Identification of peptide ligands to the chemokine receptor CCR5 and their maturation by gene shuffling.

The determination of protein-protein interactions and their role in diverse pathophysiological processes is a promising approach to the identification of molecules of therapeutic potential. This paper describes the identification of peptidic CCR5 receptor ligands as potential drug leads against HIV-1 infection using in vitro evolution based on phage display. A phage-displayed peptide library was used to select for anti-CCR5 peptide. Further in vitro evolution of the peptide by exon shuffling was performed to identify peptides with optimized characteristics for CCR5 receptor. This peptide inhibited HIV coreceptor activity in a cell fusion assay with an IC50 of 5 microM. It did not exhibit either agonistic or antagonistic activity on CCR5 in the concentration range used. To our knowledge, this is a first report that describes the identification of peptide ligands specific to the CCR5 receptor from a phage-displayed library and the maturation of the selected peptide sequence by gene shuffling.

Additive functions in boolean models of gene regulatory network modules.

Gene-on-gene regulations are key components of every living organism. Dynamical abstract models of genetic regulatory networks help explain the genome's evolvability and robustness. These properties can be attributed to the structural topology of the graph formed by genes, as vertices, and regulatory interactions, as edges. Moreover, the actual gene interaction of each gene is believed to play a key role in the stability of the structure. With advances in biology, some effort was deployed to develop update functions in Boolean models that include recent knowledge. We combine real-life gene interaction networks with novel update functions in a Boolean model. We use two sub-networks of biological organisms, the yeast cell-cycle and the mouse embryonic stem cell, as topological support for our system. On these structures, we substitute the original random update functions by a novel threshold-based dynamic function in which the promoting and repressing effect of each interaction is considered. We use a third real-life regulatory network, along with its inferred Boolean update functions to validate the proposed update function. Results of this validation hint to increased biological plausibility of the threshold-based function. To investigate the dynamical behavior of this new model, we visualized the phase transition between order and chaos into the critical regime using Derrida plots. We complement the qualitative nature of Derrida plots with an alternative measure, the criticality distance, that also allows to discriminate between regimes in a quantitative way. Simulation on both real-life genetic regulatory networks show that there exists a set of parameters that allows the systems to operate in the critical region. This new model includes experimentally derived biological information and recent discoveries, which makes it potentially useful to guide experimental research. The update function confers additional realism to the model, while reducing the complexity and solution space, thus making it easier to investigate.

The N-terminal DNA-binding 'zinc finger' of the oestrogen and glucocorticoid receptors determines target gene specificity.

Steroid hormone receptors activate specific gene transcription by binding as hormone-receptor complexes to short DNA enhancer-like elements termed hormone response elements (HREs). We have shown previously that a highly conserved 66 amino acid region of the oestrogen (ER) and glucocorticoid (GR) receptors, which corresponds to part of the receptor DNA binding domain (region C) is responsible for determining the specificity of target gene activation. This region contains two sub-regions (CI and CII) analogous to the 'zinc-fingers' of the transcription factor TFIIIA. We show here that CI and CII appear to be separate domains both involved in DNA binding. Furthermore, using chimaeric ERs in which either the first (N-terminal) (CI) or second (CII) 'zinc finger' region has been exchanged with that of the GR, indicates that it is the first 'zinc finger' which largely determines target gene specificity. We suggest that receptor recognition of the HRE is analogous to that of the helix-turn-helix DNA binding motif in that the receptor binds to DNA as a dimer with the first 'zinc finger' lying in the major groove recognizing one half of the palindromic HRE, and that protein-DNA interaction is stabilized through non-specific DNA binding and dimer interactions contributed by the second 'zinc finger'.

Gene-lifestyle interaction and type 2 diabetes: the EPIC interact case-cohort study.

