Metabolic modeling and analysis of the metabolic switch in Streptomyces coelicolor

Background The transition from exponential to stationary phase in Streptomyces coelicolor is accompanied by a major metabolic switch and results in a strong activation of secondary metabolism. Here we have explored the underlying reorganization of the metabolome by combining computational predictions based on constraint-based modeling and detailed transcriptomics time course observations. Results We reconstructed the stoichiometric matrix of S. coelicolor, including the major antibiotic biosynthesis pathways, and performed flux balance analysis to predict flux changes that occur when the cell switches from biomass to antibiotic production. We defined the model input based on observed fermenter culture data and used a dynamically varying objective function to represent the metabolic switch. The predicted fluxes of many genes show highly significant correlation to the time series of the corresponding gene expression data. Individual mispredictions identify novel links between antibiotic production and primary metabolism. Conclusion Our results show the usefulness of constraint-based modeling for providing a detailed interpretation of time course gene expression data

Identification of a novel retrieval-dependent memory process in the crab neohelice granulata

Fully consolidated associative memories may be altered by alternative retrieval dependent memory processes. While a brief exposure to the conditioned stimulus (CS) can trigger reconsolidation of the original memory, a prolonged CS exposure will trigger memory extinction. The conditioned response is maintained after reconsolidation, but is inhibited after extinction, presumably by the formation of a new inhibitory memory trace. In rats and humans, it has been shown that CS exposure of intermediate duration leave the memory in an insensitive or limbo state. Limbo is characterised by the absence of reconsolidation or extinction. Here we investigated the evolutionary conserved nature of limbo using a contextual Pavlovian conditioning (CPC) memory paradigm in the crab Neohelice granulata. In animals with fully consolidated CPC memory, systemic administration of the protein synthesis inhibitor cycloheximide after 1 CS presentation disrupted the memory, presumably by interfering with memory reconsolidation. The same intervention given after 320 CSs prevented CPC memory extinction. Cycloheximide had no behavioural effect when administered after 80 CS presentations, a protocol that failed to extinguish CPC memory. Also, we observed that a stronger CPC memory engaged reconsolidation after 80 CS instead of limbo, indicating that memory strength affects the parametrical conditions to engage either reconsolidation or limbo. Altogether, these results indicate that limbo is an evolutionary conserved memory process segregating reconsolidation from extinction in the number of CSs space. Limbo appears as an intrinsic component of retrieval dependent memory processing, with a key function in the transition from memory maintenance to inhibition

Expression of Foxp3 in colorectal cancer but not in Treg cells correlates with disease progression in patients with colorectal cancer

Background: Regulatory T cells (Treg) expressing the transcription factor forkhead-box protein P3 (Foxp3) have been identified to counteract anti-tumor immune responses during tumor progression. Besides, Foxp3 presentation by cancer cells itself may also allow them to evade from effector T-cell responses, resulting in a survival benefit of the tumor. For colorectal cancer (CRC) the clinical relevance of Foxp3 has not been evaluated in detail. Therefore the aim of this study was to study its impact in colorectal cancer (CRC). Methods and Findings: Gene and protein analysis of tumor tissues from patients with CRC was performed to quantify the expression of Foxp3 in tumor infiltrating Treg and colon cancer cells. The results were correlated with clinicopathological parameters and patients overall survival. Serial morphological analysis demonstrated Foxp3 to be expressed in cancer cells. High Foxp3 expression of the cancer cells was associated with poor prognosis compared to patients with low Foxp3 expression. In contrast, low and high Foxp3 level in tumor infiltrating Treg cells demonstrated no significant differences in overall patient survival. Conclusions: Our findings strongly suggest that Foxp3 expression mediated by cancer cells rather than by Treg cells contribute to disease progression

