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The complexity of many cellular and organismal traits results from the integration of genetic and environmental factors via molecular networks. Network structure and effect propagation are best understood at the level of functional modules, but so far, no concept has been established to include the global network state. Here, we show when and how genetic perturbations lead to molecular changes that are confined to small parts of a network versus when they lead to modulation of network states. Integrating multi‐omics profiling of genetically heterogeneous budding and fission yeast strains with an array of cellular traits identified a central state transition of the yeast molecular network that is related to PKA and TOR (PT) signaling. Genetic variants affecting this PT state globally shifted the molecular network along a single‐dimensional axis, thereby modulating processes including energy and amino acid metabolism, transcription, translation, cell cycle control, and cellular stress response. We propose that genetic effects can propagate through large parts of molecular networks because of the functional requirement to centrally coordinate the activity of fundamental cellular processes. Synopsis: Genetic variant effects can be described according to the spread of affected molecules across the cellular molecular network. Integrative multi‐omics analyses show how variants can shift network states in a global manner while other variant effects remain local or regional.Global changes of the cellular molecular network in response to genetic variation result from the requirement to balance the activity of diverse cellular processes.Quantification of cellular molecular network state differences due to combined PKA and TOR activity in a scalar quantity ("PT score") captures genetically encoded and environmental variability in transcripts, proteins, and protein phosphorylation in yeast.Genetic alteration of the (PKA/TOR‐dependent) network state affects correlated and anti‐correlated protein pairs across large distances in a physical interaction network.Complex fitness traits such as thermotolerance and longevity are subject to network state alteration. [ABSTRACT FROM AUTHOR]

Genetically encoded fluorescent biosensors have emerged as a powerful tool to support phenotypic screenings of microbes. Optical analyses of fluorescent sensor signals from colonies grown on solid media can be challenging as imaging devices need to be equipped with appropriate filters matching the properties of fluorescent biosensors. Toward versatile fluorescence analyses of different types of biosensor signals derived from arrayed colonies, we investigate here the use of monochromator equipped microplate readers as an alternative to imaging approaches. Indeed, for analyses of the LacI-controlled expression of the reporter mCherry in Corynebacterium glutamicum, or promoter activity using GFP as reporter in Saccharomyces cerevisiae, an improved sensitivity and dynamic range was observed for a microplate reader-based analyses compared to their analyses via imaging. The microplate reader allowed us to capture signals of ratiometric fluorescent reporter proteins (FRPs) with a high sensitivity and thereby to further improve the analysis of internal pH via the pH-sensitive FRP mCherryEA in Escherichia coli colonies. Applicability of this novel technique was further demonstrated by assessing redox states in C. glutamicum colonies using the FRP Mrx1-roGFP2. By the use of a microplate reader, oxidative redox shifts were measured in a mutant strain lacking the non-enzymatic antioxidant mycothiol (MSH), indicating its major role for maintaining a reduced redox state also in colonies on agar plates. Taken together, analyses of biosensor signals from microbial colonies using a microplate reader allows comprehensive phenotypic screenings and thus facilitates further development of new strains for metabolic engineering and systems biology. [ABSTRACT FROM AUTHOR]

Gene expression is controlled by pathways of regulatory factors often involving the activity of protein kinases on transcription factor proteins. Despite this well established mechanism, the number of well described pathways that include the regulatory role of protein kinases on transcription factors is surprisingly scarce in eukaryotes. To address this, PhosTF was developed to infer functional regulatory interactions and pathways in both simulated and real biological networks, based on linear cyclic causal models with latent variables. GeneNetWeaverPhos, an extension of GeneNetWeaver, was developed to allow the simulation of perturbations in known networks that included the activity of protein kinases and phosphatases on gene regulation. Over 2000 genome-wide gene expression profiles, where the loss or gain of regulatory genes could be observed to perturb gene regulation, were then used to infer the existence of regulatory interactions, and their mode of regulation in the budding yeast Saccharomyces cerevisiae. Despite the additional complexity, our inference performed comparably to the best methods that inferred transcription factor regulation assessed in the DREAM4 challenge on similar simulated networks. Inference on integrated genome-scale data sets for yeast identified ∼ 8800 protein kinase/phosphatase-transcription factor interactions and ∼ 6500 interactions among protein kinases and/or phosphatases. Both types of regulatory predictions captured statistically significant numbers of known interactions of their type. Surprisingly, kinases and phosphatases regulated transcription factors by a negative mode or regulation (deactivation) in over 70% of the predictions. Author summary: In this work we addressed the challenging problem of inferring indirect (secondary) regulation by protein kinases and phosphatases via their activity on transcription factors. Although many protein kinase activity predictors have been developed for classes of protein kinases on specific amino acids within target sequences, our approach (PhosTF) provides predictions of regulatory activity for specific protein kinases and phosphatases on specific transcription factors. Our inference approach achieves this using the functional output observed in gene expression data of gene knock out strains, along with known transcription factor regulatory interactions. We formulated and tested a model for inference of regulation as well as a model for simulation of genes expression, transcription and translation. The simulation was used for computational validation of the inference method, which performed comparably to the best performers on a simpler inference problem in the DREAM4 competition. The inference method was then applied to yeast expression data, with significant validation by known kinase/phosphatase interactions. Over 15,000 novel regulatory interactions were predicted, suggesting that kinase activity provided a surprising level of repression of gene expression, either through the deactivation of activators or the activation of repressors. [ABSTRACT FROM AUTHOR]