BACKGROUND Understanding of the genetic basis of type 2 diabetes (T2D) has progressed rapidly, but the interactions between common genetic variants and lifestyle risk factors have not been systematically investigated in studies with adequate statistical power. Therefore, we aimed to quantify the combined effects of genetic and lifestyle factors on risk of T2D in order to inform strategies for prevention. METHODS AND FINDINGS The InterAct study includes 12,403 incident T2D cases and a representative sub-cohort of 16,154 individuals from a cohort of 340,234 European participants with 3.99 million person-years of follow-up. We studied the combined effects of an additive genetic T2D risk score and modifiable and non-modifiable risk factors using Prentice-weighted Cox regression and random effects meta-analysis methods. The effect of the genetic score was significantly greater in younger individuals (p for interaction  = 1.20×10-4). Relative genetic risk (per standard deviation [4.4 risk alleles]) was also larger in participants who were leaner, both in terms of body mass index (p for interaction  = 1.50×10-3) and waist circumference (p for interaction  = 7.49×10-9). Examination of absolute risks by strata showed the importance of obesity for T2D risk. The 10-y cumulative incidence of T2D rose from 0.25% to 0.89% across extreme quartiles of the genetic score in normal weight individuals, compared to 4.22% to 7.99% in obese individuals. We detected no significant interactions between the genetic score and sex, diabetes family history, physical activity, or dietary habits assessed by a Mediterranean diet score. CONCLUSIONS The relative effect of a T2D genetic risk score is greater in younger and leaner participants. However, this sub-group is at low absolute risk and would not be a logical target for preventive interventions. The high absolute risk associated with obesity at any level of genetic risk highlights the importance of universal rather than targeted approaches to lifestyle intervention.

Adaptive divergence of ancient gene duplicates in the avian MHC class II beta.

Gene duplication and neofunctionalization are known to be important processes in the evolution of phenotypic complexity. They account for important evolutionary novelties that confer ecological adaptation, such as the major histocompatibility complex (MHC), a multigene family crucial to the vertebrate immune system. In birds, two MHC class II β (MHCIIβ) exon 3 lineages have been recently characterized, and two hypotheses for the evolutionary history of MHCIIβ lineages were proposed. These lineages could have arisen either by 1) an ancient duplication and subsequent divergence of one paralog or by 2) recent parallel duplications followed by functional convergence. Here, we compiled a data set consisting of 63 MHCIIβ exon 3 sequences from six avian orders to distinguish between these hypotheses and to understand the role of selection in the divergent evolution of the two avian MHCIIβ lineages. Based on phylogenetic reconstructions and simulations, we show that a unique duplication event preceding the major avian radiations gave rise to two ancestral MHCIIβ lineages that were each likely lost once later during avian evolution. Maximum likelihood estimation shows that following the ancestral duplication, positive selection drove a radical shift from basic to acidic amino acid composition of a protein domain facing the α-chain in the MHCII α β-heterodimer. Structural analyses of the MHCII α β-heterodimer highlight that three of these residues are potentially involved in direct interactions with the α-chain, suggesting that the shift following duplication may have been accompanied by coevolution of the interacting α- and β-chains. These results provide new insights into the long-term evolutionary relationships among avian MHC genes and open interesting perspectives for comparative and population genomic studies of avian MHC evolution.

Human synthetic lethal inference as potential anti-cancer target gene detection

Background: Two genes are called synthetic lethal (SL) if mutation of either alone is not lethal, but mutation of both leads to death or a significant decrease in organism's fitness. The detection of SL gene pairs constitutes a promising alternative for anti-cancer therapy. As cancer cells exhibit a large number of mutations, the identification of these mutated genes' SL partners may provide specific anti-cancer drug candidates, with minor perturbations to the healthy cells. Since existent SL data is mainly restricted to yeast screenings, the road towards human SL candidates is limited to inference methods. Results: In the present work, we use phylogenetic analysis and database manipulation (BioGRID for interactions, Ensembl and NCBI for homology, Gene Ontology for GO attributes) in order to reconstruct the phylogenetically-inferred SL gene network for human. In addition, available data on cancer mutated genes (COSMIC and Cancer Gene Census databases) as well as on existent approved drugs (DrugBank database) supports our selection of cancer-therapy candidates.Conclusions: Our work provides a complementary alternative to the current methods for drug discovering and gene target identification in anti-cancer research. Novel SL screening analysis and the use of highly curated databases would contribute to improve the results of this methodology.

