Developmental splicing deregulation in leukodystrophies related to EIF2B mutations.

Leukodystrophies (LD) are rare inherited disorders that primarily affect the white matter (WM) of the central nervous system. The large heterogeneity of LD results from the diversity of the genetically determined defects that interfere with glial cells functions. Astrocytes have been identified as the primary target of LD with cystic myelin breakdown including those related to mutations in the ubiquitous translation initiation factor eIF2B. EIF2B is involved in global protein synthesis and its regulation under normal and stress conditions. Little is known about how eIF2B mutations have a major effect on WM. We performed a transcriptomic analysis using fibroblasts of 10 eIF2B-mutated patients with a severe phenotype and 10 age matched patients with other types of LD in comparison to control fibroblasts. ANOVA was used to identify genes that were statistically significantly differentially expressed at basal state and after ER-stress. The pattern of differentially expressed genes between basal state and ER-stress did not differ significantly among each of the three conditions. However, 70 genes were specifically differentially expressed in eIF2B-mutated fibroblasts whatever the stress conditions tested compared to controls, 96% being under-expressed. Most of these genes were involved in mRNA regulation and mitochondrial metabolism. The 13 most representative genes, including genes belonging to the Heterogeneous Nuclear Ribonucleoprotein (HNRNP) family, described as regulators of splicing events and stability of mRNA, were dysregulated during the development of eIF2B-mutated brains. HNRNPH1, F and C mRNA were over-expressed in foetus but under-expressed in children and adult brains. The abnormal regulation of HNRNP expression in the brain of eIF2B-mutated patients was concomitant with splicing dysregulation of the main genes involved in glial maturation such as PLP1 for oligodendrocytes and GFAP in astrocytes. These findings demonstrate a developmental deregulation of splicing events in glial cells that is related to abnormal production of HNRNP, in eIF2B-mutated brains.

Microarray-based identification of gonad transcripts differentially expressed between lines of Pacific oyster selected to be resistant or susceptible to summer mortality.

Summer mortality of the Pacific oyster Crassostrea gigas is the result of a complex interaction between oysters, their environment, and pathogens. Heredity appears to be a major factor determining the sensitivity of oysters to summer mortality, allowing resistant (R) and susceptible (S) lines to be produced. We conducted genome-wide expression profiling of R and S gonads during the 3-month period preceding a summer mortality event, using a cDNA microarray that we designed. ANOVA analysis revealed that 34 genes were differentially expressed between R and S lines on four dates preceding the mortality event. Annotation of some of these genes highlights reproduction and its allocation and antioxidant defenses as the main pathways that operate differentially between R and S lines. This transcriptional analysis provides new indications to define markers for quantitative trait loci searches and functional studies and evaluate the potential role of each gene in the resistance to summer mortality.

Transcriptional analysis of L-methionine catabolism in the cheese-ripening yeast Yarrowia lipolytica in relation to volatile sulfur compound biosynthesis.

Yarrowia lipolytica is one of the yeasts most frequently isolated from the surface of ripened cheeses. In previous work, it has been shown that this yeast is able to convert L-methionine into various volatile sulfur compounds (VSCs) that may contribute to the typical flavors of several cheeses. In the present study, we show that Y. lipolytica does not assimilate lactate in the presence of L-methionine in a cheeselike medium. Nineteen presumptive genes associated with L-methionine catabolism or pyruvate metabolism in Y. lipolytica were transcriptionally studied in relation to L-methionine degradation. The expression levels of the YlARO8 (YALI0E20977g), YlBAT1 (YALI0D01265g), and YlBAT2 (YALI0F19910g) genes (confirmed by real-time PCR experiments) were found to be strongly up-regulated by L-methionine, and a greater variety and larger amounts of VSCs, such as methanethiol and its autooxidation products (dimethyl disulfide and dimethyl trisulfide), were released in the medium when Y. lipolytica was grown in the presence of a high concentration of L-methionine. In contrast, other genes related to pyruvate metabolism were found to be down-regulated in the presence of L-methionine; two exceptions were the YlPDB1 (YALI0E27005g) and YlPDC6 (YALI0D06930g) genes, which encode a pyruvate dehydrogenase and a pyruvate decarboxylase, respectively. Both transcriptional and biochemical results corroborate the view that transamination is the first step of the enzymatic conversion of L-methionine to VSCs in Y. lipolytica and that the YlARO8, YlBAT1, and YlBAT2 genes could play a key role in this process.

Analyzing stochastic transcription to elucidate the nucleoid's organization.

