Abstract Background Whilst being closely related to the model actinomycete Streptomyces coelicolor A3(2), S. lividans 66 differs from it in several significant and phenotypically observable ways, including antibiotic production. Previous comparative gene hybridization studies investigating such differences have used low-density (one probe per gene) PCR-based spotted arrays. Here we use new experimentally optimised 104,000 × 60-mer probe arrays to characterize in detail the genomic differences between wild-type S. lividans 66, a derivative industrial strain, TK24, and S. coelicolor M145. Results The high coverage and specificity (detection of three nucleotide differences) of the new microarrays used has highlighted the macroscopic genomic differences between two S. lividans strains and S. coelicolor . In a series of case studies we have validated the microarray and have identified subtle changes in genomic structure which occur in the Asp-activating adenylation domains of CDA non-ribosomal peptide synthetase genes which provides evidence of gene shuffling between these domains. We also identify single nucleotide sequence inter-species differences which exist in the actinorhodin biosynthetic gene cluster. As the glyoxylate bypass is non-functional in both S. lividans strains due to the absence of the gene encoding isocitrate lyase it is likely that the ethylmalonyl-CoA pathway functions as the alternative mechanism for the assimilation of C 2 compounds. Conclusions This study provides evidence for widespread genetic recombination, rather than it being focussed at 'hotspots', suggesting that the previously proposed 'archipelago model' of genomic differences between S. coelicolor and S. lividans is unduly simplistic. The two S. lividans strains investigated differ considerably in genetic complement, with TK24 lacking 175 more genes than its wild-type parent when compared to S. coelicolor . Additionally, we confirm the presence of bldB in S. lividans and deduce that S. lividans 66 and TK24, both deficient in the glyoxylate bypass, possess an alternative metabolic mechanism for the assimilation of C 2 compounds. Given that streptomycetes generally display high genetic instability it is envisaged that these high-density arrays will find application for rapid assessment of genome content (particularly amplifications/deletions) in mutational studies of S. coelicolor and related species.
Cortisol is a robust circadian signal that synchronises peripheral circadian clocks with the central clock in the suprachiasmatic nucleus via glucocorticoid receptors that regulate peripheral gene expression. Misalignment of the cortisol rhythm with the sleep-wake cycle, as occurs in shift work, is associated with negative health outcomes, but underlying molecular mechanisms remain largely unknown. We experimentally induced misalignment between the sleep-wake cycle and melatonin and cortisol rhythms in humans and measured time series blood transcriptomics while participants slept in-phase and out-of-phase with the central clock. The cortisol rhythm remained unchanged, but many glucocorticoid signalling transcripts were disrupted by mistimed sleep. To investigate which factors drive this dissociation between cortisol and its signalling pathways, we conducted bioinformatic and temporal coherence analyses. We found that glucocorticoid signalling transcripts affected by mistimed sleep were enriched for binding sites for the transcription factor SP1. Furthermore, changes in the timing of the rhythms of SP1 transcripts, a major regulator of transcription, and changes in the timing of rhythms in transcripts of the glucocorticoid signalling pathways were closely associated. Associations between the rhythmic changes in factors that affect SP1 expression and its activity, such as STAT3, EP300, HSP90AA1, and MAPK1, were also observed. We conclude that plasma cortisol rhythms incompletely reflect the impact of mistimed sleep on glucocorticoid signalling pathways and that sleep-wake driven changes in SP1 may mediate disruption of these pathways. These results aid understanding of mechanisms by which mistimed sleep affects health.
Using a sequence-based approach we previously identified an IncI1 CTX-M-1 plasmid, pIFM3791, on a single pig farm in the UK that was harboured by Klebsiella pneumoniae, Escherichia coli and Salmonella enterica serotype 4,5,12:i:-. To test the hypothesis that the plasmid had spread rapidly into these differing host bacteria we wished to assess whether the plasmid conferred a fitness advantage. To do this an IncI1 curing vector was constructed and used to displace the IncI1 CTX-M-1 plasmids from K. pneumoniae strain B3791 and several other unrelated IncI1-harbouring strains indicating the potential wider application of the curing vector. The IncI1 CTX-M-1 plasmid was reintroduced by conjugation into the cured K. pneumoniae strain and also a naturally IncI1 plasmid free S. enterica serotype 4,5,12:i:-, S348/11. Original, cured and complemented strains were tested for metabolic competence using Biolog technology and in competitive growth, association to mammalian cells and biofilm formation experiments. The plasmid-cured K. pneumoniae strain grew more rapidly than either the original plasmid-carrying strain or plasmid-complemented strains in competition experiments. Additionally, the plasmid-cured strain was significantly better at respiring with l-sorbose as a carbon source and putrescine, γ-amino-n-butyric acid, l-alanine and l-proline as nitrogen sources. By contrast, no differences in phenotype were found when comparing plasmid-harbouring and plasmid-free S. enterica S348/11. In conclusion, the IncI1 curing vector successfully displaced multiple IncI plasmids. The IncI1 CTX-M1 plasmid conferred a growth disadvantage upon K. pneumoniae, possibly by imposing a metabolic burden, the mechanism of which remains to be determined.