Metabolomics methods for the synthetic biology of secondary metabolism

Many microbial secondary metabolites are of high biotechnological value for medicine, agriculture, and the food industry. Bacterial genome mining has revealed numerous novel secondary metabolite biosynthetic gene clusters, which encode the potential to synthesize a large diversity of compounds that have never been observed before. The stimulation or “awakening” of this cryptic microbial secondary metabolism has naturally attracted the attention of synthetic microbiologists, who exploit recent advances in DNA sequencing and synthesis to achieve unprecedented control over metabolic pathways. One of the indispensable tools in the synthetic biology toolbox is metabolomics, the global quantification of small biomolecules. This review illustrates the pivotal role of metabolomics for the synthetic microbiology of secondary metabolism, including its crucial role in novel compound discovery in microbes, the examination of side products of engineered metabolic pathways, as well as the identification of major bottlenecks for the overproduction of compounds of interest, especially in combination with metabolic modeling. We conclude by highlighting remaining challenges and recent technological advances that will drive metabolomics towards fulfilling its potential as a cornerstone technology of synthetic microbiology

Antibiotic use among 8-month-old children in Malmö, Sweden – in relation to child characteristics and parental sociodemographic, psychosocial and lifestyle factors

In the county of Scania, Sweden, antibiotic use among small children is among the highest in the country. The aim of this study was to investigate the associations between antibiotic use among 8-month-old children in Malmö and characteristics of the child as well as parental sociodemographic characteristics, lifestyle factors, and psychosocial support. The study was a population-based cross-sectional survey. The study population consisted of children who visited the Child Health Care (CHC) centres in Malmö for their 8-month health checkup during 2003–2006 and whose parents answered a self-administered questionnaire (n = 7266 children). The questionnaire was distributed to parents of children registered with the CHC and invited for an 8-month checkup during the study period. The odds of using antibiotics increased as parental educational level decreased. Using high educational level as a reference group, low maternal educational level was associated with an increased antibiotic use for the child, odds ratio (OR) = 1.61 (95% CI: 1.34–1.93). Furthermore, children whose parents were born outside Sweden showed higher antibiotic use, OR = 1.43 (95% CI: 1.24–1.65), in comparison with children whose parents were born in Sweden. Exposure to environmental smoking, parental experience of economic stress, and a low level of emotional support increased the odds for antibiotic use. Boys had higher odds of use of antibiotics than girls, OR = 1.40 (95% CI: 1.25–1.57). Having a low birth weight, having an allergy and having siblings also increased the odds for early antibiotic use, while breastfeeding seemed to have a protective role. Conclusion There were clear associations between parental factors such as sociodemographic, psychosocial and lifestyle factors and antibiotic use at this early stage of life. Several characteristics of the child also affected the use of antibiotics

Circulating Cell-Free DNA in Dogs with Mammary Tumors: Short and Long Fragments and Integrity Index

Circulating cell-free DNA (cfDNA) has been considered an interesting diagnostic/prognostic plasma biomarker in tumor-bearing subjects. In cancer patients, cfDNA can hypothetically derive from tumor necrosis/apoptosis, lysed circulating cells, and some yet unrevealed mechanisms of active release. This study aimed to preliminarily analyze cfDNA in dogs with canine mammary tumors (CMTs). Forty-four neoplastic, 17 non-neoplastic disease-bearing, and 15 healthy dogs were recruited. Necrosis and apoptosis were also assessed as potential source of cfDNA on 78 CMTs diagnosed from the 44 dogs. The cfDNA fragments and integrity index significantly differentiated neoplastic versus non-neoplastic dogs (P<0.05), and allowed the distinction between benign and malignant lesions (P<0.05). Even if without statistical significance, the amount of cfDNA was also affected by tumor necrosis and correlated with tumor size and apoptotic markers expression. A significant (P<0.01) increase of Bcl-2 in malignant tumors was observed, and in metastatic CMTs the evasion of apoptosis was also suggested. This study, therefore, provides evidence that cfDNA could be a diagnostic marker in dogs carrying mammary nodules suggesting that its potential application in early diagnostic procedures should be further investigated