BACKGROUND: The processes of gene transcription, translation, as well as the reactions taking place between gene products, are subject to stochastic fluctuations. These stochastic events are being increasingly examined as it emerges that they can be crucial in the cell's survival. In a previous study we had examined the transcription patterns of two bacterial species (Escherichia coli and Bacillus subtilis) to elucidate the nucleoid's organization. The basic idea is that genes that share transcription patterns, must share some sort of spatial relationship, even if they are not close to each other on the chromosome. We had found that picking any gene at random, its transcription will be correlated with genes at well-defined short - as well as long-range distances, leaving the explanation of the latter an open question. In this paper we study the transcription correlations when the only transcription taking place is stochastic, in other words, no active or "deterministic" transcription takes place. To this purpose we use transcription data of Sinorhizobium meliloti. RESULTS: Even when only stochastic transcription takes place, the co-expression of genes varies as a function of the distance between genes: we observe again the short-range as well as the regular, long-range correlation patterns. CONCLUSION: We explain these latter with a model based on the physical constraints acting on the DNA, forcing it into a conformation of groups of a few successive large and transcribed loops, which are evenly spaced along the chromosome and separated by small, non-transcribed loops. We discuss the question about the link between shared transcription patterns and physiological relationship and come to the conclusion that when genes are distantly placed along the chromosome, the transcription correlation does not imply a physiological relationship.

A new molecular breast cancer subclass defined from a large scale real-time quantitative RT-PCR study.

BACKGROUND: Current histo-pathological prognostic factors are not very helpful in predicting the clinical outcome of breast cancer due to the disease's heterogeneity. Molecular profiling using a large panel of genes could help to classify breast tumours and to define signatures which are predictive of their clinical behaviour. METHODS: To this aim, quantitative RT-PCR amplification was used to study the RNA expression levels of 47 genes in 199 primary breast tumours and 6 normal breast tissues. Genes were selected on the basis of their potential implication in hormonal sensitivity of breast tumours. Normalized RT-PCR data were analysed in an unsupervised manner by pairwise hierarchical clustering, and the statistical relevance of the defined subclasses was assessed by Chi2 analysis. The robustness of the selected subgroups was evaluated by classifying an external and independent set of tumours using these Chi2-defined molecular signatures. RESULTS: Hierarchical clustering of gene expression data allowed us to define a series of tumour subgroups that were either reminiscent of previously reported classifications, or represented putative new subtypes. The Chi2 analysis of these subgroups allowed us to define specific molecular signatures for some of them whose reliability was further demonstrated by using the validation data set. A new breast cancer subclass, called subgroup 7, that we defined in that way, was particularly interesting as it gathered tumours with specific bioclinical features including a low rate of recurrence during a 5 year follow-up. CONCLUSION: The analysis of the expression of 47 genes in 199 primary breast tumours allowed classifying them into a series of molecular subgroups. The subgroup 7, which has been highlighted by our study, was remarkable as it gathered tumours with specific bioclinical features including a low rate of recurrence. Although this finding should be confirmed by using a larger tumour cohort, it suggests that gene expression profiling using a minimal set of genes may allow the discovery of new subclasses of breast cancer that are characterized by specific molecular signatures and exhibit specific bioclinical features.

Gene expression and biochemical analysis of cheese-ripening yeasts: focus on catabolism of L-methionine, lactate, and lactose.

DNA microarrays of 86 genes from the yeasts Debaryomyces hansenii, Kluyveromyces marxianus, and Yarrowia lipolytica were developed to determine which genes were expressed in a medium mimicking a cheese-ripening environment. These genes were selected for potential involvement in lactose/lactate catabolism and the biosynthesis of sulfur-flavored compounds. Hybridization conditions to follow specifically the expression of homologous genes belonging to different species were set up. The microarray was first validated on pure cultures of each yeast; no interspecies cross-hybridization was observed. Expression patterns of targeted genes were studied in pure cultures of each yeast, as well as in coculture, and compared to biochemical data. As expected, a high expression of the LAC genes of K. marxianus was observed. This is a yeast that efficiently degrades lactose. Several lactate dehydrogenase-encoding genes were also expressed essentially in D. hansenii and K. marxianus, which are two efficient deacidifying yeasts in cheese ripening. A set of genes possibly involved in l-methionine catabolism was also used on the array. Y. lipolytica, which efficiently assimilates l-methionine, also exhibited a high expression of the Saccharomyces cerevisiae orthologs BAT2 and ARO8, which are involved in the l-methionine degradation pathway. Our data provide the first evidence that the use of a multispecies microarray could be a powerful tool to investigate targeted metabolism and possible metabolic interactions between species within microbial cocultures.

Transcriptional analysis of L-methionine catabolism in Brevibacterium linens ATCC9175.

