Trends in tuna carbon isotopes suggest global changes in pelagic phytoplankton communities

Considerable uncertainty remains over how increasing atmospheric CO₂ and anthropogenic climate changes are affecting open‐ocean marine ecosystems from phytoplankton to top predators. Biological time series data are thus urgently needed for the world's oceans. Here, we use the carbon stable isotope composition of tuna to provide a first insight into the existence of global trends in complex ecosystem dynamics and changes in the oceanic carbon cycle. From 2000 to 2015, considerable declines in δ¹³C values of 0.8‰–2.5‰ were observed across three tuna species sampled globally, with more substantial changes in the Pacific Ocean compared to the Atlantic and Indian Oceans. Tuna recorded not only the Suess effect, that is, fossil fuel‐derived and isotopically light carbon being incorporated into marine ecosystems, but also recorded profound changes at the base of marine food webs. We suggest a global shift in phytoplankton community structure, for example, a reduction in ¹³C‐rich phytoplankton such as diatoms, and/or a change in phytoplankton physiology during this period, although this does not rule out other concomitant changes at higher levels in the food webs. Our study establishes tuna δ¹³C values as a candidate essential ocean variable to assess complex ecosystem responses to climate change at regional to global scales and over decadal timescales. Finally, this time series will be invaluable in calibrating and validating global earth system models to project changes in marine biota.     

Melanocortin‐1 receptor (MC1R) genotypes do not correlate with size in two cohorts of medium‐to‐giant congenital melanocytic nevi

Congenital melanocytic nevi (CMN) are cutaneous malformations whose prevalence is inversely correlated with projected adult size. CMN are caused by somatic mutations, but epidemiological studies suggest that germline genetic factors may influence CMN development. In CMN patients from the U.K., genetic variants in MC1R, such as p.V92M and loss‐of‐function variants, have been previously associated with larger CMN. We analyzed the association of MC1R variants with CMN characteristics in two distinct cohorts of medium‐to‐giant CMN patients from Spain (N = 113) and from France, Norway, Canada, and the United States (N = 53), similar at the clinical and phenotypical level except for the number of nevi per patient. We found that the p.V92M or loss‐of‐function MC1R variants either alone or in combination did not correlate with CMN size, in contrast to the U.K. CMN patients. An additional case–control analysis with 259 unaffected Spanish individuals showed a higher frequency of MC1R compound heterozygous or homozygous variant genotypes in Spanish CMN patients compared to the control population (15.9% vs. 9.3%; p = .075). Altogether, this study suggests that MC1R variants are not associated with CMN size in these non‐UK cohorts. Additional studies are required to define the potential role of MC1R as a risk factor in CMN development.     

Incorporating intraspecific variation into species distribution models improves distribution predictions,but cannot predict species traits for a wide-spread plant species

The most common approach to predicting how species ranges and ecological functions will shift with climate change is to construct correlative species distribution models (SDMs). These models use a species’ climatic distribution to determine currently suitable areas for the species and project its potential distribution under future climate scenarios. A core, rarely tested, assumption of SDMs is that all populations will respond equivalently to climate. Few studies have examined this assumption, and those that have rarely dissect the reasons for intraspecific differences. Focusing on the arctic-alpine cushion plant Silene acaulis, we compared predictive accuracy from SDMs constructed using the species’ full global distribution with composite predictions from separate SDMs constructed using subpopulations defined either by genetic or habitat differences. This is one of the first studies to compare multiple ways of constructing intraspecific-level SDMs with a species-level SDM. We also examine the contested relationship between relative probability of occurrence and species performance or ecological function, testing if SDM output can predict individual performance (plant size) and biotic interactions (facilitation). We found that both genetic- and habitat-informed SDMs are considerably more accurate than a species-level SDM, and that the genetic model substantially differs from and outperforms the habitat model. While SDMs have been used to infer population performance and possibly even biotic interactions, in our system these relationships were extremely weak. Our results indicate that individual subpopulations may respond differently to climate, although we discuss and explore several alternative explanations for the superior performance of intraspecific-level SDMs. We emphasize the need to carefully examine how to best define intraspecific-level SDMs as well as how potential genetic, environmental, or sampling variation within species ranges can critically affect SDM predictions. We urge caution in inferring population performance or biotic interactions from SDM predictions, as these often-assumed relationships are not supported in our study.     

