UPLC-TOF-MS for plant metabolomics: a sequential approach for wound marker analysis in Arabidopsis thaliana.

The model plant Arabidopsis thaliana was studied for the search of new metabolites involved in wound signalling. Diverse LC approaches were considered in terms of efficiency and analysis time and a 7-min gradient on a UPLC-TOF-MS system with a short column was chosen for metabolite fingerprinting. This screening step was designed to allow the comparison of a high number of samples over a wide range of time points after stress induction in positive and negative ionisation modes. Thanks to data treatment, clear discrimination was obtained, providing lists of potential stress-induced ions. In a second step, the fingerprinting conditions were transferred to longer column, providing a higher peak capacity able to demonstrate the presence of isomers among the highlighted compounds.

Land plants and DNA barcodes: short-term and long-term goals.

Land plants have had the reputation of being problematic for DNA barcoding for two general reasons: (i) the standard DNA regions used in algae, animals and fungi have exceedingly low levels of variability and (ii) the typically used land plant plastid phylogenetic markers (e.g. rbcL, trnL-F, etc.) appear to have too little variation. However, no one has assessed how well current phylogenetic resources might work in the context of identification (versus phylogeny reconstruction). In this paper, we make such an assessment, particularly with two of the markers commonly sequenced in land plant phylogenetic studies, plastid rbcL and internal transcribed spacers of the large subunits of nuclear ribosomal DNA (ITS), and find that both of these DNA regions perform well even though the data currently available in GenBank/EBI were not produced to be used as barcodes and BLAST searches are not an ideal tool for this purpose. These results bode well for the use of even more variable regions of plastid DNA (such as, for example, psbA-trnH) as barcodes, once they have been widely sequenced. In the short term, efforts to bring land plant barcoding up to the standards being used now in other organisms should make swift progress. There are two categories of DNA barcode users, scientists in fields other than taxonomy and taxonomists. For the former, the use of mitochondrial and plastid DNA, the two most easily assessed genomes, is at least in the short term a useful tool that permits them to get on with their studies, which depend on knowing roughly which species or species groups they are dealing with, but these same DNA regions have important drawbacks for use in taxonomic studies (i.e. studies designed to elucidate species limits). For these purposes, DNA markers from uniparentally (usually maternally) inherited genomes can only provide half of the story required to improve taxonomic standards being used in DNA barcoding. In the long term, we will need to develop more sophisticated barcoding tools, which would be multiple, low-copy nuclear markers with sufficient genetic variability and PCR-reliability; these would permit the detection of hybrids and permit researchers to identify the 'genetic gaps' that are useful in assessing species limits.

Living with an imperfect cell wall: compensation of femAB inactivation in Staphylococcus aureus.

BACKGROUND: Synthesis of the Staphylococcus aureus peptidoglycan pentaglycine interpeptide bridge is catalyzed by the nonribosomal peptidyl transferases FemX, FemA and FemB. Inactivation of the femAB operon reduces the interpeptide to a monoglycine, leading to a poorly crosslinked peptidoglycan. femAB mutants show a reduced growth rate and are hypersusceptible to virtually all antibiotics, including methicillin, making FemAB a potential target to restore beta-lactam susceptibility in methicillin-resistant S. aureus (MRSA). Cis-complementation with wild type femAB only restores synthesis of the pentaglycine interpeptide and methicillin resistance, but the growth rate remains low. This study characterizes the adaptations that ensured survival of the cells after femAB inactivation. RESULTS: In addition to slow growth, the cis-complemented femAB mutant showed temperature sensitivity and a higher methicillin resistance than the wild type. Transcriptional profiling paired with reporter metabolite analysis revealed multiple changes in the global transcriptome. A number of transporters for sugars, glycerol, and glycine betaine, some of which could serve as osmoprotectants, were upregulated. Striking differences were found in the transcription of several genes involved in nitrogen metabolism and the arginine-deiminase pathway, an alternative for ATP production. In addition, microarray data indicated enhanced expression of virulence factors that correlated with premature expression of the global regulators sae, sarA, and agr. CONCLUSION: Survival under conditions preventing normal cell wall formation triggered complex adaptations that incurred a fitness cost, showing the remarkable flexibility of S. aureus to circumvent cell wall damage. Potential FemAB inhibitors would have to be used in combination with other antibiotics to prevent selection of resistant survivors.

