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

Extracting biological information from DNA arrays: an unexpected link between arginine and methionine metabolism in Bacillus subtilis

BACKGROUND: In global gene expression profiling experiments, variation in the expression of genes of interest can often be hidden by general noise. To determine how biologically significant variation can be distinguished under such conditions we have analyzed the differences in gene expression when Bacillus subtilis is grown either on methionine or on methylthioribose as sulfur source. RESULTS: An unexpected link between arginine metabolism and sulfur metabolism was discovered, enabling us to identify a high-affinity arginine transport system encoded by the yqiXYZ genes. In addition, we tentatively identified a methionine/methionine sulfoxide transport system which is encoded by the operon ytmIJKLMhisP and is presumably used in the degradation of methionine sulfoxide to methane sulfonate for sulfur recycling. Experimental parameters resulting in systematic biases in gene expression were also uncovered. In particular, we found that the late competence operons comE, comF and comG were associated with subtle variations in growth conditions. CONCLUSIONS: Using variance analysis it is possible to distinguish between systematic biases and relevant gene-expression variation in transcriptome experiments. Co-variation of metabolic gene expression pathways was thus uncovered linking nitrogen and sulfur metabolism in B. subtilis

Analyzing stochastic transcription to elucidate the nucleoid's organization.

International audienceABSTRACT: 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

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