Evolution favors protein mutational robustness in sufficiently large populations

BACKGROUND: An important question is whether evolution favors properties such as mutational robustness or evolvability that do not directly benefit any individual, but can influence the course of future evolution. Functionally similar proteins can differ substantially in their robustness to mutations and capacity to evolve new functions, but it has remained unclear whether any of these differences might be due to evolutionary selection for these properties. RESULTS: Here we use laboratory experiments to demonstrate that evolution favors protein mutational robustness if the evolving population is sufficiently large. We neutrally evolve cytochrome P450 proteins under identical selection pressures and mutation rates in populations of different sizes, and show that proteins from the larger and thus more polymorphic population tend towards higher mutational robustness. Proteins from the larger population also evolve greater stability, a biophysical property that is known to enhance both mutational robustness and evolvability. The excess mutational robustness and stability is well described by existing mathematical theories, and can be quantitatively related to the way that the proteins occupy their neutral network. CONCLUSIONS: Our work is the first experimental demonstration of the general tendency of evolution to favor mutational robustness and protein stability in highly polymorphic populations. We suggest that this phenomenon may contribute to the mutational robustness and evolvability of viruses and bacteria that exist in large populations

Glucagon-like peptide 1 (GLP-1).

BACKGROUND: The glucagon-like peptide-1 (GLP-1) is a multifaceted hormone with broad pharmacological potential. Among the numerous metabolic effects of GLP-1 are the glucose-dependent stimulation of insulin secretion, decrease of gastric emptying, inhibition of food intake, increase of natriuresis and diuresis, and modulation of rodent β-cell proliferation. GLP-1 also has cardio- and neuroprotective effects, decreases inflammation and apoptosis, and has implications for learning and memory, reward behavior, and palatability. Biochemically modified for enhanced potency and sustained action, GLP-1 receptor agonists are successfully in clinical use for the treatment of type-2 diabetes, and several GLP-1-based pharmacotherapies are in clinical evaluation for the treatment of obesity. SCOPE OF REVIEW: In this review, we provide a detailed overview on the multifaceted nature of GLP-1 and its pharmacology and discuss its therapeutic implications on various diseases. MAJOR CONCLUSIONS: Since its discovery, GLP-1 has emerged as a pleiotropic hormone with a myriad of metabolic functions that go well beyond its classical identification as an incretin hormone. The numerous beneficial effects of GLP-1 render this hormone an interesting candidate for the development of pharmacotherapies to treat obesity, diabetes, and neurodegenerative disorders

Gene-Expression Signatures Can Distinguish Gastric Cancer Grades and Stages

Microarray gene-expression data of 54 paired gastric cancer and adjacent noncancerous gastric tissues were analyzed, with the aim to establish gene signatures for cancer grades (well-, moderately-, poorly- or un-differentiated) and stages (I, II, III and IV), which have been determined by pathologists. Our statistical analysis led to the identification of a number of gene combinations whose expression patterns serve well as signatures of different grades and different stages of gastric cancer. A 19-gene signature was found to have discerning power between high- and low-grade gastric cancers in general, with overall classification accuracy at 79.6%. An expanded 198-gene panel allows the stratification of cancers into four grades and control, giving rise to an overall classification agreement of 74.2% between each grade designated by the pathologists and our prediction. Two signatures for cancer staging, consisting of 10 genes and 9 genes, respectively, provide high classification accuracies at 90.0% and 84.0%, among early-, advanced-stage cancer and control. Functional and pathway analyses on these signature genes reveal the significant relevance of the derived signatures to cancer grades and progression. To the best of our knowledge, this represents the first study on identification of genes whose expression patterns can serve as markers for cancer grades and stages

Obesity and poor breast cancer prognosis: an illusion because of hormone replacement therapy?

High body mass index (BMI) and use of hormone replacement therapy (HRT) increase the risk of postmenopausal breast cancer. It has been shown that BMI modifies the effect of HRT, as its influence is most pronounced in lean women. We investigated the influence of BMI and HRT on prognosis in 2640 postmenopausal women diagnosed with breast cancer in Sweden in 1993–1995, taking into account HRT and mammography before diagnosis. Logistic and Cox regression were used. In non-users of HRT, obese women (BMI >30) compared with normal weight women (BMI <25) had a similar prognosis (hazard ratio (HR) 1.1, 95% confidence interval (CI) 0.8–1.6), despite larger tumours found in obese women. Obese HRT users had less favourable tumour characteristics and poorer prognosis compared with normal weight women (HR 3.7, 95% CI 1.9–7.2). The influence of BMI on breast cancer prognosis was similar whether diagnosed by mammographic screening or not. We found a similar prognosis of postmenopausal breast cancer-specific death regardless of BMI in non-users of HRT, but among HRT users obesity was associated with a poorer breast cancer prognosis

Directed evolution of a magnetic resonance imaging contrast agent for noninvasive imaging of dopamine