In silico and empirical evaluation of twelve metabarcoding primer sets for insectivorous diet analyses

During the most recent decade, environmental DNA metabarcoding approaches have been both developed and improved to minimize the biological and technical biases in these protocols. However, challenges remain, notably those relating to primer design. In the current study, we comprehensively assessed the performance of ten COI and two 16S primer pairs for eDNA metabarcoding, including novel and previously published primers. We used a combined approach of in silico, in vivo‐mock community (33 arthropod taxa from 16 orders), and guano‐based analyses to identify primer sets that would maximize arthropod detection and taxonomic identification, successfully identify the predator (bat) species, and minimize the time and financial costs of the experiment. We focused on two insectivorous bat species that live together in mixed colonies: the greater horseshoe bat (Rhinolophus ferrumequinum) and Geoffroy's bat (Myotis emarginatus). We found that primer degeneracy is the main factor that influences arthropod detection in silico and mock community analyses, while amplicon length is critical for the detection of arthropods from degraded DNA samples. Our guano‐based results highlight the importance of detecting and identifying both predator and prey, as guano samples can be contaminated by other insectivorous species. Moreover, we demonstrate that amplifying bat DNA does not reduce the primers' capacity to detect arthropods. We therefore recommend the simultaneous identification of predator and prey. Finally, our results suggest that up to one‐third of prey occurrences may be unreliable and are probably not of primary interest in diet studies, which may decrease the relevance of combining several primer sets instead of using a single efficient one. In conclusion, this study provides a pragmatic framework for eDNA primer selection with respect to scientific and methodological constraints.     

First characterization of congenital myasthenic syndrome type 5 in North Africa

Molecular Biology Reports - Congenital myasthenic syndromes (CMS) are associated with defects in the structure and the function of neuromuscular junctions. These rare disorders can result from...     

Unbiased proteomic profiling of host cell extracellular vesicle composition and dynamics upon HIV‐1 infection

Cells release diverse types of extracellular vesicles (EVs), which transfer complex signals to surrounding cells. Specific markers to distinguish different EVs (e.g. exosomes, ectosomes, enveloped viruses like HIV) are still lacking. We have developed a proteomic profiling approach for characterizing EV subtype composition and applied it to human Jurkat T cells. We generated an interactive database to define groups of proteins with similar profiles, suggesting release in similar EVs. Biochemical validation confirmed the presence of preferred partners of commonly used exosome markers in EVs: CD81/ADAM10/ITGB1, and CD63/syntenin. We then compared EVs from control and HIV‐1‐infected cells. HIV infection altered EV profiles of several cellular proteins, including MOV10 and SPN, which became incorporated into HIV virions, and SERINC3, which was re‐routed to non‐viral EVs in a Nef‐dependent manner. Furthermore, we found that SERINC3 controls the surface composition of EVs. Our workflow provides an unbiased approach for identifying candidate markers and potential regulators of EV subtypes. It can be widely applied to in vitro experimental systems for investigating physiological or pathological modifications of EV release.     

Predictive markers of safety and immunogenicity of adjuvanted vaccines

Vaccination represents one of the greatest public health triumphs; in part due to the effect of adjuvants that have been included in vaccine preparations to boost the immune responses through different mechanisms. Although a variety of novel adjuvants have been under development, only a limited number have been approved by regulatory authorities for human vaccines. This report reflects the conclusions of a group of scientists from academia, regulatory agencies and industry who attended a conference on the current state of the art in the adjuvant field. Held at the U.S. Pharmacopeial Convention (USP) in Rockville, Maryland, USA, from 18 to 19 April 2013 and organized by the International Association for Biologicals (IABS), the conference focused particularly on the future development of effective adjuvants and adjuvanted vaccines and on overcoming major hurdles, such as safety and immunogenicity assessment, as well as regulatory scrutiny. More information on the conference output can be found on the IABS website, http://www.iabs.org/.     

Major plant communities of North America's most arid region: The San Felipe Desert,Baja California,México

Abstract

This vegetation study describes the landscape of the San Felipe Desert (Baja California, México) based on the phytosociological analysis of its major plant associations, as determined by the Braun-Blanquet method and supported by cluster analysis. Four geomorphological or phytotopographical units were identified in the landscape of the San Felipe Desert (salt marshes, playas or sandy flats, bajadas or alluvial fans, and malpaíses or badlands), each characterized by its own plant communities. Two communities and eleven associations were identified, four of which are described and typified for the first time: Atriplici linearis-Frankenietum palmeri, Parkinsonio microphyllae-Olneyetum tesotae, Errazurizio megacarpae-Ephedretum trifurcae and Pachycereo schottii-Prosopidetum torreyanae. Ecological, phytogeographical, bioclimatic, syntaxonomical and floristic data are provided for each of these new associations.