Snake venoms represent a danger to human health, but also a gold mine of bioactive proteins that can be harnessed for drug discovery purposes. The evolution of snakes and their venom has been studied for decades, particularly via traditional morphological and basic genetic methods alongside venom proteomics. However, while the field of genomics has matured rapidly over the past 2 decades, owing to the development of next-generation sequencing technologies, snake genomics remains in its infancy. Here, we provide an overview of the state of the art in snake genomics and discuss its potential implications for studying venom evolution and toxinology. On the basis of current knowledge, gene duplication and positive selection are key mechanisms in the neofunctionalization of snake venom proteins. This makes snake venoms important evolutionary drivers that explain the remarkable venom diversification and adaptive variation observed in these reptiles. Gene duplication and neofunctionalization have also generated a large number of repeat sequences in snake genomes that pose a significant challenge to DNA sequencing, resulting in the need for substantial computational resources and longer sequencing read length for high-quality genome assembly. Fortunately, owing to constantly improving sequencing technologies and computational tools, we are now able to explore the molecular mechanisms of snake venom evolution in unprecedented detail. Such novel insights have the potential to affect the design and development of antivenoms and possibly other drugs, as well as provide new fundamental knowledge on snake biology and evolution. [ABSTRACT FROM AUTHOR]

Background: Several childhood asthma risk loci that relate to immune function have been identified by genome‐wide association studies (GWAS), but the underlying mechanisms remain unknown. Objective: Here, we examined whether perturbed innate immune responses mediate the association between known genetic risk variants and development of childhood asthma. Methods: Peripheral blood mononuclear cells from 336 six‐month‐old infants from the Copenhagen Prospective Studies on Asthma in Childhood (COPSAC2000) cohort were stimulated in vitro with six different innate ligands (LPS, CpG, poly(I:C), R848, HDMAPP and aluminium hydroxide together with low levels of LPS) followed by quantification of 18 released cytokines and chemokines 40 h after the stimulations. The innate immune response profiles were decomposed by principal component (PC) analysis, and PC1‐5 were used in mediation analyses of the effect of 25 known genetic risk variants on childhood asthma until age 7. Results: The effects of two variants from the 17q21 locus (rs7216389, rs2305480) on asthma and exacerbation risk were significantly mediated by immune parameters induced in response to ligands mimicking intracellular colonization; bacterial DNA (CpG) and double‐stranded viral RNA (poly(I:C)). The Th17 and innate lymphoid cell type 3‐amplifying cytokine IL‐23 was the most prominent cytokine involved. Conclusion: The 17q21 effect on childhood asthma and exacerbations was partly mediated by deregulation of IL‐23 in response to intracellular microbial ligands, which may suggest ineffective clearance of intracellular pathogens in the lungs. [ABSTRACT FROM AUTHOR]

Reproducibility is a key challenge of synthetic biology, but the foundation of reproducibility is only as solid as the reference materials it is built upon. Here we focus on the reproducibility of fluorescence measurements from bacteria transformed with engineered genetic constructs. This comparative analysis comprises three large interlaboratory studies using flow cytometry and plate readers, identical genetic constructs, and compatible unit calibration protocols. Across all three studies, we find similarly high precision in the calibrants used for plate readers. We also find that fluorescence measurements agree closely across the flow cytometry results and two years of plate reader results, with an average standard deviation of 1.52-fold, while the third year of plate reader results are consistently shifted by more than an order of magnitude, with an average shift of 28.9-fold. Analyzing possible sources of error indicates this shift is due to incorrect preparation of the fluorescein calibrant. These findings suggest that measuring fluorescence from engineered constructs is highly reproducible, but also that there is a critical need for access to quality controlled fluorescent calibrants for plate readers. [ABSTRACT FROM AUTHOR]

