 parous and 22 nulliparous postmenopausal women. RNA was hybridized to Affymetrix HG_U133 Plus 2.0 oligonucleotide arrays containing probes to 54,675 transcripts, scanned and the images analyzed using Affymetrix GCOS software. Surrogate variable analysis, logistic regression, and significance analysis of microarrays were used to identify statistically significant differences in expression of genes. The false discovery rate (FDR) approach was used to control for multiple comparisons. We found that 208 genes (305 probe sets) were differentially expressed between parous and nulliparous women in both discovery and validation phases of the study at an FDR of 10% and with at least a 1.25-fold change. These genes are involved in regulation of transcription, centrosome organization, RNA splicing, cell-cycle control, adhesion, and differentiation. The results provide initial evidence that full-term pregnancy induces long-term genomic changes in the breast. The genomic signature of pregnancy could be used as an intermediate marker to assess potential chemopreventive interventions with hormones mimicking the effects of pregnancy for prevention of breast cancer.

One-year prevalence of low back pain in two Swiss regions: estimates from the population participating in the 1992-1993 MONICA project.

STUDY DESIGN: A cross-sectional survey was performed. OBJECTIVE: To estimate the extent of low back pain as a public health problem. SUMMARY OF BACKGROUND DATA: Health surveys converge on very high estimates of low back pain in general populations, but few studies have included severity criteria in their definition and conclusions. Because it is unlikely that interventions will influence the prevalence of minimal and infrequent symptoms, greater attention should be paid to characteristics of low back pain that indicate some impact on the life of survey respondents. METHODS: Two regions participated in the MONICA (MONitoring of trends and determinants in CArdiovascular disease) project in Switzerland. Participants randomly selected from the general population completed a standard self-administered questionnaire on cardiovascular risk factors. A special section on low back pain was added in the third (1992-1993) MONICA survey and completed by 3227 participants. RESULTS: A regional difference found in the 12-month prevalence rate disappeared with the inclusion of severity criteria. Low back pain over more than seven cumulated days was reported among men by 20.2% (age range, 25-34 years) to 28.5% (age range, 65-74 years), respectively, among women by 31.1% to 38.5%. Similar rates of reduction in activity (professional, housekeeping, and leisure time) and medical consultation (conventional and nonconventional) motivated by low back pain characterized the two participating regions. The cumulative duration of pain was related to all the indicators showing the impact of low back pain on everyday life. CONCLUSIONS: Determining the cumulative duration of low back pain over the preceding year is a straightforward task, and a cutoff at 1 week seems appropriate for distinguishing between low- and high-impact low back pain.

Comparative genomic and phylogeographic analysis of Mycobacterium leprae.

Reductive evolution and massive pseudogene formation have shaped the 3.31-Mb genome of Mycobacterium leprae, an unculturable obligate pathogen that causes leprosy in humans. The complete genome sequence of M. leprae strain Br4923 from Brazil was obtained by conventional methods (6x coverage), and Illumina resequencing technology was used to obtain the sequences of strains Thai53 (38x coverage) and NHDP63 (46x coverage) from Thailand and the United States, respectively. Whole-genome comparisons with the previously sequenced TN strain from India revealed that the four strains share 99.995% sequence identity and differ only in 215 polymorphic sites, mainly SNPs, and by 5 pseudogenes. Sixteen interrelated SNP subtypes were defined by genotyping both extant and extinct strains of M. leprae from around the world. The 16 SNP subtypes showed a strong geographical association that reflects the migration patterns of early humans and trade routes, with the Silk Road linking Europe to China having contributed to the spread of leprosy.

Effects of genetics and environment on isoflavone content of soybean from different regions of Brazil

The effects of genetics and environmental factors on isoflavone content of soybean (Glycine max L.) cultivars grown in different locations in Brazil in 1993/94 were evaluated. Seeds of different cultivars were analised by high performance liquid chromatography (HPLC). In Rio Grande do Sul (RS), Paraná (PR), and Mato Grosso do Sul (MS) States, a significant difference in the isoflavone total content average of the cultivars IAS 5 and FT-Abyara (163.9, 116.4 and 79.5 mg/100 g, respectively) was observed. In general, IAS 5 contained higher isoflavone than FT-Abyara. Cultivars IAS 5 and FT-Abyara grown at Vacaria, RS (28°30' S latitude) with temperature average of 19°C, had the highest isoflavone concentrations (218.7 and 163.8 mg/100 g, respectively). In Palotina, PR (24°27' S latitude), where temperature average was 24°C, the isoflavone concentrations were 105.9 and 86.8 mg/100 g, respectively. The lowest isoflavone contents were observed for FT-Estrela and FT-Cristalina, (27.6 and 46.5 mg/100 g, repectively) at Rondonópolis, MT (16°20' S latitude), where the temperature was 27°C.

Segmentation of Head and Neck Lymph Node Regions for Radiotherapy Planning Using Active Contour-Based Atlas Registration

In this paper, we present the segmentation of the headand neck lymph node regions using a new active contourbased atlas registration model. We propose to segment thelymph node regions without directly including them in theatlas registration process; instead, they are segmentedusing the dense deformation field computed from theregistration of the atlas structures with distinctboundaries. This approach results in robust and accuratesegmentation of the lymph node regions even in thepresence of significant anatomical variations between theatlas-image and the patient's image to be segmented. Wealso present a quantitative evaluation of lymph noderegions segmentation using various statistical as well asgeometrical metrics: sensitivity, specificity, dicesimilarity coefficient and Hausdorff distance. Acomparison of the proposed method with two other state ofthe art methods is presented. The robustness of theproposed method to the atlas selection, in segmenting thelymph node regions, is also evaluated.

