What can we learn from tobacco and other Solanaceae about horizontal DNA transfer?

In eukaryotic organisms, horizontal gene transfer (HGT) is regarded as an important though infrequent source of reticulate evolution. Many confirmed instances of natural HGT involving multicellular eukaryotes come from flowering plants. This review intends to provide a synthesis of present knowledge regarding HGT in higher plants, with an emphasis on tobacco and other species in the Solanaceae family because there are numerous detailed reports concerning natural HGT events, involving various donors, in this family. Moreover, in-depth experimental studies using transgenic tobacco are of great importance for understanding this process. Valuable insights are offered concerning the mechanisms of HGT, the adaptive role and regulation of natural transgenes, and new routes for gene trafficking. With an increasing amount of data on HGT, a synthetic view is beginning to emerge.     

Gene Silencing Mediated by Endogenous MicroRNAs under Heat Stress Conditions in Mammalian Cells

Heat shock, sudden change in temperature, triggers various responses in cells for protecting the cells from such a severe circumstance. Here we investigated gene silencing mediated by endogenous microRNAs (miRNAs) in mammalian cells exposed to a mild hyperthermia, by means of miRNA activity assay using a luciferase reporter gene as well as miRNA expression analysis using a DNA microarray. Our findings indicated that the gene silencing activities involving miRNAs were enhanced without increasing in their expression levels under heat-stress conditions. Additionally, the gene silencing activity appeared to be independent of the cytoprotective action involving heat shock proteins that are immediately activated in heat-shocked cells and that function as molecular chaperons for restoring heat-denatured proteins to normal proteins. Our current findings suggested the possibility that gene silencing involving endogenous miRNAs might play a subsidiary role in heat-shocked cells for an aggressive inhibition of the expression of heat-denatured proteins.     

A mixture model with random-effects components for clustering correlated gene-expression profiles

MOTIVATION: The clustering of gene profiles across some experimental conditions of interest contributes significantly to the elucidation of unknown gene function, the validation of gene discoveries and the interpretation of biological processes. However, this clustering problem is not straightforward as the profiles of the genes are not all independently distributed and the expression levels may have been obtained from an experimental design involving replicated arrays. Ignoring the dependence between the gene profiles and the structure of the replicated data can result in important sources of variability in the experiments being overlooked in the analysis, with the consequent possibility of misleading inferences being made. We propose a random-effects model that provides a unified approach to the clustering of genes with correlated expression levels measured in a wide variety of experimental situations. Our model is an extension of the normal mixture model to account for the correlations between the gene profiles and to enable covariate information to be incorporated into the clustering process. Hence the model is applicable to longitudinal studies with or without replication, for example, time-course experiments by using time as a covariate, and to cross-sectional experiments by using categorical covariates to represent the different experimental classes. RESULTS: We show that our random-effects model can be fitted by maximum likelihood via the EM algorithm for which the E(expectation)and M(maximization) steps can be implemented in closed form. Hence our model can be fitted deterministically without the need for time-consuming Monte Carlo approximations. The effectiveness of our model-based procedure for the clustering of correlated gene profiles is demonstrated on three real datasets, representing typical microarray experimental designs, covering time-course, repeated-measurement and cross-sectional data. In these examples, relevant clusters of the genes are obtained, which are supported by existing gene-function annotation. A synthetic dataset is considered too. AVAILABILITY: A Fortran program blue called EMMIX-WIRE (EM-based MIXture analysis WIth Random Effects) is available on request from the corresponding author.     

Increasing the power to detect causal associations by combining genotypic and expression data in segregating populations

