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

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

Texture Segregation By Visual Cortex: Perceptual Grouping, Attention, and Learning

A neural model is proposed of how laminar interactions in the visual cortex may learn and recognize object texture and form boundaries. The model brings together five interacting processes: region-based texture classification, contour-based boundary grouping, surface filling-in, spatial attention, and object attention. The model shows how form boundaries can determine regions in which surface filling-in occurs; how surface filling-in interacts with spatial attention to generate a form-fitting distribution of spatial attention, or attentional shroud; how the strongest shroud can inhibit weaker shrouds; and how the winning shroud regulates learning of texture categories, and thus the allocation of object attention. The model can discriminate abutted textures with blurred boundaries and is sensitive to texture boundary attributes like discontinuities in orientation and texture flow curvature as well as to relative orientations of texture elements. The model quantitatively fits a large set of human psychophysical data on orientation-based textures. Object boundar output of the model is compared to computer vision algorithms using a set of human segmented photographic images. The model classifies textures and suppresses noise using a multiple scale oriented filterbank and a distributed Adaptive Resonance Theory (dART) classifier. The matched signal between the bottom-up texture inputs and top-down learned texture categories is utilized by oriented competitive and cooperative grouping processes to generate texture boundaries that control surface filling-in and spatial attention. Topdown modulatory attentional feedback from boundary and surface representations to early filtering stages results in enhanced texture boundaries and more efficient learning of texture within attended surface regions. Surface-based attention also provides a self-supervising training signal for learning new textures. Importance of the surface-based attentional feedback in texture learning and classification is tested using a set of textured images from the Brodatz micro-texture album. Benchmark studies vary from 95.1% to 98.6% with attention, and from 90.6% to 93.2% without attention.Air Force Office of Scientific Research (F49620-01-1-0397, F49620-01-1-0423); National Science Foundation (SBE-0354378); Office of Naval Research (N00014-01-1-0624

Reframing gene essentiality in terms of adaptive flexibility

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

Ambivalence related to potential lifestyle changes following preventive cardiovascular consultations in general practice: A qualitative study

<p>Abstract</p> <p>Background</p> <p>Motivational interviewing approaches are currently recommended in primary prevention and treatment of cardiovascular disease (CVD) in general practice in Denmark, based on an empirical and multidisciplinary body of scientific knowledge about the importance of motivation for successful lifestyle change among patients at risk of lifestyle related diseases. This study aimed to explore and describe motivational aspects related to potential lifestyle changes among patients at increased risk of CVD following preventive consultations in general practice.</p> <p>Methods</p> <p>Individual interviews with 12 patients at increased risk of CVD within 2 weeks after the consultation. Grounded theory was used in the analysis.</p> <p>Results</p> <p>Ambivalence related to potential lifestyle changes was the core motivational aspect in the interviews, even though the patients rarely verbalised this experience during the consultations. The patients experienced ambivalence in the form of conflicting feelings about lifestyle change. Analysis showed that these feelings interacted with their reflections in a concurrent process. Analysis generated a typology of five different ambivalence sub-types: perception, demand, information, priority and treatment ambivalence.</p> <p>Conclusion</p> <p>Ambivalence was a common experience in relation to motivation among patients at increased risk of CVD. Five different ambivalence sub-types were found, which clinicians may use to explore and resolve ambivalence in trying to aid patients to adopt lifestyle changes. Future research is needed to explore whether motivational interviewing and other cognitive approaches can be enhanced by exploring ambivalence in more depth, to ensure that lifestyle changes are made and sustained. Further studies with a wider range of patient characteristics are required to investigate the generalisability of the results.</p

Serum lipid responses to psyllium fiber: differences between pre- and post-menopausal, hypercholesterolemic women

<p>Abstract</p> <p>Background</p> <p>Cardiovascular disease is the leading cause of death in women and men. Psyllium, a soluble fiber has been known to reduce serum lipids. In this pilot study, we evaluated whether menopausal status would affect the serum lipid responses to psyllium fiber in women.</p> <p>Methods</p> <p>Eleven post-menopausal and eight pre-menopausal women with serum total cholesterol >200 mg/dL were included in the study. Subjects consumed their habitual diet and 15 g psyllium/d for 6 weeks. Psyllium was incorporated into cookies. Each cookie contained ≈5 g of psyllium fiber. Subjects ate one cookie in each meal.</p> <p>Results</p> <p>With psyllium fiber, total cholesterol concentration was significantly lower (≈5.2%, P < 0.05) in post-menopausal women but not in pre-menopausal women (≈1.3%). Also, there was a significant decrease in HDL-cholesterol in post-menopausal women (≈10.2%, P < 0.05). There were no significant changes observed in concentrations of LDL-cholesterol, triglycerides, apolipoprotein A1, and apolipoprotein B in both pre- and post-menopausal women with psyllium.</p> <p>Conclusion</p> <p>In this pilot study, post- and pre-menopausal, hypercholesterolemic women responded differently to psyllium fiber supplementation. Post-menopausal women would benefit from addition of psyllium to their diets in reducing the risk for heart diseases. The results of this study should be used with caution because the study was based on a small sample size.</p

Waist Circumference as Compared with Body-Mass Index in Predicting Mortality from Specific Causes

Background Whether waist circumference provides clinically meaningful information not delivered by body-mass index regarding prediction of cause-specific death is uncertain. Methods We prospectively examined waist circumference (WC) and body-mass index (BMI) in relation to cause-specific death in 225,712 U.S. women and men. Cox regression was used to estimate relative risks and 95% confidence intervals (CI). Statistical analyses were conducted using SAS version 9.1. Results During follow-up from 1996 through 2005, we documented 20,977 deaths. Increased WC consistently predicted risk of death due to any cause as well as major causes of death, including deaths from cancer, cardiovascular disease, and non-cancer/non-cardiovascular diseases, independent of BMI, age, sex, race/ethnicity, smoking status, and alcohol intake. When WC and BMI were mutually adjusted in a model, WC was related to 1.37 fold increased risk of death from any cancer and 1.82 fold increase risk of death from cardiovascular disease, comparing the highest versus lowest WC categories. Importantly, WC, but not BMI showed statistically significant positive associations with deaths from lung cancer and chronic respiratory disease. Participants in the highest versus lowest WC category had a relative risk of death from lung cancer of 1.77 (95% CI, 1.41 to 2.23) and of death from chronic respiratory disease of 2.77 (95% CI, 1.95 to 3.95). In contrast, subjects in the highest versus lowest BMI category had a relative risk of death from lung cancer of 0.94 (95% CI, 0.75 to 1.17) and of death from chronic respiratory disease of 1.18 (95% CI, 0.89 to 1.56). Conclusions Increased abdominal fat measured by WC was related to a higher risk of deaths from major specific causes, including deaths from lung cancer and chronic respiratory disease, independent of BMI