Characterisation of the putative effector interaction site of the regulatory HbpR protein from Pseudomonas azelaica by site-directed mutagenesis.

Bacterial transcription activators of the XylR/DmpR subfamily exert their expression control via σ(54)-dependent RNA polymerase upon stimulation by a chemical effector, typically an aromatic compound. Where the chemical effector interacts with the transcription regulator protein to achieve activation is still largely unknown. Here we focus on the HbpR protein from Pseudomonas azelaica, which is a member of the XylR/DmpR subfamily and responds to biaromatic effectors such as 2-hydroxybiphenyl. We use protein structure modeling to predict folding of the effector recognition domain of HbpR and molecular docking to identify the region where 2-hydroxybiphenyl may interact with HbpR. A large number of site-directed HbpR mutants of residues in- and outside the predicted interaction area was created and their potential to induce reporter gene expression in Escherichia coli from the cognate P(C) promoter upon activation with 2-hydroxybiphenyl was studied. Mutant proteins were purified to study their conformation. Critical residues for effector stimulation indeed grouped near the predicted area, some of which are conserved among XylR/DmpR subfamily members in spite of displaying different effector specificities. This suggests that they are important for the process of effector activation, but not necessarily for effector specificity recognition.

Revisiting sodium and water reabsorption with functional genomics tools.

PURPOSE OF REVIEW: The kidney plays an essential role in maintaining sodium and water balance, thereby controlling the volume and osmolarity of the extracellular body fluids, the blood volume and the blood pressure. The final adjustment of sodium and water reabsorption in the kidney takes place in cells of the distal part of the nephron in which a set of apical and basolateral transporters participate in vectorial sodium and water transport from the tubular lumen to the interstitium and, finally, to the general circulation. According to a current model, the activity and/or cell-surface expression of these transporters is/are under the control of a gene network composed of the hormonally regulated, as well as constitutively expressed, genes. It is proposed that this gene network may include new candidate genes for salt- and water-losing syndromes and for salt-sensitive hypertension. A new generation of functional genomics techniques have recently been applied to the characterization of this gene network. The purpose of this review is to summarize these studies and to discuss the potential of the different techniques for characterization of the renal transcriptome. RECENT FINDINGS: Recently, DNA microarrays and serial analysis of gene expression have been applied to characterize the kidney transcriptome in different in-vivo and in-vitro models. In these studies, a set of new interesting genes potentially involved in the regulation of sodium and water reabsorption by the kidney have been identified and are currently under detailed investigation. SUMMARY: Characterization of the kidney transcriptome is greatly expanding our knowledge of the gene networks involved in multiple kidney functions, including the maintenance of sodium and water homeostasis.

Identification of cancer/testis-antigen genes by massively parallel signature sequencing.

Massively parallel signature sequencing (MPSS) generates millions of short sequence tags corresponding to transcripts from a single RNA preparation. Most MPSS tags can be unambiguously assigned to genes, thereby generating a comprehensive expression profile of the tissue of origin. From the comparison of MPSS data from 32 normal human tissues, we identified 1,056 genes that are predominantly expressed in the testis. Further evaluation by using MPSS tags from cancer cell lines and EST data from a wide variety of tumors identified 202 of these genes as candidates for encoding cancer/testis (CT) antigens. Of these genes, the expression in normal tissues was assessed by RT-PCR in a subset of 166 intron-containing genes, and those with confirmed testis-predominant expression were further evaluated for their expression in 21 cancer cell lines. Thus, 20 CT or CT-like genes were identified, with several exhibiting expression in five or more of the cancer cell lines examined. One of these genes is a member of a CT gene family that we designated as CT45. The CT45 family comprises six highly similar (>98% cDNA identity) genes that are clustered in tandem within a 125-kb region on Xq26.3. CT45 was found to be frequently expressed in both cancer cell lines and lung cancer specimens. Thus, MPSS analysis has resulted in a significant extension of our knowledge of CT antigens, leading to the discovery of a distinctive X-linked CT-antigen gene family.

Generative FDG-PET and MRI model of aging and disease progression in Alzheimer's disease.

