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Strong spatiotemporal variation in population size often leads to reduced genetic diversity limiting the adaptive potential of individual populations. Key genes of adaptive variation are encoded by the immune genes of the major histocompatibility complex (MHC) playing an essential role in parasite resistance. How MHC variation persists in rodent populations that regularly experience population bottlenecks remains an important topic in evolutionary genetics. We analysed the consequences of strong population fluctuations on MHC class II DRB exon 2 diversity in two distant common vole (Microtus arvalis) populations in three consecutive years using a high-throughput sequencing approach. In 143 individuals, we detected 25 nucleotide alleles translating into 14 unique amino acid MHC alleles belonging to at least three loci. Thus, the overall allelic diversity and amino acid distance among the remaining MHC alleles, used as a surrogate for the range of pathogenic antigens that can be presented to T-cells, are still remarkably high. Both study populations did not show significant population differentiation between years, but significant differences were found between sites. We concluded that selection processes seem to be strong enough to maintain moderate levels of MHC diversity in our study populations outcompeting genetic drift, as the same MHC alleles were conserved between years. Differences in allele frequencies between populations might be the outcome of different local parasite pressures and/or genetic drift. Further understanding of how pathogens vary across space and time will be crucial to further elucidate the mechanisms maintaining MHC diversity in cyclic populations.
Species diversity is changing globally and locally, but the complexity of ecological communities hampers a general understanding of the consequences of animal species loss on ecosystem functioning. High animal diversity increases complementarity of herbivores but also increases feeding rates within the consumer guild. Depending on the balance of these counteracting mechanisms, species-rich animal communities may put plants under top-down control or may release them from grazing pressure. Using a dynamic food-web model with body-mass constraints, we simulate ecosystem functions of 20,000 communities of varying animal diversity. We show that diverse animal communities accumulate more biomass and are more exploitative on plants, despite their higher rates of intra-guild predation. However, they do not reduce plant biomass because the communities are composed of larger, and thus energetically more efficient, plant and animal species. This plasticity of community body-size structure reconciles the debate on the consequences of animal species loss for primary productivity.
Earthworms affect various soil ecosystem processes in their role as ecosystem engineers. The spatial distribution of earthworms determines the spatial distribution of their functional effects. In particular, earthworm-induced macropore networks may act as preferential flow pathways. In this research we aimed to determine earthworm distributions at the catchment scale with species distribution models (SDMs). We used land-use types, temporally invariant topography-related variables and plot-scale soil characteristics such as pH and organic matter content. We used data from spring 2013 to estimate probability distributions of the occurrence of ten earthworm species. To assess the robustness of these models, we tested temporal transferability by evaluating the accuracy of predictions from the models derived for the spring data with the predictions from data of two other field surveys in autumn 2012 and 2013. In addition, we compared the performance of SDMs based (i) on temporally varying plot-scale predictor variables with (ii) those based on temporally invariant catchment-scale predictors. Models based on catchment-scale predictors, especially land use and slope, experience a small loss of predictive performance only compared with plot-scale SDMs but have greater temporal transferability. Earthworm distribution maps derived from this kind of SDM are a prerequisite for understanding the spatial distribution patterns of functional effects related to earthworms.
