Contrasting the seasonal and elevational prevalence of generalist avian haemosporidia in co‐occurring host species

Understanding the ecology and evolution of parasites is contingent on identifying the selection pressures they face across their infection landscape. Such a task is made challenging by the fact that these pressures will likely vary across time and space, as a result of seasonal and geographical differences in host susceptibility or transmission opportunities. Avian haemosporidian blood parasites are capable of infecting multiple co‐occurring hosts within their ranges, yet whether their distribution across time and space varies similarly in their different host species remains unclear. Here, we applied a new PCR method to detect avian haemosporidia (genera Haemoproteus, Leucocytozoon, and Plasmodium) and to determine parasite prevalence in two closely related and co‐occurring host species, blue tits (Cyanistes caeruleus, N = 529) and great tits (Parus major, N = 443). Our samples were collected between autumn and spring, along an elevational gradient in the French Pyrenees and over a three‐year period. Most parasites were found to infect both host species, and while these generalist parasites displayed similar elevational patterns of prevalence in the two host species, this was not always the case for seasonal prevalence patterns. For example, Leucocytozoon group A parasites showed inverse seasonal prevalence when comparing between the two host species, being highest in winter and spring in blue tits but higher in autumn in great tits. While Plasmodium relictum prevalence was overall lower in spring relative to winter or autumn in both species, spring prevalence was also lower in blue tits than in great tits. Together, these results reveal how generalist parasites can exhibit host‐specific epidemiology, which is likely to complicate predictions of host–parasite co‐evolution.     

Acknowledging uncertainty in evolutionary reconstructions of ecological niches

Reconstructing ecological niche evolution can provide insight into the biogeography and diversification of evolving lineages. However, comparative phylogenetic methods may infer the history of ecological niche evolution inaccurately because (a) species' niches are often poorly characterized; and (b) phylogenetic comparative methods rely on niche summary statistics rather than full estimates of species' environmental tolerances. Here, we propose a new framework for coding ecological niches and reconstructing their evolution that explicitly acknowledges and incorporates the uncertainty introduced by incomplete niche characterization. Then, we modify existing ancestral state inference methods to leverage full estimates of environmental tolerances. We provide a worked empirical example of our method, investigating ecological niche evolution in the New World orioles (Aves: Passeriformes: Icterus spp.). Temperature and precipitation tolerances were generally broad and conserved among orioles, with niche reduction and specialization limited to a few terminal branches. Tools for performing these reconstructions are available in a new R package called nichevol.     

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.     

High predictability of direct competition between marine diatoms under different temperatures and nutrient states

The distribution of marine phytoplankton will shift alongside changes in marine environments, leading to altered species frequencies and community composition. An understanding of the response of mixed populations to abiotic changes is required to adequately predict how environmental change may affect the future composition of phytoplankton communities. This study investigated the growth and competitive ability of two marine diatoms, Phaeodactylum tricornutum and Thalassiosira pseudonana, along a temperature gradient (9–35°C) spanning the thermal niches of both species under both high‐nitrogen nutrient‐replete and low‐nitrogen nutrient‐limited conditions. Across this temperature gradient, the competitive outcome under both nutrient conditions at any assay temperature, and the critical temperature at which competitive advantage shifted from one species to the other, was well predicted by the temperature dependencies of the growth rates of the two species measured in monocultures. The temperature at which the competitive advantage switched from P. tricornutum to T. pseudonana increased from 18.8°C under replete conditions to 25.3°C under nutrient‐limited conditions. Thus, P. tricornutum was a better competitor over a wider temperature range in a low N environment. Being able to determine the competitive outcomes from physiological responses of single species to environmental changes has the potential to significantly improve the predictive power of phytoplankton spatial distribution and community composition models.     

Genomic analysis of Asian honeybee populations in China reveals evolutionary relationships and adaptation to abiotic stress

The geographic and biological diversity of China has resulted in the differential adaptation of the eastern honeybee, Apis cerana, to these varied habitats. A. cerana were collected from 14 locations in China. Their genomes were sequenced, and nucleotide polymorphisms were identified at more than 9 million sites. Both STRUCTURE and principal component analysis placed the bees into seven groups. Phylogenomic analysis groups the honeybees into many of the same clusters with high bootstrap values (91%–100%). Populations from Tibet and South Yunnan are sister taxa and together represent the earliest diverging lineage included in this study. We propose that the evolutionary origin of A. cerana in China was in the southern region of Yunnan Province and expanded from there into the southeastern regions and into the northeastern mountain regions. The Cold‐Temperate West Sichuan Plateau and Tropical Diannan populations were compared to identify genes under adaptive selection in these two habitats. Pathway enrichment analysis showing genes under selection, including the Hippo signaling pathway, GABAergic pathway, and trehalose‐phosphate synthase, indicates that most genes under selection pressure are involved in the process of signal transduction and energy metabolism. qRT‐PCR analysis reveals that one gene under selection, the AcVIAAT gene, involved in the GABAergic pathway, is responding to cold temperature stress. Through homologous recombination, we show that the AcVIAAT gene is able to replace the CNAG_01904 gene in the fungus Cryptococcus neoformans and that it makes the fungus less sensitive to conditions of oxidative stress and variations in temperature. Our results contribute to our understanding of the evolutionary origin of A. cerana in China and the molecular basis of environmental adaptation.     

