Liver X receptors regulate adrenal steroidogenesis and hypothalamic-pituitary-adrenal feedback

The nuclear hormone receptors liver X receptor alpha (LXRalpha) (NR1H3) and LXRbeta (NR1H2) are established regulators of cholesterol, lipid, and glucose metabolism and are attractive drug targets for the treatment of diabetes and cardiovascular disease. Adrenal steroid hormones including glucocorticoids and mineralocorticoids are known to interfere with glucose metabolism, insulin signaling, and blood pressure regulation. Here we present genome-wide expression profiles of LXR-responsive genes in both the adrenal and the pituitary gland. LXR activation in cultured adrenal cells inhibited expression of multiple steroidogenic genes and consequently decreased adrenal steroid hormone production. In addition, LXR agonist treatment elevated ACTH mRNA expression and hormone secretion from pituitary cells both in vitro and in vivo. Reduced expression of the glucocortioid-activating enzyme 11beta-hydroxysteroid dehydrogenase 1 in pituitary cells upon LXR activation suggests blunting of the negative feedback of glucocorticoids by LXRs. In conclusion, LXRs independently interfere with the hypothalamic-pituitary-adrenal axis regulation at the level of the pituitary and the adrenal gland.     

Rapid assessment of Dreissena population in Lake Erie using underwater videography

Hydrobiologia - Dreissenid bivalves (Dreissena polymorpha and D. rostriformis bugensis) are considered the most aggressive freshwater invaders inflicting profound ecological and economic impacts on...     

Comprehensive Absolute Quantification of the Cytosolic Proteome of Bacillus subtilis by Data Independent,Parallel Fragmentation in Liquid Chromatography/Mass Spectrometry (LC/MSE)

