Brain perfusion and blood-brain barrier (BBB) integrity are reduced early in Alzheimer's disease (AD). We performed single nucleus RNA sequencing of vascular cells isolated from AD and non-diseased ...control brains to characterise pathological transcriptional signatures responsible for this. We show that endothelial cells (EC) are enriched for expression of genes associated with susceptibility to AD. Increased β-amyloid is associated with BBB impairment and a dysfunctional angiogenic response related to a failure of increased pro-angiogenic HIF1A to increased VEGFA signalling to EC. This is associated with vascular inflammatory activation, EC senescence and apoptosis. Our genomic dissection of vascular cell risk gene enrichment provides evidence for a role of EC pathology in AD and suggests that reducing vascular inflammatory activation and restoring effective angiogenesis could reduce vascular dysfunction contributing to the genesis or progression of early AD.
In this paper, we present experimental results and simulation data of an electrostatically doped and therefore voltage-programmable, planar, CMOS-compatible field-effect transistor (FET) structure. ...This planar device is based on our previously published Si-nanowire (SiNW) technology. Schottky barrier source/drain (S/D) contacts and a silicon-on-insulator (SOI) technology platform are the key features of this dual-gated but single channel universal FET. The combination of two electrically independent gates, one back-gate for S/D Schottky barrier modulation as well as channel formation to establish Schottky barrier FET (SBFET) operation and one front-gate forming a junctionless FET (JLFET) for actual current control, significantly increases the temperature robustness of the device.
The Meishan pig breed exhibits increased prolificacy and reduced neonatal mortality compared to commercial breeds, such as the Large White, prompting breeders to introduce the Meishan genotype into ...commercial herds. Commercial piglets are highly susceptible to hypoglycemia, hypothermia, and death, potentially due to limited lipid stores and/or delayed hepatic metabolic ability. We therefore hypothesized that variation in hepatic development and lipid metabolism could contribute to the differences in neonatal mortality between breeds. Liver samples were obtained from piglets of each breed on days 0, 7, and 21 of postnatal age and subjected to molecular and biochemical analysis. At birth, both breeds exhibited similar hepatic glycogen contents, despite Meishan piglets having significantly lower body weight. The livers from newborn Meishan piglets exhibited increased C18∶1n9C and C20∶1n9 but lower C18∶0, C20∶4n6, and C22∶6n3 fatty acid content. Furthermore, by using an unsupervised machine learning approach, we detected an interaction between C18∶1n9C and glycogen content in newborn Meishan piglets. Bioinformatic analysis could identify unique age-based clusters from the lipid profiles in Meishan piglets that were not apparent in the commercial offspring. Examination of the fatty acid signature during the neonatal period provides novel insights into the body composition of Meishan piglets that may facilitate liver responses that prevent hypoglycaemia and reduce offspring mortality.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
The use of genome-wide methylation arrays has proved very informative to investigate both clinical and biological questions in human epigenomics. The use of clustering methods either for exploration ...of these data or to compare to an a priori grouping, e.g., normal versus disease allows assessment of groupings of data without user bias. However no consensus on the methods to use for clustering of methylation array approaches has been reached. To determine the most appropriate clustering method for analysis of illumina array methylation data, a collection of data sets was simulated and used to compare clustering methods. Both hierarchical clustering and non-hierarchical clustering methods (k-means, k-medoids, and fuzzy clustering algorithms) were compared using a range of distance and linkage methods. As no single method consistently outperformed others across different simulations, we propose a method to capture the best clustering outcome based on an additional measure, the silhouette width. This approach produced a consistently higher cluster accuracy compared to using any one method in isolation.