The failure of current strategies to provide an explanation for controversial findings on the pattern of pathophysiological changes in Alzheimer's Disease (AD) motivates the necessity to develop new integrative approaches based on multi-modal neuroimaging data that captures various aspects of disease pathology. Previous studies using [18F]fluorodeoxyglucose positron emission tomography (FDG-PET) and structural magnetic resonance imaging (sMRI) report controversial results about time-line, spatial extent and magnitude of glucose hypometabolism and atrophy in AD that depend on clinical and demographic characteristics of the studied populations. Here, we provide and validate at a group level a generative anatomical model of glucose hypo-metabolism and atrophy progression in AD based on FDG-PET and sMRI data of 80 patients and 79 healthy controls to describe expected age and symptom severity related changes in AD relative to a baseline provided by healthy aging. We demonstrate a high level of anatomical accuracy for both modalities yielding strongly age- and symptom-severity- dependant glucose hypometabolism in temporal, parietal and precuneal regions and a more extensive network of atrophy in hippocampal, temporal, parietal, occipital and posterior caudate regions. The model suggests greater and more consistent changes in FDG-PET compared to sMRI at earlier and the inversion of this pattern at more advanced AD stages. Our model describes, integrates and predicts characteristic patterns of AD related pathology, uncontaminated by normal age effects, derived from multi-modal data. It further provides an integrative explanation for findings suggesting a dissociation between early- and late-onset AD. The generative model offers a basis for further development of individualized biomarkers allowing accurate early diagnosis and treatment evaluation.

Implicit methods for qualitative modeling of gene regulatory networks.

Advancements in high-throughput technologies to measure increasingly complex biological phenomena at the genomic level are rapidly changing the face of biological research from the single-gene single-protein experimental approach to studying the behavior of a gene in the context of the entire genome (and proteome). This shift in research methodologies has resulted in a new field of network biology that deals with modeling cellular behavior in terms of network structures such as signaling pathways and gene regulatory networks. In these networks, different biological entities such as genes, proteins, and metabolites interact with each other, giving rise to a dynamical system. Even though there exists a mature field of dynamical systems theory to model such network structures, some technical challenges are unique to biology such as the inability to measure precise kinetic information on gene-gene or gene-protein interactions and the need to model increasingly large networks comprising thousands of nodes. These challenges have renewed interest in developing new computational techniques for modeling complex biological systems. This chapter presents a modeling framework based on Boolean algebra and finite-state machines that are reminiscent of the approach used for digital circuit synthesis and simulation in the field of very-large-scale integration (VLSI). The proposed formalism enables a common mathematical framework to develop computational techniques for modeling different aspects of the regulatory networks such as steady-state behavior, stochasticity, and gene perturbation experiments.

Proteomics of methylene blue photo-treated plasma before and after removal of the dye by an absorbent filter.

Methylene blue (MB) and light are used for virus inactivation of plasma for transfusion. However, the presence of MB has been the subject of concern, and efforts have been made to efficiently remove the dye after photo-treatment. For this study, plasma was collected by apheresis from 10 donors (group A), then treated using the MacoPharma THERAFLEX procedure (MB; 1 microM, and light exposure; 180 J/cm(2)) (group B), and finally filtered in order to remove the dye (group C). Proteins were analyzed by two-dimensional electrophoresis, and peptides showing modifications were characterized by mass spectrometry. Clottable and antigenic fibrinogen levels, as well as fibrin polymerization time were measured. Analyses of the gels focused on a region corresponding to pI between 4.5 and 6.5, and M(r) from 7000 to 58 000. In this area, 387 +/- 47 spots matched, and four of these spots presented significant modifications. They corresponded to changes of the gamma-chain of fibrinogen, of transthyretin, and of apolipoprotein A-I, respectively. A decrease of clottable fibrinogen and a prolongation of fibrin polymerization time were observed in groups B and C. Removal of MB by filtration was not responsible for additional protein alterations. The effect of over-treatment of plasma by very high concentrations of MB (50 microM) in association with prolonged light exposure (3 h) was also analyzed, and showed complex alterations of most of the plasma proteins, including fibrinogen gamma-chain, transthyretin, and apolipoprotein A-I. Our data indicates that MB treatment at high concentration and prolonged illumination severely injure plasma proteins. By contrast, at the MB concentration used to inactivate viruses, damages are apparently very restricted.

GENCODE: producing a reference annotation for ENCODE.