Combination of fluorescent reporters for simultaneous monitoring of root colonization and antifungal gene expression by a biocontrol pseudomonad on cereals with flow cytometry.

Some root-associated pseudomonads sustain plant growth by suppressing root diseases caused by pathogenic fungi. We investigated to which extent select cereal cultivars influence expression of relevant biocontrol traits (i.e., root colonization efficacy and antifungal activity) in Pseudomonas fluorescens CHA0. In this representative plant-beneficial bacterium, the antifungal metabolites 2,4-diacetylphloroglucinol (DAPG), pyrrolnitrin (PRN), pyoluteorin (PLT), and hydrogen cyanide (HCN) are required for biocontrol. To monitor host plant effects on the expression of biosynthetic genes for these compounds on roots, we developed fluorescent dual-color reporters suited for flow cytometric analysis using fluorescence-activated cell sorting (FACS). In the dual-label strains, the constitutively expressed red fluorescent protein mCherry served as a cell tag and marker for root colonization, whereas reporter fusions based on the green fluorescent protein allowed simultaneous recording of antifungal gene expression within the same cell. FACS analysis revealed that expression of DAPG and PRN biosynthetic genes was promoted in a cereal rhizosphere, whereas expression of PLT and HCN biosynthetic genes was markedly less sustained. When analyzing the response of the bacterial reporters on roots of a selection of wheat, spelt, and triticale cultivars, we were able to detect subtle species- and cultivar-dependent differences in colonization and DAPG and HCN gene expression levels. The expression of these biocontrol traits was particularly favored on roots of one spelt cultivar, suggesting that a careful choice of pseudomonad-cereal combinations might be beneficial to biocontrol. Our approach may be useful for selective single-cell level analysis of plant effects in other bacteria-root interactions.

Developmental and Environmental Regulation of Aquaporin Gene Expression across Populus Species: Divergence or Redundancy?

Aquaporins (AQPs) are membrane channels belonging to the major intrinsic proteins family and are known for their ability to facilitate water movement. While in Populus trichocarpa, AQP proteins form a large family encompassing fifty-five genes, most of the experimental work focused on a few genes or subfamilies. The current work was undertaken to develop a comprehensive picture of the whole AQP gene family in Populus species by delineating gene expression domain and distinguishing responsiveness to developmental and environmental cues. Since duplication events amplified the poplar AQP family, we addressed the question of expression redundancy between gene duplicates. On these purposes, we carried a meta-analysis of all publicly available Affymetrix experiments. Our in-silico strategy controlled for previously identified biases in cross-species transcriptomics, a necessary step for any comparative transcriptomics based on multispecies design chips. Three poplar AQPs were not supported by any expression data, even in a large collection of situations (abiotic and biotic constraints, temporal oscillations and mutants). The expression of 11 AQPs was never or poorly regulated whatever the wideness of their expression domain and their expression level. Our work highlighted that PtTIP1;4 was the most responsive gene of the AQP family. A high functional divergence between gene duplicates was detected across species and in response to tested cues, except for the root-expressed PtTIP2;3/PtTIP2;4 pair exhibiting 80% convergent responses. Our meta-analysis assessed key features of aquaporin expression which had remained hidden in single experiments, such as expression wideness, response specificity and genotype and environment interactions. By consolidating expression profiles using independent experimental series, we showed that the large expansion of AQP family in poplar was accompanied with a strong divergence of gene expression, even if some cases of functional redundancy could be suspected.