The engineering of microorganisms to produce a variety of extracellular enzymes (exoenzymes), for example for producing renewable fuels and in biodegradation of xenobiotics, has recently attracted ...increasing interest. Productivity is often reduced by “cheater” mutants, which are deficient in exoenzyme production and benefit from the product provided by the “cooperating” cells. We present a game‐theoretical model to analyze population structure and exoenzyme productivity in terms of biotechnologically relevant parameters. For any given population density, three distinct regimes are predicted: when the metabolic effort for exoenzyme production and secretion is low, all cells cooperate; at intermediate metabolic costs, cooperators and cheaters coexist; while at high costs, all cells use the cheating strategy. These regimes correspond to the harmony game, snowdrift game, and Prisoner's Dilemma, respectively. Thus, our results indicate that microbial strains engineered for exoenzyme production will not, under appropriate conditions, be outcompeted by cheater mutants. We also analyze the dependence of the population structure on cell density. At low costs, the fraction of cooperating cells increases with decreasing cell density and reaches unity at a critical threshold. Our model provides an estimate of the cell density maximizing exoenzyme production.
Epigenetic modifications of DNA, such as cytosine methylation are differentially abundant in diseases such as cancer. A goal for clinical research is finding sites that are differentially methylated ...between groups of samples to act as potential biomarkers for disease outcome. However, clinical samples are often limited in availability, represent a heterogeneous collection of cells or are of uncertain clinical class. Array-based methods for identification of methylation provide a cost-effective method to survey a proportion of the methylome at single base resolution. The Illumina Infinium array has become a popular and reliable high throughput method in this field and are proving useful in the identification of biomarkers for disease. Here, we compare a commonly used statistical test with a new intuitive and flexible computational approach to quickly detect differentially methylated sites. The method rapidly identifies and ranks candidate lists with greatest inter-group variability whilst controlling for intra-group variability. Intuitive and biologically relevant filters can be imposed to quickly identify sites and genes of interest.
While previous studies have shed light on the link between the structure of metabolism and its transcriptional regulation, the extent to which transcriptional regulation controls metabolism has not ...yet been fully explored. In this work, we address this problem by integrating a large number of experimental data sets with a model of the metabolism of Escherichia coli. Using a combination of computational tools including the concept of elementary flux patterns, methods from network inference and dynamic optimization, we find that transcriptional regulation of pathways reflects the protein investment into these pathways. While pathways that are associated to a high protein cost are controlled by fine‐tuned transcriptional programs, pathways that only require a small protein cost are transcriptionally controlled in a few key reactions. As a reason for the occurrence of these different regulatory strategies, we identify an evolutionary trade‐off between the conflicting requirements to reduce protein investment and the requirement to be able to respond rapidly to changes in environmental conditions.
Synopsis
The increasing availability and decreasing prices of experimental techniques have led to an explosion in the number of available experimental data sets (Ishii et al, 2007; Lu et al, 2007; Bennett et al, 2009; Lewis et al, 2010). However, approaches to integrate these diverse data sets into a coherent model of cellular mechanisms have lagged behind (Palsson and Zengler, 2010). In this study, we want to contribute to this effort through the analysis of a large number of data sets in order to identify global principles in the regulation of metabolism in Escherichia coli. While previous studies have shed light onto the link between the transcriptional regulation of metabolism and its structure (Ihmels et al, 2004; Reed and Palsson, 2004; Schwartz et al, 2007; Seshasayee et al, 2009), the extent to which transcriptional regulation controls metabolism has remained elusive.
To address this problem, we investigated the coexpression of enzymes within the same pathway in all biochemically annotated subsystems of E. coli metabolism. As a reference for metabolic pathways, we used elementary flux patterns, a recently introduced concept for pathway analysis in genome‐scale metabolic networks (Kaleta et al, 2009). Through this analysis, we found that while pathways in many subsystems of metabolism show a high degree of coexpression, pathways in the subsystems cofactor and prosthetic group biosynthesis, glycerophospholipid metabolism, murein recycling, nucleotide salvage pathway and pentose phosphate pathway show only weak coexpression. We refer to these subsystems with a low coordination of transcriptional regulation as transcriptionally sparsely regulated subsystems.