Little is known about the involvement of type 2 immune response-promoting intestinal tuft cells in metabolic regulation. We here examined the temporal changes in small intestinal tuft cell number and activity in response to high-fat diet-induced obesity in mice and investigated the relation to whole-body energy metabolism and the immune phenotype of the small intestine and epididymal white adipose tissue. Intake of high fat diet resulted in a reduction in overall numbers of small intestinal epithelial and tuft cells and reduced expression of the intestinal type 2 tuft cell markers Il25 and Tslp. Amongst >1,700 diet-regulated transcripts in tuft cells, we observed an early association between body mass expansion and increased expression of the gene encoding the serine protease inhibitor neuroserpin. By contrast, tuft cell expression of genes encoding gamma aminobutyric acid (GABA)-receptors was coupled to Tslp and Il25 and reduced body mass gain. Combined, our results point to a possible role for small intestinal tuft cells in energy metabolism via coupled regulation of tuft cell type 2 markers and GABA signaling receptors, while being independent of type 2 immune cell involvement. These results pave the way for further studies into interventions that elicit anti-obesogenic circuits via small intestinal tuft cells. [ABSTRACT FROM AUTHOR]

Abstract Background Characterization of cellular growth is central to understanding living systems. Here, we applied a three-factor design to study the relationship between specific growth rate and genome-wide gene expression in 36 steady-state chemostat cultures of Saccharomyces cerevisiae. The three factors we considered were specific growth rate, nutrient limitation, and oxygen availability. Results We identified 268 growth rate dependent genes, independent of nutrient limitation and oxygen availability. The transcriptional response was used to identify key areas in metabolism around which mRNA expression changes are significantly associated. Among key metabolic pathways, this analysis revealed de novo synthesis of pyrimidine ribonucleotides and ATP producing and consuming reactions at fast cellular growth. By scoring the significance of overlap between growth rate dependent genes and known transcription factor target sets, transcription factors that coordinate balanced growth were also identified. Our analysis shows that Fhl1, Rap1, and Sfp1, regulating protein biosynthesis, have significantly enriched target sets for genes up-regulated with increasing growth rate. Cell cycle regulators, such as Ace2 and Swi6, and stress response regulators, such as Yap1, were also shown to have significantly enriched target sets. Conclusion Our work, which is the first genome-wide gene expression study to investigate specific growth rate and consider the impact of oxygen availability, provides a more conservative estimate of growth rate dependent genes than previously reported. We also provide a global view of how a small set of transcription factors, 13 in total, contribute to control of cellular growth rate. We anticipate that multi-factorial designs will play an increasing role in elucidating cellular regulation.

Glutathione (GSH) plays a central role in the redox balance maintenance in mammalian cells. Previous studies of industrial Chinese hamster ovary cell lines have demonstrated a relationship between GSH metabolism and clone productivity. However, a thorough investigation is required to understand this relationship and potentially highlight new targets for cell engineering. In this study, we have modulated the GSH intracellular content of an industrial cell line under bioprocess conditions to further elucidate the role of the GSH synthesis pathway. Two strategies were used: the variation of cystine supply and the direct inhibition of the GSH synthesis using buthionine sulfoximine (BSO). Over time of the bioprocess, a correlation between intracellular GSH and product titer has been observed. Analysis of metabolites uptake/secretion rates and proteome comparison between BSO‐treated cells and nontreated cells has highlighted a slowdown of the tricarboxylic acid cycle leading to a secretion of lactate and alanine in the extracellular environment. Moreover, an adaptation of the GSH‐related proteome has been observed with an upregulation of the regulatory subunit of glutamate–cysteine ligase and a downregulation of a specific GSH transferase subgroup, the Mu family. Surprisingly, the main impact of BSO treatment was observed on a global downregulation of the cholesterol synthesis pathways. As cholesterol is required for protein secretion, it could be the missing piece of the puzzle to finally elucidate the link between GSH synthesis and productivity. [ABSTRACT FROM AUTHOR]