BACKGROUND: The GENCODE consortium was formed to identify and map all protein-coding genes within the ENCODE regions. This was achieved by a combination of initial manual annotation by the HAVANA team, experimental validation by the GENCODE consortium and a refinement of the annotation based on these experimental results. RESULTS: The GENCODE gene features are divided into eight different categories of which only the first two (known and novel coding sequence) are confidently predicted to be protein-coding genes. 5' rapid amplification of cDNA ends (RACE) and RT-PCR were used to experimentally verify the initial annotation. Of the 420 coding loci tested, 229 RACE products have been sequenced. They supported 5' extensions of 30 loci and new splice variants in 50 loci. In addition, 46 loci without evidence for a coding sequence were validated, consisting of 31 novel and 15 putative transcripts. We assessed the comprehensiveness of the GENCODE annotation by attempting to validate all the predicted exon boundaries outside the GENCODE annotation. Out of 1,215 tested in a subset of the ENCODE regions, 14 novel exon pairs were validated, only two of them in intergenic regions. CONCLUSION: In total, 487 loci, of which 434 are coding, have been annotated as part of the GENCODE reference set available from the UCSC browser. Comparison of GENCODE annotation with RefSeq and ENSEMBL show only 40% of GENCODE exons are contained within the two sets, which is a reflection of the high number of alternative splice forms with unique exons annotated. Over 50% of coding loci have been experimentally verified by 5' RACE for EGASP and the GENCODE collaboration is continuing to refine its annotation of 1% human genome with the aid of experimental validation.

Comparative genomics of emerging pathogens in the Candida glabrata clade

BACKGROUND: Candida glabrata follows C. albicans as the second or third most prevalent cause of candidemia worldwide. These two pathogenic yeasts are distantly related, C. glabrata being part of the Nakaseomyces, a group more closely related to Saccharomyces cerevisiae. Although C. glabrata was thought to be the only pathogenic Nakaseomyces, two new pathogens have recently been described within this group: C. nivariensis and C. bracarensis. To gain insight into the genomic changes underlying the emergence of virulence, we sequenced the genomes of these two, and three other non-pathogenic Nakaseomyces, and compared them to other sequenced yeasts. RESULTS: Our results indicate that the two new pathogens are more closely related to the non-pathogenic N. delphensis than to C. glabrata. We uncover duplications and accelerated evolution that specifically affected genes in the lineage preceding the group containing N. delphensis and the three pathogens, which may provide clues to the higher propensity of this group to infect humans. Finally, the number of Epa-like adhesins is specifically enriched in the pathogens, particularly in C. glabrata. CONCLUSIONS: Remarkably, some features thought to be the result of adaptation of C. glabrata to a pathogenic lifestyle, are present throughout the Nakaseomyces, indicating these are rather ancient adaptations to other environments. Phylogeny suggests that human pathogenesis evolved several times, independently within the clade. The expansion of the EPA gene family in pathogens establishes an evolutionary link between adhesion and virulence phenotypes. Our analyses thus shed light onto the relationships between virulence and the recent genomic changes that occurred within the Nakaseomyces.

Genome-wide prediction of matrix attachment regions that increase gene expression in mammalian cells.

Gene transfer in eukaryotic cells and organisms suffers from epigenetic effects that result in low or unstable transgene expression and high clonal variability. Use of epigenetic regulators such as matrix attachment regions (MARs) is a promising approach to alleviate such unwanted effects. Dissection of a known MAR allowed the identification of sequence motifs that mediate elevated transgene expression. Bioinformatics analysis implied that these motifs adopt a curved DNA structure that positions nucleosomes and binds specific transcription factors. From these observations, we computed putative MARs from the human genome. Cloning of several predicted MARs indicated that they are much more potent than the previously known element, boosting the expression of recombinant proteins from cultured cells as well as mediating high and sustained expression in mice. Thus we computationally identified potent epigenetic regulators, opening new strategies toward high and stable transgene expression for research, therapeutic production or gene-based therapies.

