Genomic evidence of genetic variation with pleiotropic effects on caterpillar fitness and plant traits in a model legume

Plant–insect interactions are ubiquitous, and have been studied intensely because of their relevance to damage and pollination in agricultural plants, and to the ecology and evolution of biodiversity. Variation within species can affect the outcome of these interactions. Specific genes and chemicals that mediate these interactions have been identified, but genome‐ or metabolome‐scale studies might be necessary to better understand the ecological and evolutionary consequences of intraspecific variation for plant–insect interactions. Here, we present such a study. Specifically, we assess the consequences of genome‐wide genetic variation in the model plant Medicago truncatula for Lycaeides melissa caterpillar growth and survival (larval performance). Using a rearing experiment and a whole‐genome SNP data set (>5 million SNPs), we found that polygenic variation in M. truncatula explains 9%–41% of the observed variation in caterpillar growth and survival. Genetic correlations among caterpillar performance and other plant traits, including structural defences and some anonymous chemical features, suggest that multiple M. truncatula alleles have pleiotropic effects on plant traits and caterpillar performance (or that substantial linkage disequilibrium exists among distinct loci affecting subsets of these traits). A moderate proportion of the genetic effect of M. truncatula alleles on L. melissa performance can be explained by the effect of these alleles on the plant traits we measured, especially leaf toughness. Taken together, our results show that intraspecific genetic variation in M. truncatula has a substantial effect on the successful development of L. melissa caterpillars (i.e., on a plant–insect interaction), and further point toward traits potentially mediating this genetic effect.     

Low‐tech riparian and wet meadow restoration increases vegetation productivity and resilience across semiarid rangelands

Restoration of riparian and wet meadow ecosystems in semiarid rangelands of the western United States is a high priority given their ecological and hydrological importance in the region. However, traditional restoration approaches are often intensive and costly, limiting the extent over which they can be applied. Practitioners are increasingly trying new restoration techniques that are more cost‐effective, less intensive, and can more practically scale up to the scope of degradation. Unfortunately, practitioners typically lack resources to undertake outcome‐based evaluations necessary to judge the efficacy of these techniques. In this study, we use freely available, satellite remote sensing to explore changes in vegetation productivity (normalized difference vegetation index) of three distinct, low‐tech, riparian and wet meadow restoration projects. Case studies are presented that range in geographic location (Colorado, Oregon, and Nevada), restoration practice (Zeedyk structures, beaver dam analogs, and grazing management), and time since implementation. Restoration practices resulted in increased vegetation productivity of up to 25% and increased annual persistence of productive vegetation. Improvements in productivity with time since restoration suggest that elevated resilience may further enhance wildlife habitat and increase forage production. Long‐term, documented outcomes of conservation are rare; we hope our findings empower practitioners to further monitor and explore the use of low‐tech methods for restoration of ecohydrologic processes at meaningful spatial scales.     

Molecular simulation of protein aggregation

Computer simulation offers unique possibilities for investigating molecular-level phenomena difficult to probe experimentally. Drawing from a wealth of studies concerning protein folding, computational studies of protein aggregation are emerging. These studies have been successful in capturing aspects of aggregation known from experiment and are being used to refine experimental methods aimed at abating aggregation. Here we review molecular-simulation studies of protein aggregation conducted in our laboratory. Specific attention is devoted to issues with implications for biotechnology.     

Sex in flies: what 'body--mind' dichotomy?

Sexual behavior in Drosophila results from interactions of multiple neural and genetic pathways. Male-specific fruitless (fruM) is a major component inducing male behaviors, but recent work indicates key roles for other sex-specific and sex-non-specific components. Notably, male-like courtship by retained (retn) mutant females reveals an intrinsic pathway for male behavior independent of fruM, while behavioral differences between males and females with equal levels of fruM expression indicate involvement of another sex-specific component. Indeed, sex-specific products of doublesex (dsxF and dsxM), that control sexual differentiation of the body, also contribute to sexual behavior and neural development of both sexes. In addition, the single product of the dissatisfaction (dsf) gene is needed for appropriate behavior in both sexes, implying additional complexities and levels of control. The genetic mechanisms controlling sexual behavior are similar to those controlling body sexual development, suggesting biological advantages of modifying an intermediate intrinsic pathway in generation of two substantially different behavioral or morphological states.     