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data. In an inter-laboratory study, the authors compare the accuracy and performance of three optical density calibration protocols (colloidal silica, serial dilution of silica microspheres, and colony-forming unit (CFU) assay). They demonstrate that serial dilution of silica microspheres is the best of these tested protocols, allowing precise and robust calibration that is easily assessed for quality control and can also evaluate the effective linear range of an instrument. [ABSTRACT FROM AUTHOR]

Chemostat cultivation mode imposes selective pressure on the cells, which may result in slow adaptation in the physiological state over time. We applied a two‐compartment scale‐down chemostat system imposing feast–famine conditions to characterize the long‐term (100 s of hours) response of Saccharomyces cerevisiae to fluctuating glucose availability. A wild‐type strain and a recombinant strain, expressing an insulin precursor, were cultured in the scale‐down system, and analyzed at the physiological and proteomic level. Phenotypes of both strains were compared with those observed in a well‐mixed chemostat. Our results show that S. cerevisiae subjected to long‐term chemostat conditions undergoes a global reproducible shift in its cellular state and that this transition occurs faster and is larger in magnitude for the recombinant strain including a significant decrease in the expression of the insulin product. We find that the transition can be completely avoided in the presence of fluctuations in glucose availability as the strains subjected to feast–famine conditions under otherwise constant culture conditions exhibited constant levels of the measured proteome for over 250 hr. We hypothesize possible mechanisms responsible for the observed phenotypes and suggest experiments that could be used to test these mechanisms. [ABSTRACT FROM AUTHOR]

Snake venom metalloproteinases (SVMPs) and snake venom serine proteinases (SVSPs) are among the most abundant enzymes in many snake venoms, particularly among viperids. These proteinases are responsible for some of the clinical manifestations classically seen in viperid envenomings, including hemorrhage, necrosis, and coagulopathies. The objective of this study was to investigate the enzymatic activities of these proteins using a high-throughput peptide library to screen for the proteinase targets of the venoms of five viperid (Echis carinatus, Bothrops asper, Daboia russelii, Bitis arietans, Bitis gabonica) and one elapid (Naja nigricollis) species of high medical importance. The proteinase activities of these venoms were each tested against 360 peptide substrates, yielding 2160 activity profiles. A nonlinear regression model that accurately described the observed enzymatic activities was fitted to the experimental data, allowing for the comparison of cleavage rates across species. In this study, previously unknown protein targets of snake venom proteinases were identified, potentially implicating novel human and animal proteins that may be involved in the pathophysiology of viper envenomings. The functional relevance of these targets was further evaluated and discussed. These new findings may contribute to our understanding of the clinical manifestations and underlying biochemical mechanisms of snakebite envenoming by viperid species. [ABSTRACT FROM AUTHOR]

Aims: Congenital heart defects (CHD) affect almost 1% of all live born children and the number of adults with CHD is increasing. In families where CHD has occurred previously, estimates of recurrence risk, and the type of recurring malformation are important for counselling and clinical decision-making, but the recurrence patterns in families are poorly understood. We aimed to determine recurrence patterns, by investigating the co-occurrences of CHD in 1163 families with known malformations, comprising 3080 individuals with clinically confirmed diagnosis. Methods and results: We calculated rates of concordance and discordance for 41 specific types of malformations, observing a high variability in the rates of concordance and discordance. By calculating odds ratios for each of 1640 pairs of discordant lesions observed between affected family members, we were able to identify 178 pairs of malformations that co-occurred significantly more or less often than expected in families. The data show that distinct groups of cardiac malformations co-occur in families, suggesting influence from underlying developmental mechanisms. Analysis of human and mouse susceptibility genes showed that they were shared in 19% and 20% of pairs of co-occurring discordant malformations, respectively, but none of malformations that rarely co-occur, suggesting that a significant proportion of co-occurring lesions in families is caused by overlapping susceptibility genes. Conclusion: Familial CHD follow specific patterns of recurrence, suggesting a strong influence from genetically regulated developmental mechanisms. Co-occurrence of malformations in families is caused by shared susceptibility genes. [ABSTRACT FROM AUTHOR]

