Mapping the Environmental Fitness Landscape of a Synthetic Gene Circuit

Gene expression actualizes the organismal phenotypes encoded within the genome in an environment-dependent manner. Among all encoded phenotypes, cell population growth rate (fitness) is perhaps the most important, since it determines how well-adapted a genotype is in various environments. Traditional biological measurement techniques have revealed the connection between the environment and fitness based on the gene expression mean. Yet, recently it became clear that cells with identical genomes exposed to the same environment can differ dramatically from the population average in their gene expression and division rate (individual fitness). For cell populations with bimodal gene expression, this difference is particularly pronounced, and may involve stochastic transitions between two cellular states that form distinct sub-populations. Currently it remains unclear how a cell population's growth rate and its subpopulation fractions emerge from the molecular-level kinetics of gene networks and the division rates of single cells. To address this question we developed and quantitatively characterized an inducible, bistable synthetic gene circuit controlling the expression of a bifunctional antibiotic resistance gene in Saccharomyces cerevisiae. Following fitness and fluorescence measurements in two distinct environments (inducer alone and antibiotic alone), we applied a computational approach to predict cell population fitness and subpopulation fractions in the combination of these environments based on stochastic cellular movement in gene expression space and fitness space. We found that knowing the fitness and nongenetic (cellular) memory associated with specific gene expression states were necessary for predicting the overall fitness of cell populations in combined environments. We validated these predictions experimentally and identified environmental conditions that defined a “sweet spot” of drug resistance. These findings may provide a roadmap for connecting the molecular-level kinetics of gene networks to cell population fitness in well-defined environments, and may have important implications for phenotypic variability of drug resistance in natural settings

The contribution of dynamic stromal remodeling during mammary development to breast carcinogenesis

Breast cancer is a heterogeneous disease whose prognosis varies depending upon the developmental stage of the breast tissue at diagnosis. Notably, breast cancers associated with pregnancy exhibit increased rates of metastasis and poorer long-term survival compared to those diagnosed after menopause. However, postmenopausal breast cancers associated with obesity exhibit a more aggressive behavior and confer decreased overall patient survival compared to those diagnosed in non-obese individuals. Since the mammary gland is a dynamic tissue that undergoes significant changes throughout a woman's lifetime, especially during pregnancy and following menopause, we present evidence to support the notion that changes occurring throughout development within the mammary stromal compartment may account for some of the biological differences in breast cancer subtypes and behaviors

Essentials of forensic post-mortem MR imaging in adults

Post-mortem magnetic resonance (PMMR) imaging is a powerful diagnostic tool with a wide scope in forensic radiology. In the past 20 years, PMMR was used both as adjunct and alternative to autopsy. The role of PMMR in forensic death investigations largely depends on the rules and habits of local jurisdictions, availability of experts, financial resources, and individual case circumstances.PMMR images are affected by post-mortem changes, including position dependent sedimentation, variable body temperature, and decomposition. Investigators must be familiar with the appearance of normal findings on PMMR to distinguish them from disease or injury.Coronal whole-body images provide a comprehensive overview. Notably, STIR (short-tau-inversion-recovery) images enable investigators to screen for pathologic fluid accumulation, which we refer to as "forensic sentinel sign". If scan time is short, subsequent PMMR imaging may be focussed on regions with a positive forensic sentinel sign.PMMR offers excellent anatomical detail and is especially useful to visualise pathologies of the brain, the heart, the subcutaneous fat tissue, and the abdominal organs. PMMR may also be used document skeletal injury. Cardiovascular imaging is a core area of PMMR imaging and growing evidence indicates that PMMR may be able to detect ischemic injury at an earlier stage than traditional autopsy and routine histology.The aim of this review is to present an overview of normal findings on forensic PMMR, provide general advice on the application of PMMR and summarise the current literature on PMMR imaging of the head and neck, the cardiovascular system, the abdomen and the musculoskeletal system

Edema is a sign of early acute myocardial infarction on post-mortem magnetic resonance imaging

The aim of this study was to investigate if acute myocardial infarction can be detected by post-mortem cardiac magnetic resonance (PMMR) at an earlier stage than by traditional autopsy, i.e., within less than 4 h after onset of ischemia; and if so, to determine the characteristics of PMMR findings in early acute infarcts. Twenty-one ex vivo porcine hearts with acute myocardial infarction underwent T2-weighted cardiac PMMR imaging within 3 h of onset of iatrogenic ischemia. PMMR imaging findings were compared to macroscopic findings. Myocardial edema induced by ischemia and reperfusion was visible on PMMR in all cases. Typical findings of early acute ischemic injury on PMMR consist of a central zone of intermediate signal intensity bordered by a rim of increased signal intensity. Myocardial edema can be detected on cardiac PMMR within the first 3 h after the onset of ischemia in porcine hearts. The size of myocardial edema reflects the area of ischemic injury in early acute (per-acute) myocardial infarction. This study provides evidence that cardiac PMMR is able to detect acute myocardial infarcts at an earlier stage than traditional autopsy and routine histology. © 2013 Springer Science+Business Media New York

Age at menarche is associated with prediabetes and diabetes in women (aged 32-81 years) from the general population: the KORA F4 Study.

AIMS/HYPOTHESIS: The aim of this study was to examine the association between age at menarche and prediabetes as well as diabetes, considering confounding factors and the possible mediating role of adult obesity. METHODS: This cross-sectional study analysed data on 1,503 women aged 32-81 years from the German population-based KORA (Cooperative Health Research in the Region of Augsburg, South Germany) F4 Study (2006-2008). Data were collected by standardised interviews, physical examinations, and whole blood and serum measurements, including administration of an OGTT in non-diabetic participants. RESULTS: Of the 1,503 women, 226 showed a prediabetic state (impaired fasting glucose and/or impaired glucose tolerance) and 140 persons had diabetes (45 participants with previously undiagnosed diabetes and 95 with known diabetes). In Poisson regression analysis, age at menarche was significantly inversely associated with prediabetes or diabetes after adjustment for year of birth (RR 0.88; 95% CI 0.82, 0.94, p < 0.0001 per additional year of menarche) and after additional adjustment for a number of confounding factors (RR 0.88; 95% CI 0.83, 0.94, p = 0.0001). Further adjustment for current BMI slightly attenuated the association with prediabetes or diabetes (RR 0.89; 95% CI 0.83, 0.95, p = 0.0009), but the association remained clearly significant. CONCLUSIONS/INTERPRETATION: Age at menarche seems to be inversely associated with prediabetes and diabetes independent of confounding factors including current BMI. Women at risk for diabetes might be identified by a history of young age at menarche