To dissect common human diseases such as obesity and diabetes, a systematic approach is needed to study how genes interact with one another, and with genetic and environmental factors, to determine clinical end points or disease phenotypes. Bayesian networks provide a convenient framework for extracting relationships from noisy data and are frequently applied to large-scale data to derive causal relationships among variables of interest. Given the complexity of molecular networks underlying common human disease traits, and the fact that biological networks can change depending on environmental conditions and genetic factors, large datasets, generally involving multiple perturbations (experiments), are required to reconstruct and reliably extract information from these networks. With limited resources, the balance of coverage of multiple perturbations and multiple subjects in a single perturbation needs to be considered in the experimental design. Increasing the number of experiments, or the number of subjects in an experiment, is an expensive and time-consuming way to improve network reconstruction. Integrating multiple types of data from existing subjects might be more efficient. For example, it has recently been demonstrated that combining genotypic and gene expression data in a segregating population leads to improved network reconstruction, which in turn may lead to better predictions of the effects of experimental perturbations on any given gene. Here we simulate data based on networks reconstructed from biological data collected in a segregating mouse population and quantify the improvement in network reconstruction achieved using genotypic and gene expression data, compared with reconstruction using gene expression data alone. We demonstrate that networks reconstructed using the combined genotypic and gene expression data achieve a level of reconstruction accuracy that exceeds networks reconstructed from expression data alone, and that fewer subjects may be required to achieve this superior reconstruction accuracy. We conclude that this integrative genomics approach to reconstructing networks not only leads to more predictive network models, but also may save time and money by decreasing the amount of data that must be generated under any given condition of interest to construct predictive network models.     

Microbial adaptations to the psychrosphere/piezosphere

Low temperature and high pressure deep-sea environments occupy the largest fraction of the biosphere. Nevertheless, the molecular adaptations that enable life to exist under these conditions remain poorly understood. This article will provide an overview of the current picture on high pressure adaptation in cold oceanic environments, with an emphasis on genetic experiments performed on Photobacterium profundum. Thus far genes which have been found or implicated as important for pressure-sensing or pressure-adaptation include genes required for fatty acid unsaturation, the membrane protein genes toxR and rseC and the DNA recombination gene recD. Many deep-sea bacteria possess genes for the production of omega-3 polyunsaturated fatty acids. These could be of biotechnological significance since these fatty acids reduce the risk of cardiovascular disease and certain cancers and are useful as dietary supplements.     

Some statistical issues in microarray gene expression data

In this paper we discuss some of the statistical issues that should be considered when conducting experiments involving microarray gene expression data. We discuss statistical issues related to preprocessing the data as well as the analysis of the data. Analysis of the data is discussed in three contexts: class comparison, class prediction and class discovery. We also review the methods used in two studies that are using microarray gene expression to assess the effect of exposure to radiofrequency (RF) fields on gene expression. Our intent is to provide a guide for radiation researchers when conducting studies involving microarray gene expression data.     

A paleoecological model for the origin of higher primates

Tertiary climatic oscillations initiated the origin of anthropoid primates. A paleoecological model of anthropoid evolution is presented which assumes increasing global seasonality in the late Eocene. Size changes are effected to stabilize internal temperature fluctuations under cooler climatic conditions. Because larger body size is associated with diurnality and reduced litter size, these anthropoid behavoral and reproductive features also fit into the model. Dietary changes involving an emphasis on frugivory, which becomes a more predictable dietary mode under seasonal conditions, can be associated with the development of a post-orbital septum, a broad mesiodistal incisal span, the evolution of color vision, reduction of the olfactory bulbs, and the concomitant enlargement of areas of the brain relating to the processing of visual information. Finally, postural behavior or locomotion might be included in this model if frugivorous foraging and feeding behavior led to the development of a basic level of anthropoid locomotor morphology, involving adaptations for arboreal quadrupedalism.     

Meiotic transmission of Drosophila pseudoobscura chromosomal arrangements

Drosophila pseudoobscura harbors a rich gene arrangement polymorphism on the third chromosome generated by a series of overlapping paracentric inversions. The arrangements suppress recombination in heterokaryotypic individuals, which allows for the selective maintenance of coadapted gene complexes. Previous mapping experiments used to determine the degree to which recombination is suppressed in gene arrangement heterozygotes produced non-recombinant progeny in non-Mendelian ratios. The deviations from Mendelian expectations could be the result of viability differences between wild and mutant chromosomes, meiotic drive because of achiasmate pairing of homologues in heterokaryotypic females during meiosis, or a combination of both mechanisms. The possibility that the frequencies of the chromosomal arrangements in natural populations are affected by mechanisms other than adaptive selection led us to consider these hypotheses. We performed reciprocal crosses involving both heterozygous males and females to determine if the frequency of the non-recombinant progeny deviates significantly from Mendelian expectations and if the frequencies deviate between reciprocal crosses. We failed to observe non-Mendelian ratios in multiple crosses, and the frequency of the non-recombinant classes differed in only one of five pairs of reciprocal crosses despite sufficient power to detect these differences in all crosses. Our results indicate that deviations from Mendelian expectations in recombination experiments involving the D. pseudoobscura inversion system are most likely due to fitness differences of gene arrangement karyotypes in different environments.     