Protein association networks can be inferred from a range of resources including experimental data, literature mining and computational predictions. These types of evidence are emerging for non-coding RNAs (ncRNAs) aswell. However, integration of ncRNAs into protein association networks is challenging due to data heterogeneity. Here, we present a database of ncRNA-RNA and ncRNA-protein interactions and its integration with the STRING database of protein-protein interactions. These ncRNA associations cover four organisms and have been established from curated examples, experimental data, interaction predictions and automatic literaturemining. RAIN uses an integrative scoring scheme to assign a confidence score to each interaction. We demonstrate that RAIN outperforms the underlying microRNA-target predictions in inferring ncRNA interactions. RAIN can be operated through an easily accessibleweb interface and all interaction data can be downloaded. [ABSTRACT FROM AUTHOR]

Summary Obesity is a heritable disorder, with children of obese fathers at higher risk of developing obesity. Environmental factors epigenetically influence somatic tissues, but the contribution of these factors to the establishment of epigenetic patterns in human gametes is unknown. Here, we hypothesized that weight loss remodels the epigenetic signature of spermatozoa in human obesity. Comprehensive profiling of the epigenome of sperm from lean and obese men showed similar histone positioning, but small non-coding RNA expression and DNA methylation patterns were markedly different. In a separate cohort of morbidly obese men, surgery-induced weight loss was associated with a dramatic remodeling of sperm DNA methylation, notably at genetic locations implicated in the central control of appetite. Our data provide evidence that the epigenome of human spermatozoa dynamically changes under environmental pressure and offers insight into how obesity may propagate metabolic dysfunction to the next generation. [ABSTRACT FROM AUTHOR]

Cellular responses to oxidative stress are important for restoring redox balance and ensuring cell survival. Genetic defects in response factors can lead to impaired response to oxidative damage and contribute to disease and aging. In single cell organisms, such as yeasts, the integrity of the oxidative stress response can be observed through its influences on growth characteristics. In this study, we investigated the time-dependent batch growth effects as a function of oxidative stress levels in protein kinase and phosphatase deletion backgrounds of Saccharomyces cerevisiae. In total, 41 different protein kinases and phosphatase mutants were selected for their known activities in oxidative stress or other stress response pathways and were investigated for their dosage-dependent response to hydrogen peroxide. Detailed growth profiles were analyzed after the induction of stress for growth rate, lag time duration and growth efficiency, and by a novel method to identify stress-induced diauxic shift delay. This approach extracts more phenotypic information than traditional plate-based methods due to the assessment of time dynamics in the time scale of minutes. With this approach, we were able to identify surprisingly diverse sensitivity and resistance patterns as a function of gene knockout. [ABSTRACT FROM AUTHOR]

Schizosaccharomyces pombe is a popular model eukaryotic organism to study diverse aspects of mammalian biology, including responses to cellular stress triggered by redox imbalances within its compartments. The review considers the current knowledge on the signaling pathways that govern the transcriptional response of fission yeast cells to elevated levels of hydrogen peroxide. Particular attention is paid to the mechanisms that yeast cells employ to promote cell survival in conditions of intermediate and acute oxidative stress. The role of the Sty1/Spc1/Phh1 mitogen-activated protein kinase in regulating gene expression at multiple levels is discussed in detail. [ABSTRACT FROM AUTHOR]

Background: Atopic dermatitis (AD) is a common inflammatory skin disease with limited treatment options. Several microarray experiments have been conducted on lesional/LS and non-lesional/NL AD skin to develop a genomic disease phenotype. Although these experiments have shed light on disease pathology, inter-study comparisons reveal large differences in resulting sets of differentially expressed genes (DEGs), limiting the utility of direct comparisons across studies. Methods: We carried out a meta-analysis combining 4 published AD datasets to define a robust disease profile, termed meta-analysis derived AD (MADAD) transcriptome. Results: This transcriptome enriches key AD pathways more than the individual studies, and associates AD with novel pathways, such as atherosclerosis signaling (IL-37, selectin E/SELE). We identified wide lipid abnormalities and, for the first time in vivo, correlated Th2 immune activation with downregulation of key epidermal lipids (FA2H, FAR2, ELOVL3), emphasizing the role of cytokines on the barrier disruption in AD. Key AD "classifier genes" discriminate lesional from nonlesional skin, and may evaluate therapeutic responses. Conclusions: Our meta-analysis provides novel and powerful insights into AD disease pathology, and reinforces the concept of AD as a systemic disease. [ABSTRACT FROM AUTHOR]

