Effect of a Standardised Dietary Restriction Protocol on Multiple Laboratory Strains of Drosophila melanogaster

Background

Outcomes of lifespan studies in model organisms are particularly susceptible to variations in technical procedures. This is especially true of dietary restriction, which is implemented in many different ways among laboratories.

Principal Findings

In this study, we have examined the effect of laboratory stock maintenance, genotype differences and microbial infection on the ability of dietary restriction (DR) to extend life in the fruit fly Drosophila melanogaster. None of these factors block the DR effect.

Conclusions

These data lend support to the idea that nutrient restriction genuinely extends lifespan in flies, and that any mechanistic discoveries made with this model are of potential relevance to the determinants of lifespan in other organisms.     

Antepartum glucose tolerance test results as predictors of type 2 diabetes mellitus in women with a history of gestational diabetes mellitus: A systematic review

Background: Women with a history of gestational diabetes mellitus (GDM) are at high risk for type 2 diabetes mellitus (T2DM).Objective: We reviewed prospective studies of antepartum glucose tolerance test results as risk factors for development of T2DM among women with a history of GDM.Methods: We searched 4 electronic databases and hand-searched 13 journals for literature published through January 2007. The search strategy consisted of medical subject headings and text words for GDM, T2DM, and other relevant terms. Articles were excluded for the following reasons: (1) not written in English; (2) no human data; (3) no original data; (4) <90% of sample was diagnosed with GDM without a separate analysis for women with GDM; (5) case report or series; (6) diagnosis of GDM not based on 3-hour 100-g oral glucose tolerance test (OGTT) or 2-hour 75-g OGTT; (7) T2DM not evaluated as outcome; (8) no relative measure of association or incidence reported; or (9) design did not address antepartum OGTT as a predictor of T2DM. Two investigators independently reviewed citations, performed serial data abstraction on full articles, and assessed the quality of each article. Data were abstracted for study participants and characteristics, T2DM diagnosis, length of follow-up, regression model covariates, and measures of association and variability.Results: Of 11,400 unique citations, we identified 11 articles that evaluated antepartum glucose testing and risk of T2DM in women with a history of GDM. Five studies found that the fasting blood glucose (FBG) on the antepartum diagnostic OGTT was a significant predictor of T2DM (odds ratio [OR] range: 11.1–21.0; relative risk [RR] range: 1.37–1.5; relative hazard [RH] = 2.47). Risk of incident T2DM was predicted by the antepartum 2-hour OGTT plasma glucose in 3 studies (OR range: 1.02–1.03; RR = 1.3) and by the antepartum OGTT glucose AUC in 3 other studies (OR range: 3.64–15; RH = 2.13). Overall, study quality was limited by high losses to follow-up (>20% in 6 studies) and short duration. Few studies adjusted for adiposity, an established diabetes risk factor.Conclusion: FBG, OGTT 2-hour blood glucose, and OGTT glucose AUC appeared to be strong and consistent predictors of subsequent T2DM among women who met diagnostic criteria for GDM using the OGTT.     

Improving pairwise sequence alignment accuracy using near-optimal protein sequence alignments

Background  

While the pairwise alignments produced by sequence similarity searches are a powerful tool for identifying homologous proteins - proteins that share a common ancestor and a similar structure; pairwise sequence alignments often fail to represent accurately the structural alignments inferred from three-dimensional coordinates. Since sequence alignment algorithms produce optimal alignments, the best structural alignments must reflect suboptimal sequence alignment scores. Thus, we have examined a range of suboptimal sequence alignments and a range of scoring parameters to understand better which sequence alignments are likely to be more structurally accurate.     

New insights into neuropeptide modulation of aggression: field studies of arginine vasotocin in a territorial tropical damselfish

The neuropeptides arginine vasotocin (AVT) and arginine vasopressin are key modulators of affiliation and aggression among non-mammalian and mammalian vertebrates, respectively. Here, we explored AVT's effect on aggression in a wild population of beaugregory damselfish, Stegastes leucostictus, a highly territorial species. Aggression by territorial males towards 'intruders' (bottled fishes) was assessed before and after each male received intramuscular injections of either AVT, Manning compound (an AVT V1a receptor antagonist), isotocin (the teleost homologue of mammalian oxytocin differing from AVT by two amino acids) or saline (vehicle control). Compared to saline controls, AVT and Manning increased and decreased aggression, respectively, while isotocin had no effect. Response selectivity was further established in a dose-response study that revealed an inverted U-shaped function. Compared to saline controls, aggression levels for low and high AVT doses were similar, while medium dose treatments were significantly greater. This type of behavioural response, the first that we know of for a vertebrate neuropeptide, could depend on the binding of AVT to both V1-type and other AVT or non-AVT receptors. The pattern revealed here for damselfish may be symptomatic of species- and context-dependent specificity of AVT's modulation of aggression across teleosts, as is currently proposed for tetrapods.     

UniEuk: Time to Speak a Common Language in Protistology!

Universal taxonomic frameworks have been critical tools to structure the fields of botany, zoology, mycology, and bacteriology as well as their large research communities. Animals, plants, and fungi have relatively solid, stable morpho‐taxonomies built over the last three centuries, while bacteria have been classified for the last three decades under a coherent molecular taxonomic framework. By contrast, no such common language exists for microbial eukaryotes, even though environmental ‘‐omics’ surveys suggest that protists make up most of the organismal and genetic complexity of our planet's ecosystems! With the current deluge of eukaryotic meta‐omics data, we urgently need to build up a universal eukaryotic taxonomy bridging the protist ‐omics age to the fragile, centuries‐old body of classical knowledge that has effectively linked protist taxa to morphological, physiological, and ecological information. UniEuk is an open, inclusive, community‐based and expert‐driven international initiative to build a flexible, adaptive universal taxonomic framework for eukaryotes. It unites three complementary modules, EukRef, EukBank, and EukMap, which use phylogenetic markers, environmental metabarcoding surveys, and expert knowledge to inform the taxonomic framework. The UniEuk taxonomy is directly implemented in the European Nucleotide Archive at EMBL‐EBI, ensuring its broad use and long‐term preservation as a reference taxonomy for eukaryotes.     

Dynamic linear model for the identification of miRNAs in next-generation sequencing data

Summary Next‐generation sequencing technologies are poised to revolutionize the field of biomedical research. The increased resolution of these data promise to provide a greater understanding of the molecular processes that control the morphology and behavior of a cell. However, the increased amounts of data require innovative statistical procedures that are powerful while still being computationally feasible. In this article, we present a method for identifying small RNA molecules, called miRNAs, which regulate genes by targeting their mRNAs for degradation or translational repression. In the first step of our modeling procedure, we apply an innovative dynamic linear model that identifies candidate miRNA genes in high‐throughput sequencing data. The model is flexible and can accurately identify interesting biological features while accounting for both the read count, read spacing, and sequencing depth. Additionally, miRNA candidates are also processed using a modified Smith–Waterman sequence alignment that scores the regions for potential RNA hairpins, one of the defining features of miRNAs. We illustrate our method on simulated datasets as well as on a small RNA Caenorhabditis elegans dataset from the Illumina sequencing platform. These examples show that our method is highly sensitive for identifying known and novel miRNA genes.