Dramatic influence of V beta gene polymorphism on an antigen-specific CD8+ T cell response in vivo.

According to recent crystallographic studies, the TCR-alpha beta contacts MHC class I-bound antigenic peptides via the polymorphic V gene-encoded complementarity-determining region 1 beta (CDR1 beta) and the hypervariable (D)J-encoded CDR3 beta and CDR3 alpha domains. To evaluate directly the relative importance of CDR1 beta polymorphism on the fine specificity of T cell responses in vivo, we have taken advantage of congenic V beta a and V beta b mouse strains that differ by a CDR1 polymorphism in the V beta 10 gene segment. The V beta 10-restricted CD8+ T cell response to a defined immunodominant epitope was dramatically reduced in V beta a compared with V beta b mice, as measured either by the expansion of V beta 10+ cells or by the binding of MHC-peptide tetramers. These data indicate that V beta polymorphism has an important impact on TCR-ligand binding in vivo, presumably by modifying the affinity of CDR1 beta-peptide interactions.

C/EBPbeta couples dopamine signalling to substance P precursor gene expression in striatal neurones.

Dopamine-induced changes in striatal gene expression are thought to play an important role in drug addiction and compulsive behaviour. In this study we report that dopamine induces the expression of the transcription factor CCAAT/Enhancer Binding Protein beta (C/EBP)-beta in primary cultures of striatal neurones. We identified the preprotachykinin-A (PPT-A) gene coding for substance P and neurokinin-A as a potential target gene of C/EBPbeta. We demonstrated that C/EBPbeta physically interacts with an element of the PPT-A promoter, thereby facilitating substance P precursor gene transcription. The regulation of PPT-A gene by C/EBPbeta could subserve many important physiological processes involving substance P, such as nociception, neurogenic inflammation and addiction. Given that substance P is known to increase dopamine signalling in the striatum and, in turn, dopamine increases substance P expression in medium spiny neurones, our results implicate C/EBPbeta in a positive feedback loop, changes of which might contribute to the development of drug addiction.

Reactive electrophile species activate defense gene expression in Arabidopsis.

Compounds containing alpha,beta-unsaturated carbonyl groups are increasingly implicated as potent regulators of gene expression; some are powerful cytotoxins known to accumulate at the site of lesion formation in host-pathogen interactions. We used a robust measurement of photosynthetic efficiency to quantify the toxicity of a variety of lipid derivatives in Arabidopsis leaves. Small alpha,beta-unsaturated carbonyl compounds (e.g. acrolein and methyl vinyl ketone) were highly active and proved to be potent stimulators of expression of the pathogenesis-related gene HEL (PR4). These small volatile electrophiles were far more active than larger alkenal homologs like 2(E)-hexenal, and activated HEL expression in a manner independent of salicylate, ethylene, and jasmonate production/perception. Electrophile treatment massively increased the levels of unesterified cyclopentenone jasmonates, which themselves are electrophiles. Patterns of gene expression in response to electrophile treatment and in response to avirulent bacteria were compared, which revealed strikingly similar transcript profiles. The results broaden the range of known biologic effects of reactive electrophile species to include the activation of a pathogenesis-related gene (HEL) and genes involved in metabolism. Electrophiles can act as mediators of both genetic and biochemical effects on core defense signal transduction.

Plants respond to pathogen infection by enhancing the antifungal gene expression of root-associated bacteria.

Plant health and fitness widely depend on interactions with soil microorganisms. Some bacteria such as pseudomonads can inhibit pathogens by producing antibiotics, and controlling these bacteria could help improve plant fitness. In the present study, we tested whether plants induce changes in the antifungal activity of root-associated bacteria as a response to root pathogens. We grew barley plants in a split-root system with one side of the root system challenged by the pathogen Pythium ultimum and the other side inoculated with the biocontrol strain Pseudomonas fluorescens CHA0. We used reporter genes to follow the expression of ribosomal RNA indicative of the metabolic state and of the gene phlA, required for production of 2,4-diacetylphloroglucinol, a key component of antifungal activity. Infection increased the expression of the antifungal gene phlA. No contact with the pathogen was required, indicating that barley influenced gene expression by the bacteria in a systemic way. This effect relied on increased exudation of diffusible molecules increasing phlA expression, suggesting that communication with rhizosphere bacteria is part of the pathogen response of plants. Tripartite interactions among plants, pathogens, and bacteria appear as a novel determinant of plant response to root pathogens.