The expression of genes possibly involved in L-methionine and lactate catabolic pathways were performed in Brevibacterium linens (ATCC9175) in the presence or absence of added L-methionine. The expression of 27 genes of 39 selected genes differed significantly in L-methionine-enriched cultures. The expression of the gene encoding L-methionine gamma-lyase (MGL) is high in L-methionine-enriched cultures and is accompanied by a dramatic increase in volatile sulfur compounds (VSC) biosynthesis. Several genes encoding alpha-ketoacid dehydrogenase and one gene encoding an acetolactate synthase were also up-regulated by L-methionine, and are probably involved in the catabolism of alpha-ketobutyrate, the primary degradation product of L-methionine to methanethiol. Gene expression profiles together with biochemical data were used to propose catabolic pathways for L-methionine in B. linens and their possible regulation by L-methionine.

Local decoding of sequences and alignment-free comparison.

Subword composition plays an important role in a lot of analyses of sequences. Here we define and study the "local decoding of order N of sequences," an alternative that avoids some drawbacks of "subwords of length N" approaches while keeping informations about environments of length N in the sequences ("decoding" is taken here in the sense of hidden Markov modeling, i.e., associating some state to all positions of the sequence). We present an algorithm for computing the local decoding of order N of a given set of sequences. Its complexity is linear in the total length of the set (whatever the order N) both in time and memory space. In order to show a use of local decoding, we propose a very basic dissimilarity measure between sequences which can be computed both from local decoding of order N and composition in subwords of length N. The accuracies of these two dissimilarities are evaluated, over several datasets, by computing their linear correlations with a reference alignment-based distance. These accuracies are also compared to the one obtained from another recent alignment-free comparison.

Comments on selected fundamental aspects of microarray analysis.

Microarrays are becoming a ubiquitous tool of research in life sciences. However, the working principles of microarray-based methodologies are often misunderstood or apparently ignored by the researchers who actually perform and interpret experiments. This in turn seems to lead to a common over-expectation regarding the explanatory and/or knowledge-generating power of microarray analyses. In this note we intend to explain basic principles of five (5) major groups of analytical techniques used in studies of microarray data and their interpretation: the principal component analysis (PCA), the independent component analysis (ICA), the t-test, the analysis of variance (ANOVA), and self organizing maps (SOM). We discuss answers to selected practical questions related to the analysis of microarray data. We also take a closer look at the experimental setup and the rules, which have to be observed in order to exploit microarrays efficiently. Finally, we discuss in detail the scope and limitations of microarray-based methods. We emphasize the fact that no amount of statistical analysis can compensate for (or replace) a well thought through experimental setup. We conclude that microarrays are indeed useful tools in life sciences but by no means should they be expected to generate complete answers to complex biological questions. We argue that even well posed questions, formulated within a microarray-specific terminology, cannot be completely answered with the use of microarray analyses alone.

Decoding the nucleoid organisation of Bacillus subtilis and Escherichia coli through gene expression data.

BACKGROUND: Although the organisation of the bacterial chromosome is an area of active research, little is known yet on that subject. The difficulty lies in the fact that the system is dynamic and difficult to observe directly. The advent of massive hybridisation techniques opens the way to further studies of the chromosomal structure because the genes that are co-expressed, as identified by microarray experiments, probably share some spatial relationship. The use of several independent sets of gene expression data should make it possible to obtain an exhaustive view of the genes co-expression and thus a more accurate image of the structure of the chromosome. RESULTS: For both Bacillus subtilis and Escherichia coli the co-expression of genes varies as a function of the distance between the genes along the chromosome. The long-range correlations are surprising: the changes in the level of expression of any gene are correlated (positively or negatively) to the changes in the expression level of other genes located at well-defined long-range distances. This property is true for all the genes, regardless of their localisation on the chromosome. We also found short-range correlations, which suggest that the location of these co-expressed genes corresponds to DNA turns on the nucleoid surface (14-16 genes). CONCLUSION: The long-range correlations do not correspond to the domains so far identified in the nucleoid. We explain our results by a model of the nucleoid solenoid structure based on two types of spirals (short and long). The long spirals are uncoiled expressed DNA while the short ones correspond to coiled unexpressed DNA.

Characterization of the GATC regulatory network in E. coli.

BACKGROUND: The tetranucleotide GATC is methylated in Escherichia. coli by the DNA methyltransferase (Dam) and is known to be implicated in numerous cellular processes. Mutants lacking Dam are characterized by a pleiotropic phenotype. The existence of a GATC regulated network, thought to be involved in cold and oxygen shift, had been proposed and its existence has recently been confirmed. The aim of this article is to describe the components of the GATC regulated network of E. coli in detail and propose a role of this network in the light of an evolutionary advantage for the organism. RESULTS: We have classified the genes of the GATC network according to the EcoCyc functional classes. Comparisons with all of E. coli's genes and the genes involved in the SOS and stress response show that the GATC network forms a group apart. The functional classes that characterize the network are the Energy metabolism (in particular respiration), Fatty acid/ Phospholipid metabolism and Nucleotide metabolism. CONCLUSIONS: The network is thought to come into play when the cell undergoes coldshock and is likely to enter stationary phase.The respiration is almost completely under GATC control and according to our hypothesis it will be blocked at the moment of coldshock; this might give the cell a selective advantage as it increases its chances for survival when entering stationary phase under coldshock. We predict the accumulation of formate and possibly succinate, which might increase the cell's resistance, in this case to antimicrobial agents, when entering stationary phase.