Our current understanding of how natural genetic variation affects gene expression beyond well-annotated coding genes is still limited. The use of deep sequencing technologies for the study of expression quantitative trait loci ( eQTLs) has the potential to close this gap. Here, we generated the first recombinant strain library for fission yeast and conducted an RNA-seq-based QTL study of the coding, non-coding, and antisense transcriptomes. We show that the frequency of distal effects ( trans- eQTLs) greatly exceeds the number of local effects ( cis- eQTLs) and that non-coding RNAs are as likely to be affected by eQTLs as protein-coding RNAs. We identified a genetic variation of swc5 that modifies the levels of 871 RNAs, with effects on both sense and antisense transcription, and show that this effect most likely goes through a compromised deposition of the histone variant H2A.Z. The strains, methods, and datasets generated here provide a rich resource for future studies. [ABSTRACT FROM AUTHOR]

Background: Prioritizing genetic variants is a challenge because disease susceptibility loci are often located in genes of unknown function or the relationship with the corresponding phenotype is unclear. A global data-mining exercise on the biomedical literature can establish the phenotypic profile of genes with respect to their connection to disease phenotypes. The importance of protein-protein interaction networks in the genetic heterogeneity of common diseases or complex traits is becoming increasingly recognized. Thus, the development of a network-based approach combined with phenotypic profiling would be useful for disease gene prioritization. Results: We developed a random-set scoring model and implemented it to quantify phenotype relevance in a network-based disease gene-prioritization approach. We validated our approach based on different gene phenotypic profiles, which were generated from PubMed abstracts, OMIM, and GeneRIF records. We also investigated the validity of several vocabulary filters and different likelihood thresholds for predicted protein-protein interactions in terms of their effect on the network-based gene-prioritization approach, which relies on text-mining of the phenotype data. Our method demonstrated good precision and sensitivity compared with those of two alternative complex-based prioritization approaches. We then conducted a global ranking of all human genes according to their relevance to a range of human diseases. The resulting accurate ranking of known causal genes supported the reliability of our approach. Moreover, these data suggest many promising novel candidate genes for human disorders that have a complex mode of inheritance. Conclusion: We have implemented and validated a network-based approach to prioritize genes for human diseases based on their phenotypic profile. We have devised a powerful and transparent tool to identify and rank candidate genes. Our global gene prioritization provides a unique resource for the biological interpretation of data from genome-wide association studies, and will help in the understanding of how the associated genetic variants influence disease or quantitative phenotypes. [ABSTRACT FROM AUTHOR]

The objective of this study was the application of the synthetic promoter library (SPL) technology for modulation of actinorhodin production in Streptomyces coelicolor A3(2). The SPL technology was used to optimize the expression of a pathway specific positive transcriptional regulator ActII orf4, which activates the transcription of the S. coelicolor actinorhodin biosynthetic gene cluster. The native actII orf4 promoter was replaced with synthetic promoters, generating a S. coelicolor library with a broad range of expression levels of actII orf4. The resulting library was screened based on the yield of actinorhodin. Selected strains were further physiologically characterized. One of the strains from the library, ScoSPL20, showed considerably higher yield of actinorhodin and final actinorhodin titer, compared to S. coelicolor wild type and S. coelicolor with actII orf4 expressed from a strong constitutive promoter. ScoSPL20 demonstrated exceptional productivity despite having a comparatively weak expression from the promoter. Interestingly, the ScoSPL20 promoter was activated at a much earlier stage of growth compared to the wild type, demonstrating the advantage of fine-tuning and temporal tuning of gene expression in metabolic engineering. Transcriptome studies were performed in exponential and actinorhodin-producing phase of growth to compare gene expression between ScoSPL20 and the wild type. To our knowledge, this is the first successful application of the SPL technology for secondary metabolite production in filamentous bacteria. [ABSTRACT FROM AUTHOR]

