Nutrient-Dependent Trade-Offs between Ribosomes and Division Protein Synthesis Control Bacterial Cell Size and Growth

Cell size control emerges from a regulated balance between the rates of cell growth and division. In bacteria, simple quantitative laws connect cellular growth rate to ribosome abundance. However, it remains poorly understood how translation regulates bacterial cell size and shape under growth perturbations. Here, we develop a whole-cell model for growth dynamics of rod-shaped bacteria that links ribosomal abundance with cell geometry, division control, and the extracellular environment. Our study reveals that cell size maintenance under nutrient perturbations requires a balanced trade-off between ribosomes and division protein synthesis. Deviations from this trade-off relationship are predicted under translation inhibition, leading to distinct modes of cell morphological changes, in agreement with single-cell experimental data on Escherichia coli. Furthermore, by calibrating our model with experimental data, we predict how combinations of nutrient-, translational-, and shape perturbations can be chosen to optimize bacterial growth fitness and antibiotic resistance

Surface-to-volume scaling and aspect ratio preservation in rod-shaped bacteria

Rod-shaped bacterial cells can readily adapt their lengths and widths in response to environmental changes. While many recent studies have focused on the mechanisms underlying bacterial cell size control, it remains largely unknown how the coupling between cell length and width results in robust control of rod-like bacterial shapes. In this study we uncover a conserved surface-to-volume scaling relation in Escherichia coli and other rod-shaped bacteria, resulting from the preservation of cell aspect ratio. To explain the mechanistic origin of aspect-ratio control, we propose a quantitative model for the coupling between bacterial cell elongation and the accumulation of an essential division protein, FtsZ. This model reveals a mechanism for why bacterial aspect ratio is independent of cell size and growth conditions, and predicts cell morphological changes in response to nutrient perturbations, antibiotics, MreB or FtsZ depletion, in quantitative agreement with experimental dat

A Hybrid Spam Detection Method Based on Unstructured Datasets

This document is the accepted manuscript version of the following article: Shao, Y., Trovati, M., Shi, Q. et al. Soft Comput (2017) 21: 233. The final publication is available at Springer via http://dx.doi.org/10.1007/s00500-015-1959-z. © Springer-Verlag Berlin Heidelberg 2015.The identification of non-genuine or malicious messages poses a variety of challenges due to the continuous changes in the techniques utilised by cyber-criminals. In this article, we propose a hybrid detection method based on a combination of image and text spam recognition techniques. In particular, the former is based on sparse representation-based classification, which focuses on the global and local image features, and a dictionary learning technique to achieve a spam and a ham sub-dictionary. On the other hand, the textual analysis is based on semantic properties of documents to assess the level of maliciousness. More specifically, we are able to distinguish between meta-spam and real spam. Experimental results show the accuracy and potential of our approach.Peer reviewedFinal Accepted Versio

INDCOR white paper on the Design of Complexity IDNs

This white paper was written by the members of the Work Group focusing on design practices of the COST Action 18230 - Interactive Narrative Design for Complexity Representation (INDCOR, WG1). It presents an overview of Interactive Digital Narratives (IDNs) design for complexity representations through IDN workflows and methodologies, IDN authoring tools and applications. It provides definitions of the central elements of the IDN alongside its best practices, designs and methods. Finally, it describes complexity as a feature of IDN, with related examples. In summary, this white paper serves as an orienting map for the field of IDN design, understanding where we are in the contemporary panorama while charting the grounds of their promising futures

Impact of a cis-associated gene expression SNP on chromosome 20q11.22 on bipolar disorder susceptibility, hippocampal structure and cognitive performance.