Experiment specific expression patterns

The differential analysis of genes between microarrays from several experimental conditions or treatments routinely estimates which genes change significantly between groups. As genes are never regulated individually, observed behavior may be a consequence of changes in other genes. Existing approaches like co-expression analysis aim to resolve such patterns from a wide range of experiments. The knowledge of such a background set of experiments can be used to compute expected gene behavior based on known links. It is particularly interesting to detect previously unseen specific effects in other experiments. Here, a new method to spot genes deviating from expected behavior (PAttern DEviation SCOring--Padesco) is devised. It uses linear regression models learned from a background set to arrive at gene specific prediction accuracy distributions. For a given experiment, it is then decided whether each gene is predicted better or worse than expected. This provides a novel way to estimate the experiment specificity of each gene. We propose a validation procedure to estimate the detection of such specific candidates and show that these can be identified with an average accuracy of about 85%.     

Cloning and characterization of araA, araB, and araD, the structural genes for L-arabinose utilization in Bacillus subtilis.

Two recombinant plasmids, pSNL1 and pSNL2, carrying structural genes for L-arabinose utilization were isolated from a Bacillus subtilis gene library. Both plasmids complemented araD mutations in a Rec- B. subtilis strain and in Escherichia coli. Moreover, pSNL1 also complemented araB mutations in both species and efficiently transformed araA Rec+ B. subtilis strains to Ara+. Detailed physical mapping of both plasmids in addition to transformation experiments involving defined restriction fragments from the pSNL1 insert unambiguously determined the gene order to be araD, araB, and araA, an order different from that found in E. coli.     

Global gene expression profiling in Escherichia coli K12. The effects of oxygen availability and FNR

The work presented here is a first step toward a long term goal of systems biology, the complete elucidation of the gene regulatory networks of a living organism. To this end, we have employed DNA microarray technology to identify genes involved in the regulatory networks that facilitate the transition of Escherichia coli cells from an aerobic to an anaerobic growth state. We also report the identification of a subset of these genes that are regulated by a global regulatory protein for anaerobic metabolism, FNR. Analysis of these data demonstrated that the expression of over one-third of the genes expressed during growth under aerobic conditions are altered when E. coli cells transition to an anaerobic growth state, and that the expression of 712 (49%) of these genes are either directly or indirectly modulated by FNR. The results presented here also suggest interactions between the FNR and the leucine-responsive regulatory protein (Lrp) regulatory networks. Because computational methods to analyze and interpret high dimensional DNA microarray data are still at an early stage, and because basic issues of data analysis are still being sorted out, much of the emphasis of this work is directed toward the development of methods to identify differentially expressed genes with a high level of confidence. In particular, we describe an approach for identifying gene expression patterns (clusters) obtained from multiple perturbation experiments based on a subset of genes that exhibit high probability for differential expression values.     

The Evaluation and Quantitation of Dihydrogen Metabolism Using Deuterium Isotope in Rats

Purpose

Despite the significant interest in molecular hydrogen as an antioxidant in the last eight years, its quantitative metabolic parameters in vivo are still lacking, as is an appropriate method for determination of hydrogen effectivity in the mammalian organism under various conditions.

Basic Procedures

Intraperitoneally-applied deuterium gas was used as a metabolic tracer and deuterium enrichment was determined in the body water pool. Also, in vitro experiments were performed using bovine heart submitochondrial particles to evaluate superoxide formation in Complex I of the respiratory chain.

Main Findings

A significant oxidation of about 10% of the applied dose was found under physiological conditions in rats, proving its antioxidant properties. Hypoxia or endotoxin application did not exert any effect, whilst pure oxygen inhalation reduced deuterium oxidation. During in vitro experiments, a significant reduction of superoxide formation by Complex I of the respiratory chain was found under the influence of hydrogen. The possible molecular mechanisms of the beneficial effects of hydrogen are discussed, with an emphasis on the role of iron sulphur clusters in reactive oxygen species generation and on iron species-dihydrogen interaction.

Principal Conclusions

According to our findings, hydrogen may be an efficient, non-toxic, highly bioavailable and low-cost antioxidant supplement for patients with pathological conditions involving ROS-induced oxidative stress.     