The development of molecular probes that allow in vivo imaging of neural signaling processes with high temporal and spatial resolution remains challenging. Here we applied directed evolution techniques to create magnetic resonance imaging (MRI) contrast agents sensitive to the neurotransmitter dopamine. The sensors were derived from the heme domain of the bacterial cytochrome P450-BM3 (BM3h). Ligand binding to a site near BM3h's paramagnetic heme iron led to a drop in MRI signal enhancement and a shift in optical absorbance. Using an absorbance-based screen, we evolved the specificity of BM3h away from its natural ligand and toward dopamine, producing sensors with dissociation constants for dopamine of 3.3–8.9 μM. These molecules were used to image depolarization-triggered neurotransmitter release from PC12 cells and in the brains of live animals. Our results demonstrate the feasibility of molecular-level functional MRI using neural activity–dependent sensors, and our protein engineering approach can be generalized to create probes for other targets.Charles A. Dana Foundation. Brain and Immuno-ImagingRaymond and Beverley Sackler FoundationNational Institutes of Health (U.S.) (grant R01-DA28299)National Institutes of Health (U.S.) (grant DP2-OD2441)National Institutes of Health (U.S.) (grant R01-GM068664)Jacobs Institute for Molecular Engineering for Medicine. Jacobs Institute for Molecular Engineering for MedicineNational Institutes of Health (U.S.) (grant R01-DE013023

Methods for specifying the target difference in a randomised controlled trial : the Difference ELicitation in TriAls (DELTA) systematic review

Peer reviewedPublisher PD

Mutation Bias Favors Protein Folding Stability in the Evolution of Small Populations

Mutation bias in prokaryotes varies from extreme adenine and thymine (AT) in obligatory endosymbiotic or parasitic bacteria to extreme guanine and cytosine (GC), for instance in actinobacteria. GC mutation bias deeply influences the folding stability of proteins, making proteins on the average less hydrophobic and therefore less stable with respect to unfolding but also less susceptible to misfolding and aggregation. We study a model where proteins evolve subject to selection for folding stability under given mutation bias, population size, and neutrality. We find a non-neutral regime where, for any given population size, there is an optimal mutation bias that maximizes fitness. Interestingly, this optimal GC usage is small for small populations, large for intermediate populations and around 50% for large populations. This result is robust with respect to the definition of the fitness function and to the protein structures studied. Our model suggests that small populations evolving with small GC usage eventually accumulate a significant selective advantage over populations evolving without this bias. This provides a possible explanation to the observation that most species adopting obligatory intracellular lifestyles with a consequent reduction of effective population size shifted their mutation spectrum towards AT. The model also predicts that large GC usage is optimal for intermediate population size. To test these predictions we estimated the effective population sizes of bacterial species using the optimal codon usage coefficients computed by dos Reis et al. and the synonymous to non-synonymous substitution ratio computed by Daubin and Moran. We found that the population sizes estimated in these ways are significantly smaller for species with small and large GC usage compared to species with no bias, which supports our prediction

No association of breast cancer risk with integrin beta3 (ITGB3) Leu33Pro genotype

To pursue a borderline increased risk of breast cancer for carriers of two integrin beta3 (ITGB3) 33Pro alleles found in a recent prospective study, we conducted a case–control study of 1088 women with breast cancer and 4815 female controls. Leu33Pro heterozygotes, homozygotes and heterozygotes+homozygotes vs noncarriers had odds ratios for breast cancer of 1.0 (95% confidence interval: 0.8–1.1), 0.8 (0.5–1.2) and 1.0 (0.8–1.1), respectively. After stratification for conventional risk factors, odds ratio for breast cancer in heterozygotes, homozygotes and heterozygotes+homozygotes vs noncarriers were not increased above 1.0 in any of the 14 strata examined. This was also true after stratification for tumour histological subtype and cancer stage at the time of diagnosis

Neuropilin-2 expression in breast cancer: correlation with lymph node metastasis, poor prognosis, and regulation of CXCR4 expression

<p>Abstract</p> <p>Background</p> <p>Neuropilin-2 (Nrp2) is a receptor for vascular endothelial growth factor-C (VEGF-C), which is a well-known lymphangiogenic factor and plays an important role in lymph node metastasis of various human cancers, including breast cancer. Recently, Nrp2 was shown to play a role in cancer by promoting tumor cell metastasis. CXC chemokine receptor 4 (CXCR4) also promotes tumor metastasis. In the previous studies, we demonstrated that VEGF-C and cytoplasmic CXCR4 expressions were correlated with poorer patient prognosis (BMC Cancer 2008,8:340; Breast Cancer Res Treat 2005, 91:125–132).</p> <p>Methods</p> <p>The relationship between Nrp2 expression and lymph node metastasis, VEGF-C expression, CXCR4 expression, and other established clinicopathological variables (these data were cited in our previous papers), including prognosis, was analyzed in human breast cancer. Effects of neutralizing anti-Nrp2 antibody on CXCR4 expression and chemotaxis were assessed in MDA-MB-231 breast cancer cells.</p> <p>Results</p> <p>Nrp2 expression was observed in 53.1% (60 of 113) of the invasive breast carcinomas. Nrp2 expression was significantly correlated with lymph node metastasis, VEGF-C expression, and cytoplasmic CXCR4 expression. Survival curves determined by the Kaplan-Meier method showed that Nrp2 expression was associated with reduced overall survival. In multivariate analysis, Nrp2 expression emerged as a significant independent predictor for overall survival. Neutralizing anti-Nrp2 antibody blocks cytoplasmic CXCR4 expression and CXCR4-induced migration in MDA-MB-231 cells.</p> <p>Conclusion</p> <p>Nrp2 expression was correlated with lymph node metastasis, VEGF-C expression, and cytoplasmic CXCR4 expression. Nrp2 expression may serve as a significant prognostic factor for long-term survival in breast cancer. Our data also showed a role for Nrp2 in regulating cytoplasmic CXCR4 expression <it>in vitro</it>.</p