Separating the wheat from the chaff: a prioritisation pipeline for the analysis of metabolomics datasets

Liquid Chromatography Mass Spectrometry (LC-MS) is a powerful and widely applied method for the study of biological systems, biomarker discovery and pharmacological interventions. LC-MS measurements are, however, significantly complicated by several technical challenges, including: (1) ionisation suppression/enhancement, disturbing the correct quantification of analytes, and (2) the detection of large amounts of separate derivative ions, increasing the complexity of the spectra, but not their information content. Here we introduce an experimental and analytical strategy that leads to robust metabolome profiles in the face of these challenges. Our method is based on rigorous filtering of the measured signals based on a series of sample dilutions. Such data sets have the additional characteristic that they allow a more robust assessment of detection signal quality for each metabolite. Using our method, almost 80% of the recorded signals can be discarded as uninformative, while important information is retained. As a consequence, we obtain a broader understanding of the information content of our analyses and a better assessment of the metabolites detected in the analyzed data sets. We illustrate the applicability of this method using standard mixtures, as well as cell extracts from bacterial samples. It is evident that this method can be applied in many types of LC-MS analyses and more specifically in untargeted metabolomics

Use of hierarchical models to evaluate performance of cardiac surgery centres in the Italian CABG outcome study

<p>Abstract</p> <p>Background</p> <p>Hierarchical modelling represents a statistical method used to analyze nested data, as those concerning patients afferent to different hospitals. Aim of this paper is to build a hierarchical regression model using data from the "Italian CABG outcome study" in order to evaluate the amount of differences in adjusted mortality rates attributable to differences between centres.</p> <p>Methods</p> <p>The study population consists of all adult patients undergoing an isolated CABG between 2002–2004 in the 64 participating cardiac surgery centres.</p> <p>A risk adjustment model was developed using a classical single-level regression. In the multilevel approach, the variable "clinical-centre" was employed as a group-level identifier. The intraclass correlation coefficient was used to estimate the proportion of variability in mortality between groups. Group-level residuals were adopted to evaluate the effect of clinical centre on mortality and to compare hospitals performance. Spearman correlation coefficient of ranks (<it>ρ</it>) was used to compare results from classical and hierarchical model.</p> <p>Results</p> <p>The study population was made of 34,310 subjects (mortality rate = 2.61%; range 0.33–7.63). The multilevel model estimated that 10.1% of total variability in mortality was explained by differences between centres. The analysis of group-level residuals highlighted 3 centres (VS 8 in the classical methodology) with estimated mortality rates lower than the mean and 11 centres (VS 7) with rates significantly higher. Results from the two methodologies were comparable (<it>ρ </it>= 0.99).</p> <p>Conclusion</p> <p>Despite known individual risk-factors were accounted for in the single-level model, the high variability explained by the variable "clinical-centre" states its importance in predicting 30-day mortality after CABG.</p

Constraints on the χ_(c1) versus χ_(c2) polarizations in proton-proton collisions at √s = 8 TeV

The polarizations of promptly produced χ_(c1) and χ_(c2) mesons are studied using data collected by the CMS experiment at the LHC, in proton-proton collisions at √s=8  TeV. The χ_c states are reconstructed via their radiative decays χ_c → J/ψγ, with the photons being measured through conversions to e⁺e⁻, which allows the two states to be well resolved. The polarizations are measured in the helicity frame, through the analysis of the χ_(c2) to χ_(c1) yield ratio as a function of the polar or azimuthal angle of the positive muon emitted in the J/ψ → μ⁺μ⁻ decay, in three bins of J/ψ transverse momentum. While no differences are seen between the two states in terms of azimuthal decay angle distributions, they are observed to have significantly different polar anisotropies. The measurement favors a scenario where at least one of the two states is strongly polarized along the helicity quantization axis, in agreement with nonrelativistic quantum chromodynamics predictions. This is the first measurement of significantly polarized quarkonia produced at high transverse momentum