Effects of husbandry parameters on the life-history traits of the apple snail, Marisa cornuarietis: effects of temperature, photoperiod, and population density

These experiments are part of a larger study designed to investigate the influence of husbandry parameters on the life history of the apple snail, Marisa cornuarietis. The overall objective of the program is to identify suitable husbandry conditions for maintaining multi-generation populations of this species in the laboratory for use in ecotoxicological testing. In this article, we focus on the effects of photoperiod, temperature, and population density on adult fecundity and juvenile growth. Increasing photoperiod from 12 to 16 h of light per day had no effect on adult fecundity or egg hatching and relatively minor effects on juvenile growth and development. Rearing snails at temperatures between 22°C and 28°C did not influence the rates of egg production or egg clutch size. However, the rates of growth and development (of eggs and juveniles) increased with increasing temperature in this range, and when temperatures were reduced to 22°C egg-hatching success was impaired. Juvenile growth and development were more sensitive to rearing density than adult fecundity traits. On the basis of the present results, we conclude that rearing individuals of M. cornuarietis at a temperature of 25°C, a photoperiod of 12L:12D, and a density of <0.8 snails L−1 (with lower densities for juvenile snails) should provide favorable husbandry conditions for maintaining multi-generation populations of this species

Effects of food type, feeding frequency, and temperature on juvenile survival and growth of Marisa cornuarietis (Mollusca: Gastropoda)

The present experiments are part of a larger study designed to investigate the influence of husbandry parameters on the life history of the ramshorn snail, Marisa cornuarietis, in order to identify suitable husbandry conditions for maintaining multi-generation populations in the laboratory for use in ecotoxicological testing. In this paper we focus on the effects of a combination of food types and feeding frequencies (i.e., the frequency with which the snails were offered food) on juvenile growth and survival at different temperatures. Offspring produced in the laboratory by wild specimens of M. cornuarietis, from Puerto Rico, were used to test the effects of three types of food (lettuce, alginate with fish food, alginate with snail mix) fed at three frequencies (given ad libitum on 4/4, 2/4, or 1/4 d) on juvenile survival and growth. The 4-d feeding regimens were repeated four times, giving a total of 16 d for the experiments. The experiments were conducted at two temperatures (22° and 25°C) under a 12 h light:12 h dark photoperiod. Juvenile growth rates increased with increasing feeding frequency for all food types. The most rapid growth rates occurred in the high-frequency lettuce treatments and the slowest growth rates in the low-frequency lettuce and alginate with snail mix treatments. Juvenile snails grew faster at 25° than at 22°C, and mortality was about twice as high at the lower temperature. Growth rates were used to provide a rough estimate of time to maturity, which was determined to take about twice as long at 22° than at 25°C. The results showed that lettuce is the best food if supplied in abundance, but effects on growth are very dependent on feeding frequency and temperature. We conclude that 25°C is a more appropriate temperature for maintaining populations than 22°C, that lettuce provides a suitable food source, and that food should be supplied continuously for husbandry and toxicity testing of populations of M. cornuarietis

Common Variants at 10 Genomic Loci Influence Hemoglobin A(1C) Levels via Glycemic and Nonglycemic Pathways

OBJECTIVE-Glycated hemoglobin (HbA(1c)), used to monitor and diagnose diabetes, is influenced by average glycemia over a 2- to 3-month period. Genetic factors affecting expression, turnover, and abnormal glycation of hemoglobin could also be associated with increased levels of HbA(1c). We aimed to identify such genetic factors and investigate the extent to which they influence diabetes classification based on HbA(1c) levels.RESEARCH DESIGN AND METHODS-We studied associations with HbA(1c) in up to 46,368 nondiabetic adults of European descent from 23 genome-wide association studies (GWAS) and 8 cohorts with de novo genotyped single nucleotide polymorphisms (SNPs). We combined studies using inverse-variance meta-analysis and tested mediation by glycemia using conditional analyses. We estimated the global effect of HbA(1c) loci using a multilocus risk score, and used net reclassification to estimate genetic effects on diabetes screening.RESULTS-Ten loci reached genome-wide significant association with HbA(1c), including six new loci near FN3K (lead SNP/P value, rs1046896/P = 1.6 x 10(-26)), HFE (rs1800562/P = 2.6 x 10(-20)), TMPRSS6 (rs855791/P = 2.7 x 10(-14)), ANK1 (rs4737009/P = 6.1 x 10(-12)), SPTA1 (rs2779116/P = 2.8 x 10(-9)) and ATP11A/TUBGCP3 (rs7998202/P = 5.2 x 10(-9)), and four known HbA(1c) loci: HK1 (rs16926246/P = 3.1 x 10(-54)), MTNR1B (rs1387153/P = 4.0 X 10(-11)), GCK (rs1799884/P = 1.5 x 10(-20)) and G6PC2/ABCB11 (rs552976/P = 8.2 x 10(-18)). We show that associations with HbA(1c) are partly a function of hyperglycemia associated with 3 of the 10 loci (GCK, G6PC2 and MTNR1B). The seven nonglycemic loci accounted for a 0.19 (%HbA(1c)) difference between the extreme 10% tails of the risk score, and would reclassify similar to 2% of a general white population screened for diabetes with HbA(1c).CONCLUSIONS-GWAS identified 10 genetic loci reproducibly associated with HbA(1c). Six are novel and seven map to loci where rarer variants cause hereditary anemias and iron storage disorders. Common variants at these loci likely influence HbA(1c) levels via erythrocyte biology, and confer a small but detectable reclassification of diabetes diagnosis by HbA(1c) Diabetes 59: 3229-3239, 201