Type 1 diabetes is due to destruction of pancreatic β-cells. Lysine deacetylase inhibitors (KDACi) protect β-cells from inflammatory destruction in vitro and are promising immunomodulators. Here we demonstrate that the clinically well-tolerated KDACi vorinostat and givinostat revert diabetes in the nonobese diabetic (NOD) mouse model of type 1 diabetes and counteract inflammatory target cell damage by a mechanism of action consistent with transcription factor—rather than global chromatin—hyperacetylation. Weaning NOD mice received low doses of vorinostat and givinostat in their drinking water until 100–120 d of age. Diabetes incidence was reduced by 38% and 45%, respectively, there was a 15% increase in the percentage of islets without infiltration, and pancreatic insulin content increased by 200%. Vorinostat treatment increased the frequency of functional regulatory T-cell subsets and their transcription factors Gata3 and FoxP3 in parallel to a decrease in inflammatory dendritic cell subsets and their cytokines IL-6, IL-12, and TNF-α. KDACi also inhibited LPS-induced Cox-2 expression in peritoneal macrophages from C57BL/6 and NOD mice. In insulin-producing β-cells, givinostat did not upregulate expression of the anti-inflammatory genes Socs1-3 or sirtuin-1 but reduced levels of IL-1β + IFN-γ–induced proinflammatory Il1a, Il1b, Tnfα, Fas, Cxcl2, and reduced cytokine-induced ERK phosphorylation. Further, NF-κB genomic iNos promoter binding was reduced by 50%, and NF-κB-dependent mRNA expression was blocked. These effects were associated with NF-κB subunit p65 hyperacetylation. Taken together, these data provide a rationale for clinical trials of safety and efficacy of KDACi in patients with autoimmune disease such as type 1 diabetes. [ABSTRACT FROM AUTHOR]

Summary: Members of the SH2 domain family modulate signal transduction by binding to short peptides containing phosphorylated tyrosines. Each domain displays a distinct preference for the sequence context of the phosphorylated residue. We have developed a high-density peptide chip technology that allows for probing of the affinity of most SH2 domains for a large fraction of the entire complement of tyrosine phosphopeptides in the human proteome. Using this technique, we have experimentally identified thousands of putative SH2-peptide interactions for more than 70 different SH2 domains. By integrating this rich data set with orthogonal context-specific information, we have assembled an SH2-mediated probabilistic interaction network, which we make available as a community resource in the PepspotDB database. A predicted dynamic interaction between the SH2 domains of the tyrosine phosphatase SHP2 and the phosphorylated tyrosine in the extracellular signal-regulated kinase activation loop was validated by experiments in living cells. [Copyright &y& Elsevier]

Identifying causal genes that underlie complex traits such as susceptibility to disease is a primary aim of genetic and biomedical studies. Genetic mapping of quantitative trait loci (QTL) and gene expression profiling based on high-throughput technologies are common first approaches toward identifying associations between genes and traits; however, it is often difficult to assess whether the biological function of a putative candidate gene is consistent with a particular phenotype. Here, we have implemented a network-based disease gene prioritization approach for ranking genes associated with quantitative traits and diseases in livestock species. The approach uses ortholog mapping and integrates information on disease or trait phenotypes, geneassociated phenotypes, and protein-protein interactions. It was used for ranking all known genes present in the cattle genome for their potential roles in bovine mastitis. Gene-associated phenome profile and transcriptome profile in response to Escherichia coli infection in the mammary gland were integrated to make a global inference of bovine genes involved in mastitis. The top ranked genes were highly enriched for pathways and biological processes underlying inflammation and immune responses, which supports the validity of our approach for identifying genes that are relevant to animal health and disease. These gene-associated phenotypes were used for a local prioritization of candidate genes located in a QTL affecting the susceptibility to mastitis. Our study provides a general framework for prioritizing genes associated with various complex traits in different species. To our knowledge this is the first time that gene expression, ortholog mapping, protein interactions, and biomedical text data have been integrated systematically for ranking candidate genes in any livestock species. [ABSTRACT FROM AUTHOR]

Laboratory evolution experiments have led to important findings relating organism adaptation and genomic evolution. However, continuous monitoring of long-term evolution has been lacking for natural systems, limiting our understanding of these processes in situ. Here we characterize the evolutionary dynamics of a lineage of a clinically important opportunistic bacterial pathogen, Pseudomonas aeruginosa, as it adapts to the airways of several individual cystic fibrosis patients over 200.000 bacterial generations, and provide estimates of mutation rates of bacteria in a nat- ural environment. In contrast to predictions based on in vitro evolution experiments, we document limited diversification of the evolving lineage despite a highly structured and complex host environment. Notably, the lineage went through an initial period of rapid adaptation caused by a small number of mutations with plelotropic effects, followed by a period of genetic drift with limited phenotypic change and a genomic signature of negative selection, suggesting that the evolving lineage has reached a major adaptive peak in the fitness landscape. This contrasts with previous findings of continued positive selection from long-term in vitro evolution experiments. The evolved phenotype of the infecting bacteria further suggests that the opportunistic pathogen has transitioned to become a primary pathogen for cystic fibrosis patients. [ABSTRACT FROM AUTHOR]