Significance Insufficient sleep and circadian rhythm disruption are associated with negative health outcomes, but the mechanisms involved remain largely unexplored. We show that one wk of insufficient sleep alters gene expression in human blood cells, reduces the amplitude of circadian rhythms in gene expression, and intensifies the effects of subsequent acute total sleep loss on gene expression. The affected genes are involved in chromatin remodeling, regulation of gene expression, and immune and stress responses. The data imply molecular mechanisms mediating the effects of sleep loss on health and highlight the interrelationships between sleep homeostasis, circadian rhythmicity, and metabolism.
Abstract Motivation: In vitro and in vivo selection of vaccines is time consuming, expensive and the selected vaccines may not be able to provide protection against broad-spectrum viruses because of emerging antigenically novel disease strains. A powerful computational model that incorporates these protein/DNA or RNA level fluctuations can effectively predict antigenically variant strains, and can minimize the amount of resources spent on exclusive serological testing of vaccines and make wide spectrum vaccines possible for many diseases. However, in silico vaccine prediction remains a grand challenge. To address the challenge, we investigate the use of linear and non-linear regression models to predict the antigenic similarity in foot-and-mouth disease virus strains and in influenza strains, where the structure and parameters of the non-linear model are optimized using an evolutionary algorithm (EA). In addition, we examine two different scoring methods for weighting the type of amino acid substitutions in the linear and non-linear models. We also test our models with some unseen data. Results: We achieved the best prediction results on three datasets of SAT2 (Foot-and-Mouth disease), two datasets of serotype A (Foot-and-Mouth disease) and two datasets of influenza when the scoring method based on biochemical properties of amino acids is employed in combination with a non-linear regression model. Models based on substitutions in the antigenic areas performed better than those that took the entire exposed viral capsid proteins. A majority of the non-linear regression models optimized with the EA performed better than the linear and non-linear models whose parameters are estimated using the least-squares method. In addition, for the best models, optimized non-linear regression models consist of more terms than their linear counterparts, implying a non-linear nature of influences of amino acid substitutions. Our models were also tested on five recently generated FMDV datasets and the best model was able to achieve an 80% agreement rate. Contact: yaochu.jin@surrey.ac.uk or e.laing@surrey.ac.uk
Polymorphisms in human circadian clock gene PERIOD3 (PER3) are associated with a wide variety of phenotypes such as diurnal preference, delayed sleep phase disorder, sleep homeostasis, cognitive performance, bipolar disorder, type 2 diabetes, cardiac regulation, cancer, light sensitivity, hormone and cytokine secretion, and addiction. However, the molecular mechanisms underlying these phenotypic associations remain unknown. Per3 knockout mice (Per3-/-) have phenotypes related to activity, sleep homeostasis, anhedonia, metabolism, and behavioural responses to light. Using a protocol that induces behavioural differences in response to light in wild type and Per3-/- mice, we compared genome-wide expression in the eye and hypothalamus in the two genotypes. Differentially expressed transcripts were related to inflammation, taste, olfactory and melatonin receptors, lipid metabolism, cell cycle, ubiquitination, and hormones, as well as receptors and channels related to sleep regulation. Differentially expressed transcripts in both tissues co-localised with Per3 on an ~8Mbp region of distal chromosome 4. The most down-regulated transcript is Prdm16, which is involved in adipocyte differentiation and may mediate altered body mass accumulation in Per3-/- mice. eQTL analysis with BXD mouse strains showed that the expression of some of these transcripts and also others co-localised at distal chromosome 4, is correlated with brain tissue expression levels of Per3 with a highly significant linkage to genetic variation in that region. These data identify a cluster of transcripts on mouse distal chromosome 4 that are co-regulated with Per3 and whose expression levels correlate with those of Per3. This locus lies within a topologically associating domain island that contains many genes with functional links to several of the diverse non-circadian phenotypes associated with polymorphisms in human PER3.