In the growing field of systems biology, the knowledge of protein concentrations is highly required to truly understand metabolic and adaptational networks within the cells. Therefore we established a workflow relying on long chromatographic separation and mass spectrometric analysis by data independent, parallel fragmentation of all precursor ions at the same time (LC/MS^E). By prevention of discrimination of co-eluting low and high abundant peptides a high average sequence coverage of 40% could be achieved, resulting in identification of almost half of the predicted cytosolic proteome of the Gram-positive model organism Bacillus subtilis (>1,050 proteins). Absolute quantification was achieved by correlation of average MS signal intensities of the three most intense peptides of a protein to the signal intensity of a spiked standard protein digest. Comparative analysis with heavily labeled peptides (AQUA approach) showed the use of only one standard digest is sufficient for global quantification.The quantification results covered almost four orders of magnitude, ranging roughly from 10 to 150,000 copies per cell. To prove this method for its biological relevance selected physiological aspects of B. subtilis cells grown under conditions requiring either amino acid synthesis or alternatively amino acid degradation were analyzed. This allowed both in particular the validation of the adjustment of protein levels by known regulatory events and in general a perspective of new insights into bacterial physiology. Within new findings the analysis of “protein costs” of cellular processes is extremely important. Such a comprehensive and detailed characterization of cellular protein concentrations based on data independent, parallel fragmentation in liquid chromatography/mass spectrometry (LC/MS^E) data has been performed for the first time and should pave the way for future comprehensive quantitative characterization of microorganisms as physiological entities.In contrast to the rather static genome, composition of the proteome greatly varies with respect to environmental conditions (availability of nutrients, medium composition, stress, etc.) reflecting its key role in the adaptation of cells (1). Hence, proteome data for varying growth conditions should help to reach a comprehensive understanding of the physiology of adaptation to different nutritional conditions, which is the typical situation of bacterial cells in nature (2). In this context the availability of high quality absolute protein quantification data is of outstanding importance for the emerging field of systems biology because (a) proteins are major players for most biological processes and (b) their abundances decisively determine the adaptation rate of cellular processes. Additionally, an emerging set of theoretical and experimental works (reviewed in (3)) recently emphasized the importance of resource allocation in the growth rate management. Bacterial cells have to invest an available set of limited resources into biological processes to ensure growth and survival. Protein costs (or protein burden) of a biological process, defined as the total mass of proteins invested in the biological process, is then critical and must be finely tuned to sustain growth of bacteria. The determination of protein costs of different biological processes using genome-scale absolute protein quantification should thus represent a major breakthrough in understanding bacterial physiology and cellular design.For many years the gold standard for absolute protein quantification has been quantitative Western blotting and has been successfully applied, for example, to the yeast proteome (4). In recent years mass spectrometry based absolute proteome quantification techniques have become available allowing determination of cellular protein concentrations. The absolute protein amount can be precisely determined by spiking defined amounts of isotopically labeled synthetic peptides into a protein digest (5). Absolute protein amounts become available by detection and comparison of signal intensities of heavy and light peptides, but only for proteins related to the added synthetic peptides. This method was extended to a more global absolute quantification (AQUA)¹ by calibrating 2D gels with anchor proteins (6). Although the use of internal labeled standards for absolute protein quantification is very precise, availability and costs for such reference peptides are surely limiting. Therefore label free quantification techniques emerged. One of these methods is based on spectral counting. There, the number of sequenced peptides per protein is used to calculate the absolute quantity of one single protein in a complex sample (emPAI) (7). This can be refined by consideration of physicochemical properties of its peptides (APEX) (8, 9). Absolute protein quantification can also be achieved by comparing average signal intensities of the three most intense peptides per protein to an internally digested standard protein (Hi3 approach). Previous results showed that these average signal intensities per mole protein are constant within a tolerance of 10% (10). Recently the smart combination of AQUA technique and APEX approach was successfully applied to Leptospira interrogans covering about half of the proteome with an error less than threefold (11).In order to quantify the highest possible number of expressed proteins in an absolute manner mass spectrometry based methods seem to be the method of choice. Within the field of proteomics MS is often coupled with liquid chromatography to reduce sample complexity prior to MS analysis (LC/MS). Commonly applied data dependent acquisition (DDA) methods for peptide identification suffer from some limitations. Often low abundant peptides with a low MS signal intensity are discriminated and their isobaric precursor ions cannot be isolated leading to low scores in database search and wrong assignments (12, 13). These obstacles lead to lower protein sequence coverage in general and higher numbers of protein identifications based on a single peptide only. In contrast, with data independent acquisition (DIA) methods like LC/MS^E (14) all available precursor ions are fragmented in parallel without any selection by switching between low and high collision energy scans in high frequency. Therefore DIA can circumvent the disadvantages of DDA mentioned above. LC/MS^E utilizes chromatographic elution profiles of precursor masses to track the fragment ion spectra. Because all charge states and isotopic peaks of precursor ions are included for fragmentation (15) the LC/MS^E technique enables higher sequence coverage and has large advantages in the analysis of highly complex samples consisting of numerous co-eluting peptides (16). Combination of DIA methods with the approach based on Hi3 signal intensities was shown to be of potentially high performance for absolute protein quantification at global scale (17, 18) and is therefore used in this study.In this article, we applied a global absolute quantification approach based on the Hi3 method and data independent acquisition to the Gram-positive model bacterium Bacillus subtilis grown under two conditions for which large differences both in absolute protein amount per cell and in the predicted configurations of metabolic pathways were expected (19): a glucose and ammonia salts minimal medium (condition S) and a solely amino acid based medium (condition CH). This experimental set up enabled the physiologically meaningful comparison of profound consequences of growth under conditions requiring amino acid synthesis (S) or amino acid degradation (CH), as well as concerning the change between glycolytic (S) and gluconeogenic growth (CH). Moreover, as a model bacterium closely related to very important pathogens, B. subtilis is one of the best studied microorganisms. Particularly relevant for our study, the genomic organization of the chromosome, the regulatory network and metabolic pathways are well characterized. Based on this existing knowledge, global absolute protein quantification exemplary enabled (a) the large-scale investigation of protein distribution between cellular processes, (b) the systematic analysis of differential protein abundances for genes belonging to an operon (referred to as operon heterogeneity); and (c) the computation of the protein costs of cellular processes and of metabolic pathways in particular.     

Photoactivation Approaches Reveal a Role for Rab11 in FGFR4 Recycling and Signalling

Fibroblast growth factor receptor 4 (FGFR4) plays important roles during development and in the adult to maintain tissue homeostasis. Moreover, overexpression of FGFR4 or activating mutations in FGFR4 has been identified as tumour‐promoting events in several forms of cancer. Endocytosis is important for regulation of signalling receptors and we have previously shown that FGFR4 is mainly localized to transferrin‐positive structures after ligand‐induced endocytosis. Here, using a cell line with a defined pericentriolar endocytic recycling compartment, we show that FGFR4 accumulates in this compartment after endocytosis. Furthermore, using classical recycling assays and a new, photoactivatable FGFR4‐PA‐GFP fusion protein combined with live‐cell imaging, we demonstrate that recycling of FGFR4 is dependent on Rab11. Upon Rab11b depletion, FGFR4 is trapped in the pericentriolar recycling compartment and the total levels of FGFR4 in cells are increased. Moreover, fibroblast growth factor 1 (FGF1)‐induced autophosphorylation of FGFR4 as well as phosphorylation of phospholipase C (PLC)‐γ is prolonged in cells depleted of Rab11. Interestingly, the activation of mitogen‐activated protein kinase and AKT pathways were not prolonged but rather reduced in Rab11‐depleted cells, indicating that recycling of FGFR4 is important for the nature of its signalling output. Thus, Rab11‐dependent recycling of FGFR4 maintains proper levels of FGFR4 in cells and regulates FGF1‐induced FGFR4 signalling.      

