The importance of epigeic beetles (Coleoptera) in tropical paddy fields: Example from Cameroon

Abstract

Indicators of diversity (population density, relative number of species, percentage of singletons, evenness) of ground beetles (Carabidae) and rove beetles (Staphylinidae) in rain-fed rice fields were assessed between 1995 and 1999 at Garoua in the Benue valley in North Cameroon. A total of 4369 individuals belonging to 44 species of carabids and 2109 staphylinids in 27 species were caught by means of pitfall traps. Among the carabids, five species: Menigius lucidus var. strigiceps Qued., Chlaeniostenus denticulatus elatus Erichson, Lissauchenius venator (Laferté), Pheropsophus marginatus Dej. and Abacetus crenulatus Dej. in decreasing order, were dominant. In the staphylinid group, the species Paederus sabaeus Erichson was the most common, followed by Stenus ravus Puthz and Stenus (mendicus) senegalensis Bernhauer. Shannon-Weiner and evenness indices varied marginally from year to year. Diversity values remained relatively low ( < 2.8) among each group of beetles, which indicated that paddy fields were moderately populated by this group of polyphagous predators. Features of predacious soil surface-dwelling beetles in West African rice ecosystems are discussed in the light of Integrated Pest Management concepts.     

Oro-Gustatory Perception of Dietary Lipids and Calcium Signaling in Taste Bud Cells Are Altered in Nutritionally Obesity-Prone Psammomys obesus

Since the increasing prevalence of obesity is one of the major health problems of the modern era, understanding the mechanisms of oro-gustatory detection of dietary fat is critical for the prevention and treatment of obesity. We have conducted the present study on Psammomys obesus, the rodent desert gerbil which is a unique polygenic natural animal model of obesity. Our results show that obese animals exhibit a strong preference for lipid solutions in a two-bottle test. Interestingly, the expression of CD36, a lipido-receptor, in taste buds cells (TBC), isolated from circumvallate papillae, was decreased at mRNA level, but remained unaltered at protein level, in obese animals. We further studied the effects of linoleic acid (LA), a long-chain fatty acid, on the increases in free intracellular calcium (Ca²⁺) concentrations, [Ca²⁺]i, in the TBC of P. obesus. LA induced increases in [Ca²⁺]i, largely via CD36, from intracellular pool, followed by the opening of store-operated Ca²⁺ (SOC) channels in the TBC of these animals. The action of this fatty acid on the increases in [Ca²⁺]i was higher in obese animals than that in controls. However, the release of Ca²⁺ from intracellular stores, studied also by employing thapsigargin, was lower in TBC of obese animals than control rodents. In this study, we show, for the first time, that increased lipid intake and altered Ca²⁺ signaling in TBC are associated with obesity in Psammomys obesus.     

Identification of Roles for Peptide: N-Glycanase and Endo-β-N-Acetylglucosaminidase (Engase1p) during Protein N-Glycosylation in Human HepG2 Cells

Background

During mammalian protein N-glycosylation, 20% of all dolichol-linked oligosaccharides (LLO) appear as free oligosaccharides (fOS) bearing the di-N-acetylchitobiose (fOSGN2), or a single N-acetylglucosamine (fOSGN), moiety at their reducing termini. After sequential trimming by cytosolic endo β-N-acetylglucosaminidase (ENGase) and Man2c1 mannosidase, cytosolic fOS are transported into lysosomes. Why mammalian cells generate such large quantities of fOS remains unexplored, but fOSGN2 could be liberated from LLO by oligosaccharyltransferase, or from glycoproteins by NGLY1-encoded Peptide-N-Glycanase (PNGase). Also, in addition to converting fOSGN2 to fOSGN, the ENGASE-encoded cytosolic ENGase of poorly defined function could potentially deglycosylate glycoproteins. Here, the roles of Ngly1p and Engase1p during fOS metabolism were investigated in HepG2 cells.

Methods/Principal Findings

During metabolic radiolabeling and chase incubations, RNAi-mediated Engase1p down regulation delays fOSGN2-to-fOSGN conversion, and it is shown that Engase1p and Man2c1p are necessary for efficient clearance of cytosolic fOS into lysosomes. Saccharomyces cerevisiae does not possess ENGase activity and expression of human Engase1p in the png1Δ deletion mutant, in which fOS are reduced by over 98%, partially restored fOS generation. In metabolically radiolabeled HepG2 cells evidence was obtained for a small but significant Engase1p-mediated generation of fOS in 1 h chase but not 30 min pulse incubations. Ngly1p down regulation revealed an Ngly1p-independent fOSGN2 pool comprising mainly Man₈GlcNAc₂, corresponding to ∼70% of total fOS, and an Ngly1p-dependent fOSGN2 pool enriched in Glc₁Man₉GlcNAc₂ and Man₉GlcNAc₂ that corresponds to ∼30% of total fOS.

Conclusions/Significance

As the generation of the bulk of fOS is unaffected by co-down regulation of Ngly1p and Engase1p, alternative quantitatively important mechanisms must underlie the liberation of these fOS from either LLO or glycoproteins during protein N-glycosylation. The fully mannosylated structures that occur in the Ngly1p-dependent fOSGN2 pool indicate an ERAD process that does not require N-glycan trimming.     

Statistical optimization of the phytoremediation of arsenic by Ludwigia octovalvis- in a pilot reed bed using response surface methodology (RSM) versus an artificial neural network (ANN)

In this study, the removal of arsenic (As) by plant, Ludwigia octovalvis, in a pilot reed bed was optimized. A Box-Behnken design was employed including a comparative analysis of both Response Surface Methodology (RSM) and an Artificial Neural Network (ANN) for the prediction of maximum arsenic removal. The predicted optimum condition using the desirability function of both models was 39 mg kg^?1 for the arsenic concentration in soil, an elapsed time of 42 days (the sampling day) and an aeration rate of 0.22 L/min, with the predicted values of arsenic removal by RSM and ANN being 72.6% and 71.4%, respectively. The validation of the predicted optimum point showed an actual arsenic removal of 70.6%. This was achieved with the deviation between the validation value and the predicted values being within 3.49% (RSM) and 1.87% (ANN). The performance evaluation of the RSM and ANN models showed that ANN performs better than RSM with a higher R² (0.97) close to 1.0 and very small Average Absolute Deviation (AAD) (0.02) and Root Mean Square Error (RMSE) (0.004) values close to zero. Both models were appropriate for the optimization of arsenic removal with ANN demonstrating significantly higher predictive and fitting ability than RSM.