The evolutionary conserved BER1 gene is involved in microtubule stability in yeast

In yeast, microtubules are dynamic filaments necessary for spindle and nucleus positioning, as well as for proper chromosome segregation. We identify a function for the yeast gene BER1 (Benomyl REsistant 1) in microtubule stability. BER1 belongs to an evolutionary conserved gene family whose founding member Sensitivity to Red light Reduced is involved in red-light perception and circadian rhythms in Arabidopsis. Here, we present data showing that the ber1Delta mutant is affected in microtubule stability, particularly in presence of microtubule-depolymerising drugs. The pattern of synthetic lethal interactions obtained with the ber1Delta mutant suggests that Ber1 may function in N-terminal protein acetylation. Our work thus suggests that microtubule stability might be regulated through this post-translational modification on yet-to-be determined proteins

Relationship between estrogen receptor alpha location and gene induction reveals the importance of downstream sites and cofactors.

BACKGROUND: To understand cancer-related modifications to transcriptional programs requires detailed knowledge about the activation of signal-transduction pathways and gene expression programs. To investigate the mechanisms of target gene regulation by human estrogen receptor alpha (hERalpha), we combine extensive location and expression datasets with genomic sequence analysis. In particular, we study the influence of patterns of DNA occupancy by hERalpha on expression phenotypes. RESULTS: We find that strong ChIP-chip sites co-localize with strong hERalpha consensus sites and detect nucleotide bias near hERalpha sites. The localization of ChIP-chip sites relative to annotated genes shows that weak sites are enriched near transcription start sites, while stronger sites show no positional bias. Assessing the relationship between binding configurations and expression phenotypes, we find binding sites downstream of the transcription start site (TSS) to be equally good or better predictors of hERalpha-mediated expression as upstream sites. The study of FOX and SP1 cofactor sites near hERalpha ChIP sites shows that induced genes frequently have FOX or SP1 sites. Finally we integrate these multiple datasets to define a high confidence set of primary hERalpha target genes. CONCLUSION: Our results support the model of long-range interactions of hERalpha with the promoter-bound cofactor SP1 residing at the promoter of hERalpha target genes. FOX motifs co-occur with hERalpha motifs along responsive genes. Importantly we show that the spatial arrangement of sites near the start sites and within the full transcript is important in determining response to estrogen signaling.

Gene Ontology Function prediction in Mollicutes using Protein-Protein Association Networks

Abstract Background: Many complex systems can be represented and analysed as networks. The recent availability of large-scale datasets, has made it possible to elucidate some of the organisational principles and rules that govern their function, robustness and evolution. However, one of the main limitations in using protein-protein interactions for function prediction is the availability of interaction data, especially for Mollicutes. If we could harness predicted interactions, such as those from a Protein-Protein Association Networks (PPAN), combining several protein-protein network function-inference methods with semantic similarity calculations, the use of protein-protein interactions for functional inference in this species would become more potentially useful. Results: In this work we show that using PPAN data combined with other approximations, such as functional module detection, orthology exploitation methods and Gene Ontology (GO)-based information measures helps to predict protein function in Mycoplasma genitalium. Conclusions: To our knowledge, the proposed method is the first that combines functional module detection among species, exploiting an orthology procedure and using information theory-based GO semantic similarity in PPAN of the Mycoplasma species. The results of an evaluation show a higher recall than previously reported methods that focused on only one organism network.