Perspective: from molecular endocrinology of mouse to genomic endocrinology of animals.

This short perspective explores some ways in which new genomic methodologies impact the study of endocrine signaling. Emphasis is put on the impact of studying species which are not molecular biology models. This opens the door to using knowledge molecular endocrinology in areas of biology as distant as conservation biology, as well as enriching endocrinology with information from biodiversity and natural variation.

Genome-wide association study identifies loci influencing concentrations of liver enzymes in plasma.

Concentrations of liver enzymes in plasma are widely used as indicators of liver disease. We carried out a genome-wide association study in 61,089 individuals, identifying 42 loci associated with concentrations of liver enzymes in plasma, of which 32 are new associations (P = 10(-8) to P = 10(-190)). We used functional genomic approaches including metabonomic profiling and gene expression analyses to identify probable candidate genes at these regions. We identified 69 candidate genes, including genes involved in biliary transport (ATP8B1 and ABCB11), glucose, carbohydrate and lipid metabolism (FADS1, FADS2, GCKR, JMJD1C, HNF1A, MLXIPL, PNPLA3, PPP1R3B, SLC2A2 and TRIB1), glycoprotein biosynthesis and cell surface glycobiology (ABO, ASGR1, FUT2, GPLD1 and ST3GAL4), inflammation and immunity (CD276, CDH6, GCKR, HNF1A, HPR, ITGA1, RORA and STAT4) and glutathione metabolism (GSTT1, GSTT2 and GGT), as well as several genes of uncertain or unknown function (including ABHD12, EFHD1, EFNA1, EPHA2, MICAL3 and ZNF827). Our results provide new insight into genetic mechanisms and pathways influencing markers of liver function.

Influence of row spacing reduction on maize grain yield in regions with a short summer

The interest in reducing maize row spacing in the short growing season regions of Brazil is increasing due to potential advantages such as higher radiation use efficiency. This experiment was conducted to evaluate the effect of row spacing reduction on grain yield of different maize cultivars planted at different dates. The trial was conducted in Lages, in the State of Santa Catarina, Brazil, during 1996/97 and 1997/98 growing seasons, in a split-split plot design. Early (October 1st) and normal (November 15) planting dates were tested in the main plot; two morphologically contrasting cultivars (an early single-cross and a late double-cross hybrids) were evaluated in the split plots and three row widths (100, 75 and 50 cm) were studied in the split-split plots. The reduction of row spacing from 100 to 50 cm increased linearly maize grain yield. The yield edge provided by narrow rows was higher when maize was sown earlier in the season. Differences in hybrid cycle and plant architecture did not alter maize response to the reduction of row spacing.

Cognate peptide-receptor ligand mapping by directed phage display

Background: A rapid phage display method for the elucidation of cognate peptide specific ligand for receptors is described. The approach may be readily integrated into the interface of genomic and proteomic studies to identify biologically relevant ligands.Methods: A gene fragment library from influenza coat protein haemagglutinin (HA) gene was constructed by treating HA cDNA with DNAse I to create 50 ¿ 100 bp fragments. These fragments were cloned into plasmid pORFES IV and in-frame inserts were selected. These in-frame fragment inserts were subsequently cloned into a filamentous phage display vector JC-M13-88 for surface display as fusions to a synthetic copy of gene VIII. Two well characterized antibodies, mAb 12CA5 and pAb 07431, directed against distinct known regions of HA were used to pan the library. Results: Two linear epitopes, HA peptide 112 ¿ 126 and 162¿173, recognized by mAb 12CA5 and pAb 07431, respectively, were identified as the cognate epitopes.Conclusion: This approach is a useful alternative to conventional methods such as screening of overlapping synthetic peptide libraries or gene fragment expression libraries when searching for precise peptide protein interactions, and may be applied to functional proteomics.

Membrane mu poly(A) signal and 3' flanking sequences function as a transcription terminator for immunoglobulin-encoding genes.

Developmentally regulated mechanisms involving alternative RNA splicing and/or polyadenylation, as well as transcription termination, are implicated in controlling the levels of secreted mu (mu s), membrane mu (mu m) and delta immunoglobulin (Ig) heavy chain mRNAs during B cell differentiation (mu gene encodes the mu heavy chain). Using expression vectors constructed with genomic DNA segments composed of the mu m polyadenylation signal region, we analyzed poly(A) site utilization and termination of transcription in stably transfected myeloma cells and in murine fibroblast L cells. We found that the gene segment containing the mu m poly(A) signals, along with 536 bp of downstream flanking sequence, acted as a transcription terminator in both myeloma cells and L cell fibroblasts. Neither a 141-bp DNA fragment (which directed efficient polyadenylation at the mu m site), nor the 536-bp flanking nucleotide sequence alone, were sufficient to obtain a similar regulation. This shows that the mu m poly(A) region plays a central role in controlling developmentally regulated transcription termination by blocking downstream delta gene expression. Because this gene segment exhibited the same RNA processing and termination activities in fibroblasts, it appears that these processes are not tissue-specific.