Two-component regulatory systems allow bacteria to respond adequately to changes in their environment. In response to a given stimulus, a sensory kinase activates its cognate response regulator via reversible phosphorylation. The response regulator DevR activates a state of dormancy under hypoxia in Mycobacterium tuberculosis, allowing this pathogen to escape the host defense system. Here, we show that OsdR (SCO0204) of the soil bacterium Streptomyces coelicolor is a functional orthologue of DevR. OsdR, when activated by the sensory kinase OsdK (SCO0203), binds upstream of the DevR-controlled dormancy genes devR, hspX, and Rv3134c of M. tuberculosis. In silico analysis of the S. coelicolor genome combined with in vitro DNA binding studies identified many binding sites in the genomic region around osdR itself and upstream of stress-related genes. This binding correlated well with transcriptomic responses, with deregulation of developmental genes and genes related to stress and hypoxia in the osdR mutant. A peak in osdR transcription in the wild-type strain at the onset of aerial growth correlated with major changes in global gene expression. Taken together, our data reveal the existence of a dormancy-related regulon in streptomycetes which plays an important role in the transcriptional control of stress- and development-related genes. IMPORTANCE Dormancy is a state of growth cessation that allows bacteria to escape the host defense system and antibiotic challenge. Understanding the mechanisms that control dormancy is of key importance for the treatment of latent infections, such as those from Mycobacterium tuberculosis. In mycobacteria, dormancy is controlled by the response regulator DevR, which responds to conditions of hypoxia. Here, we show that OsdR of Streptomyces coelicolor recognizes the same regulatory element and controls a regulon that consists of genes involved in the control of stress and development. Only the core regulon in the direct vicinity of dosR and osdR is conserved between M. tuberculosis and S. coelicolor, respectively. Thus, we show how the system has diverged from allowing escape from the host defense system by mycobacteria to the control of sporulation by complex multicellular streptomycetes. This provides novel insights into how bacterial growth and development are coordinated with the environmental conditions.
Post-transcriptional control of gene expression is mediated via RNA-binding proteins (RBPs) that interact with mRNAs in a combinatorial fashion. While recent global RNA interactome capture experiments expanded the repertoire of cellular RBPs quiet dramatically, little is known about the assembly of RBPs on particular mRNAs; and how these associations change and control the fate of the mRNA in drug-treatment conditions. Here we introduce a novel biochemical approach, termed tobramycin-based tandem RNA isolation procedure (tobTRIP), to quantify proteins associated with the 3'UTRs of cyclin-dependent kinase inhibitor 1B (CDKN1B/p27Kip1) mRNAs in vivo. P27Kip1 plays an important role in mediating a cell's response to cisplatin (CP), a widely used chemotherapeutic cancer drug that induces DNA damage and cell cycle arrest. We found that p27Kip1 mRNA is stabilized upon CP treatment of HEK293 cells through elements in its 3'UTR. Applying tobTRIP, we further compared the associated proteins in CP and non-treated cells, and identified more than 50 interacting RBPs, many functionally related and evoking a coordinated response. Knock-downs of several of the identified RBPs in HEK293 cells confirmed their involvement in CP-induced p27 mRNA regulation; while knock-down of the KH-type splicing regulatory protein (KHSRP) further enhanced the sensitivity of MCF7 adenocarcinoma cancer cells to CP treatment. Our results highlight the benefit of specific in vivo mRNA-protein interactome capture to reveal post-transcriptional regulatory networks implicated in cellular drug response and adaptation.
A general paucity of knowledge about the metabolic state of Mycobacterium tuberculosis within the host environment is a major factor impeding development of novel drugs against tuberculosis. Current experimental methods do not allow direct determination of the global metabolic state of a bacterial pathogen in vivo, but the transcriptional activity of all encoded genes has been investigated in numerous microarray studies. We describe a novel algorithm, Differential Producibility Analysis (DPA) that uses a metabolic network to extract metabolic signals from transcriptome data. The method utilizes Flux Balance Analysis (FBA) to identify the set of genes that affect the ability to produce each metabolite in the network. Subsequently, Rank Product Analysis is used to identify those metabolites predicted to be most affected by a transcriptional signal. We first apply DPA to investigate the metabolic response of E. coli to both anaerobic growth and inactivation of the FNR global regulator. DPA successfully extracts metabolic signals that correspond to experimental data and provides novel metabolic insights. We next apply DPA to investigate the metabolic response of M. tuberculosis to the macrophage environment, human sputum and a range of in vitro environmental perturbations. The analysis revealed a previously unrecognized feature of the response of M. tuberculosis to the macrophage environment: a down-regulation of genes influencing metabolites in central metabolism and concomitant up-regulation of genes that influence synthesis of cell wall components and virulence factors. DPA suggests that a significant feature of the response of the tubercle bacillus to the intracellular environment is a channeling of resources towards remodeling of its cell envelope, possibly in preparation for attack by host defenses. DPA may be used to unravel the mechanisms of virulence and persistence of M. tuberculosis and other pathogens and may have general application for extracting metabolic signals from other "-omics" data.
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