A genetic uncertainty problem

The existence of genes that, when knocked out, result in no obvious phenotype has puzzled biologists for many years. The phenomenon is often ascribed to redundancy in regulatory networks, caused by duplicated genes. However, a recent systematic analysis of data from the yeast genome projects does not support a link between gene duplications and redundancies. An alternative explanation suggests that genes might also evolve by very weak selection, which would mean that their true function cannot be studied in normal laboratory experiments. This problem is comparable to Heisenberg's uncertainty relationship in physics. It is possible to formulate an analogous relationship for biology, which, at its extreme, predicts that the understanding of the full function of a gene might require experiments on an evolutionary scale, involving the entire effective population size of a given species.     

Analysis and quantification of diagnostic serum markers and protein signatures for Gaucher disease

Novel approaches for the qualitative and quantitative proteomics analysis by nanoscale LC-MS applied to the study of protein expression response in depleted and undepleted serum of Gaucher patients undergoing enzyme replacement therapy are presented. Particular emphasis is given to the method reproducibility of these LC-MS experiments without the use of isotopic labels. The level of chitotriosidase, an established Gaucher biomarker, was assessed by means of an absolute concentration determination technique for alternate scanning LC-MS generated data. Disease associated proteins, including fibrinogens, complement cascade proteins, and members of the high density lipoprotein serum content, were recognized by various clustering methods and sorting and intensity profile grouping of identified peptides. Condition-unique LC-MS protein signatures could be generated utilizing the measured serum protein concentrations and are presented for all investigated conditions. The clustering results of the study were also used as input for gene ontology searches to determine the correlation between the molecular functions of the identified peptides and proteins.     

Gene transfer: DNA microinjection compared with DNA transfection with a very high efficiency.

We have developed a procedure that gives a very high efficiency of transfection in mammalian cells with low-molecular-weight DNA (approximately 10(4) base pairs). The procedure uses cells in suspension that are shocked with polyethylene glycol 4 h after replating. We compared this transfection technique to the standard technique involving manual microinjection of DNA into the nuclei of mammalian cells, using recombinant plasmids containing the simian virus 40 A gene or the herpes simplex virus thymidine kinase gene or both. The efficiency of transfection depends on a number of variables, the most important of which is the difference in transfectability of different cell lines. In our laboratory, the cell line that had the highest efficiency of transfection was tk-ts13, which is derived from baby hamster kidney cells that are deficient in thymidine kinase and temperature sensitive for growth. Under the appropriate conditions, as many as 70% of these cells can be transfected so that transient gene expression can be detected. With the manual microinjection technique, gene expression is independent of the cell line used and occurs faster than after transfection. The results suggest that the critical stage in transfection is the delivery of DNA molecules to the nucleus. Our experiments also indicate that an enzymatic function, in our case, thymidine kinase activity, gives a higher percentage of positive transfectants than when proteins are visualized only by indirect immunofluorescence. The transfection procedure described in this paper is simple and reproducible and, although less efficient than microinjection, ought to be useful in phenotypic and genotypic studies in which transfer of genes to a large number of cells is desirable.     

Identification of differentially expressed gene categories in microarray studies using nonparametric multivariate analysis

MOTIVATION: The field of microarray data analysis is shifting emphasis from methods for identifying differentially expressed genes to methods for identifying differentially expressed gene categories. The latter approaches utilize a priori information about genes to group genes into categories and enhance the interpretation of experiments aimed at identifying expression differences across treatments. While almost all of the existing approaches for identifying differentially expressed gene categories are practically useful, they suffer from a variety of drawbacks. Perhaps most notably, many popular tools are based exclusively on gene-specific statistics that cannot detect many types of multivariate expression change. RESULTS: We have developed a nonparametric multivariate method for identifying gene categories whose multivariate expression distribution differs across two or more conditions. We illustrate our approach and compare its performance to several existing procedures via the analysis of a real data set and a unique data-based simulation study designed to capture the challenges and complexities of practical data analysis. We show that our method has good power for differentiating between differentially expressed and non-differentially expressed gene categories, and we utilize a resampling based strategy for controlling the false discovery rate when testing multiple categories. AVAILABILITY: R code (www.r-project.org) for implementing our approach is available from the first author by request.