254 research outputs found

    The genetic basis for adaptation of model-designed syntrophic co-cultures.

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    Understanding the fundamental characteristics of microbial communities could have far reaching implications for human health and applied biotechnology. Despite this, much is still unknown regarding the genetic basis and evolutionary strategies underlying the formation of viable synthetic communities. By pairing auxotrophic mutants in co-culture, it has been demonstrated that viable nascent E. coli communities can be established where the mutant strains are metabolically coupled. A novel algorithm, OptAux, was constructed to design 61 unique multi-knockout E. coli auxotrophic strains that require significant metabolite uptake to grow. These predicted knockouts included a diverse set of novel non-specific auxotrophs that result from inhibition of major biosynthetic subsystems. Three OptAux predicted non-specific auxotrophic strains-with diverse metabolic deficiencies-were co-cultured with an L-histidine auxotroph and optimized via adaptive laboratory evolution (ALE). Time-course sequencing revealed the genetic changes employed by each strain to achieve higher community growth rates and provided insight into mechanisms for adapting to the syntrophic niche. A community model of metabolism and gene expression was utilized to predict the relative community composition and fundamental characteristics of the evolved communities. This work presents new insight into the genetic strategies underlying viable nascent community formation and a cutting-edge computational method to elucidate metabolic changes that empower the creation of cooperative communities

    Reframing gene essentiality in terms of adaptive flexibility

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    Abstract Background Essentiality assays are important tools commonly utilized for the discovery of gene functions. Growth/no growth screens of single gene knockout strain collections are also often utilized to test the predictive power of genome-scale models. False positive predictions occur when computational analysis predicts a gene to be non-essential, however experimental screens deem the gene to be essential. One explanation for this inconsistency is that the model contains the wrong information, possibly an incorrectly annotated alternative pathway or isozyme reaction. Inconsistencies could also be attributed to experimental limitations, such as growth tests with arbitrary time cut-offs. The focus of this study was to resolve such inconsistencies to better understand isozyme activities and gene essentiality. Results In this study, we explored the definition of conditional essentiality from a phenotypic and genomic perspective. Gene-deletion strains associated with false positive predictions of gene essentiality on defined minimal medium for Escherichia coli were targeted for extended growth tests followed by population sequencing and transcriptome analysis. Of the twenty false positive strains available and confirmed from the Keio single gene knock-out collection, 11 strains were shown to grow with longer incubation periods making these actual true positives. These strains grew reproducibly with a diverse range of growth phenotypes. The lag phase observed for these strains ranged from less than one day to more than 7 days. It was found that 9 out of 11 of the false positive strains that grew acquired mutations in at least one replicate experiment and the types of mutations ranged from SNPs and small indels associated with regulatory or metabolic elements to large regions of genome duplication. Comparison of the detected adaptive mutations, modeling predictions of alternate pathways and isozymes, and transcriptome analysis of KO strains suggested agreement for the observed growth phenotype for 6 out of the 9 cases where mutations were observed. Conclusions Longer-term growth experiments followed by whole genome sequencing and transcriptome analysis can provide a better understanding of conditional gene essentiality and mechanisms of adaptation to such perturbations. Compensatory mutations are largely reproducible mechanisms and are in agreement with genome-scale modeling predictions to loss of function gene deletion events

    A meta-analytic review of stand-alone interventions to improve body image

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    Objective Numerous stand-alone interventions to improve body image have been developed. The present review used meta-analysis to estimate the effectiveness of such interventions, and to identify the specific change techniques that lead to improvement in body image. Methods The inclusion criteria were that (a) the intervention was stand-alone (i.e., solely focused on improving body image), (b) a control group was used, (c) participants were randomly assigned to conditions, and (d) at least one pretest and one posttest measure of body image was taken. Effect sizes were meta-analysed and moderator analyses were conducted. A taxonomy of 48 change techniques used in interventions targeted at body image was developed; all interventions were coded using this taxonomy. Results The literature search identified 62 tests of interventions (N = 3,846). Interventions produced a small-to-medium improvement in body image (d+ = 0.38), a small-to-medium reduction in beauty ideal internalisation (d+ = -0.37), and a large reduction in social comparison tendencies (d+ = -0.72). However, the effect size for body image was inflated by bias both within and across studies, and was reliable but of small magnitude once corrections for bias were applied. Effect sizes for the other outcomes were no longer reliable once corrections for bias were applied. Several features of the sample, intervention, and methodology moderated intervention effects. Twelve change techniques were associated with improvements in body image, and three techniques were contra-indicated. Conclusions The findings show that interventions engender only small improvements in body image, and underline the need for large-scale, high-quality trials in this area. The review identifies effective techniques that could be deployed in future interventions

    Biases in the Explore-Exploit Tradeoff in Addictions: The Role of Avoidance of Uncertainty.