BackgroundBipolar disorder is a highly heritable polygenic disorder. Recent enrichment analyses suggest that there may be true risk variants for bipolar disorder in the expression quantitative trait loci (eQTL) in the brain.AimsWe sought to assess the impact of eQTL variants on bipolar disorder risk by combining data from both bipolar disorder genome-wide association studies (GWAS) and brain eQTL.MethodTo detect single nucleotide polymorphisms (SNPs) that influence expression levels of genes associated with bipolar disorder, we jointly analysed data from a bipolar disorder GWAS (7481 cases and 9250 controls) and a genome-wide brain (cortical) eQTL (193 healthy controls) using a Bayesian statistical method, with independent follow-up replications. The identified risk SNP was then further tested for association with hippocampal volume (n = 5775) and cognitive performance (n = 342) among healthy individuals.ResultsIntegrative analysis revealed a significant association between a brain eQTL rs6088662 on chromosome 20q11.22 and bipolar disorder (log Bayes factor = 5.48; bipolar disorder P = 5.85×10(-5)). Follow-up studies across multiple independent samples confirmed the association of the risk SNP (rs6088662) with gene expression and bipolar disorder susceptibility (P = 3.54×10(-8)). Further exploratory analysis revealed that rs6088662 is also associated with hippocampal volume and cognitive performance in healthy individuals.ConclusionsOur findings suggest that 20q11.22 is likely a risk region for bipolar disorder; they also highlight the informative value of integrating functional annotation of genetic variants for gene expression in advancing our understanding of the biological basis underlying complex disorders, such as bipolar disorder

Paroxetine suppresses recombinant human P2X7 responses

P2X7 receptor (P2X7) activity may link inflammation to depressive disorders. Genetic variants of human P2X7 have been linked with major depression and bipolar disorders, and the P2X7 knockout mouse has been shown to exhibit anti-depressive-like behaviour. P2X7 is an ATP-gated ion channel and is a major regulator of the pro-inflammatory cytokine interleukin 1β (IL-1β) secretion from monocytes and microglia. We hypothesised that antidepressants may elicit their mood enhancing effects in part via modulating P2X7 activity and reducing inflammatory responses. In this study, we determined whether common psychoactive drugs could affect recombinant and native human P2X7 responses in vitro. Common antidepressants demonstrated opposing effects on human P2X7-mediated responses; paroxetine inhibited while fluoxetine and clomipramine mildly potentiated ATP-induced dye uptake in HEK-293 cells stably expressing recombinant human P2X7. Paroxetine inhibited dye uptake mediated by human P2X7 in a concentration-dependent manner with an IC50 of 24 μM and significantly reduces ATP-induced inward currents. We confirmed that trifluoperazine hydrochloride suppressed human P2X7 responses (IC50 of 6.4 μM). Both paroxetine and trifluoperazine did not inhibit rodent P2X7 responses, and mutation of a known residue (F 95L) did not alter the effect of either drug, suggesting neither drug binds at this site. Finally, we demonstrate that P2X7-induced IL-1β secretion from lipopolysaccharide (LPS)-primed human CD14+ monocytes was suppressed with trifluoperazine and paroxetine

The absence of P2X7 receptors (P2rx7) on non-haematopoietic cells leads to selective alteration in mood-related behaviour with dysregulated gene expression and stress reactivity in mice

The purpose of this study was to explore how genetic deletion and pharmacological antagonism of the P2X7 receptor (P2rx7) alter mood-related behaviour, gene expression and stress reactivity in the brain. The forced swim test (FST), tail suspension test (TST) and amphetamine-induced hyperlocomotion (AH) tests were used in wild-type (P2rx7+/+) and P2rx7-deficient (P2rx7-/-) mice. Biogenic amine levels were analysed in the amygdala and striatum, adrenocorticotropic hormone (ACTH) and corticosterone levels were measured in the plasma and pituitary after restraint stress. Chimeric mice were generated by bone marrow transplantation. A whole genome microarray analysis with real-time polymerase chain reaction validation was performed on the amygdala. In the absence of P2rx7s decreased behavioural despair in the FST, reduced immobility in the TST and attenuated amphetamine-induced hyperactivity were detected. Basal norepinephrine levels were elevated in the amygdala, whereas stress-induced ACTH and corticosterone responses were alleviated in P2rx7-/- mice. Sub-acute treatment with the selective P2rx7 antagonist, Brilliant Blue G, reproduced the effect of genetic deletion in the TST and AH test in P2rx7+/+ but not P2rx7-/- mice. No change in behavioural phenotype was observed in chimeras lacking the P2rx7 in their haematopoietic compartment. Whole genome microarray analysis indicated a widespread up- and down-regulation of genes crucial for synaptic function and neuroplasticity by genetic deletion. Here, we present evidence that the absence of P2rx7s on non-haematopoietic cells leads to a mood-stabilizing phenotype in several behavioural models and suggest a therapeutic potential of P2rx7 antagonists for the treatment of mood disorders