Citizen science has been gaining momentum in the United States and Europe, where citizens are literate and often interested in science. However, in developing countries, which have a dire need for environmental data, such programs are slow to emerge, despite the large and untapped human resources in close proximity to areas of high biodiversity and poorly known floras and faunas. Thus, we propose that the parataxonomist and paraecologist approach, which originates from citizen-based science, is well suited to rural areas in developing countries. Being a paraecologist or a parataxonomist is a vocation and entails full-time employment underpinned by extensive training, whereas citizen science involves the temporary engagement of volunteers. Both approaches have their merits depending on the context and objectives of the research. We examined 4 ongoing paraecologist or parataxonomist programs in Costa Rica, India, Papua New Guinea, and southern Africa and compared their origins, long-term objectives, implementation strategies, activities, key challenges, achievements, and implications for resident communities. The programs supported ongoing research on biodiversity assessment, monitoring, and management, and participants engaged in non-academic capacity development in these fields. The programs in Southern Africa related to specific projects, whereas the programs in Costa Rica, India, and Papua New Guinea were designed for the long term, provided sufficient funding was available. The main focus of the paraecologists’ and parataxonomists’ activities ranged from collection and processing of specimens (Costa Rica and Papua New Guinea) or of socioeconomic and natural science data (India and Southern Africa) to communication between scientists and residents (India and Southern Africa). As members of both the local land user and research communities, paraecologists and parataxonomists can greatly improve the flow of biodiversity information to all users, from local stakeholders to international academia.
Tula virus (TULV) is a vole-associated hantavirus with low or no pathogenicity to humans. In the present study, 686 common voles (Microtus arvalis), 249 field voles (Microtus agrestis) and 30 water voles (Arvicola spec.) were collected at 79 sites in Germany, Luxembourg and France and screened by RT-PCR and TULV-IgG ELISA. TULV-specific RNA and/or antibodies were detected at 43 of the sites, demonstrating a geographically widespread distribution of the virus in the studied area. The TULV prevalence in common voles (16.7 %) was higher than that in field voles (9.2 %) and water voles (10.0 %). Time series data at ten trapping sites showed evidence of a lasting presence of TULV RNA within common vole populations for up to 34 months, although usually at low prevalence. Phylogenetic analysis demonstrated a strong genetic structuring of TULV sequences according to geography and independent of the rodent species, confirming the common vole as the preferential host, with spillover infections to co-occurring field and water voles. TULV phylogenetic clades showed a general association with evolutionary lineages in the common vole as assessed by mitochondrial DNA sequences on a large geographical scale, but with local-scale discrepancies in the contact areas.
Epitope mapping is crucial for the characterization of protein-specific antibodies. Commonly, small overlapping peptides are chemically synthesized and immobilized to determine the specific peptide sequence. In this study, we report the use of a fast and inexpensive planar microbead chip for epitope mapping. We developed a generic strategy for expressing recombinant peptide libraries instead of using expensive synthetic peptide libraries. A biotin moiety was introduced in vivo at a defined peptide position using biotin ligase. Peptides in crude Escherichia coli lysate were coupled onto streptavidin-coated microbeads by incubation, thereby avoiding tedious purification procedures. For read-out we used a multiplex planar microbead chip with size- and fluorescence-encoded microbead populations. For epitope mapping, up to 18 populations of peptide-loaded microbeads (at least 20 microbeads per peptide) displaying the primary sequence of a protein were analyzed simultaneously. If an epitope was recognized by an antibody, a secondary fluorescence-labeled antibody generated a signal that was quantified, and the mean value of all microbeads in the population was calculated. We mapped the epitopes for rabbit anti-PA28 gamma (proteasome activator 28 gamma) polyclonal serum, for a murine monoclonal antibody against PA28 gamma, and for a murine monoclonal antibody against the hamster polyoma virus major capsid protein VP1 as models. In each case, the identification of one distinct peptide sequence out of up to 18 sequences was possible. Using this approach, an epitope can be mapped multiparametrically within three weeks. (C) 2016 Elsevier B.V. All rights reserved.