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    We focus on exploratory decisions across disorders of compulsivity, a potential dimensional construct for the classification of mental disorders. Behaviors associated with the pathological use of alcohol or food, in alcohol use disorders (AUD) or binge-eating disorder (BED), suggest a disturbance in explore-exploit decision-making, whereby strategic exploratory decisions in an attempt to improve long-term outcomes may diminish in favor of more repetitive or exploitatory choices. We compare exploration vs exploitation across disorders of natural (obesity with and without BED) and drug rewards (AUD). We separately acquired resting state functional MRI data using a novel multi-echo planar imaging sequence and independent components analysis from healthy individuals to assess the neural correlates underlying exploration. Participants with AUD showed reduced exploratory behavior across gain and loss environments, leading to lower-yielding exploitatory choices. Obese subjects with and without BED did not differ from healthy volunteers but when compared with each other or to AUD subjects, BED had enhanced exploratory behaviors particularly in the loss domain. All subject groups had decreased exploration or greater uncertainty avoidance to losses compared with rewards. More exploratory decisions in the context of reward were associated with frontal polar and ventral striatal connectivity. For losses, exploration was associated with frontal polar and precuneus connectivity. We further implicate the relevance and dimensionality of constructs of compulsivity across disorders of both natural and drug rewards.The study was funded by the Wellcome Trust Fellowship grant for VV (093705/Z/10/Z) and Cambridge NIHR Biomedical Research Centre. VV and NAH are Wellcome Trust (WT) intermediate Clinical Fellows. LSM is in receipt of an MRC studentship. The BCNI is supported by a WT and MRC grant. MF is funded by NIMH and NSF grants and is consultant for Hoffman LaRoche pharmaceuticals. The remaining authors declare no competing financial interests.This is the final version of the article. It first appeared from NPG via http://dx.doi.org/10.1038/npp.2015.20

    Immunostimulatory Motifs Enhance Antiviral siRNAs Targeting Highly Pathogenic Avian Influenza H5N1

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    Highly pathogenic avian influenza (HPAI) H5N1 virus is endemic in many regions around the world and remains a significant pandemic threat. To date H5N1 has claimed almost 300 human lives worldwide, with a mortality rate of 60% and has caused the death or culling of hundreds of millions of poultry since its initial outbreak in 1997. We have designed multi-functional RNA interference (RNAi)-based therapeutics targeting H5N1 that degrade viral mRNA via the RNAi pathway while at the same time augmenting the host antiviral response by inducing host type I interferon (IFN) production. Moreover, we have identified two factors critical for maximising the immunostimulatory properties of short interfering (si)RNAs in chicken cells (i) mode of synthesis and (ii) nucleoside sequence to augment the response to virus. The 5-bp nucleoside sequence 5′-UGUGU-3′ is a key determinant in inducing high levels of expression of IFN -α, -β, -λ and interleukin 1- β in chicken cells. Positioning of this 5′-UGUGU-3′ motif at the 5′- end of the sense strand of siRNAs, but not the 3′- end, resulted in a rapid and enhanced induction of type I IFN. An anti-H5N1 avian influenza siRNA directed against the PB1 gene (PB1-2257) tagged with 5′-UGUGU-3′ induced type I IFN earlier and to a greater extent compared to a non-tagged PB1-2257. Tested against H5N1 in vitro, the tagged PB1-2257 was more effective than non-tagged PB1-2257. These data demonstrate the ability of an immunostimulatory motif to improve the performance of an RNAi-based antiviral, a finding that may influence the design of future RNAi-based anti-influenza therapeutics

    Control of hypersonic turbulent skin friction by boundary-layer combustion of hydrogen

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    Shvab-Zeldovich coupling of flow variables has been used to extend Van Driest's theory of turbulent boundary-layer skin friction to include injection and combustion of hydrogen in the boundary layer. The resulting theory is used to make predictions of skin friction and heat transfer that are found to be consistent with experimental and numerical results. Using the theory to extrapolate to larger downstream distances at the same experimental conditions, it is found that the reduction in skin-friction drag with hydrogen mixing and combustion is three times that with mixing alone. In application to flow on a flat plate at mainstream velocities of 2, 4, and 6 knits, and Reynolds numbers from 3 X 10(6) to 1 x 10(8), injection and combustion of hydrogen yielded values of skin-friction drag that were less than one-half of the no-injection skin-friction drag, together with a net reduction in heat transfer when the combustion heat release in air was less than the stagnation enthalpy. The mass efficiency of hydrogen injection, as measured by effective specific impulse values, was approximately 2000 s
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