Replication Study and Meta-Analysis in European Samples Supports Association of the 3p21.1 Locus with Bipolar Disorder

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Common variants at 2q11.2, 8q21.3, and 11q13.2 are associated with major mood disorders

Bipolar disorder (BPD) and major depressive disorder (MDD) are primary major mood disorders. Recent studies suggest that they share certain psychopathological features and common risk genes, but unraveling the full genetic architecture underlying the risk of major mood disorders remains an important scientific task. The public genome-wide association study (GWAS) data sets offer the opportunity to examine this topic by utilizing large amounts of combined genetic data, which should ultimately allow a better understanding of the onset and development of these illnesses. Genome-wide meta-analysis was performed by combining two GWAS data sets on BPD and MDD (19,637 cases and 18,083 controls), followed by replication analyses for the loci of interest in independent 12,364 cases and 76,633 controls from additional samples that were not included in the two GWAS data sets. The single-nucleotide polymorphism (SNP) rs10791889 at 11q13.2 was significant in both discovery and replication samples. When combining all samples, this SNP and multiple other SNPs at 2q11.2 (rs717454), 8q21.3 (rs10103191), and 11q13.2 (rs2167457) exhibited genome-wide significant association with major mood disorders. The SNPs in 2q11.2 and 8q21.3 were novel risk SNPs that were not previously reported, and SNPs at 11q13.2 were in high LD with potential BPD risk SNPs implicated in a previous GWAS. The genome-wide significant loci at 2q11.2 and 11q13.2 exhibited strong effects on the mRNA expression of certain nearby genes in cerebellum. In conclusion, we have identified several novel loci associated with major mood disorders, adding further support for shared genetic risk between BPD and MDD. Our study highlights the necessity and importance of mining public data sets to explore risk genes for complex diseases such as mood disorders

Possible Associations of NTRK2 Polymorphisms with Antidepressant Treatment Outcome: Findings from an Extended Tag SNP Approach

Background: Data from clinical studies and results from animal models suggest an involvement of the neurotrophin system in the pathology of depression and antidepressant treatment response. Genetic variations within the genes coding for the brain-derived neurotrophic factor (BDNF) and its key receptor Trkb (NTRK2) may therefore influence the response to antidepressant treatment. Methods: We performed a single and multi-marker association study with antidepressant treatment outcome in 398 depressed Caucasian inpatients participating in the Munich Antidepressant Response Signature (MARS) project. Two Caucasian replication samples (N = 249 and N = 247) were investigated, resulting in a total number of 894 patients. 18 tagging SNPs in the BDNF gene region and 64 tagging SNPs in the NTRK2 gene region were genotyped in the discovery sample; 16 nominally associated SNPs were tested in two replication samples. Results: In the discovery analysis, 7 BDNF SNPs and 9 NTRK2 SNPs were nominally associated with treatment response. Three NTRK2 SNPs (rs10868223, rs1659412 and rs11140778) also showed associations in at least one replication sample and in the combined sample with the same direction of effects ($P_{corr}$ = .018, $P_{corr}$ = .015 and $P_{corr}$ = .004, respectively). We observed an across-gene BDNF-NTRK2 SNP interaction for rs4923468 and rs1387926. No robust interaction of associated SNPs was found in an analysis of BDNF serum protein levels as a predictor for treatment outcome in a subset of 93 patients. Conclusions/Limitations: Although not all associations in the discovery analysis could be unambiguously replicated, the findings of the present study identified single nucleotide variations in the BDNF and NTRK2 genes that might be involved in antidepressant treatment outcome and that have not been previously reported in this context. These new variants need further validation in future association studies