In order to understand these different patterns of regulation, we constructed a simplified model of a linear metabolic pathway that converts a substrate s via four intermediates into a product p. We then used dynamic optimization to identify a regulatory program (i.e. a time course for the enzyme concentrations), which allows the cell to maintain the concentration of the product p in a changing environment while obeying a set of physiological constraints. As an objective function we used the minimization of the level of transcriptional regulation, specified through absolute deviations of enzyme concentrations from their initial values, and the minimization of protein costs. Protein costs are measured as the sum of the initial enzyme concentrations.
The optimization results revealed that for a full control of the flux through a pathway, transcriptional regulation of initial and terminal reactions of the pathway is sufficient (sparse transcriptional regulation). Regulation of the first reaction is required to control the flux into the pathway, and hence, the intermediate concentrations. In contrast, regulation at the terminal position is required to tightly control the rate of synthesis of the product. By performing the same optimization for randomly chosen kinetic parameters, we found that this pattern is also optimal in most cases with differences in the catalytic properties of enzymes. Moreover, we found that with increasing enzyme costs (i.e. increasing enzyme concentrations), there is a shift from sparse transcriptional regulation to coordinated transcriptional regulation of all enzymes within a pathway (pervasive transcriptional regulation).
To verify these predictions, we analyzed the position‐specific frequency of regulatory events in the pathways of the transcriptionally sparsely regulated subsystems. We could confirm that there is a significant increase in the frequency of transcriptional regulation at the end and a less pronounced increase at the beginning of pathways. Performing the same analysis for post‐translational regulation, we found that there is a statistically significant increase at the beginning of pathways. Thus, the control at the beginning of pathways is achieved through a combination of transcriptional and post‐translational regulation. In other subsystems that were not identified as transcriptionally sparsely regulated, we did not find this pattern of transcriptional regulation while the same pattern of post‐translational regulation could be observed. By analyzing protein abundance data, we confirmed that particularly pathways within subsystems, for which enzyme costs are low, are transcriptionally sparsely regulated.
Having confirmed the predictions made by the optimization, we found that there appears to be a mechanism favoring sparse transcriptional regulation in pathways with low‐cost enzymes. We suggest an evolutionary trade‐off between the cellular objectives of protein cost minimization and response time minimization as a cause of this mechanism. The optimal strategy to reduce average protein costs is to transcriptionally control enzymes within a pathway. However, responses on a transcriptional level are usually very slow. In contrast, short response times can be achieved through a constitutive expression of enzymes with a focused regulation of key steps within a pathway. The interplay between the two cellular objectives leads to the observation that particularly pathways with highly abundant and thus costly enzymes are transcriptionally pervasively regulated (Figure 7A). In contrast, pathways with low abundance enzymes are transcriptionally sparsely regulated (Figure 7B). In agreement with these results, we found that pathways such as the pentose phosphate pathway, for which rapid response times are required, are sparsely regulated even if they contain costly enzymes (Figure 7C). Finally, if the fitness advantage achieved through following either of the cellular objectives is low, sparse transcriptional regulation is the minimum requirement to control flux through a pathway (Figure 7D).
In summary, our results demonstrate that, in contrast to the classical picture, regulation of key positions of metabolic pathways is sufficient for full control of flux and is implemented in vivo. This pattern of sparse regulation is particularly useful if a higher fitness advantage can be achieved through rapid response times compared to the fitness advantage achieved through the reduced protein cost of pervasive transcriptional regulation.
Pathways in Escherichia coli show large differences in the extent to which enzymes from the same pathway are expressed in a coordinated manner.
Using dynamic optimization, we show that regulation of the initial and terminal reactions of a pathway is the minimum requirement for a precise control of flux.
We find that in E. coli a regulation of initial and terminal reactions is predominantly used to control pathways with low costs of enzymes while a regulation of all enzymes occurs if protein costs are high.
A trade‐off between minimization of protein investment and minimization of response time can explain the preference for transcriptional regulation at key positions (leading to high protein costs, but low response time) or coordinated transcriptional regulation of all enzymes (leading to low protein costs, but high response time).
PDF