The in situ distribution of glycoprotein-bound 4-O-Acetylated sialic acids in vertebrates

Sialic acids are located at the terminal branches of the cell glycocalyx and secreted glycan molecules. O-Acetylation is an important modification of the sialic acids, however very few studies have demonstrated the in situ distribution of the O-Acetylated sialic acids. Here the distribution of glycoprotein bound 4-O-Acetylated sialic acids (4-O-Ac sias) in vertebrates was determined using a novel virus histochemistry assay. The 4-O-Ac sias were found in the circulatory system, i.e. on the surface of endothelial cells and RBCs, of several vertebrate species, though most frequently in the cartilaginous fish (class Chondrichthyes) and the bony fish (class Osteichthyes). The O-Acetylated sialic acid was detected in 64 % of the examined fish species. Even though the sialic acid was found less commonly in higher vertebrates, it was found at the same location in the positive species. The general significance of this endothelial labelling pattern distribution is discussed. The seemingly conserved local position through the evolution of the vertebrates, suggests an evolutionary advantage of this sialic acid modification.     

Variables Associated with Change in Quality of Life among Persons with Dementia in Nursing Homes: A 10 Months Follow-Up Study

Aim

To investigate variables associated with change in quality of life (QOL), measured by QUALID scale and three subscales; tension, sadness and wellbeing, among dementia patients in nursing homes.

Method

A 10 months follow-up study including 198 (female 156, 79%) nursing home patients, mean age 87 (s.d 7.7) years. Scales applied; quality of life in late stage dementia (QUALID) scale and three subscales (wellbeing, sadness and tension), neuropsychiatric inventory questionnaire 10 items (NPI-10-Q), clinical dementia rating (CDR) scale, physical self-maintenance (PSMS) scale and a scale of general medical health. Use of psychotropic medication, gender and age was collected from the patient''s records.

Results

Mean baseline QUALID score: 20.6 (s.d.7.0), follow-up score: 22.9 (s.d.7.4), mean change 2.8 (s.d.7.4). QOL improved in 30.8%, were unchanged in 14.7%, deteriorated in 54.6% of patients. A regression analysis revealed that change in QUALID score was significantly associated with: QUALID baseline score (beta -.381, p-value.000), change in NPI score (beta.421, p-value.000), explained variance 38.1%. Change in score on wellbeing subscale associated with: change in PSMS score (beta.185, p-value.019), wellbeing baseline score (beta -.370, p-value.000), change in NPI score (beta.186, p-value.017), explained variance 25.3%. Change in score on tension subscale associated with: change in CDR sum-of-boxes (beta.214, p-value.003), change in NPI score (beta.270, p-value.000), tension baseline score (beta -.423, p-value.000), explained variance 34.6%. Change in score on sadness subscale associated with: change in NPI score (beta.404, p-value.000), sadness baseline score (beta -.438, p-value.000), explained variance 38.8%.

Conclusion

The results imply that a lower baseline score (better QOL) results in a larger change in QOL (towards worse QOL). Change in QOL is mostly associated with change in neuropsychiatric symptoms. In almost 50% of patients QOL did not deteriorate.     

Risk‐sensitive reproductive allocation: fitness consequences of body mass losses in two contrasting environments

For long‐lived organisms, the fitness value of survival is greater than that of current reproduction. Asymmetric fitness rewards suggest that organisms inhabiting unpredictable environments should adopt a risk‐sensitive life history, predicting that it is adaptive to allocate resources to increase their own body reserves at the expense of reproduction. We tested this using data from reindeer populations inhabiting contrasting environments and using winter body mass development as a proxy for the combined effect of winter severity and density dependence. Individuals in good and harsh environments responded similarly: Females who lost large amounts of winter body mass gained more body mass the coming summer compared with females losing less mass during winter. Additionally, females experienced a cost of reproduction: On average, barren females gained more body mass than lactating females. Winter body mass development positively affected both the females' reproductive success and offspring body mass. Finally, we discuss the relevance of our findings with respect to scenarios for future climate change.