The effect of grazing on winter survival of midday gerbil (Meriones meridianus) of different genders

The objective of this study was to investigate the effects of grazing on midday gerbil (Meriones meridianus) population characteristics and survival of animals of different genders. The experiment used a randomized complete block design and was conducted in Alxa Left Banner, Inner Mongolia, China, in 2002 (The agricultural reclamation plots set up in 1994). From April 2006 to October 2010, midday gerbils were live‐trapped in 3 light grazing plots, 3 overgrazed plots, and 3 grazing exclusion plots. The quantity of vegetation was investigated in the two different grazing intensity areas and grazing exclusion area to determine the relationship between gerbils and plant food availability. The results suggested that there was higher gerbil density, individual body mass, and daily body mass growth rate in the grazing exclusion sites than the other sites across the whole year. Females had higher survival in grazing exclusion areas than in other treatments, but the males’ survival showed the opposite pattern. Our results indicated that grazing negatively influenced the midday gerbil population by reducing food availability. Grazing influenced the survival rates of male midday gerbils positively, but had negative effects on females. The reason for gendered differences in survival rates of midday gerbils requires further investigation.     

Maximizing antibody production in a targeted integration host by optimization of subunit gene dosage and position

Historically, therapeutic protein production in Chinese hamster ovary (CHO) cells has been accomplished by random integration (RI) of expression plasmids into the host cell genome. More recently, the development of targeted integration (TI) host cells has allowed for recombination of plasmid DNA into a predetermined genomic locus, eliminating one contributor to clone-to-clone variability. In this study, a TI host capable of simultaneously integrating two plasmids at the same genomic site was used to assess the effect of antibody heavy chain and light chain gene dosage on antibody productivity. Our results showed that increasing antibody gene copy number can increase specific productivity, but with diminishing returns as more antibody genes are added to the same TI locus. Random integration of additional antibody DNA copies in to a targeted integration cell line showed a further increase in specific productivity, suggesting that targeting additional genomic sites for gene integration may be beneficial. Additionally, the position of antibody genes in the two plasmids was observed to have a strong effect on antibody expression level. These findings shed light on vector design to maximize production of conventional antibodies or tune expression for proper assembly of complex or bispecific antibodies in a TI system.     

Integration of high-throughput analytics and cell imaging enables direct early productivity and product quality assessment during Chinese Hamster ovary cell line development for a complex multi-subunit vaccine antigen

Mammalian cell line generation typically includes stable pool generation, single cell cloning and several rounds of clone selection based on cell growth, productivity and product quality criteria. Individual clone expansion and phenotype-based ranking is performed initially for hundreds or thousands of mini-scale cultures, representing the major operational challenge during cell line development. Automated cell culture and analytics systems have been developed to enable high complexity clone selection workflows; while ensuring traceability, safety, and quality of cell lines intended for biopharmaceutical applications. Here we show that comprehensive and quantitative assessment of cell growth, productivity, and product quality attributes are feasible at the 200–1,200 cell colony stage, within 14 days of the single cell cloning in static 96-well plate culture. The early cell line characterization performed prior to the clone expansion in suspension culture can be used for a single-step, direct selection of high quality clones. Such clones were comparable, both in terms of productivity and critical quality attributes (CQAs), to the top-ranked clones identified using an established iterative clone screening approach. Using a complex, multi-subunit antigen as a model protein, we observed stable CQA profiles independently of the cell culture format during the clonal expansion as well as in the batch and fed-batch processes. In conclusion, we propose an accelerated clone selection approach that can be readily incorporated into various cell line development workstreams, leading to significant reduction of the project timelines and resource requirements.     

Physiological and metabolomic responses of bermudagrass (Cynodon dactylon) to alkali stress

Bermudagrass (Cynodon dactylon) is a widely used warm‐season turfgrass species with superior stress tolerance except for cold. In this study, a comparative analysis of the responses to alkali stress in bermudagrass at the physiological and metabolomic levels were performed. Mild alkali with relatively low pH slightly inhibited growth of bermudagrass as evidenced by lower electrolyte leakage, more rapid growth and higher survival rate when compared to moderate and severe alkali treatments. Moreover, the amount of 37 metabolites including amino acids, organic acids, sugars and sugar alcohols were modulated by the alkali treatments. Among them, 15 metabolites were involved in carbon and amino acid metabolic pathways. Under mild alkali stress, bermudagrass possibly slowed down metabolisms to maintain basic growth. However, moderate and severe alkali‐stressed plants accumulated significantly higher amount of carbohydrates which might result in carbon starvation. Taken together, alkali stress had severely inhibitory effect partially due to combined ionic stress and high pH stress. These results suggested that bermudagrass employed different strategies in response to alkali stresses with different pH and ionic values.