Autophagy Protein Atg3 is Essential for Maintaining Mitochondrial Integrity and for Normal Intracellular Development of Toxoplasma gondii Tachyzoites

Autophagy is a cellular process that is highly conserved among eukaryotes and permits the degradation of cellular material. Autophagy is involved in multiple survival-promoting processes. It not only facilitates the maintenance of cell homeostasis by degrading long-lived proteins and damaged organelles, but it also plays a role in cell differentiation and cell development. Equally important is its function for survival in stress-related conditions such as recycling of proteins and organelles during nutrient starvation. Protozoan parasites have complex life cycles and face dramatically changing environmental conditions; whether autophagy represents a critical coping mechanism throughout these changes remains poorly documented. To investigate this in Toxoplasma gondii, we have used TgAtg8 as an autophagosome marker and showed that autophagy and the associated cellular machinery are present and functional in the parasite. In extracellular T. gondii tachyzoites, autophagosomes were induced in response to amino acid starvation, but they could also be observed in culture during the normal intracellular development of the parasites. Moreover, we generated a conditional T. gondii mutant lacking the orthologue of Atg3, a key autophagy protein. TgAtg3-depleted parasites were unable to regulate the conjugation of TgAtg8 to the autophagosomal membrane. The mutant parasites also exhibited a pronounced fragmentation of their mitochondrion and a drastic growth phenotype. Overall, our results show that TgAtg3-dependent autophagy might be regulating mitochondrial homeostasis during cell division and is essential for the normal development of T. gondii tachyzoites

Conformation-regulated mechanosensory control via titin domains in cardiac muscle

The giant filamentous protein titin is ideally positioned in the muscle sarcomere to sense mechanical stimuli and transform them into biochemical signals, such as those triggering cardiac hypertrophy. In this review, we ponder the evidence for signaling hotspots along the titin filament involved in mechanosensory control mechanisms. On the way, we distinguish between stress and strain as triggers of mechanical signaling events at the cardiac sarcomere. Whereas the Z-disk and M-band regions of titin may be prominently involved in sensing mechanical stress, signaling hotspots within the elastic I-band titin segment may respond primarily to mechanical strain. Common to both stress and strain sensor elements is their regulation by conformational changes in protein domains

Modulation of 11β-hydroxysteroid dehydrogenase as a strategy to reduce vascular inflammation

Atherosclerosis is a chronic inflammatory disease in which initial vascular damage leads to extensive macrophage and lymphocyte infiltration. Although acutely glucocorticoids suppress inflammation, chronic glucocorticoid excess worsens atherosclerosis, possibly by exacerbating systemic cardiovascular risk factors. However, glucocorticoid action within the lesion may reduce neointimal proliferation and inflammation. Glucocorticoid levels within cells do not necessarily reflect circulating levels due to pre-receptor metabolism by 11β-hydroxysteroid dehydrogenases (11β-HSDs). 11β-HSD2 converts active glucocorticoids into inert 11-keto forms. 11β-HSD1 catalyses the reverse reaction, regenerating active glucocorticoids. 11β-HSD2-deficiency/ inhibition causes hypertension, whereas deficiency/ inhibition of 11β-HSD1 generates a cardioprotective lipid profile and improves glycemic control. Importantly, 11β-HSD1-deficiency/ inhibition is atheroprotective, whereas 11β-HSD2-deficiency accelerates atherosclerosis. These effects are largely independent of systemic risk factors, reflecting modulation of glucocorticoid action and inflammation within the vasculature. Here, we consider whether evidence linking the 11β-HSDs to vascular inflammation suggests these isozymes are potential therapeutic targets in vascular injury and atherosclerosis

Mining the human phenome using allelic scores that index biological intermediates

J. Kaprio ja M-L. Lokki työryhmien jäseniä.It is common practice in genome-wide association studies (GWAS) to focus on the relationship between disease risk and genetic variants one marker at a time. When relevant genes are identified it is often possible to implicate biological intermediates and pathways likely to be involved in disease aetiology. However, single genetic variants typically explain small amounts of disease risk. Our idea is to construct allelic scores that explain greater proportions of the variance in biological intermediates, and subsequently use these scores to data mine GWAS. To investigate the approach's properties, we indexed three biological intermediates where the results of large GWAS meta-analyses were available: body mass index, C-reactive protein and low density lipoprotein levels. We generated allelic scores in the Avon Longitudinal Study of Parents and Children, and in publicly available data from the first Wellcome Trust Case Control Consortium. We compared the explanatory ability of allelic scores in terms of their capacity to proxy for the intermediate of interest, and the extent to which they associated with disease. We found that allelic scores derived from known variants and allelic scores derived from hundreds of thousands of genetic markers explained significant portions of the variance in biological intermediates of interest, and many of these scores showed expected correlations with disease. Genome-wide allelic scores however tended to lack specificity suggesting that they should be used with caution and perhaps only to proxy biological intermediates for which there are no known individual variants. Power calculations confirm the feasibility of extending our strategy to the analysis of tens of thousands of molecular phenotypes in large genome-wide meta-analyses. We conclude that our method represents a simple way in which potentially tens of thousands of molecular phenotypes could be screened for causal relationships with disease without having to expensively measure these variables in individual disease collections.Peer reviewe