Estimating differential reproductive success from nests of related individuals, with application to a study of the mottled sculpin, Cottus bairdi

Understanding how variation in reproductive success is related to demography is a critical component in understanding the life history of an organism. Parentage analysis using molecular markers can be used to estimate the reproductive success of different groups of individuals in natural populations. Previous models have been developed for cases where offspring are random samples from the population but these models do not account for the presence of full- and half-sibs commonly found in large clutches of many organisms. Here we develop a model for comparing reproductive success among different groups of individuals that explicitly incorporates within-nest relatedness. Inference for the parameters of the model is done in a Bayesian framework, where we sample from the joint posterior of parental assignments and fertility parameters. We use computer simulations to determine how well our model recovers known parameters and investigate how various data collection scenarios (varying the number of nests or the number of offspring) affect the estimates. We then apply our model to compare reproductive success among different age groups of mottled sculpin, Cottus bairdi, from a natural population. We demonstrate that older adults are more likely to contribute to a nest and that females in the older age groups contribute more eggs to a nest than younger individuals.     

Differential modulation of 3T3-L1 adipogenesis mediated by 11beta-hydroxysteroid dehydrogenase-1 levels

The localized activation of circulating glucocorticoids in vivo by the enzyme 11beta-hydroxysteroid dehydrogenase type 1 (11beta-HSD1) plays a critical role in the development of the metabolic syndrome. However, the precise contribution of 11beta-HSD1 in the initiation of adipogenesis by inactive glucocorticoids is not fully understood. 3T3-L1 fibroblasts can be terminally differentiated to mature adipocytes in a glucocorticoid-dependent manner. Both inactive rodent dehydrocorticosterone and human cortisone were able to substitute for the synthetic glucocorticoid dexamethasone in 3T3-L1 adipogenesis, suggesting a potential role for 11beta-HSD1 in these effects. Differentiation of 3T3-L1 cells caused a strong increase in 11beta-HSD1 protein levels, which occurred late in the differentiation protocol. Reduction of 11beta-HSD1 activity in 3T3-L1 fibroblasts, achieved by pharmacological inhibition or adenovirally mediated delivery of short hairpin RNA constructs, specifically blocked the ability of inactive glucocorticoids to drive 3T3-L1 differentiation. However, even modest increases in exogenous 11beta-HSD1 expression in 3T3-L1 fibroblasts, to levels comparable with endogenous 11beta-HSD1 in differentiated 3T3-L1 adipocytes, were sufficient to block adipogenesis. Luciferase reporter assays indicated that overexpressed 11beta-HSD1 was catalyzing the inactivating dehydrogenase reaction, because the ability of both active and inactive glucocorticoids to activate the glucocorticoid receptor were largely suppressed. These results suggest that the temporal regulation of 11beta-HSD1 expression is tightly controlled in 3T3-L1 cells, so as to mediate the initiation of differentiation by inactive glucocorticoids and also to prevent the inhibitory activity of prematurely expressed 11beta-HSD1 during adipogenesis.     

National mass drug administration costs for lymphatic filariasis elimination

Background

Because lymphatic filariasis (LF) elimination efforts are hampered by a dearth of economic information about the cost of mass drug administration (MDA) programs (using either albendazole with diethylcarbamazine [DEC] or albendazole with ivermectin), a multicenter study was undertaken to determine the costs of MDA programs to interrupt transmission of infection with LF. Such results are particularly important because LF programs have the necessary diagnostic and treatment tools to eliminate the disease as a public health problem globally, and already by 2006, the Global Programme to Eliminate LF had initiated treatment programs covering over 400 million of the 1.3 billion people at risk.

