Effects of Echinostoma trivolvis metacercariae infection during development and metamorphosis of the wood frog (Lithobates sylvaticus)

Many organisms face energetic trade-offs between defense against parasites and other host processes that may determine overall consequences of infection. These trade-offs may be particularly evident during unfavorable environmental conditions or energetically demanding life history stages. Amphibian metamorphosis, an ecologically important developmental period, is associated with drastic morphological and physiological changes and substantial energetic costs. Effects of the trematode parasite Echinostoma trivolvis have been documented during early amphibian development, but effects during later development and metamorphosis are largely unknown. Using a laboratory experiment, we examined the energetic costs of late development and metamorphosis coupled with E. trivolvis infection in wood frogs, Lithobates [=Rana] sylvaticus. Echinostoma infection intensity did not differ between tadpoles examined prior to and after completing metamorphosis, suggesting that metacercariae were retained through metamorphosis. Infection with E. trivolvis contributed to a slower growth rate and longer development period prior to the initiation of metamorphosis. In contrast, E. trivolvis infection did not affect energy expenditure during late development or metamorphosis. Possible explanations for these results include the presence of parasites not interfering with pronephros degradation during metamorphosis or the mesonephros compensating for any parasite damage. Overall, the energetic costs of metamorphosis for wood frogs were comparable to other species with similar life history traits, but differed from a species with a much shorter duration of metamorphic climax. Our findings contribute to understanding the possible role of energetic trade-offs between parasite defense and host processes by considering parasite infection with simultaneous energetic demands during a sensitive period of development

Effects of Ultraviolet Radiation on Amphibians: Field Experiments

Numerous reports suggest that populations of amphibians from a wide variety of locations are experiencing population declines and/or range reductions. In some cases, unusually high egg mortality has been reported. Field experiments have been used with increasing frequency to investigate ultraviolet radiation as one of the potential factors contributing to these declines. Results from field experiments illustrate that hatching success of eggs is hampered by ultraviolet radiation in a number of species, while other species appear to be unaffected. Continued mortality in early life-history stages may ultimately contribute to a population decline. Although UV-B radiation may not contribute to the population declines of all species, it may play a role in the population decline of some species, especially those that lay eggs in open shallow water subjected to solar radiation and in those that have a poor ability to repair UV-induced DNA damage.Peer reviewe

Using “omics” and integrated multi-omits approaches to guide probiotic selection to mitigate chytridiomycosis and other emerging infectious diseases

Emerging infectious diseases in wildlife are responsible for massive population declines. In amphibians, chytridiomycosis caused by Batrachochytrium dendrobatidis, Bd, has severely affected many amphibian populations and species around the world. One promising management strategy is probiotic bioaugmentation of antifungal bacteria on amphibian skin. In vivo experimental trials using bioaugmentation strategies have had mixed results, and therefore a more informed strategy is needed to select successful probiotic candidates. Metagenomic, transcriptomic, and metabolomic methods, colloquially called “omics,” are approaches that can better inform probiotic selection and optimize selection protocols. The integration of multiple omic data using bioinformatic and statistical tools and in silico models that link bacterial community structure with bacterial defensive function can allow the identification of species involved in pathogen inhibition. We recommend using 16S rRNA gene amplicon sequencing and methods such as indicator species analysis, the Kolmogorov–Smirnov Measure, and co-occurrence networks to identify bacteria that are associated with pathogen resistance in field surveys and experimental trials. In addition to 16S amplicon sequencing, we recommend approaches that give insight into symbiont function such as shotgun metagenomics, metatranscriptomics, or metabolomics to maximize the probability of finding effective probiotic candidates, which can then be isolated in culture and tested in persistence and clinical trials. An effective mitigation strategy to ameliorate chytridiomycosis and other emerging infectious diseases is necessary; the advancement of omic methods and the integration of multiple omic data provide a promising avenue toward conservation of imperiled species

Antifungal isolates database of amphibian skin-associated bacteria and function against emerging fungal pathogens

Microbial symbionts of vertebrate skin have an important function in defense of the host against pathogens. In particular, the emerging chytrid fungus Batrachochytrium dendrobatidis, causes widespread disease in amphibians but can be inhibited via secondary metabolites produced by many different skin-associated bacteria. Similarly, the fungal pathogens of terrestrial salamander eggs Mariannaea elegans and Rhizomucor variabilis are also inhibited by a variety of skin-associated bacteria. Indeed, probiotic therapy against fungal diseases is a recent approach in conservation medicine with growing experimental support. We present a comprehensive Antifungal Isolates Database of amphibian skin-associated bacteria that have been cultured, isolated, and tested for antifungal properties. At the start, this database includes nearly 2000 cultured bacterial isolates from 37 amphibian host species across 18 studies on five continents: Africa, Oceania, Europe, and North and South America. As the research community gathers information on additional isolates, the database will be updated periodically. The resulting database can serve as a conservation tool for amphibians and other organisms, and provides empirical data for comparative and bioinformatic studies. The database consists of a FASTA file containing 16S rRNA gene sequences of the bacterial isolates, and a metadata file containing information on the host species, life-stage, geographic region, and antifungal capacity and taxonomic identity of the isolate

The genetic architecture of the human cerebral cortex

The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder

Conversion Discriminative Analysis on Mild Cognitive Impairment Using Multiple Cortical Features from MR Images

Neuroimaging measurements derived from magnetic resonance imaging provide important information required for detecting changes related to the progression of mild cognitive impairment (MCI). Cortical features and changes play a crucial role in revealing unique anatomical patterns of brain regions, and further differentiate MCI patients from normal states. Four cortical features, namely, gray matter volume, cortical thickness, surface area, and mean curvature, were explored for discriminative analysis among three groups including the stable MCI (sMCI), the converted MCI (cMCI), and the normal control (NC) groups. In this study, 158 subjects (72 NC, 46 sMCI, and 40 cMCI) were selected from the Alzheimer's Disease Neuroimaging Initiative. A sparse-constrained regression model based on the l2-1-norm was introduced to reduce the feature dimensionality and retrieve essential features for the discrimination of the three groups by using a support vector machine (SVM). An optimized strategy of feature addition based on the weight of each feature was adopted for the SVM classifier in order to achieve the best classification performance. The baseline cortical features combined with the longitudinal measurements for 2 years of follow-up data yielded prominent classification results. In particular, the cortical thickness produced a classification with 98.84% accuracy, 97.5% sensitivity, and 100% specificity for the sMCI–cMCI comparison; 92.37% accuracy, 84.78% sensitivity, and 97.22% specificity for the cMCI–NC comparison; and 93.75% accuracy, 92.5% sensitivity, and 94.44% specificity for the sMCI–NC comparison. The best performances obtained by the SVM classifier using the essential features were 5–40% more than those using all of the retained features. The feasibility of the cortical features for the recognition of anatomical patterns was certified; thus, the proposed method has the potential to improve the clinical diagnosis of sub-types of MCI and predict the risk of its conversion to Alzheimer's disease

Clutch monitoring data

Summary of fates of embryos from male removal experiment

Sequence metadata

Metadata for all sequences contained in adjoining sequence (.fastq) file