Minimization of biosynthetic costs in adaptive gene expression responses of yeast to environmental changes

Yeast successfully adapts to an environmental stress by altering physiology and fine-tuning metabolism. This fine-tuning is achieved through regulation of both gene expression and protein activity, and it is shaped by various physiological requirements. Such requirements impose a sustained evolutionary pressure that ultimately selects a specific gene expression profile, generating a suitable adaptive response to each environmental change. Although some of the requirements are stress specific, it is likely that others are common to various situations. We hypothesize that an evolutionary pressure for minimizing biosynthetic costs might have left signatures in the physicochemical properties of proteins whose gene expression is fine-tuned during adaptive responses. To test this hypothesis we analyze existing yeast transcriptomic data for such responses and investigate how several properties of proteins correlate to changes in gene expression. Our results reveal signatures that are consistent with a selective pressure for economy in protein synthesis during adaptive response of yeast to various types of stress. These signatures differentiate two groups of adaptive responses with respect to how cells manage expenditure in protein biosynthesis. In one group, significant trends towards downregulation of large proteins and upregulation of small ones are observed. In the other group we find no such trends. These results are consistent with resource limitation being important in the evolution of the first group of stress responses.

Angiogenic activity of breast cancer patients' monocytes reverted by combined use of systems modeling and experimental approaches.

Angiogenesis plays a key role in tumor growth and cancer progression. TIE-2-expressing monocytes (TEM) have been reported to critically account for tumor vascularization and growth in mouse tumor experimental models, but the molecular basis of their pro-angiogenic activity are largely unknown. Moreover, differences in the pro-angiogenic activity between blood circulating and tumor infiltrated TEM in human patients has not been established to date, hindering the identification of specific targets for therapeutic intervention. In this work, we investigated these differences and the phenotypic reversal of breast tumor pro-angiogenic TEM to a weak pro-angiogenic phenotype by combining Boolean modelling and experimental approaches. Firstly, we show that in breast cancer patients the pro-angiogenic activity of TEM increased drastically from blood to tumor, suggesting that the tumor microenvironment shapes the highly pro-angiogenic phenotype of TEM. Secondly, we predicted in silico all minimal perturbations transitioning the highly pro-angiogenic phenotype of tumor TEM to the weak pro-angiogenic phenotype of blood TEM and vice versa. In silico predicted perturbations were validated experimentally using patient TEM. In addition, gene expression profiling of TEM transitioned to a weak pro-angiogenic phenotype confirmed that TEM are plastic cells and can be reverted to immunological potent monocytes. Finally, the relapse-free survival analysis showed a statistically significant difference between patients with tumors with high and low expression values for genes encoding transitioning proteins detected in silico and validated on patient TEM. In conclusion, the inferred TEM regulatory network accurately captured experimental TEM behavior and highlighted crosstalk between specific angiogenic and inflammatory signaling pathways of outstanding importance to control their pro-angiogenic activity. Results showed the successful in vitro reversion of such an activity by perturbation of in silico predicted target genes in tumor derived TEM, and indicated that targeting tumor TEM plasticity may constitute a novel valid therapeutic strategy in breast cancer.

Task-Driven Activity Reduces the Cortical Activity Space of the Brain: Experiment and Whole-Brain Modeling.

How a stimulus or a task alters the spontaneous dynamics of the brain remains a fundamental open question in neuroscience. One of the most robust hallmarks of task/stimulus-driven brain dynamics is the decrease of variability with respect to the spontaneous level, an effect seen across multiple experimental conditions and in brain signals observed at different spatiotemporal scales. Recently, it was observed that the trial-to-trial variability and temporal variance of functional magnetic resonance imaging (fMRI) signals decrease in the task-driven activity. Here we examined the dynamics of a large-scale model of the human cortex to provide a mechanistic understanding of these observations. The model allows computing the statistics of synaptic activity in the spontaneous condition and in putative tasks determined by external inputs to a given subset of brain regions. We demonstrated that external inputs decrease the variance, increase the covariances, and decrease the autocovariance of synaptic activity as a consequence of single node and large-scale network dynamics. Altogether, these changes in network statistics imply a reduction of entropy, meaning that the spontaneous synaptic activity outlines a larger multidimensional activity space than does the task-driven activity. We tested this model's prediction on fMRI signals from healthy humans acquired during rest and task conditions and found a significant decrease of entropy in the stimulus-driven activity. Altogether, our study proposes a mechanism for increasing the information capacity of brain networks by enlarging the volume of possible activity configurations at rest and reliably settling into a confined stimulus-driven state to allow better transmission of stimulus-related information.