Methodology/Principal Findings

To obtain annual costs to carry out the MDA strategy, researchers from seven countries developed and followed a common cost analysis protocol designed to estimate 1) the total annual cost of the LF program, 2) the average cost per person treated, and 3) the relative contributions of the endemic countries and the external partners. Costs per person treated ranged from $0.06 to $2.23. Principal reasons for the variation were 1) the age (newness) of the MDA program, 2) the use of volunteers, and 3) the size of the population treated. Substantial contributions by governments were documented – generally 60%–90% of program operation costs, excluding costs of donated medications.

Conclusions/Significance

MDA for LF elimination is comparatively inexpensive in relation to most other public health programs. Governments and communities make the predominant financial contributions to actual MDA implementation, not counting the cost of the drugs themselves. The results highlight the impact of the use of volunteers on program costs and provide specific cost data for 7 different countries that can be used as a basis both for modifying current programs and for developing new ones.     

Liquid chromatography-mass spectrometry assay for quantification of Gluten Exorphin B5 in cerebrospinal fluid

A sensitive, precise and accurate method for the quantification of the alimentary opioid peptide Gluten Exorphin B5 (GE-B5, Tyr-Gly-Gly-Trp-Leu) in cerebrospinal fluid (CSF) was developed using liquid chromatography-mass spectrometry (LC-MS). Aliquots (10 microL) of sheep CSF were injected into a LC-MS instrument equipped with a reversed-phase C12 column at a flow rate of 250 microL/min. The mobile phase consisted of Eluent A water with 0.01% acetic acid as an ion-pairing reagent, and Eluent B acetonitrile. The LC-MS system was programmed to divert column flow to waste for 3.5 min after injection, after which time flow was directed into the mass spectrometer that operated in positive ion mode. DADLE (Tyr-D-Ala-Gly-Phe-D-Leu) was used as Internal Standard. No significant interfering peaks were detected at the retention times of GE-B5 in CSF blanks. The calibration curves were linear in the range of 0.39-78.00 ng/mL. The lower limit of detection and the lower limit of quantitation values for GE-B5 in CSF were established at 0.30 and 0.78 ng/mL, respectively. The intra-day and inter-day precision values were <12% relative standard deviation. The intra-day and inter-day accuracy were 99.46-100.86% and 98.95-100.02%, respectively. Recovery of GE-B5 in CSF samples was greater than 80%. Stability studies indicate that GE-B5 in CSF undergoes significant degradation (>55% after 600 min), which is reduced by the addition of protease inhibitors. This is the first reported method for the quantification of GE-B5 in CSF.     

Discovering robust protein biomarkers for disease from relative expression reversals in 2-D DIGE data

This study assesses the ability of a novel family of machine learning algorithms to identify changes in relative protein expression levels, measured using 2-D DIGE data, which support accurate class prediction. The analysis was done using a training set of 36 total cellular lysates comprised of six normal and three cancer biological replicates (the remaining are technical replicates) and a validation set of four normal and two cancer samples. Protein samples were separated by 2-D DIGE and expression was quantified using DeCyder-2D Differential Analysis Software. The relative expression reversal (RER) classifier correctly classified 9/9 training biological samples (p<0.022) as estimated using a modified version of leave one out cross validation and 6/6 validation samples. The classification rule involved comparison of expression levels for a single pair of protein spots, tropomyosin isoforms and alpha-enolase, both of which have prior association as potential biomarkers in cancer. The data was also analyzed using algorithms similar to those found in the extended data analysis package of DeCyder software. We propose that by accounting for sources of within- and between-gel variation, RER classifiers applied to 2-D DIGE data provide a useful approach for identifying biomarkers that discriminate among protein samples of interest.