Background: Non-typhoid Salmonella Typhimurium (S. Typhimurium) accounts for a high number of registered salmonellosis cases, and O-serotyping is one important tool for monitoring epidemiology and spread of the disease. Moreover, variations in glucosylated O-antigens are related to immunogenicity and spread in the host. However, classical autoagglutination tests combined with the analysis of specific genetic markers cannot always reliably register phase variable glucose modifications expressed on Salmonella O-antigens and additional tools to monitor O-antigen glucosylation phenotypes of S. Typhimurium would be desirable. Results: We developed a test for the phase variable O-antigen glucosylation state of S. Typhimurium using the tailspike proteins (TSP) of Salmonella phages 9NA and P22. We used this ELISA like tailspike adsorption (ELITA) assay to analyze a library of 44 Salmonella strains. ELITA was successful in discriminating strains that carried glucose 1-6 linked to the galactose of O-polysaccharide backbone (serotype O1) from non-glucosylated strains. This was shown by O-antigen compositional analyses of the respective strains with mass spectrometry and capillary electrophoresis. The ELITA test worked rapidly in a microtiter plate format and was highly O-antigen specific. Moreover, TSP as probes could also detect glucosylated strains in flow cytometry and distinguish multiphasic cultures differing in their glucosylation state. Conclusions: Tailspike proteins contain large binding sites with precisely defined specificities and are therefore promising tools to be included in serotyping procedures as rapid serotyping agents in addition to antibodies. In this study, 9NA and P22TSP as probes could specifically distinguish glucosylation phenotypes of Salmonella on microtiter plate assays and in flow cytometry. This opens the possibility for flow sorting of cell populations for subsequent genetic analyses or for monitoring phase variations during large scale O-antigen preparations necessary for vaccine production.
Background
Non-typhoid Salmonella Typhimurium (S. Typhimurium) accounts for a high number of registered salmonellosis cases, and O-serotyping is one important tool for monitoring epidemiology and spread of the disease. Moreover, variations in glucosylated O-antigens are related to immunogenicity and spread in the host. However, classical autoagglutination tests combined with the analysis of specific genetic markers cannot always reliably register phase variable glucose modifications expressed on Salmonella O-antigens and additional tools to monitor O-antigen glucosylation phenotypes of S. Typhimurium would be desirable.
Results
We developed a test for the phase variable O-antigen glucosylation state of S. Typhimurium using the tailspike proteins (TSP) of Salmonella phages 9NA and P22. We used this ELISA like tailspike adsorption (ELITA) assay to analyze a library of 44 Salmonella strains. ELITA was successful in discriminating strains that carried glucose 1-6 linked to the galactose of O-polysaccharide backbone (serotype O1) from non-glucosylated strains. This was shown by O-antigen compositional analyses of the respective strains with mass spectrometry and capillary electrophoresis. The ELITA test worked rapidly in a microtiter plate format and was highly O-antigen specific. Moreover, TSP as probes could also detect glucosylated strains in flow cytometry and distinguish multiphasic cultures differing in their glucosylation state.
Conclusions
Tailspike proteins contain large binding sites with precisely defined specificities and are therefore promising tools to be included in serotyping procedures as rapid serotyping agents in addition to antibodies. In this study, 9NA and P22TSP as probes could specifically distinguish glucosylation phenotypes of Salmonella on microtiter plate assays and in flow cytometry. This opens the possibility for flow sorting of cell populations for subsequent genetic analyses or for monitoring phase variations during large scale O-antigen preparations necessary for vaccine production.
When sampling animal movement paths, the frequency at which location measurements are attempted is a critical feature for data analysis. Important quantities derived from raw data, e.g. travel distance or sinuosity, can differ largely based on the temporal resolution of the data. Likewise, when movement models are fitted to data, parameter estimates have been demonstrated to vary with sampling rate. Thus, biological statements derived from such analyses can only be made with respect to the resolution of the underlying data, limiting extrapolation of results and comparison between studies. To address this problem, we investigate whether there are models that are robust against changes in temporal resolution. First, we propose a mathematically rigorous framework, in which we formally define robustness as a model property. We then use the framework for a thorough assessment of a range of basic random walk models, in which we also show how robustness relates to other probabilistic concepts. While we found robustness to be a strong condition met by few models only, we suggest a new method to extend models so as to make them robust. Our framework provides a new systematic, mathematically founded approach to the question if, and how, sampling rate of movement paths affects statistical inference.