The difficult interpretation of transcriptome data: the case of the GATC regulatory network.

Genomic analyses on part of Escherichia coli's chromosome had suggested the existence of a GATC regulated network. This has recently been confirmed through a transcriptome analysis. Two hypotheses about the molecular control mechanism have been proposed-(i) the GATC network regulation is caused by the presence of GATC clusters within the coding sequences; the regulation is the direct consequence of the clusters' hemi-methylation and therefore their elevated melting temperature, (ii) the regulation is caused by the presence of GATCs in the non-coding 500 bp upstream regions of the affected genes; it is the consequence of an interaction with a regulatory protein like Fnr or CAP. An analysis of the transcriptome data has not allowed us to decide between the two hypotheses. We have therefore taken a classic genomic approach, analyzing the statistical distribution of GATC along the chromosome, using a realistic model of the chromosome as theoretical reference. We observe no particular distribution of GATC in the non-coding upstream regions; however, we confirm the presence of GATC clusters within the genes. In order to verify that the particular distribution observed in E. coli is not a statistical artefact, but has a physiological role, we have carried out the same analysis on Salmonella, making the hypothesis that the genes containing a GATC clusters should be largely the same in the two bacteria. This has been indeed observed, showing that the genes containing a GATC cluster are part of a regulation network. The present is a case study, which demonstrates that the analysis of transcriptome data does not always permit to identify the primary cause of a phenomenon observed; on the other hand, a classic genomic approach linked with a comparative study of related genomes may allow this identification.

The operons, a criterion to compare the reliability of transcriptome analysis tools: ICA is more reliable than ANOVA, PLS and PCA.

The number of statistical tools used to analyze transcriptome data is continuously increasing and no one, definitive method has so far emerged. There is a need for comparison and a number of different approaches has been taken to evaluate the effectiveness of the different statistical tools available for microarray analyses. In this paper, we describe a simple and efficient protocol to compare the reliability of different statistical tools available for microarray analyses. It exploits the fact that genes within an operon exhibit the same expression patterns. In order to compare the tools, the genes are ranked according to the most relevant criterion for each tool; for each tool we look at the number of different operons represented within the first twenty genes detected. We then look at the size of the interval within which we find the most significant genes belonging to each operon in question. This allows us to define and estimate the sensitivity and accuracy of each statistical tool. We have compared four statistical tools using Bacillus subtilis expression data: the analysis of variance (ANOVA), the principal component analysis (PCA), the independent component analysis (ICA) and the partial least square regression (PLS). Our results show ICA to be the most sensitive and accurate of the tools tested. In this article, we have used the protocol to compare statistical tools applied to the analysis of differential gene expression. However, it can also be applied without modification to compare the statistical tools developed for other types of transcriptome analyses, like the study of gene co-expression.

The new variant of the Creutzfeldt-Jakob disease accounts for no relative increase of the Creutzfeldt-Jakob disease mortality rate in the United Kingdom; this fits ill with the new variant being the consequence of consumption of food infected with the agent of Bovine Spongiform Encephalopathy.

BACKGROUND: A new variant of Creutzfeldt-Jakob disease was described in the United Kingdom. It is often claimed that it is caused by consumption of food infected with the agent of bovine spongiform encephalopathy. However, this remains open to question because the number of cases of the variant is, at the present time, less than would be expected from a major food-borne source. DISCUSSION: The EUROCJD cooperative study presents currently available epidemiological data of Creutzfeldt-Jakob disease and its new variant, for nine European countries plus Australia and Canada. Unexpectedly, for the United Kingdom where all but a few cases of the new variant have been reported, these cases have to be included in the incidence curve of the sporadic forms of the disease in order to obtain the best fit with the median curve from all the countries. This variant could be merely a rare clinical phenotype within the sporadic disease. The published clinical and experimental data which suggest that it is linked with bovine spongiform encephalopathy, lead us to propose that this link could be a common etiological origin other than consumption of bovine infected food. In any case, public health recommendations hold and further investigation is required. SUMMARY: The lack of a relative increase of the Creutzfeldt-Jakob-disease mortality rate in the United Kingdom, does not fit well with the new variant being the consequence of consumption of food infected with the agent of bovine spongiform encephalopthy.